Alliance University

This chapter interrogates the constitutive role of education in shaping economic futures in the Global South, arguing that educational systems function both as narrative infrastructures, i.e., constructing societal grammars of value, success, and belonging, and as systemic design spaces, structuring the material conditions under which these narratives are enacted. Integrating insights from narrative economics, systemic design theory, and decolonial pedagogy, it examines how colonial legacies, neoliberal reforms, and alternative pedagogies influence economic subject formation. Drawing on case studies from Asia, Africa, and Latin America, including Bhutan's GNH schools, Brazil's Landless Workers' Movement, and innovation hubs across Africa, it demonstrates that plural, justice-oriented models are operational realities. The chapter advances a framework for scaling such innovations through policy reform, participatory governance, and post-growth valuation systems, positioning education as a generative commons for building equitable, sustainable, and pluriversal economies.

The current research has proposed an innovative methodology to enhance PVA/CSP/AgNPs hybrid biocomposite films by integrating the CRITIC and CoCoSo multi-criteria decision-making (MCDM) frameworks with machine learning techniques. Bio composite films can be used in medicine, packaging, and environmental applications. The biocomposite films were developed by mixing polyvinyl alcohol (PVA), coconut shell powder (CSP), and silver nanoparticles (AgNPs) to attain better mechanical, thermal, and antibacterial properties. The experimental design comprises 25 distinct trials to assess the tensile strength (TS), Young’s Modulus (YM), percentage elongation (%E), and maximum degradation temperature (T) of the fabricated composite films. CRITIC method was adopted to evaluate the weights of the criteria in an unbiased way, and CoCoSo technique ranked the alternatives. The results were analyzed using supervised machine learning algorithms, including Random Forest, Neural Network, Linear Regression, and AdaBoost. AdaBoost algorithm demonstrated superior performance with an R 2 value greater than 0.98 for all output responses. Decision tree analysis revealed that the composition of silver nitrate significantly influences tensile strength, while coconut shell powder affects Young’s modulus. The optimized film, composed of PVA/20%CSP/4 mM AgNPs, exhibited improved UV-shielding, reduced water absorption (26.2%), and decreased soil weight loss (41.4%). SEM images confirmed the uniform dispersion of AgNPs within the PVA matrix. The integration of CRITIC-CoCoSo with machine learning provides a scalable approach for designing multifunctional bio-composites with enhanced properties for sustainable applications.

Abstract Each year, millions of tons of fly ash (FA), a hazardous byproduct of coal-fired power plants, are disposed of in landfills, causing serious environmental pollution and substantial health risks. Consequently, effective FA management has become critically important. Despite its popularity in the construction sector, FA has rarely been used to create multifunctional porous materials capable of addressing heat insulation, CO 2 capture, and wastewater purification. This paper reports the successful development of highly durable, lightweight, flexible and multifunctional xerogels derived from FA. The FA was chemically modified and blended with cellulose nanofibers (CNFs), a binder, and a crosslinker to enhance structural stability and multifunctionalities. The resulting xerogel exhibited a compressive strength of 293.5 ± 9.6 kPa and a Young’s modulus of 264.1 ± 6.8 kPa at 70% strain, representing an increase of 86.6% in strength and 94% in modulus compared to pure CNF xerogel. Moreover, it exhibited excellent thermal conductivity of 32.1 mW/m.K, and a CO 2 adsorption capacity of 1.67 mmol/g, superior to many contemporary materials. Interestingly, the xerogel also performed extremely well in selectively removing both cationic and anionic dyes from water. These results highlight the effectiveness of our formulation and design approach in producing a robust multifunctional xerogel. With its simple fabrication process, lightweight structure, mechanical robustness and multifunctionality, the developed xerogel emerges as an attractive solution for wastewater management, CO 2 mitigation and building insulation.

In present work, tribology tests were enacted to analyze the wear behavior of composite reinforced with Aloe vera, Corn, Eucalyptus and Soybean Fiber and Epoxy resin. Fatigue and creep tests were accomplished to evaluate the strength of prepared composite specimen under fluctuating and static load conditions. Tribological analysis revealed that hybrid composites achieved higher frictional force as compared to single fiber-based composites. Hybrid ACESE composite exhibits maximum frictional force of 14.01 N, 35.78 N and 37.46 N at 10, 30 and 50 N load for 5 m/s sliding speed as compared to other prepared composite specimens. COF of prepared composite samples were calculated at different sliding speeds (3, 5 and 7 m/s) and applied load of 10, 30 and 50 N load. Hybrid ACESE composite shows maximum value of COF at 10, 30 and 50 N load for 3, 5 and 7 m/s sliding speed. Sliding speed (3, 5 and 7 m/s) with respect to applied load (10, 30 and 50 N) shows the variations in specific wear rate (SWR) for all prepared specimens. During tribological analysis, higher frictional force achieved by hybrid ACESE composite exhibits the highest value of interfacial temperature at 5 m/s sliding speed for 10, 30 and 50 N applied load. While the lower value of frictional force achieved by CE composite displays the lowest value of interfacial temperature at 5 m/s sliding speed for 10, 30 and 50 N applied load. The fatigue test illustrated that hybrid ACESE composite attained the highest fatigue number of cycles at 3822, 3217 and 2218 for 25, 50 and 75% UTS. While CE composites resulted in the lowest fatigue number of cycles at 2234, 1826, and 1219 for 25, 50 and 75% UTS among all prepared specimens.

Dementia is an emerging public health challenge in India, particularly among older adults in rural and underserved regions. Early detection is crucial for timely intervention and care planning. However, existing screening tools, such as the Mini-Mental State Examination (MMSE) and the Montreal Cognitive Assessment (MoCA), have limitations in low-literacy populations due to their reliance on reading, writing, and numeracy skills. In India's primary healthcare (PHC) settings-where time, training, and resources are limited-there is a critical need for a culturally appropriate, easy-to-administer cognitive screening tool. This study aimed to develop and validate a brief, culturally relevant, and literacy-independent tool-the Primary Healthcare Cognitive Screening (PHC-CS) tool-for the early detection of cognitive impairment among adults aged 50 years and above in Indian primary healthcare settings. The PHC-CS tool was developed through a multistep process, including a literature review, expert consultation, and field testing. The final 21-item tool assessed eight cognitive domains (memory, attention, language, visuospatial ability, executive function, orientation, constructional ability, and mental flexibility) using orally delivered tasks supported by visual aids. The tool was administered to 172 participants at a rural PHC in Karnataka. MoCA scores and neurologist-confirmed ICD-10 diagnoses served as reference standards. Psychometric validation included ROC curve analysis, internal consistency (Cronbach's alpha), test-retest reliability, and interrater agreement. At an optimal cutoff score of <45, the PHC-CS tool demonstrated an area under the ROC curve of 0.957 (95% CI: 0.922-0.992), with a sensitivity of 95%, a specificity of 92%, a positive predictive value of 96%, and a negative predictive value of 92%. Internal consistency was strong (Cronbach's alpha = 0.90), with good test-retest reliability (r = 0.88) and interrater agreement (κ = 0.88). The average administration time was 15 minutes. The PHC-CS tool demonstrates promising preliminary validity and feasibility for routine cognitive screening in Indian PHC settings, particularly for low-literate populations. Further multicentric validation is recommended.