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Metal/metal oxides and conductive polymers are common supercapacitor electrode materials, revealing high power density as well as long cycle life. In composites, graphene and metal oxides displayed the combination of the excellent cycle stability of graphene and the high-capacity properties of metal oxides which remarkably improve the comprehensive properties of nanocomposites. The current developments of metal/metal oxide decorated graphene (MGr) composites in the field of electrochemical capacitors are elucidated here on account of their synergistic properties. It is demonstrated that, in comparison with their individual influences, MGr composites have attained substantial improvement in rate capability, capacity, and cycling stability. Mainly, an overview of the characteristics, preparation approaches, and application of graphene (Gr) is outlined. Mechanism of different types of electrochemical capacitance is described explicitly. Finally, the future prospects and challenges of MGr composites have been discussed for energy storage.

Chilika Lake, a RAMSAR site, is an environmentally and ecologically pivotal coastal lagoon in India facing significant emerging environmental challenges due to anthropogenic activities and natural processes. Traditional in situ water quality monitoring methods are often labor intensive and time consuming. This study presents a novel approach for ex situ water quality monitoring in Chilika Lake, located on the east coast of India, utilizing Google Earth Engine (GEE) and spectral indices, such as the Normalized Difference Turbidity Index (NDTI), Normalized Difference Chlorophyll Index (NDCI), and total suspended solids (TSS). The methodology involves the integration of multi-temporal satellite imagery and advanced spectral indices to assess key water quality parameters, such as turbidity, chlorophyll-a concentration, and suspended sediments. The NDTI value in Chilika Lake increased from 2019 to 2021, and the Automatic Water Extraction Index (AWEI) method estimated the TSS concentration. The results demonstrate the effectiveness of this approach in providing accurate and comprehensive water quality assessments, which are crucial for the sustainable management of Chilika Lake. Maps and visualization are presented using GIS software. This study can effectively detect floating algal blooms, identify pollution sources, and determine environmental changes over time. Developing intuitive dashboards and visualization tools can help stakeholders engage with data-driven insights, increase community participation in conservation, and identify pollution sources.

Fresh groundwater is essential for sustaining life and socio-economic development, particularly in regions with limited safe drinking water alternatives. However, contamination from natural and anthropogenic sources poses severe health and environmental risks. This research examines the health risks linked to groundwater quality in the agroeconomic region of Boudh district, Odisha, India, where residents depend on untreated groundwater due to limited access to alternative sources. A total of 82 groundwater samples were analyzed during pre- and post-monsoon of the year 2023 using multivariate statistical methods (PCA, correlation analysis) to determine pollutant sources and regulatory factors, while XRD was employed to characterize fluoride-bearing minerals in associated rock samples. Fluoride concentrations range from 0.14 to 4.6 mg/L, with 49% of samples exceeding the WHO limit of 1.5 mg/L, which raises significant health concerns. Nitrate levels fluctuate between 1.57 and 203.51 mg/L, primarily due to agricultural fertilizers. A health risk assessment (hazard quotient and hazard index) indicates that 63% of samples fall into the low-risk category, 21% into moderate-risk, and 16% into high-risk. Children (HI = 29.23) and infants (HI = 19.51) are at the greatest health risk, surpassing that of adult males (HI = 12.2) and females (HI = 11.2). Findings provide scientific evidence for policymakers to implement groundwater protection and remediation strategies. Immediate interventions, including water quality monitoring, defluoridation measures, and community awareness programs, are essential for ensuring long-term water security and public health.

The tasar silk production of India’s sericulture industry supports tribal livelihoods and economic sustainability. However, Antheraea mylitta Drury, 1773, the primary species for tasar silk, faces habitat threats due to deforestation, climate change, and anthropogenic pressures. This study evaluates the distribution and habitat suitability of wild tasar silkworm using multi-criteria approach, Geographic Information System (GIS), Remote Sensing (RS), and ecological niche modeling using the MaxEnt algorithm. Field surveys were conducted to collect cocoon samples, and the analysis of environmental parameters and assessment of soil micronutrient influences were also carried out. The MaxEnt model predictions indicate that the Central, Western, and Southern zones of Mayurbhanj, encompassing the Similipal Biosphere Reserve, provide the most suitable habitats. The jackknife test confirmed that these climatic variables collectively contributed 68.7% to the habitat suitability model. This study highlights the impact of habitat fragmentation and deforestation on tasar silkworm populations, emphasizing the need for conservation strategies, sustainable forest management, and afforestation programs. The findings highlight the following key conservation strategies: restoring habitats in Similipal, enforcing anti-deforestation laws, promoting community-led planting of host trees, and adopting climate-resilient silk farming to protect biodiversity and support tribal livelihoods.

Access to clean drinking water is crucial for any region’s social and economic growth. However, rapid urbanization and industrialization have significantly deteriorated water quality, posing severe pollution threats from domestic, agricultural, and industrial sources. This study presents an innovative framework for assessing water quality in North Bhubaneswar, integrating the Water Quality Index (WQI) with statistical analysis, geospatial technologies, and machine learning models. The WQI, calculated using the Weighted Arithmetic Index method, provides a single composite value representing overall water quality based on several key physicochemical parameters. To evaluate potable water quality across 21 wards in the northern zone, several key parameters were monitored, including pH, electrical conductivity (EC), dissolved oxygen (DO), hardness, chloride, total dissolved solids (TDSs), and biochemical oxygen demand (BOD). The Weighted Arithmetic WQI method was employed to determine overall water quality, which ranged from excellent to good. Furthermore, Principal Component Analysis (PCA) revealed a strong positive correlation (r > 0.6) between pH, conductivity, hardness, and alkalinity. To enhance the accuracy and reliability of water quality assessment, multiple machine learning models Logistic Regression (LR), Decision Tree (DT), Random Forest (RF), Support Vector Machine (SVM), K-Nearest Neighbors (KNN), and Naïve Bayes (NB) were applied to classify water quality based on these parameters. Among them, the Decision Tree (DT) and Random Forest (RF) models demonstrated the highest precision (91.8% and 92.7%, respectively) and overall accuracy (91.7%), making them the most effective in predicting water quality and integrating WQI, machine learning, and statistics to analyze water quality. The study emphasizes the importance of continuous water quality monitoring and offers data-driven recommendations to ensure sustainable access to clean drinking water in North Bhubaneswar.

Amidst global shifts in land use patterns due to urbanization, this study focuses on the rapid land use and land cover (LULC) changes in Midnapore City during the periods 2003–2014 and 2014–2024. The study employs Landsat 5 and 8 imagery with 30 m spatial resolution which were processed through Maximum Likelihood Classifier (MLC) algorithms. The results were attained through ArcGIS 10.2.2 and ERDAS IMAGINE 2014 software, with ground-truth validation using data from 117, 111, and 116 points for 2024, 2014, and 2003, respectively. For the validation, the kappa coefficient was calculated and achieved 87.3%, 88.1%, and 81.7% for 2024, 2014, and 2003, indicating substantial accuracy. Using statistical measures such as change matrix union, binary logistic regression, and correlation matrix analysis applied to classified LULC outputs and spatial drivers, the research highlights significant transformations in the region. The study reveals significant transformations, notably the conversion of 77% of forest areas and 5% of fallow land to built-up land. The increased rate of agricultural land conversion to built-up areas is evident after 2014, indicating rapid urban growth. These factors led to the reduction of LULC classes possessing substantial ecological value like forests and scrub lands which are becoming more accessible due to the increasing population. The results point out the drastic alteration of these developments and recommend a planning approach responsive to environmental needs for safeguarded ecological impacts. The research highlights the importance of reforestation, preservation of water bodies, and socio-economic surveillance in fostering urban management and sustainable development in Midnapore City.

Secondary erythrocytosis occurs in cyanotic heart disease as a physiological response to chronic hypoxia, and this leads to hyperviscosity and various complications of the same. Microvascular stasis due to hyperviscosity results in symptoms including headache, fatigue, paraesthesia, and loss of vision. An important and dreadful feature of hyperviscosity is overt thrombosis in organ systems, resulting in cerebrovascular accident and myocardial infarction. Limited body iron store in a state of secondary erythrocytosis brings forth iron-deficient microcytic red cells; these being more rigid and less deformable than normocytic cells, further aggravate vascular occlusion. The management of hyperviscosity syndrome starts with intravenous hydration and correction of latent iron deficiency. However, therapeutic phlebotomy may be employed as a rescue measure if symptoms persist despite correction of dehydration and anemia. We present a series of four patients with uncorrected cyanotic congenital heart disease who presented with a spectrum of features of hyperviscosity and discuss pathophysiology, clinical features, and management of hyperviscosity in detail.

In this study, we focused on the rapid land use and land cover (LULC) changes in Bankura in 1990, 2000, 2010, and 2024, employing an integrated remote sensing, geospatial, and statistical approach to track land use changes. The supervised classification technique and change detection analysis were applied with the Supper Vector Machine (SVM), Maximum Likelihood (ML), and Random Forest (RF) methods to identify land use classes in various categories like Dense Forest, Open Forest, water body, agricultural land, settlement, barren land, and sand. The Kappa Coefficient was used for the accuracy assessment, which revealed that the overall accuracy of 1990 was 93.33%, 2000 was 93.23%, 2010 was 93.43%, and 2024 was 90%. The analysis revealed a significant increase in built-up land from agricultural and forested areas, with a higher percentage of agricultural land converted to built-up areas observed between 1990 and 2024. During this interval, the built-up land area increased by approximately 13.6%, primarily due to the conversion of agricultural land and forest cover. Agricultural land decreased by 11.45%, while dense forest cover declined by 7.75%, indicating a significant anthropogenic influence on landscape transformation. Our findings underscore the importance of sustainable land use planning, conservation efforts, and policy interventions in mitigating environmental degradation, leveraging the effectiveness of space-based inputs and geospatial techniques. The research emphasizes the need for continuous monitoring and further investigation into socio-economic drivers and environmental consequences to ensure resilient urban management and sustainable development. This reveals the importance of reforestation, preserving water bodies, and developing ecologically sensitive infrastructure. Moreover, the study highlights the importance of sustainable land use planning in mitigating adverse environmental impacts and preserving ecological balance.

Poly[3,4-(ethylenedioxy)thiophene] (PEDOT) nanocomposites (NCs) reinforced by varying titanium(IV)-doped iron(III) nano oxide (NITO) particles have been fabricated in dodecylbenzene sulphonic acid by in situ polymerization process using ammonium perdisulfate as initiator. The samples were characterized by X-ray diffraction, Fourier transform infrared spectroscopy, electron microscopy, BET surface analysis etc. followed by subsequent evaluation of thermal properties, temperature-dependent 3D electrical transport. Thermal stability of the NCs increased with increasing NITO amount in PEDOT matrix. Electrical conductivity of the NCs increased significantly with increasing NITO content (0.45–67.73 S cm −1 ) and also with the temperature (50–300 K). 3D variable range hopping conduction mechanism explained the conduction pathways. Specific capacitance of NCs are enhanced with higher NITO content in polymer from 107 F g −1 (pristine PEDOT) to 158 F g −1 (NC) owing to the development of mesoporous (pore size: 4.1 nm and cylindrical pore volume: 0.103 cm 3  g −1 ) structure and high specific surface area (~104 m 2  g −1 ).

Major population in the Boudh district of Odisha, India basically depends upon groundwater for various household needs. The presence of underlying hard-rock terrain increases the scarcity, and fluoride content in the groundwater. Hydrochemical studies have been conducted to evaluate the quality of groundwater using GIS. A field reconnaissance survey has been done for assessing water table conditions. The presence of fluoride in groundwater varies from 0.239 to 4.20 mg/L before the monsoon and 0.184–3.75 mg/L after the monsoon period. Fluoride (F − ) ion content is found to be more in samples of the pre-monsoon period than post-monsoon due to the dilution in the rainy season. The statistical analysis has directed that fluoride ion has a positive correlation with bicarbonate (HCO 3 ), TA, Sodium (Na) and pH. The suitability of this groundwater is further examined and analysed with World Health Organization (WHO) standard. Various groundwater samples were cross-examined with high-end analytical techniques. A computational decision tree approach of data mining with an accuracy of 92.68% has been used to confirm the classification result of groundwater of different categories calculated through statistical analysis. The experiment through decision tree (J48) classification algorithm and Canadian water quality index (CWQI) concluded that 2 areas contain good quality of groundwater, 19 areas contain the fair quality of groundwater, 70 areas are considered marginal for drinking and only 11 areas contain poor water quality.