Vivekananda Global University

Under the framework of sustainable development, ensuring the quality of water for drinking and irrigation purposes presents a complex challenge, as it is influenced by the interrelated effects of multiple surface water management parameters. Therefore, the present study aims to improve the assessment of surface water quality and to evaluate the suitability of surface water networks for domestic and industrial use in Rourkela and its surrounding areas within Rourkela City, Odisha. This region exhibits a high dependence on surface water resources, which are limited in availability, underscoring the need for comprehensive quality evaluation. The WQI (water quality index) of the study region was trained and tested using various ML (machine learning) algorithms employing Python application software. These ML models are: Support Vector Machine (SVM), Random Forest (RF), Extra Trees (ET), Multiple Linear Regression (MLR), Decision Tree (DT), Logistic Regression, K-Nearest Neighbors (KNN), Gradient Boosting (GB), Naive Bayes (NB), and AdaBoost (AB). To achieve this objective, a total of 12 water samples were collected from ten designated monitoring sites over a two-year period (2023–2025) during the pre-monsoon season. The samples were analyzed for key physicochemical parameters, including pH, electrical conductivity (EC), total dissolved solids (TDS), alkalinity, total hardness (TH), copper (Cu2⁺), zinc (Zn2⁺), sodium (Na⁺), potassium (K⁺), lead (Pb2⁺), phosphate (PO43⁻), and iron (Fe2⁺). The Water Quality Index (WQI) approach was applied to assess overall suitability, while Pearson Correlation analysis helped to identify relationships among parameters. Radar distribution maps were generated using Python software to visualize the variability of water quality across the study area. Observed physicochemical results depicts that, localized exceedances in EC, TH, TDS, and trace metals concentrations (Cu2+, Zn2+, Pb2+, Fe2+) highlight potential risks, particularly in areas with higher drinking and agricultural activity. The WA (weighted–arithmetic) WQI results spanned between 40 and 361, indicating that most samples fall within the Poor/ Very Poor/ Unsuitable” WQI classes, suggesting that surface water in the area is generally unsuitable for drinking and household purposes. Pearson’s coefficient visualized that Alkalinity, TH, and K+, are the most influential parameters controlling WQI, while parameters like EC, TDS, Na+, and pH, have a less minimal impact. MLR (Multiple Linear Regression) analysis reveals that, although all examined parameters are statistically significant, sodium (Na⁺), iron (Fe2⁺), potassium (K⁺), and alkalinity exhibit the most substantial influence on surface water quality. This is indicated by their relatively lower standardized beta coefficients, which are closely linked to the observed classification of water as moderately hard in the study area. The statistical ML models' performance was assessed using RMSE, MSE, NSE, and R2. The class-wise ML models' performance was assessed using F1 Score, Precision, Accuracy, Recall, and AUC. The results of this study showed that the highest values of R2, MSE, RMSE, and NSE during the testing and training of models were 0.978, 5.65, 6.85, and 0.98, and 0.988, 4.25, 4.85, and 0.965, respectively. The highest results of class-wise model performance evaluation of F1-Score, accuracy, recall, and precision were 0.969, 0.999, 0.978, and 0.985 respectively. The highest value of the ROC-AUC curve in this study was 0.93 during GB and RF; this indicates that these models were the best for forecasting the WQI of this study. Overall, the findings indicate that surface water in the Rourkela City, is chemically suitable for use at some sampling locations, but continued monitoring is necessary to address localized contamination and to ensure long-term water security for the growing population.

Combines circular economy principles with hydroponics to minimize resource waste and maximize crop productivity. Reuses water, nutrients, and organic by-products to support zero-waste, closed-loop agricultural systems. Reduces land, water, and chemical inputs while ensuring year-round, climate-resilient food production. Transforms agricultural waste into valuable inputs, enhancing efficiency, sustainability, and economic viability. Offers a scalable model for urban and peri-urban farming aligned with zero-waste and sustainability goals. The integration of circular economy (CE) and zero-waste principles into hydroponic agriculture offers a system-level pathway for addressing resource scarcity, nutrient losses, and environmental degradation associated with conventional linear farming. This study develops a structured conceptual and analytical framework that operationalizes CE principles within hydroponic systems through defined system boundaries, closed-loop resource configurations, and a multidimensional performance assessment model. The research employs system mapping, resource-flow analysis, and indicator structuring to translate circular design strategies into measurable environmental, operational, and economic metrics. Unlike prior reviews that primarily discuss conceptual alignment or isolated efficiency gains, this study contributes: (i) a system-boundary-based circular design taxonomy for hydroponic configurations, (ii) an integrated indicator set linking resource circulation efficiency, system stability, and economic resilience, and (iii) a comparative assessment logic distinguishing linear, partial recirculation, and near-zero discharge systems. The analytical results show that circular hydroponic configurations improve resource retention through continuous nutrient recirculation and controlled dosing, minimize discharge via closed-loop management, and enhance operational stability when buffering capacities across water, nutrient, and energy subsystems are aligned. Secondary resource integration, including biomass valorisation and nutrient recovery, further increases system-level circularity and reduces external input dependency. The study identifies capacity balance and feedback control as critical determinants of sustainability performance in tightly coupled bio-physical production systems. By shifting evaluation from yield maximization to resource productivity, variability management, and value retention, the proposed framework advances sustainability assessment in hydroponic agriculture. The resulting model provides a transferable analytical foundation for circular system design, resilience enhancement, and policy-supported scaling of climate-adaptive food production systems.

Microplastics are increasingly recognized as pervasive environmental pollutants with adverse consequences for ecosystems, animal health, and human well-being. Their widespread presence in air, water, soil, and food systems has created chronic, population-level exposure pathways, analogous to occupational hazards that require systematic risk assessment and preventive management. Despite growing scientific evidence on their distribution and toxicity, current responses to microplastic pollution remain fragmented, reactive, and sector-specific. This paper introduces the CLEAN framework—Cut, Lock, Extract, Amend, and Network—as a prevention-driven, OSH-inspired One Health approach that extends worker-level hazard control principles to population and ecosystem health. Cut emphasizes source reduction through sustainable material design, circular economy practices, and low-waste manufacturing. Lock focuses on containment and filtration across industrial and environmental pathways, including advanced wastewater treatment, stormwater controls, and upstream capture technologies. Extract addresses the removal of legacy microplastic contamination from soils, sediments, and aquatic systems using nature-based and engineered remediation methods. Amend supports ecosystem restoration through habitat protection and soil–water amendments that enhance microbial, plant-based, and physicochemical recovery processes. Network promotes cross-sectoral collaboration and policy alignment, integrating community engagement with national and global governance mechanisms to ensure harmonized standards, transparent monitoring, and effective risk communication. By synthesizing insights from environmental monitoring, toxicology, epidemiology, and policy analysis, the CLEAN framework provides a structured, multi-level roadmap that links scientific evidence with actionable interventions. Its application demonstrates that coordinated, prevention-oriented strategies—analogous to occupational risk management—can reduce exposure risks, strengthen ecological resilience, and safeguard public health. Compared to existing fragmented approaches, CLEAN offers a novel, replicable, and scalable population-health hazard management model for advancing One Health solutions to microplastic pollution. The framework’s adaptability allows it to be tailored across diverse socio-ecological contexts, from highly industrialized regions to resource-limited communities, ensuring that interventions remain both equitable and effective. By integrating preventive controls with restorative actions, the CLEAN framework not only addresses current contamination but also establishes mechanisms to curb future accumulation, positioning it as a forward-looking blueprint for policymakers, industries, and communities confronting an increasingly urgent global environmental challenge. Introduces the CLEAN framework as a holistic tool to manage microplastic pollution through multi-sectoral coordination. Aligns microplastic mitigation strategies with the One Health paradigm, emphasizing interconnections between human, animal, and environmental health. Advocates for systems-based thinking to identify leverage points across policy, industry, and community sectors for sustainable plastic lifecycle management. Encourages collaboration among scientists, policymakers, healthcare professionals, and community stakeholders to co-develop context-specific interventions. Promotes continuous learning and adaptive evaluation to ensure interventions are responsive to emerging microplastic risks and health impacts.

Organizations usually rely on stringent access control mechanisms where access policies are an important asset. Their storage or transmission in plaintext can compromise sensitive access rules. It is important in dynamic environments where access decisions are made in real time such as Zero Trust (ZT). Existing ZT approaches were found to oversee the aspect of securing these policies. This investigation presents a Multi-layer Access Policy Encryption System for ZT systems (MAPE-ZT). The first stage uses the trapdoor index to generate a secure index to find the applicable access policies. Advanced Encryption Standard-256 is used in counter mode for the encryption of the policies. They are re-encrypted using the Ciphertext-Policy Attribute-Based Encryption (CP-ABE) to allow decryption based on a matching set of attributes. Various experiments using quantitative metrics, including comparison with baseline access control systems simulation, scalability evaluation, storage overhead, etc., highlight the efficacy of the MAPE-ZT and establish new benchmarks. The result count entropy for the policies ranged 3.84–4.21 for different scales of policies. The evaluation in different scales of systems shows that the MAPE-ZT reduces various observable patterns even if the deployment size grows. Its unique design of securing policies makes this approach scalable for multi-domain integration.

This study undertakes a comparative examination of ancient Indian taxation philosophy, as articulated in classical texts such as the Arthashastra and Manusmriti, and the contemporary Indian tax system shaped by constitutional mandates and reforms such as the Goods and Services Tax (GST). Drawing on qualitative textual analysis and modern public finance theory, the research analyzes tax structures, revenue sources, expenditure priorities, administrative mechanisms, and ethical foundations. The findings reveal normative continuities in proportional taxation, welfare orientation, administrative accountability, and fiscal moderation, alongside significant institutional transformations driven by democratization, federalism, and digitalization. While ancient fiscal philosophy emphasized moral duty (dharma) and state responsibility, modern taxation operates within constitutional legality, technological infrastructure, and global economic integration. The study recommends integrating historically grounded ethical principles such as predictability, moderation, and administrative integrity into ongoing tax governance reforms. Future research should extend this comparative framework through empirical evaluation of taxpayer trust, compliance behaviour, and fiscal legitimacy in contemporary India, as well as comparative studies across other civilizational traditions. By bridging Indian Knowledge Systems and modern public finance theory, the paper contributes to interdisciplinary debates on sustainable and equitable revenue systems.

Precise targeting of the tumor micro-environment (TME) through nanotherapeutic innovations offers a transformative approach to cancer treatment. In order to increase the treatment efficacy, this review delves into the complex tactics for targeting different parts of the TME. Targeting the extracellular matrix, controlling acidosis and hypoxia, and preventing neovascularization by concentrating on pericytes and endothelial cells are important areas covered in this article. Strategies to stimulate anti-tumor immunity, regulate chronic inflammation, and restrict macrophage recruitment emphasize the immune system's participation. We have also highlighted the role of fibroblasts and exosomes linked to the cancer progression. The EPR effect, which is vital for cancer nanotherapeutics to work, and vascular pathophysiology are also included in the review. We examine how changes to the dynamics of pH inside the TME affect by nano-therapeutics. Additionally, the possibility of prodrug therapy within the TME, the use of controlled release mechanisms in nanocarriers to imitate metronomic therapy has been discussed. Lastly, the paper examines nanoparticle preference targeting as a potential strategy to improve treatment specificity and therapeutic efficacy in cancer management.

In nature, bioconvection generated by motile microorganisms may offer great opportunities in various applications such as environmental engineering, renewable energy technologies, and biomedical applications. In this paper, for the enrichment of heat transport and the regulation of bioconvection, a trihybrid nanofluid composed of gold (Au), silver (Ag), and multi-walled carbon nanotube (MWCNT) nanoparticles are considered within an MHD flow over a stretching cylinder. Unlike common single-nanoparticle nanofluids, trihybrid nanofluids utilize the synergistic behavior of multiple nanoparticles to achieve superior thermal conductivity, improved energy transport, and increased stability of fluids. The various key physical mechanisms incorporated here are thermal radiation, internal heat generation or absorption, electroosmotic effects and electromagnetic forces, to evaluate their impacts on microbial motility and bio-convective flow behavior. Furthermore, an activation energy-based chemical reaction is considered to show the moderation in microbial activity and enhancement in system performance. This set of coupled nonlinear partial differential equations is reduced to a system of ODEs by invoking proper similarity transformations and solved numerically via the Galerkin finite element method (G-FEM). Both multiple linear and quadratic regression analyses have been performed to develop the predictive models. It has been observed that the quadratic model presents more reliable and accurate predictions compared to the linear one. In general, the results show that bioconvection can be effectively controlled through adjusting parameters of the bioconvective Schmidt number, Peclet number, and Biot number to enhance heat and mass transfer characteristics of the system.