The increasing number and intensity of floods in India show the urgent need for better early-warning systems that combine different data sources and modeling methods. To address this need, this paper introduces the Multi-Source Hybrid Framework (MSHF). MSHF merges an LSTM-Transformer module for analyzing rainfall and discharge patterns over time, a Graph Neural Network for understanding spatial dependencies in river networks, a satellite-radar fusion pipeline for detailed precipitation mapping, and a social media sentiment analyzer for gathering situational awareness from crowdsourcing. All these elements are connected by an attention-based ensemble meta-learner. MSHF runs on a cloud platform that processes real-time gauge and weather data from over 200 stations in the Brahmaputra, Ganga, and Krishna basins. It generates rolling six hour forecasts with an end-to-end delay of under five minutes. Trained on historical events from the INDOFLOODS database and validated with data from 2021 to 2024, MSHF achieves over ninety-five percent predictive accuracy and high hydrological efficiency. A comparative evaluation against standalone LSTM-Transformer, GNN, satellite-radar, and social media models uses paired t-tests and chi-square goodness-of-fit tests to confirm significant statistical improvements. Targeted ablation experiments—Temporal, Spatial, Fusion, Social, and Attention Ablations—show that removing any component significantly reduces performance. Operational trials also demonstrate consistent detection of severe flood events with few false alarms across various lead times and river basins. This emphasizes MSHF’s readiness for proactive flood risk reduction in India’s diverse hydrological contexts.

Rajesh Kumar Prasad has taught at Chanakya University’s School of Engineering since January 2025. He is interested in Fluid and Thermal Sciences, Modern Engines and Ignition systems, Refrigeration and Air-conditioning and Laser fired combustion. Earlier he has served as Head of Mechanical Engineering Department, Chhatrapati Shahuji Maharaj University Kanpur formally known as Kanpur University from September 2022 to December 2024. He also served as Assistant Professor in ICFAI university Jharkhand from September 2019 to September 2022 and many more. He also served as NAAC Coordinator, Mechanical Engineering Department, CSJM University Kanpur (A++) from 1st October 2022 to 23rd December 2024 And Assistant Dean, Innovation Cell, CSJM University Kanpur (A++) from 1st October 2022 to 23rd December 2024. Prasad teaches Basic Thermodynamics, Fluid Mechanics and Machines, Heat transfer, Refrigeration and Air-conditioning, Internal combustion engines in the core curriculum and an elective course. He has published widely cited work on “Elsevier” Journals ( Q1) like Fuel, Energy, Applied Energy, Renewable Energy etc. and Scopus indexed Book Chapter in “Springer Nature”. He has also published several text books on Mechanical Engineering Courses as author/co-author.

Banu Priya Mohan has taught at Chanakya University’s School of Engineering since 2024. She is interested in deep learning for healthcare, artificial intelligence in diagnostics, database systems, and cloud technologies. She has held prior academic positions at CMR University, ICEAS Bangalore, SEA College of Engineering and Technology, CMR Institute of Technology, and Impact College of Engineering and Applied Science. She is currently pursuing her Ph.D. in Artificial Intelligence at Vels University, Chennai, where her research focuses on building interpretable deep learning models for early disease detection using multi-modal healthcare data. She has co-authored work on lightweight cryptographic security in IoT environments, recently published in the Journal of Information Systems Engineering and Management. Her published design patent on “Patient Monitoring System with Mobile Alerting for Early Detection in Smart Health Environments” reflects her applied interest in smart healthcare innovation. In her project AI-Powered Early Detection System for Ovarian Cancer, she integrates clinical and imaging data with attention-based deep learning models, while incorporating explain ability techniques such as SHAP and LIME to support transparent decision-making in clinical settings.

Uttar Pradesh has a huge upside potential for economic growth if its people are engaged more productively. This study cursorily reviews the prospects of employment creation and argues that UP should focus on the secondary and tertiary sectors for generating self-employment opportunities. In this regard, growth diagnostics framework, developed at Harvard University, is used to analyse the possible constraints that may be impeding the entrepreneurship in the state. Based on secondary data analysis and wider consultation with many stakeholders, study provides observational conclusion that ‘access to finance’ can be a major constraint in growth of enterprises. This constraint is channelled through high-risk perception and aversion for microentrepreneurs from supply side of f inance. Additionally, other constraints such as coordination, infrastructure, lower desire for entrepreneurship among youth are also weakly identified. The study concludes with offering focused recommendations to deal with the identified obstacles in a systemic way, hitting their root causes.

Dr. Madhuri Mukhopadhyay is a passionate researcher specializing in ultrafast coherent spectroscopy and nonlinear optics both in experiments and theory. She believes in “eduvate,” a blend of education and innovation, and is a lifelong learner. She is a dedicated educator, she has a wide range of expertise that includes quantum mechanics, electromagnetic wave, light-matter interaction, computation, and material properties. Her recent research interests focus on the nonlinear optical behaviour of nano-photonics, controlled dissipation during exciton transport, and the application of deep learning in ultrafast spectroscopy. In her leisure time, Madhuri loves to travel and play badminton.

Educational institutions plays a crucial role in providing electronic resources to research scholars, students, and professionals. To ensure the integrity of licensed information and prevent malpractices, these institutions must uphold ethical standards. Additionally, they should raise awareness among users about issues such as copyright, data duplication, plagiarism, and other related concerns. This study is on Karnatak University research scholars for consideration of the ethics. Most of the respondents i,e., 41(68.3%) are aware of the copyright laws related to e-resources, only 1(1.7%) respondent never used open access resources for reference purpose and mainly this study found that the respondents i.e., 23 (38.3%) are strongly agreed the statement that yes very clearly communicated about ethical guidelines in using e-resources.