National Informatics Centre

Serving as significant coastal ecosystems, mangroves and coastlines offer wide range of services and contribute majorly to the socio-economic persistence to the communities. Coastal zones of the Bhitarkanika region (encompasses Bhitarkanika mangrove), in the eastern coastal state of India, exhibit pronounced geomorphic instability driven by hydrodynamic forcing, sediment disequilibrium, and expanding anthropogenic activities. This study formulates an integrated geospatial framework combining Digital Shoreline Analysis System (DSAS), Coastal Vulnerability Index (CVI), and Binary Logistic Regression (BLR) to quantify shoreline dynamics and assess multi-hazard coastal vulnerability. Multi-temporal shorelines derived from Landsat-8 (2013) and Sentinel-2 (2016, 2019, 2022, and 2025) datasets, corrected for tidal variability and validated using Google Earth. The results revealed a predominantly erosional trend, with 87.80% of transect undergoing shoreline retreat and a mean erosion rate of –11.57 m yr⁻¹. Field observations corroborate approximately 174 m of sediment deposition in accretion zones and ~189 m of land loss across rapidly eroding around the mangrove tract. The CVI was developed using elevation, slope, land use land cover (LULC), proximity to shoreline, river, and road, wherein the parameter weights were computed through Principal Component Analysis (PCA), correlation, entropy weighting, and an Ensemble Weighted Model (EWM). The CVI-based outputs indicate that ~47% of the coastline falls within high to very high vulnerability zone, primarily influenced by low-lying terrain, fluvio-marine interactions, and intense human activities. The BLR-based model demonstrates strong predictive performance (accuracy> 85%) and statistically validates the CVI-based output (>75% spatial agreement). The BLR and ensemble-based approaches represents a robust, multi-criteria framework for coastal vulnerability assessment and critical high-risk zonation. The findings provide reliable spatial intelligence to support shoreline management, mangrove restoration strategies, and climate-resilience planning in the Bhitarkanika coastal system.

Global food security poses a significant challenge in meeting the needs of a rapidly growing population. Currently, producers rely on chemical pesticides to overcome pest-related problems in crop husbandry. However, the extensive use of synthetic molecules results in environmental pollution, resistance development, residual toxicity, pest recurrence and negative impacts on human and animal health. The expanding worldwide population has generated a substantial need for agricultural goods in terms of both quality and quantity, leading to a notable rise in the application of agricultural chemicals, including chemical pesticides, to combat insect pests. As a result, the use of entomopathogens for biological control has emerged as a prominent choice among these options. Currently, farmers are using microbial biopesticide solutions to counteract the negative effects of specific insects on crops. Microbes present a sustainable and adaptable solution that can effectively combat harmful pests without causing significant economic damage while simultaneously improving the health and productivity of plants. In 2020, biopesticides held a 6 % share in the global pesticide industry, with projections indicating a twofold increase to approximately 15 % by 2031. The purpose of this review was to highlight the widely accessible endophytic entomopathogens and explore their potential as a substitute for chemical pesticides. The primary goal of using endophytic entomopathogens is to maintain an optimal level of production, improve environmental well-being, reduce pesticide use and conserve natural resources. Moreover, research is now being conducted to investigate further potential characteristics, particularly concentrating on effective and rapidly spreading endophytic entomopathogens. This paper presents an overview of the mechanisms of action and the resistance they provide against herbivore insects, along with their respective benefits and limitations.

Climate change significantly threatens pulse crop production, particularly C? crops like chickpeas, pigeonpeas, lentils and blackgram, which are highly sensitive to rising temperatures and erratic weather patterns. Even brief exposure to heat stress during critical growth stages can cause substantial yield losses. Integrating advanced information technologies and geospatial tools into agricultural decision-making is crucial to mitigate these challenges. The Decision Support System for Agrotechnology Transfer (DSSAT) has emerged as a powerful crop simulation model that aids in assessing and mitigating climate change impacts on pulse crops. This review explores the role of DSSAT in climate-smart agriculture by integrating soil, weather and crop management data for precise yield predictions. By simulating diverse climatic scenarios, DSSAT facilitates the development of adaptive strategies, including selecting heat-tolerant genotypes, optimizing sowing dates and improving irrigation and nutrient management. Moreover, DSSATs’ ability to evaluate extreme weather events such as droughts and heatwaves enhances its application in risk assessment and sustainable agricultural planning. Despite its advantages, challenges such as data availability, model calibration and regional specificity hinder its widespread adoption. Integrating DSSAT with remote sensing, Artificial Intelligence (AI) and Machine Learning (ML) algorithms further enhances its predictive capabilities, making it a more robust tool for climate-resilient pulse production. By leveraging DSSATs’ potential, policymakers, researchers and farmers can develop climate-smart strategies to ensure sustainable pulse production and food security under changing climatic conditions.

In the realm of cloud computing, reliable detection of threats forms a very important aspect since systems might be at risk. In this research, they proposed a new model that incorporates GANs with transfer learning to allow for the development of accurate detection systems that can identify even the more concealed forms of hacks that are yet to be recognized. Data gathering encompasses compiling a large number of heterogeneous datasets, including historical attack data, network traffic logs, UNSW-NB15, and CICIDS, as well as those obtained from cloud service providers. A novel approach is then proposed that combines both steps: The first step involves the generation of synthetic data through GANs, and the second step involves improving the feature representation of the same. The utilization of the hybrid model has been demonstrated to have an astounding accuracy of 98% when it comes to the capability of recognizing both classic and new types of attacks, as indicated by the assessments. According to the comparative analysis of the results, the proposed hybrid approach that was provided has a higher level of efficiency compared to traditional threat detection systems while also having increased adaptability in different scenarios of cloud computing. This work not only makes a contribution to the improvement of cloud threat detection, but it also offers insights that may be used for the later development and applications of threat detection in a variety of cloud environments.

Research and results: This study examines how meditation affects the brain utilizing fMRI, EEG-fMRI, machine learning, AI, molecular profiling, optogenetics, animal models, and clinical trials. It examines how meditation affects brain oscillations, connection patterns, and neurofeedback mechanisms and its therapeutic potential in Alzheimer's, epilepsy, Parkinson's, migraines, chronic pain, and mental health issues. Meditation increases brain structure, gray matter density, cortical thickness, and information processing speed. Meditation affects neurotransmitters, hormones, and the autonomic nervous system, regulating mood, attention, immunological function, and inflammation. Focus, emotion regulation, empathy, communal bonding, reduced inflammation, enhanced productivity, and illness mitigation are also discussed in meditation. Aim: This study endeavors to inform mental health patients and healthcare providers about the benefits of meditation as a therapy for mental diseases. Methods and tools: A professional psychologist who self-healed from schizophrenia found that meditation may help. Personal experience and literature evaluation inform the research, which includes peer-reviewed papers and empirical research. Psychology ethics provide anonymity and informed consent in the study. The data confirm meditation's therapeutic and mental health effects. Conclusion: The study advances meditation science and lays the groundwork for mental health clinical trials.

Blockchain technology has the potential to bring about a technological revolution in the rapidly evolving digital world by offering a decentralised, distributed, and immutable ledger that can be verified and made accessible electronically over a network. However, blockchains are constrained by disparate problems, including security and privacy. Current blockchain approaches are quite unattainable to survive the privacy difficulties, despite many attempts to devise and combine new privacy solutions. Here we discuss the possibility of using a ring signature with blockchain. The unlinkability and anonymity of ring signatures can be used to preserve blockchain security and privacy. Further, we discuss a real-time implementation that is studied and evaluated with the ring signature model to facilitate user signing by preserving privacy and maintaining anonymity, revealing better efficiency and effectiveness. The findings demonstrate how our method is better and more successful in handling issues with trust and intermediaries in an environment of digital transactions.

Fisheries sector bears significance in terms of its inherent livelihood opportunity, income generation, food and nutritional security.Keeping this in view, the Government of India has introduced the "Blue Revolution" with a target to augment fish production in the country.In India, the Blue Revolution, also known as Neel or Nili Kranti Mission, was started between 1985 and 1990 as part of the 7th Five-Year Plan.The primary goal is to expand, manage, and promote fisheries in order to double farmers' income.In India, the Blue Revolution, also known as Neel or Nili Kranti Mission, was started between 1985 and 1990 as part of the 7th Five-Year Plan.The primary goal is to expand, manage, and promote fisheries in order to double farmers' income.India is the third largest fish producing country, contributing 8 percent to the global fish production and ranks second in aquaculture production.The fish production in 2021-22 is 162.24 lakh Tones comprising of marine fish production of 41.28 lakh Tones and 121.22 lakh Tones from Aquaculture.The objective of the paper is to analyze the impact of the Blue Revolution on the Growth of the Fish production and Indian Economy.In the present paper, an attempt has been made to study the production trend and growth rate for Inland and Marine fish by using statistical techniques.The projected fish production for Inland and marine has been worked for 2026-27 and 2031-32.Finally, recommendations for enhancing production have been suggested.