The Global Research Network for Verified Scholars

This article develops a new penalty-based aggregation operator known as the penalty-based induced ordered weighted averaging (P-IOWA) operator which is an extension of penalty-based ordered weighted averaging (P-OWA) operator. Our goal is to figure out how the induced variable realigns penalties when gathering information. We extend the P-OWA and P-IOWA operators with the different means such as generalized mean and quasi-arithmetic mean. This article also includes different families of P-OWA and P-IOWA operators. The value of these new operators is demonstrated through a case study centered on investment matters. This study evaluates the economic and governance performance of seven South Asian nations utilizing nine indicators from 2021 data. The research examines 5 economic indicators including GDP growth, exports and imports (% of GDP), inflation, and labor force metrics, alongside 4 governance indicators focusing on corruption control, government effectiveness, and political stability. We use min–max normalization to standardize the varied values, which originally ranged from 0.5% to 77.7% across various metrics. Following this, the normalized inverse penalty method is used to derive optimal weights for these indicators, tackling the task of combining multidimensional data. Subsequently, we implement and evaluate various penalty-based aggregation methodologies on the normalized data, each offering a distinct approach to penalizing outliers and balancing indicator weights. The study compares the results obtained from these operators to assess their impact on country rankings and overall performance evaluation. This approach allows for a comprehensive comparison of countries’ performances, integrating both economic and governance dimensions into a single, quantifiable framework.

Blockchain enables decentralized, tamper-evident, and auditable data sharing among untrusted parties, but deployments face a trade-off between scalability and privacy. Public blockchains expose transactional metadata, risking confidentiality, while privacy-preserving approaches like zero-knowledge proofs (ZKPs) often reduce throughput and increase latency due to proof computation. Scalability methods—Layer-2 rollups, sharding, state channels—typically offer limited privacy, leaving metadata open to inference attacks. We propose a privacy-preserving, scalable blockchain architecture for secure data sharing in distributed environments such as federated clouds, healthcare networks, IoT ecosystems, and inter-bank settlements. The design combines Layer-2 zero-knowledge rollups with a modular Layer-1 settlement layer (Ethereum or Hyperledger Fabric), decentralized storage (IPFS/Filecoin), and fine-grained access control. Transactions are batched off-chain, validated with succinct ZK proofs, and only aggregate proofs and state roots are committed on-chain, enabling confidentiality with high throughput. The architecture, deployed in a Kubernetes-orchestrated environment, supports horizontal scaling, automated failover, and observability via Prometheus, Grafana, and Jaeger. A prototype shows up to 5.8× throughput gains over baseline privacy-preserving blockchains while keeping latency within acceptable limits. Evaluation against three baselines—Layer-1 only, Layer-1 + privacy, and Layer-1 + scalability—using throughput, latency, cost, privacy efficacy, and fault tolerance confirms that integrating privacy-preserving cryptography with scalable rollup architectures is both feasible and effective for secure, high-performance blockchain systems.

Water scarcity is increasingly becoming a global concern, intensified by urbanization, climate change, and unsustainable water management practices. In India, major industrial cities like Jamshedpur remain under severe water stress situations arising from increasing demand, pollution, and infrastructure‐less efficiency. This study looks into the present water crisis in Jamshedpur by describing major drivers for it, reviewing past trends, and then suggesting sustainable options that might fit in well with the particular socio‐industrial conditions of the city. A GIS‐based spatial analysis using Kriging interpolation of groundwater records (2010–2022) was performed, followed by validation having an RMSE value of 0.00424 bcm. In addition, the study scrutinized government reports, local‐level case studies, and institutional records that attempted to gauge demand, pollution levels, and governance challenges. The findings highlight a 20%–30% gap between water demand and supply as well as a massive groundwater decline in some places where the water level is going down by over 10 m in 10 years. Such a scenario arises due to industrial overexploitation and a terribly fragmented governance scenario. Spatial maps are shown concerning at‐risk areas with respect to a water crisis in the future. To achieve long‐term water security, the study suggests the implementation of integrated water resources management (IWRM), rainwater harvesting, wastewater reuse, and making a strong push for public‐private partnerships while promoting community engagement, as well as data‐based decision‐making, to increase climate resilience. The findings are not only relevant to Jamshedpur but also offer a replicable framework for other industrial cities grappling with water scarcity under climate uncertainty.

Despite global progress, digital health adoption in low-income countries remains uneven. Pakistan presents a critical case due to its large population, rural-urban disparities, limited public health expenditure, and emerging yet fragmented digital initiatives. While global trends show a shift towards E-Health, Pakistan presents a unique case study where these global innovations meet specific local implementation barriers.

Introduction The dawn of digitalization brings with it a plethora of opportunities to streamline processes and optimize efficiency. However, as we integrate AI and automated workflows into our daily operations, we risk overlooking the heart of our organizations: the people. Emotional intelligence (EQ) becomes a guiding compass, allowing us to navigate this complex terrain with grace and awareness. By harmonizing technological advancements with the human experience, we can cultivate workplaces that are not only efficient, but also enriching and supportive.