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In order to better grasp the development and trends of tannery wastewater (TWW) treatment research, this paper provides a review of the TWW treatment research dynamics based on the Web of Science (WoS) database and using CiteSpace software. The research dynamics, hot topics, evolutionary history and research trends in this field are revealed. The results showed that research related to TWW treatment has shown a high growth trend in the number of articles in recent years, and India was outstanding in terms of influence in this area. The keyword clustering analysis showed that the main research hotspots in the field of TWW treatment were biological treatment processes (phytoremediation, constructed wetlands, anaerobic treatment and biofilm reactors) and chemical treatment processes (coagulation and flocculation, and advanced oxidation processes). The analysis of new research frontiers showed that the bioremediation and the application of biofuel cells in TWW will become important research directions in the future. [ABSTRACT FROM AUTHOR]

In this paper, different mathematical expressions are derived to compute the residual magnitude of voltage caused by faults along the line and on the bus. Symmetrical and unsymmetrical faults are taken into consideration, and the consequences of the various fault distributions are considered. A new way of assessing a sag is proposed that incorporates the method of fault position and mathematical expression based on sequence currents and voltages. The fault impedance is introduced to obtain a better result. A fast and efficient load flow analysis technique produces quick computational results. In addition, the sag analysis is performed using the bivariate joint discrete probability distribution method that gives a clear idea about the probability of occurrence of sag in a meshed network. The suggested approach is applied in the IEEE 39-bus system and with an existing real-time electrical power distribution system in India. [ABSTRACT FROM AUTHOR]

This paper will analyse a series of dialogues that features kings named Janaka, which appear in the Śānti Parvan of the Mahābhārata. Although there is some variation among these episodes, kings named Janaka tend to be characterised as exemplary rulers who engage in dialogue with learned philosophers and who are strongly associated with the ideals of self-cultivation, renunciation, and liberation. I will argue that the name Janaka functions as a conceptual repertoire for ideas and practices associated with a particular understanding of royal authority. As I will show, the dialogues featuring kings named Janaka characterise sovereignty as both dynamic and fragile because the king is always in the process of displaying his knowledge and self-control. In this way, the different dialogical episodes featuring different Janakas conceptualise political authority differently, thus contributing to an ongoing, inter-textual and inter-religious discussion about sovereignty in ancient India. [ABSTRACT FROM AUTHOR]

Background: India continues to share a colossal count of the global tuberculosis load, with a perturbing 19% spring in the reported cases in 2021. With the National Tuberculosis Elimination Program (NTEP) consolidated to bring this epidemic to an end by 2025, the rapidly growing mobile health technologies can be utilized to offer promising results. Even though the implementation of this novel strategy is escalating around the globe, its triumph is still sub optimal in India. Objectives: This scoping review intends to explore the available mobile health (mHealth) technologies and analyse the effectiveness of the same for tuberculosis management in India. Methods: An elaborate search in electronic databases, such as PubMed and Google scholar, using the key terms and focussing from the year 2015, provided very broad results focussing on mHealth interventions and their utilisation in TB management in India. Further selection of the inclusive publications was carried out based upon the eligibility requirements as formulated for this review, pertaining to the objective of this study. Results: The collaborate search yielded a total of 858 scientific research papers. After the filtering of the obtained results, a total of 45 articles were selected to be analysed for this review. Published manuscripts, articles in peer review and abstracts from reliable databases were included to obtain vast range of information. Conclusion: The extensive literature search showed a preponderance of mHealth intervention studies focusing on TB treatment and drug monitoring. There exists a paucity of mHealth applications targeted to educate the public and intercept this infectious disease. The scientific articles reviewed and analysed in this scoping review strongly recommend the demployment of mHealth applications to achieve the target of eradicating TB by 2025 in India. [ABSTRACT FROM AUTHOR]

Crop residue burning (CRB) poses a serious threat to the climate, soil fertility, human health and wellbeing, and air quality, which increases mortality rates and slumps agricultural productivity. This study conducts a pan-India analysis of CRB burning based on the spatial characteristic of crop residue management practices and analyzes the linkage among health, agriculture value addition, and regional finance using the simultaneous equation to find the causality and panel quantile regression for direct effect and intergroup difference. We discuss some of the alternative crop residue management practices and policy interventions. Along with in situ management, this paper discusses ex situ crop residue management (CRM) solutions. The ex situ effort to manage crop residue failed due to the scarcity of the supply chain ecosystem. Force of habit and time constrain coupled with risk aversion have made farmers reluctant to adopt these solutions. Our results show that financial viability and crop residue have bidirectional causality; therefore, both the central and state governments must provide a financial solution to lure farmers into adopting residue management practices. Our analysis shows that framers are likely to adopt the management solution (farmers have some economic benefits) and are reluctant to adopt the scientific solution because the scientific solution, such as "pusa decomposer", is constrained by the weather, temperature, and humidity, and these parameters vary throughout India. [ABSTRACT FROM AUTHOR]

Simple Summary: Drugs are used to treat cancer. Most drugs available in the market are chemosynthetic drugs and have side effects on the patient during and after the treatment, in addition to cancer itself. For instance, hair loss, loss of skin color and texture, loss of energy, nausea, infertility, etc. To overcome these side effects, naturally obtained drugs from medicinal plants are preferred. Our review paper aims to encourage the study of anticancer medicinal plants by giving detailed information on thirty-three medicinal plants and parts that constitute the phytochemicals responsible for the treatment of cancer. The development of plant-based drugs could be a game changer in treating cancer as well as boosting the immune system. Cancer is a serious and significantly progressive disease. Next to cardiovascular disease, cancer has become the most common cause of mortality in the entire world. Several factors, such as environmental factors, habitual activities, genetic factors, etc., are responsible for cancer. Many cancer patients seek alternative and/or complementary treatments because of the high death rate linked with cancer and the adverse side effects of chemotherapy and radiation therapy. Traditional medicine has a long history that begins with the hunt for botanicals to heal various diseases, including cancer. In the traditional medicinal system, several plants used to treat diseases have many bioactive compounds with curative capability, thereby also helping in disease prevention. Plants also significantly contributed to the modern pharmaceutical industry throughout the world. In the present review, we have listed 33 medicinal plants with active and significant anticancer activity, as well as their anticancer compounds. This article will provide a basic set of information for researchers interested in developing a safe and nontoxic active medicinal plant-based treatment for cancer. The research will give a scientific foundation for the traditional usage of these medicinal herbs to treat cancer. [ABSTRACT FROM AUTHOR]

The increased demand for this form of food delivery has been expected to drastically alter restaurant patrons' dining habits. As people have been forced to stay indoors to prevent the virus from spreading, food delivery services over the internet are in high demand. As established in this study, the planned ideal is a good executive implementation for online meal delivery services. Food delivery services are rapidly growing in India, opening up several opportunities for a wide range of online food delivery (OFD) platforms while also generating a competitive commercial sector. Following that, the fuzzy technique for order performance by similarity to ideal solution method (FTOPSIS) is used to rank online food delivery (OFD) enterprises based on the characteristics chosen. In this paper, we study the present multi-criteria decision-analysis (MCDA) paradigm based on the fuzzy analytic hierarchy process (FAHP) and the fuzzy technique for order performance by similarity to ideal solution (FTOPSIS) method to achieve the goal. After that, a hierarchy multiple criteria decision-analysis (MCDA) model based on fuzzy sets theory is introduced to deal with the online food delivery Service in the chain system. The fuzzy analytic hierarchy process (FAHP) is a fuzzy set theory technique for generating criteria weights, which are then used to interpret expert phonological evaluation statements. [ABSTRACT FROM AUTHOR]

The paper adopts the conventional data envelopment analysis (DEA) and bootstrap procedure to analyze the technical efficiency, while tobit regression is applied to identify the factors affecting efficiencies of exotic fish polyculture in Jammu and Kashmir (India). According to the statistical analysis of the variables utilized, there was a lot of variability in the inputs being used by the farmers, with the most variation being in the lime input. The DEA estimated technical efficiency for the sample farms in Jammu and Kashmir is 0.9771 and 0.9741, respectively, with least technical inefficiency of 3%. The bias-corrected (bootstrapped) technical efficiencies found were slightly lower than the ones estimated by conventional DEA. Mean allocative and cost efficiencies for sample farms in the Jammu region were 92% and 75%, respectively, and 84% and 74%, respectively, for farmers in the Kashmir region. Farming experience, age, and education have favorable impacts on technical efficiency of farmers in the state, but family size showed negative impacts. Efficiency improvement will eventually lead to increase in the production providing better scope for marketed surplus. More fisheries extension is suggested for expanding the exotic fish culture in the state making the enterprise a more profitable venture. [ABSTRACT FROM AUTHOR]

This paper examines the application of surface drilling parameters and drilling optimization techniques, such as mechanical specific energy (MSE) and equivalent strength (EST), in detecting hydrate gas-bearing sediments during drilling operations. Gas hydrates are usually detected from 3D seismic imaging and later confirmed with Measurement-While-Drilling (MWD)/Logging-While-Drilling (LWD) data and collected core samples. Here, we describe an analysis of the time-based surface drilling parameters recorded from two wells drilled during the International Ocean Discovery Program (IODP) Expedition 372A offshore of New Zealand and the Indian National Gas Hydrate Program Expedition 02 (NGHP-02) offshore of India. The investigation revealed that drilling parameters, as well as MSE/EST methods, can and should be used to monitor and optimize the drilling process and to detect lithological/tectonic (fractures, fault zones, rock hardness, etc.) changes in the drilled substrata and signs of the dynamic changes in the downhole environment (tool vibration, washouts, pack-offs, etc.). However, surface drilling parameters with MSE models cannot explicitly determine the hydrate gas-bearing sediments. This qualitative analysis of whether the gas-bearing sediments consist of hydrates can only be accomplished with the use of the MWD/LWD suite, preferably located as close as possible to the bit. [ABSTRACT FROM AUTHOR]

Crop yield forecasting is becoming more essential in the current scenario when food security must be assured, despite the problems posed by an increasingly globalized community and other environmental challenges such as climate change and natural disasters. Several factors influence crop yield prediction, which has complex non-linear relationships. Hence, to study these relationships, machine learning methodologies have been increasingly adopted from conventional statistical methods. With wheat being a primary and staple food crop in the Indian community, ensuring the country's food security is crucial. In this paper, we study the prediction of wheat yield for India overall and the top wheat-producing states with a comparison. To accomplish this, we use Multivariate Adaptive Regression Splines (MARS) after extracting the main features by Principal Component Analysis (PCA) considering the parameters such as area under cultivation and production for the years 1962–2018. The performance is evaluated by error analyses such as RMSE, MAE, and R2. The best-fitted MARS model is chosen using cross-validation and user-defined parameter optimization. We find that the MARS model is well suited to India as a whole and other top wheat-producing states. A comparative result is obtained on yield prediction between India overall and other states, wherein the state of Rajasthan has a better model than other major wheat-producing states. This research will emphasize the importance of improved government decision-making as well as increased knowledge and robust forecasting among Indian farmers in various states. [ABSTRACT FROM AUTHOR]

The socio-economic aspects of the people who directly share space with elephants not only influence the occurrence of human-elephant conflict (HEC) but also shape their sentiments towards coexistence with elephants. The objectives of this paper are to (i) assess the demographic situation and map people's sentiments towards elephants in the HEC hotspot villages of the Keonjhar forest division in India and (ii) rank the most suitable policy instruments and the urgency of mitigation strategies. The results indicated that cultivation and marginal agriculture were positively related with HEC incidences, whereas literacy and employment were negatively associated. Despite being severely affected by human–elephant conflict, many of the respondents (78%) in the HEC hotspot regions still had positive sentiments towards elephants. According to expert opinions, strengthening of laws regarding land use facilitation and interlinking conservation values to socio-cultural aspects need urgent implementation in order to balance infrastructural development and protection of ecosystems by enhancing community participation. Communal crop guarding, chilly-dung and honeybee fencing, accompanied by tracking and maintaining an elephant locational database are suggested as the HEC mitigation methods with highest urgency. [ABSTRACT FROM AUTHOR]

Pneumonia is one of the main causes of child mortality in the world and has been reported by the World Health Organization (WHO) to be the cause of one-third of child deaths in India. Designing an automated classification system to detect pneumonia has become a worthwhile research topic. Numerous deep learning models have attempted to detect pneumonia by applying convolutional neural networks (CNNs) to X-ray radiographs, as they are essentially images and have achieved great performances. However, they failed to capture higher-order feature information of all objects based on the X-ray images because the topology of the X-ray images' dimensions does not always come with some spatially regular locality properties, which makes defining a spatial kernel filter in X-ray images non-trivial. This paper proposes a principal neighborhood aggregation-based graph convolutional network (PNA-GCN) for pneumonia detection. In PNA-GCN, we propose a new graph-based feature construction utilizing the transfer learning technique to extract features and then construct the graph from images. Then, we propose a graph convolutional network with principal neighborhood aggregation. We integrate multiple aggregation functions in a single layer with degree-scalers to capture more effective information in a single layer to exploit the underlying properties of the graph structure. The experimental results show that PNA-GCN can perform best in the pneumonia detection task on a real-world dataset against the state-of-the-art baseline methods. [ABSTRACT FROM AUTHOR]

Recent developments in passive microwave remote sensing have provided an effective tool for monitoring global soil moisture (SM) observations on a spatiotemporal basis, filling the gap of uneven in-situ measurement distribution. In this paper, four passive microwave SM products from three bands (L, C, and X) are evaluated using in-situ observations, over a dry–wet cycle agricultural (mostly paddy/wheat cycle crops) critical zone observatory (CZO) in the Central Ganga basin, India. The L-band and C/X-band information from Soil Moisture Active Passive (SMAP) Passive Enhanced Level 3 (SMAP-L3) and Advanced Microwave Scanning Radiometer 2 (AMSR2), respectively, was selected for the evaluation. The AMSR2 SM products used here were derived using the Land Parameter Retrieval Model (LPRM) algorithm. Spatially averaged observations from 20 in-situ distributed locations were initially calibrated with a single and continuous monitoring station to obtain long-term ground-based data. Furthermore, several statistical metrices along with the triple collocation (TC) error model were used to evaluate the overall accuracy and random error variance of the remote sensing products. The results indicated an overall superior performance of SMAP-L3 with a slight dry bias (−0.040 m3·m−3) and a correlation of 0.712 with in-situ observations. This also met the accuracy requirement (0.04 m3·m−3) during most seasons with a modest accuracy (0.059 m3·m−3) for the entire experimental period. Among the LPRM datasets, C1 and C2 products behaved similarly (R = 0.621) with a ubRMSE of 0.068 and 0.081, respectively. The X-band product showed a relatively poor performance compared to the other LPRM products. Seasonal performance analysis revealed a higher correlation for all the satellite SM products during monsoon season, indicating a strong seasonality of precipitation. The TC analysis indicated the lowest error variance (0.02 ± 0.003 m3·m−3) for the SMAP-L3. In the end, we introduced Spearman's rank correlation to assess the dynamic response of SM observations to climatic and vegetation parameters. [ABSTRACT FROM AUTHOR]

Insular grids are fragile owing to lower inertia and the absence of interconnection with other grids. With the increasing penetration of non-dispatchable renewable energy sources, the vulnerability of such insular grids increases further. The government of India has proposed several projects to improve the photovoltaic systems (PV) penetration in the Andaman and Nicobar Islands' grid. This paper investigates joint stochastic scheduling of energy and reserve generation for insular grids fed from diesel and gas-based generators, PV, and battery energy storage systems (BESS). The proposed stochastic scheduling model considers a wide range of probabilistic forecast scenarios instead of a deterministic model that assumes a single-point forecast. Hence, it provides an optimal solution that is technically feasible for a wide range of PV power forecast scenarios. The striking feature of the model developed in this work is the inclusion of stochastic constraints that represent (i) the coordination between PV and BESS, (ii) reserve constraints, (iii) battery charging/discharging limit constraints, and (iv) non-anticipatory constraints that ensure technical viability of scheduling decisions. The proposed model is validated on the dataset for South Andaman Island. Results reveal the applicability and feasibility of the proposed stochastic dispatch model for different generation mix scenarios. [ABSTRACT FROM AUTHOR]

The rapid growth of electric vehicles in India necessitates more power to energize such vehicles. Furthermore, the transport industry emits greenhouse gases, particularly SO2, CO2. The national grid has to supply an enormous amount of power on a daily basis due to the surplus power required to charge these electric vehicles. This paper presents the various hybrid energy system configurations to meet the power requirements of the electric vehicle charging station (EVCS) situated in the northwest region of Delhi, India. The three configurations are: (a) solar photovoltaic/diesel generator/battery-based EVCS, (b) solar photovoltaic/battery-based EVCS, and (c) grid-and-solar photovoltaic-based EVCS. The meta-heuristic techniques are implemented to analyze the technological, financial, and environmental feasibility of the three possible configurations. The optimization algorithm intends to reduce the total net present cost and levelized cost of energy while keeping the value of lack of power supply probability within limits. To confirm the solution quality obtained using modified salp swarm algorithm (MSSA), the popularly used HOMER software, salp swarm algorithm (SSA), and the gray wolf optimization are applied to the same problem, and their outcomes are equated to those attained by the MSSA. MSSA exhibits superior accuracy and robustness based on simulation outcomes. The MSSA performs much better in terms of computation time followed by the SSA and gray wolf optimization. MSSA results in reduced levelized cost of energy values in all three configurations, i.e., USD 0.482/kWh, USD 0.684/kWh, and USD 0.119/kWh in configurations 1, 2, and 3, respectively. Our findings will be useful for researchers in determining the best method for the sizing of energy system components. [ABSTRACT FROM AUTHOR]

The India-France SARAL/AltiKa mission is the first Ka-band altimetric mission dedicated to oceanography. The mission objectives are primarily the observation of the oceanic mesoscales but also include coastal oceanography, global and regional sea level monitoring, data assimilation, and operational oceanography. The mission ended its nominal phase after 3 years in orbit and began a new phase (drifting orbit) in July 2016. The objective of this paper is to provide a state of the art of the achievements of the SARAL/AltiKa mission in terms of quality assessment and unique characteristics of AltiKa data. It shows that the AltiKa data have similar accuracy at the centimeter level in term of absolute water level whatever the method (from local to global) and the type of water surfaces (ocean and lakes). It shows also that beyond the fact that AltiKa data quality meets the expectations and initial mission requirements, the unique characteristics of the altimeter and the Ka-band offer unique contributions in fields that were previously not fully foreseen. [ABSTRACT FROM AUTHOR]

Solar photovoltaic (SPV) installations are growing in the distribution network due to the continuously decreasing prices of solar photovoltaic panels. Installing the SPV Plant on the distribution feeder supplying to the agricultural pumps is a challenging task due to the varying agricultural load pattern of the Agricultural Feeder (AG Feeder). Supply of power and demand creates potential challenges in the low voltage (LV) distribution system. This paper presents a case study of a 2 MW SPV connected to an agricultural feeder in India. Performance analysis has been carried out using field measurement data. The key parameters such as PV Penetration and Capacity Utilization Factor (CUF) are calculated for analysis. Parameters such as Grid Dependency of the load and PV Contribution have been introduced in this paper, which relates to the SPV system behavior more aptly. It is recommended that the Time of Day (ToD) metering with the lowest cost during the solar generation hours will make agricultural consumers shift their demand matching with solar generation hours. Extensive analysis of agricultural feeder connected SPV power plant indicates that the power supply has improved for the feeder during winter and summer months. [ABSTRACT FROM AUTHOR]

This paper investigates the nexus between CO2 emissions (CO2E), GDP, energy use (ENU), and population growth (PG) in India from 1980–2018 by comparing the "vector error correction" model (VECM) and "auto regressive distributed lag" (ARDL). We applied the unit root test, Johansen multi-variate cointegration, and performed a Variance decomposition analysis using the Cholesky approach. The VECM and ARDL-bound testing approaches to cointegration suggest a long-term equilibrium nexus between GDP, energy use, population growth and CO2E. The empirical outcomes show the existence of a long-term equilibrium nexus between the variables. The Granger causality results show that short-term bi-directional causality exists between GDP and ENU, while a uni-directional causality between CO2E and GDP, CO2E and ENU, CO2E and PG, and PG and ENU. Evidence from variance decomposition indicates that 58.4% of the future fluctuations in CO2E are due to changes in ENU, 2.8% of the future fluctuations are due to changes in GDP, and 0.43% of the future fluctuations are due to changes in PG. Finally, the ARDL test results indicate that a 1% increase in PG will lead to a 1.4% increase in CO2E. Our paper addresses some important policy implications. [ABSTRACT FROM AUTHOR]

By considering the weight penalty of batteries on payload and total vehicle weight, this paper shows that almost all forms of land-based transport may be served by battery electric vehicles (BEV) with acceptable cost and driving range. Only long-distance road freight is unsuitable for battery electrification. The paper models the future Indian electricity grid supplied entirely by low-carbon forms of generation to quantify the additional solar PV power required to supply energy for transport. Hydrogen produced by water electrolysis for use as a fuel for road freight provides an inter-seasonal energy store that accommodates variations in renewable energy supply. The advantages and disadvantages are considered of midday electric vehicle charging vs. overnight charging considering the temporal variations in supply of renewable energy and demand for transport services. There appears to be little to choose between these two options in terms of total system costs. The result is an energy scenario for decarbonized surface transport in India, based on renewable energy, that is possible, realistically achievable, and affordable in a time frame of year 2050. [ABSTRACT FROM AUTHOR]

A large section of the population around the globe is migrating towards urban settlements. Nations are working toward smart city projects to provide a better wellbeing for the inhabitants. Cyber-physical systems are at the core of the smart city setups. They are used in almost every system component within a smart city ecosystem. This paper attempts to discuss the key components and issues involved in transforming conventional cities into smart cities with a special focus on cyber-physical systems in the Indian context. The paper primarily focuses on the infrastructural facilities and technical knowhow to smartly convert classical cities that were built haphazardly due to overpopulation and ill planning into smart cities. It further discusses cyber-physical systems as a core component of smart city setups, highlighting the related security issues. The opportunities for businesses, governments, inhabitants, and other stakeholders in a smart city ecosystem in the Indian context are also discussed. Finally, it highlights the issues and challenges concerning technical, financial, and other social and infrastructural bottlenecks in the way of realizing smart city concepts along with future research directions. [ABSTRACT FROM AUTHOR]

Since the first fully homomorphic encryption scheme was published in 2009, many papers have been published on fully homomorphic encryption and its applications. Machine learning is one of the most interesting applications and has drawn a lot of attention from researchers. To better represent and understand the field of Homomorphic Encryption in Machine Learning (HEML), this paper utilizes automated citation and topic analysis to characterize the HEML research literature over the years and provide the bibliometrics assessments for this burgeoning field. This is conducted by using a bibliometric statistical analysis approach. We make use of web-based literature databases and automated tools to present the development of HEML. This allows us to target several popular topics for in-depth discussion. To achieve these goals, we have chosen the well-established Scopus literature database and analyzed them through keyword counts and Scopus relevance searches. The results show a relative increase in the number of papers published each year that involve both homomorphic cryptography and machine learning. Using text mining of articles titles, we have found that cloud computing is a popular topic in this field, which also includes neural networks, big data, and the Internet of Things. The analysis results show that China, the US, and India have generated almost half of all the research contributions in HEML. The citation statistics, keyword statistics, and topic analyses give us a quick overview of the development of the field, which can be of great help to new researchers. It is also possible to apply our methodology to other research areas, and we see great value in this approach. [ABSTRACT FROM AUTHOR]

This paper provides a summary of financial instruments to address two biggest risks to renewable projects in India. These risks include the following: first, off-taker (or counterparty) risk, which relates to payment delays by public-sector distribution companies to independent power producers, which then impact project level cash flows in the domestic currency; second, currency (or foreign exchange) risk related to currency fluctuations, which impact foreign investor level cash flows in foreign currencies. This paper then describes multiple solutions for each of these risks, using public funding mechanisms. For payment delays, the category of solutions is termed Payment Security Mechanisms; whereas, for currency fluctuations, the category of solutions is termed Foreign Exchange Hedging Facilities. The coverage in this paper shows the evolution of the solutions from theory to practice over time. These solutions are likely to be applicable to other developing countries. [ABSTRACT FROM AUTHOR]

This paper discusses the application of the Cross-Correlation Analysis (CCA) technique to multi-spatial resolution Earth Observation (EO) data for detecting and quantifying changes in forest ecosystems in two different protected areas, located in Southern Italy and Southern India. The input data for CCA investigation were elaborated from the forest layer extracted from an existing Land Cover/Land Use (LC/LU) map (time T1) and a more recent (T2, with T2 > T1) single date image. The latter consist of a High Resolution (HR) Landsat 8 OLI image and a Very High Resolution (VHR) Worldview-2 image, which were analysed separately. For the Italian site, the forest layer (1:5000) was first compared to the HR Landsat 8 OLI image and then to the VHR Worldview-2 image. For the Indian site, the forest layer (1:50,000) was compared to the Landsat 8 OLI image then the changes were interpreted using Worldview-2. The changes detected through CCA, at HR only, were compared against those detected by applying a traditional NDVI image differencing technique of two Landsat scenes at T1 and T2. The accuracy assessment, concerning the change maps of the multi-spatial resolution outputs, was based on stratified random sampling. The CCA technique allowed an increase in the value of the overall accuracy: from 52% to 68% for the Italian site and from 63% to 82% for the Indian site. In addition, a significant reduction of the error affecting the stratified changed area estimation for both sites was obtained. For the Italian site, the error reduction became significant at VHR (±2 ha) in respect to HR (±32 ha) even though both techniques had comparable overall accuracy (82%) and stratified changed area estimation. The findings obtained support the conclusions that CCA technique can be a useful tool to detect and quantify changes in forest areas due to both legal and illegal interventions, including relatively inaccessible sites (e.g., tropical forest) with costs remaining rather low. The data obtained through CCA intervention could not only support the commitments undertaken by the European Habitats Directive (92/43/EEC) and the Convention of Biological Diversity (CBD) but also satisfy UN Sustainable Development Goals (SDG). [ABSTRACT FROM AUTHOR]

Energy storage ceramics is among the most discussed topics in the field of energy research. A bibliometric analysis was carried out to evaluate energy storage ceramic publications between 2000 and 2020, based on the Web of Science (WOS) databases. This paper presents a detailed overview of energy storage ceramics research from aspects of document types, paper citations, h-indices, publish time, publications, institutions, countries/regions, research areas, highly cited papers, and keywords. A total of 3177 publications were identified after retrieval in WOS. The results show that China takes the leading position in this research field, followed by the USA and India. Xi An Jiao Tong Univ has the most publications, with the highest h-index. J.W. Zhai is the most productive author in energy storage ceramics research. Ceramics International, Journal of Materials Science-Materials in Electronics, and the Journal of Alloys and Compounds are the most productive journals in this field, and materials science—multidisciplinary is the most frequently used subject category. Keywords, highly cited papers, and the analysis of popular papers indicate that, in recent years, lead-free ceramics are prevalent, and researchers focus on fields such as the microstructure, thin films, and phase transition of ceramics. [ABSTRACT FROM AUTHOR]

Simple Summary: Donkeys and mules are still commonly worked across the world in place of mechanical vehicles. They are prone to various diseases and welfare issues, often as a result of poor working conditions. A proportion of the associated literature and a number of interventions are still driven by the assumption that the owners of working equids base their decisions on how to treat their animal upon economic factors or access to veterinary services. This paper uses a mixture of qualitative and quantitative methods to understand the reasons behind why equid owners choose to treat their animals in the way that they do. It explores the various means by which they choose to do this and the avenues available to them. It identifies four factors which influence how and why owners of working equids choose to treat their animals in a particular way and highlights in particular the frequency with which traditional methods or 'home remedies' play a significant role in attempts to remedy the poor health of an animal. The findings demonstrate a greater need to validate traditional methods used, in order to promote better health and to reduce risk, as well as the requirement to tailor animal welfare interventions according to these influencing factors to encourage more sustainable outcomes for both animals and owners. This paper challenges assumptions that the health management of working equids among some of India's poorest communities is mainly dependent upon income, economic influence, or access to veterinary services. Using a mixed-methods approach, hierarchies of treatment practices are revealed through an examination of the 'lived experience' of equid owners in brick kilns and construction sites in northern India. Semi-structured interviews with 37 equid owners and corresponding livelihood surveys, combined with data from two focus groups with professional animal health practitioners and the welfare data of 63 working equids collected using the Equid Assessment, Research, and Scoping (EARS) tool, contributed to the findings of the study. Four principal influencing factors were found to affect the decision-making practices of equid owners. Infrastructural factors, community characteristics and experience, owners' characteristics and experience, and economic factors all impact the belief structures of equid owners. However, without verifying the validity of the treatment measures being employed, some animals are at risk from hazardous treatment behaviours. By understanding decision-making using the theory of planned behaviour, the findings of this study can provide a crucial contribution to informing future interventions involved in the health management and welfare of working equids. [ABSTRACT FROM AUTHOR]

The modern-day paper industry is highly capital-intensive industries in the core sector. Though there are several uses of paper for currency, packaging, education, information, communication, trade and hygiene, the flip side of this industry is the impact on the forest resources and other ecosystems which leads to increasing pollution in water and air, influencing several local communities. In the present paper, the authors have tried to explore potential and alternate source of industrial pulp through ruminant animal dung, which is widely available as a rural resource in India. Three types of undigested animal dung fibers from Indigenous cow (IDF), Jersey cow (JDF), and Buffalo (BDF) were taken. Wheat straw (WS) was the main diet of all animals. The cellulose, hemicellulose and lignin content for all animal dung samples were found in a range of (29–31.50%), (21–23.50%), and (11–13%), respectively. The abundant holocellulose and low lignin contents are suitable for handmade pulp and paper. Surface characteristics of fodder (WS) and all dung fibers have been investigated using Fourier Transform Infrared Spectroscopy (FTIR), scanning electron microscopy (SEM), and SEM-Energy dispersive X-ray spectroscopy (SEM-EDX). To increase paper production without damaging forest cover, it is essential to explore unconventional natural resources, such as dung fiber, which have the huge potential to produce pulp and paper, reinforcement components, etc. [ABSTRACT FROM AUTHOR]

India, Pakistan, and Bangladesh (IPB) are the largest South Asian countries in terms of land area, gross domestic product (GDP), and population. The growth in these countries is impacted by inadequate renewable energy policy and implementation over the years, resulting in slow progress towards human development and economic sustainability. These developing countries are blessed with huge potential for renewable energy resources; however, they still heavily rely on fossil fuels (93%). IPB is a major contributor to the total energy consumption of the world and its most energy-intensive building sector (India 47%, Pakistan 55% and Bangladesh 55%) displays inadequate energy performance. This paper comprehensively reviews the energy mix and consumption in IPB with special emphasis on current policies and its impact on economic and human development. The main performance indicators have been critically analyzed for the period 1970–2017. The strength of this paper is a broad overview on energy and development of energy integration in major South Asian countries. Furthermore, it presents a broad deepening on the main sector of energy consumption, i.e., the building sector. The paper also particularly analyzes the existing buildings energy efficiency codes and policies, with specific long-term recommendations to improve average energy consumption per person. The study also examines the technical and regulatory barriers and recommends specific measures to adapt renewable technologies, with special attention to policies affecting energy consumption. The analysis and results are general and can be applied to other developing countries of the world. [ABSTRACT FROM AUTHOR]

Optimal planning of renewable energy generator (REG) units helps to meet future power demand with improved flexibility. Hence, this paper proposes a grid-oriented genetic algorithm (GOGA) based on a hybrid combination of a genetic algorithm (GA) and a solution using analytical power flow equations for optimal sizing and placement of REG units in a power system network. The objective of the GOGA is system loss minimization and flexibility improvement. The objective function expresses the system losses as a function of the power generated by different generators, using the Kron equation. A flexibility index (FI) is proposed to evaluate the improvement in the flexibility, based on the voltage deviations and system losses. A power flow run is performed after placement of REGs at various buses of the test system, and system losses are computed, which are considered as chromosome fitness values. The GOGA searches for the lowest value of the fitness function by changing the location of REG units. Crossover, mutation, and replacement operators are used by the GOGA to generate new chromosomes until the optimal solution is obtained in terms of size and location of REGs. A study is performed on a part of the practical transmission network of Rajasthan Rajya Vidyut Prasaran Nigam Ltd. (RVPN), India for the base year 2021 and the projected year 2031. Load forecasting for the 10-year time horizon is computed using a linear fit mathematical model. A cost–benefit analysis is performed, and it is established that the proposed GOGA provides a financially viable solution with improved flexibility. It is established that GOGA ensures high convergence speed and good solution accuracy. Further, the performance of the GOGA is superior compared to a conventional GA. [ABSTRACT FROM AUTHOR]

Contrary to conventional fossil fuel-based electricity generation technologies, renewable energy centered technologies, specifically small hydropower, release a lesser amount of anthropogenic greenhouse gases but are normally more expensive. A major segment of the capital investment in the current small hydropower scenario accounts for equipment and construction process costs. The construction and cost administration process are generally limited to analysis of the capital cost of civil constructions, electro-mechanical equipment works, neglecting the costs related to operating and maintaining the plant, replacement or refurbishment, certified emission reductions, among others. Contemporary studies indicate that these costs form a substantial fraction of the total capital investment. Consequently, for cost management and investment decision making, small hydropower plant developers are drawing increased attention in recent years towards conducting life cycle costing studies that take into account the ignored costs. In addition, small hydropower plants in developing nations can become more competitive by trading the emission reductions achieved under the provision of the Clean Development Mechanism, an outcome of the Kyoto Protocol proposed at the United Nations Framework Convention on Climate Change. In this paper, a modest attempt has been made to determine the Levelized cost of electricity generation using life cycle costing methodology, which accounts for all the costs over operating lifetime on a range of small hydropower plants and the results are analyzed. [ABSTRACT FROM AUTHOR]

Air quality levels do not just affect climate change; rather, it leaves a significant impact on public health and wellbeing. Indoor air pollution is the major contributor to increased mortality and morbidity rates. This paper is focused on the assessment of indoor air quality based on several important pollutants (PM10, PM2.5, CO2, CO, tVOC, and NO2). These pollutants are responsible for potential health issues, including respiratory disease, central nervous system dysfunction, cardiovascular disease, and cancer. The pollutant concentrations were measured from a rural site in India using an Internet of Things-based sensor system. An Adaptive Dynamic Fuzzy Inference System Tree was implemented to process the field variables. The knowledge base for the proposed model was designed using a global optimization algorithm. However, the model was tuned using a local search algorithm to achieve enhanced prediction performance. The proposed model gives normalized root mean square error of 0.6679, 0.6218, 0.1077, 0.2585, 0.0667 and 0.0635 for PM10, PM2.5, CO2, CO, tVOC, and NO2, respectively. This approach was compared with the existing studies in the literature, and the approach was also validated against the online benchmark dataset. [ABSTRACT FROM AUTHOR]

Crimes against women have critical implications, not only for victims but also for overall community health and safety. Communities entrust law enforcement agencies with the responsibility to safeguard vulnerable people through effective and efficient policing approaches that provide a safe environment. Enhancing and improving the efficiency and performance of the police is an important part of preventing and reducing crimes against women. One approach to addressing specific performance targets is to adopt a performance management strategy. This paper examines survey data from 310 police officials in northern India about one such strategy: the balanced scorecard (BSC). Our analysis illuminates police perspectives about the perceived benefits of a generalized performance management strategy such as the BSC for improving police performance in addressing crimes against women and the needs of female citizens. Our findings reveal that respondents' assessments of all four dimensions of the balanced scorecard are associated with their degree of optimism that performance measurement can improve the police response to crimes against women. [ABSTRACT FROM AUTHOR]

The global COVID-19 pandemic has hit the agriculture sector hard around the world. A study was conducted to assess the impact of the pandemic on cropping patterns, crop management, usage of chemical inputs and their organic alternatives, harvesting, and marketing avenues through a survey approach in the two states of Kerala and Tamil Nadu in India. A total of 250 farmers participated in the study, the data was analyzed by Chi-square test and Kruskal–Wallis test. The assessment of the impact of COVID-19 on some aspects was undertaken by dividing the study period into three phases. Though a smaller number of people were infected with COVID-19 in the initial phase of the pandemic compared to the later phases, farm operations and the procurement of inputs were significantly affected at this phase as there was a sudden disruption in transportation due to COVID-19-induced movement restrictions. During the entire study period, commodities such as rice, bananas, vegetables, coconuts, and flowers suffered maximum crop loss compared to pulses, groundnuts, cotton, and rubber. Among fertilizers, the maximum shortage was observed for chemical fertilizers (46%) and biofertilizers (30%) compared to cow dung (18%) and poultry manure (6%), indicating that farmers tended to use more local materials that could be easily procured and accessed compared to shop-based inputs. A rise in the cost of cultivation, scarcity of farm workforce, and difficulty in hiring farm machinery all have contributed to the loss of profit during the pandemic period. As a response to COVID-19, growers initiated post-harvest processing of commodities, and cropping systems remained the same during the period. The paper also discusses some remedial measures to be adopted by households in the future, to minimize the impacts of such pandemics in the agrarian sector. [ABSTRACT FROM AUTHOR]

This paper deals with the mathematical modeling of the second wave of COVID-19 and verifies the current Omicron variant pandemic data in India. We also we discussed such as uniformly bounded of the system, Equilibrium analysis and basic reproduction number R 0 . We calculated the analytic solutions by HPM (homotopy perturbation method) and used Mathematica 12 software for numerical analysis up to 8th order approximation. It checked the error values of the approximation while the system has residual error, absolute error and h curve initial derivation of square error at up to 8th order approximation. The basic reproduction number ranges between 0.8454 and 2.0317 to form numerical simulation, it helps to identify the whole system fluctuations. Finally, our proposed model validated (from real life data) the highly affected five states of COVID-19 and the Omicron variant. The algorithm guidelines are used for international arrivals, with Omicron variant cases updated by the Union Health Ministry in January 2022. Right now, the third wave is underway in India, and we conclude that it may peak by the end of May 2022. [ABSTRACT FROM AUTHOR]

Industrial waste such as Ground Granulated Blast-Furnace Slag (GGBS) and Granite Waste Powder (GWP) is available in huge quantities in several states of India. These ingredients have no recognized application and are usually shed in landfills. This process and these materials are sources of severe environmental pollution. This industrial waste has been utilized as a binder for geopolymers, which is our primary focus. This paper presents the investigation of the optimum percentage of granite waste powder as a binder, specifically, the effect of molar and alkaline to binder (A/B) ratio on the mechanical properties of geopolymer concrete (GPC). Additionally, this study involves the use of admixture SP-340 for better performance of workability. Current work focuses on investigating the effect of a change in molarity that results in strength development in geopolymer concrete. The limits for the present work were: GGBS partially replaced by GWP up to 30%; molar ranging from 12 to 18 with the interval of 2 M; and A/B ratio of 0.30. For 16 M of GPC, a maximum slump was observed for GWP with 60 mm compared to other molar concentration. For 16 M of GPC, a maximum compressive strength (CS) was observed for GWP with 20%, of 33.95 MPa. For 16 M of GPC, a maximum STS was observed for GWP, with 20%, of 3.15 MPa. For 16 M of GPC, a maximum FS was observed for GWP, with 20%, of 4.79 MPa. Geopolymer concrete has better strength properties than conventional concrete. GPC is $13.70 costlier than conventional concrete per cubic meter. [ABSTRACT FROM AUTHOR]

Agriculture is the primary source of income in developing countries like India. Agriculture accounts for 17 percent of India's total GDP, with almost 60 percent of the people directly or indirectly employed. While researchers and planters focus on a variety of elements to boost productivity, crop loss due to disease is one of the most serious issues they confront. Crop growth monitoring and early detection of pest infestations are still a problem. With the expansion of cultivation to wider fields, manual intervention to monitor and diagnose insect and pest infestations is becoming increasingly difficult. Failure to apply on time fertilizers and pesticides results in more crop loss and so lower output. Farmers are putting in greater effort to conserve crops, but they are failing most of the time because they are unable to adequately monitor the crops when they are infected by pests and insects. Pest infestation is also difficult to predict because it is not evenly distributed. In the recent past, modern equipment, tools, and approaches have been used to replace manual involvement. Unmanned aerial vehicles serve a critical role in crop disease surveillance and early detection in this setting. This research attempts to give a review of the most successful techniques to have precision-based crop monitoring and pest management in agriculture fields utilizing unmanned aerial vehicles (UAVs) or unmanned aircraft. The researchers' reports on the various types of UAVs and their applications to early detection of agricultural diseases are rigorously assessed and compared. This paper also discusses the deployment of aerial, satellite, and other remote sensing technologies for disease detection, as well as their Quality of Service (QoS). [ABSTRACT FROM AUTHOR]

Studying and analyzing the challenges that the renewable energy sector faces can help evaluate the risks and improve the planning. This research is done by considering the challenges in the implementation of sustainable generation of electricity through RESs in India, based on factors, including technical, financial, involvement, support, and others. The triangular fuzzy number (TFN) method, based on fuzzy logic concept, is used to analyze the challenges in this study. In general, TFN comprises of three numbers, likewise Gaussian fuzzy numbers, trapezoidal fuzzy numbers also exist. The classified sets of numbers are denotations to decision-makers' perspective or a choice towards the criterion preference. Although alternatives are many to design a fuzzy set depending on elements count, the TFNs are the ones considered as actual representations of a fuzzy number. On the other hand, cases the Gaussian or trapezoidal, are manifestations of fuzzy intervals. Another argument is that the membership function shape corresponding to the number of fuzzy set elements is largely dependent on the study. The challenges identified along with analysis in this paper will help the industry, governments, and policymakers focus and tackle essential issues to facilitate further the deployment of RESs in India towards a more sustainable country. [ABSTRACT FROM AUTHOR]

With the negative climate impact of fossil fuel power generation and the requirement of global policy to shift towards a green mix of energy production, the investment in renewable energy is an opportunity in developing countries. However, poor economy associated with limited income, funds availability, and regulations governing project funding and development are key factors that challenge investors in the energy sector. Given the various power generation resources, including renewables, it is necessary to evaluate the possible power generation investment options from an economic perspective. To realize this objective, solar PV, wind and diesel power generations are economically compared, considering the incremental rate of return and incremental benefit to cost ratio techniques. The alternative investment options of distributed generation technologies are evaluated for Maharashtra, India under different depreciation methods, and the effect of the latter on selecting the best investment candidate is investigated. The paper also conducts sensitivity analysis to examine the impact of capital cost, operation and maintenance cost, and fuel cost variations on the selection decision considering a comparison of the different general projects' cash flow structures discussed in the literature. The economic aspects of selecting a project among possible alternatives for an investment in the power sector are analyzed, and the presented review provides comprehensive comparisons with respect to the literature approaches. The results reveal that, in the benchmark case study, the PV project is rejected and disregarded from further comparisons with other candidate projects since its equity internal rate of return (10.25%) is less than the minimum accepted rate of return, leaving the selection between wind and diesel energy projects. The study reveals that the incremental rates of return under such a comparison are 37.88%, 45.94% and 37.50% when MACRS, declining balance and straight line depreciations techniques are applied, respectively. Thus, the wind energy project is the favored option in this case. For the economic assessment of other case studies, the application of both sensitivity analysis on the capital cost and operation and maintenance cost and literature approaches to structure the projects reveal that wind energy for Maharashtra, India is a more attractive and feasible option compared to other distribution generation projects, while diesel is only considered to be a good option when its fuel cost is reduced by 5%. Finally, the paper highlights policy implications that can influence the decision to move towards investment in distributed generation technologies as a future research direction. [ABSTRACT FROM AUTHOR]

Smartphones have become an inevitable part of every facet of modern society. The selection of a particular smartphone brand from multiple options that are available is a complex and dynamic decision-making problem, involving multiple conflicting criteria that are associated with imprecise asymmetric information imposed by the uncertainty of the consumers. In this paper, we propose a novel hybrid full consistency method (FUCOM) and a combinative distance based assessment (CODAS) based on the multi-criteria group decision-making (MAGDM) framework in the Fermatean fuzzy (FF) domain for smartphone brand selection. We derive the criteria using the UTAUT2 (unified theory of acceptance and ese of technology) model. A group of 15 decision makers (DMs) participated in our study. We compare 14 leading smartphone brands in India and find that the brands having superior features of a good quality and selling a brand image at a affordable price outperform other smartphones. To check the validity of our framework, we compare the results using extant multi-criteria decision-making (MCDM) models. We observe our model provides a consistent solution. Furthermore, we carry out a sensitivity analysis for ascertaining the robustness and stability of the results generated by our model. The results of the sensitivity analysis show that our proposed framework delivers a stable and robust solution. [ABSTRACT FROM AUTHOR]

The magnetotelluric (MT) method is one of the useful geophysical techniques to investigate deep crustal structures. However, in hilly terrains, e.g., the Garhwal Himalayan region, due to the highly undulating topography, MT responses are distorted. Such responses, if not corrected, may lead to the incorrect interpretation of geoelectric structures. In the present paper, we implemented terrain corrections in MT data recorded from the Garhwal Himalayan Corridor (GHC). We used AP3DMT, a 3D MT data modeling and inversion code written in the MATLAB environment. Terrain corrections in the MT impedance responses for 39 sites along the Roorkee–Gangotri profile in the period range of 0.01 s to 1000 s were first estimated using a synthetic model by recording the topography and locations of MT sites. Based on this study, we established the general character of the terrain and established where terrain corrections were necessary. The distortion introduced by topography was computed for each site using homogenous and heterogeneous models with actual topographic variations. Period-dependent, galvanic and inductive distortions were observed at different sites. We further applied terrain corrections to the real data recorded from the GHC. The corrected data were inverted, and the inverted model was compared with the corresponding inverted model obtained with uncorrected data. The modification in electrical resistivity features in the model obtained from the terrain-corrected response suggests the necessity of terrain correction in MT data recorded from the Himalayan region. [ABSTRACT FROM AUTHOR]

The formation of the Ailaoshan metallogenic belt was the result of: the Neoproterozoic super mantle plume, the Indosinian and South China blocks in the Late Triassic after the Paleo-Tethys Ocean closure, and Oligocene-Eocene continental-scale shearing related to the India-Eurasia collision. It is one of the most important Cenozoic gold ore province in the world. In this paper, the geological characteristics, isotopic geochemistry, and geochemical data of ore-forming fluids of four large-scale gold deposits in the Ailaoshan metallogenic belt (Mojiang Jinchang, Zhenyuan Laowangzhai, Yuanyang Daping, and Jinping Chang'an) are comprehensively compared. The features of host-rock alteration, metallogenetic periods and stages, geochronology, fluid inclusion, and C-H-O-S-Pb isotopes of gold deposits are summarized and analyzed. The gold mineralization in the Ailaoshan metallogenic belt occurred mostly in 50–30 Ma, belonging to the Himalayan period. The gold mineralization is closely related to silicification, argillation, carbonation, and pyritization due to the strong mineralization of hydrothermal fluid, the development of alteration products, and the inconspicuous spatial zonation of alteration types. The ore-forming fluid is mainly composed of mantle fluid (magmatic water) and metamorphic fluid (metamorphic water). The ore-forming materials of the Jinchang, Chang'an, and Laowangzhai gold deposits mainly originate the host-rock strata of the mining area, and the carbon is more likely to from marine carbonate. The carbon in the Daping gold deposit from the original magma formed by the partial melting of the mantle. Pb isotopes have characteristics of crustal origin, accompanied by mixing of mantle-derived materials and multisource sulfur mixing, and are strongly homogenized. [ABSTRACT FROM AUTHOR]

An extraction method for deep-seated thick seam deposits by underground mining with high resource recovery has remained a great challenge for Indian mining engineers, whereas the longwall top coal caving (LTCC) method has evolved as an effective method for various geo mining conditions in China and other counties. The percentage of top coal recovery (TCR) plays a predominant role in determining the feasibility of LTCC, which relies on the First Top Coal Caving Distance (FTCD). In this paper, the critical geotechnical parameters are identified, numerically simulated, and statistically analyzed, and the FTCD for Indian geo-mining conditions is developed and validated. A financial assessment is conducted, considering 70% top coal recovery at 85% performance level, cost of production escalated by 20% and fall in coal grade by two grades. The internal rate of return (IRR) for LTCC is 30.24% as per the sensitivity analysis where it is only 18% in single pass longwall method. This study contributes to evaluating both the technical and economic feasibility of introducing LTCC in Indian geo-mining conditions. [ABSTRACT FROM AUTHOR]

With the technical growth and the reduction of deployment cost for distributed energy resources (DERs), such as solar photovoltaic (PV), energy trading has been recently encouraged to energy consumers, which can sell energy from their own energy storage system (ESS). Meanwhile, due to the unprecedented rise of greenhouse gas (GHG) emissions, some countries (e.g., Republic of Korea and India) have mandated using a renewable energy certificate (REC) in energy trading markets. In this paper, we propose an energy broker model to boost energy trading between the existing power grid and energy consumers. In particular, to maximize the profits of energy consumers and the energy provider, the proposed energy broker is in charge of deciding the optimal demand and dynamic price of energy in an REC-based energy trading market. In this solution, the smart agents (e.g., IoT intelligent devices) of consumers exchange energy trading associated information, including the amount of energy generation, price and REC. For deciding the optimal demand and dynamic pricing, we formulate convex optimization problems using dual decomposition. Through a numerical simulation analysis, we compare the performance of the proposed dynamic pricing strategy with the conventional pricing strategies. Results show that the proposed dynamic pricing and demand control strategies can encourage energy trading by allowing RECs trading of the conventional power grid. [ABSTRACT FROM AUTHOR]

Higher penetration of variable renewable energy sources into the grid brings down the plant load factor of thermal power plants. However, during sudden changes in load, the thermal power plants support the grid, though at higher ramping rates and with inefficient operation. Hence, further renewable additions must be backed by battery energy storage systems to limit the ramping rate of a thermal power plant and to avoid deploying diesel generators. In this paper, battery-integrated renewable energy systems that include floating solar, bifacial rooftop, and wind energy systems are evaluated for a designated smart city in India to reduce ramping support by a thermal power plant. Two variants of adaptive-local-attractor-based quantum-behaved particle swarm optimization (ALA-QPSO) are applied for optimal sizing of battery-integrated and hybrid renewable energy sources to minimize the levelized cost of energy (LCoE), battery life cycle loss (LCL), and loss of power supply probability (LPSP). The obtained results are then compared with four variants of differential evolution. The results show that out of 427 MW of the energy potential, an optimal set of hybrid renewable energy sources containing 274 MW of rooftop PV, 99 MW of floating PV, and 60 MW of wind energy systems supported by 131 MWh of batteries results in an LPSP of 0.005%, an LCoE of 0.077 USD/kW, and an LCL of 0.0087. A sensitivity analysis of the results obtained through ALA-QPSO is performed to assess the impact of damage to batteries and unplanned load appreciation, and it is found that the optimal set results in more energy sustainability. [ABSTRACT FROM AUTHOR]

Solar energy is going to be a major component of global energy generation. Loss due to dust deposition has raised a great concern to the investors in this field. Pre-estimation of this reduced generation and hence the economic loss will help the operators' readiness for efficient and enhanced economic energy management of the system. In an earlier article, a physics–based model is proposed for assessment of dust accumulation under various climatic conditions which is validated by data of a single location. In this paper, the universality of this model is established and is used to demonstrate the effect of generation loss due to dust deposition and of cleaning. Variation in the soiling pattern due to climatic covariates has also been studied. Generation loss is calculated for Solar Photovoltaic power plants of different capacities at various locations in India. Finally this model has also been extended to predict the generation accounting for the soiling loss in Photovoltaic system. All the calculated and predicted results are validated with the measured values of the above plants. [ABSTRACT FROM AUTHOR]

This paper investigates the physical and mechanical properties of bighorns of Deccani breed sheep native from Karnataka, India. The exhaustive work comprises two cases. First, rehydrated (wet) and ambient (dry) conditions, and second, the horn coupons were selected for longitudinal and lateral (transverse) directions. More than seventy-two samples were subjected to a test for physical and mechanical property extraction. Further, twenty-four samples were subjected to physical property testing, which included density and moisture absorption tests. At the same time, mechanical testing included analysis of the stress state dependence with the horn keratin tested under tension, compression, and flexural loading. The mechanical properties include the elastic modulus, yield strength, ultimate strength, failure strain, compressive strength, flexural strength, flexural modulus, and hardness. The results showed anisotropy and depended highly on the presence of water content more than coupon orientation. Wet conditioned specimens had a significant loss in mechanical properties compared with dry specimens. The observed outcomes were shown at par with results for yield strength of 53.5 ± 6.5 MPa (which is better than its peers) and a maximum compressive stress of 557.7 ± 5 MPa (highest among peers). Young's modulus 6.5 ± 0.5 GPa and a density equivalent to a biopolymer of 1.2 g/cc are expected to be the lightest among its peers; flexural strength 168.75 MPa, with lowest failure strain percentage of 6.5 ± 0.5 and Rockwell hardness value of 60 HRB, seem best in the class of this category. Simulation study identified a suitable application area based on impact and fatigue analysis. Overall, the exhaustive experimental work provided many opportunities to use this new material in various diversified applications in the future. [ABSTRACT FROM AUTHOR]

In recent studies, various reports reveal that stubble burning of crop residues in India generates nearly 150 million tons of carbon dioxide (CO2), more than 9 million tons of carbon monoxide (CO), a quarter-million tons of sulphur oxides (SOX), 1 million tons of particulate matter and more than half a million tons of black carbon. These contribute directly to environmental pollution, as well as the haze in the Indian capital, New Delhi, and the diminishing glaciers of the Himalayas. Although stubble burning crop residue is a crime under Section 188 of the Indian Penal Code (IPC) and the Air and Pollution Control Act (APCA) of 1981, a lack of implementation of these government acts has been witnessed across the country. Instead of burning, crop residues can be utilized in various alternative ways, including use as cattle feed, compost with manure, rural roofing, bioenergy, beverage production, packaging materials, wood, paper, and bioethanol, etc. This review article aims to present the current status of stubble-burning practices for disposal of crop residues in India and discuss several alternative methods for valorization of crop residues. Overall, this review article offers a solid understanding of the negative impacts of mismanagement of the crop residues via stubble burning in India and the other more promising management approaches including use for bioenergy, which, if widely employed, could not only reduce the environmental impacts of crop residue management, but generate additional value for the agricultural sector globally. [ABSTRACT FROM AUTHOR]

In this paper, I explore how India's complex regime of control and management of religious institutions and communities—ironically, particularly Hindu institutions—influences the capacity of these institutions to promote various dimensions of human flourishing and socio-economic uplift among the most marginalized. In addition, I provide an overview of India's highly varied landscape when it comes to the freedom of religious institutions from state control, and in particular discuss how some minority religious institutions experience fewer government constraints on some aspects of their freedom to self-identify and self-govern, especially when compared to some majority institutions, such as Hindu temples. Although some minority institutions still face constraints on certain aspects of their operations, the freedom they have to manage their internal affairs can, at times, translate into greater agility and the ability to innovate and flourish in the context of 21st-century India. [ABSTRACT FROM AUTHOR]

India's Nationally Determined Contributions (NDC) aim to increase the share of non-fossil fuel, especially renewables, in power generation. But at the same time, it mentions that coal is likely to dominate the power generation in the short and medium term to meet the increase in demand and support the intermittency of renewable energy-based power generation. Thus, additional efforts to transform the thermal power generation to a more efficient and less emitting one in the near term by increasing the use of natural gas (a fossil fuel with a lower emission factor than coal) may be planned towards achieving India's additional mitigation commitments. The paper presents the implications of a proposed increase in the share of natural gas in thermal power generation of India by looking into the trade-off between emission mitigation and energy security. Along with a Reference Scenario, three alternative emission scenarios are proposed to understand the likely impacts of increased penetration of natural gas in power generation on India's projected emission profile up to 2050. Results suggest that higher mitigation potential can be achieved through fuel-switch in thermal generation and technological up-gradation to enhance energy use efficiency. The energy security due to the increased share of natural gas imports can be dealt with by diversifying import sources. Shifts can achieve this in the emphasis on long-term contracts. [ABSTRACT FROM AUTHOR]

This article aims to trace and describe the bioethical threads in medical practice and the understanding of medicine among Tibetan refugees living in India. Taking up such a task results mainly from the fact that only traces of bioethical reflection are visible in Tibetan society, but without the awareness that it requires systematic reflection on its essence and changes that accompany modern medicine. I define the state of the discussion on Tibetan bioethics as preparadigmatic, i.e., one that precedes the recognition of the importance of bioethics and the elaboration of its basic concepts. In this paper, I will show how the Tibetan refugees today, in an unconscious way, approach bioethics, using the example of life-related topics, namely beginning and death. To this end, I chose topics such as abortion, fetal sex reassignment, euthanasia, and suicide. On this basis, I will indicate the main reasons that hinder the emergence of bioethics and those that may contribute to systematic discussions in the future. An introduction to Tibetan medicine will precede these considerations. I will show how medical traditions, especially the Rgyud bzhi text, are related to Tibetan Buddhism and opinions of the 14th Dalai Lama. [ABSTRACT FROM AUTHOR]

Agriculture residue is a promising resource of energy. It can be seen as a source of power production. In India, there is a huge amount of biomass available, but it cannot be used in proper ways, and with the help of GIS it can be customised. In the present paper, it is estimated that biomass reserves are available for power generation. The biomass produced by the surplus agricultural crops is reflected as a source of fuel for electricity generation. The data taken by satellite are useful for assessment of the areas with the help of satellite images taken in high resolution, which increases the preciseness of estimation. An agriculture cropland map with agricultural statistics has been analyzed in GIS to discover the agricultural straw potential for bioenergy generation. Due to unawareness about the benefits and uses of GIS, the modern farming sector bears a loss of huge bioenergy potential every year. To overcome the above mentioned challenges, the agricultural system needs a major shift from conventional farming to smart farming practices with the help of GIS. Agricultural waste is the best source for bioenergy production, and it can be used as biomass for meeting renewable energy goals in the country. [ABSTRACT FROM AUTHOR]