Resource
2026 EN
Panigrahi Ansuman · Dandsena Rutuparna Sibani · Mohanty Swati Sambita
+2 more
Nipah virus (NiV) is a significant public health issue because of its high fatality rate and frequent outbreaks. This systematic review synthesizes key spillover and transmission patterns and evaluates ecological management strategies to inform priority interventions and resource allocation. Following PRISMA guidelines, we searched multiple electronic databases, including PubMed, Embase, and Scopus. Study selection, data extraction, and quality assessment were done by three independent reviewers, with a fourth reviewer resolving any disagreements. Close contact with NiV patients, especially during household caregiving and in healthcare settings, drove human-to-human transmission, while consumption of raw date-palm sap was a major spillover pathway. Outbreak contexts differed: pig-amplified spillover in Malaysia; recurrent seasonal bat-to-human spillover in Bangladesh linked to sap; and sporadic outbreaks in India associated with suspected exposure to bat-contaminated fruits or environments, with secondary transmission mainly in households and healthcare settings. Bamboo sap skirts reduce, but do not eliminate, bat contamination of sap, supporting their use as a risk-reducing ecological intervention. Studies have reported various transmission and spillover pathways; however, data on exact modes and pathways remain scarce. Management strategies must also report feasibility and acceptability, and greater emphasis is needed on ecological management practices. https://www.crd.york.ac.uk/prospero identifier is CRD42024546848.
Journals
2026 EN
Rambha Devi Konsam · Sahu Ramendu Bikas
This study examines the cyclic response of inorganic and organic clays under undrained and semi-drained conditions using stress-controlled triaxial loading. Key focus areas include deformation behaviour, pore pressure evolution, and cyclic stress resistance. Reconstituted samples were tested at 100 kPa confining pressure and 0.1 Hz frequency across varying cyclic stress ratios (CSR) to simulate field-relevant loading. Results show that organic clay, despite generating higher pore pressures, exhibited lower axial strains than inorganic clay. Semi-drained conditions delayed instability and reduced axial strain, with a 52% reduction for inorganic and 23% for organic clay at CSR = 0.35 after 100 cycles. The coefficient of consolidation was higher in organic clay under semi-drained loading, while pore pressure influenced the compression behaviour, especially beyond a pore pressure ratio of 0.4. Changes in the consolidation coefficient with loading cycles were found to be independent of CSR for both soil types.
Journals
2026 EN
Chaudhary Vijay · Sahu Rohit · Ahlawat Chanchal
+4 more
The increasing global dependance on plastics made from synthetic materials has led to noteworthy ecological apprehensions because of their non-biodegradable nature. The mechanical and water retention characteristics of composites with corn, aloe vera, soybean, and eucalyptus fibers are the main topics of this study, which investigates the possibilities of natural fiber-reinforced polymeric composites (NFRPCs) as environmentally friendly substitutes. These composites, which were made with an epoxy matrix and the hand lay-up technique, were submerged in water for a six-month period to evaluate any changes in their surface morphology and mechanical characteristics. The following characteristics were assessed after the water submerged activity: hardness, elongation at break, impact strength, flexural strength, tensile strength, and surface roughness. Composites made of aloe vera and epoxy showed the largest increases in surface roughness and the largest percentage losses in tensile strength, impact strength, flexural strength, and flexural modulus. Compared to other composites, the soybean/epoxy composites showed a significant shift in elongation at break after water absorption and retained a better tensile strength. Corn/epoxy composites exhibited the lowest percentage change in tensile strength and hardness, whereas eucalyptus/epoxy composites had the least percentage shift in impact strength and surface roughness.
Journals
2026 EN
Yadav Anupam · Al-Asady Heba Abdul-Jaleel · Narmadha T
+7 more
This study introduces a student-centred informatics framework designed to predict the risk of depression among students, with the aim of supporting early mental health interventions and personalized educational support. The framework integrates two ensemble machine learning models Logistic Regression Classifier (LRC) and Extra Trees Classifier (ETC) optimized using Subtraction-Average-Based Optimizer (SABO) and Golf Optimization Algorithm (GOA) to enhance predictive accuracy and interpretability. The dataset, collected from a large and diverse student population, includes variables related to study stress, sleep duration, and academic satisfaction factors frequently linked to student mental health. A feature sensitivity analysis using ANOVA ranks these variables by influence, offering insights into potential intervention points. The optimized ETC model (ETSB) achieved an accuracy of 0.9638 (96.38%), significantly outperforming other single and hybrid models. Beyond technical performance, this framework provides a potential digital health tool for use in school health systems or student support platforms. By identifying at-risk individuals early, the study contributes to the development of more equitable, data-informed, and preventive mental health strategies within educational environments.
Journals
2026 EN
Chandel Surya Pratap Singh · Singh Monika · Sahu Praveen Kumar
In the contemporary energy landscape, coal remains a dominant choice due to its widespread availability and cost efficiency. However, addressing the pressing need to mitigate fuel expenses and emissions demands enhanced operational efficiency. Enter SUPERTHERM K2R, a versatile combustion catalyst meticulously crafted to optimize the combustion process of Coal/Petcoke, the primary fuels across various industries. This innovative solution aims to curtail direct fuel consumption by 10–15%, offering efficacy across diverse coal variants including Indian, Indonesian, Australian, South African, US Coal, and Petcoke. The key advantages of this coal additive encompass reduced coal usage, diminished pollutant emissions, decreased trace metal presence, and mitigated land degradation resulting from mining activities. There are some auxiliary advantages with this product like – reduction in coal crusher power consumption, reduce forced draft (FD) fan power consumption, reduce coal handling cost because of less coal consumption as compare to normal operation of industry. In case of power plant increased consumption of demineralized (DM) water has been observed.
Journals
2026 EN
Mishra Krish. · Srivastava Satyam · Srivastava Prashansha
+2 more
Citral, a natural monoterpene aldehyde, is used in fragrances, food, and pharmaceuticals. However, its high hydrophobicity, volatility, and sensitivity to oxidative degradation limit its applications. This study aims to address these challenges by developing novel citral derivatives with antibacterial and drug resistance reversal properties. Citral was used as a primary synthon for the synthesis of chalcone-like derivatives ( C-1 - C-6 ) via aldol condensation, and imine derivatives were obtained by condensing citral with hydrazine ( C-7 ), heptyl amine ( C-8 ), glycine ethyl ester ( C-9 ), and 4-amino piperidine ( C-10 ). Citral showed MICs of 500 and 1000 μg/mL against a sensitive strain of Staphylococcus aureus (MTCC-96) and a methicillin-resistant S. aureus (MRSA) clinical isolate, respectively. Compared with the parent compound citral, its derivatives C-6 , C-8 , and C-10 showed 8-fold greater antibacterial activity against the MRSA clinical isolate. In fixed-dose combinatorial studies, at a 10 μg/mL concentration of the derivatives, the MIC of ethidium bromide (EtBr, MIC 7.81 μg/mL) was reduced up to fourfold. The derivatives showed favorable physicochemical and ADMET profiles in in silico predictions and docked well with the efflux pump proteins NorA, NorB, and MepA, as well as the biofilm targets IcaA, IcaB, and IcaC. The binding affinities of C-4 , C-8 , and C-10 for biofilm protein icaC were further verified through 200 ns molecular dynamics simulations. Overall, C-8 and C-10 may be useful for developing safe and cost-effective treatments for S. aureus infections.
Journals
2026 EN
Sahu Aparna · Rajeshree Shivani · Kalika Mayuri
+2 more
Naming difficulty is associated with temporal lobe epilepsy and a decline in naming ability is reported following dominant temporal lobe resections. The Boston Naming Test (BNT) is the most frequently used test for assessing naming ability. Evaluating naming ability in bilingual/multilingual populations is a challenge when participants are restricted to responding in one language. The study aimed to adapt and standardize the BNT as a valid clinical tool for evaluating bilingual/multilingual people undergoing epilepsy surgery in urban India. Culture-appropriate adaptations were done, and participants were allowed to respond in any language. Data from 197 participants showed a strong education effect. The adaptation showed strong internal consistency, reliability, construct validity, and high sensitivity to left temporal lobe epilepsy performance. The adapted version that allowed for flexible use of more than one language is a useful clinical tool for evaluating bilingual people undergoing epilepsy surgery.
Journals
2026 EN
Mahapatro Susrita · Sahu Prabhat Kumar · Subudhi Asit Kumar
This paper proposes a robust framework for cryptocurrency price forecasting by integrating technical indicators, genetic algorithm based feature selection, and hybrid deep learning models. Technical indicators capture historical patterns, while a genetic algorithm optimizes features for Bitcoin, Ethereum, and Litecoin. Four hybrid models are introduced: Convolutional Neural Network Long Short Term Memory Gated Recurrent Unit with Attention, Convolutional Neural Network Gated Recurrent Unit Long Short Term Memory with Attention, Convolutional Neural Network Bi Long Short Term Memory Bi Gated Recurrent Unit, and Convolutional Neural Network Bi Gated Recurrent Unit Bi Long Short Term Memory with Dual Attention. These architectures combine Convolutional Neural Networks for feature extraction with Long Short Term Memory and Gated Recurrent Unit networks for temporal modeling, while attention mechanisms emphasize critical time steps influencing prediction. A dual attention mechanism further improves prediction by applying both spatial and temporal attention. Hyperparameters are optimized using a hybrid Adam Particle Swarm Optimization strategy that balances local and global search. Evaluation metrics include Mean Squared Error, Mean Absolute Error, and R squared. Results show the CNN BiLSTM BiGRU model performs best for Ethereum with an MSE of 0.0002 and for Litecoin with 95.72 percent accuracy, while the CNN LSTM GRU with Attention model achieves the highest accuracy for Bitcoin at 99.44 percent. Model interpretability is supported using LIME, providing insights for traders. The proposed framework demonstrates statistically significant improvements with p values less than 0.05 and shows potential for future enhancement through integration of sentiment and macroeconomic indicators.
Resource
2026 EN
Louhichi Borhen · Elfar Abdullah A. · Sahu Santosh Kumar
+3 more
This study presents a comprehensive review on biochar-filled polymer composites as a sustainable material. Biochar has emerged as one of the most promising reinforcement fillers in polymer matrices owing to its high surface area, thermal stability, and renewability. In addition, it enhances the mechanical properties of polymer matrices, including tensile strength, stiffness, and impact resistance. The study examined 450 articles published over the past decade, from November 2013 to November 2025, using data from Scopus and VOSviewer software to investigate global trends in research and international collaborations. It was followed by a critical review of various synthesis methods for biochars and their subsequent effects on composite properties, including mechanical, thermal, water-absorption, and biodegradability. Several studies have reported that incorporating 5–10 wt.% biochar can substantially improve the tensile strength, Young’s modulus, hardness, impact strength, thermal properties, and crystallinity of polymers. Furthermore, it enhances several other properties, while influencing water absorption behavior and biodegradability depending on composition. The challenges and prospects for biochar-filled polymer composites are also discussed in depth. The study concludes that economic and ecological benefits will render the biochar-filled polymer composite an important material for developing eco-friendly construction materials, biomaterials, wastewater treatment, energy storage, CO 2 capture, and soil remediation.
Journals
2026 EN
Kar Nishikanta · Sahu Sarat Chandra
Understanding regional-scale temperature variability is essential for climate assessment in vulnerable regions such as eastern India. This study examines long-term trends, spatial variability, and large-scale climatic associations of near-surface air temperature over Odisha during 1980–2020 using a multi-reanalysis ensemble constructed from the Indian Monsoon Data Assimilation and Analysis (IMDAA), ERA5, and the MERRA-2 datasets. The ensemble was developed at a common 0.5° spatial resolution and evaluated against gridded observations from the India Meteorological Department (IMD). Trends in mean (Tmean), maximum (Tmax), and minimum (Tmin) temperatures were analyzed using the Modified Mann–Kendall (MMK) test with autocorrelation correction, and magnitudes were estimated using Sen's slope. Spatial analyses indicate predominantly positive trends in Tmean and Tmax across most of Odisha, suggesting widespread daytime warming. Temporal analysis shows modest warming rates of ~0.1–0.3 °C decade⁻¹, stronger over interior regions than coastal areas. In contrast, Tmin exhibits weaker and spatially heterogeneous behavior, with statistically significant cooling detected only in the North Interior region. Empirical Orthogonal Function (EOF) analysis shows that variability is dominated by a leading large-scale mode, while secondary modes capture regional differences. Teleconnection analysis suggests modest linear associations with large-scale climate drivers, including the El Niño–Southern Oscillation (ENSO), the Indian Ocean Dipole (IOD), and All-India Summer Monsoon Rainfall (AISMR), whereas Tmin shows weak and statistically non-significant relationships. These results provide a baseline assessment of regional temperature variability over Odisha, supporting climate-resilient planning and sustainable development initiatives in this environmentally vulnerable region.