Arka Jain University is a private university located in Gamharia, Seraikela Kharsawan district, Jamshedpur, Jharkhand, India. It was established under Arka Jain University Act on 14 July 2017.
Aluminum matrix composites are progressively utilized in automotive, aerospace, and structural applications that necessitate lightweight materials with superior wear resistance and consistent frictional properties under rigorous operating conditions. Enhancing the tribological performance of aluminum alloys by appropriate reinforcement techniques and effective multi-objective optimization is a significant task. This work examined and refined tribological attribute of stir-cast AA8011 aluminum matrix composites augmented with bimodal micro-sized silicon dioxide (SiO₂) particles. A constant reinforcement content of 5 wt
In modern cryptography, improving the cryptographic security of Zero-Knowledge Proofs (ZKP) has become a compelling trend. Traditional models like the zk-SNARK and zk-STARK has shown strong security but are accompanied by the inherent issues of computational complexity and proof size. This work presents the Algebraic Zero-Knowledge Proof (AZKP) framework, using algebraic structures and integration of elliptic curves to optimize proof creation and verification. The suggested approach fills in key gaps found in the current methodologies, such as huge computational overhead and enormous proof sizes. Prime factorization in algebraic groups and ring homomorphisms of the AZKP framework is used to achieve small proof size without sacrificing computational efficiency. Comparing AZKP with zk-SNARK and zk-STARK models, experimental evaluation was applied to four critical performance metrics. generation time of proof, verification time, size of proof, and computational overhead. Results show that the AZKP is able to make a 48% decrease in proof generation duration and 20% increase in verification speed in comparison to zk-SNARK. Also, AZKP incurred lower computational cost than zk-STARK, with a proof size that is manageable. These results highlight the prospect of AZKP in cryptographic use where highspeed low-latency verification operations are desired. Further research will integrate AZKP in blockchain environments in order to increase real-time transaction validation.
Climate-Smart Agriculture (CSA) has emerged as a pivotal framework for achieving sustainable food security under accelerating climate change. Rooted in three interlinked pillars—productivity enhancement, resilience building, and greenhouse gas (GHG) mitigation—CSA integrates diverse interventions that align agronomic innovation with climate action. Core strategies include climate-resilient crop varieties, conservation agriculture to sustain soil fertility, agroforestry systems for carbon sequestration and biodiversity conservation, and precision agriculture leveraging digital tools for efficient resource management. Meta-analytical evidence indicates that CSA adoption can raise equivalent yields by up to 38%, while biochar application enhances productivity by 15.1% and reduces global warming potential by 27.1%. Climate-Smart Agriculture enhances food security by increasing productivity and resilience, and reducing emissions. Meta-analyses indicate that CSA can increase equivalent yields, standardized output adjusted for crop type, energy or economic value, by as much as 38%, with practices like biochar further increasing productivity and reducing climate impacts. Growing investments around the world are foregrounding the role of CSA in realizing a ''triple win'' for agriculture. Similarly, improved nutrient and soil management practices significantly curb nitrous oxide (N₂O) emissions, strengthening the productivity–mitigation nexus. At the policy scale, global momentum is accelerating—the World Bank has expanded CSA financing portfolios, the United States invested USD 19.5 billion under the Inflation Reduction Act, and countries such as India and Kenya have mainstreamed CSA within national adaptation strategies to empower smallholder farmers. Collectively, CSA delivers a “triple win” of enhanced productivity, adaptive capacity, and climate mitigation, positioning it as a cornerstone for resilient and low-carbon agri-food systems of the future.
The convergence of regenerative engineering and circular bioeconomy principles has stimulated growing interest in waste-derived carbon materials as candidates for sustainable scaffold design. This review critically examines porous carbon scaffolds and carbon-hydrogel composites derived from agricultural residues, food-processing byproducts, and polymeric waste for applications in bone, cartilage, wound, and neural tissue engineering. Particular emphasis is placed on feedstock selection, fabrication routes, purification requirements, structure-property-function relationships, and biological performance in vitro and in vivo. Waste-derived carbons offer tunable porosity, large surface area, electrical functionality, and adaptable surface chemistry, which together can support cell attachment, mineralization, angiogenesis, and electroactive tissue responses. Carbon-hydrogel systems further improve mechanical stability, swelling control, and multifunctionality, especially in soft and osteochondral tissue applications. At the same time, their translational promise is constrained by precursor heterogeneity, impurity removal, batch-to-batch reproducibility, long-term biosafety, and regulatory qualification. The review, therefore, evaluates these materials not only from a performance perspective but also through the lenses of standardization, sustainability, and clinical manufacturability. Overall, waste-derived carbon biomaterials are promising but remain preclinical platforms, and their future clinical relevance will depend on rigorous purification, quality control, and evidence-based translational pathways. This review aligns with Sustainable Development Goals (SDGs) 3, 9, and 12 by linking regenerative healthcare materials to sustainable waste valorization.
This research addresses the critical challenge of deploying sustainable grid-compatible Electric Vehicle charging infrastructure in view of India's power distribution systems. The research presents an integrative decision-making framework that synthesizes four complementary analytical approaches-SWOT analysis for internal capacity assessment, PESTELI examination of broad contextual factors, SOAR methodology for goal-oriented strategic planning, and NOISE analysis for operational gap identification to create a holistic evaluation model for charging infrastructure deployment priorities. Qualitative findings from this multidimensional assessment are systematized into measurable decision parameters through Saaty's Analytic Hierarchy Process (AHP), with subsequent ranking and prioritization accomplished via the TOPSIS algorithm. When applied to India's distribution landscape, the framework identifies critical success factors such as government support systems, current grid capacity, the ability to connect renewable energy sources, and the readiness of the stakeholders. The systematic analysis reveals that the biggest problems are high capital costs, not being able to get to some places, and charging infrastructure-related issues. When considering smart grid modernization, integrating renewable energy, and technology-driven solutions, also highlighting the pros and cons of each option. Some of the risks identified in this study are digital security and uncertainty about regulations. This comprehensive assessment finds its importance by enabling distribution authorities, governmental bodies, and market participants to implement incremental infrastructure improvements to enhance grid resilience, optimize operational efficacy, and establish open-access electric vehicle charging networks. The framework also helps strategic planners balance technological needs, economic trade-offs, environmental imperatives, and policy goals in EV infrastructure development.
