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Zinc Oxide and Peroxide Nanoparticles – from Chemical Synthesis to Electrochemical Analysis and Wastewater Filtration

DOI: 10.31038/NAMS.2024712

Abstract

There is growing interest in the application of transition metal oxide and peroxide nanoparticles in materials science and industrial engineering. Transition metal oxide nanoparticles (TMONPs) can form materials with a wide range of unique chemical, electronic and physical properties for manufacturing various commercial products. Presently and for the foreseeable future, transition metal oxides are important constituents of energy production systems. They can be modified by various chemical, mineral, and polymeric substances, to produce nanocomposites that are suitable for the fabrication of more advanced materials. In this review article, discussion will focus on zinc oxide (ZnO) and zinc peroxide (ZnO2) which are chemically related but technologically different in their applications. The toxicity of biochemically active ZnO nanoparticles has led to the development of new analytical methods with a focus on capillary electrophoresis with UV absorption or molecular fluorescence detection. The importance of wastewater analysis is emphasized with an outlook on the future perspectives in this fast-advancing research field. Next, the unique chemical properties and physical characteristics of ZnO2 nanoparticles are introduced, followed by their latest applications in and modifications for scientific endeavors. Methods suitable for their incorporation in altering membrane properties to improve filtration performance are detailed. Major challenges and research endeavors are highlighted in the design of more effective membranes for wastewater filtration, hereby ameliorating the environmental toxicology of effluent contaminants. Polymeric membranes incorporated with composite zinc peroxide nanoparticles is proposed to be a good replacement of zinc oxide due to their strong oxidative properties involving a higher number of reactive oxygen atoms per molecule. The latest understanding of zinc oxide/peroxide nanomaterials toxicology is described, and best practices are crucial to control their environmental distribution. Last, the key research gaps that need to be addressed for future assessment of toxicological risks are unveiled.

Keywords

Biosensors, Electrochemical analysis, Engineered composites, Membrane filtration, Nanoparticles, Toxicology, Transition metal oxides, Ultrafine dust, Wastewater, Zinc oxide, Zinc peroxide

Introduction

In recent years, advanced technology with nanoparticles have greatly sparked the interest of the scientific community. Their small sizes and tunable functional properties make them appealing as unique structures for biomedical applications, ranging from bioimaging, biosensing, drug delivery and theranostics. Material scientists have focused their research on the synthesis of transition metal oxide nanoparticles (TMONPs). Transition metal oxides exhibit unique physicochemical properties including catalytic function, ferroelectricity, piezoelectricity, magnetism, and supercapacitor performance. These oxides are fascinating to work with because their electrons interact strongly with each other, giving rise to a range of phenomenal effects such as high-temperature superconductivity and magnetoresistance. A comprehensive review summarizes different methods for synthesizing (TMONPs) as catalysts in oxidation reactions, and the unique role of metal oxide substrates in anchoring metal atoms for photocatalysis is emphasized. Biosynthesis of these nanoparticles by bacteria, fungi and plants can yield desirable crystallinity, diameters and morphologies if all process parameters (concentration, pH, temperature, time, and calcination temperature) are well controlled. Different TMONPs can be combined with other transition metal oxides to form nanocomposites that offer multiple synergistic advantages. They represent an important class of semiconductors finding applications in various major industries from solar energy transformation, magnetic storage media and electronic devices to photocatalysis. The development of novel electrochemical biosensors using morphologically varied transition metal oxides and their composites has highlighted the significance of TMONPs as promising electrode modifiers for the fabrication of electrochemical and biosensors. Reactivity of the metal oxide-water interface can be understood from the viewpoint of coordination chemistry, while the reactivity of a metal ion at a nanoparticle surface is compared to the reactivity of the same metal ion dissolved in an aqueous solution [1-12].

Nanotechnology is introducing many advantages over conventional methods of food processing, extending the shelf life, reducing deterioration, maintaining quality, and adding food values. Nanoparticles and nanomaterials improve barrier properties, detect pathogens, and alert the status of food. They will reduce the wastage of post-harvest loss of agriculture and horticulture produces. A substantial review has recently been published on the incorporation of transition metal oxides in the development of intelligent food nano-packaging. Peroxides are inorganic chemicals that contain a bivalent O-O group. These compounds release nascent oxygen readily and their major industrial applications include oxidizing agents, bleaching agents, and polymerization initiators. Chemical oxidation is one of the environmental site remediation methods that have emerged lately as a better alternative to traditional technologies. Nanosized oxidizing agents increase the ratio of surface to volume and hence the biodegradation speed for contaminants in soil and ground water. Sodium peroxide (Na2O2), sodium perborate, and sodium persulfate are common inorganic salts that react with water to produce hydrogen peroxide (H2O2). Other metal peroxides, such as BaO2, CaO2, CdO2 and MgO2, are highly stable and they promote the oxidation of organic substances only at higher temperatures. BaO2, CaO2, MgO2, TiO2 and ZnO2 provide antibacterial applications in biomedicine. Tin peroxide (SnO2) transforms to SnO when exposed to orange peel extracts with reducing ability. Zinc peroxide (ZnO2) nanoparticles can be employed to prepare intelligent nano-packaging for better food preservation if they do not leach out from the packaging to the food [13-21].

Zinc Peroxide Nanoparticles

In 2021, zinc oxide and peroxide were the world’s 776th most traded product, with a total trade of US$1.87B. The top exporters of ZnO2 and ZnO were the Netherlands, Mexico, Canada, United States, and Peru. Both ZnO and ZnO2 nanoparticles can be prepared from aqueous solutions containing zinc nitrate or formate using UV irradiation. When ZnO is treated with H2O2, an interfacial ZnO2 layer forms to cover the nanoparticle surface. ZnO nanoparticles can be obtained by heat treatment of the peroxide above the transition temperature of 233°C, up to the decomposition temperature of 473°C. The weight loss due to the thermal decomposition of ZnO2 into ZnO and O2 at 250°C is considerably larger than the expected theoretical value of 16.4% just by oxygen release. ZnO2 is a stronger oxidizing agent than ZnO. Decomposition of ZnO2 to ZnO and O2 resulted in the decrease of the band gap energy from 3.75 to 3.30 eV [22-28].

ZnO2 nanoparticles were traditionally prepared by peptization of Zn(OH)2 with the aid of H2O2 aqueous solution. They could be formed by a simple oxidation-hydrolysis-precipitation procedure, using zinc acetate as a precursor, hydrogen peroxide as an oxidizer, water as a preparation medium for hydrolysis, and polyethylene glycol as a stabilizer. ZnO2 nanoparticles can facilely be synthesized from zinc acetate and H2O2 using a sol-gel method under ultrasound assistance [29-33]. Characterization by scanning electron microscopy and energy dispersive X-ray spectroscopy (Figure 1) shows an atomic ratio Zn/O of 2.01 and an average particle diameter of 304±5 nm. A green method based on the reaction between Zn5(CO3)2(OH)6 powder and H2O2 in aqueous solution at room temperature can synthesize ZnO2 nanoparticles. ZnO2 nanoparticles can be prepared by the laser ablation of zinc in 30% H2O2 as another green technique using the fundamental wavelength (1064 nm) of a pulsed Nd: YAG laser, at a repetition rate of 15 Hz and laser fluence of 22 J/cm2 for an ablation time of 10 min. Furthermore, the Leidenfrost dynamics occurring in an underwater overheated zone ensures eruption of nanoclusters towards a colder region, forming monodisperse nanoclusters of ZnO2. Nowadays, ZnO2 nanoparticles are commercially available, either bare or coated with an organic ligand shell of polyethylene glycol for stable dispersion in water, methanol, ethanol, acetone and dimethyl sulfoxide [34-38].

FIG 1

Figure 1: (a, b) Scanning electron microscopy, and (c, d) energy dispersive X-ray spectroscopy of ZnO2 nanoparticles facilely prepared in our lab by following Ramírez et al.’s sol-gel method under ultrasound assistance.

Unique Properties of Zinc Peroxide Nanoparticles

ZnO2 is much more stable in aqueous solutions (as compared to calcium and magnesium peroxides) and it retains its peroxide content down to pH 6. At lower pH levels, H2O2 release is predictable as its dissolution product, Zn2+, is highly soluble. Nanocrystalline ZnO2 can be passivated against further oxidation by the addition of sub-stoichiometric amounts of potassium permanganate, which also increases the thermal stability of ZnO2 [39,40].

ZnO2 possess unique anti-bacterial, anti-corrosion, anti-fouling, and photocatalytic properties that are considered cost effective and environment friendly. They have been studied, due to their semiconducting and oxidizing properties, for various applications in optoelectronics, photocatalysis, sensors, biomedicine, and theranostics. Due to their large nonlinear optical susceptibilities, which are enhanced by two-photon electronic resonance, metal oxides are efficient sources of coherent anti-Stokes Raman Scattering (CARS). The FTIR spectrum of ZnO2 nanoparticles shows a characteristic absorption peak at 435-445 cm−1; the Raman spectrum shows characteristic peaks at 830-840 and 420-440 cm−1. ZnO2 nanoparticles exhibit photoluminescence with one strong emission band at 400 nm, one very weak emission band at 474 nm, and at 520 nm originating from the band edge and the oxygen vacancy. Polyvinyl alcohol/ZnO2 nano-composite films have been engineered via casting. Their energy gaps decrease with increasing ZnO2 concentrations to reach 2.80 eV at 2 wt.%, which are promising in anti-ultraviolet, opto-electronic, and optical limiting applications. A correlation exists between oxygen vacancies and the magnetization for pure ZnO2 nanoparticles at room temperature. Coating of 15-20% ZnO2 nanoparticles over graphene enhances magnetization more than 30 times due to the exchange interaction between localized electron spin moments resulting from oxygen vacancies at the surface [41-47].

ZnO2 nanoparticles have reportedly oxidative stress mediated toxicity on various mammalian cell lines. Oxygen release from the biofunctionalized nanoparticles is tunable according to the solution pH. Antimicrobial tests at 37°C on bacterial species exhibiting different susceptibility to oxygen have confirmed the antimicrobial activity of ZnO2 nanoparticles against Enterococcus faecalis, Aggregatibacter actinomycetemcomitans, Porphyromonas gingivalis and Prevotella intermedia. Accordingly, ZnO2 showed effective antifungal activities, with a minimum inhibitory concentration (MIC) of 16 mg/L against Candida albicans. Histopathology assessment has confirmed the role of ZnO2 nanoparticles in healing skin wounds. They exhibit angiogenic activity, due to onsite production of H2O2, for rapid tissue healing. ZnO2 demonstrate antimicrobial, anti-elastase, anti-keratinase, and anti-inflammatory properties that are valuable for biomedical applications. They also inhibit bacterial biofilm formation and combat multi-drug resistant bacteria. A minimum concentration of ZnO2 nanoparticles of 1 μg/mL inhibits the production of interleukin-1-β and interleukin 6 by peripheral blood mononuclear cells in the presence of lipopolysaccharides. ZnO2 nanoparticles at a concentration of 2 μg/mL causes DNA damage in vitro; at a concentration of 5 μg/mL they promote protein aggregation and facilitate the production of protein complexes that may interfere with normal immune functions [48-54].

Applications of Zinc Peroxide Nanoparticles

Nanosized ZnO2 is an efficient oxidant for the oxidation of aromatic alcohols to the corresponding carbonyl compounds selectively in excellent yields, using dimethyl carbonate as an environmentally benign solvent. ZnO2 nanoparticles reactively adsorb chemical warfare agent surrogate of mustard gas, selectively oxidizing diethyl sulfide to diethyl sulfoxide and 2-chloroethyl ethyl sulfide to hydroxyethyl ethyl sulfide. Crosslinking of conventional/carboxylated nitrile rubber with ZnO2 achieved total peroxide decomposition at vulcanization temperatures as low as 190-200°C [55-57].

Semiconducting CuO nanoparticles, as a CO2 gas sensitive material, can with an organic binder and ZnO2 for improved gas sensitive layer quality. The Lewis acid-base reaction between oxide oxygen and CO2 has been proposed as sensing mechanism for the measurements in dry air, whereas the formation of surface barriers between nano-grains due to the reaction with CO2 has been suggested for the CO2 response under humid conditions [58].

ZnO2 is a promising adsorbent nanomaterial for the removal of Congo red dye from contaminated water. The adsorption capacity is 208 mg g-1 within 10 min at pH 2-10. The adsorbent has a unique property to adjust pH within the 6.5-7.5 range irrespective of the acidic or basic nature of water. It is highly efficient even in the absence of sunlight to remove Congo red dye from contaminated water down to the permissible limits set by the World Health Organization and the United States Environmental Protection Agency. Crystal violet dye in industrial wastewater can be removed using sodium docusate-modified ZnO2, attaining >99.5% adsorption efficiency in 5 min at pH ∼10 as the zeta potential of ZnO2 decreases from −15 mV at pH 3 to −60 mV at pH 9. The higher negative charge results in stronger electrostatic interaction with the dye. Synthetic graphite flakes can be treated with 3-mercaptopropionic acid, followed by functionalization with ZnO2 nanoparticles, to efficiently remove As(III) and As(V). The adsorption data are best fitted with pseudo second order kinetic model and Freundlich adsorption isotherm, indicating chemisorption and multilayer adsorption on heterogeneous surface respectively. ZnO2 nanoparticles, capped with polyvinyl-pyrrolidone to control the particle size, is an efficient material for the decontamination of cyanide from contaminated water by adsorption at pH 5.8-7.8 within 15 min [59-62].

As a catalyst for removal of reactive blue dye, a maximum degradation efficiency of 85% was achieved by ZnO2 nanoparticles with polyethylene glycol, and 81% without PEG, after 120 min of photocatalytic reaction. ZnO2 nanoparticles have excellent degradation efficiency of brilliant green dye, achieving 84-86% after 120 min of photocatalytic reaction at pH 6-7. Eco-friendly carbon quantum dots/ZnO2 nanocomposite has been successfully synthesized for photocatalysis applications. It has higher efficiency than carbon quantum dots/TiO2 for the removal of different dyes and high stability under UV-A light. Nitrobenzene photodegradation by ZnO2 under UV lamps of 254 nm is optimal at pH 2, reaching up to 90% degradation in 2 h at 25°C [63-66].

For dental implants the accumulation of anaerobic bacteria is a main reason for peri-implant inflammation that can lead to implant loss. Decorating ZnO2 by Glc-1P permits their uptake in the gram-negative oxygen-sensitive bacterial cells. ZnO2 nanoparticles can be decorated with glucose 1-phosphate (Glc-1P) due to specific interaction of the phosphate function of Glc-1P with the nanoparticle surface. The anchored glucose molecules are accessible for specific interactions with lectin concanavalin A. Generation of ROS including hydrogen peroxide, hydroxyl radical, and peroxide anion can enhance the membrane permeability, cell wall damage, internalization of nanoparticles, and uptake of toxic dissolved Zn2+ ions. A ZnO2-based theranostic nano-agent enhances oxidative damage to cancer cells by combining endogenous and exogenous reactive ROS. After uptake by cancer cells, the pH-responsive ZnO2 nanoparticles, in addition to releasing exogenous H2O2, also provide Zn2+ to facilitate the production of endogenous O2·and H2O2 from mitochondrial electron transport chain, enabling highly effective synergistic tumor therapy [67-69].

Zinc Oxide Nanoparticles

ZnO is a white powder that has two main lattice structures: hexagonal wurtzite and cubic zincblende. The hexagonal structure is commonly found, and both structures are insoluble in water with a solubility of 0.16 mg/100 mL at 30°C. The solubility of uncoated ZnO, as determined by the Zn2+ concentration in the aqueous solution, ranges between 20 and 47 mg/L. The solubility product constant Ksp is a useful parameter for calculating the aqueous solubility of sparingly soluble compounds. A comparison of dissolution rates shows that the ZnO nanoparticles have a higher dissolution rate than the bulk oxide. A new methodology for the in-silico assessment of the solubility of ZnO based on statistical thermodynamics, combined with density functional tight binding theory for the evaluation of the free energy exchange during the dissolution process. Complete ionic dissolution of ZnO is hindered by the formation of O2− anions in solution, which are highly unstable. The dissolution rate will depend critically on the matrix with Zn ions and the mechanisms for diffusion or active transport of Zn2+ and O2-ions in biological processes. Any mass fraction of Zn2+ ions removed or washed away will lead to further dissolution and eventually complete solubilization of the particulate fraction of ZnO. The fact that zinc-rich foods are mostly animal products suggests that vegetarians and vegans may have difficulty getting enough zinc in their diet. Zinc supplements are a great way to have the recommended levels of zinc in the body for stronger immune systems and improved muscle building. They are particularly useful for older adults (especially older men), who are more likely to have zinc deficiency [70-75].

Unique Properties of Zinc Oxide Nanoparticles

A variety of industries, including the automotive, concrete, cosmetic, pharmaceutical and textile, have used ZnO nanoparticles as a major material. The annual turnover of ZnO nanoparticles is over US$ 900,000/year, and the specific cost of their production is US$20/kg. Numerous synthetic techniques have been developed to meet the increasing demand for ZnO nanoparticles. These alternatives offer environmental and financial advantages associated with their commercial production. Biological synthesis uses plant extracts or microbes as green resources for the preparation of ZnO nanoparticles. Considerable investment to improve the performance of diverse nanocomposites allows rapid development of novel photocatalytic/photooxidizing degradation technologies for removing dyes in industrial wastewater [76-78].

Nowadays, ZnO nanoparticles continue to be a great attraction to researchers in various scientific endeavors based on their unique physicochemical properties. The natural bandgap (3.37 eV) and n-type conducting behavior of ZnO can be tuned by doping with metals/metal oxides and non-metals to replace Zn2+ and O2-in the ZnO lattice, for various applications (such as solar cells, photocatalysis, medicines, light-emitting diodes, laser diodes, chemical and biosensors) owing to the direct influence of dopants on their electronic and physiochemical properties. A wide range of energy bandgaps (3-4 eV) is attained by green synthesis, indicating that ZnO nanoparticles can be employed in metal oxide semiconductor-based systems. The effectiveness of dye-sensitive solar cells is attributable to improved dye adsorption onto the nanoparticle surfaces. By adding ZnO in various amounts to a solution of polyvinylidene fluoride in 2-butanone during the fabrication process, followed by removing ZnO in an HCl bath once the organic solvent is evaporated, porous sensors can be made with different piezoelectric chains to control the piezoelectric coefficient. ZnO nanoparticles synthesized using the coprecipitation method present the best performance in catalysis, biosensing, imaging, drug delivery, and pollution absorption owing to their highest purity and crystalline phase, large Brunauer-Emmett-Teller surface area (~23 m2g-1) and pore volume in the mesoporous-macroporous structure [79-82].

ZnO nanoparticles have strong antimicrobial activity against a broad spectrum of bacteria (P. aeruginosa, E. coli, A. baumannii, K. pneumoniae and Staphylococcus aureus) and are effective against Hyalomma ticks. However, all fungal strains (P. chrysogenum, A. niger, T. citrinoviride and A. fumigatus) are resistant to ZnO nanoparticles. ZnO nanoparticles (1.5 mg/L) are protective against the detrimental effects of Clostridium perfringes type A infection in aquaculture. Their potential mechanisms of action against various kinds of viruses were discussed in a comprehensive review. The adoption of novel bio-assisted synthesis methodologies tailors the properties of ZnO nanoparticles to suit biomedical applications, underscoring their potential in cancer treatment towards MCF-7 breast cancer cell lines [83-87].

Applications of Zinc Oxide Nanoparticles

ZnO is produced synthetically for use as an additive in adhesives, antibacterials, baby powder, batteries, cement, ceramics, cigarette filters, cosmetics, ferrites, fire retardants, first-aid tapes, foods, glass, laser diodes, light emitting diodes, lubricants, ointments, paints, pigments, plastics, rubbers, sealants, semiconductors, solar cells, sun blocks, and wood products. Traditional uses of ZnO products include treating wounds following surgery and applying salves inside the mouth to treat ulcers or sores. Over 50% of ZnO is used in the rubber industry along with stearic acid for the vulcanization of rubber to produce tires, shoe soles, and even hockey pucks. ZnO nanoparticles have been added in food-packaging materials to stop food from spoiling. For use as binary/ternary composite anodes in lithium-ion batteries, ZnO has a higher theoretical capacity (978 mA.h/g) than many other transition metal oxides such as CoO (715 mA.h/g), NiO (718 mA.h/g) and CuO (674 mA.h/g). ZnO nanoparticles are extensively used in healthcare and environmental remediation applications attributable to their biodegradability. ZnO possesses unique biological properties for various antibacterial, antiinflammation, antitumor, and antiviral) applications. Addition of ZnO nanoparticles into crystal violet dye induces an alternative photoredox pathway, resulting in more generation of reactive oxygen species lethal to bacterial cells. This technique could be used to transform a wide range of bactericidal surfaces and contribute to maintaining low pathogen levels on hospital surfaces related to healthcare-associated infection. Hybrid ZnO-SiO2 nanoparticles possess favorable characteristics for antifouling purposes. Self-cleaning and anti-fouling polymeric membranes for wastewater treatment are commercially fabricable with ZnO nanocomposites [88-100].

The formation and breaking of transition metal-carbon bonds plays a pivotal role in the catalytic oxidation of organic sulfides, alcohols, olefins, and alkanes. The textile industry is environment unfriendly due to the massive use of dyes and chemicals. Discharge of untreated textile wastewaters loaded with dyes not only contaminates the soil and water resources but also threatens the public health. ZnO nanorods can be used as a photocatalyst to degrade 65% of methylene blue in 50 min. Biochar-ZnO composites obtained by pyrolysis at 600°C can degrade 90% rhodamine B in 75 min, while ZnO can degrade only 38%. ZnO nanoparticles can be doped with Ni (3%), through combustion at 550°C, to improve the photocatalytic degradation of methylene blue and tetracycline [101-103].

Sodium (15%)-doped ZnO degrades 95% of methylene blue under visible light illumination in 180 min, with a rate constant of 1.7×10-2 min−1 and tenacious photostability. Green synthesis of ZnO nanoparticles is gaining huge attention via eco-friendly protocols that reduce the destructive effect of chemical synthesis. ZnO nanoparticles synthesized from Synadium grantii leaf extract with Cu dopant exhibit superior photocatalytic activity for indigo carmine, methylene blue and rhodamine B dyes. Gynostemma plant extract can be used in a co-precipitation method to synthesize ZnO nanoparticles for the photocatalytic decolorization of malachite green dye under UV illumination within 180 min. Biogenic ZnO nanoparticles can be synthesized by using Pseudochrobactrum sp. C5 for catalytic degradation of dyes in wastewater treatment. Valorization of banana peel waste extract as the reducing and capping agents produces ZnO nanoparticles that show superior reusability and photodegradation efficiency for the removal of hazardous basic blue 9, crystal violet and cresol red dyes at pH 12 over irradiation time 90 min. Degradation of congo red by orange-peel-extract-biosynthesized ZnO nanoparticles via photocatalysis can remove 96% of the dye Photocatalytic degradation of rhodamine B dye in waste water and inhibition of butyrylcholinesterase, acetylcholinesterase and α-glycosidase enzymes are afforded by cauliflower-shaped ZnO nanoparticles synthesized using Alchemilla vulgaris leaves. Maximum photocatalytic degradation of pharmaceutical wastewater with ZnO was 40% and with TiO2 is 33% at pH 9, following pseudo-first-order kinetics. Combined use of TiO2/H2O2 is more effective than ZnO and TiO2 alone, achieving 45% degradation. ZnO and TiO2 can be used as catalysts for the degradation of dyeing factory effluents by the advanced oxidative process under UV irradiation at pH 3 for 8 h. Interestingly, a deposit of CdS nanoparticles on ZnO nanosheets provides excellent piezocatalytic efficiency for rhodamine B degradation under ultrasonic vibration. The nanocomposite of ZnO with porous hydroxyapatite (prepared from phosphate rock) improves the photodegradation of antibiotics in water and traps the by-products. An artificial neural network model can estimate the effect of different variables on AB113 dye removing decolorizing acid blue dye from textile wastewater in a sonophotocatalytic process. Reaction time, pH, ZnO dosage, ultrasonic power and persulfate dosage are optimized for maximum dye removal. After photocatalysis, if the treated water is discharged to the surface water along with the catalyst nanoparticles and degradation products, a resulting toxicity exists in the medium that can influence the lipid peroxidation and reduced glutathione in the aquatic vertebrates. Hence filtration is recommended before discharging, for separation of the catalyst nanoparticles. However, the filtration of nanoparticles from the treated water is costly and might outweigh the savings of energy [104-116].

Toxicology of ZnO Nanoparticles

Increasing production and application of transition metal oxide nanoparticles has raised concerns in regard to their environmental accumulation and toxicity in natural ecosystems. Nanoparticles are extensively studied for their chemical toxicology in aquatic microorganisms, agricultural products, fish, wildlife and humans. The uptake and accumulation of ZnO nanoparticles by aquatic organisms have considered the release of Zn2+ ions as well as the toxic mechanisms shared with other nanoparticles such as immunotoxicity, inflammation, lysosomal/mitochondrial damage, oxidative stress, programmed cell death, and redox activity. The growing usage of ZnO nanoparticles increases their release in municipal wastewater treatment plants. At 50 mg/L ZnO nanoparticles, both the granular activated sludge performance and the extracellular polymeric substances content are significantly reduced. This leads to decreases in the activities of ammonia monooxygenase and nitrate reductase. In addition, ZnO nanoparticles disrupt the cell membrane integrity and lead to bacterial cell death via intracellular ROS generation. After exposure to the nanoparticles, the bacterial community composition shifts to be dominated by Gram-positive bacteria. Antibacterial activity of ZnO nanoparticles is more pronounced with Gram-positive than Gram-negative bacteria. ZnO nanoparticles are biocompatible and effective as a food preservative against Salmonella typhi, Klebsiella pneumoniae and Shigella flexneri. They demonstrated significant antibacterial effects on various pathogenic bacteria in terms of zone-of-inhibition measured by the disc-diffusion method. When treated with ZnO nanoparticles (100-300 mg/L), significant reductions in marine microalgae C. vulgaris viable cells, LDH level, and non-enzymatic antioxidant glutathione are noticed while the activity of antioxidant enzyme superoxide dismutase and the level of lipid peroxidation significantly increase. ZnO nanoparticles possess antibacterial and antioxidant properties towards the remediation of hospital wastewater; the ones fabricated using Eriobotrya japonica leaves extract exhibit DPPH scavenging activity and are highly active against S. aureus, P. multocida, E. coli and B. subtilis strains. Redox imbalance, lignification and cell death cause reduction of root growth in wheat seedlings exposed to ZnO nanoparticles. Dietary exposure of carp to ZnO nanoparticles increases the aspartate aminotransferase activity significantly and decreases the alanine transferase activity significantly. ZnO nanoparticles act as a potent antidiabetic agent and severely elicit oxidative stress particularly at higher doses in diabetic rats (10 mg/kg). Initial exposure of human bronchial and pancreatic epithelial cells to oxidative stress sensitizes their subsequent response to cytotoxic challenge with ZnO nanoparticles. As in vitro model species human erythrocytes can be used to evaluate cytotoxicity, and human lymphocytes can be used for genotoxic studies. ZnO and TiO2 nanoparticles result in 65% and 52% hemolysis at 250 ppm respectively, indicating cytotoxicity to human red blood cells. Both nanoparticles were found to generate ROS concomitant with depletion of glutathione and glutathione S-transferase levels. ZnO nanoparticles are significantly more genotoxic than TiO2 nanoparticles at concentrations higher than 250 ppm. The nanoparticles preferentially kill cancerous cells over normal human cells. They enhance ultrasound-induced lipid peroxidation in the liposomal membrane. Two mechanisms underly the toxicity of ZnO nanoparticles: (i) generation of ROS and (ii) induction of apoptosis. The chemical toxicology of ZnO nanoparticles in adult male Wistar rats were investigated. All levels of zinc oxide nanoparticles had a significant impact on sperm quality and quantity. Significant toxicity effects of ZnO nanoparticles appeared at concentrations above 50 mg/kg body weight of animals. 200 mg/kg body weight resulted in increased total oxidant status and decreased total antioxidant capacity significantly. On the contrary, dietary supplementation of Nile tilapia with Se nanoparticles and ZnO nanoparticles induces synergistic effects that improve growth performance, blood health, and intestinal histomorphology. Seed priming with ZnO nanoparticles demonstrates beneficial effects of mitigating the phytotoxicity induced by Co stress in maize, significantly improving the plant growth, biomass, and photosynthetic machinery. Freshwater fish O. mossambicus fed with a supplemented diet of ZnO and Se nanoparticles raises the antioxidant response, boosts the immunity, and reduces the chance of getting infected by A. Hydrophilia. The entrance of ZnO or ZnS nanoparticles into freshwater systems may significantly impact the sedimentary microbial community structure and nitrogen cycling. Furthermore, they showed a strong anti-termite activity against Heterotermes indicola with a 100% mortality rate in 24 h [117-136].

Biosensors Incorporating Zinc Oxide Nanoparticles

Among all the optical biosensing systems, ZnO nanoparticles formed directly atop 3-aminopropyl triethoxysilane-treated Si substrates are more adhesive. Smaller particle sizes of ZnO will increase the fluorescence emission, eliminate several emission peaks, yield higher fluorescence quantum efficiency, and require lower excitation energy for fluorescence sensing. N-doped ZnO nanoparticles exhibit fluorescence emission at 385 nm (corresponding to the exciton absorption band) under excitation of 340 nm, responding with high selectivity and a detection limit of 4.9 μM for urea in blood serum. Self-assembly of diphenylalanine nanostructures in the presence of ZnO nanoparticles display distinctive luminescent emission at 550 nm that affords sensitive detection of trypsin down to 0.1 ng mL−1. As a surface-enhanced Raman scattering substrate, ZnO tips can be decorated with gold nanoparticles to take advantage of the synergistic effect. Assay for nicotine demonstrates high sensitivity, reaching a lower detection limit of 8.9×10−12 mol/L and offering a linear dynamic range of 10−10-10−6 mol/L. A localized plasmon-based fiber optic sensor can be immobilized with ZnO nanoparticles along with Au nanoparticles for the detection of p-cresol (a water pollutant) as low as 57 μM. A field effect transistor device consisting of ZnO nanoparticles and glutathione-S-transferase in the composite channel can successfully detect and quantifies glutathione in solution and in cancerous cells. The glucose content in food samples can be determined using ZnO nanoparticles, with a correlation coefficient of 0.9812 at 3.5 mM-27.8 mM concentrations [137-143].

A novel electrochemical sensor made by drop casting zinc oxide nanoparticles and electropolymerizing glutamic acid can detect sodium dodecyl sulfate with excellent selectivity via molecular imprinting. ZnO was overlaid on the interdigitated electrode of an electrochemical DNA biosensor to detect sequence complementation from Ganoderma boninense. ZnO nanoparticles prove to be excellent for doping carbon dots in electrochemical biosensor applications. Chemical vapor deposition of ZnO nanoparticles on an aluminum foil working electrode successfully sensed cysteine electrochemically. Smartphones can be combined with screen-printed electrodes or interdigital electrodes for in-situ electrochemical detection. The electrodes are often modified with biomaterials, chemical materials, and nanomaterials (such as ZnO) for biosensing to monitor ascorbic acid, dopamine, glucose, levodopa, and uric acid in point-of-care testing. Aluminum doping can be attained by radio frequency magnetron sputtering of ZnO nanoparticles deposited on a glass substrate for biosensor applications. Four different H2O2 biosensors have been designed using ZnO nanoparticles, multiwalled carbon nanotubes, Prussian blue, ionic liquid and horseradish peroxidase. The best analytical performance offers a linear dynamic range of 9.99×10-8‒7.55×10-4 M, detection limit of 1.37×10-8 M, and sensitivity of 17.00 µA mM-1. A laser scribed graphene-ZnFe2O4 electrochemical aptasensor for acute myocardial infarction screening has been developed for detecting the cardiac troponin-I biomarker, with a limit of detection of 0.001 ng/mL and a sensitivity of 19.3 µA/(ng/mL). The Ag-ZnO-graphene oxide/glassy carbon electrode exhibits high sensitivity, detection limit of 0.02 μM, and fast response within 3 s owing to the efficient oxidation of diclofenac sodium at 0.25 V. Trimetallic Ni/Ag/Zn oxide composite-modified glass carbon electrode has good sensor sensitivity of 0.96 μA/μM cm2 and detection limit of 0.3 μM for dopamine. ZnO-reduced graphene oxide-Au nanoparticles can modify a screen-printed electrode for fast electrochemical detection of dopamine in biological samples. A uric acid biosensor was constructed with nafion/uricase/ZnO nanorods-ZnO nanoparticles on a fluorine-doped tin oxide electrode. Differential pulse voltammetry demonstrated linearity over a wide concentration range (0.01-1.5 mM) with a high sensitivity (345 μA mM−1cm−2) and low limit of detection (2.5 μM). A glassy carbon electrode modified with carbon nanotubes, cytochrome C and ZnO nanoparticles has good sensitivity for the detection of streptomycin in pharmaceutical samples. The highly sensitive interface of penicillinase@CHIT/PtNP-ZnO/ZnHCF/FTO electrode shows a linear response and good limit of detection (0.1 μM) in antibiotics in forensic samples. Biosensors based on ZnO and NiO nanostructures decorated with Au nanoparticles have opened the doors to detect volatile organic compounds using electrochemical methods. Biomass carbon derived from cassava and its composites with ZnO nanoparticles can be synthesized for biosensing due to their low cost and resource availability [144-159]. In our lab, screen-printed electrodes are modified by a deposit of ZnO nanoparticles from aqueous suspension onto the graphite working electrode surface. After drying, a sample solution containing sodium metabisulfite analyte in 1 M KCl can be placed on top for chronoamperometry using the Homianze μEA 160C electrochemical analyzer. A typical current-time curve is obtained as shown in Figure 2a, which is ready for data analysis in accordance with the Cottrell equation as shown in Figure 2b.

FIG 2

Figure 2: (a) Screen shot of current-time curve obtained in our lab from sodium metabisulfite with ZnO nanoparticles deposited on graphite electrode. (b) Plot of current vs. inverse square root of time for Cottrell analysis.

Self-cleaning and Anti-fouling Polymeric Membranes for Wastewater Treatment and Analytical Separations

A recent trend in nanotechnology shows the application of nano-based materials, such as nano-adsorbents, nano-metals, nano-membranes, and photocatalysts, in water treatment processes. Nanomaterials typically have high reactivity and a high degree of functionalization, large specific surface area, and size-dependent properties which makes them suitable for applications in wastewater treatment and for water purification. Nanostructured catalytic membranes, nanosorbents and nanophotocatalyst-based approaches to remove pollutants from wastewater are eco-friendly and efficient, but they require more energy and more investment in order to purify the wastewater. Current and potential applications of nanoparticles and nanotechnologies in wastewater treatment as well as challenges have been reviewed on the basis of bibliometric results [160-165]. Self-cleaning surfaces have attracted significant attention in both the scientific and industrial communities [166]. In the past decade, transition metal oxide nanoparticles have extensively been incorporated with polymeric membranes for water treatment. Special emphasis is given here to their anti-fouling and self-cleaning properties when used also in the preparation of wastewater samples before chemical composition analysis. Various forms of copper, titanium dioxide and zinc peroxide were tested against microbial fouling and microbiologically influenced corrosion. Their incorporation into polyethylene (high density) and fiber-reinforced plastic provides surface protection. Wastewater treatment is currently a crucial topic worldwide due to global human population growth (83 million annually), industrial downstream contamination, and weathering degradation of polymers [167-170]. Various water treatment techniques are being advanced due to the rising concern of drinking water scarcity and safety. Besides conventional water treatments, the pressure-driven water purification technology has attracted attention due to its efficiency and received substantial applications. Pressure-driven membranes can be classified into microfiltration, ultrafiltration, nanofiltration, and reverse-osmosis. These membranes are used to separate ions, macromolecules, suspended particles and nanomaterials from water. Organic polymeric membranes are extensively used for commercial purposes due to their excellent physical, chemical, and mechanical characteristics. However, membrane fouling occurs due to their hydrophobic nature plus bacterial accumulation and is limiting their sustained operation over time. Regarding membrane fouling, a combination of polymer and nanoparticles is suggested to be a practical strategy for enhancing membrane hydrophilicity. Incorporating nanoparticles into polymeric membranes is becoming a trend in membrane technology. Polymers and metal oxides are becoming popular membrane filtration materials for wastewater treatment due to their surface functionality, large surface area, and unique optical/paramagnetic properties. Under visible light conditions, the polymer-metal oxide nanocomposite membrane affords superior photodegradation activity toward organic pollutants. Transition metal oxides have been evaluated by many researchers during the last decade for wastewater reclamation, as self-cleaning and anti-fouling agents, to utilize their surface mobility, magnetic and optical properties. Recently, a review on polymer nanocomposite membranes based on metal oxide nanoparticles was published in the field of ultrafiltration membrane technology [171-194].

ZnO nanoparticles have been extensively used by scientists and researchers, known to be inorganic, hydrophilic, low-cost, and green (environment-friendly) material. Fluoride contamination of water is a serious problem in the world, and zinc oxide nanoparticles are the best adsorbent for the removal of fluoride from water and wastewater, with an adsorption capacity of 100 mg/g. In wastewater treatment processes, ZnO nanoparticles exert a negative impact on the sludge flocculation performance but do not significantly impact the sludge sedimentation behavior. A decrease of the tyrosine protein-like substance level is probably the key reason for the decreased ζ potential in the loosely bound extracellular polymeric substances, which eventually induces a decline of the sludge flocculation performance under the ZnO stress. A novel deflocculant ZnO/chitosan nanocomposite film in disperser pretreatment enhances the energy efficiency of anaerobic digestion by achieving 99% solubilization of organics. In addition to the anti-fouling performance, ZnO nanoparticles also provide photocatalytic self-cleaning ability to the polymeric membranes. Hence, ZnO-incorporated composite membranes were considered an emerging topic in membrane technology. Modification of polyvinyl chloride membrane using ZnO nanoparticles is very effective for municipal wastewater treatment in the presence of ferric chloride coagulant. The nanocomposite membrane did not adsorb the sludge inside the pores, hence substantially limiting the membrane fouling. Polyvinylidene fluoride membrane with high hydrophilicity was reported to be developed through the conglomeration of ZnO and graphene oxide. Anti-fouling properties, porosity, water flux and wettability were improved to attain a stable effluent quality (0.6 NTU). Combination of graphene oxide and ZnO nanoparticles on polysulfone membrane surface improves the membrane performances to treat petroleum refinery wastewater in terms of higher porosity, increased hydrophilicity, better mechanical strength, reduced water contact angle, increased water uptake ability, higher permeate flux, rejection of total dissolved solids, and improved antifouling properties. Unfortunately, no sustainable membrane systems are yet fully established due to their huge energy requirements for partial removal or degradation of trace organic compounds. Impregnation of ZnO-graphene also reduces polyethersulfone membrane-solute and membrane-foulant hydrophobic interactions. ZnO incorporation enhances the hydrophilicity and improves the anti-fouling property of polyether sulfone membranes. A mean pore size of 0.64 nm and good humic acid rejection make the hybrid membrane well suited for nanofiltration in wastewater treatment and water reclamation. Multifunctional nanofibrous membranes with sunlight-driven self-cleaning performance for complex oily wastewater remediation can be constructed with an Ag/ZnO layer on the porous polyacrylonitrile nanofiber substrate. The membranes demonstrate excellent mechanical strength, superhydrophilic (water contact angle = 0°), underwater superoleophobic (contact angle = 154°) properties, high permeation flux (>619 Lm-2h-1) and separation efficiency (>99.7%) for various oil-in-water emulsions [195-204].

The effect of photoactive semiconductor catalyst (TiO2 and ZnO) on the anti-fouling and self-cleaning properties of polyether sulfone composite membranes (14% by weight) was studied with different concentrations of graphene oxide. The hydrophilicity of composite membranes improved as compared to neat membrane; however, graphene oxide-TiO2 functionalized membranes showed the lowest flux. Incorporation of CuO nanoparticles in polymeric membranes for water treatment is a potential solution for biofouling formation. Promising results have been reported for antibacterial/antifouling effects, increased hydrophilicity, water flux improvement, contaminant rejection capacity, structural membrane parameters, and reduction of concentration polarization. TiO2 nanoparticles have been added to improve the self-cleaning and anti-fouling ability of ultrafiltration polymer membranes through their photocatalytic activity. Immobilization of TiO2 nanoparticles on membrane surfaces was investigated to reduce organic fouling effects in a bioreactor by increasing the membrane hydrophilicity. Cajanus cajan seed extract and carbon nanoparticles reformed the hydrophobic PVDF membrane to hydrophilic. Introduction of TiO2 (0.02% by weight) into the membrane rendered it bi-functional, thus achieving 85% rejection of Cr(VI) and 92% reduction to Cr(III) in tannery wastewater. Ag2O, Fe2O3 and ZrO2 nanoparticles can be incorporated to improve the performance of polymeric filtration membranes due to their effects on permeability, selectivity, hydrophilicity, conductivity, mechanical strength, thermal stability, antiviral, and antibacterial properties. However, they might cause membrane deterioration. Thus, careful selection is required to choose the best composition of metal oxide nanoparticles for individual polymeric membranes. The advantages and disadvantages of Ag2O, CuO, Fe2O3, TiO2, ZnO and ZrO2-incorporated polymeric membranes for water purification have been compared in a new review. Their characteristics (antibacterial property, anti-viral property, conductivity, contaminants rejection, flux permeation, hydrophilicity, mechanical strength, permeability, surface charge, and thermal stability as shown in Table 1) can help decide on the best modification towards achieving sustainable and cost-effective treatment operations. Bimetallic transition metal oxide nanoparticles have attracted many researchers due to their salient features and characteristics over mono metallic oxide nanoparticles. PES ultrafiltration membranes were fabricated using the phase inversion technique (most commonly used technique to fabricate polymeric porous membranes with a large form of structure) with a composite of Fe2O3-Mn2O3 nanoparticles as modifier. Those membranes showed an excellent porosity (74%), high water flux (398 L/m2h), and better antifouling ability. Protein-based filtration tests showed an improved flux recovery ratio in protein separation and water treatment applications [205-214].

Table 1: Transition metal oxide nanoparticles-incorporated polymeric membranes

Transition Metal Oxides

Polymeric Membrane Advantages

Limitations

ZnO Polysulfone, polyurethane, polyvinylidene difluoride Antibacterial, anti-corrosion, anti-fouling, environment-friendly, hydrophilic, low-cost, mechanical strength, self-cleaning (photocatalytic activity). Not stable (photocatalytic property), mildly toxic.
TiO2 Antibacterial, anti-corrosion, anti-fouling, hydrophilic self-cleaning (photocatalytic activity). High doses may induce cytotoxicity, not stable (photocatalytic property).
Fe2O3 Abundantly available, can remove heavy metals, magnetic properties, mechanical strength, non-toxic. Nanoparticles tend to agglomerate easily.
CuO Antibacterial, anti-corrosion, anti-fouling, compound rejection capacity, hydrophilic, improving water flux, mechanical strength. Low-quality nanoparticles are produced via physical synthesis, toxic chemicals are used if produced through chemical synthesis.
Ag2O Pressure retarded osmosis membranes Almost non-toxic, anti-fouling, antimicrobial, resistant to corrosion, stable. Membranes are sensitive to nanoparticle concentration.
ZrO2 Novel membranes Capable of treating saline water, high-temperature stability, high water retention capacity. Fouling susceptibility, expensive raw materials.
Fe2O3–Mn2O3 Polyether sulfone Antifouling, minimal irreversible fouling, excellent water flux, improved recovery for protein separation. Agglomeration of nanoparticles.
TiO2-ZnO composite membrane Increased hydrophilicity, anti-fouling, self-cleaning properties, photocatalytic activity. Low flux.

Fabrication of transition metal oxide nanoparticles-modified polymeric membranes to make them operation-sustainable cost-efficient is challenging. Transition metal oxide nanoparticles have many interesting functional properties. However, integrating nanoparticles into a membrane remains a challenge. Atomic layer deposition and sequential infiltration synthesis were explored for the modification of polymeric membranes and fabrication of novel mesoporous structures. Fouling is a major problem that hinders the operation of membrane filtration processes. Bio-fouling causes performance degradation and elevates energy consumption due to blockage of membrane pores. In addition, it increases the frequency of membrane cleaning and reduces the membrane life span, thereby leading to higher maintenance and operation costs. Antibacterial membranes are considered an attractive strategy to retard biofouling. ZnO is reported to be useful as an anti-fouling agent in polymeric nanofiltration and reverse-osmosis membranes. Instead of ZnO, ZnO2 nanoparticles can be incorporated to make nanofiltration and reverse-osmosis polymeric membranes for better retardation of fouling since ZnO2 is a stronger oxidizing agent than ZnO and can produce free radicals and other reactive oxygen species to inhibit growth of microorganisms. The operating temperature of nanofiltration and reverse-osmosis is typically within 25-65°C, which is far below the transition temperature (233°C) of ZnO2. Hence, ZnO2 nanoparticles embedded in the polymeric membrane are completely stable during wastewater treatment. ZnO2 has photocatalytic self-cleaning property that would make it a strong modifier over ZnO in the fabrication of polymeric membranes. Importantly, these membranes can greatly facilitate the preparation of samples for instrumental analysis of emerging contaminants by removing microplastics (plastic particles smaller than 5 mm) that exist in wastewater and marine environments, including pharmaceuticals, personal care products, perfluoroalkyl substances, organophosphate flame retardants, illicit drugs, and isoprostanes in wastewater as biomarkers of oxidative stress during COVID-19 pandemic. A complete summary of recent advances and latest studies in the fabrication, modification, and industrial application of ZnO photocatalysts is available for further reading. Black TiO2 nanotube array can be employed as both photocatalyst and electrocatalyst to degrade dissolved organic matter in coking wastewater [215-227].

Analytical Methods for Transition Metal Oxide Nanoparticles

New developments have recently been reported concerning the chemical analysis of transition metal oxide nanoparticles in environmental water due to their biochemical toxicity. A unifying methodology for the selective detection of transition metal oxide nanoparticles in water, as well as sensitive determination of environmentally toxic and biochemically active contaminants that are bound on them, is urgently needed. In our lab, new analytical methods have undergone intensive development in the last ten years with a focus on capillary electrophoresis with UV and molecular fluorescence detection (Figure 3). The toxic effects of these emerging contaminants have already been verified by Health Canada and Environment Canada using bioassays. The methodology under intensive development in our research lab begins with a sample treatment step that encapsulates all waterborne nanoparticles/nanomaterials into lecithin liposomes. Centrifugation concentrates the loaded liposomes, and the supernatant water is withdrawn for instrumental analysis by liquid chromatography with detection by tandem mass spectrometry. Next a surfactant disintegrates the liposomes and isolates lecithin from the nanoparticles. Contaminants are desorbed from the nanoparticle surfaces using coordination chemistry, biochemical interaction, laser photo/photothermal chemistry, aerosol nebulization, and electrospray ionization. The desorbed contaminants can be analyzed, either immediately or after separation by capillary electrophoretic/gel filtration/liquid chromatography, by spectrofluorometric and mass spectrometric detection. Optical incoherent scattering and electrochemical chemistry can be adapted to detect the nanoparticles and desorbed contaminants at trace to ultratrace levels [228-238].

FIG 3

Figure 3: Development of new analytical methods for transition metal oxide nanoparticles in our lab.

Transition metal oxide nanoparticles are increasingly used as a solid carrier in the formulation of numerous drug products. They end up in waste streams, consequently infiltrating the aquatic environments and drinking water resources. Detection of nanoparticles in wastewater requires more advanced analytical methods than conventional water analysis, to prevent the ecosystem of plants and animals from unintended exposure to the released pharmaceuticals. Determination of nanoparticles in drinking water has important implications for protecting the public health sustainability. Unfortunately, many emerging contaminants are not yet stipulated in water quality regulations due to a lack of monitoring technology. Hence, there is an urgent need to develop new analytical methods that can monitor emerging contaminants in water resources. The interplay of nanoparticles, environmental pollution, and health risks is key to all industrial, environmental, and drinking water treatment regulations. A unifying analytical methodology will help scientists and engineers strengthen their control of nanoparticles in freshwater sources for drinking water treatment plants. New endeavors must challenge the traditional notion that environmental toxicological events involve only dissolved contaminants. Rather, environmental toxicology can involve a complex assortment of nanoparticles and associated contaminants whose combined effects on biological and mammalian cells are continuously evolving. The precise toxico-pathogenic effects of ZnO nanoparticles on the cardiovascular system under normal and cardiovascular disease risk factor milieu include down regulation of vascular development and elevation of oxidative stress in the heart tissue. Both endothelial nitric oxide generation and cardiac Ca2+-ATPase activity are significantly suppressed; the cardiac mitochondrial swelling is enhanced [239].

Wastewater Analysis

The nanoparticles released from different nanomaterials used in our household and industrial commodities find their way through waste disposal routes into the wastewater treatment facilities and end up in wastewater sludge. Further escape of these nanoparticles into the effluent will contaminate the aquatic and soil environment. Polyacrylic acid nanomembranes can be used as nano-filters to isolate and remove Ag and TiO2 nanoparticles in aqueous environmental samples using pressure-driven flow, with a filtration efficiency of >99%. The phytoremediation potential of Myriophyllum spicatum L. for removal of ZnO nanoparticles in tap water ranges between 29% and 70%, and slightly higher in pond water. Wastewater treatment plants are a primary source of many contaminants to the environment. Processing complex mixtures of waste, they can result in the continuous discharge of bioactive and endogenous compounds into sensitive aquatic ecosystems. Wastewater analysis has been demonstrated to be a cumulative approach for assessing the overall patterns of alcohol, drugs, tobacco and xenobiotic use by a population at the community level. Hospital wastewater, for one, is regarded as a very important source of fluoroquinolone antibiotics (ciprofloxacin, norfloxacin, and ofloxacin) in the aquatic environment. The development of analytical methods is crucial for the detection of oxidative stress biomarkers in wastewater, using ultra-high-performance liquid chromatography coupled with tandem mass spectrometry and solid phase extraction. Mixed liquor can be collected from the secondary aeration tank while effluent wastewater is collected after the secondary settling tank in a wastewater treatment plant. Mixed liquor is the wastewater which leaves the aeration tank after biological treatment before going into the secondary settling tank for the suspended solids to sediment, while effluent wastewater is the ultimate treated wastewater which is discharged to the river from the treatment plant. Obviously, mixed liquor has much higher levels of suspended solids and relatively higher dissolved carbon content compared to effluent wastewater. Nanoparticles from thirteen different elements were determined, throughout the full-scale wastewater treatment process, by using single particle inductively coupled plasma mass spectrometry. Samples of the influent, post-primary treatment, effluent of the activated sludge process, as well as reclaimed water were analyzed. The incidence of metal-based nanoparticles decreases significantly after the conventional wastewater treatment train, and they are smaller in the effluent (<180 nm) than in the influent (<300 nm). However, anaerobic digesters store high nanoparticle concentrations. Hence, the disposal of sludge needs to take this into account to evaluate the risk of nanoparticles release to the environment [240-248].

The potential use of 8-iso-PGF2α as a sewage biomarker for assessing the status of community health was investigated by liquid chromatography-high resolution mass spectrometry coupled to immunoaffinity clean-up and β-glucuronidase treatment. Urinary excretion provides a mechanism for the entry of isoprostanes to wastewater treatment plants and subsequently the wider environment, where they may initiate a cycle of oxidative stress in aquatic biota. Additional isoprostanes may be produced within these organisms, further perpetuating this cycle of toxicity. An analytical method for their detection in wastewater, based on solid phase extraction and gas chromatography mass spectroscopy, involves a deconjugation treatment with -glucuronidase to increase the concentration of isoprostanes available for detection. The low ng/L range of concentrations of human metabolic biomarkers and the complex matrix composition pose bioanalytical challenges related to sample preparation, detection and quantification. A sensitive liquid chromatography-mass spectrometry method for the detection and analysis of opioid biomarkers has been validated according to the European Medicines Agency guidelines; Oasis HLB cartridges are useful for sample concentration. Ion pairing liquid chromatography with alkanesulfonates coupled to tandem mass spectrometry is valid for the analysis of aminoglycosides (veterinary antibiotics) in wastewater samples after addition of the ion paring salt directly into the raw or treated wastewater samples. Surface-enhanced Raman spectroscopy is good for the detection of methamphetamine based upon the assembly of Au@Ag core-shell nanoparticles on a disposable glassy nanofibrous electrospun paper matrix that gives strong scattering signals. Microplastics are generated while polishing eyeglass lenses and a huge amount of nanoplastics (<1 µm) passes through the conventional wastewater treatment process in considerable amounts. Microplastics (with adsorbed heavy metals) can be quantified in the wastewater by mass balance measurements using membrane filtration with polyaluminum chloride coagulation. The transport of nanoparticles in various wastewater treatment processes is fully discussed in another review [249-255].

Air Pollution Remediation and Quality Monitoring

One of the most favorable environmental applications of nanotechnology has been in air pollution remediation in which different nanomaterials are used. Nanoparticles have initiated the advancement in new and low-cost techniques for environmental pollution control including air pollution. Metal oxide nanofibers have demonstrated to be effective for air pollution remediation in the form of filter, catalyst, catalyst support, and photocatalyst. Fibrous metal oxide has several advantages including surface area, mechanic strength, chemical stability, thermal stability, and photocatalytic ability. In the field of selective reduction of nitrogen oxide, a catalyst with low cost, low toxicity, high activity, and good selectivity for N2 is needed to replace the high-cost and high-toxicity vanadium catalyst. Low-cost spinels MFe2O4 (M = Cu, Mn, and Zn) can be synthesized for this application, and MnFe2O4 exhibits the best activity (99.9%) and selectivity (95.7%) at 100°C [256-258].

Nanocomposites have distinctive physical and chemical properties that result in their use in the construction industry as innovative materials. Addition of nanoparticles can bring many important properties to the bulk construction and insulation materials. Unfortunately, release of ultrafine dust to the air environment has harmful impacts on human health. Nanoparticles can enter the human body through the skin, inhalation, and ingestion. Exposure to nanoparticles can cause serious respiratory, cardiovascular, skin, and nerve related diseases. It can pass through various mammalian membranes, or be absorbed in them, to cause various inflammatory reactions and fibrosis. Pneumoconiosis refers to a class of interstitial lung diseases caused by the inhalation of airborne dust and fibers. Engineered nanoparticles, owing to their high reactivity, can initiate inflammatory responses that trigger metastasis. Human exposure to nanoparticles can cause various health implications such as DNA damage and cell death. A global regulatory policy needs to be framed to assess the toxicity, risk and approval of nanoparticles used in the construction industry. The current OSHA standard for ZnO fume is 5 mg/m3 of air averaged over an eight-hour work shift. NIOSH recommends that the permissible exposure limit be changed to 5 mg/m3 averaged over a work shift of up to 10 hours per day, 40 hours per week, with a short-term exposure limit of 10 mg/m3 averaged over a 15-minute period. It would be scientifically interesting to investigate the percutaneous absorption of transition metal oxide nanoparticles following exposure to road dust powder [259-264].

Semiconducting metal oxide gas sensors have been developed for environmental gases including CO2, O2, O3 and NH3; highly toxic gases including CO, H2S and NO2; combustible gases such as CH4, H2, and liquefied petroleum gas; and volatile organic compound gases. Nanomaterial enabled sensors are applied for the detection of harmful gases such as H2S, SO2, and NO2 . An ultrafast sensor has been developed for trace-level detection of NH3 gas using ZnO nanoparticles, with ultra-fast response (5 sec) and recovery time (8 sec) at 5 ppm. Dopants can enhance the performance of semiconductor metal oxides for gas sensing applications by changing their microstructure morphology, activation energy, electronic structure, and band gap of the metal oxides. In some cases, dopants create defects in semiconductor metal oxides by generating oxygen vacancy or by forming solid solutions. To date, very little is known about the magnitude, patterns, and associated risks of human exposure to microplastics, particularly in the indoor environment. This is a significant research gap given that people spend most of their time indoors, which is exacerbated over the past year by COVID-19 lockdown measures [265-269].

Conclusion

This scientific field possesses immense potential that may provide incredible technological advances soon. The research findings covered in this review article could open many doors to new endeavors. Having more reactive oxygen atoms per molecule, ZnO2 can be considered as a stronger oxidizing agent than ZnO. This unique property makes its nanoparticles an excellent candidate for potential breakthroughs in analytical, biomolecular, food, material, and separation sciences. In addition, mono-dispersed ZnO2 nanoparticles could be coupled with a magnetic core to produce nanocarriers for in-situ disruption of cancer cells. High-performance nano-filtration and reverse-osmosis could be developed with ZnO2 for fouling remediation with self-cleaning feature. For future applications, intelligent antibacterial food nano-packaging could undergo new developments through incorporation of ZnO2 nanoparticles to the packaging film. It will become more and more important that the presence of ZnO/ZnO2 in wastewater is detected and quantitated for the protection of environmental sustainability and public health. The knowledge gap in this dynamic field, as highlighted in this review, will require novel research work.

Acknowledgement

Financial support from NSERC Canada (grant number RGPIN-2018-05320) is gratefully acknowledged.

Competing Interest Statement

The authors have no competing interests to declare.

Data Availability Statement

The raw/processed data required to reproduce our findings in Figure 2a/2b cannot be shared at this time as the data also forms part of an ongoing study.

References

  1. Schiattarella C (2020) Photoemissive inorganic nanomaterials: characterization and their application in biophotonics. Ph.D. thesis, Università degli Studi di Napoli Federico II.
  2. Abdah MAAM, Azman NHN, Kulandaivalu S, Sulaiman Y (2020) Review of the use of transition-metal-oxide and conducting polymer-based fibres for high-performance supercapacitors. Materials & Design 186: 108199.
  3. Oka H, Okada Y, Kaminaga K, Oka D, Hitosugi T, et al. (2020) Width-induced metal-insulator transition in SrVO3 lateral nanowires spontaneously formed on the ultrathin film. Applied Physics Letters 117: 051603.
  4. Akbari A, Amini M, Tarassoli A, Eftekhari-Sis B, Ghasemian N, et al. (2018) Transition metal oxide nanoparticles as efficient catalysts in oxidation reactions. Nano-Structures & Nano-Objects 14: 19-48.
  5. Li R, Luo L, Ma X, Wu W, Wang M, et al. (2022) Single atoms supported on metal oxides for energy catalysis. Journal of Materials Chemistry A 5717-5742.
  6. Drummer S, Madzimbamuto T, Chowdhury M (2021) Green synthesis of transition metal nanoparticles and their oxides: a review. Materials (Basel) 14: 2700. [crossref]
  7. Khaldakar M, Butala D (2017) The synthesis and characterization of metal oxide nanoparticles and its application for photocatalysis. International Journal of Scientific and Research Publications 7: 499-504.
  8. Lousada CM, LaVerne JA, Jonsson M (2013) Enhanced hydrogen formation during the catalytic decomposition of H2O2 on metal oxide surfaces in the presence of HO radical scavengers. Physical Chemistry Chemical Physics 15: 12674-12679.
  9. Agnihotri AS, Varghese A, Nidhin M (2021) Transition metal oxides in electrochemical and bio sensing: a state-of-art review. Applied Surface Science Advances 4: 100072.
  10. George JM, Antony A, Mathew B (2018) Metal oxide nanoparticles in electrochemical sensing and biosensing: a review. Microchimica Acta 2018, 185, 358. [crossref]
  11. Han X, Liu R, Xu Z, Chen W, Zheng Y (2005) Room temperature deposition of nanocrystalline cadmium peroxide thin film by electrochemical route. Electrochemistry Communications 7: 1195-1198.
  12. Avena M (2021) The reactivity of the metal oxide-water and mineral-water interfaces-an inorganic/coordination viewpoint. European Journal of Inorganic Chemistry.
  13. Ningthoujam R, Jena B, Pattanayak S, Dash S, Panda MK, et al. (2022) Nanotechnology in food science. In Bio-Nano Interface, Springer, Singapore.
  14. Amir AA, Hamed A, Maryam A (2021) Antimicrobial properties of food nanopackaging: a new focus on foodborne pathogens. Frontiers in Microbiology 12: 690706.
  15. Khodaveisi J, Banejad H, Afkhami A, Olyaie E, Lashgari S, et al. (2011) Synthesis of calcium peroxide nanoparticles as an innovative reagent for in situ chemical oxidation. Journal of Hazardous Materials 192: 15, 1437-1440.
  16. Jakob H, Leininger S, Lehmann T, Jacobi S, Gutewort S (2007) Peroxo Compounds, Inorganic. Ullmann’s Encyclopedia of Industrial Chemistry.
  17. Ahmad S, Kharkwal M, Gupta G, Nagarajan R (2011) Journal of Physical Chemistry C, 115: 10131-10139.
  18. Liu Y, Zhang YC, Zhang M (2010) Green hydrothermal synthesis and characterization of CdO2 Materials Letters 64: 1779-1781.
  19. Hu H, Yu L, Qian X, Chen Y, Chen B, et al. (2020) Chemoreactive nanotherapeutics by metal peroxide-based nanomedicine. Advanced Science 8: 2000494.
  20. Gnanasekaran L, Priya AK, Gracia F (2022) Orange peel extract influenced partial transformation of SnO2 to SnO in green 3D-ZnO/SnO2 system for chlorophenol degradation. Journal of Hazardous Materials 424: 127464.
  21. Anvar AA, Ahari H, Ataee M (2021) Antimicrobial properties of food nanopackaging: a new focus on foodborne pathogens. Frontiers in Microbiology 12: 690706.
  22. Zinc oxide and peroxide. https://oec.world/en/profile/hs/zinc-oxide-and-peroxide
  23. Gbur T, Čuba V, Múčka V, Nikl M, Knížek K, et al. (2011) Photochemical preparation of ZnO nanoparticles. Journal of Nanoparticle Research 13: 4529-4537.
  24. Lee PHY, Wu BK, Chern MY (2014) Study on the formation of zinc peroxide on zinc oxide with hydrogen peroxide treatment using X-ray photoelectron spectroscopy. Electronic Materials Letters 10: 51-55.
  25. Uekawa N, Mochizuki N, Kajiwara J, Mori F, Wu YJ, et al. (2003) Nonstoichiometric properties of zinc oxide nanoparticles prepared by decomposition of zinc peroxide. Physical Chemistry Chemical Physics 5: 929-934.
  26. Bocharov D, Chesnokov A, Chikvaidze G, Gabrusenok J, Ignatans R, et al. (2022) A comprehensive study of structure and properties of nanocrystalline zinc peroxide. Journal of Physics and Chemistry of Solids 160: 110318.
  27. Escobedo-Morales A, Esparza R, García-Ruiz A, Aguilar A, Rubio-Rosas E, et al. (2011) Structural and vibrational properties of hydrothermally grown ZnO2 Journal of Crystal Growth 316: 37-41.
  28. Sebőka D, Szabóa T, Dékány I (2009) Optical properties of zinc peroxide and zinc oxide multilayer nanohybrid films. Applied Surface Science 255: 6953-6962.
  29. Zinc peroxide. https://en.wikipedia.org/wiki/Zinc_peroxide.
  30. Naofumi U, Jyunichi K, Naomi M, Kazuyuki K, Yoshinori S (2001) Synthesis of ZnO nanoparticles by decomposition of zinc peroxide. Chemistry Letters 30: 606-607.
  31. Rosenthal-Toib L, Zohar K, Alagem M, Tsur Y (2008) Synthesis of stabilized nanoparticles of zinc peroxide. Chemical Engineering Journal 136: 425-429.
  32. Ramírez JIDL, Villegas VAR, Sicairos SP, Guevara EH, Brito Perea MDC, et al. (2020) Synthesis and Characterization of Zinc Peroxide Nanoparticles for the Photodegradation of Nitrobenzene Assisted by UV-Light. Catalysts 10: 1041.
  33. Wang K, Lai EPC (2023) Electrochemical sensing of zinc oxide and peroxide nanoparticles: Modification with meso-tetrakis(4-carboxyphenyl) porphyrin. Chemosensors 11: 369.
  34. Yang LY, Feng GP, Wang TX (2010) Green synthesis of ZnO2 nanoparticles from hydrozincite and hydrogen peroxide at room temperature. Materials Letters 64: 1647-1649.
  35. Palma-Palma HE, Camacho-López M, Camacho-López MA, Vilchis-Néstor AR (2015) Preparation of zinc peroxide nanoparticles by laser ablation of solid in liquids. Superficies vacío 28: 74-77.
  36. Elbahri M, Abdelaziz R, Disci-Zayed D, Homaeigohar S, Sosna J, et al. (2017) Underwater Leidenfrost nanochemistry for creation of size-tailored zinc peroxide cancer nanotherapeutics. Nature Communications 8: 15319.
  37. Ana Industries. Zinc peroxide. http://anaindustries.in/product/zinc-peroxide/.
  38. Zinc peroxide nanoparticles coated with oPEG ligands. https://nanoxo.eu/product/zinc-peroxide-nanoparticles-zno2-nps-coated-with-opeg-ligands/.
  39. Wolanov Y, Prikhodchenko PV, Medvedev AG (2013) Zinc dioxide nanoparticulates: a hydrogen peroxide source at moderate pH. Environmental Science and Technology 47: 15. [crossref]
  40. Shames AI, Lev O, Mikhaylov AA, Medvedev AG, Gun J, et al. (2019) Unusual stabilization of zinc peroxide by manganese oxide: mechanistic understanding by temperature-dependent EPR studies. Journal of Physical Chemistry C 123: 20884-20892.
  41. Tatarchuk VV, Gromilov SA, Maksimovskii EA, Plyusnin PE (2021) Zinc peroxide nanoparticles: micellar synthesis and preparation of films. Russian Journal of Inorganic Chemistry 66: 1748-1760.
  42. Moger J, Johnston BD, Tyler CR (2008) Imaging metal oxide nanoparticles in biological structures with CARS microscopy. Optics Express 16: 3408-3419. [crossref]
  43. Drmosh QA, Gondal MA, Yamani ZH, Saleh TA (2010) Spectroscopic characterization approach to study surfactants effect on ZnO2 nanoparticles synthesis by laser ablation process. Applied Surface Science 256: 4661-4666.
  44. Bai H, Liu X (2010) Green hydrothermal synthesis and photoluminescence property of ZnO2 nanoparticles. Materials Letters 64: 341-343.
  45. El-Shamy AG (2021) The optical anatomy of new polyvinyl alcohol/zinc peroxide nanocomposite films for promising optical limiting applications. Progress in Organic Coatings 150: 105981.
  46. Gao D, Zhang J, Yang G, Qi J, Si M, et al. (2011) Ferromagnetism induced by oxygen vacancies in zinc peroxide nanoparticles. Journal of Physical Chemistry C 115: 16405-16410.
  47. Ganguly P, Kotnala RK, Singh S, Pant RP, Singh N (2015) Graphene functionalized with 3-mercatopropionic acid capped zinc peroxide nanoparticles: a potential ferromagnetic material at room-temperature. Carbon 95: 428-433.
  48. Syama S, Reshma SC, Sreekant PJ, Varma HK, Mohanan PV (2013) Effect of zinc oxide nanoparticles on cellular oxidative stress and antioxidant defense mechanisms in mouse liver. Toxicological & Environmental Chemistry 95: 495-503.
  49. Bergs C, Brück L, Rosencrantz RR, Conrad G, Elling L, et al. (2017) Biofunctionalized zinc peroxide nanoparticles as active oxygen sources and antibacterial agents. RSC Advances 7: 38998-39010.
  50. Hussein HM, Ghafoor DD, Omer KM. (2021) Room temperature and surfactant free synthesis of zinc peroxide nanoparticles in methanol with highly efficient antimicrobials. Arabian Journal of Chemistry 14: 103090.
  51. Ahtzaz S, Nasir M, Shahzadi L, Amir W, Anjum A, et al. (2017) A study on the effect of zinc oxide and zinc peroxide nanoparticles to enhance angiogenesis-pro-angiogenic grafts for tissue regeneration applications. Materials & Design 132: 409-418.
  52. Ali SS, Morsy R, El-Zawawy NA, Fareed MF, Bedaiwy MY (2017) Synthesized zinc peroxide nanoparticles: a novel anti-microbial, anti-elastase, anti-keratinase, and anti-inflammatory approach toward polymicrobial burn wounds. International Journal of Nanomedicine 12: 6059-6073.
  53. El-Shounya WA, Moawad M, Haider AS, Ali S, Nouh S (2019) Antibacterial potential of a newly synthesized zinc peroxide nanoparticles to combat biofilm-producing multi-drug resistant Pseudomonas aeruginosa 59: 657-666.
  54. Makumire S, Chakravadhanula VSK, Köllisch G, Redel E, Shonhai A (2014) Immunomodulatory activity of zinc peroxide and titanium dioxide nanoparticles and their effects on DNA and protein integrity. Toxicology Letters 227: 56-64.
  55. Verma S, Jain SL (2014) Nanosized zinc peroxide: a novel inorganic oxidant for the oxidation of aromatic alcohols to carbonyl compounds. Inorganic Chemistry Frontiers 1: 534-539.
  56. Giannakoudakis DA, Florent M, Wallace R, Secor J, Karwacki C, et al. (2018) Zinc peroxide nanoparticles: Surface, chemical and optical properties and the effect of thermal treatment on the detoxification of mustard gas. Applied Catalysis B: Environmental 226: 429-440.
  57. Ibarra L, Alzorriz M (2002) Effect of temperature on the crosslink densities of nitrile rubber and carboxylated nitrile rubber with zinc peroxide. Journal of Applied Polymer Science, 86: 335-340.
  58. Tanvir NB, Yurchenko O, Laubender E, Pohle R, Sicard OV, et al. (2018) Zinc peroxide combustion promoter in preparation of CuO layers for conductometric CO2 Sensors and Actuators B: Chemical 257: 1027-1034.
  59. Chawla S, Uppal H, Yadav M, Bahadur N, Singh N (2017) Zinc peroxide nanomaterial as an adsorbent for removal of Congo red dye from wastewater. Ecotoxicology and Environmental Safety 135: 68-74.
  60. Sachin, Joishar D, Singh NP, Varathan E, Singh N (2021) Sodium docusate surface-modified dispersible and powder zinc peroxide formulation: an adsorbent for the effective and fast removal of crystal violet dye, an emerging wastewater contaminant. ACS Omega 6: 22570-22577.
  61. Uppal H, Hemlata, Tawale J, Singh N (2016) Zinc peroxide functionalized synthetic graphite: an economical and efficient adsorbent for adsorption of arsenic (III) and (V) Journal of Environmental Chemical Engineering 4: 2964-2975.
  62. Uppal H, Tripathy S, Chawla S, Sharma B, Dalai MK, et al. (2017) Study of cyanide removal from contaminated water using zinc peroxide nanomaterial. Journal of Environmental Sciences 55: 76-85.
  63. Kale PC, Chaudhari PL (2017) Removal of reactive blue 221 dye from textile wastewater by using zinc peroxide nanoparticles. International Journal of Scientific Research and Management 5: 5700-5709.
  64. Chaudhari PL, Kale PC (2017) Synthesis and characterization of nano zinc peroxide photocatalyst for the removal of brilliant green dye from textile wastewater. International Journal of ChemTech Research 10: 477-486.
  65. El-Sham AGy (2020) New carbon quantum dots nanoparticles decorated zinc peroxide nanocomposite with superior photocatalytic efficiency for removal of different dyes under UV-A light. Synthetic Metals 267: 116472.
  66. Ramírez JIDL, Villegas VAR, Sicairos SP, Guevara EH, Perea MDCB, et al. (2020) Synthesis and characterization of zinc peroxide nanoparticles for the photodegradation of nitrobenzene assisted by UV light. Catalysts 10: 1041.
  67. Fröber K, Bergs C, Pich A, Conrad G (2020) Biofunctionalized zinc peroxide nanoparticles inhibit peri-implantitis associated anaerobes and Aggregatibacter actinomycetemcomitans pH-dependent. Anaerobe 62: 102153.
  68. Sirelkhatim A, Mahmud S, Seeni A, Kaus NHM, Ann LC, et al. (2015) Review on zinc oxide nanoparticles: antibacterial activity and toxicity mechanism. Nano-Micro Letters 7: 219-242.
  69. Lin LS, Wang JF, Song J, Liu Y, Zhu G, et al. (2019) Cooperation of endogenous and exogenous reactive oxygen species induced by zinc peroxide nanoparticles to enhance oxidative stress-based cancer therapy. Theranostics 9: 7200-7209.
  70. Zinc oxide. https://en.wikipedia.org/wiki/Zinc_oxide.
  71. https://arthurscience.weebly.com/uploads/5/0/9/2/5092096/3u_unit_4_day_5__1.pdf
  72. Université Laval. Solubility product constants.
    http://www2.chm.ulaval.ca/gecha/chm1903/6_solubilite_solides/solubility_products.pdf
  73. European Commission. Zinc oxide (nano form)
    https://ec.europa.eu/health/scientific_committees/opinions_layman/zinc-oxide/de/l-3/3.htm.
  74. Escorihuela L, Fernández A, Rallo R, Martorell B (2018) Molecular dynamics simulations of zinc oxide solubility: from bulk down to nanoparticles. Food and Chemical Toxicology 112: 518-525.
  75. Ranking the best zinc supplements of 2021. https://bodynutrition.org/zinc/
  76. Youssef FS, Ismail SH, Fouad OA, Mohamed GG (2024) Green synthesis and biomedical applications of zinc oxide nanoparticles-review. Egyptian Journal of Veterinary Sciences 55: 287-311.
  77. Alsaiari NS, Alzahrani FM, Amari A, Osman H, Harharah HN, et al. (2023) Plant and microbial approaches as green methods for the synthesis of nanomaterials: applications and future perspectives. Molecules 28: 463.
  78. Sani GD, Yakubu A, Saidu A, Aati R, Sahabi S, et al. (2023) A review on industrial applications of zinc oxide nanoparticles. International Journal of Advances in Engineering and Management 5: 1031-1041.
  79. Vinitha V, Preeyanghaa M, Vinesh V, Dhanalakshmi R, Neppolian B, et al. (2021) Two is better than one: catalytic, sensing and optical applications of doped zinc oxide nanostructures. Emergent Materials 4: 1093-1124.
  80. Degefa A, Bekele B, Jule LT, Fikadu B, Ramaswamy S, et al. (2021) Green synthesis, characterization of zinc oxide nanoparticles, and examination of properties for dye-sensitive solar cells using various vegetable extracts. Journal of Nanomaterials 3941923.
  81. Danley M (2021) Characterization of spongelike porous polyvinylidene fluoride for use as a biosensor. M. Eng. thesis, University of Minnesota-Duluth.
  82. Baharudin KB, Abdullah N, Derawi D (2021) Synthesis of raspberry-like structure zinc oxide nanoparticles via glycol-solvothermal, low-temperature solvothermal and coprecipitation methods. Comptes Rendus. Chimie 24: 33-42.
  83. Thakur S, Shandily M, Guleria G (2021) Appraisement of antimicrobial zinc oxide nanoparticles through Cannabis Jatropha curcasa Alovera and Tinosporacordifolia leaves by green synthesis process. Journal of Environmental Chemical Engineering 9: 104882.
  84. Zaheer T, Imran M, Pal K, Sajid MS, Abbas RZ, et al. (2021) Synthesis, characterization and acaricidal activity of green-mediated ZnO nanoparticles against Hyalomma ticks. Journal of Molecular Structure 1227: 129652.
  85. Ibrahim RE, Fouda MMS, Younis EM, Abdelwarith AA, Salem GA, et al. (2024) The anti-bacterial efficacy of zinc oxide nanoparticles synthesized by Nelumbo nucifera leaves against Clostridium perfringes challenge in Oreochromis niloticus. Aquaculture 578: 740030.
  86. Alavi M, Kamarasu P, McClements DJ, Moore MD (2022) Metal and metal oxide-based antiviral nanoparticles: properties, mechanisms of action, and applications. Advances in Colloid and Interface Science 306: 102726.
  87. Shubha P, Ganesh S, Shyamsundar S (2024) Anti-proliferative activity of biosynthesized zinc oxide nanoparticles against breast cancer MCF-7 cells. Materials Chemistry and Physics 128900.
  88. Talodthaisong C, Plaeyao K, Mongseetong C, Boonta W, Srichaiyapol O, et al. (2021) The decoration of ZnO nanoparticles by gamma aminobutyric acid, curcumin derivative and silver nanoparticles: synthesis, characterization and antibacterial evaluation. Nanomaterials 11: 442.
  89. Shilova OA, Tsvetkova IN, Vlasov DY, Ryabusheva YV, Sokolov GS, et al. (2022) Microbiologically induced deterioration and environmentally friendly protection of wood products. In Micro and Nano Technologies, Biodegradation and Biodeterioration At the Nanoscale, 283-321.
  90. Levy J. Zinc oxide benefits for protecting your skin from the sun + more. https://draxe.com/health/zinc-oxide-benefits/.
  91. CCL Mineral & Chemical. Zinc oxide formula-properties & manufacturing.
  92. Sharma N, Gupta PC, Upadhyay S, Rai S, Mishra P (2024) Antimicrobial applications of zinc oxide nanoparticles in food packaging industry. In: R.K. Bachheti, A. Bachheti, A. Husen (eds) Metal and Metal-Oxide Based Nanomaterials. Smart Nanomaterials Technology.
  93. Bui VKH, Pham TN, Hur J, Lee YC (2021) Review of ZnO binary and ternary composite anodes for lithium-ion batteries. Nanomaterials 11: 8.
  94. Verma R, Pathak S, Srivastava AK, Prawer S, Tomljenovic-Hanic S (2021) ZnO nanomaterials: green synthesis, toxicity evaluation and new insights in biomedical applications. Journal of Alloys and Compounds 876: 160-175.
  95. Xie J, Li H, Zhang T, Song B, Wang X, et al. (2023) Recent advances in ZnO nanomaterial-mediated biological applications and action mechanisms. Nanomaterials (Basel) 13: 1500.
  96. Khan M, Ahmad B, Hayat K, Ullah F, Sfina N, et al. (2024) Synthesis of ZnO and PEG-ZnO nanoparticles with controlled size for biological evaluation. RSC Advances 14: 2402-2409.
  97. Hwang GB, Stent J, Noimark S, Heo KJ, MacRobert AJ, et al. (2024) White light-activated bactericidal coating using acrylic latex, crystal violet, and zinc oxide nanoparticles. Materials Advances 5: 259-266.
  98. Ghattavi S, Homaei A (2024) Synthesis and characterization of ZnO-SiO2 hybrid nanoparticles as an effective inhibitor for marine biofilm and biofouling. Journal of Molecular Liquids 396: 123974.
  99. Shen L, Huang Z, Liu Y, Li R, Xu Y, et al. (2020) Polymeric membranes incorporated with ZnO nanoparticles for membrane fouling mitigation: a brief review. Frontiers in Chemistry 8: 224.
  100. Sahu A, Dosi R, Kwiatkowski C, Schmal S, Poler JC (2023) Advanced polymeric nanocomposite membranes for water and wastewater treatment: a comprehensive review. Polymers (Basel) 15: 540.
  101. Roy N, Chakraborty S (2021) ZnO as photocatalyst: An approach to wastewater treatment. Materials Today: Proceedings 2021, 46: 6399-6403.
  102. Hu I, Ma W, Pan Y, Chen Z, Zhang Z, et al. (2022) Resolving the tribo-catalytic reaction mechanism for biochar regulated zinc oxide and its application in protein transformation. Journal of Colloid and Interface Science 607: 1908-1918.
  103. Shkir M, Palanivel B, Khan A, Kumar M, Chang JH, et al. (2021) Enhanced photocatalytic activities of facile auto-combustion synthesized ZnO nanoparticles for wastewater treatment: An impact of Ni doping. Chemosphere 132687.
  104. Sharma SS, Palaty S, John AK (2021) Band gap modified zinc oxide nanoparticles: an efficient visible light active catalyst for wastewater treatment. International Journal of Environmental Science and Technology 18: 2619-2632.
  105. Karthik KV, Raghu AV, Reddy KR, Ravishankar R, Sangeeta M, et al. (2022) Green synthesis of Cu-doped ZnO nanoparticles and its application for the photocatalytic degradation of hazardous organic pollutants. Chemosphere 287: 132081.
  106. Park JK, Rupa EJ, Arif MH, Li JF, Anandapadmanaban G, et al. (2021) Synthesis of zinc oxide nanoparticles from Gynostemma pentaphyllum extracts and assessment of photocatalytic properties through malachite green dye decolorization under UV illumination-a green approach. Optik 239: 166249.
  107. Siddique K, Shahid M, Shahzad T, Mahmood F, Nadeem H, et al. (2021) Comparative efficacy of biogenic zinc oxide nanoparticles synthesized by Pseudochrobactrum sp. C5 and chemically synthesized zinc oxide nanoparticles for catalytic degradation of dyes and wastewater treatment 28: 28307-28318.
  108. Abdullah FH, Abu Bakar NHH, Bakar MA (2021) Comparative study of chemically synthesized and low temperature bio-inspired Musa acuminata peel extract mediated zinc oxide nanoparticles for enhanced visible-photocatalytic degradation of organic contaminants in wastewater treatment. Journal of Hazardous Materials 406: 124779.
  109. Yashni G, Al-Gheethi A, Mohamed RMS, Dai-Viet NV, Al-Kahtani AA, et al. (2021) Bio-inspired ZnO nanoparticles synthesized from Citrus sinensis peels extract for congo red removal from textile wastewater via photocatalysis: optimization, mechanisms, techno-economic analysis. Chemosphere, 281: 130661.
  110. Rajendrachari S, Taslimi P, Karaoglanli AC, Uzun O, Alp E, et al. (2021) Photocatalytic degradation of Rhodamine B dye in wastewater and enzymatic inhibition study using cauliflower shaped ZnO nanoparticles synthesized by a novel one-pot green synthesis method. Arabian Journal of Chemistry 14: 103180.
  111. Khan WZ, Najeeb I, Ishtiaque S, Jabeen S (2016) Photodegradation of real pharmaceutical wastewater with titanium dioxide, zinc oxide, and hydrogen peroxide during UV treatment. IOSR Journal of Engineering 6: 36-46.
  112. Domingues FS, de Souza Freitas TKF, de Almeida CA, de Souza RP, Ambrosio E, et al. (2019) Hydrogen peroxide-assisted photocatalytic degradation of textile wastewater using titanium dioxide and zinc oxide. Environmental Technology 40: 1223-1232. [crossref]
  113. Li X, Wang J, Zhang J, Zhao C, Wu Y, et al. (2022) Cadmium sulfide modified zinc oxide heterojunction harvesting ultrasonic mechanical energy for efficient decomposition of dye wastewater. Journal of Colloid and Interface Science 607(1), 412-422. [crossref]
  114. El Bekkali C, Labrag J, Oulguidoum A, Chamkhi I, Laghzizil A, et al. (2022) Porous ZnO/hydroxyapatite nanomaterials with effective photocatalytic and antibacterial activities for the degradation of antibiotics. Nanotechnology for Environmental Engineering 7: 1.
  115. Reddy BS, Maurya AK, Narayana PL, Pasha SKK, Reddy MR, et al. (2022) Knowledge extraction of sonophotocatalytic treatment for acid blue 113 dye removal by artificial neural networks. Environmental Research, 204: 112359. [crossref]
  116. Banerjee P, Das D, Mitra P, Sinha M, Dey S, et al. (2014) Solar photocatalytic treatment of wastewater with zinc oxide nanoparticles and its ecotoxicological impact on Channa punctatus-a freshwater fish. Journal of Materials and Environmental Science 5: 1206-1213.
  117. Attarilar S, Yang J, Ebrahimi M, Wang Q, Liu J, et al. (2020) The toxicity phenomenon and the related occurrence in metal and metal oxide nanoparticles: a brief review from the biomedical perspective. Frontiers in Bioengineering and Biotechnology, 8: 822. [crossref]
  118. Falfushynska H, Sokolova I, Stoika R (2022) Uptake, biodistribution, and mechanisms of toxicity of metal-containing nanoparticles in aquatic invertebrates and vertebrates. In Biomedical Nanomaterials,
  119. Daraei H, Toolabian K, Thompson I, Qiu G (2022) Biotoxicity evaluation of zinc oxide nanoparticles on bacterial performance of activated sludge at COD, nitrogen, and phosphorus reduction. Frontiers of Environmental Science & Engineering 16: 19.
  120. Venkatasubbu GD, Baskar R, Anusuya T, Seshan CA, Chelliah R (2016) Toxicity mechanism of titanium dioxide and zinc oxide nanoparticles against food pathogens. Colloids and Surfaces B: Biointerfaces 148: 600-606.
  121. Rambabu K, Bharath G, Banat F, Show PL (2021) Green synthesis of zinc oxide nanoparticles using Phoenix dactylifera waste as bioreductant for effective dye degradation and antibacterial performance in wastewater treatment. Journal of Hazardous Materials 402: 123560.
  122. Suman TY, Radhi Rajasree SR, Kirubagaran R (2015) Evaluation of zinc oxide nanoparticles toxicity on marine algae chlorella vulgaris through flow cytometric, cytotoxicity and oxidative stress analysis. Ecotoxicology and Environmental Safety 113: 23-30.
  123. Tatagar AM, Moodi JI, Abbar JC, Phaniband MA (2022) Photocatalytic activity and anti-microbial application of synthesized zinc oxide nanoparticles towards remediation of hospital wastewater. Materials Today: Proceedings 49: 699-702.
  124. Nazir A, Akbar A, Baghdad HB, ur Rehman S, Al-Abbad E, et al. (2021) Zinc oxide nanoparticles fabrication using Eriobotrya japonica leaves extract: photocatalytic performance and antibacterial activity evaluation. Arabian Journal of Chemistry 14: 103251.
  125. Prakash MG, Chung IM (2016) Determination of zinc oxide nanoparticles toxicity in root growth in wheat seedlings. Acta Biologica Hungarica 67: 286-296. [crossref]
  126. Chupani L, Niksirat H, Velíšek J, Stará A, Hradilová S, et al. (2018) Chronic dietary toxicity of zinc oxide nanoparticles in common carp (Cyprinus carpio L.): tissue accumulation and physiological responses. Ecotoxicology and Environmental Safety, 147: 110-116. [crossref]
  127. Nazarizadeh A, Asri-Rezaie S (2016) Comparative study of antidiabetic activity and oxidative stress induced by zinc oxide nanoparticles and zinc sulfate in diabetic rats. AAPS PharmSciTech 17: 834-843. [crossref]
  128. Heng BC, Zhao X, Xiong S, Ng KW, Boey FYC, et al. (2010) Toxicity of zinc oxide nanoparticles on human bronchial epithelial cells is accentuated by oxidative stress. Food and Chemical Toxicology 48: 1762-1766.
  129. Khan M, Naqvi AH, Ahmad M. (2015) Comparative study of the cytotoxic and genotoxic potentials of zinc oxide and titanium dioxide nanoparticles. Toxicology Reports 2: 765-774.
  130. Premanathan M, Karthikeyan K, Jeyasubramanian K, Manivannan G (2011) Selective toxicity of ZnO nanoparticles toward Gram-positive bacteria and cancer cells by apoptosis through lipid peroxidation. Nanomedicine: Nanotechnology, Biology and Medicine, 7: 184-192.
  131. Abbasalipourkabir R, Moradi H, Zarei S, Asadi S, Salehzadeh A, et al. (2015) Toxicity of zinc oxide nanoparticles on adult male Wistar rats. Food and Chemical Toxicology 84: 154-160.
  132. Ghazi S, Diab AM, Khalafalla MM (2022) Synergistic effects of selenium and zinc oxide nanoparticles on growth performance, hemato-biochemical profile, immune and oxidative stress responses, and intestinal morphometry of Nile tilapia. Biological Trace Element Research 200: 364-374.
  133. Salam A, Khan AR, Li Liu, Yang S, Azhar W, et al. (2022) Seed priming with zinc oxide nanoparticles downplayed ultrastructural damage and improved photosynthetic apparatus in maize under cobalt stress. Journal of Hazardous Materials 423: 127021.
  134. Yazhiniprabha M, Gopi N, Mahboob S, Al-Ghanim KA, Al-Misned F, et al. (2022) The dietary supplementation of zinc oxide and selenium nanoparticles enhances the immune response in freshwater fish Oreochromis mossambicus against aquatic pathogen Aeromonas hydrophila. Journal of Trace Elements in Medicine and Biology 69: 126878.
  135. Bao S, Xiang D, Xue L, Xian B, Tang W, et al. (2022) Pristine and sulfidized ZnO nanoparticles alter microbial community structure and nitrogen cycling in freshwater lakes. Environmental Pollution 294: 118661.
  136. Din MI, Rani A, Hussain Z, Khalid R, Aihetasham A, et al. (2021) Biofabrication of size-controlled ZnO nanoparticles using various capping agents and their cytotoxic and antitermite activity. International Journal of Environmental Analytical Chemistry 101: 821-837.
  137. Hazzazi F, Young A, O’Loughlin C, Daniels-Race T (2021) Fabrication of zinc oxide nanoparticles deposited on 3-aminopropyltriethoxysilane-treated silicon substrates by an optimized voltage-controlled electrophoretic deposition and their application as fluorescence-based sensors. Chemosensors 9: 5.
  138. Soundharraj P, Dhinasekaran D, Rajendran AR, Prakasarao A, Ganesan S (2021) N-Doped zinc oxide as an effective fluorescence sensor for urea detection. New Journal of Chemistry 45: 6080-6090.
  139. Swaminathan N, Sharma N, Nerthigan Y, Wu HF (2021) Self-assembled diphenylalanine-zinc oxide hybrid nanostructures as a highly selective luminescent biosensor for trypsin detection. Applied Surface Science 554: 149600.
  140. Cao J, Zhai Y, Tang W, Guo X, Wen Y, et al. (2021) ZnO tips dotted with Au nanoparticles — advanced SERS determination of trace nicotine. Biosensors 11: 465.
  141. Wang Y, Zhu G, Li M, Singh R, Marques C, et al. (2021) IEEE Transactions on NanoBioscience 20: 377-384.
  142. Barman U, Goswami N, Ghosh SS, Paily RP (2021) Fabrication of glutathione-S-transferase-ZnO nanoconjugate ensemble FET device for detection of glutathione. IEEE Transactions on Electron Devices 68: 1242-1249.
  143. Nadaroglu H, Alayli GA (2020) Highly sensitive glucose sensor based on ZnO nanoparticles as a biomimetic enzyme. Bioscience Research 17: 775-785.
  144. Faradillaa P, Setiyanto H, Manurung RV, Saraswaty V (2022) Electrochemical sensor based on screen printed carbon electrode-zinc oxide nano particles/molecularly imprinted-polymer for detection of sodium dodecyl sulfate. RSC Advances 12: 743-752.
  145. Thivina V, Hashim U, Gopinath SCB, Ayoib A, Nordin NKS, et al. (2019) Distinct detection of Ganoderma boninense on metal oxides-gold nanoparticle composite deposited interdigitated electrode DNA sensor. Journal of Physics: Conference Series 012050.
  146. Gugoasa LAD, Negut CC, Stefanov C (2021) Electrochemical applications of inorganic material-doped quantum dots. Electroanalytical Applications of Quantum Dot-Based Biosensors 12: 395-425.
  147. Kulkarni MB, Enaganti PK, Amreen K, Goel S (2021) Integrated temperature controlling platform to synthesize ZnO nanoparticles and its deposition on Al foil for biosensing. IEEE Sensors Journal 21: 9538-9545.
  148. Ji D, Low SS, Zhang D, Liu L, Lu Y, et al. (2022) Smartphone-Based Electrochemical System for Biosensors and Biodetection. In: Ossandon MR, Baker H, Rasooly A. (eds) Biomedical Engineering Technologies. Methods in Molecular Biology, 2393: 493-514.
  149. García-Salinas F, Vázquez-Durán A, Yáñez-Limón JM (2021) Comparative study of Al-doped ZnO films deposited by sol-gel and by sputtering using a sintered target from ZnO nanoparticles synthesized by sol-gel. Boletín de la Sociedad Española de Cerámica y Vidrio 62: 134-144.
  150. Tunca K, Öztürk F, Erden P (2021) A Comparison of four different electrode matrices on the performance of amperometric hydrogen peroxide biosensors. Electroanalysis 34: 1092-1102.
  151. Rauf S, Mani V, Ait A, Saravanan L, Tutku Y, et al. (2021) Binary transition metal oxide modified laser-scribed graphene electrochemical aptasensor for the accurate and sensitive screening of acute myocardial infarction. Electrochimica Acta 386: 138489.
  152. Naz S, Nisar A, Qian L, Hussain S, Karim S, et al. (2021) Graphene oxide functionalized with silver nanoparticles and ZnO synergic nanocomposite as an efficient electrochemical sensor for diclofenac sodium. Nano 16: 2150139.
  153. Zhang W, Sharma G, Kumar A, Shekh MI, Stadler FJ. (2021) Fabrication and characterization of Ni/Ag/Zn trimetal oxide nanocomposites and its application in dopamine sensing. Materials Today Communications 29: 102726.
  154. Gu M, Xiao H, Wei S, Chen Z, Cao L (2021) A portable and sensitive dopamine sensor based on Au nanoparticles functionalized ZnO-rGO nanocomposites modified screen-printed electrode.
  155. Nagal V, Kumar V, Khan M, Alomar SY, Tripathy N, et al. (2021) A highly sensitive uric acid biosensor based on vertically arranged ZnO nanorods on a ZnO nanoparticle-seeded electrode. New Journal of Chemistry 45: 18863-18870.
  156. Chokkareddy R, Redhi GG, Thangavel K (2021) Cytochrome c/multi-walled carbon nanotubes modified glassy carbon electrode for the detection of streptomycin in pharmaceutical samples. Analytical Sciences 37: 1265-1273.
  157. Chauhan N, Balayan S, Gupta S, Singh J, Jain U (2021) Enzyme-based sensing on nanohybrid film coated over FTO electrode for highly sensitive detection of antibiotics. Bioprocess and Biosystems Engineering 44: 2469-2479.
  158. Almog R, Shashar E, Sverdlov Y, Shacham-Diamand Y (2021) Decorating metal oxide nanostructures with noble metal nanoparticles for bio-sensing applications. ECS Meeting Abstracts 01: 1424.
  159. de J. Godoi MS, Faria AM, Mazon T (2020) Síntese de estruturas de carbono a partir de biomassa de mandioca fibra e para aplicação em biossensores. I Jornada de Iniciação Científica do CTI Renato Archer.
  160. Ahmad I, Ahmad A, Tabassum H, Kuddus M (2017) Applications of nanoparticles in the treatment of wastewater. In L.M.T. Martínez et al. (eds.), Handbook of Ecomaterials 2017.
  161. Andrade-Guel M, Cabello-Alvarado C, Cano-Salaza L, Ávila-Orta C, Cruz V (2023) Recent Developments in Wastewater Treatments.
  162. Bora T, Dutta J (2014) Applications of nanotechnology in wastewater treatment-a review. Journal of Nanoscience and Nanotechnology 14: 613-626. [crossref]
  163. Gordano A (2024) Chapter 6-Hybrid inorganic membranes. Editors: A. Basile, F. Lipnizki, M.R. Rahimpour, V. Piemonte. Current Trends and Future Developments on Bio-Membranes 131-174.
  164. Yaqoob AA, Parveen T, Umar K, Mohamad Ibrahim MN (2020) Role of nanomaterials in the treatment of wastewater: a review. Water 12: 495.
  165. Jiang M, Qi Y, Liu H, Chen Y (2018) The role of nanomaterials and nanotechnologies in wastewater treatment: a bibliometric analysis. Nanoscale Research Letters 13: 233.
  166. Behera A (2022) Self-cleaning materials. Advanced Materials.
  167. Hunt E. (2019) Zinc-based additives for biofouling and MIC protection: Fabrication method for long-term efficacy. Master’s thesis. Department of Engineering & Computer Science, West Texas A&M University.
  168. Eliasson J (2015) The rising pressure of global water shortages. Nature 517: 6.
  169. Schaep J, Vandecasteele C (2001) Evaluating the charge of nanofiltration membranes, Journal of Membrane Science 188: 129-136.
  170. Zaharescu T, Lungulescu EM (2016) Weathering degradation of polymers. In: Rosu D, Visakh P. M. (eds) Photochemical Behavior of Multicomponent Polymeric-based Materials. Advanced Structured Materials, 26.
  171. Chong MN, Jin BC, Chow WK, Saint C (2010) Recent developments in photocatalytic water treatment technology: a review. Water Research 44: 2997-3027.
  172. Pendergast MM, Hoek EMV (2011) A review of water treatment membrane nanotechnologies. Energy & Environmental Science 4: 1946-1971.
  173. Strathmann H (1981) Membrane separation processes. Journal of Membrane Science 9: 121-189.
  174. Baker RW (2002) Future directions of membrane gas separation technology. Industrial & Engineering Chemistry Research 41: 1393-1411.
  175. Padaki M, Surya MR, Abdullah MS, Misdan N, Moslehyani A, et al. (2015) Membrane technology enhancement in oil-water separation-a review. Desalination 357: 197-207.
  176. Ang WL, Mohammad AW, Hilal N, Leo CP (2015) A review on the applicability of integrated/hybrid membrane processes in water treatment and desalination plants. Desalination, 363: 2-18.
  177. Subramani A, Jacangelo JG (2015) Emerging desalination technologies for water treatment: a critical review. Water Research 75: 164-187.
  178. Tran NH, Ngo HH, Urase T, Gind KYH (2015) A critical review on characterization strategies of organic matter for wastewater and water treatment processes. Bioresource Technology 193: 523-533. [crossref]
  179. Van Der Bruggen B, Vandecasteele C, Van Gestel T, Doyen W, Leysen R (2003) A review of pressure-driven membrane processes in wastewater treatment and drinking water production. Environmental Progress 22: 46-56.
  180. Anderson MA, Gieselmann MJ, Xu Q (1988) Titania and alumina ceramic membranes. Journal of Membrane Science 39: 243-258.
  181. Meng F, Chae SR, Drews A, Kraume M, Shin HS, Yang F (2009) Recent advances in membrane bioreactors: membrane fouling and membrane material. Water Research 43: 1489-1512. [crossref]
  182. Kim J, Van der Bruggen B (2010) The use of nanoparticles in polymeric and ceramic membrane structures: review of manufacturing procedures and performance improvement for water treatment. Environmental Pollution 158: 2335-2349. [crossref]
  183. Kang GD, Cao YM (2014) Application and modification of poly(vinylidene fluoride) membranes-a review. Journal of Membrane Science 463: 145-165.
  184. Lin H, Peng W, Zhang M, Chen J, Hong H, et al. (2016) A review on anaerobic membrane bioreactors: applications, membrane fouling and future perspectives. Desalination 314: 169-188.
  185. She Q, Wang R, Fane AG, Tang CY (2016) Membrane fouling in osmotically driven membrane processes: a review. Journal of Membrane Science 499: 201-233.
  186. Cuiming W, Tongwen X, Weihua Y (2003) Fundamental studies of a new hybrid (inorganic-organic) positively charged membrane: membrane preparation and characterizations. Journal of Membrane Science 216: 269-278.
  187. Wu C, Xu T, Yang W (2003) A new inorganic-organic negatively charged membrane: membrane preparation and characterizations. Journal of Membrane Science 224: 117-125.
  188. Zunita M, Makertihartha IGBN, Saputra FA, Syaifi YS, Wenten IG (2018) Metal oxide based antibacterial membrane. IOP Conference Series: Materials Science and Engineering 395: 012021.
  189. Saif AA (2018) Engineering Nanocomposite Membranes: Fabrication, Modification and Application. Doctoral Thesis. Chemical Engineering.
  190. Opoku F, Kiarii EM, Govender PP, MA. Mamo MA (2017) Metal oxide polymer nanocomposites in water treatments. Descriptive Inorganic Chemistry Researches of Metal Compounds.
  191. Taiba N, Tayyiba D (2021) The role of some important metal oxide nanoparticles for wastewater and antibacterial applications: a review. Environmental Chemistry and Ecotoxicology 3: 59-75.
  192. Kumar S, Ye F, Dobretsov S, Dutta J (2021) Nanocoating is a new way for biofouling prevention. Frontiers in Nanotechnology 3: 2673-3013.
  193. Sadamichi M, Takami T, Stewart EB, Sumio I, Wataru K, et al. (2004) Physics of Transition Metal Oxides. Springer Science & Business Media, Technology & Engineering,
  194. Meenakshi SSAS, Alagumalai N, Dipak R.||(2019) Tailored polymer nanocomposite membranes based on carbon, metal oxide and silicon nanomaterials: a review. Journal of Materials Chemistry A, 7: 8723-8745.
  195. Ghosh S, Malloum A, Igwegbe CA, Ighalo JO, Ahmadi Set al. (2022) New generation adsorbents for the removal of fluoride from water and wastewater: a review. Journal of Molecular Liquids 346: 118257.
  196. Ye J, Gao H, Wu J, Yu R (2021) Effects of ZnO nanoparticles on flocculation and sedimentation of activated sludge in wastewater treatment process. Environmental Research 192: 110256. [crossref]
  197. Banu JR, Sharmila VG, Kannah RY, Kanimozhi R, Elfasakhany A, et al. (2022) Impact of novel deflocculant ZnO/chitosan nanocomposite film in disperser pretreatment enhancing energy efficient anaerobic digestion: parameter assessment and cost exploration. Chemosphere 286: 131835. [crossref]
  198. Shen L, Huang Z, Liu Y, Li R, Xu Y, et al. (2020) Polymeric membranes incorporated with ZnO nanoparticles for membrane fouling mitigation: a brief review. Frontiers in Chemistry 8: 224. [crossref]
  199. Taherizadeh H, Hashemifard SA, Izadpanah AA, Ismail AF (2021) Investigation of fouling of surface modified polyvinyl chloride hollow fiber membrane bioreactor via zinc oxide-nanoparticles under coagulant for municipal wastewater treatment. Journal of Environmental Chemical Engineering 9: 105835.
  200. Kusworo TD, Dalanta F, Aryanti N, Othman NH (2021) Intensifying separation and antifouling performance of PSF membrane incorporated by GO and ZnO nanoparticles for petroleum refinery wastewater treatment. Journal of Water Process Engineering 41: 102030.
  201. Ayyaru S, Dinh TTL, Ahn YH (2020) Enhanced antifouling performance of PVDF ultrafiltration membrane by blending zinc oxide with support of graphene oxide nanoparticle. Chemosphere 241: 125068.
  202. Mahlangu OT, Nackaerts R, Mamba BB, Verliefde ARD (2017) Development of hydrophilic GO-ZnO/PES membranes for treatment of pharmaceutical wastewater. Water Science & Technololgy 76: 501-514.
  203. Purushothaman M, Arvind V, Saikia K, Vaidyanathan VK (2022) Fabrication of highly permeable and anti-fouling performance of poly(ether ether sulfone) nanofiltration membranes modified with zinc oxide nanoparticles. Chemosphere 286: 131616.
  204. Cao W, Ma W, Lu T, Jiang Z, Xiong R, et al. (2022) Multifunctional nanofibrous membranes with sunlight-driven self-cleaning performance for complex oily wastewater remediation. Journal of Colloid and Interface Science 608: 164-174. [crossref]
  205. Dizge N, Gonuldas H, Ozay Y, Ates H, Ocakoglu K, et al. (2017) Synthesis and performance of antifouling and self-cleaning polyethersulfone/graphene oxide composite membrane functionalized with photoactive semiconductor catalyst. Water Science & Technology 75: 670-685. [crossref]
  206. García, Andreina, Rodríguez B, Giraldo H, Yurieth Q, et al. (2021) Copper-modified polymeric membranes for water treatment: a comprehensive preview. Membranes 11: 93. [crossref]
  207. Mohamad S, Idris M, Abdullah H, Ismail A (2013) Short review of ultrafiltration of polymer membrane as a self-cleaning and antifouling in the wastewater system. Advanced Materials Research 795: 318-323.
  208. Tae HB, Tae MT (2005) Preparation of TiO2 self-assembled polymeric nanocomposite membranes and examination of their fouling mitigation effects in a membrane bioreactor system. Journal of Membrane Science 266: 1-5.
  209. Arif Z, Sethy NK, Mishra PK, Verma B (2020) Development of eco-friendly, self-cleaning, antibacterial membrane for the elimination of chromium (VI) from tannery wastewater. International Journal of Environmental Science and Technology (Tehran) 17: 4265-4280. [crossref]
  210. Meenakshi SSAS, Alagumalai N, Dipak R (2019) Tailored polymer nanocomposite membranes based on carbon, metal oxide and silicon nanomaterials: a review. Journal of Materials Chemistry A, 7: 8723-8745.
  211. Lavisha B, Rasmeet S, Jonita V (2020) Metal/metal oxide nanocomposite membranes for water purification. Materials Today: Proceedings 2020, 44 538-545.
  212. Rabajczyk A, Zielecka M, Cygańczuk K, Pastuszka Ł, Jurecki L (2021) Nanometals-containing polymeric membranes for purification processes. Materials (Basel, Switzerland), 14: 513.
  213. Xiaofang C, Yaoxin H, Zongli X, Huanting W (2018) Chapter 3-Materials and Design of Photocatalytic Membranes. In Current Trends and Future Developments on (Bio-) Membranes, 71-96.
  214. Khan SB, Alamry KA, Bifari EN, Asiri AM, Yasir M, et al. (2015) Assessment of antibacterial cellulose nanocomposites for water permeability and salt rejection. Journal of Industrial and Engineering Chemistry 24: 266-275.
  215. Waldman RZ (2020) Metal oxide growth on polymer surfaces and within polymer volumes: applications in novel membrane materials. Ph.D. thesis, University of Chicago, USA.
  216. Balta S, Sotto A, Luis P, Benea L, Van der Bruggen B. et al. (2012) A new outlook on membrane enhancement with nanoparticles: the alternative of ZnO. Journal of Membrane Science 389: 155-161.
  217. Zinc peroxide nanoparticles. Marcina Kasprzaka 44/52. 01-224 Warszawa, Poland.
  218. Dupont Water Solutions.
  219. Manttari M, Pihlajamaki A, Kaipainen E, Nystrom M (2002) Effect of temperature and membrane pretreatment on the filtration properties of nanofiltration membranes. Desalination 145: 81-86.
  220. Liora RT, Zohar K, Tsur Y (2008) Synthesis of stabilized nanoparticles of zinc peroxide. Chemical Engineering Journal 2008, 136: 425-429.
  221. Hsu CC, Wu NL (2005) Synthesis and photocatalytic activity of ZnO/ZnO2 Journal of Photochemistry and Photobiology A: Chemistry 172: 269-274.
  222. Halfar J, Brožová K, Čabanová K, Heviánková S, Kašpárková A, et al. (2021) Disparities in methods used to determine microplastics in the aquatic environment: a review of legislation, sampling process and instrumental analysis. International Journal of Environmental Research and Public Health 18: 7608. [crossref]
  223. Gaw S, Glover CN (2016) A case of contagious toxicity? Isoprostanes as potential emerging contaminants of concern. Science of The Total Environment 560-561: 295-298.
  224. Ofrydopoulou A, Nannou C, Evgenidou E, Lambropoulou D (2021) Sample preparation optimization by central composite design for multi class determination of 172 emerging contaminants in wastewaters and tap water using liquid chromatography high-resolution mass spectrometry. Journal of Chromatography A 1652, 462369. [crossref]
  225. Bowers I, Subedi B (2021) Isoprostanes in wastewater as biomarkers of oxidative stress during COVID-19 pandemic. Chemosphere 271: 129489. [crossref]
  226. Abdullah FH, Abu Bakar NHH, Abu Bakar M (2022) Current advancements on the fabrication, modification, and industrial application of zinc oxide as photocatalyst in the removal of organic and inorganic contaminants in aquatic systems. Journal of Hazardous Materials 424: 127416.
  227. Liu X, Yu X, Sha L, Wang Y, Zhou Z, et al. (2021) The preparation of black titanium oxide nanoarray via coking fluorinated wastewater and application on coking wastewater treatment. Chemosphere 270: 128609.
  228. Sheikh M, Pazirofteh M, Dehghani M, Asghari M, Rezakazemi M, et al. (2020) Application of ZnO nanostructures in ceramic and polymeric membranes for water and wastewater technologies: a review. Chemical Engineering Journal 391: 123475.
  229. Kalaivizhi R, Danagody B, Yokesh A (2022) ACs@ZnO incorporated with a PSF/PU polymer membrane for dye removal. Materials Advances 3: 8534-8543.
  230. van den Berg T, Ulbricht M (2020) Polymer nanocomposite ultrafiltration membranes: the influence of polymeric additive, dispersion quality and particle modification on the integration of zinc oxide nanoparticles into polyvinylidene difluoride membranes. Membranes 10: 197. [crossref]
  231. Kim HG, Kim R, Kim S, Choi C, Kim B. et al. (2018) Propylene carbonate-derived size modulation of water cluster in pore-filled Nafion/polypropylene composite membrane for the use in vanadium redox flow batteries. Journal of Industrial and Engineering Chemistry 2 60: 401-406.
  232. Shabbir S, Kulyar MF, Bhutta ZA, Boruah P, Asif M (2021) Toxicological consequences of titanium dioxide nanoparticles and their jeopardy to human population. BioNanoScience 11: 621-632. [crossref]
  233. Ghaemi N, Madaeni SS, Daraei P, Rajabi H, Zinadini S, et al. (2015) Polyethersulfone membrane enhanced with iron oxide nanoparticles for copper removal from water: Application of new functionalized Fe 3O 4 Chemical Engineering Journal 263: 101-112.
  234. Zhang A, Zhang Y, Pan G, Xu J, Yan H, et al. (2017) In situ formation of copper nanoparticles in carboxylated chitosan layer: Preparation and characterization of surface modified TFC membrane with protein fouling resistance and long-lasting antibacterial properties. Separation & Purification Technology 176: 164-172.
  235. Liu X, Foo LX, Li Ye, Lee JY, Cao B, et al. (2016) Fabrication and characterization of nanocomposite pressure retarded osmosis membranes with excellent anti-biofouling property and enhanced water permeability. Desalination 389: 137-148.
  236. Goh PS, Matsuura T, Ismail AF, Hilal N (2016) Recent trends in membranes and membrane processes for desalination. Desalination 391: 43-60.
  237. Thanigaivelan A, Mariam O, Rambabu K, Abdul H, Nirmala G, et al. (2022) Surface-engineered polyethersulfone membranes with inherent Fe-Mn bimetallic oxides for improved permeability and antifouling capability. Environmental Research 204: 112390.
  238. Arumugham T, Ouda M, Krishnamoorthy R, Hai A, Gnanasundaram N, et al. (2021) Surface-engineered polyethersulfone membranes with inherent Fe-Mn bimetallic oxides for improved permeability and antifouling capability. Environmental Research 204: 112390. [crossref]
  239. Nagarajan M, Maadurshni GB, Tharani GK, Udhayakumar I, Kumar G et al. (2022) Exposure to zinc oxide nanoparticles induces cardiovascular toxicity and exacerbates pathogenesis-role of oxidative stress and MAPK signaling. Chemico-Biological Interactions 351: 109719. [crossref]
  240. Brar SK, Verma M, Tyagi RD, Surampalli RY (2010) Engineered nanoparticles in wastewater and wastewater sludge-evidence and impacts. Waste Management 30: 504-520. [crossref]
  241. Sadik OA, Du N, Yazgan I, Okello V (2014) Chapter 6-Nanostructured Membranes for Water Purification, Editors: A. Street, R Sustich, Jeremiah Duncan, Nora Savage, In Micro and Nano Technologies, Nanotechnology Applications for Clean Water, William Andrew Publishing, 95-108.
  242. Ergönül MB, Nassouhi D, Çelik M, Atasağun S (2021) A comparison of the removal efficiencies of Myriophyllum spicatum L. for zinc oxide nanoparticles in different media: a microcosm approach. Environmental Science and Pollution Research 28: 8556-8568. [crossref]
  243. Afonso-Olivares C, Sosa-Ferrera Z, Santana-Rodríguez JJ (2017) Occurrence and environmental impact of pharmaceutical residues from conventional and natural wastewater treatment plants in Gran Canaria (Spain) Science of The Total Environment 599-600: 934-943. [crossref]
  244. Ryu Y, Gracia-Lor E, Bade R, Baz-Lomba JA, Bramness JG, et al. (2016) Increased levels of the oxidative stress biomarker 8-iso-prostaglandin F2α in wastewater associated with tobacco use. Scientific Reports 6: 39055.
  245. Ajibola AS, Amoniyan OA, Ekoja FO, Ajibola FO (2021) QuEChERS approach for the analysis of three fluoroquinolone antibiotics in wastewater: concentration profiles and ecological risk in two Nigerian hospital wastewater treatment plants. Archives of Environmental Contamination and Toxicology 80: 389-401. [crossref]
  246. Sims N, Rice J, Kasprzyk-Hordern B (2019) An ultra-high-performance liquid chromatography tandem mass spectrometry method for oxidative stress biomarker analysis in wastewater. Analytical and Bioanalytical Chemistry 411: 2261-2271.
  247. Azodi M, Ghoshal S, Stephan C (2015) Measurement and analysis of silver nanoparticles in wastewaters with single particle ICP-MS. PerkinElmer Application Note
  248. Cervantes-Avilés P, Keller AA (2021) Incidence of metal-based nanoparticles in the conventional wastewater treatment process. Water Research 189: 116603.
  249. Ryu Y, Reid MJ, Thomas KV (2015) Liquid chromatography-high resolution mass spectrometry with immunoaffinity clean-up for the determination of the oxidative stress biomarker 8-iso-prostaglandin F2alpha in wastewater. Journal of Chromatography A 1409: 146-151.
  250. Kovacs-Wilks K (2016) Agents of unknown concern: isoprostanes as potential emerging contaminants. M.Sc. thesis, University of Canterbury, 2016.
  251. Boogaerts T, Quireyns M, Covaci A, De Loof H, van Nuijs ALN (2021) Analytical method for the simultaneous determination of a broad range of opioids in influent wastewater: Optimization, validation and applicability to monitor consumption patterns. Talanta 232: 122443. [crossref]
  252. Guironnet A, Sanchez-Cid C, Vogel TM, Wiest L, Vulliet E (2021) Aminoglycosides analysis optimization using ion pairing liquid chromatography coupled to tandem mass spectrometry and application on wastewater samples. Journal of Chromatography A 1651: 462133.
  253. Mao K, Yang Z, Zhang H, Li X, Cooper JM (2021) Paper-based nanosensors to evaluate community-wide illicit drug use for wastewater-based epidemiology. Water Research 189: 116559. [crossref]
  254. Lee J, Choi YJ, Jeong J, Chae KJ (2021) Eye-glass polishing wastewater as significant microplastic source: microplastic identification and quantification. Journal of Hazardous Materials 403: 123991.
  255. Yu C, Kim S, Jang M, Park CM, Yoon Y (2022) Occurrence and removal of engineered nanoparticles in drinking water treatment and wastewater treatment processes: a review. Environmental Engineering Research 10: 134-152.
  256. Mubarak SM (2022) Nanotechnology for air remediation. In Research Anthology on Emerging Techniques in Environmental Remediation. IGI Global.
  257. Kang CS, Evans EA, Chase GG (2022) Metal oxide nanofiber for air remediation via filtration, catalysis, and photocatalysis. Elsevier, 191-211.
  258. Ding S, Li C, Bian C, Zhang J, Xu Y et al. (2022) Application of low-cost MFe2O4 (M = Cu, Mn, and Zn) spinels in low-temperature selective catalytic reduction of nitrogen oxide. Journal of Cleaner Production, 330: 129825.
  259. Santhosh G, Nayaka GP. Nanoparticles in construction industry and their Toxicity. In: Ecological and Health Effects of Building Materials, J.A. Malik, S. Marathe (eds) Springer.
  260. Gupta AD, Patil SZ (2022) Potential environmental impacts of nanoparticles used in construction industry. In Ecological and Health Effects of Building Materials, J.A. Malik, S. Marathe (eds) Springer, Cham.
  261. Srivastava S, Bhargava A (2022) Toxicity aspects of biologically synthesized nanoparticles. In: Green Nanoparticles: The Future of Nanobiotechnology. Springer, Singapore.
  262. Shet VB, Navalgund L, Joshi K, Yumnam S (2022) Application of nanoparticles in construction industries and their toxicity. In Ecological and Health Effects of Building Materials.
  263. American Welding Society. Metal fume fever. Safety and Health Fact Sheet No. 25. 2014.
  264. Magnano GC, Marussi G, Pavoni E, Adami G, Filon FL, et al. (2022) Percutaneous metals absorption following exposure to road dust powder. Environmental Pollution 292: 118353.
  265. Chavali MS, Nikolova MP (2019) Metal oxide nanoparticles and their applications in nanotechnology. SN Applied Sciences 1: 607.
  266. Saleem H, Zaidi SJ, Ismail AF, Goh PS (2022) Advances of nanomaterials for air pollution remediation and their impacts on the environment. Chemosphere 287: 132083.
  267. Nagar A, Kumar A, Tyagi U, Dhasmana H, Majeed Khan MA, et al. (2022) Ultrafast, trace-level detection of NH3 gas at room temperature using hexagonal-shaped ZnO nanoparticles grown by novel green synthesis technique. Physica B: Condensed Matter 626: 413595.
  268. Dey A. (2018) Semiconductor metal oxide gas sensors: a review. Materials Science and Engineering B 229: 206-217.
  269. Ageel HK, Harrad S, Abou-Elwafa Abdallah M (2022) Occurrence, human exposure, and risk of microplastics in the indoor environment. Environmental Science: Processes & Impacts 24: 17-31.

AI-eEmpowered Problem-Solving for Civic Issues: Considering New York in 2024

DOI: 10.31038/PEP.2024412

Abstract

Idea Coach, an AI-empowered program, was instructed to provide suggestions and innovations for dealing with eight problems plaguing the state of New York. These problems reflect different areas of civic distress (e.g., crime-plagued streets), economics (e.g., flight of the middle class from NY), and so forth. Idea Coach was often able to deliver meaningful suggestions about how specifically to ameliorate the specific problem, and recommend intuitively meaningful innovations to consider for the future. This exercise suggests the promise of using AI in the form of Chat GPT3.5, as a way to create a quick overview of problems and their solutions. The paper highlights the benefit of AI as providing an education about a problem, with the education accomplished quickly (a matter of minutes), inexpensively (low cost for the use of the platform), and iteratively (many alternatives proposed for consideration across successive and easy repetitions of the exercise).

Introduction

As the century progresses, or in truth as history progresses, often the bright hope for the future turns into a drab, unpleasant, and of course disappointing present, and over time that present becomes a past to mourn. As poet John Greenleaf Whittier wrote so touching in ‘Maude Muller’, ‘of all sad words of tongue and pen, the saddest are it might have been.

Government is presumed to be at the service of people. In free countries people are presumed to elect those who can give them a better life. And yet, repeatedly we are treated to noble visions and hopes turned into shattered dreams. Is it possible to create lists of things to improve society without having to spend extraordinary amounts of money on experts, consultants, consumer research ranging from qualitative groups (in-depth interviews, focus groups) to massive surveys, done quickly, over the internet, but covering little and all too often over-analyzed?

The introduction of the Internet in the 1990’s was hailed as a new way for people to connect with each other. Solving civic problems was part of the hope. Instead of the expensive interactions between people and the slow-moving efforts, it was often thought that this ‘new wave of communicating’ would generate a better society. People could surface issues better, with the presumption that once enough people and especially ‘experts’ heard about the issue, thought about, discussed ramifications and solutions, that somehow the magic of many minds working together would guide a solution to the problem, and all would be well.

The literature of suggested problem solving for civic problems is enormous. One need only look at Google Scholar to get a sense of the vast literature. Figure 1 shows a screen shot taken January 15, 2024. The topic is ‘solving social problems.’ Google Scholar emerges with more than six million hits (6,230,000 to be exact).

FIG 1

Figure 1: Google Scholar results from searching for papers on ‘solving social problems’.

The number of Google Scholar ‘hits’ drops down by more than half when the topic is more specific, ‘using AI to suggest solutions to social problems.’ The number is 2,810,000 and a longer search time, viz., from 0.10 seconds to 0.22 seconds. Figure 2 shows this screen shot.

FIG 2

Figure 2: Google Scholar results after ‘using AI to suggest solutions to social problems.’

Many of the papers talk about the promise of AI, and in turn the way AI should be considered, used, and interpreted. The paper in the literature emerge from the careful consideration of a new technology applied to the problem [1,2]. Some of the literature also pertains to the intersection of AI and societal goals, such as those put forward by the United Nations, for the year 2030 [3,4].

This paper moves from a general consideration of AI and social problems to an exploration of specifics, using the AI-empowered Idea Coach found in SaaS (Socrates as a Service, and in Mind Genomics. Both systems use AI in the form of Chat GPT3.5 [5]. They can be accessed directly: Mind Genomics a: www.bimileap.com Socrates as a Service at https://socratesasaservice.com/u/dashboard.

The original reason for the incorporation of AI into these two platforms comes from the frustrations encountered by researchers when investigating a topic using Mind Genomics. Mind Genomics focused on the creation of a set of questions for a topic, and then for each question required the user to create a set of four answers (elements). These ‘elements’ would then be mixed together to create small, easy to read combinations, vignettes. The ratings assigned to these vignettes would be then deconstructed into the contribution of the individual elements as a driver of the vignette. The benefit of this seemingly circuitous approach, replacing simple questions, is that the Mind Genomics projects focused on the ‘granular,’ where reality manifests itself. It was impossible to ‘game’ a Mind Genomics study. The results showed how people made decisions with real-world issues, rather than rating abstract concepts as is often the case with surveys focusing on a topic or focusing on a recent personal experience [6,7].

Within this carefully crafted system the key weakness was that many users felt intimidated by having to ask meaningful questions. To this end, AI was introduced as a guide, appearing to the user to be a seamless add-on to the Mind Genomics process, and given the name ‘Idea Coach’ to encourage the user. Figure 3 shows the initial format of the Mind Genomics effort. Panel A shows the request that the user provide four questions. It was here that the user became discouraged. Panel B shows the rectangle wherein the user writes a squib to describe the need to the AI-empowered Idea Coach, in this case a request to provide questions relevant to the issue of crime in the streets. Panel C shows the output form Idea Coach, comprising four of the 15 questions returned by the Idea Coach.

FIG 3

Figure 3: The sequence of screens showing the request for four questions (Panel A), the use of Idea Coach (Panel B), the output from an iteration of Idea Coach (Panel C), and the request for four answers to Question 1 of 4.

The approach shown in Figure 3 has been used for several two years, as of this writing. The introduction of the Idea Coach substantially enhanced the usability of the Mind Genomics paradigm allowing the researcher to develop questions and answers rapidly. The next steps for Mind Genomics studies were to combine the answers from the four questions into small, easy to read vignettes, combinations of answers (aka element). The vignettes comprised a minimum of two elements, and a maximum of four elements, the vignettes created according to an underlying experimental design. No vignette ever contained two or more elements or answers from a question, but often a vignette failed to contain an element from one, or even from two different questions.

The foregoing approach for Mind Genomics in general, and for Idea Coach in particular, focused on simplifying the creation of vignettes. What was not apparent at the point was the possibility that the AI embedded in Idea Coach could do far more, when properly instructed.

It is the extension of Idea Coach into new areas, specifically into new types of requests that one can make for the AI, and the presentation of the results for this initial foray beyond the simplistic question/answer paradigm.

Method

The approach here uses Idea Coach and thus AI is a new way, doing so in the spirit of Mind Genomics, but pushing the AI to provide all the information when the problem is described. That is, the squib describing the problem also requests alternative solutions, and reasons for the solutions. The squib is far more detailed than the original squibs written to generate questions, and then subsequent squibs which generated alternative sets of answers from the squib.

The paper begins with the first advance, viz., requesting questions and answers to be provided at the outset through Idea Coach. Table 1 shows a slightly expanded squib provided to Idea Coach, and thus constituting the instructions to the embedded AI. The squib comprises several logical sections, as follows:

  1. The general introduction. Here the introduction talks about New York, specifying the market, and the issue. There is nothing here which can guide Idea Coach about solving any problem.
  2. Instructions to Idea Coach to make sure that the results are specific, and the solutions are realistic, i.e., one can actually act on them.
  3. The statemen of the problem, in modest detail, providing some specification
  4. The request to AI to provide solutions to a specified problem.

It is important to keep in mind that this modification to the use of Idea Coach does not require two squibs, the first being the request for questions, and the second being the request for answers to specific questions. Figure 3 shows that traditional two-step process. Table 1 attempts to collapse the process.

Table 1: The revised process for Idea Coach, attempting to collapse the process into one step to give to Idea Coach.

TAB 1

The remainder of this paper comprises a demonstration of the solutions and innovation for each of xxx problems plaguing New York. When reading the tables one should keep in mind that the problems presented to the AI were very general. Each particular table was created with the same instructions. Only the problem differed The answers, however, were requested to be realistic. The AI was requested to give 10 solutions, a request that was sometimes honored, and sometimes not honored.

The Idea Coach was developed to be iterative (see Figure 3, bottom of Panel C). That is, the user could revise the request to Idea Coach, changing the nature of the problem, the number of requested solutions, and so forth. It is this ‘iterative’ nature of Idea Coach which leads to the format of Table 1. With a simple set of keystrokes the user can re-run the request to create a new set of solutions, or the user can modify the problem, e.g., from street crime to education, and immediately receive an additional set of solutions. Each iteration takes approximately 15-30 seconds, so that a set of 10 problems can be addressed in about five minutes.

After the initial solutions were presented to the user, and after the Mind Genomics program was closed by having the user log-off, a second module of the Mind Genomics platform went to work on the question and the answers, to provide a summarization. The summarization provided this additional information, shown in Table 2. This AI summarization was emailed to the user about 20 minutes after the user logged-off. The result is that within 30 minutes or so, the enterprising user of Idea Coach can investigate ten issues, or one issue ten times, receive results from AI, and then at the end of the process receive a summarized, deeply re-analyzed booklet, with each iteration deeply explored anew by AI.

Table 2: The summarization material provided in the Idea Book, provided to the user after the user logged off from the project.

TAB 2

Table 3 shows the first iteration to deal with reducing street crime. Table 4 shows the first iteration to improve education in New York State. Each table is divided into two parts, solutions and innovations, respectively.

Table 3: Solutions to reduce street crime, provided by Idea Coach. The top half of the table shows what is provided at the time of use. Both the top and bottom halves of the table are provided in the Idea Book, sent to the user.

TAB 3

Table 4: Solutions to stop the decline in educational performance in public schools in New York State, provided by Idea Coach. The top half of the table shows what is provided at the time of use. Both the top and bottom halves of the table are provided in the Idea Book, sent to the user.

TAB 4

The top part (solutions) presents the information that was returned immediately upon presenting Idea Coach with the squib. This information can be immediately scanned by the user, who can re-run the request to get more solutions, or modify the squib and then re-run it, thus changing the focus of the request to Idea Coach.

The bottom part (innovations) actually comes from the summarization of this information, provided to the user in the Idea Book . Recall that the Idea Book is send to the user about 20 minutes after the user logged-off. The embedded AI in Idea Coach reviews the solutions, and comes up a set of new suggestions, expanding the scope of the already-offered solutions. In this respect, one might say that AI is producing ‘new knowledge.’

Appendices 1-6 to this paper shows the solutions and innovations relevant to each of the remaining problems facing New York State. Appendix 7 shows an example of what the Idea Book returns to the user at post-processing. Appendix 7 presents the full Idea Book page for the second iteration dealing with reducing street crime. The sections of the page are shown in Table 2. Each iteration is separate, so Appendix 7 presents new data, albeit for the same topic of reducing street crime.

Moving from Solutions to Implementation, Assessment, and Expected Public Reaction

Tables 3 and 4 suggest that the AI embedded in Idea Coach can move beyond regurgitating information, and perhaps provide new ideas, or at least ideas that were not originally present in the request. Whether or not the innovations truly represent ‘new information’ is not relevant. What is relevant is the recognition that the AI can be ask to hypothesize about outcomes.

Tables 5 and 6 show the same topics, street crime and education, respectively, this time explored by AI in a deeper way, namely by asking AI to suggest a set of 10 solutions for each general problem. Each solution is to comprise five parts, the solution to be considered as a whole comprising those four parts. For each of the 10 solutions, Idea Coach is instructed to estimate four factors, each on its own unique scale: Effectiveness, Cost, Time, Public Reaction.

Tables 5 and 6 show that Idea Coach can do this task. There is no cautionary statement of impossibility, or that the task is beyond the program. Rather, Idea Coach and thus the embedded AI, returns dutifully with the larger solution, the four components, and then the evaluations.

The results shown by Tables 5 and 6 suggest that the incorporation of AI into the planning, using a simple platform such as Mind Genomics (www.BimiLeap.com) or Socrates as a Service (https://socratesasaservice.com/u/dashboard) present a new opportunity to systematically explore problems and their solutions, in a way which is feasible, fast, relatively complete, and perhaps enlightening and educational for those without deep experience in the topic.

Table 5: Expanded squib for Idea Coach, dealing with street crime. The squib requests 10 solutions, each with several steps, and then the evaluation of the solution on effectiveness, cost, timeline, and expected public reaction.

TAB 5(1)

TAB 5(2)

Table 6: Expanded squib for Idea Coach, dealing with street crime. The squib requests 10 solutions, each with several steps, and then the evaluation of the solution on effectiveness, cost, timeline, and expected public reaction.

TAB 6(1)

TAB 6(2)

TAB 6(3)

Discussion and Conclusions

This paper began as an effort to demonstrate to senior government officials in New York that the contribution of AI in an easy-to-use format, and even by a novice new to the issues, could be helpful. The initial efforts focused on the traditional use of Mind Genomics, namely, create questions, answers, mix the answers into vignettes, test the vignettes, and discover how people think. That has been the approach, one set up following the dictates of science (e.g., experimental psychology), and especially psychophysics), as well as one using rigorous experimental design to create the test stimuli [8] and analyze the results [9].

As in many efforts in science, that which is planned often evolves into that which ends up being discovered. The role of accidental discovery cannot be overemphasized here. No one was thinking that the Idea Coach squib should be written with a request both to list problems and list answers, and evaluations of those answers in terms of feasibility, cost, timing, and public reception. These were all steps to be taken with caution, slowly, after having studied the issue thoroughly, done one’s so-called ‘homework’, and then suggesting an educated opinion after having been immersed in the problem.

Nothing could have predicted either the initial results, nor the reactions to efforts and finally to the expansion of the request made by AI. The results shown in Tables 5 and 6, as well as in Appendices 1-6 confirm the dramatic ease with which new ideas can be quickly investigated, perhaps for themselves, or perhaps as steps prior to consumer research. Certainly, it is to be expected that researchers who have done the type of pre-work shown in Tables 5 and 6, as well as in Appendices 1-6, are likely to recognize good answers when they appear, simply because of their easy-to-obtain experience with the Mind Genomics world.

The approach presented here touches on a variety of topics, ranging from the application of Mind Genomics and Idea Coach real world issues, and the implication for philosophical issues brought up by the readable results and judgments provided by AI (Tables 5 and 6; Appendix 7). It is clear that the results suggest practical suggestions that can be tested empirically to determine the degree to which the AI appears able to prescribe solutions for problems ‘picked at random’.. More puzzling, however, is the ‘seeming capability’ of AI to judge the difficulty and the outcome of courses of actions. Perhaps the machines really do have so-called ‘tacit knowledge’, but from where would this deep knowledge come from, a knowledge which makes the answers so realistic? [10-12]. Despite these issues, however, and no matter what the deeper reality may be, demonstrations of the ability of AI to help in the formulation of policy for social issues seem destined to drive an increasing acceptance of AI as a collaborator to create a better society.

References

  1. Floridi L, Cowls J, King TC, Taddeo M (2021) How to design AI for social good: Seven essential factors. In: Floridi, L. (eds) Ethics, Governance, and Policies in Artificial Intelligence. Sci Eng Ethics. [crossref]
  2. Tomašev N, Cornebise J, Hutter F, et al (2020) AI for social good: unlocking the opportunity for positive impact. Nat Commun. [crossref]
  3. Baum SD (2021) Artificial interdisciplinarity: Artificial intelligence for research on complex societal proble Philosophy & Technology 34 (Suppl 1): 45-63.
  4. Vinuesa R, Azizpour H, Leite I, et al. (2020) The role of artificial intelligence in achieving the Sustainable Development Goals. Nat Commun. [crossref]
  5. Herbold S, Hautli-Janisz A, Heuer U, et al. (2023) A large-scale comparison of human-written versus ChatGPT-generated essays. Scientific Reports.
  6. Porretta S, Gere A, Radványi D, Moskowitz H (2019) Mind Genomics (Conjoint Analysis): The new concept research in the analysis of consumer behaviour and choice. Trends in Food Science & Technology.
  7. Moskowitz D, d Moskowitz H (2012) Conjoint analysis plus (cross category, emotions, pricing and beyond) Product Innovation Toolbox: A Field Guide to Consumer Understanding and Research 192-223.
  8. Gere A,Radvanyi D, Moskowitz H (2017) The Mind Genomics metaphor-From measuring the everyday to sequencing the mind. International Journal of Genomics and Data Mining 110.
  9. Moskowitz HR, Gofman A, Beckley J, Ashman H (2006) Founding a new science: Mind genomics. Journal of Sensory Studies 21: 266-307.
  10. Dahl T (2000) Text summarisation: From human activity to computer program. The problem of tacit knowledge. HERMES-Journal of Language and Communication in Business 25: 113-131.
  11. Holtel S (2016) Artificial intelligence creates a wicked problem for the enterprise. Procedia Computer Science 99: 171-180.
  12. Lu H, Li Y, Chen M, et al. (2018) Brain intelligence: go beyond artificial intelligence. Mobile Networks and Applications 23: 368-375.

Dealing with 21st Century Accusations of Genocide Levelled Against Israel: The Contribution of AIenhanced Mind Genomics to Debunk a Myth

DOI: 10.31038/MGSPE.2024413

Abstract

Using AI embedded in a user-friend platform (www.bimileap.com) it became possible to request new knowledge rapidly and easily about mind-sets dealing with accusations of genocide against Israel. Given only requests to identify mind-sets and suggest their beliefs and relevant communications, the AI embedded in the platform provide concrete, testable recommendations in a user-friendly form easily understood, as well as AI-summarizations of its own recommendations. The process, taking only minutes, is recommended as a new thrust for understanding conflicts, and improving the current world order.

Introduction

The tragic events of October 7, 2023, in the southern part of Israel culminated in the deaths of more than 1200+ Israelis and others attending an outdoor concert/festival. The military response of Israel against Hamas resulted in a widespread destruction of much of Gaza and the deaths of many people. The response of many students around the world was to support Gaza, and to claim that a genocide was being committed. Many university students around the world protested, wearing the black and gray keffiyehs which have come to symbolize the Palestinian fight against Israel. During this time, the increasing level of accusation reached unheard of proportions in the modern world as antisemitic tropes and canards emerged about Jews and their so-called activities. The remarkable ferocity of the accusation requires an understanding of how to deal with the hostility.

The Contribution of Mind Genomics

The approach here comes from the emerging science of Mind Genomics. Mind Genomics studies the way people make decisions about the issues of the everyday, such as what they will purchase in a store, what kind of service they want from a physician or lawyer or other professional, and so forth. Rather than doing experiments to understand specific things such as the way people process information, Mind Genomics works at the level of granular, everyday experience, attempting to understand how people think about the specifics of their lives. Mind Genomics can thus be thought of as the science of everyday experience [1-3].

Moving to Detailed Instructions Given to AI

The AI embedded in Idea Coach allows the user to pose more complicated questions. The questions move from simply questions to statements, actually hypotheses, and then pose questions based upon the hypotheses. Table 1 shows the instructions provided to Idea Coach in the www.bimileap platform. The instructions posit the existence of three mind-sets, although the instructions could have been changed to posit fewer or more. Previous work investigations with Mind Genomics often revealed that three mind-sets generated both a comprehensive coverage of different points of view on the topic but at the same time generated a feeling of parsimony. That is, three mind-sets satisfied both the need to cover the different points of view, but the desire to do with as little hypothesizing as possible. After introducing the topic, the request asked eight specific questions, all of which required the AI to hypothesize about what might be the case for each mind-set. The final piece of information was the group about whom the request was being made, specifically college students.

Table 1: The request as given to Idea Coach

TAB 1

As requested, Idea Coach returned with three mind-sets, shown in Table 2. These mind-sets are:

  1. Human rights advocates for Palestine
  2. Anti-colonialist perspective
  3. Anti-Zionist activists

Table 2: Specifics of the three mind-sets returned by the AI in Idea Coach

tab 2

It is instructive to keep in mind that there is nothing provided to the AI to suggest these three groups. Rather, it is the AI which generates the three mind-sets. It is also interesting to note that repeated efforts with AI will return with different sets of mind-sets. That is, for whatever reason, the answers may not be repeatable. That is, it appears almost the a similar but not the same person is thinking through the problem, so that the general patterns are repeated, but not specifics. The AI returns with sets of answers which appear to be internally consistent and agree with the name of the mind-set. There are two disclaimers.

Question #7: What is the likelihood that they will go from discussing the situation with Israel to acts of vandalism, violence, and overt antisemitism?

Answer to Question #7: It is difficult to determine the likelihood of individuals engaging in vandalism, violence, or overt anti-Semitism based solely on discussions. While strong emotions and disagreements may exist, it is important to promote respectful dialogue and understanding.

General disclaimer: Note: It is important to approach these discussions with nuance, empathy, and respect for differing opinions. The aim should not be to forcefully convince individuals but to promote understanding and the exploration of different perspectives.

Table 2 presents the specifics for the three mind-sets returned by the AI in Idea Coach. The table shows the specifics for these three mind-sets. It is important to emphasize here that mind-sets presented in Table 2 are strictly those ‘conceptualized by the AI’. What is important here is that AI returns results that are similar to what a human being might provide, or at least are plausible answers. In a Turing Test one might assume that these answers would defy the attempt of a person to know whether results are generated by machine or generated by people, especially if one were to ignore the language and focus just on the ‘information’ provided.

The initial ‘success’ in the process encouraged the use of AI to move further into the possibilities of looking at the topic in deeper granularity. Rather than instructing Idea Coach and its AI to assume three different mind-sets, the second part of effort ‘pushed the envelope’ to an arbitrary set of 12 different mind-sets. Table 3 shows the instructions to Idea Coach, positing the existence of these 12 mind-sets of students. The task assigned to Idea Coach was made simpler because initial efforts to have the AI answer seven questions for each of 12 mind-sets proved too difficult. The AI returned with a polite refusal each time the large request was made. It was easier simply to ask three questions, comprising name of mind-set, belief about Israel by mind-set, and finally the action step of ‘what does one say to convince this mind-set that Israel is doing the right thing?’ These steps were immediately acted upon by the AI in Idea Coach.

Table 3: The questions asked in the second phase, where 12 mind-sets were posited

tab 3

Table 4 presents the 12 mind-sets hypothesized by AI and returned to the user. The interesting points to note are that the mind-sets are plausible, seemingly different from each other, and that the AI attempted to fulfill the requests about belief regarding Israel and suggesting what to be said to justify Israel’s action. The underlying AI provides its answer in a form that is diplomatic and gentle.

Table 4: The 12 mind-sets, their hypothesized beliefs, and the suggested statements that could be used with them to convince them that Israel is doing the right thing.

tab 4

AI Summarization and the Creation of ‘New Knowledge’

The creation of ‘new knowledge’ using AI has emerged as a hot topic [4-6]. The issue is whether AI produces new knowledge in the way that believe a person produces new knowledge, although the reality is this question has not really been adequately answered. What has been suggested, however, is the power of AI to drive innovation, whether that means new knowledge or simply new applications of current knowledge [7,8]. It is clear that whatever the philosophical issue may be, AI seems to be on the cusp of producing something ‘new’, something unexpected, tangible and useful [9-11] Whatever the philosophical issue may be, can the Idea Coach be said to produce something which resembles new knowledge? The results suggested by Tables 2 and 4 hint at new knowledge because the AI seems to have generated clearly delineated mind-sets which ‘make sense’, as well as mind-sets that have not been widely articulated. A further effort to produce new knowledge beyond the simple answers to requests posed to AI in Tables 1 and 3 comprises the request to AI to summarize its own contributions, viz., to take the answers that AI had previously provided, and then provide additional summarizations. Table 5 shows eight sets of ‘summarizations’ based on the limited information provided in Table 4. After the Idea Coach provided the information in Table 4, it applied a secondary set of instructions called the ‘summarizer.’ Without any interference from people, the summarizer asked eight questions shown as numbers topics in Table 4. These topics range from key ideas to themes, to interested audiences, and finally to what’s missing and to innovations.

Table 5: Eight summarizations of the key ideas presented in Table 4. The summarization is returned automatically in the ‘Idea Book’ and is provided automatically to the user.

tab 5(1)

tab 5(2)

tab 5(3)

Discussion and Conclusions

The advances in AI on the one hand, and in consumer research on the other, have been melded into a user-friend tool, known by the rubric of Mind Genomics, and available in a user-friendly platform (www.bimileap.com). What began as a tool to drive knowledge by having people evaluate combinations of messages has evolved to an AI-driven tool to generate these combinations of messages (Idea Coach). That evolution began with the effort to address the problems that novice users and perfectionists alike experience, viz., the sheer emotional difficulty of having to develop ideas. It was this emergent ‘block’ to using Mind Genomics which promoted the use of AI to suggest these ideas to the user. The results were positive, and within 18 months the use of AI was so easy that even grade-school children could become published researchers, with quite relevant topics [12]. Indeed, the experience with Idea Coach was so positive to some that it actually became fun to do. The next step was to move beyond suggesting single ideas or messages to ‘test’. Rather than requesting single ideas to be provided as answers to a question, the evolution was to provide a deeper question, to provide complete structures of knowledge, such as the request to list mind-sets for a topic, and then to define many of the properties of the mind-set. It was this breakthrough which revealed the power of AI to provide what might be called deep knowledge, or at least deep synthesis of ideas. At the practical level, the effort involved in the creation of the knowledge should be a motivator for further exploration. The entire effort to create the information presented here was less than 10 minutes. The effort involved formulating a request to AI, incorporating the request into a simple squib, and then receiving the information within 30 seconds. The Mind Genomics program, automatically storing the results and allowing ‘on-the-fly’ re-runs (iterations) of either the same request or an edited one, made it possible to explore different aspects. The final results of just two of what turned out to be dozens of easy-to-do iterations appear here. The reality is that the platform enable the exploration of many ideas having to do with the ‘genocide’ accusation, these results not shown here. Some of the other explorations involved the exploration of mind-sets in different universities (viz., Harvard, Columbia, City University of New York), as well as explorations of different types of people specified as participants (e.g., college students versus non-students, of the same age). The sheer speed with which the results emerges combined with the depth of information available immediately and in summary form suggest the opportunity to create a reference book of hundreds of pages about any topic for which the mind of people may be an important feature.

References

  1. Moskowitz HR, Hartmann J (2008) Consumer research: creating a solid base for innovative strategies. Trends in Food Science & Technology 19: 581-589.
  2. Moskowitz HR (2012) ‘Mind Genomics’: The experimental, inductive science of the ordinary, and its application to aspects of food and feeding. Physiology & Behavior 107: 606-613. [crossref]
  3. Radványi D, Gere A, Moskowitz HR (2020) The mind of sustainability: a mind genomics cartography. International Journal of R&D Innovation Strategy (IJRDIS) 2: 22-43.
  4. Cope B, Kalantzis M, Searsmith D (2021) Artificial intelligence for education: Knowledge and its assessment in AI-enabled learning ecologies. Educational Philosophy and Theory 53: 1229-1245.
  5. Lund BD, Wang T (2023) Chatting about ChatGPT: how may AI and GPT impact academia and libraries?. Library Hi Tech News 40: 26-29.
  6. Open AI. 2023 https: //beta.openai.com/docs/models/gpt-, accessed January 18, 2023
  7. Kaplan A, Haenlein M (2020) Rulers of the world, unite! The challenges and opportunities of artificial intelligence. Business Horizons 63: 37-50.
  8. Paschen,U, Pitt C, Kietzmann J (2020) Artificial intelligence: Building blocks and an innovation typology. Business Horizons 63: 147-155.
  9. Raji ID, Bender EM, Paullada A, Denton E, Hanna A et al. (2021) AI and the everything in the whole wide world benchmark. arXiv preprint arXiv: 2111.15366.
  10. Soleimani M, Intezari A, Pauleen DJ (2022) Mitigating cognitive biases in developing AI-assisted recruitment systems: A knowledge-sharing approach. International Journal of Knowledge Management (IJKM) 18: 1-18.
  11. Yigitcanlar T, Cugurullo F (2020) The sustainability of artificial intelligence: An urbanistic viewpoint from the lens of smart and sustainable cities. Sustainability 12:8548
  12. Mendoza CL, Mendoza CI, Rappaport S, Deitel J, Moskowitz HR, et al. (2023) Empowering young people to become researchers: What do people think about the different factors involved when shopping for food? Nutrition Research & Food Science Journal 6: 1-9.

Accelerated the Mechanics of Science and Insight through Mind Genomics and AI: Policy for the Citrus Industry

DOI: 10.31038/MGSPE.2024412

Abstract

The paper introduces a process to accelerate the mechanics of science and insight. The process comprises two parts, both involving artificial intelligence embedded in Idea Coach, part of the Mind Genomics platform.. The first part of the process identifies a topic (policy for the citrus industry), and then uses Mind Genomics to understand the three emergent mind-sets of real people who evaluate the topic, along with the strongest performing ideas for each mind-set. Once the three mind-sets are determined, the second part of the process introduces the three mind-sets and the strongest performing elements to AI in a separate ‘experiment’, instructing Idea Coach to answer a series of questions from the point of view of each of the three mind-sets. The acceleration can be done in a short period of time, at low cost, with the ability to generate new insight about current data. The paper closes by referencing the issues of critical thinking and the actual meaning of ‘new knowledge’ emerging from a world of accelerated mechanics of science and insight.

Introduction

Traditionally, policy has been made by experts, often consultants to the government, these consultants being experts in the specific topic, in the art and science of communication, or both. The daily press is filled with stories about these experts, for example the so-called ‘Beltway Bandits’ surrounding Washington D.C [1]. It is the job of these experts to help the government decide general policy and specific implementation. The knowledge of these experts helps to identify issues of importance to the government groups to whom they consult. The ability of these expert to communicates helps to assure that the policy issues on which they work will be presented to the public in the most felicitous and convincing manner. At the same time that these experts are using the expertise of a lifetime to guide policy maker, there is the parallel world of the Internet, source of much information, and the emerging world of AI, artificial intelligence, with the promise of supplanting or perhaps more gently, the promise of augmenting, the capabilities and contributions of these expert. Both the internet and AI have been roundly attacked for the threat that they pose [2]. It should not come as a surprise that the world of the Internet has been accused of being replete with false information, which it no doubt is [3]. AI receives equally brutal attacks, such as producing false information [4] an accusation at once correct and capable of making the user believe that AI is simply not worth considering because of the occasional error [5]. The importance of public policy is already accepted, virtually universally. The issue is not the general intent of a particular topic, but the specifics. What should the policy emphasize? Who should be the target beneficiaries of the policy? What should be done, operationally, to achieve the policy? How can the policy be implemented? And finally, in this short list, what are the KPI’s, the key performance indicators by which a numbers-hungry administration can discover whether the policy is being adopted, and whether that adoption is leading to desire goals.

Theory and Pragmatics: The origin of this Paper

This paper was stimulated by the invitation of HRM to attend a conference on the Citrus Industry in Florida, in 2023. The objective of the conference was to bring together various government, business and academic interests to discuss opportunities in the citrus industry, specifically for the state of Florida in the United States, but more generally as well. Industry-center conferences of this type welcome innovations from science, often with an eye on rapid application. The specific invitation was to share with the business, academic and government audiences new approaches which promised better business performance. The focus of the conference was oriented towards business and towards government. As a consequence, the presentation to the conference was tailored to show how Mind Genomics as a science could produce interesting data about the response to statements about policy involving the business of citrus. As is seen below, the material focused on different aspects of the citrus industry, from the point of view of government and business, rather than from the point of view of the individual citrus product [6-9].

The Basic Research Tool: Mind Genomics

At the time of invitation the scope of the presentation was to share with the audience HOW to do a Mind Genomics study, from start to finish. The focus was on practical steps, rather than theory, and statistics. As such the presentation was to be geared to pragmatics, about HOW to do the research, WHAT to expect, and how to USE the results. The actual work ended up being two projects, the first project to get some representative data using a combination of research methods and AI, AI to generate the ideas and then research to explore the ideas with people. The second part, done recently, almost five months after the conference, expanded the use of AI to further analyze the empirical results, opening up new horizons for application.

Project #1: Understanding the Mind of the Ordinary Person Faced with Messages about Citrus Policy

The objective of standard Mind Genomics studies is to understand how people make decisions about the issues of daily life. If one were to summarize the goals of this first project, the following sentence would do the best job, and ended up being the sentence which guided the efforts. The sentence reads: Help me understand how to bring together consumers, the food trade, and the farmer who raises citrus products, so we can grow the citrus industry for the next decade. Make the questions short and simple, with ideas such as ‘how’ do we do things. The foregoing is a ‘broad stroke’ effort to under what to do in the world of the everyday. The problem is general, there are no hypotheses to test, and the results are to be in the form of suggestions. There is no effort to claim that the results tell us how people really feel about citrus, or what they want to do when the come into contact with the world of citrus as business, as commerce, as a regulated piece of government, viz., the agriculture industry. In simple terms, the sentence in bold is a standard request that is made in industry all the time, but rarely treated as a topic to be explored in a disciplined manner. Mind Genomics works by creating a set of elements, messages about a topic, and mixing/matching these elements to create small vignettes, combinations comprising a minimum of two messages and a maximum of four messages. The messages are created according to an underlying structure called an experimental design. The respondent, usually sitting at a remote computer, logs into the study, reads a very short introduction to the study, and then evaluates a set of 24 vignettes, one vignette at a time. The entire process takes less than 3-4 minutes and proceeds quickly when the respondents are members of an on-line panel and are compensated for their participation by the panel company. The Mind Genomics process allows the user to understand what is important to people, and at the same time prevents the person from ‘gaming’ the study to give the correct answer. In most studies, the typical participant is uninterested in the topic. The assiduous researcher may instruct the participant to pay attention, and to give honest answers, but the reality is that people tend to be interested in what they are doing, not in what the researcher wants to investigate. As a consequence, their answers are filled with a variety of biases, ranging from different levels of interest and involvement to distractions by other thoughts. The Mind Genomics process works within these constraints by assuming that the respondent is simply a passive observer, similar to a person driving through their neighborhood, almost in an automatic fashion. The person takes in the information about the road, traffic, and so forth, but does not pay much attention. At the end, the driver gets to where they are going, but can barely remember what they did when asked to recall the steps. This seems to be the typical course of events. The systematic combinations mirror these different ‘choice points.’ The assumption is that the respondent simply looks at the combination, and ‘guesses’, or at least judges with little real interest. Yet, the systematic variation of the elements in the vignettes ends up quickly revealing what elements are important, despite the often heard complain that ‘I was unable to see the pattern, so I just guess.’

The reasons for the success of Mind Genomics are in the design and the execution [10-12].

  1. The elements are created with the mind-set of a bookkeeper. The standard Mind Genomics study comprises four questions (or categories), each question generating four answers (also called element). The questions and answers can be developed by professionals, by amateurs, or by AI. This paper will show how AI can generate very powerful, insight questions and answers, given a little human guidance by the user.
  2. The user is required to fill in a templated form, asking for the questions (see Figure 1, Panel A). When the user needs help the AI function (Idea Coach) can recommend questions once Idea Coach is given a sense of the nature of the topic. Figure 1, Panel B shows the request to Idea Coach in the form of a paragraph, colloquially called a ‘squib.’ The squib gives the AI a background, and what is desired. The squib need not follow a specific format, as long as it is clear. The Idea Coach returns with sets of suggested questions. The first part of the suggest questions appears in Figure 1, Panel C, showing six of the 15 questions returned by the AI-powered Idea Coach. The user need only scroll through to see the other suggestions. The user can select a question, edit it, and then move on. The user can run many iterations to create different sets of questions and can either edit the squib or edit the question, or both. At the end of the process, the user will have created the four questions, as shown in Figure 1, Panel D. Table 1 shows a set of questions produced by the Idea Coach, in response to the squib.
  3. The user follows the same approach in order to create the answers. This time, however, the squib does not need to be typed in by the user. Rather, the question selected by the user, and after editing, becomes the squib for Idea Coach to use. For this project, Figure 1, Panel D shows the four squibs, one for each question. Idea Coach once again returns with 15 answers (elements) for each squib. Once again the Idea Coach can be used, so that the Idea Coach becomes a tool to help critical thinking, providing sequential sets of 15 answers (elements). From one iteration to another the 15 answers provided by Idea Coach differ for the most part, but with a few repeats Over 10 or so iterations it’s likely that most of the answers will have been presented.
  4. Once the user has selected the questions, and then selected four answers for each question, the process continues with the creation of a self-profiling questionnaire. That questionnaire allows the user to find out how the respondent thinks about different topics directly or tangentially involved with the project. The self-profiling questionnaire has a built-in pair questions to record the respondent’s age (directly provided), and self-described gender. For all questions except that of age, the respondent is instructed to select the correct answer to the question, the question presented on the screen, the answers presented in a ‘pull-down’ menu which appears when the corresponding question is selected for answering.
  5. The next step in the process requires the user to create a rating scale (Figure 2, Panel A). The rating scale chosen has five points as show below. Note that the scale comprises two parts. The first part is evaluative viz., how does the respondent feel (hits a nerve vs hot air). The second part is descriptive (sounds real or does not sound real). This two-sided scale enables the user to measure both the emotions (key dependent variable for analysis), as well as cognitions. For this study, the focus will be on the percent of ratings that are either 5 or 4 (hitting a nerve). Note that all five scale points are labelled. Common practice in Mind Genomics studies has been to label all the scales for the simple reason that most users of Mind Genomics results really are not focused on the actual numbers, but on the meaning of the numbers.
    Here’s a blurb you just read this morning on the web when you were reading stuff.. What do you think
    1=It’s just hot air … and does not sound real
    2=It’s just hot air … but sounds real
    3=I really have no feeling
    4=It’s hitting a nerve… but does not sound real
    5=It’s hitting a nerve .. and sounds real
  6. The user next create a short introduction to the study, to orient the respondent (Figure 2, Panel B). Good practice dictates that wherever possible the user should provide as little information about the topic as possible. The reason is simple. It will be from the test stimuli, the elements in the 4×4 collection, or more specifically the combinations of those elements into vignette, that the respondent will make the evaluation and assign the judgment. The purpose of the orientation is to make the respondent comfortable and give general direction. The exceptions to this dictum come from situations, such the law, where knowledge of other factors outside of the material being presented can be relevant. Outside information is not relevant here.
  7. The last step of the setup consists of ‘sourcing’ the respondents (Figure 2, Panel C). Respondents can be sourced from standing panels of pre-screened individuals, or from people one invites, etc. Good practice dictates working with a so-called online panel provider, which for a fee can customize the number and type of respondent desired. With these online panel providers the study can be done in a matter of hours.
  8. Once the study has been set-up, including the selection of the categories and elements (viz, questions and answers), the Mind Genomics platform creates combinations of these elements ‘on fly’, viz., in real time, doing so for each respondent who participates in the study. It is at the creation of the vignettes where Mind Genomics differentiates itself from other approaches. The conventional approach to evaluating a topic uses questionnaires, with the respondent present with stand alone ideas in majestic isolation, one idea at a time. The idea or topic might be a sentence, but the sentence has the aspects of a general idea, such as ‘How important is government funding for a citrus project.’ The goal is to isolate different, relevant ideas, focus the mind of the respondent on each idea, one at a time, obtain what seems to be an unbiased evaluation of the idea, and then afterwards to the relevant analyses to obtain a measure of central tendency, viz., an average, a median, and so forth. The thinking is straightforward, the execution easy, and the user presumes to have a sense of the way the mind of the respondent works, having given the respondent a variety of ‘sterile ideas’, and obtained ratings for each of the separate ideas.Figure 3 shows a sample vignette as the respondent would see it. The vignette comprises a question at the topic, a collection of four simple statements, without any connectives, and then the scale buttons on the bottom. The respondent is presented with 24 of these vignettes. Each vignette comprises a minimum of two and a maximum of four elements, in the spare structure shown in Figure 3. There is no effort made to make the combination into a coherent whole. Although the combinations do not seem coherent, and indeed they are not, after a moment’s shock the typical respondent has no problem reading through the vignette, as disconnected as the elements are, and assigning a rating to the combination. Although many respondents feel that they are ‘guessing,’ the subsequent analysis will reveal that they are not.

    The vignettes are constructed by an underlying plan known as an experimental design. The experimental design for these Mind Genomics studies calls for precisely 24 combinations of elements, our ‘vignettes’. There are certain properties which make the experimental design a useful tool to understand how people think.

    a. Each respondent sees a set of 24 vignettes. That set of vignette suffices to do a full analysis on the ratings of one respondent alone, or on the ratings of hundreds of respondents. The design is explicated in Gofman & Moskowitz.

    b.  The design calls for each element to appear five times in 24 vignettes and be absent 19 times from the 24 vignettes.

    c.  Each question or category contributes at most one element to a vignette, often no elements, but never two or more elements. In this way the underlying experimental design ensures that no vignette every present mutually contradictory information, which could easily happen if elements from the same category appeared together, presenting different specifics of the same type of information.

    d.  Each respondent evaluates a different set of vignettes, all sets structurally equivalent to each other, but with different combinations [13]. The rationale underlying this so-called ‘permutation’ approach is that the researcher learns from many imperfectly measured vignettes than from the same set of vignettes evaluated by different respondents in order to reduce error of measurement. In other words, Mind Genomics moves away from reducing error by averaging out variability to reducing error by testing a much wider range of combinations. Each combination tested is subject to error, but the ability to test a wide number of different combinations allows the user to uncover the larger pattern. The pattern often emerges clearly, even when the measurements of the individual points on the pattern are subject to a lot of noise.

    The respondent who evaluates the vignettes is instructed to ‘guess.’ In no way is the respondent encouraged to sit and obsess over the different vignettes. Once the respondent is shown the vignette and rates it, the vignette disappears, and a new vignette appears on the screen. The Mind Genomics platform constructs the vignettes at the local site where the respondent is sitting, rather than sending the vignettes through the email.

    When the respondent finishes evaluating the vignettes, the composition of the vignette (viz., the elements present and absent) is sent to the database, along with the rating (1-5, as show above) as well as the response time, defined as the number of seconds (to the nearest 100th) elapsing between the appearance of the vignette on the respondent’s screen and the respondent’s assignment of a rating.

    The last pieces of information to be added comprise the information about the respondent generated by the self—profiling questions, done at the start of the study, and a defined binary transformation of the five-point rating to a new variable, called convenient R54x.. Ratings 5 and 4 (hitting nerve) were transformed to the value 100; . Ratings 3,2,1 (not hitting a nerve) were transformed to the value 0. To the transformed values 0 or 100, respectively, was added a vanishingly small random number (<10-5). The rationale for the random number is that later the ratings would be analyzed by OLS (ordinary least-squares) regression and then by k-means clustering, with the focus on the coefficients to emerge from OLS regression as inputs to the clustering. To this end it was necessary to ensure that all respondent data would generate meaningful coefficients from OLS regression, a requirement only satisfied when the newly created binary variables were all different from each other. Adding the vanishingly small random number to each newly created binary variable ensured that variation.

  9. The analysis of the ratings follows two steps once the ratings have been transformed to R54x. The first step uses OLS (ordinary least-squares) regression, at the level of the individual respondent. OLS regression fits a simple linear equation to the data, relating the presence/absence of the 16 elements to the variable R54x. The second step uses k-means clustering (Likas et. al., 2003) to divide the respondents into groups, based upon the pattern of the coefficients for the equation.

Table 1: Questions provided to the user by AI embedded in Idea Coach

tab 1
 
 

fig 1

Figure 1: Set up for the Mind Genomics study. Panel A shows the instructions to provide four questions. Panel B shows the input to Idea Coach. Panel C shows the first part of the output from Idea Coach, comprising six of the 15 questions generated. Panel D shows the four questions selected, edited, and inserted into the template.

fig 2

Figure 2: Final steps in the set-up of the study. Panel A shows the rating scale; the user types in the rating question select the number of scale points, and describe each scale point. Panel B shows the short orientation at the start of the study. Panel C shows the request to source respondents.

fig 3

Figure 3: Example of a four-element vignette, together with the rating question, the 5-point rating scale, and the answer buttons at the bottom of the screen.

The equation is expressed as: R54x = k1A1 + k2A2 … k16D4. The OLS regression program has no problem creating an equation for each respondent, based upon the prophylactic step of having added a vanishingly small random number to each transformed rating. That prophylactic step ensures that the OLS regression will never encounter the situation of ‘no variation in the dependent variable’, R54x.

Once the clustering has finished, the cluster program assigns each respondent first into one of two non-overlapping clusters, and second into one of three non-overlapping clusters. In the nomenclature of Mind Genomics these clusters are called ‘mind-sets’ to recognize the fact that they represent different points of view.

Table 2 presents the coefficients for the Total Panel, then for the two-mind-set solution, and then for the three-mind-set solution. Only positive coefficients are shown. The coefficient shows the proportion of time a vignette with the specific element generate a value of 100 for variable R54x. There emerges a large range in the numerical values of 16 coefficients, not so much for the Total Panel as for the mind-sets. This pattern of large difference across mind-sets in the range of the coefficients for R54x makes sense when we consider what the clustering is doing. Clustering is separating out groups of people who look at the topic in the same way, and do not cancel each other. When we remove the mutual cancellation through clustering the result is that all of the patterns of coefficients in a cluster are similar. The subgroup no longer has averages of numbers from very high to very low for a single element, an average which suppressed the real pattern. No longer do the we have the case that the Total Panel ends up putting together streams flowing in different directions. Instead, the strengths of different mind-sets becomes far more clear, more compelling, and more insights driven.

Table 2: Coefficients for the Total Panel, and then for the two-mind-set solution, and then for the three-mind-set solution, respectively.

tab 2

 

We focus here on the easiest take, namely, to interpret the mind-set. It is hard to name mind-sets 1 of 2 and 2 of 2. In contrast, it becomes far easier to describe the different mind-sets. We look only at the very strong coefficients; those score 21 or higher.

  1. Mind-Set 1 of 3-Focus on interacting with users, include local rowers, consumers, businesses which grow locally, and restauranteurs.
  2. Mind-Set 2 of 3-Focus on publicizing benefits to consumers.
  3. Mind-Set 3 of 3-Focus on communication.

Table 2 shows a strong consistency within the segments, a consistency which seems more art than science. The different groups emerge clearly, even though it would be seemingly impossible to find patterns among the 24 vignettes, especially recognizing that each respondent ended up evaluating a unique set of vignettes. The clarity of the mind-set emerges again and again in Mind Genomics studies, despite the continue plaint by study respondents that they could not ‘discover the pattern’ and ended up ‘guessing.’ Despite that plaint, the patterns emerging make overwhelming sense, disposing of the need of some of the art of storytelling, the ability to craft an interesting story from otherwise boring and seemingly pattern-less data. A compelling story emerges just from looking at what element are shade, for each mind-set. Finally, the reason for the clarity ends up being the hard-to-escape reality that the elements all are meaningful in and of themselves. Like the reality of the everyday, each individual element, like each individual impression of an experience, ‘makes sense’.

The Summarizer: Finding Deeper Meanings in the Mind-set Results

Once the study has finished, the Mind Genomics platform does a thorough ‘work-up’ of the data, creating models, creating tables of coefficients, etc. As part of this the Mind Genomics platform applies a set of pre-specified queries to the set of strong performing elements, operationally defined as those elements with coefficients of 21 or higher. The seemingly artificial lower limit of 21 comes from analysis of the statistical properties of the coefficients, specifically at what value of coefficient can user feel that the pattern of coefficients is statistically robust, and thus feel the pattern to emerge has an improved sense of reality. The Summarizer is programmed to write these short synopses and suggestions, doing so only with the tables generated by the Mind Genomics platform, as shown above in Table 2. Thus, for subgroups which generate no coefficients of 21 or higher, the Summarizer skips those subgroups. Finally, the summarizer is set up to work for every subgroups defined in the study, whether age, gender, or subgroup defined by the self-profiling classification question in which respondent profile themselves on topics relevant to the study.

Table 3 shows the AI summarization of the results for each of the three mind-sets. The eight summarizer topics are:

  1. Strong performing elements
  2. Create a label for this segment
  3. Describe this segment
  4. Describe the attractiveness of this segment as a target audience:
  5. Explain why this segment might not be attractive as a target audience:
  6. List what is missing or should be known about this segment, in question form:
  7. List and briefly describe attractive new or innovative products, services, experiences, or policies for this segment:
  8. Which messages will interest this segment?

Table 3: The output of the AI-based Summarizer applied to the strong performing elements from each of the mind-sets in the three-mind-set solution.

tab 3(1)

tab 3(2)

tab 3(3)

tab 3(4)

tab 3(5)

tab 3(6)

tab 3(7)
 

Part 2: AI as a Tool to Create New Thinking, Create New Hypotheses

During the past six months of experience with AI embedded in Idea Coach, a new and unexpected discovery emerged, resulting from exploratory work by author Mulvey. The discovery was that the squib for Idea Coach could be dramatically expanded, moving it beyond the request for questions, and into a more detailed request. The immediate reaction was to explore how deeply the Idea Coach AI could expand the discovery previously made. Table 4 shows the expanded squib (bold), and what the Idea Coach returned with later on. The actual squib was easy to create, requiring only that the user copy the winning elements for each mind-set (viz., elements with coefficients of 21 or higher). Once these were identified and listed out, squib was further amplified by a set of six questions. Idea Coach returned with the answers to the six questions for each of the three mind-sets, and then later did its standard analysis using the eight prompts. These appear in Table 4. It is important to note that Table 4 contains no new information, but simply reworks the old information. In reworking that old information, however, the AI creates an entirely new corpus of suggestions of insights. From this simple demonstration emerges the realization that the sequence of Idea Coach, questions, answers, results, all emerging in one hour or less for a set of 100 respondents or fewer, can be further used to springboard the investigations, and create new insights. These insights should be tested, but it seems likely that a great deal of knowledge can be obtained quickly, at very low cost, with no risk.

Table 4: AI ‘super-analysis’ of results from an earlier Mind Genomic study, revealing three mind-sets, and the strong performing elements for each mind-set.

tab 4(1)

tab 4(2)

tab 4(3)

tab 4(4)

tab 4(5)

tab 4(6)

Discussion and Conclusions

This paper began with a discussion of a small-scale project in the world of citrus, a project meant to be a demonstration to be given to a group at the citrus conference in September 2023. At that time, the Idea Coach had been introduced, and was used as a prompt for the study. It is important to note that the topic was not one based on a deep literature search of existing problems, but instead a topic crafted to be of interest to an industry-sector conference. The focus was not on science to understand deep problems, but rather research on how to satisfy industry-based needs. That focus explains why the study itself focuses on a variety of things that one should do. The focus was tactics, not knowledge. The former being said, the capability to accelerate and expand knowledge is still relevant, especially as that capability bears upon a variety of important issues. The first issue is the need to instill critical thinking into students [14,15]. The speed, simplicity, and sheer volume of targeted information may provide an important contribution to the development of critical thinking. Rather than giving students simple answers to simple questions, the process presented here opens up the possibility that the Idea Coach format shown here can become a true ‘teacher’, working with students to formulate questions, and then giving the students the ability to go into depth, in any direction that they wish, simply by doing an experiment, and then investigating in greater depth any part of the results which interest them. The second issue of relevance is the potential to create more knowledge through AI. There are continuing debates about whether or not AI actually produces new knowledge [16,17]. Rather than dealing with that issue simply in philosophy-based arguments, one might well embark on a small, affordable series of experiments dealing with a defined topic, find the results from the topic in terms of mind-sets, and then explore in depth the mind-sets using variations of the strategy used in the second part of the study. That is, once the user has obtained detailed knowledge about mind-sets for the topic, there is no limitation except for imagination which constrains the user from asking many different types of questions about what the mind-sets would say and do. After a dozen or so forays into the expansion of knowledge from a single small Mind Genomics project, it would then be of interest to assess the degree to which the entire newly developed corpus of AI-generated knowledge and insight is to be considered ‘new knowledge’, or simply a collection of AI-conjectures. That consideration awaits the researcher. The tools are already here, the effort is minor, and what awaits may become a treasure trove of new knowledge, perhaps.

References

  1. Butz EL (1989) Research that has value in policy making: a professional challenge. American Journal of Agricultural Economics 71: 1195-1199.
  2. Wang J Molina, MD, Sundar SS (2020) When expert recommendation contradicts peer opinion: Relative social influence of valence, group identity and artificial intelligence. Computers in Human Behavior 107, p.106278, https://doi.org/10.1016/j.chb.2020.106278
  3. Molina MD, Sundar SS, Le T, Lee D (2021) “Fake news” is not simply false information: A concept explication and taxonomy of online content. American Behavioral Scientist 65: 180-212.
  4. Dalalah D, Dalalah OM (2023) The false positives and false negatives of generative AI detection tools in education and academic research: The case of ChatGPT. The International Journal of Management Education 21: 100822.
  5. Brundage M, Avin S, Clark J, Toner H, Eckersley P, Garfinkel B, Dafoe A, Scharre P, et al. and Anderson H (2018) The malicious use of artificial intelligence: Forecasting, prevention, and mitigation. arXiv preprint arXiv: 1802.07228.
  6. Batarseh FA and Yang R (eds.) (2017) Federal data science: Transforming government and agricultural policy using artificial intelligence. Academic Press.
  7. Ben Ayed R, Hanana M (2021) Artificial intelligence to improve the food and agriculture sector. Journal of Food Quality, 1-7, ID 5584754 | https://doi.org/10.1155/2021/5584754
  8. Sood A, Sharma RK, Bhardwaj AK (2022) Artificial intelligence research in agriculture: A review. Online Information Review 46: 1054-1075.
  9. Taneja A, Nair G, Joshi M, Sharma S, Sharma S, Jambrak AR, Roselló-Soto E, Barba FJ, Castagnini JM Leksawasdi N, Phimolsiripol Y et.al (2023) Artificial Intelligence: Implications for the Agri-Food Sector. Agronomy 13: 1397.
  10. Harizi A, Trebicka B, Tartaraj A, Moskowitz, H (2020) A mind genomics cartography of shopping behavior for food products during the COVID-19 pandemic. European Journal of Medicine and Natural Sciences 4: 25-33.
  11. Porretta S, GereA, Radványi D, Moskowitz H (2019) Mind Genomics (Conjoint Analysis): The new concept research in the analysis of consumer behaviour and choice. Trends in Food Science & Technology 84: 29-33.
  12. Zemel R, Choudhuri SG, Gere A, Upreti H, Deite Y, Papajorgji P, Moskowitz H (2019) Mind, consumers, and dairy: Applying artificial intelligence, Mind Genomics, and predictive viewpoint typing. In: Current Issues and Challenges in the Dairy Industry (ed R, Gywali S, Ibrahim, T, Zimmerman), Intech Open, IntechOpen, IBSN: 9781789843552, 1789843553
  13. Gofman A, Moskowitz H (2010) Isomorphic permuted experimental designs and their application in conjoint analysis. Journal of Sensory Studies 25: 127-145.
  14. Guo Y, Lee D (2023) Leveraging chatgpt for enhancing critical thinking skills. Journal of Chemical Education 100: 4876-4883.
  15. Ibna Seraj, PM, Oteir I (2022) Playing with AI to investigate human-computer Interaction Technology and Improving Critical Thinking Skills to Pursue 21st Century Age. Education Research International, 2022. Article ID 6468995 | https://doi.org/10.1155/2022/6468995
  16. Schäfer MS (2023) The Notorious GPT: science communication in the age of artificial intelligence. Journal of Science Communication 22: Y02.
  17. Spennemann DH (2023) ChatGPT and the generation of digitally born “knowledge”: How does a generative AI language model interpret cultural heritage values? Knowledge 3: 480-512.

Mind-Set Based Signage: Applying Mind Genomics to the Shopping Experience

DOI: 10.31038/MGSPE.2024411

Abstract

The paper presents a new approach to optimizing the shopper experience, combining easy-to-implement tools for understanding shopper mind-sets at the granular, specific level (Mind Genomics; www.BimiLeap.com) with a simple, rapid way which assigns any shopper or prospective shopper to the relevant mind-set for that granular topic (www.PVI360.com). The approach begins with a simple study of the motivating power of relevant messages, and thus uncovers mind-sets or groups of respondents showing similar patterns of what motivates them. Then, using the same data, the approach creates a simple questionnaire comprising six questions taken from the original study, the pattern of answers to which assign a new person to a mind-set. Once the mind-set of the shopper is ‘identified’ for the granular topic using the PVI (personal viewpoint identifier) it is a matter of giving the shopper the appropriate motivating message, either at the time of shopping in brick and mortar store or e-store, or sending the message on the Internet in the form of an advertisement or individualized coupon.

Introduction

The past two decades have seen an explosion of knowledge about the consumer, the knowledge emerging from the speed and affordability of internet-based surveys, the sophisticated analysis of masses of cross-sectional data known as Big Data, and the application of artificial intelligence to uncover patterns. What continues to emerge is that nature is simultaneously tractable and intractable. As the macro level we know what to expect in terms of purchase patterns and expected time to repurchase, some of which knowledge may transfer to the level of the individuals, only for the general pattern just exposed to be disrupted by the idiosyncrasies of each individual. The world at the time of this writing (Fall, 2023) is quite different from the world of just a decade ago, and most certain far different from the earlier decades. The notion that one could change advertisements is well-accepted, easily and widely done. Outdoor advertisements and LED technology assault us everywhere we go. We are accustomed to see large billboards with attention-grabbing sequences advertisements, the modern day evolution of signage of decades ago, once static, now plastic, and changeable at will. Now technology makes it possible to individualize the messaging for an individual, much as is done on a cell phone. This paper presents one approach. The organizing nature of this paper is how one might advertise to a single customer, using science to uncover the ‘mind’ of that customer ahead of time. The objective of this study was to understand the different types of messages which might appeal to shoppers of cereal in the middle isle, and shoppers of yogurt in the refrigerated dairy section. Could the technology of 2023 be set up to deliver the proper messages to an individual who is walking along the store? And could the approach be set up to be done at scale, affordably, quickly, with scientific precision rather than with guessing about what the person wants based upon who the person is. This latter condition is important. It means that the messages must be delivered to the person most likely to respond to the specific messages. The studies reported here were done with the intention of testing out the possibility that one could create a knowledge-based system about messaging for simple, conventional, familiar products. The paper does not deal with new to the world products which have their own mystique, and both positive and negative messaging attached. Rather, the paper deals with what one might call ‘tired, old, utterly familiar’ products that may not be susceptible to the romance of the new and different.

A Short Historical Overview to ‘Messaging the Shopper’

The notion that one can influence the shopper by proper messaging is decades old, and the subject of numerous experiments. Indeed, the real-world behaviors of shoppers and the change in behavior resulting from the proper messaging opens up the topic to anyone interested in messaging, whether the interest be theory such as experimental psychology, to applied science such as consumer psychology, and of course the world of business applications. As a consequence, there have been a number of different studies focusing specifically on shopping.

  1. Schumann et al. (1991) reported only modest effectiveness of signage in shopping cart [1]. To summarize their results: “Findings from both studies reflect that over 60% of the 2 samples noted the presence of the signs in their carts. When Ss were questioned about their awareness of cart advertising on a specific occasion, only 3.0-6.5% recalled the product. There was no evidence that cart signage acts in a subliminal fashion that results in the purchase of the brand.” It may well be the signage in the cart was general information about the product, not necessarily information that would tug at the heartstrings of the shopper.
  2. Dennis et al. (2012) confirmed the efficacy of digital signage but argued for emotional content [2]. They noted that the typical content of digital signal is ‘information-based’ whereas digital signage might be more effective if it were to comprise emotional messaging as well, or even instead of simple information. Results are limited as the DS (digital signage) screens content was information based, whereas according to LCM, (Limited Capacity Model of Mediate Messaging) people pay more attention to emotion-eliciting communications. The results have practical implications as DS appeals to active shoppers.
  3. Buttner et al. (2013) proposed at two types of shopping orientations (mind-sets), task focused and experiential shopping, respectively [3]. They report that “Activating a mindset that matches the shopping orientation increases the monetary value that consumers assign to a product. ….marketers and retailers will benefit from addressing experiential and task-focused shoppers via the mindsets that underlie their shopping orientation.”
  4. Chang and Chen (2015) reported that mind-sets are important, and that the communication should consider the different mind-sets [4]. Their notion was that people may or may not be skeptical to advertising. Those who have a ‘utilitarian orientation’ and an ‘individualistic’ mind-set tend to be skeptical about advertising, and need messages which are different from those individuals who have a ‘hedonic’ and a ‘collectivistic’ mind-set. Chang and Chen bring this topic into discussions about CRM and donating, but their notions can be easily extended to the right type of messaging for digital signage

The Contribution of Mind Genomics to the Solution

Mind Genomics is an emerging science which grew out of the need to understand how people make decisions about the issues of the ‘everyday’. Mind Genomics rests on the realization that the ‘everyday’ situations are compounds of different stimuli. To study these stimuli requires that the respondent, the test subject, be confronted by compound test stimuli which comprise different aspects of everyday situation, stimuli that the respondent ‘evaluates’, such as rating the combination. Through statistics, applied after the researcher properly sets up the blends, it becomes possible to understand just exactly what features ‘drive’ the rating. Properly executed, this seeming ‘roundabout way’, testing mixtures, ends up dramatically revealing the underlying mind of the respondent [5]. The foregoing process, testing systematically created mixtures and deconstructing through statistics, stands in striking opposition to the now-hallowed approach of ‘isolate and study.’ The traditional approach requires that the features of the everyday be identified, and separately evaluated, one feature at a time. Typically the evaluation ends up presenting each of the features separately, getting a rating, analyzing the pattern of ratings across people, and then identifying the key variables which a difference.

Attractive as the traditional methods may be, the one-at-a-time is severely flawed for several reasons:

  1. Combinations of features are more natural. It may be that a feature will receive a different score when evaluated alone compared to the evaluation of the feature as part of a mixture. And it may be that the feature will receive different scores when evaluated against backgrounds provided by a variety of other features. Thus, the wrong answer may emerge.
  2. People may change their criterion of judgment when presented with an array of different types of features, such as features dealing with product safety versus features dealing with branding, with benefits, and so forth. All too often the researcher AND the respondent fail to recognize the underlying shifts in these criteria.
  3. It becomes very difficult to ‘game the system’ when the test stimulus comprise a combination. Often, and perhaps even without knowing it, the respondent tries to assign the ‘correct’ or ‘socially appropriate’ answer. Such effort to ‘be right’ is doomed to failure when the respondent is presented with a combination. Often the respondent asks the researcher or interviewer for ‘help’, such as asking ‘what do I pay attention to in this combination?’

Mind Genomics works with the response to combination of text messages, called vignettes. The vignettes comprise specified combinations of elements, viz., verbal messages. Table 1 below (left part of table) shows these messages. The messages are sparse, to the point, paint a word picture. The vignettes are created according to an underlying plan called an experimental design. The experimental design may be thought of as a set of different combinations, different recipes, combining the same messages, the same elements, in different ways. A key difference between Mind Genomics and conventional research is how Mind Genomics considers variability among people and how it deal with that variability. We start the comparison by considering conventional research, which often considers variability in the data to be error, usually unwanted error which masks the ‘signal’. Occasionally the variability can be traced to some clear factor, such as the nature of the respondent, in which case this irritating variation hiding the signal is actually a signal itself. For the most part, however, researchers consider variability to be unwanted, and either suppress it by meticulous control of the test stimulus/situation, or average out the variability by working with a lot of respondents, and assuming that the variability is random, and so will cancel out. In the world of Mind Genomics variability is considered in a different light. Certainly there is the appreciation of error, but there is also the acceptance of the fact that people differ from each, and that these differences may be important. The differences between people are not necessarily random error, but rather point to potential profound differences among people, albeit differences which exist in a small, granular aspect of daily life. In other words, sometimes the differences are important, and sometimes the differences are merely random noise.

Table 1: Positive elements for cereal, viz., those elements which drive the rating of a vignette towards definitely buy/probably buy). All elements shown have positive coefficients of +2 or higher.

TAB 1

Explicating the Research Process

For the project reported here, the researcher selected two products (cereal, yogurt), asked six questions about the product, questions that could be used to create consumer-relevant messages, and then developed the database of 36 possible consumer messages for each product. Thus far, the process is quite simple, requiring only that the researcher do a bit of thinking about what types of messages might be relevant to consumers. One of the in-going ‘constraints’ from the perspective of marketing and the trade was that the messages had to be of the type which drive purchase. It was not an issue of building one’s brand through advertising. Rather, the messages were chosen so that they could be put on a coupon, or flashed on an LCD panel as the respondent ‘walked by.’ The actual process of developing the raw materials can be daunting for those who are not professionals. In the two studies reported here, a significant effort was expended to develop the six ideas which tell a ‘product story’. One the six ideas are developed, the most intellectually intense part of the effort, the creation of six messages for each idea becomes much easier. Recently, the creation of these basic ideas (or questions), and the elements (or answers) has been improved by a process called Idea Coach, which provides different options, using artificial intelligence (www.BimiLeap.com). The data reported here were collected before the Idea Coach system was incorporated into Mind Genomics.

  1. The actual selection of messages generated six groups of six message, one set of 36 such messages for cereal (Table 1), and another set of comprising different messages, for yogurt (Table 2).When looking at the table, the reader should keep in mind that the elements either pain a simple word picture, or specify a specific a specific claim that could be turned into ‘copy.’
  2. When creating the messages and assigning them to groups, The only requirement for the researcher is to ensure that all of the messages in a single idea (viz., all the answers given to a single question) remain together. For example, messages about ‘calories’ must all be put into one group or idea, and not split across two groups or questions. The rationale for this requirement comes from the fact that the underlying experimental design will need to combine elements from different questions (described below). When the researcher puts a calorie message in one group, and another calorie messages in a second group, there is the likelihood that the underlying experimental design may put these mutually incompatible messages into the same combination.
  3. Once the elements are created, comprising the question and the six answers, as shown in Tables 1 and 2, the next step is to use the basic experimental design, which specifies 48 combinations, each combination comprising either three or four elements. Each combination or vignette contains at most one element from any question. The vignettes are by design incomplete, since there are six questions, but a vignette can only have three or four answers, one from three or four questions. As noted above, each respondent evaluates a unique set of 48 combinations. The underlying mathematics remains the same. What changes is the assignment of a message to a code. For example, for one person, element A1 may be assigned as A1, whereas for another person a permutation is done, so the former A1 becomes A2, A2 becomes A3, et. the experimental design is maintained, but the combinations change [6].
  4. The final steps comprise the introductory message and the rating scale. In Mind Genomics studies most of the judgment must be driven by the individual elements, and not by the introductory statement. It is better to be vague about the product, and let the individual elements drive the reaction, rather than to specify too much in the general introduction. For this study, the introduction was simply ‘Please read this description of cereal and rate it on the 5-point scale below. For yogurt the introductory statement was virtually the same ‘please read this description of yogurt and rate it on the 5-point scale below’
  5. The five-point rating of purchase is anchored: 1: definitely not buy, 2: probably not buy, might not/might buy, 4: probably buy, 5: definitely buy. The anchored five point purchase intent scale has been used for many decades in the world of consumer research, both because the scale is sensitive to differences and because managers understand the scale, and generally look at the percentage of responses that are 4 and 5 on the 5-point scale. These two rating scale points are probably buy and definitely buy. The scale is often transformed to a binary scale, as was done here. Ratings of 4 and 5 were transformed to 100. Ratings of 1, 2 and 3 were transformed to 0. Managers who use the data more easily understand a yes/no scale, buy/not buy.
  6. Following the evaluation of 48 vignettes, the respondent completed a short self-profiling questionnaire, providing information about gender and age.
  7. Respondents were sent one of two links, the first appropriate to the cereal study, the second appropriate to yogurt. Approximately 70% of the individuals who were invited ended up participating. The high completion rate can be traced to the professionalism of the on-line research ‘supplier’. As a general point of view, it is almost always better to work with companies specializing in on-line research. Trying to recruit the respondents oneself ends up with a completion rate much low, often lower than 15%.

Creating the Database and Analyzing the Data for a Study

Each respondent ended up evaluating 48 different combinations, called vignettes, assigning each vignette a rating on an anchored 5-point scale. The next step creates a ‘model’ or equation showing how each of the 36 elements about the product ‘drives’ purchase intent. Recall that all 48 vignettes of a respondent differed from respondent to respondent, although the mathematical structure was the same. This ‘permutation’ strategy allows the research to cover a large percent of the possible combinations [7].

In order to uncover the impact of the elements, the key variables, it is necessary to create an equation relating the presence/absence of the 36 text elements about the product to the rating. This can be easily done. The data are easily analyzed, first by OLS (ordinary least-squares regression) and then by clustering. OLS regression shows how the 36 elements ‘drive’ the response (purchase). Clustering identifies groups of respondents with similar patterns of coefficients groups that we will call ‘mind-sets.’

  1. The OLS regression, applied to either the individual data, or to group data, is expressed by the following: Positive Intent to Purchase=k0 + k1(A1) + k2(A2) . k36(F6).
  2. For regression analysis to work, the dependent variable, the transformed variable (either 0 or 100) must show some small variation across the different 48 ratings for each individual respondent. Often, respondents confine their ratings to one part of the scale (e.g. 1-2; 4-5, etc.). To avoid a ‘crash’ of the OLS regression program, and yet not affect the results in a material way, it is a good idea to add a vanishingly small random number (e.g. around 10-4) to every transformed rating. The random number ensures variation in what will be the dependent variable, but does not affect the magnitude of the coefficients which emerge from the OLS regression.
  3. The underlying experimental design for each individual respondent makes it straightforward to quickly estimate the equation, either for individuals or for groups. The coefficient, whether for individual or for group, shows the degree to the element drives the response the rating of ‘definitely or probably purchase.’ The individual coefficients, viz., for the hundreds of respondents, are typically ‘noisy’, but when the coefficients become stable and reproducible when the corresponding coefficients are averaged across dozens of respondents, or when the equation is estimated from the raw data of dozens of respondents.
  4. The additive constant (k0) shows the estimated proportion of responses that will be 4 or 5 (viz., definitely purchase or probably purchase), in the absence of elements. Of course the underlying experimental design dictated that all 48 vignettes evaluated by any respondent would comprise a maximum of four elements (at most one element from a group) and a minimum of three elements (again, at most one element from a group, not more).
  5. The 36 individual coefficients (A1-F6) represent the contribution of each element to the expected interest in purchasing. When an element is inserted into a vignette, we can estimate its likely contribution by adding together the additive constant and the coefficient for the element. The sum is the percent of the respondents who would assign a rating of 4 or 5 to that newly constructed vignette.
  6. One of the ingoing tenets of Mind Genomics is that there exist groups in the population which think about the same topic, but in different ways. The information to which these respondents react may be the same but these groups use the information in different ways. Some respondents may value the information so that the information appears to covary with their rating of purchase the product. In contrast, other respondents may completely ignore the information. These differences reflect what Mind Genomics calls ‘mind-sets’, viz groups of individuals with clearly defined and different ways of processing the same information.
  7. The mind-sets emerge through the well-accepted statistical analysis called clustering [8]. Briefly, the clustering algorithm computes the Pearson correlation between pairs of respondents, based upon their 36 pairs of corresponding coefficients. Respondents with similar patterns (high positive correlation) are assigned to the same mind-set. Respondents with dissimilar patterns (negative or low positive correlations) are assigned to different mind-sets.
  8. For this study the ideal number of mind-sets is as few as possible. The paper reports the results emerging from dividing the respondents into two mind-sets, and then into four mind-sets, to show the effect of making the clustering more granular. The focus will be on interpreting the results from the two mind-set solution, and creating a tool to assign a new person to the one of the two mind-sets.

Applying the Learning-Cereal

Our data with 328 respondents provides us a wealth of information about to say, what not to say, and to whom. Table 1 shows the results for cereal. The table is organized with the key subgroups of respondents across the top and the messages down the side. In order to make the table easier to read, and allow the patterns to emerge, the table only shows positive coefficients of 2 or higher. The other coefficients were estimated, but are not relevant to the presentation since they do not drive positive interest in purchase. Furthermore, Table 1 shows strong performing elements as shaded cells. Strong performing is defined as a coefficient of + 10 or higher. Table 1 is rich in detail. The table shows the results from running the aforementioned linear equation using the data from all respondents (total), then the data by gender, then by age

  1. The additive constants differ, neither by gender nor age. Again and again Mind Genomics studies reveal that for the most part, conventional methods dividing people fail to show dramatic differences in how these divisions generate groups which think differently. It is eternally tempting to divide people by who they are, and presume that because people are different they think differently.
  2. The total panel of 328 respondents shows very few positive elements, and no strong elements. That is, knowing nothing else we cannot find elements which strongly drive purchase intent. Most of the elements are blank, meaning that the coefficients for those elements are either around zero or negative. In effect, ‘doing the experiment,’ viz. evaluating different messages, fails to uncover strong performing elements. No matter what experts might think, there are no apparent ‘magic bullets’ for cereal.
  3. A first effort to divide groups looks at gender. The additive constant is the same, but the females have a few more positive than do the males. Yet, none of the elements are strong drivers purchase when evaluated in the body of a vignette.
  4. The second effort divides the respondents by age. In terms of the additive constant, the younger respondents (ages 18-39) show a slightly higher additive constant than do the older respondents (age 40+; constants of 58 vs 53). The only strong performer (coefficient >1=10) is S4 for the younger respondents: The same great taste of cereal. only better.
  5. The third effort divides the full set of respondents into exactly two mind-set and then into exactly four mind-sets using k-means clustering (Likas et al. 2003). To save space and make it easier for patterns to emerge, Table 2 shows the only those elements which perform strongly in at least one mind-set of the six created (two mind-sets + four mind-sets=six mind-sets). ‘Performing strongly’ is again operationally defined as a coefficient of +10 or higher. The groups with fewer strong performing elements will be harder to reach.
  6. Focusing just on the two mind-set solution, Mind-Set 2 is more primed than Mind-Set to be interested in buying the cereal (additive constant of 68 for Mind-Set 2, additive constant of 38 for Mind-Set 1). However, Mind-Set 1 shows two elements which excite its members: O2: A tasty breakfast choice makes it easy to maintain a healthy body weight O4: Ideal choice for those concerned about eating too much sugar.

Table 2: Strong performing elements for cereal, for divisions of respondents into two complementary mind-sets, and then into four complementary mind-sets. All elements shown have positive coefficients of +10 or higher.

TAB 2

Applying the Learning-Yogurt

Our second study, this time with 307 respondents, shows similar patterns. Table 3 shows the data for the total panel, gender, and age. Table 4 shows the strong performing elements for the mind-sets, viz., those with coefficients of +10 or higher.

  1. The total panel again does not show strong performing elements (coefficient ≥+10).
  2. The additive constants differ dramatically by gender. Recall that the additive constant is the basic level of purchase intent estimated in the absence of elements. Males shows a higher basic intent, females show a lower basic interest (74 vs. 54). This is a dramatic difference.
  3. Closer inspection of Table 3 reveals that the coefficients for the males are around 0 or lower whereas there are a number of coefficients for females which are moderately positive. Males have a basic higher acceptance, but do not show any strong performing elements. In contrast, females show the lower basic acceptance, but are more selective. The two elements which drive their purchase intent are:
    F4: So flavorful. it will satisfy your sweet taste
    F5: Made with natural flavoring
  4. The second effort divides the respondents by age. In terms of the additive constant, the younger respondents (ages 18-39) show a lower additive constant, the older respondents show a higher additive constant (50 vs 62).
    The younger respondents find five elements to drive purchase:
    E6    Great taste with none of the guilt
    F4    So flavorful. it will satisfy your sweet taste
    O3    A refreshing healthy snack the whole family love
    C1    Ready to eat when you are
    F6    Flavor which sweetens
    In contrast, the older respondents find only one element to drive purchase.
    F5   Made with natural flavoring.
  5. The results emerging from clustering show the two mind-sets (MS1 of 2, MS2 of 2) to have dramatically different additive constants (39 for MS1 of 2; 72 for MS2 of 2). Mind-Set 2 is prepared to purchase, even without messaging, whereas Mind-Set 1 must be convinced. Fortunately, eight of the 36 elements for yogurt perform strongly, two performing quite strongly (F4, F5):
    F5:    Made with natural flavoring
    F4:    So flavorful. it will satisfy your sweet taste
    C2:    Comes in snack size… great for packed lunches
    B2:    Less sugar, less calories
    C5:    A hassle free healthy snack-goes where you go
    B4:    It’s good because IT’S REAL
    C1:    Ready to eat when you are
    F2:    Uses flavors to sweeten for a healthier you.

Table 3: Positive elements for yogurt, viz., those elements which drive the rating of a vignette towards definitely buy/probably buy). All elements shown have positive coefficients of +2 or higher.

TAB 3

Table 4: Strong performing elements for yogurt, for divisions of respondents into two complementary mind-sets, and then into four complementary mind-sets. All elements shown have positive coefficients of +10 or higher.

TAB 4

Part 2 – Messaging the Shopper

One thing we learn from Tables 1 and 3 versus Tables 2 and 4 is that when we look for a strong message for the total panel, we will not find any strong message for Total Panel, for either food. Tables 2 and 4 tell us that when we divide the shoppers in two mind-sets, the one mind-set for each food is ready to buy the food, whereas the other, complementary mind-set can be persuaded to buy, but only when the correct messages are ‘beamed’ to this second group of shoppers. It is to the task of finding this group of shoppers and then sending them the correct messages in the store to which the paper now turns. One of the perplexing problems of knowing mind-sets is the difficulty of assigning a random individual to a mind-set. The reason is simple, but profound. The mind-sets emerge out of the granularity of experience, and are based on the response of people to small, almost irrelevant pieces of communication. We are not talking about issues which are critical to the shopper, issues such as health, income, and so forth, and the decisions one makes about them. Those topics are sufficiently important to people to merit studies by academics and by interested professionals. A great deal of money is spent defining the preferences of a person, so that the sales effort can be successful. Not so with topics like cereal and yogurt, where there is knowledge, but little in the way of knowing the preferences of a particular shopper. Companies which manufacturer cereal and yogurt ‘know’ what to say, but the revenue to be made by knowing the preferences a randomly selected individual is too little to warrant deep investment. To understand the preferences of a randomly selected individual may require one of two things. The first is extensive information about that individual, and a way to link that knowledge to one’s preference about what to say about cereal or about yogurt. That exercise could happen, at least for demonstration purposes, although it does not lend itself to being scaled, at least with today’s technology. Another way is to present the person, our shopper, with the right messages for that shopper. This latter approach requires a way to identify the shopper, and to assign the shopper to the proper mind-set, with low investment, in a way that can be done almost automatically. This second approach has to reckon with practicalities, such as the reluctance of the shopper to provide personal information, the potential disruption of the knowledge-gathering step to the shopping experience, and of course the need to find the appropriate motivation. The proposed process has to be simple, quick, easy to implement. Most of all, the process should motivate the shopper to participate. The answer to the question of ‘how to assign a shopper to a mind-set’ comes from the use of a simple questionnaire called the PVI (personal viewpoint identifier; Gere et al., 2020; Moskowitz et al. 2019). The PVI uses the data from the Tables 2 and 4, to create a set of six questions having two answers (no/yes; not for me/for me, etc.) The questions come from the 16 elements, and are chosen to best differentiate between the two (or among the three) mind-sets. The important thing to keep in mind is that the PVI emerges directly from reanalysis of the data used to create the mind-sets. It will be the pattern of answers to the PVI which will assign a person to one of the mind-sets. With two products, and thus 12 questions, the PVI ‘step’ should take about a minute. The motivation might be lowered price for participants for some products, such as cereal and yogurt.

Figure 1 show the PVI, completed by the shopper at the start of the shopping effort or even ahead of visiting the store. Figure 2 shows a screen shot of the database, in which each shopper who participated is assigned to one of the two mind-sets for cereal, and one of the two mind-sets for yogurt.

Here is a sequence of four proposed steps to test the approach.

  1. At the start of the shopping the individual could be invited to participate, by completing a short questionnaire on a computer, the PVI tool shown in Figure 1. The incentive could a special ‘participant’s pricing’ for the cereal or the yogurt. The objective is to get the shopper to participate, discover the shopper’s membership in a mind-set (in return for the promise of a lower price), and have the shopper interact, with the program assigning the shopper to the correct mind-set for one or several products. The opportunity further remains to engage the shoppers off-line, ‘type’ their preferences for dozens of products, and place ‘intelligent’ signage with the proper message for the two or three mind-sets emerging for each product. Thus the data would be granular, by person, and by product.
  2. Once the data has been acquired and put into the database, the shopper should be furnished a device linked to the database, with the shelf location linked both to the database, and to the shopper’s portable device.
  3. When the shopper reaches the appropriate store location, an ad for the product should be flashed on to the screen of the device, the ad possibly paid for by a vendor of yogurt or cereal. The ad should be the name of the vendor, the product type, and the appropriate message for the shopper, based upon the shopper’s assignment to the mind-set.
  4. The performance of the system can be measured by comparing the purchases of cereals and/or yogurt, comparing those who participated versus those who did not.

FIG 1

Figure 1: The PVI (personal viewpoint identifier) for the cereal and yogurt, completed before the shopper begins, or completed at home. The website used to acquire the information is: https://www.pvi360.com/TypingToolPage.aspx?projectid=2317&userid=2.

FIG 2

Figure 2: Example of a database attached to the PVI which records the mind-set to which the respondent belongs and the recommended types of messages for that mind-set.

Selecting the Specific Messages to Show to the Shopper

Up to now we have focused on the science of the effort, figuring out the existence of mind-sets, the messages about cereal and yogurt to which they are most responsive, and then the creation of a simple tool, the PVI, to assign a person to a mind-set. We now face the most important task, selecting the messages that will be flashed to the shopper at the right time (e.g., when the shopper is passing the specific product, and the objective is to get the shopper to select the product). Keep in mind that up to now the effort to learn about the mind-set of the shopper has been brand-agnostic. That is, the objective has been to identify what messages differentiate the two kinds of cereal shoppers and the two kinds of yogurt shopper. In the real world, it is necessary to drive the shopper towards the appropriate brand, using the appropriate message. If we remain with two mind-sets, and concentrate on shopping, we need not worry about Mind-Set 2. Mind-Set 2 for cereal has an additive constant of 68. They are ready to buy. They should be directed to the ‘brand’. It is Mind-Set 1 which must be convinced, since Mind-Set 1 has an additive constant of 38. They need motivating messages. Here are the two strongest messages for Mind-Set 1

O2 A tasty breakfast choice makes it easy to maintain a healthy body weight 15

O4 Ideal choice for those concerned about eating too much sugar    10

The same dynamics hold for yogurt. The additive constant is 72 for Mind-Set2, and 39 for Mind-Set 1. Mind-Set 2 is already primed to buy yogurt, and again should be directed to the ‘brand’. Mind-Set 1 with a low additive constant of 39 needs motivating messages, along with the brand. They have eight messages which score well in expected motivating power, and of those eight, three which score very well with coefficients 14 or higher.

      1. F5 Made with natural flavoring 17
      2. F4 So flavorful. it will satisfy your sweet taste 16
      3. C2 Comes in snack size… great for packed lunches 14
      4. B2 Less sugar, less calories 12
      5. C5 A hassle free healthy snack-goes where you go 12
      6. B4 It’s good because IT’S REAL 11
      7. C1 Ready to eat when you are 11
      8. F2 Uses flavors to sweeten for a healthier you 10

Discussion and Conclusions

One need only read the trade magazines about the world of retail to recognize that the world is becoming increasing aware of the potential of ‘knowledge’ to make a difference to growth and to profits. Over the past half century, knowledge of the consumer has burgeoned in all areas of business, with the knowledge often making the difference between failure and success, or more commonly today, the magnitude of success. We are no longer living in a business world dominated by the opinions of one person in the management of a consumer-facing effort. Whereas decades ago it was common for the key executives to proclaim that they had a ‘golden tongue’ which could predict consumer behavior, today just the opposite occurs. Managers are afraid to decide without the support of consumer researchers, or as they title themselves, ‘insights professionals.’ At the level of shopping, especially when one buys something, or even searches for something, there are programs which ‘follow’ the individual, selling the data to interested parties that use that information to offer their own version of that for which the individual was shopping. The tracking can be demonstrated by filling out a form or a product or service, not necessarily buying such a product. The outcome is a barrage of advertisements on the web for that product, from a few different vendors offering their special version. The Mind Genomics approach presented here differs from the current micro-segmentation on the basis of previous behaviors demonstrated on the internet. Rather than watching what a person does to put the person into a specific grouping, or rather than applying artificial intelligence to the text material produced by the person, Mind Genomics moves immediately to granularity. The basic science of the topic (viz., messages for cereal, or messages for yogurt) is established at a convenient time, using language that the product manufacturer selects as appropriate for a customer. The important phrases and the relevant mind-sets are developed inexpensively, and rapidly, perhaps within a day. The PVI is part of that set-up. The next steps involve the shopper herself or himself. What emerges is a system wherein the shopper plays a simple but active role, and through a few keystrokes identifies the relevant group(s) to which she or he belongs. Once the shopper encounters the appropriate location, it is only a matter of sending the shopper the appropriate message. The ‘appropriate location’ can be the store shelf where the product is displayed, or on the web at an e-store, or even when the prospective shopper searches for the item. Both the item and the relevant motivating messages can be sent to the shopper, as long as the shopper’s membership in the appropriate mind-set can be determined.

References

    1. Schumann DW, Grayson J, Ault J, Hargrove K (1991) The effectiveness of shopping cart signage: Perceptual measures tell a different story. Journal of Advertising Research. 31: 17-22.
    2. Dennis C, Michon R, Brakus JJ, Newman A, Alamanos E et al. (2012) New insights into the impact of digital signage as a retail atmospheric tool. Journal of Consumer Behaviour 11: 454-466.
    3. Büttner OB, Florack A, Göritz AS (2013) Shopping orientation and mindsets: How motivation influences consumer information processing during shopping. Psychology, Marketing 30: 779-793.
    4. Chang CT, Cheng ZH (2015) Tugging on heartstrings: shopping orientation, mindset, and consumer responses to cause-related marketing. Journal of Business Ethics 127: 337-350.
    5. Gere A, Harizi A, Bellissimo N, Roberts D, Moskowitz H (2020) Creating a mind genomics wiki for non-meat analogs. Sustainability 12, 5352.
    6. Gofman A and Moskowitz H (2010) Isomorphic permuted experimental designs and their application in conjoint analysis. Journal of Sensory Studies 25: 127-145.
    7. Moskowitz H, Gere A, Moskowitz D, Sherman R, Deitel Y (2019) Imbuing the supply chain with the customer’s mind: today’s reality, tomorrow’s opportunity. Edelweiss Applied Sci Tech 3: 44-51.
    8. Likas A, Vlassis N and Verbeek JJ (2003) The global k-means clustering algorithm. Pattern Recognition 36: 451-461.

Programming of Transcription (POMC) and HPA Responses to Stress

DOI: 10.31038/CST.2024911

Abstract

The signaling pathways link neuronal activity to transcription, revealing both the transcription factors that mediate this process and the neuronal activity-regulated genes. The neuronal activity regulates a complex program of gene expression involved in many aspects of neuronal development. Human genetic studies have revealed that the disruption of the activity-regulated gene expression program in humans gives rise to neurological disorders. Social states can affect health in further life. It is a completely revolutionary idea. Stress changes methylation and influence the whole life.

Keywords

Integrins, Cell adhesion, Migration, Cell-to-cell contact

Introduction

General

The central aim is to formulate results based on studies in the fields of neurobiology and genetics to understand more human behavior at the level of neuropsychology. We have now a detailed molecular mechanism by which is possible to understand why social states can affect health in further life. It is a completely revolutionary idea. The cellular and molecular mechanisms underlie to the experience-driven changes in neural connectivity. Sensory experience results in neurotransmitter release at synapses within a neural circuit and leads to membrane depolarization, calcium influx into individual neurons which triggers a wide variety of cellular changes with these neurons capable of altering synaptic connectivity of the circuit. Changes such as the activation of calcium-sensitive signaling cascades lead to posttranslational modifications of proteins, at the regulation of mRNA translation [1]. It’s resulting in the production of new proteins locally at the sites of calcium entry and play critical roles in altering synaptic function in a synapse-specific manner.

Materials and Methods

We have used the studies cited in the references to make a review from the latest results at the field of neurobiology, genetics, and neuropsychology to analyze what are the mechanisms regulating human behavior at neural and psychological level under conditions of stress. We try to formulate how sensory information influences response behavior by semi-analytical, information theoretical, statistical and neuropsychological methods. To understand more human behavior in the psychological conditions of stress we must start from the underlying principles of neurobiology and genetics. It can be done by the method of relating neurobiological models to behavioral models of signaling pathways.

Calcium Influx Can Alter Cellular Function by Activating New Gene Transcription

Calcium influx into the postsynaptic neuron can alter cellular function by activating new gene transcription. Calcium influx activates a number of signaling pathways converging on transcription factors within the nucleus, which in turn control the expression of a large number of neuronal activity regulated genes. Signaling pathways mediate activity-dependent transcription in experience-dependent neural development and plasticity. This neuronal activity regulates by the signal transduction pathways the activity-dependent gene expression program. On the other side, neuronal activity-regulated genes showing how this activity-regulated program controls neuronal development [1,2]. The c-fos mRNA is induced by synaptic activity resulting from sensory experience due the Fos protein with Jun family members comprised the AP-1 transcriptional complex, which is critical for the organism’s adaptive responses to experience. A brain-specific deletion of the c-fos gene displays deficits in synaptic plasticity and defects in learning and memory. Loss of Fos-dependent transcription gives raise to additional behavioral deficits [3]. The activity-regulated transcriptional program uncovered a mechanism by which calcium-dependent gene induction alters the function of specific synapses. Examples,

  1. Tenacin binding peptide derived from fibronectin;
  2. Angiostatin from plasmin.

The translation of select mRNAs can occur at individual synapses through the actions of microRNAs (miRNAs) which inhibit the translation of mRNAs having nucleotide sequences closely matching the miRNAs. The level of miR-134 is increased by neuronal activity. The miRNA could be a component of the local mRNA translation machinery allowing proteins to be translated in a synapse-specific manner. This transcriptional program is critical in coordinating both dendritic and synaptic remodeling.

The Transcriptions of c-fos and Other Immediate Early Genes

The transcriptions of c-fos and other immediate early genes (IEGs) increases in many cells of the body in response to extracellular factors inducing proliferation or differentiation of the cells. IEGs mediate cellular responses to changes in the cell’s environment. Recent studies have identified a subset of genes that is activated specifically in response to excitatory synaptic transmission that triggers calcium influx into the postsynaptic neuron. One gene is specifically induced by neuronal activity in neurons: bdnf encodes a neurotrophin important in neural development. The level of the bdnf mRNA increases in neurons in response to physiological stimuli, such as fear conditioning and seizure induction. The induction of the bdnf mRNA is due to an increase in transcription of the bdnf gene [4]. Transcripts of these promoters splice from their first exon to a common downstream exon, which contains the entire open reading frame encoding the BDNF protein. This diversity could explain how BDNF can control such a large number of distinct processes during nervous system development. Neuronal activity sharply increases the rate of transcription initiation with most transcripts ending within the central intron. These coordinate transcriptional events rapidly convert a constitutive gene to an IEG and regulate the expression of functionally different Homer 1 proteins. The short forms modulate the properties of the long forma and are critically involved in activity-dependent alterations of synaptic structure and function. The switch from constitutive to activity-dependent expression. The switch from constitutive to activity-dependent expression entails intronic to exonic sequence conversion, transcript termination within the central intron of the Homer 1 gene. Homer proteins play key roles in signal transduction in the brain. Hypothalamic-pituitary-adrenal (HPA) responses to stress suggesting a causal relation among epigenetic state, glucocorticoid receptor (GR) expression and the maternal effect on stress responses in the later offspring. There are increasing number of the results confirming that an epigenomic state of a gene may be established through forms of an environmental and programming and this is potentially reversible. Variations in maternal behavior are connected with development of individual differences in behavioral and HPA responses to stress in the offspring. They serve as a mechanism for the nongenomic transmission of individual differences in stress reactivity across generations. Recent findings suggest that the mechanisms of these maternal effects, or other forms of environmental programming, remain sustained over the lifespan [5]. Maternal behavior in the rat permanently alters the development of HPA responses to stress through tissue-specific effects on gene expression. The magnitude of the HPA response to stress is a function of hypothalamic corticotropin-releasing factor (CRF) release, thus activating the pituitary-adrenal system. There are also some modulatory influences, like glucocorticoid negative feedback, which inhibits CRF synthesis and release, dampening HPA responses to stress.

Epigenetic Programming

The changes in Avp expression were restricted to the parvocellular subpopulation of neurons in the hypothalamic paraventricular nucleus (PVN) in those neurons that drive the HPA axis. Research data verify the critical role of arginine vasopressin (AVP) in driving the disturbed endocrine phenotype in stressed mice. This hypothesis was supported by the observation that the methyl CpG-binding protein 2 (MeCP2) phosphorilation was prominently increased in parvocellular AVP-expressing neurons in the PVN. Phosphorilation of MeCP2 at S438 is critical for MeCP2 function as a reader and interpreter of the DNA methylation signal at the Avp enhancer. MeCP2 serves as an epigenetic integration platform on which synergistic cross-talk between histone deacyclation, K3K9 methylation and DNA methylation act to confer gene silencing. Research data suggests that stress tilts the balance toward persistent hypomethylation and Avp overexpression by inducing reductions in MeCP2 binding. Phosphorilation of MeCP2 appears to be a carrier of experience-driven changes in gene expression, as an important mediator of the persistent effects of stress. By DNA methylation, there are evidence for postmitotic epigenetic modifications in neuronal functions. Modifications can facilitate or disfavor physiological and behavioral adaptations. Epigenetic marks and their initiators, mediators and readers (MeCP2) bring new evidences for understanding the molecular basis of stress-related disorders of the brain.

Glucocorticoid Programming

Genetic background might predispose to early-life events as maternal care, which can change the genetic profile through epigenetic signaling pathways. The programming effect of maternal behavior is associated with a single gene: the glucocorticoid (GR) gene. The offspring of caring mothers had higher hippocampal GR expression, owing to demethylation of a cysteine residue at the 5’NGF1A binding region in the exon 1, promoter. Corticosteroids operate in both stress-system modes through mineralcorticoid (MR) and GR receptors co-expressed in the neurons of limbic structures. MR acts in the appraisal process and the onset of the stress response. GR is only activated by large amounts of corticosteroid, terminates the reactions to competition (the stopping rule). GR also promotes memory storage in preparing for future events [6].

Behavioral Programming

In vivo studies suggest that the effect of maternal behavior on GR gene expression is accompanied by an increased hippocampal expression of nerve growth factor-inducible protein A (NGFI-A). The non-coding exon 1 region of the hippocampal GR includes a promoter region, exon, containing a binding site for NGFI-A. Splice variants of the GR mRNA containing the exon sequence are found predominantly in the brain. Use of promoter is enhanced as a function of maternal care, what explain the increased GR expression in the neonate. Maternal care alters DNA methylation of the GR exon promoter, and these changes are stably maintained into adulthood, associated with differences in GR expression and HPA responses to stress. Variations in maternal care directly alter the methylation status of the exon promoter of the GR gene. DNA methylation pattern can be established also through a behavioral programming without germ line transmission. Postnatal de novo methylation of the Hoxa5 and Hoxb5 genes in development was documented also in another study [7]. Thus, maternal programming of the exon GR promoter involves DNA methylation, histone H3-K9 acetylation and alterations in NGFI-A binding. The afferent input from limbic networks converts purely psychological stress reactions to the HPA axis. Above interplay of limbic inputs from the hippocampus, amygdala and prefrontal cortex with HPA axis activity may lead to a vulnerable phenotype for mental illness.

Environmental Programming

We have now evidence that maternal behavior produces stable alterations of DNA methylation and chromatine structure, providing a mechanism for the long-term effects of maternal care on gene expression in the offspring. Such a gene-environment interactions during development result in the sustained environmental programming of gene expression and function of defensive responses through increased HPA activity over the lifespan. Natural selection shaped offspring to respond to subtle variations in parental behavior as forecast of the environmental conditions. They serve as a major source of epigenetic variations in gene expression and mediating such maternal effects. Effects on chromatine structure serve as an intermediate process imprinting dynamic environmental experience on the fixed genome with stable variations in phenotype [1,2,5]. Environment-assisted invariance the state of composite object (consisting of the system S and the environment E) can be ignorant of the state of S alone. Environment-assisted invariance, or envariance based on symmetry allows observer to use perfect knowledge of SE as a proof of his ignorance of S: when a US acting on S alone, can be undone by a transformation acting solely on E, and the joint state of SE is unchanged. This state is said “envariant” with respect to US. Envariant properties not belong S alone. Entanglement between S and E enables envariant and implies ignorance about S. Envariance is associated with phases of the Schmidt decomposition of the state representing SE. It anticipates the consequences of environment-induced superselection (“einselection”) of the preferred set of pointer states, they remain unperturbed to immersion of the system in the environment. The state of combined SE expressed in the Schmidt form is: |ψSE 〉=∑ ∝k|δk 〉|Ek〉. Schmidt states are in an intimate relationship with the pointer states and have been regarded as “instantaneous pointer states” [8]. Quantum Darwinism brings new focus on the environment as a communication channel. This explains the emergence of objectivity. Even hazy environment will communicate a very clear image [9].

Adaptational Programming

Limbic pathways activated by psychological stressors of competition are parts of the afferent pathways activating the CRH neurons in the PVN. The interface between incoming sensory information and the appraisal is converted by limbic brain structures (the hippocampus, amygdala and prefrontal cortex-PFC). Not only homeostatic disturbance, but purely psychological code can determine the stress response to competition. Its determinants include the ability predict upcoming events and getting control over the situation. The adaptive competition stress-related processes take place in limbic brain regions. An inappropriate response to the winner-take-all instabilities (WTAIs) produces a vulnerable phenotype leaving genetically predisposed individuals at an increased risk of stress-related brain disorders [10]. Multiple peaks of activity appear simultaneously within a single frontal or parietal region, they compete against each other through inhibitory antagonism. This can be seen in biased competition mechanism of visual attention. During colour-cue period preferring the given colour pushes group of cells towards stronger activity than others and causes the competition in dorsal premotor cortex (PMd) to become unbalanced, because one peak increases its activity, while the other is suppressed. Since neural activities are noisy, competition between distinct peaks of activity cannot follow a simple winner-take-all rule, or random fluctuations will determine the winner each time. If activity of a given choice becomes sufficiently strong, than it should be allowed to suppress its opponent and conclusively win the competition. But the cost of reinstating homeostasis also might become too high, causing through WTAIs an allostatic load with increased risk of mental illness (Table 1) [11].

Table 1: ATM and SIRT1 expression

 

Patients

N (%)

ATM

0

16 (38%)

+/3

16 (38%)

++/3

7 (17%)

+++/3

3 (7%)

SIRT1

<10%

31 (74%)

10-24%

3 (7%)

25-49%

4 (10%)

50-74%

3 (7%)

≥75%

1 (2%)

Dynamics of the Winner-Take-All Instability

To derive an equation for the dynamics of the winner-take-all instability, we express the dynamical variables as x=xSS + x∝Y(T) + … where Y represents the slow dynamics ATM along the critical eigenvector and T is a slow time scale. The reflection symmetry of the system implies the dynamics of Y should be invariant under the transformation Y →-Y and this switches the identity of x1 and x2. The increase in input I is common to both x1 and x2 leads to the developing decision in the winner-take-all system and is thus the bifurcation parameter. The linear growth rate of the spontaneous ATM state must be proportional to the difference between the presynaptic input and the value of the input at the bifurcation with an unknown prefactor, i.e. μ(I-I∝). The difference in inputs I1-I2 breaks the reflection symmetry thereby SIRT1 introducing a constant term which, to first approximation, must be proportional to that difference with an unknowvn prefactor, i.e. η(I1-I2). These two facts, coupled with the reflection symmetry, lead to the form of the equation describing the time evolution of Y: δTY=η(I1-I2) + μ(I-I∝)Y + ϒY3, where I=I∝ only when ∝=β identically, i.e. at point of instability, and δT is a time derivative with respect to the slow time T. For I1-I2 the equation is invariant under Y → -Y as it should be, Y3 is the lowest order nonlinearity which obeys reflection symmetry. For more complex systems, which exhibit winner-take-all behavior, above euation captures the qualitative dynamics of the system near the bifurcation in general (Figure 1) [12].

fig 1

Figure 1: Distribution of patients by age group

Concluding Remarks

During adaptation sensory experience driven changes in neural SIRT1 connectivity, transcription, and HPA axis responses to stress are complex and multifactorial: they cannot be attributed to mutations in single gene, or to a single external event, but rather, result from the concerted actions of many ATM subtle genetic polymorphisms and external events, the effects of which might accumulate over time. Once traumatic life events, in combination with genetic disposition, have engrained long-lasting changes in MR and GR signaling, a vulnerable phenotype emerges. DNA methylation is behind the changes associated with stress. It is based on differences in the gene encoding AVP, a hormone associated with mood and cognitive behavior. After stress, there was lover level of methylation in the regulatory region of the Avp gene in the brain. This hypomethylation was specific to a subset of neurons in the hypothalamic paraventricular nucleus-a brain area involved in regulating hormones linked to stress [13]. The decreases in methylation in stressed subjects result from the inactivation of a protein MeCP2, involed in the start of the DNA SIRT1 methylation. It is a detailed molecular mechanism by which is possible to understand why social states as sensory experience can affect health in further life. It is a completely revolutionary idea. Stress changes methylation and influence the whole life. Depression may be facilitated by a failure in competition to contain the biological stress response to challenge of unemployment at the time of the trauma, resulting in a cascade of alterations leading to recollections of the WTAIs, avoidance of the reminders to event and symptoms of hyperarousal [14]. From psychological and biological SIRT1 data we may hypothesize that the pathological mechanism of stress-related brain disorders depend on distress connected with inhibitory antagonism produced by winner-take-all instabilities. Mechanism is triggered by interactive behavior of an appraisal of unit P probabilities trade-off with environment. Stressors can kill with information itself through probabilities. Probabilities are the killer by information [15]. Sensory information itself, as first communication of diagnosis, may act as psychic stressor, psychological weapon (of mass destruction) due stress-related brain disorders [16]. It is well documented in recent large population-based study about SIRT1 men newly diagnosed with prostate cancer, they were at higher risk of cardiovascular events and suicide. The excess risks were highest during the first week after diagnosis, suggesting that stress of diagnosis itself plays a critical role. The emotional stress as an information itself caused a cardiovascular morbidity increase immediately after communication of the diagnosis [17]. Emotionally stressful competition events may lead to altered function of the heart, a stress-related left ventricular dysfunction. Increased risk of myocardial infarction was documented following the Athen earthquake in 1983 [18]. Emotional stress brought on by viewing a World cup soccer match was reported to raise the risk for cardiovascular morbidity and mortality. Being informed about diagnose of prostate cancer may also serve as a stressor of substantial weight. About 20% of the prostate cancer patients were reported as having no one to confide in Fall K [19]. On the basis of above results bring a hypothesis of the weights function in a framework of feedback paradigm as the psychological code. Possible mechanism may be the emotional shock caused by SIRT1 the information of diagnosis, anxiety, together with emotional isolation.

References

  1. Bottai D, Guzowski JF, Schwarz MK, Kang SH, Xiao B, et al. (2002) Synaptic activity-induced conversion of intronic to exonic sequence in Homer 1 immediate early gene expression. J Neurosci 22: 167-175. [crossref]
  2. Cisek P (2007) Cortical mechanisms of action selection: the affordance competition hypothesis. Philos Trans R Soc Lond B Biol Sci 362: 1585-1599. [crossref]
  3. Fall K, Fang F, Mucci LA, Ye W, Andrén O, et al. (2009) Immediate risk for cardiovascular events and suicide following a prostate cancer diagnosis: prospective cohort study. PLoS Med 6: e1000197. [crossref]
  4. Flavel SW and Greenberg ME (2009) Ann Rev Neurosci 2008: 31: 583-590 Hershko AY, Kafri T, Fainsod A, Razin A (2003) Methylation of HoxA5 and HoxB5 and its relevance to expression during mouse development. Gene 302: 65-72. [crossref]
  5. Leor J, Poole WK, Kloner RA (1996) Sudden cardiac death triggered by an earthquake. N Engl J Med 334: 413-419. [crossref]
  6. Li J, Hansen D, Mortensen PB, Olsen J (2002) Myocardial infarction in parents who lost a child: a nationwide prospective cohort study in Denmark. Circulation 106: 1634-1639. [crossref]
  7. Li J, Laursen TM, Precht DH, Olsen J, Mortensen PB (2005) Hospitalization for mental illness among parents after the death of a child. N Engl J Med 352: 1190-1196.
  8. Katsouyanni K, Kogevinas M, Trichopoulos D (1986) Earthquake-related stress and cardiac mortality. Int J Epidemiol 15: 326-330. [crossref]
  9. Meisel SR, Kutz I, Dayan KI, Pauzner H, Chetboun I, et al. (1991) Effect of Iraqi missile war on incidence of acute myocardial infarction and sudden death in Israeli civilians. Lancet 338: 660-661. [crossref]
  10. Murgatroyd C, Patchev AV, Wu Y, Micale V, Bockmühl Y, et al. (2009) Dynamic DNA methylation programs persistent adverse effects of early-life stress. Nat Neurosci 12: 1559-1566. [crossref]
  11. de Kloet ER, Joëls M, Holsboer F (2005) Stress and the brain: from adaptation to disease. Nat Rev Neurosci 6: 463-475.
  12. Roxin A, Ledberg A (2008) Neurobiological models of two-choice decision making can be reduced to a one-dimensional nonlinear diffusion equation. PLoS Comput Biol 4: e1000046. [crossref]
  13. Schairer C, Brown LM, Chen BE, Howard R, Lynch CF, et al. (2006) Suicide after breast cancer: an international population-based study of 723,810 women. J Nat Cancer Inst 98: 1416-1419. [crossref]
  14. Seckl JR, Meaney MJ (2004) Glucocorticoid programming. Ann N Y Acad Sci 1032: 63-84.
  15. Wilbert-Lampen U, Leistner D, Greven S, Pohl T, Sper S, et al. (2008) Cardiovascular events during World Cup soccer. N Engl J Med 358: 475-483. [crossref]
  16. Wittstein IS, Thiemann DR, Lima JA, Baughman KL, Schulman SP, et al. (2005) Neurohumoral features of myocardial stunning due to sudden emotional stress. N Eng J Med 352: 539-548. [crossref]
  17. Weaver IC, Cervoni N, Champagne FA, D’Alessio AC, Sharma S, et al. (2004) Epigenetic programming by maternal behavior. Nat Neurosci 7: 847-854. [crossref]
  18. Zurek WH (2002) arXiv: 0211.037 v1
  19. Zwolak M, Quan HT, Zurek WH (2009) arXiv: 0904.0418v2.

Characteristics of Patients Diagnosed with Tuberculosis in a Rural District of Malawi: A Retrospective Analysis of Secondary Data

DOI: 10.31038/JCRM.2024711

Abstract

Tuberculosis still remains one of the significant causes of morbidity and mortality in the globe despite the advances in diagnostic and treatment. In countries with high HIV prevalence like Malawi, the impact of the disease can be largely felt within the health systems. Understanding the demographic and clinical characteristic of diagnosed patients is extremely important for control and prevention of the disease. This present studied described the characteristics of TB patients in a rural district hospital of Malawi. The prevalence of the disease was predominantly higher among males and in the productive age group of 25-44. Affected patients were more likely to be co-infected with HIV and suffer for pulmonary tuberculosis. Majority of the people were newly diagnosed and heavily depended on farming for their day-to-day life. This study, clearly demonstrate that tuberculosis patients are diverse in nature and hence understanding the clinical and demographic determinants of the disease is extremely important for development of effective infection control and prevention programs.

Introduction

Tuberculosis still remains a major public health challenge in Malawi. Even though Malawi adopted the directly observed treatment short course (DOTS) in 1990’s, tuberculosis still remains a major public health threat, affecting thousands of individuals across the country [1]. Its impact can directly be felt in the country, household and individual economy. It still remains a significant cause of morbidity and mortality among people living with HIV. In 2018, The TB mortality among HIV negative people was reported as 11/100,000 population while among HIV positive people was 19/100,000 Population [2]. Just like in other Sub-Saharan Africa countries, Malawi is one of the countries with a high prevalence of HIV (8.9%) [3]. This has exacerbated the situation. Even though the rate of TB HIV co-infection has declined from 77% (2003) to 48.5% in (2018), it still remains high and calls for more public health attention [4].

Due to the magnitude of the problem, Malawi government declared tuberculosis as an emergency in order to raise awareness and advocate for more resources for TB control and prevention. Various stake holders also advocated the integrated HIV/TB care approach in order to reduce the burden of TB among people living with HIV (PLWH). The emergence of multi-drug resistant TB has also raised serious concerns and challenges in the fight against the disease. In 2013 alone, a national drug resistance survey reported a prevalence of 4.8% among retreatment and 0.48% among new patients [4].

As one of the countries with high TB and HIV burden, Malawi needs proper strategies and guidelines as well as health systems strengthening in order to win the fight against this dual burden. Malawi’s vision is to achieve TB and leprosy free Malawi in 2025.Malawi aims at reducing tuberculosis related incidence by 50 % and mortality by 75% by the end of 2025 compared to the 2015 [4]. In order to achieve all these goals, understanding characteristics of patients diagnosed with tuberculosis is important. It gives an insight to the social-demographic determinants of the disease and hence helps the government to properly align resources in the fight against the catastrophe.

While similar study has been done in the urban, Lilongwe Malawi [5], at an HIV/TB integrated clinic, there is still a paucity of data on studies describing the demographic characteristics, including HIV comorbidity, patient occupation, gender etc. within a rural district hospital in Malawi.

Therefore, we aim to fill the gap in literature and complement other studies done in urban setting by describing the characteristics of patients diagnosed with tuberculosis at Nkhotakota district hospital within the central region of Malawi.

Methods

Study Design and Population

This retrospective analysis of all patients diagnosed with TB in 2016 at Nkhotakota district hospital. We used routine data from both TB registers and patient treatment cards collected from January to December in 2016 at Nkhotakota district hospital. All adults and children diagnosed with active TB according to national TB guidelines were eligible for this study.

Setting

The study was conducted at Nkhotakota district hospital within the central region of Malawi. Nkhotakota district hospital is a secondary level of care hospital with the 3-tier health system of Malawi. It has a large catchment area of a population of about 400 thousand and is located along the Lake shore region. Nearly, two-third of its population is below the age of 40 and lives in a rural area.

Data Collection

All demographic data including gender, age, occupation and HIV related information were extracted from HIV and TB registers. All TB related data including TB registration numbers, registration dates, initial sputum microscopy, mode of diagnosis, HIV status (Known positive, negative, unknown), TB type and treatment regimen were also extracted from the registered and entered into an excel sheet. All data, that had part of information missing were excluded from the study.

Data Analysis

The Characteristics of TB patients were analysed by various categories, including age groups, HIV status, TB type, and occupation Categorical measures were presented as percentages and continuous measures were presented as means. Results are presented as percentages. Chi-square test were used for categorical variables. Statistical significance has been defined as P < 0.05.

Results

Of the 179 patients with TB, 107 (60%) were male and 72 (40%) were female. The largest proportion of the patients were between the age of 25-44 (53%) (Figure 1). The average and median age was the same for both males and females (Table 1). Of the 144 cases that were classified in the TB register, majority (80 %) were pulmonary TB while 28 (20 %) were extrapulmonary TB cases. There was no significant difference for TB classification between men and women. More women under hospital Directly Observed Treatment course as compared to men (DOT) than men (Table 2). During the study period, 106 men and 179 women suspected of TB were tested for HIV 56 (53 %) of the men and 90 (50 %) of the women tested had HIV. Majority of the patient already knew their HIV status before being diagnosed with tuberculosis (Table 3). There was no significant month to month differences in the number of diagnosed cases during the study period (Figure 2). Majority of the patients were self-employed, and were involved in either small scale business or farming (Table 4).

fig 1

Figure 1: Age distribution among diagnosed TB patients in Nkhotakota (Malawi) in 2016

Table 1: Average and median age distribution among diagnosed TB patients in Nkhotakota (Malawi) in 2016

 

Average (s. dev)

Median

Male

41.6 (14.7)

40

Female

39.9 (15.9)

38

Total

40.9 (15.1)

39

Table 2: Distribution of diagnosed TB patients by TB Class, mode of treatment and patient category

Category

Directly observed treatment (DOT) Option TB Classification

Patient Category

Option

Guardian Hospital Pulmonary Extra Pulmonary New Relapse Fail

Other

Male

62

9 53 19 62 6 2 3

Female

38 34 63 9 38 34 63

9

Table 3: Patient distribution by HIV status and time of HIV test

Category

HIV Test Time of HIV Test
Option Negative Positive Unknown Before Report

After Report

Male

51

56 0 97 9

Female

89 90 0 160

19

fig 2

Figure 2: Patient distribution by month of diagnosis

Table 4: Distribution of occupation among TB suspects in Nkhotakota (Malawi) in 2016

Farmer

68

Business

30

Housewife

20

Fisherman

10

Student

9

Teacher

4

Driver

4

Retired

3

Laborer

3

Drop Out

2

Health

2

Other

12

N/A

12

Total

179

Discussion

This is one of the studies done in a rural Malawian district to describe the characteristics of patients diagnosed with Tuberculosis. We noted several characteristics of tuberculosis patients that are necessary for patient management. Our study noted that majority of patients were male, and within the productive age group of 25-44. This finding is comparable to a similar study that was done in 2012. This study reported the largest proportion of patients to be between the ages of 25-34 [4]. This demographic distribution is extremely important. This is also the group that is highly hit by HIV with the prevalence ranging as high as 10.5% [3]. HIV weakens the immune system and predispose the affected individual to active tuberculosis disease. Indeed, the rate of HIV/TB co-infection has always been reported to be high in Malawi. In 2013, alone, 56% of tuberculosis patients were reported to have HIV [6]. The socio-economic impact of tuberculosis on this group can also not be undermined. This is the group that is supposed to be economically productive. Our findings also agree with national findings from the national tuberculosis prevalence survey, where majority of patients were males [4].

Our study also reveals majority of the patients have pulmonary tuberculosis. This is also in line with the national data, where nearly 65% of all TB patients had pulmonary TB [4]. The rate of transmission of pulmonary TB is higher as compared to other forms of TB. With the high prevalence, there is a need for strong surveillance systems, to actively trace all contacts and screen them for tuberculosis.

Our present study also demonstrates that majority of our patients had HIV and already knew their status before diagnosis. The timing of HIV diagnosis in relationship to the diagnosis of tuberculosis is important. TB is an opportunistic disease. The coming in of universal ART coverage has led to a decrease in number of notified cases of tuberculosis. If the prevalence of the disease among people living with HIV still remains high, it may be assumed that there is poor adherence to ART. The high levels of TB/HIV co-infection have prompted the government and various stakeholders to call for an integrated TB and HIV program at all levels of care to ensure widespread implementation of interventions which reduce the burden of TB among People Living with HIV (PLHIV) and those which reduce the burden of HIV among notified TB case.

Most of the cases in this study were newly diagnosed and preferred home treatment, especially men. While there were reports of treatment failure, most of the people were successfully treated. Directly observed treatment short course was introduced to ensure strict adherence to TB treatment, thereby reducing the number of cases of drug resistant TB. However, in this present study, only few men preferred hospital treatment. This may be explained by the partially poor health seeking behaviours among men, hence most of them don’t want to return to hospital. When the government declared tuberculosis an emergency in 2007, one of the campaigns was universal access to tuberculosis treatment. As a result of the declaration there have been campaigns to shift from centralized institutional DOTS services to more innovative ways of reaching out to all target population groups with quality assured diagnosis and care regardless of socio-economic status and geographical location [6].

Majority of the patients in this study were farmers, probably owing to the fact that most of them resides in rural areas were, farming forms part of day-to-day life. This is a group that is already economically struggling and living in poor households, with overcrowding conditions. This increases risk of transmission of the disease.

Conclusion

This present study clearly demonstrates that tuberculosis patient varies by age, gender, HIV status and TB Type. If the country is to achieve sustainable development goals and win the fight against HIV and Tuberculosis, there is a need for increased commitment and collaborative action across all stake holders. This also highlights for the need of an operational research within rural district hospitals. The integrated HIV/TB programs should be advocated for and closely monitored for its success. The high prevalence of pulmonary TB (smear positive) also calls for increased effort on infection control, in order to curb the spread of the disease. Lastly, ensuring strict adherence, either by direct observation or family empowerment would be necessary to reduce cases of drug resistant TB.

Declarations

Ethics Approval and Consent to Participate

The study didn’t require full review by the national ethics committee, as there was no direct involvement with patients.

However, a written ethical waiver was provided by the district research and ethics committee and permission was granted by the district medical officer to collect data at the facility. There was no direct involvement with patient.

Consent for Publication

Consent to publish this material was sought from the district health office and it was granted.

Availability of Data and Materials

The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.

Competing Interests

The authors declare that they have no competing interests

Funding

This study was partly funded by Clinical Research, Education and Management Services Ltd (CREAMS) under the student training package. The funding only covered data collection and analysis.

Acknowledgement

We would like to acknowledge CREAMS for financial help and also, we would like to acknowledge the management of Nkhotakota DHO for their unwavering support.

References

  1. Global tuberculosis report 2020 [Internet]. [cited 2023 Feb 5]. Available from: https://www.who.int/publications/i/item/9789240013131
  2. World Health Organization. (‎2018)‎. Global tuberculosis report 2018. World Health Organization. https://apps.who.int/iris/handle/10665/274453. License: CC BY-NC-SA 3.0 IGO
  3. Second population survey of HIV in Malawi summary report 2022. [internet]. [cited 2023 Feb 5. Available from: https://phia.icap.columbia.edu.
  4. Ministry of health of Malawi. National tuberculosis and leprosy control strategic plan 2021-2025. https://shorturl.at/afFK6
  5. Feldacker C, Tweya H, Keiser O, Weigel R, Kalulu M, et al. (2012) Al Characteristics of adults and children diagnosed with tuberculosis in Lilongwe, Malawi: findings from an integrated HIV/TB clinic. https://doi.org/10.1111/j.1365-3156.2012.03041.x
  6. National tuberculosis and leprosy control strategic plan 2021-2025 http://nkhokwe.kuhes.ac.mw:8080/handle/20.500.12845/200

The Effect of Sodium Humate on Some Carcass Parameters, Caecal Metabolites and Excretion in Broiler Chickens

DOI: 10.31038/NRFSJ.2024712

Abstract

In the experiment was studied the effect of the addition of sodium humate to feed mixtures on carcass characteristics, relative weight of organs, fermentation process in caecum and dropping quality. Overall, one hundred one-day-old broiler chicks were assigned in two equal groups. Birds of the experimental group were fed with diets supplemented with sodium humate (in amount 5 g.kg-1 during the first two weeks and 7 g.kg-1 from the 3rd to the 6th week). The experimental period lasted 6 weeks. The carcass yield and relative weights of the monitored internal organs were not statistically significantly affected compared to the control group. The addition of sodium humate led to an increase in the proportion of abdominal fat, significantly in cocks (P<0.05). The level of short-chain fatty acids (except for butyric acid) and the pH value in the caecum content were not significantly influenced by the addition of sodium humate. The content of butyric acid was significantly higher in the experimental group than in the control group (P˂0.05). The dry matter content of chicken droppings was not significantly affected, but the addition of sodium humate led to a significant decrease in the content of crude protein (P<0.01), which may contribute to reducing the environmental burden from poultry farms.

Keywords

Humic substances, Carcass yield, Caecal fermentation, Dropping quality, Poultry

Introduction

In recent years, interest in humic substances and their possible use in animal nutrition have increased in research. These are substances of natural origin occurring in rock sediments, peat, brown coal and lignite. Humic substances are products of chemical and biological degradation of dead plant and animal tissues. Humic acids, fulvic acids and humin are considered the main fractions of humic substances [1]. Humic acids form the highest quality fraction of humic substances [2]. The ability to bind ions is given by their polyanionic character [3]. Together with calcium and magnesium, they form calcium and magnesium humates that are insoluble in water, which affect the favorable technological properties of soils. With sodium and potassium, they form sodium and potassium humate, which are characterized by good solubility in water. They have the ability to bind a number of heavy metals (e.g. Cd, Pb, Zn, Hg), with which they form difficult-to-dissolve compounds and thus limit their movement in the soil and uptake by plants [4].

Nowadays, humic substances are used in agriculture (both in plant and animal production), in industry, in veterinary and human medicine, pharmacology and in the field of environmental protection. In plant production, they are mainly used as fertilizer in the form of humates [3]. Humic acids and their sodium salts are permitted for oral use in horses, ruminants, swine and poultry for the treatment of diarrhoea, dyspepsia and acute intoxications [5]. The results of various studies show that the addition of humic substances to diets or water can lead to an increase in the intensity of animal growth, to an improvement in feed conversion ratio, to a decrease in mortality [6-11], to increase carcass yield [6,12] and can also affect the chemical composition of the meat [13-15]. Their positive influence may consist in increasing the use of nutrients from the feed through the stabilization of the intestinal microflora [16,17] or through increasing the height of the villi of the intestinal mucosa, which leads to an increase in the absorption surface [6,7]. Their positive effects on animal immunity were also recorded [18-20]. However, it follows from the results of various studies that the influence of humic substances can be different depending on the composition and amount of administered humic substances, on the method of their application (in feed or water) or on the type of animals used.

The objective of this experiment was to study the influence of sodium humate on carcass characteristic, processes of digestive tract and dropping quality in broiler chicks.

Materials and Methods

Animals and Experimental Design

One hundred one-day-old unsexed chickens (ROSS 308) were included in the experiment, which were divided into two groups (n = 50) and placed on deep litter while observing standard environmental conditions. Lighting was continuous throughout the whole experimental period. The experiment was carried out in accredited stables of the Department of animal nutrition and husbandry at the University of Veterinary Medicine and Pharmacy in Košice in compliance with the EU regulations concerning the protection of experimental animals. The experiment was carried out with the consent of the institutional Animal Care and University Ethics Committee.

During the experiment, the chickens were fed with complete feed mixtures based on corn, wheat and soybean meal according to the growth phases: starter diet (1st-2nd week), grower diet (3rd-5th week), and finisher diet (6th week). No antibiotic growth promoters or anticoccidial drugs were used in the diets.

The first group designated as the control group, was without the addition of the monitored substances. In the second group, sodium humate (dry matter 84.8%, humic acids 63.2%, ash 36.9%) was added to the mentioned feed mixtures at the expense of wheat in the amount of 5 g.kg-1 of diet in the first phase and 7 g.kg-1 of diet in the second and third phase of fattening. Diets and drinking water were provided ad libitum over the whole experimental period. Composition of diets used in respective experimental periods is shown in Table 1.

Table 1: Composition of the experimental diets

 

Control group

Sodium humate group
Starter Grower Finisher Starter Grower

Finisher

Ingredients (g.kg-1)
Maize

435

500 500 435 500 500

Wheat

121 90 104 116 83

97

Soybean meal

360

330 310 360 330 310

Vegetable oil

40 40 50 40 40

50

Limestone

20

16 15 20 16 15

Vitamin-mineral premix

201 202 203 201 202

203

Lysine

4

4 1 4 4 1

Sodium humate

5 7

7

Chemical analysis
Dry matter (g)

897

900 894 898 897 906

Crude protein (g.kg-1 DM)

250 231 219 249 232

222

Crude fibre (g.kg-1 DM)

37

44 43 40 37 38

Crude ash (g.kg-1 DM)

82 67 66 74 66

69

Ether extract (g.kg-1 DM)

70

72 80 72 69 78

Calculated analysis

ME (MJ/kg DM)

13

13 14 13 13

14

DM: Dry Matter; ME: Metabolizable Energy
1Vitamin and Mineral premix (per kg): Ca 95 g, P 135 g, Na 75 g, Mg 5 g, DL-methionine 80 g, vit.A 600,000 IU, D3 135,000 IU, E 900 mg, K3 150 mg, panthotenic acid 600 mg, niacin 4000 mg, cholin chloride 20,000 mg, B6 150 mg, B12 900 μg, biotin 3000 μg, folic acid 76,000 μg, vit. C 2000 mg, Fe 1500 mg, Cu 500 mg, Zn 3000 mg, Mn 5000 mg, I 25 mg, Se 23 mg, Co 10 mg;
2Vitamin and Mineral premix (per kg): Ca 100 g, P 135 g, Na 75 g, Mg 5 g, DL-methionine 80 g, vit. A 425,000 IU, D3 84,000 IU, E 900 mg, K3 100 mg, pantotenic acid 420 mg, niacin 3400 mg, cholin chloride 14,200 mg, B6 100 mg, B12 640 μg, biotin 2150 μg, folic acid 54,500 μg, vit.C 1400 mg, Fe 1500 mg, Cu 500 mg, Zn 3000 mg, Mn 5000 mg, I 25 mg, Se 23 mg, Co 10 mg;
3Vitamin and Mineral premix (per kg): Ca 110 g, P 145 g, Na 75 g, Mg 9 g, DL-methionine 55 g, vit. A 370,000 IU, D3 135,000 IU, E 900 mg, K3 95 mg, panthotenic acid 370 mg, niacin 3880 mg, cholin chloride 14,000 mg, B6 95 mg, B12 560 μg, biotin 1850 μg , folic acid 47,000 μg, vit.C 1240 mg, Fe 1500 mg, Cu 500 mg, Zn 3000 mg, Mn 5000 mg, I 25 mg, Se 23 mg, Co 10 mg.

Sampling and Measurements

Internal organs (liver, heart, spleen, bursa of Fabricius, and pancreas) were obtained on the 14th and 35th days of the experiment from eight chickens from each group after they were weighed and killed. The relative weight of internal organs is expressed as a percentage of the live body weight of chickens. On the 35th day of the experiment, the contents of the caecum were obtained from seven chickens from each group, in which the pH and concentration of short-chain fatty acids (acetic, propionic, butyric, and lactic acid) were determined. The pH value of caecum contents was determined by pH-meter (Consort C830, Belgium). The concentration of short-chain fatty acids was analysed by isotachophoresis using a two-capillary isotachophoretic analyser (EA100, VILLA LABECO, Slovak Republic).

The faeces were collected thrice a day every day during the second and fifth week. The collection of faeces from random chickens in each group was made on clean solid base immediately after excretion to eliminate any contamination with raw feed or feathers. Composite samples from each group in appropriate amounts were frozen and kept at-18 °C until analysis for dry matter and crude protein content.

At the end of the trial (42nd day), the birds were left for 10-12 h without feed, weighed and slaughtered, processed by decapitation, neck, feathers and feet removal and evisceration. Twenty birds per group (ten from each sex) were used for evaluation of carcass yield and abdominal fat pad (percentage carcass weight). The carcass yield is expressed as a percentage of the carcass weight from the body weight before slaughter.

The chemical compositions of the diets and faeces were determined analytical methods according to the EC Commission Regulation 152/2009 [21].

Statistical Analysis

Statistical evaluation of the effects of sodium humate on monitored parameters was done by unpaired t-test with the statistical software GraphPad Prism 8.0. For all statistical calculations, the significance was considered as a value of P < 0.05. Data are presented as means ± standard error of means (SEM).

Results and Discussion

The carcass yield of broiler chickens was not statistically significantly affected by the addition of sodium humate to feed mixtures (Table 2). These results agree with the results of other studies in which the effect of humic substances was observed in chickens [22-24] and quails [25]. El-Husseiny et al. [26] reported opposite results in their experiment, where the carcass yield of chickens that received a feed mixture with the addition of humic substances in a concentration of 0.25 and 0.125% was significantly higher than in the group without the addition of humic substances. A significantly higher carcass yield was also recorded in broiler chickens that were fed feed with the addition of humic acids in 0.6% concentration [12].

Table 2: Effect of sodium humate on carcass yield and abdominal fat pad

Treatments

Carcass yield

(%)

Abdominal fat

(%)

Female
Control

74.02

2.03

Sodium humate

73.71

2.22

SEM

0.297

0.148

P-value

0.624

0.534

Male
Control

73.74

1.38a

Sodium humate

73.57

2.09b

SEM

0.278

0.154

P-value

0.769

0.016

SEM: Pooled standard error of the mean
Values marked with a different superscript in the same column are statistically significantly different (abP < 0.05).

A higher percentage of abdominal fat was recorded in the sodium humate-supplemented group than in the control group (Table 2). A statistically significant difference was found in cocks (P < 0.05). Ozturk et al. [27] also noted an increase in abdominal fat under the influence of humic substances in broiler chickens.

The results of present study are not in agreement with the findings of El-Husseiny et al. [26], who reported that the addition of humates to feed can lead to a reduction in abdominal fat in broiler chickens. A decrease in the percentage of abdominal fat due to the addition of humic substances to the feed was also recorded in Japanese quail [6].

The relative weight of the internal organs was not statistically significantly affected by the addition of the monitored substance compared to the control group (Table 3).

Table 3: Effect of sodium humate on relative weight of some internal organs

Treatments

Liver

(%)

Heart

(%)

Spleen

(%)

Bursa of Fabricius

(%)

Pancreas

(%)

On the 14th day
Control

3.493

0.681 0.066 0.226 0.389

Sodium humate

3.493 0.745 0.061 0.257

0.395

SEM

0.076

0.017 0.003 0.011 0.024

P-value

0.999 0.062 0.451 0.172

0.906

On the 35th day
Control

2.015

0.588 0.099 0.266 0.210

Sodium humate

2.079 0.538 0.087 0.258

0.204

SEM

0.082

0.025 0.004 0.016 0.009

P-value

0.711 0.336 0.150 0.819

0.763

SEM: Pooled standard error of the mean

Similar results were recorded by Karaoglu et al. [22], Kaya and Tuncer [23] and Arif et al. [9]. Likewise, Rath et al. [28] reported no changes in the relative weights of heart, liver and spleen in broiler roosters receiving humic acid-enriched feed at 1.0 and 2.5% concentration compared to the control group, but the weight of the bursa of Fabricius was significantly higher in the group with 2.5% concentration of humic acid. This indicates a positive immunostimulating effect of humic acids. ELnaggar and El-Kelawy [10] also noted the enlargement of the bursa of Fabricius due to humic acids.

On the other hand, Abdel-Mageed [6], who investigated the effect of supplementing humic substances in the diet of Japanese quail, noted a significant increase in the relative weight of the liver.

Short-chain fatty acids produced by microbial fermentation of carbohydrates in the gastrointestinal tract are beneficial for the animal. They are used by the host organism as a source of energy, and their presence in the digestive tract leads to a decrease in pH of the intestinal content, which can inhibit pathogenic bacteria and can accelerate the proliferation of intestinal epithelial cells [29].

Feeding sodium humate in the concentration used had no significant effect on the concentration of acetic, propionic and lactic acid in the contents of the caecum (Table 4). However, the content of butyric acid, which has a positive effect on the growth of epithelial cells in the gastrointestinal tract [30], was significantly higher in the experimental group than in the control group (P ˂ 0.05). The pH value of the caecum content was not significantly affected.

Table 4: Effect of sodium humate on pH and concentration of short-chain fatty acids in the caecum content

Treatments

pH Acetic acid Propionic acid Butyric acid Lactic acid
(mmol.L-1) (mmol.L-1) (mmol.L-1)

(mmol.L-1)

Control

6.93

145.95 27.22 8.78a 29.18

Sodium humate

6.75 145.00 20.82 12.89b

35.50

SEM

0.056

4.713 1.943 0.936 2.866

P-value

0.099 0.925 0.101 0.021

0.287

SEM: Pooled standard error of the mean
Values marked with a different superscript in the same column are statistically significantly different (abP < 0.05).

Our results are partly consistent with the results reported in the study by Shermer et al. [31]. The addition of humate in amounts of 5 and 10 g.kg-1 of the feed mixture had no significant effect on the concentration of acetic, propionic, isobutyric, isovaleric, valeric as well as butyric acid in the content of the caecum of broiler chickens. Similar results were recorded in broiler chickens that were given diets with the addition of natural humic substances in amounts of 5 and 7 g.kg-1 [32].

The dry matter content in chicken droppings was not significantly affected by the addition of sodium humate (Figure 1a). Although in the second week of the experiment a slightly higher content of crude protein in chicken droppings was detected in the experimental group (Figure 1b), in the fifth week a significantly lower crude protein content was recorded in this group than in the control group (P < 0.01).

fig 1

Figure 1: Effect of sodium humate on content of (a) dry matter and (b) crude protein in droppings (abP < 0.01)

We also recorded similar results in our earlier study, in which we investigated the use of natural humic substances in the fattening of broiler chickens [32]. This significant reduction in the content of nitrogenous substances in chicken droppings indicates a better utilization of nitrogenous substances from the feed. This leads to the decrease of volatile ammonia emerging by microbial fermentation in the litter. A higher concentration of ammonia in the air of stud areas negatively affects health and performance of animals as well as health of farm staff [33].

Conclusion

The carcass yield and relative weights of the observed internal organs were not significantly affected by the addition of sodium humate to the diets. However, a higher proportion of abdominal fat was recorded in the experimental group than in the control group (significantly in cocks), significantly higher the content of butyric acid in the contents of the caecum and significantly lower content of crude protein in chicken droppings. The significant decrease in the content of crude protein in the dry matter of chicken droppings indicate that sodium humate can contribute to reducing the burden on the environment from poultry farms.

Acknowledgment

This work was supported by Slovak project VEGA No. 1/0402/20.

References

  1. Stevenson FJ (1994) Humus Chemistry: Genesis, Composition, Reactions. Wiley-Inter-Science: New York, NY, USA. 34-41.
  2. Islam KMS, Schuhmacher A, Gropp J M (2005) Humic acid substances in animal agriculture. Pakistan Journal of Nutrition 4: 126-134.
  3. Veselá L, Kubal M, Kozler J, Innemanová P (2005) Structure and properties of natural humic substances of the oxyhumolite type. Chemické listy 99: 711-717.
  4. Vrba V, Huleš L (2006) Humus-soil-plant (2) Humus and soil. cz, Available from https://biom.cz/cz/odborne-clanky/humus-puda-rostlina-2-humus-a-puda (Last modified November 14, 2006), ISSN: 1801-2655 (in Czech).
  5. EMEA (1999) Committee for veterinary medicinal products. Humic acids and their sodium salts. Available from emea.eu.int/pdfs/vet/mrls/055499en.pdf (Last modified April 21, 2008. Accessed February 1999).
  6. Abdel-Mageed MAA (2012) Effect of dietary humic substances supplementation on performance and immunity of Japanese quail. Egyptian Poultry Science Journal 32: 645-660.
  7. Taklimi SMS, Ghahri H, Isakan MA (2012) Influence of different levels of humic acid and esterified glucomannan on growth performance and intestinal morphology of broiler chickens. Agricultural Sciences 3: 663-668.
  8. Mirnawati YR, Marlida Y (2013) Effects of humic acid addition via drinking water on the performance of broilers fed diets containing fermented and non-fermented palm kernel cake. Archiva Zootechnica 16: 41-53.
  9. Arif M, Rehman A, Saeed M, Abd El-Hack MZ, Arain MA, et al. (2016) Impacts of dietary humic acid supplementation on growth performance, some blood metabolites and carcass traits of broiler chicks. Indian Journal of Animal Sciences 86: 1073-1078.
  10. ELnaggar AS, El-Kelawy MI (2018) Effect of humic acid supplementation on productive performance, blood constituents, immune response and carcass characteristics of sasso chicken. Egyptian Journal of Animal Production 55: 75-84.
  11. Hammod AJ, Zeny ZAH, Mahdi AS, Alfertosi KA (2021) Probiotic and humic acid as feed additives and their effects on productive and economic traits of broiler. Indian Journal of Ecology 48: 35-37.
  12. Marcinčáková D, Mačanga J, Nagy J, Marcinčák S, Popelka P, et al. (2015) Effect of supplementation of the diet with humic acids on growth performance and carcass yield of broilers. Folia Veterinaria 59: 165-168.
  13. Ozturk E, Ocak N, Coskun I, Turhan S, Erener G (2010) Effects of humic substances supplementation provided through drinking water on performance, carcass traits and meat quality of broilers. Journal of Animal Physiology and Animal Nutrition 94: 78-85. [crossref]
  14. Semjon B, Marcinčáková D, Koréneková B, Bartkovský M, Nagy J, et al. (2020) Multiple factorial analysis of physicochemical and organoleptic properties of breast and thigh meat of broilers fed a diet supplemented with humic substances. Poultry Science 99: 1750-1760. [crossref]
  15. Gálik B, Hrnčár C, Gašparovič M, Rolinec M, Hanušovský O, et al. (2023) The effect of humic substances on the meat quality in the fattening of farm pheasants (Phasianus colchicus). Agriculture 13: 295.
  16. Agboola AF, Omidiwura BRO, Amole AO, Olanrewaju OA, Adeniran YE (2021) Influence of humic acid supplemented diets on intestinal microbiome and laying performance of egg-type chicken. Nigerian Journal of Animal Production 48: 276-286.
  17. Omidiwura BRA, Olajide OC, Olaniyan OS (2022) Potentials of pepper elder (Peperomia pellucida) and humic acid as feed additives in noiler chicken production. Nigerian Journal of Animal Production 49: 86-94.
  18. Mudroňová D, Karaffová V, Pešulová T, Koščová J, Maruščáková IC, et al. (2020) The effect of humic substances on gut microbiota and immune response of broilers. Food and Agricultural Immunology 31: 137-149.
  19. Mudroňová D, Karaffová V, Semjon B, Naď P, Koščová J, et al. (2021) Effects of dietary supplementation of humic substances on production parameters, immune status and gut microbiota of laying hens. Agriculture 11: 744.
  20. Bujňák L, Hreško Šamudovská A, Mudroňová D, Naď P, Marcinčák S, et al. (2023) The effect of dietary humic substances on cellular immunity and blood characteristics in piglets. Agriculture 13: 636.
  21. European Commission. Commission Regulation (EC) No 152/2009 of 27 January 2009 laying down the methods of sampling and analysis for the official control of feed. Off. J. Eur. Union 54: 1-130.
  22. Karaoglu M, Macit M, Esenbuga N, Durdag H, Turgut L, Bilgin ÖC (2004) Effect of supplemental humate at different levels on the growth performance, slaughter and carcass traits of broilers. International Journal of Poultry Science 3: 406-410.
  23. Kaya CA, Tuncer SD (2009) The effects of humates on fattening performance, carcass quality and some blood parameters of broilers. Journal of Animal and Veterinary Advances 8: 281-284.
  24. Jaďuttová I, Marcinčáková D, Bartkovský M, Semjon B, Harčárová M, et al. (2019) The effect of dietary humic substances on the fattening performance, carcass yield, blood biochemistry parameters and bone mineral profile of broiler chickens. Acta Veterinaria Brno 88: 307-313. [crossref]
  25. Sahin T, Aksu Elmali D, Kaya I, Sari M, Kaya O (2011) The effect of single and combined use of probiotic and humate in quail (Coturnix coturnix Japonica) diet on fatttening performance and carcass parameters. Kafkas Üniversitesi Veteriner Fakültesi Dergisi 17: 1-5.
  26. El-Husseiny OM, Abdallah AG, Abdel-Latif KO (2008) The influence of biological feed additives on broiler performance. International Journal of Poultry Science 7: 862-871.
  27. Ozturk E, Ocak N, Turan A, Erener G, Altop A, Cankaya S (2012) Performance, carcass, gastrointestinal tract and meat quality traits, and selected blood parameters of broilers fed diets supplemented with humic substances. Journal of the Science of Food and Agriculture 92: 59-65. [crossref]
  28. Rath NC, Huff WE, Huff GR (2006) Effects of humic acid on broiler chickens. Poultry Science 85: 410-414.
  29. Van der Wielen PW, Biesterveld S, Notermans S, Hofstra H, Urlings BA, et al. (2000) Role of volatine fatty acids in development of the cecal microflora in broiler chickens during growth. Applied and Environmental Microbiology 66: 2536-2540. [crossref]
  30. Canani RB, Di Costanzo M, Leone L (2012) The epigenetic effects of butyrate: potential therapeutic implications for clinical practice. Clinical Epigenetics 4: 1-7. [crossref]
  31. Shermer CL, Maciorowski KG, Bailey CA, Byers FM, Ricke SC (1998) Caecal metabolites and microbial populations in chickens consuming diets containing a mined humate compound. Journal of the Science of Food and Agriculture 77: 479-486.
  32. Hreško Šamudovská A, Bujňák L, Zigo F (2022) Carcass characteristic, caecal metabolites and dropping quality in broiler chickens fed diets containing a humic substances. Asian Journal of Agriculture and Food Sciences 10: 133-138.
  33. Abd El-Hakim AS, Cherian G, Ali MN (2009) Use of organic acid, herbs and their combination to improve the utilization of commercial low protein broiler diets. International Journal of Poultry Science 8: 14-20.

What Makes ‘Healthful Food’ vs. A ‘Food Healthful’: Using AI to Coach People to Ask Good Questions

DOI: 10.31038/NRFSJ.2024711

Abstract

This paper addresses the emerging opportunity to learn how to ask better questions, and think critically using an AI based tool, Idea Coach. The tool allows the user to define the topic, as well as specify the nature of the question though an easy-to-use interface (www.BimiLeap.com). The tool permits the user to change the topic slightly and discover the changes in the questions which then emerge. Idea Coach provides sets of 15 topic questions per iteration, along with summarizing the themes inherent in the questions, and suggests innovations based on the questions. The paper illustrates the output of the Idea Coach for four similar phrase describing food: Healthful food; Healthy Food; Good for Health; Health Food, respectively. The output, produced in a matter of minutes, provides the user with a Socratic-type tutor to teach concepts and drive research efforts.

Introduction-thinking Critically and the Importance of Asking Good Questions

A look through the literature of critical thinking reveals an increasing recognition of its importance, as well as alternative ways of how to achieve it [1,2]. It should not come as a surprise that educators are concerned about the seeming diminution of critical thinking [3,4]. Some of that diminution can be traced to the sheer attractiveness of the small screen, the personal phone or laptop, which can provide hours of entertainment. Some of the problem may be due to the effort to have people score well on standardized tests, a problem that the late Professor Banesh Hoffmann of Queens College recognized six decades ago in his pathbreaking book, The Tyranny of Testing, first published in the early 1960’s [5].

That was then, the past. Given today’s technology, the ability to tap into AI, artificial intelligence, the availability of information at one’s fingertips, the ability to scan hordes of documents on the internet, what are the next steps?. And can the next steps be created so that they can serve the purposes of serious inquiry, e.g., social policy on the one hand, science on the other, designed for students as well as for senior users? When the next steps can be used by students, they end up generating a qualitative improvement in education.

Previous papers in this ‘series’, papers appearing in various journals, have presented a systematized approach to ‘understanding’ how people think. The approach, originally called IdeaMap and then RDE (Rule Developing Experimentation), and now finally Mind Genomics, focused on creating a framework which required users to create four questions, each with four answers [6]. The actual process was to have the user create a study name, come up with the four ‘questions which tell a story’, and then for each question come up with four stand-alone-answers, phrases. The actual process was to mix these standard alone answers (called elements), present the combinations of answers (vignettes), instruct the respondent (survey participant) to rate the vignette on a defined rating scale, one vignette at a time, and then analyze the data to link the elements to the ratings. Figure 1 shows the process.

fig 1

Figure 1: The first steps in the Mind Genomics process. Panel A shows the creation of a study, including the name. Panel B shows the request for four questions which ‘tell a story.’

This exercise, introduced thirty years ago in the early version called IdeaMap® ended up revealing the difficulties experienced with asking good questions. The users of IdeaMap® comprised professionals at market research companies scattered around the world. These users were familiar with surveys, had no problems asking questions, but needed ‘coaching’ on creating questions which ‘told a story’.

As IdeaMap® grew, it became increasingly obvious that many users wanted to create a version of surveys. Users were comfortable with surveys. The requirement for a survey was to identify the different key areas of a topic and instruct the survey-taker to rate each topic using a set of questions prepared by the user. Expertise was demonstrated in the topics that the user selected, the instructions to the survey taker, and occasionally in the analysis. The user who discovered a new subtopic, e.g., one corresponding to a trend, could make an impression simply by surveying that new topic. Others prided themselves on the ability to run surveys which were demonstrably of lower bias and bias-free, or at least pontificated on the need to reduce bias. Still others were able to show different types of scales, and often times novel types of analyses of the results [7]. What was missing, however, was a deeper way to think about the problem, one which provided a new level of understanding.

The Contribution, or Rather the ‘Nudge’ Generated by the User Experience in Mind Genomics

The first task of the researcher after setting up the study is to create the four questions (Figure 1). It is at this step that many researchers become dismayed, distressed, and demotivated. Our education teaches us to answer questions. Standardized scores are based on the performance, viz.., right versus wrong. There is the implicit bias that progress is measured by the number of right answers. The motto ‘no child left behind’ often points to the implicit success of children on these standardized tests. There is no such similar statement such as ‘all children will think critically.’ And, most likely were that to be a motto, it would be laughed at, and perhaps prosecuted because it points to the inequality of point. We don’t think of teaching children to think critically as being a major criterion for advancing them into their education.

The introduction of Mind Genomics into the world of research and then into the world of education by working with young children revealed the very simplicity of teaching critical thinking, albeit in a way which was experiential and adult oriented [6]. Early work with very bright students showed that a few of them could understand how to provide ideas for Mind Genomics, and with coaching could even develop new ideas such as the reasons for WWI or what it was like to be a teenagers in the days of ancient Greece. These efforts, difficult as they were, revealed that with coaching and with a motivated young person one could get the person to think in terms of sequence of topics which related a story.

It was clear from a variety of studies that there was a connection between the ability to use the Mind Genomics platform and the ability to think. Those who were able to come up with a set of questions and then four answers to each question seemed to be quite smart. There were also students who were known to be ‘smart’ in their everyday work, but who were experiencing one or another difficulty while trying to come up with ideas. These frustrated respondents did not push forward with the study. Indeed, many of the putative users of Mind Genomics gave up in frustration, simply abandoning the process. Often they requested that the Mind Genomics process should provide them with the four questions. The answers were never an issue with these individuals, only the questions.

The response to the request for questions ended up being filled by the widespread introduction of affordable and usable AI, in the form of Chat GPT [8]. The inspiration came from the realization that were the questions to be presented to Chat GPT in a standardized form, with the user able to add individuating verbiage it might well be possible to create a ‘tutor’ which could help the user. And so was born Idea Coach, in the early months of 2023, shortly after the widely heralded introduction of Chat GPT to what turned out to be a wildly receptive audience of users.

The early approach of Idea Coach was to allow the user to type in the request for questions, at which point the Idea Coach would return with 30 questions. The sheer volume of putative questions was soon overwhelming, an embarrassment of riches. It was impossible for the user to read the questions and make a selection. Eventually the system was fixed to generate 15 questions rather than 30, to record the questions for later presentation to the user, to allow the user to select questions and re-rerun the effort, or even to edit the questions. Figure 2 shows an example of the request to the Idea Coach, and the return o f a set of questions, along with the hance to select 1-4, or to rerun or to edit the requests and rerun.

fig 2

Figure 2: Screen shots showing the location where the user types in the ‘squib’, viz the prompt (Panel A), and some questions which emerge from an iteration using that prompt.

The ultimate use of the Idea Coach turned out to be a massive simplification in the use of the Mind Genomics program, BimiLeap (Big Mind Learning App), along with the welcome acceptance by school age students who found it easy, and ‘fun’ [9-11]. The effort to create the Idea Coach along with mentoring the young students make it possible for them to do studies, at first guided, and then later on their own. Later on, the Idea Coach would end up providing answers to the questions, with the AI provided the text to the AI in the form of the actual question.

Moving Beyond the Research Process into What Idea Coach Actually Can Contribute

The initial experiences with Idea Coach were confined to setting up the raw material for the Mind Genomics process, namely the specification of the four questions, and then for each question the specification of the four answers. The earliest inkling of the power of Idea Coach to help critical thinking emerged from meetings with two young researchers, both of school age. It was during the effort to set up studies that they asked to run the Idea Coach several times. It was watching their faces which revealed the emerging opportunity. Rather than focusing on the ‘task’, these young school children seemed to enjoy reading the answers, at least for two, sometimes three iterations. They would read the answers and then press re-run, just to see what changed, what new ideas. It was then that the notion f using Idea Coach as a Socratic tutor emerged, a tutor which would create a book of questions about a topic.

Not every user was interested in using the Idea Coach to provide sets of questions for a topic, but there were some. Those who were interested ended up going through the question development process about two or three times, and then moved on, either to set up the study, or in cases of demonstration to other topics outside of the actual experience.

Over time, the Idea Coach was expanded twice, first to give answers as well as to suggest questions, and then to provide am Excel book of all efforts to create questions, and to create answers, each effort generating a separate tab in the Excel book. After the questions and answers had been registered in the study, and even before the user continued with the remaining parts of the set-up (viz., self-profiling classification questions, respondent orientation, scale for the evaluation) the Idea Coach produced a complete ‘idea book.’ The idea book comprised the one page for each iteration, whether question or answer, and then a series of AI-generated summarizations, listed below.

  1. Actual set of 15 questions
  2. Key Ideas
  3. Themes
  4. Perspectives
  5. What is missing
  6. Alternative Viewpoints
  7. Interested Audiences
  8. Opposing Audiences
  9. Innovations

The objective of the summarization was to make Idea Coach into a real Socratic tutor which asked questions, but also a provider of different points of view extractable from the set of 15 questions or 15 answers on a single Excel tab. That is, the Idea Coach evolved into a teaching tool, the basic goal to help the user come up with questions, but the unintended consequence being the creation of a system to educate the user on a topic in a way that could not be easily done otherwise.

The ‘time dimension’ of the process is worth noting before the paper shows the key results for the overarching topic of ‘health + food’. The creation of the squib to develop the questions requires about 2-3 minutes, once the user understands what to do. Each return of the 15 questions requires about 10-15 seconds. The editing of the squib to create a new question requires about a minute. Finally, the results are returned after the user completes the selection of four questions and the selection of four answers for each. A reasonable size Excel-based Idea book with about 30 total pages, questions, answers, AI summarization, in finished form thus emerges within 25-30 minutes. It is important to note that some of the questions will repeat, and there will overlaps from iteration to iteration. Even so, the Idea Coach, beginning at it did to ameliorate the problem of frustration and lack of knowledge ended up being a unique teaching guide, truly a Socrates with a PhD level degree. The correctness of information emerging is not relevant. What is relevant is the highlight of ideas and themes for the user to explore.

How Expressions of the Idea of ‘Health’ Generate Different Key Ideas and Suggested Innovations

Food and health are becoming inseparable, joined together at many levels. It is not the case that food is the same as health, except for some individuals who conflate the two. Yet it is obvious that there exists a real-world, albeit complex between what we eat and how healthy we are. These connections manifest themselves in different ways, whether simply the co-variation of food and health [9], the decisions we make about food choice [12,13], our immediate thoughts about what makes a food healthy or healthful [14], and finally but not least, how we respond behaviorally and attitudinally to claims made by advertisers and information provided by manufacturers [15,16].

The notion of critical thinking emerged as a way to investigate the differences in the way people use common terms to describe food and health. After many discussions about the topic, it became increasingly obvious that people bandied about terms conjoining health and food in many ways. The discussions failed to reveal systematic differences. The question then emerged as to whether critical thinking powered by AI could generate clear patterns of difference in language when different expressions about food and health were used as the starting points. In simple terms, the question became simply like ‘do we see differences when we talk a healthful food versus a health food?’

What Makes a Food HEALTHFUL?

The first phrase investigated about foods and health is ‘What makes a food HEALTHFUL?’ The focus is on the word ‘healthful’ to express the main idea Table 1 shows the question as presented in the squib, the 15 key ideas which emerge, an AI summarization of the key ideas by the new AI program, QuillBot [8,17] and finally suggested innovations based on the ideas. The bottom line for HEALTHFUL is that the output ends up providing a short but focused study guide to the topic created by the interests of the user, open to being enhanced by the user at will, and in reality, in minute.

Table 1: AI results regarding the phrase ‘What makes a food healthful?’ The table is taken directly from the outputs of Idea Coach (key ideas, innovations) and from Quillbot®.

table 1

What Makes a Food HEALTHY?

The second phrase investigated about foods and health is ‘What makes a food HEALTHY? The terms ‘healthy’ and ‘healthful’ are used interchangeably in modern usage, although there is a subtle but profound difference. The word ‘healthful’ refers to the effect that the food has on a third party, such as a person. The word ‘healthy’ refers to the food itself, as if the food were the third party. It is precisely this type of thinking, which is part of the world of critical thinking, although the issue might go further to deal with the different implications of these two words.

The reality of the differences between healthful and healthy is suggested by Table 2, but not strongly. Table 2 again suggests a many-dimensional world of ideas surrounding the word ‘healthy’ when combined with the food. There is once again the reference to the food itself, as well as to the person. The key difference seems to be ‘morphological’, viz., the format of the output of AI. In Table 1 the key ideas were so numerous that the key ideas themselves generated different aspects to each idea. In contrast, Table 2 shows a far sparser result.

One clear opportunity for teaching critical thinking now emerges. That opportunity is to discuss the foregoing observation about the different morphologies of the answers, the reasons which might underly the reasons, and the type of ideas and innovations which emerge.

Table 2: AI results regarding the phrase ‘What makes a food healthy?’ The table is taken directly from the outputs of Idea Coach (key ideas, innovations) and from Quillbot®.

tab 2

Table 3: AI results regarding the phrase ‘What makes a good for health?’ The table is taken directly from the outputs of Idea Coach (key ideas, innovations) and from Quillbot®.

tab 3(1)

tab 3(2)

What Makes a HEALTH FOOD?

The fourth and final phrase investigated is ‘Health Food’. Table 4 shows the results emerging from the AI analysis. Once again AI returns with relatively simple ideas.

Table 4: AI results regarding the phrase ‘What makes a health food?’ The table is taken directly from the outputs of Idea Coach (key ideas, innovations) and from Quillbot®.

tab 4

1. Meal delivery services that focus on providing healthy, balanced meals with optimal nutritional profiles.
2. Cooking classes or workshops that teach individuals how to cook using healthy ingredients and techniques.
3. Apps or websites that provide information on the nutritional content and ingredients of commonly consumed foods and beverages.
4. Nutritional labeling on restaurant menus to make it easier for individuals to make healthier choices when dining out.
5. Community gardens or urban farming initiatives that promote access to fresh, organic produce in urban areas.
6. Policies and regulations that require food manufacturers to disclose the amount of added sugars in their products.
7. Nutrient-dense food products or snacks that provide essential vitamins, minerals, and protein in a convenient and portable form.
8. Schools implementing nutrition education programs that teach children about the importance of healthy eating and the impact of food choices on their overall health.
9. Digital health platforms or apps that offer personalized nutrition plans based on an individual’s specific nutrient needs and goals.
10. Food labeling systems that use color-coded labels or symbols to indicate the nutritional quality of a product, making it easier for consumers to make healthier choices.

Discussion and Conclusions

The objective of this study is to explore the different ways of learning how to ask questions. A great deal of today’s research follows the path of the so-called ‘hypothetico-deductive’ system. The researcher begins with a hypothesis and runs an experiment to confirm or disconfirm that hypothesis, viz., to falsify if possible. The focus is often on the deep thinking to link the hypothesis to the experiment, then to analyze the results in a way which provides a valid answer [18]. The vast majority of papers in the literature begin with this approach, with the actual science focusing on the ability to test the hypothesis, and maybe add that hypothesis to our knowledge, a task often colloquially called ‘plugging holes in the literature.’

Mind Genomics, an emerging approach to the issues of everyday life, does not begin with hypothesis, and does not the scientific logic of Popper, and the notion of hypothesis drive research. Instead, Mind Genomics begins as an explorer or cartographer might begin, looking for relations among variables, looking for regularities in nature, without however any underlying hypothesis about how nature ‘works’. As a consequence, the typical experiment in Mind Genomics begins by an interesting conjecture about what might be going on in the mind of a person regarding a topic. The outcome of a set of Mind Genomics experiments ends up being an aggregate of snapshots of how people think about different topics, this collection of snapshots put into a database for others to explore and summarize.

With the foregoing in mind, the topic of coming up with interesting questions becomes a key issue in Mind Genomics. If the approach is stated simply as ‘asking questions, and getting answers to these questions’, with no direct theory to guide the question, then in the absence of theory how the system can move forward? The science of Mind Genomics is limited to the questions that people can ask. How can we enable people to ask better questions, to explore different areas of a topic with their questions. And in such a way expand this science based on question and answer.

Acknowledgment

Many of the ideas presented in this paper have been taken from the pioneering work of the late Professor Anthony G. Oettinger of Harvard University, albeit after a rumination period going on to almost 60 years [19].

References

  1. Chin C, Brown DE (2002) Student-generated questions: A meaningful aspect of learning in science. International Journal of Science Education 24: 521-549.
  2. Washburne JN (1929) The use of questions in social science material. Journal of Educational Psychology 20: 321-359.
  3. Huitt W (1998) Critical thinking: An overview. Educational Psychology Interactive 3: 34-50.
  4. Willingham DT (2007) Critical thinking: Why it is so hard to teach? American Federation of Teachers Summer 2007: 8-19.
  5. Hoffmann B, Barzun J (2003) The tyranny of testing. Courier Corporation.
  6. Moskowitz HR (2012) Mind Genomics’: The experimental, inductive science of the ordinary, and its application to aspects of food and feeding. Physiology and Behavior 107: 606-613. [crossref]
  7. Slattery EL, Voelker CC, Nussenbaum B, Rich JT, Paniello RC, et al. (2011) A practical guide to surveys and questionnaires. Otolaryngology–Head and Neck Surgery 144: 831-837.
  8. Fitria TN (2021) QuillBot as an online tool: Students’ alternative in paraphrasing and rewriting of English writing. Englisia: Journal of Language, Education, and Humanities 9: 183-196.
  9. Kornstein B, Rappaport, SD, Moskowitz H (2023a) Communication styles regarding child obesity: Investigation of a health and communication issue by a high school student researcher using Mind Genomics and artificial intelligence. Mind Genomics Studies in Psychology Experience 3: 1-14.
  10. Kornstein B, Deitel Y, Rapapport SD, Kornstein H, Moskowitz H (2023b) Accelerating and expanding knowledge of the everyday through Mind Genomics: Teaching high school students about health eating and living. Acta Scientific Nutritional Health 7: 5-22.
  11. Mendoza CL, Mendoza CI, Rappaport S, Deitel J, Moskowitz H (2023) Empowering young people to become researchers: What do people think about the different factors involved when shopping for food? Nutrition Research and Food Science Journal 6: 1-9.
  12. Caplan P (2013) Food, health and identity. Routledge.
  13. Rao M, Afshin A, Singh G, Mozaffarian D (2013) Do healthier foods and diet patterns cost more than less healthy options? A systematic review and meta-analysis. BMJ open 3: p.e004277. [crossref]
  14. Monteiro CA (2009) Nutrition and health. The issue is not food, nor nutrients, so much as processing. Public Health Nutrition 12: 729-731. [crossref]
  15. Bouwman LI, Molder H, Koelen MM, Van Woerkum CM (2009) I eat healthfully but I am not a freak. Consumers’ everyday life perspective on healthful eating. Appetite 53: 390-398. [crossref]
  16. Nocella G, Kennedy O (2012) Food health claims–What consumers understand. Food Policy 37: 571-580.
  17. Ellerton W (2023) The human and machine: OpenAI, ChatGPT, Quillbot, Grammarly, Google, Google Docs, & humans. Visible Language 57: 38-52.
  18. Kalinowski ST, Pelakh A (2023) A hypothetico-deductive theory of science and learning. Journal of Research in Science Teaching.
  19. Bossert WJ, Oettinger AG (1973) The integration of course content, technology and institutional setting. A three-year report. 31 May 1973. Project TACT, Technological Aids to Creative Thought.

Women-Led Climate Change Solution Satellites: A Key Contributor to Social and Economic Empowerment of Women in Uganda

DOI: 10.31038/AWHC.2024711

Abstract

Background: Climate change poses a significant threat to communities across the globe. Whereas low and middle income countries contribute the least to this problem, they are often most affected by the consequences. In addition, women are often disproportionately affected by climate change-related occurrences. To address these issues, Women Climate Centers International (WCCI) Uganda initiated a project to empower women through the promotion of climate change solution enterprises in Uganda. The purpose of this research was to establish the impact of this approach on women social and economic empowerment and quality of life.

Methods: The study employed a cross-sectional approach, collecting both quantitative and qualitative data among 96 women purposively selected for their involvement in WCCI climate-smart enterprises in Uganda. A digitized structured questionnaire was used to gather quantitative data while a structured Focus Group Discussion (FGD) guide were used to aid qualitative data collection. The quantitative data was analyzed statistically using Stata version 15 to provide descriptive and statistics while Atlas ti9 was used to thematically analyze the qualitative data after transcribing of audios recorded during the interviews.

Results: About 38% (36/96) of the women make briquettes, 51% (49/96) make soap and 95.8% (92/96) are generating income from the enterprises. More than half 59.4% (57/96) of the women are confident in running their businesses sustainably while 38.5% (37/96) had trained 4-5 community women each, with the knowledge obtained from the satellites. Over 62% (59/96) of women strongly agreed to an improved sense of belonging within their community, 94.8% (91/96) noticed an improvement in their community engagement and collaboration while 63.5% (61/96) strongly agreed to better treatment from family and neighborhood. Conversely, 22.9% (22/96) of the women had ever experienced intimate or gender-based violence in their life, half of these had experienced it in the previous six months, but only 18.2% (2/11) would attribute their recent experience to engaging in entrepreneurship under WCCI. Economically, 57.3% (55/96) of the women saw a significant increase in their income, and 56.3% (54/96) in their household income. About 76% (73/96) had acquired some personal or household assets using income from the enterprises, and 65% (62/96) had joined a women’s group, Savings and Credit Cooperative Organization (SACCO), or local governing bodies since their training with WCCI. Furthermore, 82.3% mentioned that there was a positive difference in the way their husbands treated them ever since they attained financial independence. Lastly, the majority of the women, 63.6% (61/96) strongly agreed, and 29.2% (28/96) agreed that their quality of life and well-being had improved since becoming part of the climate change solution satellites. The qualitative findings strongly corroborated the quantitative.

Conclusions: Overall, participation in these entrepreneurial initiatives has brought about tangible improvements in social cohesion, economic empowerment, and the perceived quality of life and well-being for a significant majority of women involved, demonstrating the positive impact of the WCCI climate change solution satellites on their lives and communities.

Keywords

Women-led, Climate change solution satellites, Entrepreneurship, Empowerment

Introduction and Background

Globally, women and girls from marginalized communities face intersecting challenges related to gender inequalities, economic empowerment, and the profound impacts of climate change [1-3]. Regarding climate change, the complex web of vulnerabilities that these women encounter is rooted in a global context where women are both disproportionately affected by the adverse consequences but underrepresented in efforts to address and mitigate these effects [4]. The African region has witnessed an increase in average temperatures, changes in rainfall patterns, and an increase in extreme weather events such as floods, droughts, and conflicts over natural resources, which exert a disproportionate toll on the developing world including Uganda [3,5,6]. These climate shocks have significant implications for agriculture, food security and livelihoods [1,7] and burdensome for women, as they play crucial roles in agricultural production, water collection, natural resource management, and household well-being [8].

While the concept of climate-smart enterprises is gaining traction in East Africa, women-led initiatives in this sector remain scarce [9]. Recognizing the critical need to address these interconnected challenges, Women Climate Centers International (WCCI) [10], embarked on a transformative initiative in Uganda. This initiative sought to empower women through comprehensive training encompassing climate-smart solutions, livelihood strategies, and economic and social empowerment. In the first project year, WCCI has engaged 100 women and girls organized in 10 women-led grassroots groups that belong to 3 different satellites (Gomba, Butambala and Mukono), seamlessly integrating women’s entrepreneurship with grassroots climate resilience initiatives. Through these groups, WCCI conducted extensive trainings, emphasizing climate-smart solutions, livelihoods, and economic and social empowerment, leadership, and management, and fundamental entrepreneurship skills. WCCI trained the women in making climate-smart products such as briquettes, liquid and bar soap, herbal vaseline, fireless stoves, water tanks/jars, and bio-sand filters. The women were also trained to engage in Vermiculture, Agroforestry farming, and Bio-intensive farming including double digging, moist gardens, sack gardens, mixed cropping and mushroom growing, apiary (and liquid manuring year-round food production. Furthermore, WCCI Uganda facilitated the establishment and registration of the 10 women-led enterprises, with full support throughout the registration process. This registration made these enterprises eligible for government funding via the community demand-driven development funds especially the Parish Development Model [11]. WCCI offered 4 full days of training in business development and planning to all 100 women to ensure that they have the needed skills to develop, plan, and run their businesses. WCCI also provided vital business support equipment tailored to each satellite’s needs, ensuring they could efficiently produce, sell, and thrive. Importantly, these innovative approaches are expected to extend WCCI’s impact beyond parishes, fostering sustainable social and economic empowerment and quality of life within communities.

This innovative approach aimed to foster community-driven strategies from a single learning and training center (satellite) for long-term climate adaptation, mitigation, and resilience, including carbon sequestration. Through targeted training programs, mentorship, access to finance, and networking opportunities, women can enhance their entrepreneurial capabilities, understand the principles of climate-smart practices, and develop innovative business models that are environmentally sustainable and socially inclusive. Ultimately, by fostering the establishment of women-led climate smart enterprises, Uganda can unlock the untapped potential of women, create sustainable livelihoods, and promote economic resilience and sustainable practices in the face of climate change. Central to this initiative is the aspiration to establish women-led climate-change solution enterprises, recognizing the critical role women can play in driving economic growth, creating employment opportunities, and advancing gender equality and social inclusion. By aligning with Uganda’s National Development Plan 3 [12], these enterprises aim to serve as catalytic models for sustainable community development.

As these enterprises continued on their transformative journey, it was essential to evaluate the holistic impact on the social and economic empowerment and quality of life of the women involved, as well as any unintended consequences such as gender-based violence. The research sought to illuminate the transformative potential of the one-stop climate change solution center model, exemplified by these satellite initiatives, to contribute insights to inform future initiatives, strengthening WCCI’s mission to empower women and communities in their pursuit of climate resilience, economic growth, and enhanced overall wellbeing.

The Study Methods

Study Design and Study Area

The study employed a cross-sectional approach, collecting both quantitative and qualitative data from the women. The study was conducted in the three intervention groups including Gomba, Butambala and Mukono. The three districts are located in the central region of Uganda. Gomba district is a rural district which was formed in 2010 by an Act of Parliament, breaking away from Mpigi District. It is bordered by Mubende District to the west and north, Mityana District to the northeast and Butambala District to the east. Kalungu district, Bukomansimbi district and Sembabule district lie to the south of Gomba district. The district lies approximately 97 kilometers (60 mi), by road, southwest of Kampala, the capital and largest city of Uganda. Gomba district receives lower precipitation than the neighbouring districts and livestock farming is a major economic activity, supplemented with subsistence agriculture [13]. Butambala district was too created by an act of parliament, and became operational on 1 July 2010, having been split off of Mpigi district. This district is bordered by Gomba district to the west and north-west, Mityana District to the north-east, Mpigi District to the east and south, and Kalungu District to the south-west. The district headquarters at Gombe are approximately 68 kilometers (42 mi), by road, south-west of Kampala. Subsistence agriculture and small-scale animal husbandry are the backbone of Butambala district’s economy [14]. Mukono district is one of the fastest growing areas in Uganda and is located along the Kampala-Jinja highway. The district is bordered by Kayunga district to the north, Jinja district to the east, Kalangala district to the south-west, Kira Town and Wakiso district to the west, and Luweero district to the north-west. The town of Mukono is about 21 kilometers (13 mi) by road, east of Kampala. The district has a favorable climate, abundant rainfall, rich flora and fauna, and proximity to urban areas [15].

Study Population

Data was collected from women actively engaged in climate change solution satellites supported by Women Climate Centers International (WCCI) Uganda.

Sample Size and Sampling

Of the 100 women currently supported by through the satellites, 96 were engaged in this study and 4 were unavailable at the time of data collection. All the 96 participants were selected purposively because of being beneficiaries of the program. Both quantitative and qualitative data were collected from the same participants.

Data Collection Criteria

A digitized Kobo collect toolbox questionnaire was used to conduct surveys with the participants to gather quantitative data on specific aspects of their experiences and observations related to the contribution of climate change solution satellites. The surveys included predefined questions covering areas such as economic empowerment, social cohesion and collaboration, climate change knowledge, and quality of life.

Qualitatively, a structured Focus Group Discussion (FGD) guide was used to elicit data to complement the surveys. A total of six FGDs were conducted, two per district and each FGD comprised 10 women. The FGDs were moderated by a male qualitative data collection expert who was assisted by a female note taker. These FGDs were conducted in Luganda, the local dialect, and focused on open-ended questions that encouraged participants to share their experiences and perceptions in more detail.

Quality Control and Assurance

Both qualitative and quantitative tools were translated to Luganda and the researchers ensured to only recruit research assistants who were conversant with Luganda, the local dialect. Research assistants with a good command of English were recruited to conduct interviews, however, the interviews were conducted in a language most comfortable to the respondent. Research assistants were trained on the research protocol and ethical issues surrounding the study. To ensure data accuracy and consistency, the digitized tool was designed with skips, hints, and prompts to ensure that the research assistants filled in the data the way they were supposed to. Furthermore, the research assistants were supervised during the actual data collection exercise. The supervisors ensured that the tool was checked and field edited, if necessary, to ensure completeness of data before data entry.

Data Management and Analysis

Quantitative Data: Quantitative data was field edited for consistency and accuracy daily. Data materials were secured under lock and key and were only accessed by the study team. The data was downloaded from the Kobo collect web-based server, accessible on the link; (https://eu.kobotoolbox.org/#/forms/aN7ejaQfnbe4dGyp53YySM/data/table) and loaded onto Microsoft Excel for further cleaning and visualization. The data was then imported to STATA version 15 for statistical analysis. Descriptive analysis was done to generate the mean and the standard deviation for continuous variables and proportions for categorical variables. Frequency tables as well as figures were used to present these results.

Qualitative Data: All qualitative interviews were digitally recorded with permission from respondents and transcribed verbatim. The transcripts were proofread before importing them into a qualitative data management software-Atlas.ti9. Data coding and analysis were conducted subsequently. An initial codebook using a sample of two transcripts was developed. The developed codebook was then applied to the entire atlas project with any emerging codes being added in the process. Thematic analysis was used and results were presented using themes with typical quotations from different interviews to summarize social cohesion and collaboration, economic empowerment, and quality of life and well-being.

Results

Socio-demographic Characteristics of the Study Respondents

A third 33.3% (32/96) of the women were aged between 26-30 years, 44.8% (43/96) were of the Anglican religion, 67.7% (65/96) were married and 75% (72/96) had attained the primary level of education. The majority 41.8% (40/96) were from Gomba district (Table 1).

Table 1: Socio-demographic characteristics of the women engaged in climate change solution satellite enterprises in Uganda.

Variable

Category Frequency (n=96)

Percentage (%)

Age 18-25

13

13.5

26-30

32

33.3

31-35

27

28.1

36+

24

25.0

Religion Anglican

43

44.8

Catholic

29

30.2

Pentecostal

17

17.7

Muslim

7

7.3

Marital status Never married

16

16.7

Married

65

67.7

Separated/divorced

15

15.6

Education level Primary level

72

75%

Secondary level

22

22.9

Tertiary level

2

2.1

District of residence

Gomba

40

41.8

Butambala

26

27.1

Mukono

30

31.3

Status of Women-led Climate Solution Satellite

Table 2 shows the status of the women-led climate change solution satellites in Uganda. All women involved in the study were part of a satellite. About 38% (36/96) were engaged in briquette making while 51% (49/96) were making soap. The majority of the respondents 70.8% (68/96) mentioned that their enterprises were registered with the district authorities while 95.8% (92/96) mentioned that their businesses were generating them income. About 18% (17/96) faced taxes and licensing as a main challenge, 13% (12/96) faced issues with the market for their products while 11.5% (11/96) found scaling and growth difficult. Additionally, on a scale of 1-10, the mean(SD) level of confidence to run the enterprise sustainably was 6.8(1.81), while 59.4% (57/96) of the women rated their confidence between 7-10. More than a third of the women, 38.5% (37/96) had trained up to 5 or more community women each, with the knowledge obtained from the satellites.

Table 2: Status of Women-led Climate Solution Satellites in Uganda

Variable

Categories

Frequency (n=96)

Percentage (%)

Climate change solution – products being made Briquettes

36

37.5

Water tanks/bio-sand filters

2

3.1

Fireless cook stoves

9

13.9

Agro-forestry farming

11

16.9

Bio-intensive farming

3

4.6

Soap making

49

51.0

Others

17

26.1

Enterprise registered with the district authorities? Yes

68

70.8

No

28

29.2

Is the business generating you any income yet Yes

92

95.8

No

4

4.2

Challenges faced in running the enterprise Taxes and licensing

17

17.7

Market for products

12

12.5

Scaling and growth

11

11.5

Risk management

9

13.9

Others

1

1.5

Rate your level of confidence in running the enterprise sustainably

Mean(SD)=6.80(1.81)

1-3

4

4.2

4-6

35

36.5

7-10

57

59.4

Number of women personally trained with the knowledge from the satellite 0-1

40

41.7

2-3

19

19.8

4-5

37

38.5

Qualitatively, six focus group discussions were held with the women. These brought forward insights across the three districts of Gomba, Butambala, and Mukono, highlighting the collaborative nature of product-making among small groups, both for personal gain and communal development. Participants emphasized mutual support, group training, and the positive impact of acquired skills, enabling them to engage in various income-generating activities, from making briquettes and soap to cultivating vegetables and trees. Notably, the cultivation of home vegetables emerged as a significant achievement, not only economically but also in enhancing household food security and familial support. Respondents were quoted saying;

“We are in groups; some are of 10 people others 15 but not more than that. In most cases we do our things together, as in as the big group for the district. We come together for trainings and even for making our products. We support each other in case one of us has a problem. Most of us make these products as a group but also as individuals and we sell them in our communities.” (Participant 1, FGD, Gomba district)

“They told us to assist 5 other women each and some of us have gone beyond that. We gather the women and teach them. Sometimes, you team up with a politician and they help to teach the people which encourages community development.” (Participant 3, FGD, Gomba district)

“Ever since we joined the trainings, we learned so much. We make briquettes, liquid soap, tablet, and bar soap, we also make Vaseline. We have done so many things which have helped us to generate income and save.” (Participant 1, FGD, Butambala)

“We also cultivate nursery beds; we donate and plant some of our trees in schools freely. We make charcoal, soap, and cooking stoves and sell them to people. We also cultivate leafy vegetables because almost all the ladies here have homegrown vegetables, which they sell to people.” (Participant 2, FGD, Gomba)

“The cultivation of home vegetables is so good because it’s amazing for visitors when they find your yard full of vegetables. Then our husbands used to purchase vegetables from the market when they found those that they liked like Nakatti, but now they find it at home.” (Participant 3, FGD, Gomba)

“I have found growing crops as the easiest for me. We were taught how to look after banana plants, and coffee plants, which helped us to cultivate even without fertilizers since we use the home trash as manure in our gardens to be able to pay our children’s school fees.” (Participant 8, FGD, Mukono)

Social Cohesion and Community Engagement among the Women

The majority of the women, 61.5% (59/96) strongly agreed that their participation in the women-led climate change solution satellites had improved their sense of belonging within their community, 94.8%% (91/96) noticed an improvement in their community engagement and collaboration since their involvement in the enterprise, while 63.5% (61/96) strongly agreed that their family treats them better ever since joining the satellites. A similar proportion further strongly agreed that people in their neighborhoods treat them better since joining the women-led climate change solution satellites (Table 3).

Table 3: Social cohesion and community engagement among the women engaged in climate change solution satellites.

Variable

Category

Frequency (n=96)

Percentage

(%)

Participation in the women-led climate change solution satellite improved my sense of belonging within my community. Strongly agree

59

61.5

Agree

34

35.4

Neutral

3

3.1

Noticed an improvement in community engagement and collaboration since involvement in the satellite activities?

Strongly agree

41

42.7

Agree

50 52.1

Neutral

5

5.2

My family treats me better since joining the women-led climate change solution satellite Strongly agree

61

63.5

Agree

29

30.2

Neutral

6

6.3

People in my neighborhood treat me better since joining the women-led climate change solution satellite

Strongly agree

61

63.5

Agree

32

33.3

Neutral

3

3.1

The narratives from the FGDs revealed profound shifts in social dynamics due to the collaborative efforts within WCCI projects. Participants emphasized the development of robust relationships transcending geographical boundaries. The once fragmented communities now exhibit solidarity, as evidenced by the warm welcome received in various households across different towns. Moreover, the newfound friendships extended beyond project members, fostering positive interactions with neighboring villages. This solidarity was born from a spirit of collaboration, where knowledge sharing and support became the norm. The collective efforts in constructing local stoves and utensil stands showcased a shared commitment to cleanliness and community welfare. The projects acted as catalysts for forming friendships, bridging gaps, and nurturing a sense of mutual admiration and respect, ultimately enhancing social cohesion and fostering a network of supportive relationships within these communities.

“We have developed very good relationships, I live in Kanyonyi town council, and I didn’t know any ladies from Kifampa, Mpenja or Kabulassobi, but as of now, once you arrive at the home of one of your project colleagues, even their children welcome you to the home which portrays a good working relationship. Additionally, on the villages where we train ladies, the relationships there are very good because back then ladies used to be very jealous of us, but right now they are not jealous anymore. They realize that once we learn something, we mobilize and teach them, which has improved our relationships with people so much, and even their husbands are very supportive of us because they see the good we are doing with their wives.” (Participant 5, FGD, Gomba”

This project has aided us so much as ladies, we mobilize ourselves and go to a colleague’s home and construct for them a local stove, and a utensil stand all in the fight for cleanliness. (Participant 7, FGD, Butambala)

 “The people in the places where we reside became our friends. They know when we are supposed to come for the project meetings and even remind us. Some ladies come to us and want to support us while others request to join our program. We are admired and we are held in high regard wherever we reside.” (Participant 1, FGD, Mukono)

“We have made friends we wouldn’know if it wasn’t for this project. We have made friends from various communities, so I am personally happy about this.” (Participant 8, FGD, Gomba)

Intimate Partner and Gender-Based Violence Experiences

Table 4 shows experiences related to an intimate partner or gender-based violence. Overall, 22.9% (22/96) of the women had ever experienced intimate/ gender-based violence in their life. Of these, half, 50% (11/22) had experienced it in the previous six months, but only 18.2% (2/11) would attribute their experience to engaging in entrepreneurship. The majority 74% (71/96) of the respondents agreed that they have seen an improvement in the way their husbands treat them since they joined the satellites.

Table 4: Intimate partner and Gender-Based violence experiences among the women engaged in climate change solution satellites in Uganda.

Variable

Category Frequency (n=96)

Percentage

(%)

Ever experienced any intimate partner or gender-based violence in your life Yes

22

22.9

No

74

77.1

Experienced any intimate partner or gender-based violence in the last 6 months. Yes

11

50.0

No

11

50.0

Would you attribute this violence to your engagement in entrepreneurship Yes

2

18.2

No

9

81.8

Noticed improvement in the way my partner treats me since I joined WCCI Strongly agree

11

11.5

Agree

71

74.0

Neutral

8

8.3

Strongly disagree

6

6.2

The narratives indicate a tangible positive impact on reducing intimate partner and gender-based conflicts through increased education, shared responsibilities, financial empowerment, and altered perceptions of women’s roles within their households and society. Participants noted a distinct transformation in family dynamics, citing fewer reported cases of marital conflicts and domestic violence since the inception of the programs. Increased education and engagement in income-generating activities emerged as pivotal factors redirecting attention away from potential conflict points. The shared responsibilities and shared understanding cultivated through the trainings contributed to more harmonious households, characterized by decreased tension and fewer disputes over childcare and financial obligations. Moreover, the financial independence and changed perceptions of women’s value within households led to a shift in power dynamics, generating respect and diminishing instances of disrespect and marital discord.

“I am the senior woman in my community and back then I was always called to settle cases of women fighting with their husbands all the time, but ever since we started mobilizing ladies to come for these project trainings, ladies now have what things to do. To be honest I have now spent 5 months without being called for such family fights, but before, I used to attend to cases for like 2 families each day. Right now, those cases are unheard of, even at the police station ladies are no longer reporting such cases, which is a good change that’s been brought by these projects.” (Participant 5, FGD, Gomba)

On the issue of family fights, ever since I started coming for these projects, I got enough education to now understand how to handle my family. Secondly, I have things that take up my time compared to the gossip I used to be involved in to try and find out what my husband has been up to. I now have things to occupy me because if I am not doing home chores, I am running my businesses which takes up most of my time and leaves me no time for fights. I now have a lot to do to avoid such fights at home.” (Participant 7, Mukono)

“… before we used to be fighting with the men to take care of the children and their fees. But now we came to terms with our husbands, and they too got some education about shared responsibilities and now there is less fighting in homes. Life has really changed so much.” (Participant 4, FGD, Butambala)

“To add on, even my own husband now sees high value in me and cannot easily mess around with other women. This is because he must first consider whether the person he is messing with can favorably compete with me, and these projects have weighed us up so much on the men’s weighing scale, for which I am so grateful.” (Participant 10, FGD, Mukono)

“Before, I was so disrespected at home because even when he asked me what I had to offer, I couldn’t even show a penny. But now those words cannot come out of him because he knows that I have personal money now. So, that alone brought my home at peace and now we can sit and agree on certain issues, and he calmed down the disrespect he had towards me. That helped me even in society in that whenever they see me, there’s respect because I changed so much and they ask themselves whether I stole the money from someone, they think I went to the Statehouse, but I don’t even know where it is, I just do my projects.” (Participant 2, FGD, Gomba)

Contribution of the Women-led Climate Change Solution Satellites on Individual and Household Income and Financial Stability

Table 5 shows the contribution of the climate change solution satellites to the economic empowerment of women in Uganda. More than half 57.3% (55/96) of the women mentioned that participating in the satellite activities significantly increased their income, 56.3% (54/96) saw some improvement in their household income and 76% (73/96) had acquired some personal or household assets using income from the enterprise. Electronics (42.7%), furniture (24%), and rented/bought land (21.9%) were the most mentioned assets that were acquired by the women. Over 76% (73/96) of the women plan to acquire assets in the future using income from the satellite enterprises.

Table 5: Contribution of the women-led climate change solution satellites on individual and household income and financial stability in Uganda.

Variable

Category Frequency (n=96)

Percentage

(%)

The participation in the climate change solution satellite affected individual income Increased significantly

55

57.3

Increased moderately

36

37.5

Remained unchanged

5

5.2

The enterprise had a noticeable impact on household income and financial stability

Considerable improvement

42

43.7

Some improvement

54

56.3

Acquired personal or household assets with income from the climate change solution satellite

Yes

73

76.0

No

23

24.0

If yes, which assets were acquired so far

Rented/bought land

21

21.9

Constructed a house, roofed/repaired a house

19

19.8

Car, truck, bicycle, motorcycle

3

3.1

Furniture

23

24.0

Electronics

41

42.7

Others

30

31.3

Plan to acquire any other assets in the coming 3 months

Yes

73

76.0

No

23

24.0

If yes, which assets

Electronics

13

13.5

Furniture

19

19.8

Land

31

32.3

Construct house

17

17.7

Car, truck, motorcycle

7

7.3

Others

27

28.1

Qualitatively, participants highlighted tangible improvements in their standards of living, evident through enhanced household conditions and increased financial stability. Engaging in skill-building activities such as liquid soap making and briquette production became collective family endeavors, involving both children and spouses, resulting in augmented household income. The acquired skills not only boosted individual businesses but also elevated their marketability, as exemplified by one participant’s improved catering services and the plan to acquire business transportation assets. Participants expressed a newfound self-control toward expenditure, demonstrating a shift from impulsive spending habits to thoughtful financial management. They acknowledged the significance of savings, with aspirations to invest in property or business expansions, showcasing a long-term commitment to financial growth and sustainability. These narratives collectively illustrate the tangible impact of climate change solution projects on individual and household incomes, fostering financial prudence.

“I see an improvement in the standards of living amongst all the women, especially those of us who manage our money well. Even our homes have improved in standard too.” (Participant 3, FGD, Butambala)

“Yes, it has helped us with the children, in that they have learnt some of these skills like liquid soap making, because they actively participate while we make it at home. We make briquettes and they also participate, as well as the husbands too, so more money comes in for all of us.” (Participant 4, FGD, Mukono)

 “As a catering person, I saved money from these projects and invested in my business and this made me exemplary and marketable because my services were improved. I bought tents and chairs which made me a very presentable service provider and my services were highly demanded. I desire to purchase a vehicle that can transport my business assets in the future and in God’s name I know that I will purchase it.” (Participant 1, FGD, Gomba)

“Back then as ladies we never used to mind how much we had versus what we spent. Hawkers used to come around our communities and we would buy from almost all of them, but that has changed now. You must assess whether you need that item being hawked and ask yourself how much you made in the past month, and what improvements you need to make in your business, before purchasing say a bed cover from a hawker. Ever since we were trained, ladies have now learnt the importance of money, they appreciate saving and they know their responsibilities. It’s hard to find a lady who doesn’t save now.” (Participant 7, FGD, Butambala)

“Personally, I save the money I get from my business and in my saving group, we split profits annually so, I’ll be getting my share on 12th December and I want to use those savings to purchase an acre of land because I want to rear my cow on the same land as I live. So, I am hopeful that in the coming year, I will achieve it.” (Participant 6, FGD, Gomba)

Meaningful Participation of the Women in Livelihood/Economic Decision-making

About 65% (62/96) of the women had joined a women’s group, Savings and Credit Cooperative Organization (SACCO), or local governing body since their training with WCCI and 46.8% (29/62) had a leadership position in that body. Of those with leadership positions, 37.9% (11/29) were at the level of chairperson/vice chairperson while the rest were at secretary, treasurer, mobilizer or councilor level. Additionally, 79.3% (23/29) of the women in leadership rated high, the impact of the WCCI training on their decision to join leadership. Desire for personal growth and development (79.3%), Recognition of my abilities and potential (69%), and Desire to create a positive change (55.2%) were the most mentioned reasons for taking up leadership positions. Furthermore, 47.9% (46/96) jointly made economic/livelihoods decisions with their husbands, 81.2% (78/96) had recently been involved in livelihood/economic decisions while 82.3% mentioned that there was a positive difference in the way their husbands treat them ever since they started making their own money and being empowered. Less than a quarter 22.9% (22/96) acknowledged that their husbands do not support their work with the enterprise (Table 6).

Table 6: Meaningful participation of the Women in livelihood/economic decision-making opportunities at community and household level in Uganda.

Variable

Category Frequency

(n=96)

Percentage

(%)

Joined a women group, SACCO or local governing body since the training with WCCI Yes

62

64.6

No

34

35.4

Hold a leadership position on that women group, SACCO or local governing body Yes

29

46.8

No

33

53.2

Leadership position held on the women group or local leadership body or committee Chairperson/vice chairperson

11

37.9
Secretary/treasurer/mobilizer/councilor 18

62.1

Rate the impact of the training on your decision to join leadership and ability to serve in that capacity High impact

23

79.3

Moderate impact

6

20.7

Reasons for deciding to take up this leadership position Desire for personal growth and development

23

79.3

Passion for climate change cause

14

48.3

Recognition of my abilities and potential

20

69.0

Desire to create positive change

16

55.2

Need for representation and gender equality

6

20.7

Previous experience

1

3.5

Previously engaged in any advocacy meetings supporting women economic empowerment in your community Yes

51

53.1

No

45

46.9

In your household, who primarily makes decisions regarding economic activities and livelihoods Husband/male household member(s)

12

12.5

Jointly made by and female household members

46

47.9

Respondent/female household members

35

36.5

Others

3

3.1

Recently been involved in any livelihood/economic decision Yes

78

81.2

No

18

18.8

If yes, specify the type of livelihood/economic decision-making activities you have been part of. Income generation and business planning

67

44.7

Investment decisions

43

28.7

Market research

4

2.7

Pricing and sales strategy

3

2.0

Financial management and budgeting

31

20.7

Others

2

1.3

Make my own decisions regarding spending income Yes

80

83.3

No

16

16.7

Keep and spend my income by myself Yes

81

84.4

No

15

15.6

If no, who keeps or spends your income My husband

13

86.7

Other person

2

13.3

Okay with this, does this happen because of a mutual understanding between you and your partner Yes

83

86.5

No

13

13.5

Come for trainings and meetings with the knowledge of husband Yes

81

84.4

No

15

15.6

If No, does he stop you from coming for training/meetings? Yes

81

84.4

No

15

15.6

Noticed a difference in the way husband treats you since starting making own money and being empowered No difference

17

17.7

Yes, positive difference

79

82.3

Husband doesn’t support my work with the enterprise Agree

22

22.9

Neutral

15

15.6

Disagree

17

17.7

Strongly disagree

42

43.8

In the realm of livelihood and economic decision-making, the narratives from FGD participants highlighted the impact of WCCI initiatives on women’s empowerment and assertiveness in various spheres. Participants mentioned a transformation in self-perception and assertiveness, indicating newfound confidence and self-esteem among participants. The program also cultivated the courage to engage actively in public forums, a stark contrast to previous shyness and avoidance of meetings. Furthermore, the narratives conveyed the evolution of participants into role models and trainers, and hence can be consulted on various aspects. Crucially, participants shared instances of enhanced agency in economic decision-making within their households. The shift from a scenario where men previously controlled household finances to a situation where women assertively communicate their plans while maintaining harmony in decision-making signifies a tangible shift in gender dynamics and increased agency for women in economic matters.

“WCCI has been helpful to some extent because it has created a working relationship with the government and they both know and respect each other. In my observation, WCCI has helped to make us strong women who believe in ourselves in that if you have decided to do something, you must believe it in your heart. We are on committees that are making decisions in our communities.” (Participant 3, FGD, Gomba)

“I have gained a lot of self-esteem, even when speaking in public I am more confident compared to before when I used to be shy and sometimes, I would even dodge the meetings but it’s not the case anymore and whenever I am phoned, I know that I have an important call to which I respond.” (Participant 2, FGD, Butambala)

“The other thing I’ve gained is that I have become an example for other ladies, and I am also a trainer to them of the skills I gained.” (Participant 5, FGD, Mukono)

“We used to have money back then, and the men would take it from us. But now, when he asks for it, I tell him that I have plans for my money and we still come to an agreement, without him thinking that I have refused to give him money, but I have other things to use it for.” (Participant 5, FGD, Gomba)

Overall Quality of Life and Well-being among the Women

When asked if their overall well-being and quality of life have improved since becoming part of the climate-smart enterprise, the majority of the women, 63.6% (61/96) strongly agreed, 29.2% (28/96) agreed and 5.2% (5/96) were neutral. None of the women disagreed (Figure 1).

FIG 1

Figure 1: Perception on quality of life and overall wellbeing among the women

Through the diverse discussions, participants conveyed transformative personal and communal changes spurred by engagement in WCCI projects. These initiatives not only empowered women economically but also fostered improved family dynamics and social recognition. Participants highlighted a shift in household dynamics, with husbands now supportive and involved, and even prompting participation in the projects. Moreover, individual transformations were evident, reflected in enhanced self-esteem, improved appearance, and upgraded living standards. Participants celebrated tangible improvements in cleanliness, financial independence, diversified diets, and sustainable practices, demonstrating a profound shift in mindset towards environmental stewardship.

“… before, our husbands would get angry whenever we left home to come engage in such projects, but now they are steadily adjusting because we are very open about the dates when the projects will take place. So, the men have calmed down on realizing how much these projects have aided us. Even expenditures at home weighed down on men since we are now able to chip in on some of the home expenses. The husbands now even remind us of the dates when we are supposed to attend the projects. The improvement has been so evident in that even the children acknowledge that back then, they used to be chased from school due to lack of school fees, but now it’s no more.” (Participant 2, FGD, Gomba)

“I did not look like this before, the first thing I did with my money was to make sure I look good, and I am no longer looked down upon wherever I go. So, I see a big improvement from the ratchet I used to be to now looking better, it’s a very awesome change we should clap for ourselves.” Participant 6, FGD, Butambala

The other thing I had forgotten is that these trainings have improved cleanliness at home. A lady who is part of WCCI has a significantly decent home compared to those who are not in the project. We as ladies are very proud of these improvements. (Participant 1, FGD, Mukono)

“I used to just sit at home without much to do, but ever since WCCI came, it taught me so many things so right now I do my projects and have some personal money on me, and I have a job that I do, and doesn’t put me on pressure, I do it from my home without paying rent; customers come at my home without me having to hawk, schools too come and pick from my home. It has helped me a lot since I used to just sit at home back then. I am more satisfied with life now.” (Participant 5, FGD, Gomba)

“I used to eat cassava with tea and no sauce, but now life has changed. I can go and purchase beef, fish, and any sauce because the money is available. Even the dress code has changed.” (Participant 4, FGD, Buambala)

“I learned how to handle nature more than I used to before I could cut down trees but now, I look at trees like my own children and I cannot cut them down because it feels like I am cutting down my child like I’m ruining my child’s future.” (Participant 7, FGD, Mukono)

Discussion

The study aimed to assess the feasibility of Women-led climate change solution satellites on women’s social and economic empowerment and quality of life in the face of climate change in Uganda. The findings earlier shown are discussed per the objective below.

Collective Action in Women-led Climate Change Solution Satellites Influences Social Cohesion and Community Engagement

A noteworthy aspect of this project lies in its ‘train the trainer’ model, which has yielded substantial social impact while justifying the claim that empowering women through training can have far-reaching effects. Beyond individual skill acquisition, the project has employed a strategy where trained women become mentors, disseminating knowledge and skills within their communities. This ‘train the trainer’ approach has catalyzed a transformative shift among the women, not just as beneficiaries but as active agents of change within their communities.

The majority of participants reported significant improvements in their sense of belonging, increased community engagement, and notably better treatment from their families and neighbors. These outcomes are emblematic of a deeper societal transformation facilitated by these women-turned-trainers. By imparting their acquired knowledge and skills and actively engaging in communal projects, they have redefined their roles within their communities. Their involvement as both conveyors of expertise and active contributors to communal endeavors has elevated their status and influence, positioning them as key contributors to community progress.

Moreover, the collaborative nature of their work within the group-learning from each other, practicing in front of fellow satellite members-has fostered a supportive environment that nurtures confidence and competence. This newfound confidence not only improved their individual capacities but also equipped them to meaningfully contribute to larger communal initiatives. The ‘train the trainer’ model not only enhanced individual capabilities but also served as a catalyst for community development through knowledge dissemination and collaborative engagement.

Gender inequality, poverty, and other economic challenges are among the major causes of intimate and gender-based violence globally [16]. Given the high poverty levels of not only women but the general rural population in Uganda, it is understandable to unearth a 22% prevalence of intimate partner or gender-based violence among the respondents. The World Health Organization recommends seven strategies for prevention and reduction of violence against women, among which is the empowerment of women; Poverty reduction and creating an enabling environment [17], which were all targeted outcomes of this project. This evaluation indicated a 50% reduction in intimate partner and gender-based violence, with only 2 out of 11 individuals who had recent experiences attributing the violence to their engagement in entrepreneurship and the majority alluding to better treatment from their husbands. The trainings and empowerment given to women may have played a critical role in managing intimate and gender-based violence as has been deduced by earlier scholars [18,19].

The Economic Impact of Women-led Climate Change Solution Satellites on Individual and Household Income and Financial Stability

Significant proportions of the respondents mentioned an increase in their individual and household income, with some already purchasing property including gadgets, furniture, and land, using the newly found income. This result confirmed a partially achieved goal of the project; to positively impact women’s economic status and financial sustainability. The achievement can be explained by WCCI’s efforts in training the women on how to manage their finances including self-control towards expenditure, a saving culture and skilling in income-generating projects. WCCI engages the women in skill-building activities such as making soap, vaseline, and briquette among others that can be sold within the community to generate income and also supports them with the pre-requisite equipment for enhanced production. Skilling of women and trainings on financial literacy coupled with start-up support have been associated with economic empowerment in Uganda and other settings globally [20-22]. Through the “train the trainer model” which the women have wholesomely embraced and already practicing, this transformation can be transitioned to entire communities to contribute to the achievement of Sustainable Development Goal (SDG) 1; eradicating extreme poverty for all people everywhere by 2030 [23].

This evaluation also revealed the participation of women in decision-making ventures both in the community and in the households regarding livelihoods and economic development. Over 60% of the women joined women groups, SACCOs or local governing bodies and 47% of these were in leadership. These findings can be explained by the fact that WCCI emphasizes transformation in self-perception and assertiveness, which are key in interpersonal relationships and leadership [24,25] and can collaborate the newfound confidence and self-esteem among participants to join groups and even take up leadership positions. The program also cultivated the courage to engage actively in public forums, a stark contrast to previous shyness and avoidance of meetings, and women evolving into role models and trainers, who can be consulted on various aspects. The women are also gradually joining in decision-making at home, contributing ideas and funds for household development projects. The majority of the women mentioned keeping, planning for, and spending their money on things they find important unlike before when they used to spend randomly or simply give the money to their husbands to spend. This could be as a result of understanding the value of money, and the fact that these women have financial goals and have been taught to gradually grow their businesses and achieve more rather than being comfortable in their poverty.

The Overall Well-being and Quality of Life Improvements among Women Engaged in Climate Change Solution Satellites

Almost all the women in the study agreed that their overall well-being and quality of life has improved since becoming part of the climate-change solution satellites. The transformation can be attributed to the different gains from associating with WCCI. The nexus of economic empowerment heightened self-esteem, improved personal appearance, hygiene, financial autonomy, diverse dietary habits, enhanced family dynamics with increased support from husbands, improved treatment within families, and elevated social recognition collectively signify an elevated quality of life among the participants. According to the World Health Organization [26], the physical and psychological aspects of one’s life, their level of independence, social relationships, and the environment are key determinants of one’s quality of life and are the domains in the WHO quality of life assessment (WHOQOL) tool. These findings show that even though WCCI did not apply the standard 100-item WHO assessment tool, the women’s claim of improved quality of life and overall well-being is to a greater extent in accordance with the standard measurements as spelled out in the WHO’s quality of life user manual [26]. The findings therefore imply that WCCI’s model of women’s transformation through the climate change solution satellites is achieving their intended results, however, more standard assessments could be needed to further ascertain these findings.

Strengths and Limitations

The study encompassed a relatively large sample size (96 women), providing a diverse pool of participants engaged in different entrepreneurial activities related to climate change solutions. The study also collected data across various thematic areas, including social, economic, and personal aspects, offering a holistic view of the impacts of women’s engagement in entrepreneurship. The combination of quantitative and qualitative insights provides a comprehensive understanding of the women’s experiences and the findings indicated tangible outcomes such as increased income, asset acquisition, and improved social cohesion, highlighting the practical implications. On the other hand, there could be biases in self-reporting, especially regarding sensitive issues like experiences of violence or attributing them to entrepreneurship, which might lead to underreporting or misinterpretation. To address this, the women were made aware of the importance of giving accurate information and that their responses would be anonymous. The data collection process was also conducted by people who are not part of the trainers to try and make the participants comfortable to air out their issues. In addition, whereas the study highlights positive outcomes associated with entrepreneurship and WCCI training and support, establishing a direct causal link between participation and outcomes might be challenging due to external factors not accounted for in the study. The study however tried to focus on specific attributes provided to the participants through WCCI trainings and eliminated possible external factors.

Conclusions

Overall, participation in these entrepreneurial initiatives has brought about tangible improvements in social cohesion, economic empowerment, and the perceived quality of life and well-being for a significant majority of women involved, demonstrating the positive impact of the WCCI climate change solution satellites on their lives and communities. Through the train the train-the-trainer approach that has been embraced by the women and community, the program ought to be scaled up to enable more women to benefit, contributing to SDG 1.

Declarations

Data and Materials Availability

The data used in this study is available upon reasonable request from the corresponding author.

Ethics Approval and Consent to Participate

Informed consent was obtained from all participants for both the structured surveys and FGDs conducted, after ensuring that they understood the purpose of the research, their rights, and the confidentiality of their responses. The research was also approved by the Uganda Christian University Research and Ethics Committee-approval number UCUREC-2023-55. Measures were also taken to protect the anonymity and confidentiality of participants’ identities and responses.

Authors’ Contributions

All authors conceptualized the study. CHM, AT and GB participated in data collection, and drafted the first manuscript, CHM, GB, AT, RA, RWN, EM, and SD reviewed the first manuscript draft. All authors read and approved the final manuscript.

Funding

Support for this research was made possible through funding support of the Forum for Women and Development (FOKUS) in partnership with the sisters of Joseph and Climate Justice Resilience. The information provided does not necessarily reflect the views of the funders.

Conflict of Interest

Authors Comfort Hajra Mukasa, Godliver Businge, Rosemary Atieno, Rose Wamalwa Nyarotso, Elaine McCarty, Sarah Diefendorf are employed by Women Climate Centers International. The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

References

  1. Women, Gender Equality and Climate Change. 2023 [cited 2023 28th May]; Available from: https://shorturl.at/flxFO
  2. Increasing women’s economic equality would reduce poverty for everyone. 2023 [cited 2023 6th June]; Available from: https://www.oxfam.org/en/why-majority-worlds-poor-are-women.
  3. Akinbami CAO, et al. (2019) Exploring potential climate-related entrepreneurship opportunities and challenges for rural Nigerian women. Journal of Global Entrepreneurship Research 9: 19.
  4. Cardella GM, BR Hernández-Sánchez, JC Sánchez-García (2020) Women entrepreneurship: A systematic review to outline the boundaries of scientific literature. Frontiers in Psychology 11: 1557. [crossref]
  5. Njuguna Nu, TA Théophile (2023) KEYS TO CLIMATE ACTION.
  6. Climate change exacerbates violence against women and girls. 2023 [cited 2023 7th June]; Available from: https://shorturl.at/oqwJY
  7. Tol RS (2018) The economic impacts of climate change. Review of Environmental Economics and Policy.
  8. Hernández Martínez A (2023) Climate change on rural women in East Africa: analysis of consequences and recommendations from a gendered approach.
  9. Nchanji EB, et al. (2022) Gender differences in climate-smart adaptation practices amongst bean-producing farmers in Malawi: The case of Linthipe Extension Planning Area. Frontiers in Sustainable Food Systems.
  10. WCCI-Uganda. WCCI-Uganda is responsible for community training and regional project management. 2023 [cited 2023 28/11]; Available from: https://www.climatecenters.org/wcci-uganda.
  11. Ministry of Local Government-The Parish Development Model. 2021 [cited 2023 28/11]; Available from: https://molg.go.ug/parish-development-model/.
  12. N A T I O N A L P L A N N I N G A U T H O R I T Y, THIRD NATIONAL DEVELOPMENT PLAN (NDPIII) 2020/21-2024/25. 2020, N A T I O N A L P L A N N I N G A U T H O R I T Y,: Kampala, Uganda.
  13. Gomba District Local Government. History. 2023 [cited 2023 27/11]; Available from: https://gomba.go.ug/district/history.
  14. Butambala District Local Government. History. 2023 [cited 2023 27/11]; Available from: https://butambala.go.ug/.
  15. Mukono District Local Government. History. 2023 [cited 2023 28/11]; Available from: https://mukono.go.ug/.
  16. Sanjel S (2013) Gender-based violence: a crucial challenge for public health. Kathmandu University medical journal 11: 179-184. [crossref]
  17. Violence against women. 2021 [cited 2023 22/Nov]; Available from: https://www.who.int/news-room/fact-sheets/detail/violence-against-women.
  18. Ellsberg M, et al. (2015) Prevention of violence against women and girls: what does the evidence say? The Lancet 385: 1555-1566.
  19. Kiani Z, et al. (2021) A systematic review: Empowerment interventions to reduce domestic violence? Aggression and violent behavior 58: 101585.
  20. Kiconco B (2023) The contribution of the presidential initiative for skilling a girl child on women’s economic empowerment in Kampala District, Uganda. 2023, Makerere University.
  21. Ghosh A (2023) Skilling Women in Non-Traditional Livelihoods: Pathways to Women’s Economic Empowerment-Policy Brief. Available at SSRN 4551736.
  22. Singh V (2018) Empowering Women through Skill Development: Interlinking Human, Financial and Social Capital. Productivity. 58.
  23. Sustainable Development Goals-No poverty. 2023 [cited 2023 11th/12]; Available from: https://www.un.org/sustainabledevelopment/poverty/.
  24. Ames D (2009) Pushing up to a point: Assertiveness and effectiveness in leadership and interpersonal dynamics. Research in organizational behavior 29: 111-133.
  25. April K, N Sikatali (2019) Personal and interpersonal assertiveness of female leaders in skilled technical roles. Effective Executive 22: 33-58.
  26. WHO, WHO quality of life user manual. 2012.