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The pulp and paper industry is critical to global industrial and economic development. Recently, India's pulp and paper industries have been facing severe competitive challenges. The challenges have impaired the environmental performance and resulted in the closure of several operations. Assessment and prediction of the performance of the Indian pulp and paper industry using various parameters is a critical task for researchers. This study proposes a framework for performance assessment and prediction based on Data Envelopment Analysis (DEA), Artificial Neural Networks, and Deep Learning (DL) to assist industry administration and decision-making. We presented a case study based on eight industries to demonstrate the methodology's applicability. This study analyses and predicts industry performance based on sample data observations over 30 years. The result suggests the DEA-DL-based efficiency prediction has an overall MSE of 0.08 compared with the actual efficiency. Furthermore, the efficiency rankings are compared between the three techniques. The results suggest that the integrated DEA-DL method is primarily accurate in most scenarios with the actual values. The findings of this study provide a comprehensive analysis of environmental performance for policymakers. [ABSTRACT FROM AUTHOR]

The bacterial diversity in terms of structure and community profile, with special reference to water quality in the wastewater treatment plant of Indian paper industries, is poorly understood. In the present work, characterization of bacterial diversity using 16S (V3-V4 region) rRNA gene amplicon sequencing data with reference to physicochemical parameters in the wastewater treatment plant of two paper industries has been carried out. Amplicon data analysis revealed the presence of bacterial taxa belonging to the phylum such as Bacteroidetes, Proteobacteria, Patescibacteria, Firmicutes, Actinobacteria, etc. Further, taxonomic classification upto genus level and functional analysis data indicated that genera such as Cloacibacterium, Aerococcus, Chryseobacterium, Microbacterium, Acinetobacter, Sphingobium, etc., were involved in the predicted metabolic pathways like carbohydrate metabolism, fatty acid and aromatic compounds biosynthesis as well as degradation. Canonical correspondence analysis confirmed a significant correlation between the microbial pollutions loads and physicochemical parameters. Further, the chemical oxygen demand, biochemical oxygen demand and total suspended solids exceeded the acceptable limits prescribed by Central Pollution Control Board New Delhi, Government of India, for discharge of wastewater. This study finds the correlation between the bacterial community residing in the polluted water of wastewater treatment plant and their environmental preferences. The presence of these bacterial diversity in the wastewater treatment plant of paper industries may affect the maintenance as well as paper quality. In future, it will provide a benchmark for the better understanding and management of wastewater treatment plant in paper industries across the globe. [ABSTRACT FROM AUTHOR]

In today's scenario of India most of the youth is preparing for some competitive exam. If we think behind 15–20 years the number of candidates appearing for competitive exams were in thousands but as the population is increasing exponentially in India day by day the number of candidates is increasing in lacks. We can observe by daily newspapers that most of the competitive exams are facing paper leak problems. Although online examination systems are more effective and secure as compared to offline examination systems because it's not easy to open the question paper before the time starts. On the other hand there are also various consequences where the examination process can be hacked online. But the main issue with online examination process is to lack of resources to conduct parallel examination of millions of candidates, lack of techno enabled exam centers in small cities etc. Our focus is to propose a system in which offline examination can be conducted at most of the govt. and private centers in metro cities as well as small techno backward cities with reduced possibility to leak the paper before commencement of examination. [ABSTRACT FROM AUTHOR]

The study aims to find the quality of research papers published in the domain of entrepreneurship in India. This study covers 100 research papers. A standardized measurement tool developed by the earlier researchers was used to evaluate the research quality. The data compiled using the measurement tool were analyzed with the support of the SPSS. The statistical tools such as descriptive statistics, Friedman's test, factor analysis, two-sample 't' test, and ANOVA are applied to analyze the data. The study findings reported that the quality of research papers published in the field of entrepreneurship is not up to the quality standards. The quality of multiple-author papers is better than single-author papers. Similarly, the quality of papers published by foreign authors is comparatively better than Indian authors. Further, the quality of papers published with the combination of foreign and Indian authors is substantially good. The quality of papers published in foreign journals is higher as compared with Indian journals. Further, the standard of papers published under the qualitative approach was comparatively better than the quantitative approach. The authors developed a Conceptual Model of Process and Product of Research (YOVA model). This model clearly shows that the whole research process yields six levels of research products. The study recommended that the researchers need to go for international collaborations to improve the quality of the publication. The funding agencies, higher learning institutions and research institutions should focus on enhancing research infrastructure. The study examined the validity of research articles searched by novice researchers in India in Google by using keywords related to entrepreneurship and, as such this non-focused approach is a big impediment to quality research. [ABSTRACT FROM AUTHOR]

Over the years, survival of children with chronic diseases has significantly improved and a large proportion of them now are entering into adulthood. Transition of Care (ToC) of such patients with having childhood onset of chronic diseases to the adult health care system is well organized in developed countries, although it is an emerging concept in India. In situations where the systems for ToC are not in place, such cases are fraught with unsatisfactory health outcomes. With proper ToC in place, these patients are likely to receive uninterrupted care by the adult care physicians and hence reach their full potential. This document highlights the need, rationale and way forward for ToC of youth with special health care needs (YSHCN) across the country. It also describes the standard operating procedures to develop the ToC at a hospital level for clinicians and administrators. [ABSTRACT FROM AUTHOR]

Bacteriophages are key viruses that can kill thousands of harmful microbes generally present at polluted sites. Such bacteriophages are abundantly present in the river Ganga, where millions of people in India and abroad drink its water and take baths every day for spiritual reasons. Besides bacteriophages, several pathogenic and zoonotic microbes are present in the river Ganga. It is interesting to study the diversity and abundance of bacteria and their respective phages present in polluted or non-polluted sites. Thus, the metagenomics study was carried out at the most polluted sites of river Ganga near Kanpur and non-polluted sites at Farakka, which harbors several harmful bacteria and their phages. The results revealed a significantly higher percentage of Microviridae phage family, ssDNA viruses, and Mimiviridae virus family near Kanpur than Farakka. In addition, compared to Kanpur, Farakka has a more significant percentage of Myoviridae, an unidentified phage family, and Retroviridae viral families. Despite heavy drainage of untreated and contaminated effluents from the leather industry, pesticide industry, paper mills, metropolitan cities, and other sources, the vast number of said phages kills several harmful pathogenic microbes in polluted sites to maintain the Ganga water's healing power or natural sterility. In a polluted aquatic environment, the varieties of bacteriophages were identified in the Ganga and their interaction with the microbial host. The taxonomic diversity of several bacteriophages found in pathogenic host systems was investigated to get exceptional knowledge of these small viruses in the aquatic environment. [ABSTRACT FROM AUTHOR]

India's Indo-Gangetic Plain (IGP) region has become the global hotspot of air pollution, and stubble burning in northern India has increased the concern due to its impact on air quality and health. The current study focuses on studying the diurnal variation of air pollutants for the first time covering Haryana, India, and identifying the sources responsible for air pollutants emissions during the different seasons of the year. Based on ecology and cropping pattern, the study area was divided in three zones. In all seasons, the diurnal peak concentrations of particulate matter (PM2.5 and PM10) were found highest in Zone 2 as compared to Zone 1 and Zone 3, which can be due to the high polluting districts located in Zone 2 including Hisar where thermal power plants, stainless steel producing industry and pulp and paper industry are located along with district Faridabad which is known as the industrial capital of Haryana. The lowest average hourly concentration of PM10 and PM2.5 was found in late afternoon hours in winter, pre-monsoon and post-monsoon season in all three zones due to a decrease in traffic volumes which lead to low emission rates along with increase in the mixing height which cause favorable dispersion conditions. The lowest hourly mean concentration of CO, NOx and NH3 in all zones was found during the afternoon hours in all seasons. The study also focuses on understanding the day and time patterns and the maxima and minima of pollutants concentrations in different zones of Haryana. [ABSTRACT FROM AUTHOR]

This paper mainly aims to identify the key factors that should be included in building of smart cities in a proper efficient way. Due to rapid increase in urban population, it should be responsible to provide a better way in building of a smart city. Smart city is an idea of providing urban development that includes social, financial, ecological parts of a society. A smart and sustainable city has goals to be achieved in an adaptable, reliable, scalable, accessible, and in resilient way which will be discussed in the methodology section. This paper mainly focuses on some important factors in improving sustainability of smart cities such as climate and environmental issues and governance authorities for improving quality of life of citizens. Also, this paper explains 3E's which are environment, economy and equity are plays a crucial role in rapid development of smart cities. This research is focused on discussing various smart technologies recently used in India and the challenges involved in them. Recent literature on smart city development is reviewed, and the challenges that prevailed in recent technologies are analysed. This paper includes how Internet of Things (IoT), Connectivity, Cloud computing and AI etc., should be effectively used for developing a smart city. This paper deals with the requirements to build smart cities in India – regarding various aspects like available resources, lifestyle, transport management system, smart healthcare system, smart waste management, smart Sanitation, smart railways, smart agriculture, home automation, smart energy consumption etc. This paper also discusses 'smart living,"smart infrastructure,"smart governance,"smart economy,' and other various systems which are need for Smart India in particular. When adopted with proper planning, all the above catalysing with smart services and solutions, build a sustainable city. [ABSTRACT FROM AUTHOR]

Early childhood development (ECD) refers to the physical, motor, socio-emotional, cognitive, and linguistic development of a young child. The 'Countdown to 2030' global distribution of 'children at risk of poor development' indicates the need for urgent action and investment in ECD. Nurturing care enhances ECD, even in the presence of adversities. Strategic actions should exist at multiple levels: the family, community, health care providers and government. Previously, child health related policies and programs of the Government of India functioned in isolation, but have recently started demonstrating multi-sectoral collaboration. Nonetheless, the status of ECD in India is far from optimal. There is strong evidence that parenting programs improve outcomes related to ECD. This is dependent on key programmatic areas (timing, duration, frequency, intensity, modality, content, etc.), in addition to political will, funding, partnership, and plans for scaling up. Each country must implement its unique ECD program that is need-based and customized to their stakeholder community. Barriers like inadequate sensitization of the community and low competency of health care providers need to be overcome. IAP firmly believes that responsive parenting interventions revolving around nurturing care should be incorporated in office practice. This paper outlines IAP's position on ECD, and its recommendations for pediatricians and policy makers. It also presents the roadmap in partnership with other stakeholders in maternal, neonatal, and child health; Federation of Obstetric and Gynaecological Societies of India (FOGSI), National Neonatology Forum (NNF), World Health Organization (WHO), and United Nation Children Fund (UNICEF) [ABSTRACT FROM AUTHOR]

While promoting manufacturing growth is imperative to boost economic growth, potential adverse consequences on natural resources and ecology have created sustainability-related concerns and challenges. In India, with the reform processes deepening further and the business environment becoming more market-oriented over the years, the adoption of appropriate measures for sustainable manufacturing growth under such conditions would require a deeper investigation of the underlying dynamics, particularly to address the impacts of external shocks. This is especially true when external shocks alter market dynamics and, hence, input is used significantly in the manufacturing sector. Given this backdrop, the present paper examines how the major external shocks to the Indian economy during in the post-reform era have altered the resource use patterns in selected manufacturing industries. The paper uses secondary data collected from the KLEMS database of the Reserve Bank of India for the period from 1980–81 to 2019–20 and applies descriptive statistics and econometric techniques to address the research objective. It is found that energy intensity, vertical integration, capital intensity, and rate of growth of total factor productivity decreased over the decades, whereas labour productivity experienced an increasing trend in most industries. However, the trends are mixed in the case of material intensity. Further, the regression results indicate significant effects of external shocks on resource use, factor productivity, and structural changes. There are also industry-specific differences in the nature and extent of such changes. Hence, a deeper investigation of the underlying factors and impacts at a disaggregate industry level is necessary to draw more robust insights. [ABSTRACT FROM AUTHOR]

In this reply to the discussion of our paper (Kumar et al. in Nat Hazards 116:2437–2455, 2023), we attempt to rebut the claims made regarding the use of the maximum sustained wind speed of a cyclone event irrespective of its location, inappropriate implementation of fitting methods, and inconsistent use of future projected sea surface temperature to historical records. While the discussion highlights certain observations about our results, the application of such techniques for evaluating PMTC parameters (adhering to AERB criteria) requires further research. [ABSTRACT FROM AUTHOR]

Technical progress has a tremendous potential to reduce carbon dioxide emissions by reducing energy consumption, a major concern across production units. However, the existing empirical literature concerning technical efficiency and carbon intensity is scanty. Thus, this paper examines the relationship between technical efficiency and carbon intensity for the organized manufacturing sector of two states, Maharashtra and Odisha, and the all-India level from 2001 to 2018. The paper uses data envelopment analysis to estimate technical efficiency scores. It applies the 2006 Intergovernmental Panel on Climate Change Tier 1 methodology for estimating carbon intensity for each 3-digit manufacturing industry in all three sample cases. The study has used static panel regression and fractional logit regression techniques to examine the deterministic relationship between technical efficiency and carbon intensity. The result shows that technical efficiency is highly sensitive to carbon intensity in the Indian manufacturing industries. The findings also addressed that the size of the industries also reduces the technical performance of manufacturing units. This paper also confirmed that increased profit could boost the Indian manufacturing industries' technical efficiency. Thus, this study addresses that carbon intensity as a proxy for the manufacturing sector's potential to affect climate change plays a crucial role in explaining the technical efficiency variations across industries. Thus, it calls for better policies aimed at reducing the emissions of industries specifically to achieve sustainable growth for the Indian manufacturing sector. [ABSTRACT FROM AUTHOR]

Child malnutrition remains a pervasive problem in India though there are significant improvements in several health indicators with country's consistent economic growth. Along with other factors, maternal autonomy is considered to be critical in influencing health outcome of a child. This paper attempts to examine the determinants of nutritional measures of children under age five with the focus to the role of mother's autonomy in India. There are studies which link characteristics of mother, like education, age, with nutrition of her children. But maternal autonomy is a complex subject as this variable is not tangible. Women's autonomy in daily life is more likely to result in their better healthcare which in turn influences children's birth weight and infant nutrition. We used nationally representative India Human Development Survey 2004–05 (IHDS- 1) and 2011–12 (IHDS 2) data for the analysis. This paper studies the association between maternal autonomy and childhood stunting, the indicator of chronic malnutrition, and the risk of having a stunted child. We have also used the panel data using both waves of IHDS and used mothers fixed effect model to evaluate the impact of maternal autonomy. The autonomy index is created using four dimensions-women's decision making, freedom of movement, financial autonomy and attitude toward domestic violence. The two dimensions of autonomy—physical autonomy, financial autonomy—remain significant determinants for childhood stunting. [ABSTRACT FROM AUTHOR]

Competitiveness is a key requirement for modern companies to survive. Effective corporate governance practices are also fast emerging as a fundamental obligation owed to shareholders and other stakeholders. The connection between competition and good corporate governance is derived from the product market competition hypothesis (PMCH) that projects the idea that operating in competitive markets would increase x-efficiency and decrease agency costs in companies, leading to superior corporate governance. Although a significant amount of work, both theoretical and empirical has been carried out on the efficacy of the PMCH, none of the research has been conclusive. Moreover, there has been no concentrated effort into determining the impact of the PMCH on the specific types of agency problems that are endemic to companies with largely concentrated shareholding structures like India. The paper highlights that a part of the reason behind the waning and unconvincing research on the PMCH (specially in India) has been the focus on competitiveness as an abstract concept or empirical construct, rather than on the regulatory aspect of competition, that is, competition law. This paper examines the connection between competition law and corporate governance, specifically the utility of competition regulation in being used to improve corporate governance in companies. It also considers the effectiveness of competition law in dispelling some of the pervasive Indian corporate governance problems such as tunneling and inefficient related party transactions. Some of the methods that are considered which would have such an impact and thus are recommended by the researcher, are a redefinition of 'dominant position' in the competition law discourse, to include within it pyramidical groups of companies as well as viewing tunneling practices as having an 'appreciable adverse effect' on competition. Doing so would result in numerous efficiencies as competition law could be used to kill two birds with one stone: increasing both competitiveness and good corporate governance. [ABSTRACT FROM AUTHOR]

Indian securities markets have undergone significant transformations in the recent past. The paper discusses and documents initiatives taken by the market regulator to expand and deepen the securities markets, including encouraging innovations in financial instruments, improving market efficiency by appropriate and timely regulatory interventions, expanding issuers' base and investors' participation for inclusive growth, ensuring regulatory compliance for fair play of market forces. The study helps investors, intermediaries, and regulators outside India to gain insights into recent developments and opportunities they offer to make the Indian securities market their preferred investment destination. The study concludes with the papers' key findings on "Investor interest and innovative instruments" in the special issue. [ABSTRACT FROM AUTHOR]

The Air Quality Index (AQI) in India is steadily deteriorating, leading to a rise in the mortality rate due to Lung Cancer. This decline in air quality can be attributed to various factors such as PM 2.5, PM 10, and Ozone (O3). To establish a relationship between AQI and Lung Cancer, several predictive models including Linear Regression, KNN, Decision Tree, ANN, Random Forest Regression, and XGBoost Regression were employed to estimate pollutant levels and Air Quality Index in India. The models relied on publicly available state-wise Air Pollution Dataset. Among all the models, the XGBoost Regression displayed the highest accuracy, with pollutant level estimations reaching an accuracy range of 81% to 98% during training and testing. The second-highest accuracy range was achieved by Random Forest. The paper also explores the impact of increasing pollution levels on the rising mortality rate among lung cancer patients in India. [ABSTRACT FROM AUTHOR]

This paper explores the historical context and current dynamics of the transboundary water issues between India and China. Both countries share multiple transboundary river basins, with the Brahmaputra River being one of the most significant. The importance of the Brahmaputra River to both nations goes beyond just providing resources. It has implications for national security, regional stability, and human livelihoods. However, China's upstream control over the river and its extensive dam-building projects have raised concerns in downstream India and Bangladesh about potential impacts on water availability, agriculture, and livelihoods. The river system is critical for the socioeconomic well-being of millions of people, yet the competing demands for water resources have led to geopolitical tensions. The paper highlights China's strategic use of water resources, including plans for large-scale dams, which India views as a potential threat to its water security. It also underscores the importance of a nuanced understanding of hydropolitics, emphasizing the need for human security, particularly water security, in addressing these challenges. It argues that while "water wars" are unlikely, "water tensions" are significant and must be addressed through comprehensive bilateral agreements and collaborative efforts. [ABSTRACT FROM AUTHOR]

This paper empirically examines the effect of domestic monetary policy shock on external commercial borrowings (ECBs) to India for the period 2000:Q2 to 2019:Q4. The impact of domestic monetary policy shock on ECBs is assessed using two variables: interest rate differential and domestic money supply growth. The paper employs a structural VAR model and utilizes impulse response functions and forecast error variance decomposition analysis to derive empirical results. The empirical results based on impulse response functions indicate that the interest rate differential has a positively significant effect on external commercial borrowings to India, while the effect of domestic money supply growth is found to be negative. The forecast error variance decomposition analysis indicates that the interest rate differential explains about 14.6% and domestic money supply growth explains about 2% of the total variation in external commercial borrowings, implying that domestic monetary policy variables together explain about 16.6% of the total variation in ECBs to India. The results suggest that the central bank, through monetary policy interventions, can influence and manage the flow of external commercial borrowings to India. Furthermore, the study finds that the exchange rate, domestic industrial activity, domestic output growth, domestic country's creditworthiness, and domestic macroeconomic instability are other significant determinants of external commercial borrowings. [ABSTRACT FROM AUTHOR]

IRNSS/NavIC is an independent navigation system developed by India. The dependence on external satellite-based navigation systems is gradually decreasing as a result of the deployment of our own navigation system, IRNSS/NavIC, which exhibits enhanced reliability. In this paper, a software-based IRNSS/NavIC receiver is developed using the standard Signal-In-Space Interface Control Document as a reference for signal structure, subframe patterns and parameter calculations. The IRNSS/NavIC receiver is validated with the I/Q data file as input which is generated by software based IRNSS/NavIC simulator. Analysis of the effect of a specific error on receiver output position necessitates repeated trials and modification, or in some cases, the development of new algorithms. The intermediate stage data can be viewed or stored as needed; a few examples are provided. In this paper Squared Correlators Code Discriminator (SCCD), a new multipath mitigation method has been designed and developed for IRNSS/NavIC receiver. The SCCD method is derived from Strobe Correlator (SC) and Combination of squared correlator method (CSC). The pseudorange bias is investigated and eliminated from the SCCD approach. The performance parameters of the IRNSS/NavIC receiver using each of the four approaches are compared, and the outcomes are discussed. [ABSTRACT FROM AUTHOR]

Sustainable development is essential for the survival of the planet. The massive increase in GHG emissions due to human activities has put the world in unrest. The Indian construction industry is emerging and evolving at a rapid rate and has understood the grave situation, and for saving the environment has come up with innovative solutions for developing green buildings or sustainable construction. In this paper, the two different (the GRIHA Rating System and the IGBC Green New Building Rating System) of India were studied. The sample size was 40 construction professionals working on green building projects. An interview schedule was used for data collection. The data was subjected to a suitable analysis and the AHP method was applied. Based on the research findings, strategies to go green has been suggested for the IGBC and GRIHA rating system which may serve as a ready reckoner for enhancing the effectiveness and efficiency of the construction management process. Therefore, keeping in mind the above view this research paper "Review of Indian Green Building Rating Systems by Using Analytical Hierarchy Process (AHP) on Various Parameters" becomes indispensable. Hence, this research study can be considered an effort to empower construction professionals to create an extensive analysis of green building concepts and develop sustainably in India. [ABSTRACT FROM AUTHOR]

All over the world, waste and its disposal are becoming a more prominent issue, as landfills swell up and growing evidence points to its contribution to climate change and environmental degradation. In the developing world, waste pickers sort through solid waste and sell it to vendors, who will recycle the product into something consumable. The work they do is vital to climate change mitigation, as well as urban cleanliness. In a way, waste pickers, especially in India, are vehicles of environmental justice, but they are often discriminated against and subjected to inhumane working conditions. In this environment, the pandemic hit, making waste pickers' already precarious life even worse. This paper attempts to fill the gap in the academic literature by compiling a systemized literature review of the impacts of COVID-19 on waste-pickers' lives using an environmental justice perspective. The review also uses a Feminist Political Ecology perspective to illuminate the double jeopardy that female waste pickers face in the era of COVID-19, which academia often ignores. Ultimately, this paper shows that COVID-19 exacerbated the preexisting injustices that the waste picker community face and created an immense burden on women. This paper will show that it is important to notice the differentiation between female and male waste picker challenges, especially at the crux of the COVID-19 pandemic. This paper has important policy implications as well as research considerations for both environmental justice and feminist political ecology scholars. [ABSTRACT FROM AUTHOR]

Forecasting of load is essential for operating power systems. India recently witnessed one of the worst power crisis with the highest ever power demand of 207 GW on April 29, 2022. The demand in the month of May and June 2022 was estimated to reach 215 GW. The peak demand this year 2023, according to the electricity ministry, is predicted to be around 230 GW from April to June. The inability to meet certain fundamental issues as power can take a toll on any country's economy. Proper prediction helps in proper decision making and planning. The main objective of this paper is to predict day ahead electrical load demand for Assam. Statistical and Machine Learning Algorithms has been studied. The study has been carried out using real-time data for the years 2016, 2017 and 2018. The paper presents a detailed analysis of the different hyper parameters of the deep learning models and their effect is seen on the learning efficiency. A novel stacked forecasting model is proposed using neural networks as base learners and CatBoost as the meta-learner. The performance of the proposed model has been evaluated and compared with individual models in terms of training time and accuracy using different error metrics namely MAE, MSE, RMSE, MAPE and R2 score. A comparison of the proposed prediction model with the prediction models available in literature has been presented. The conclusion states that both the statistical and machine learning algorithms used in this study act as useful tools for daily load forecasting with considerable accuracy; yet machine learning algorithm outperforms the statistical methods. The entire work has been done in Google Colaboratory using Python as the programming language. [ABSTRACT FROM AUTHOR]

The scholarship and discussion on urbanization and urbanism are restricted to the exploration of a few metropolitans and global cities. In this way, especially in India, several cities and towns do not fit into the understanding of knowledge produced from metropolitan or large cities. Taking the case of Dharamshala a small town in the Western Himalayas, this paper discusses how debate and conceptualization of urban processes, level of urbanization and scale of economies bypass thousands of small towns not only in India but across the global South. The paper draws attention to the categorization of the urban into small and big, metropolitan and non-metropolitan, unable to provide a comprehensive theory or concept to conceptualize activities and processes that coexist in binaries. Employing an ethnographic approach it discusses the ambiguous statistical criteria, infrastructural facilities, social and cultural dynamics, informality and illegality of Dharamshala. Building on this, the paper asserts that small towns and big cities have a lot of similarities in processes and activities, they may be different from each other at the level of size and scale. Drawing any kind of hierarchy among cities and towns that have the foundation in size (population and geographical) and scale (economies) and positioning them in 'subaltern' positions does not produce a comprehensive framework nor contribute to Southern urban theory but position small towns in between position of metropolitan's cities and urban theories. Noting such debates and discussions, the contribution opens a fresh perspective to study small towns beyond their size and scale and focuses on the processes and activities that contribute to an understanding of Indian urban transition, thereby expanding Southern urban theories. [ABSTRACT FROM AUTHOR]

Gross Domestic Product (GDP) is significant for measuring the strength of national and global economies in urban profiling areas. GDP is significant because it provides information on the size and performance of an economy. The real GDP growth rate is frequently used to indicate the economy's health. This paper proposes a new model called Pearson Correlation-Long Short-Term Memory-Recurrent Neural Network (PC-LSTM-RNN) for predicting GDP in urban profiling areas. Pearson correlation is used to select the important features strongly correlated with the target feature. This study employs two separate datasets, denoted as Dataset A and Dataset B. Dataset A comprises 227 instances and 20 features, with 70% utilized for training and 30% for testing purposes. On the other hand, Dataset B consists of 61 instances and 4 features, encompassing historical GDP growth data for India from 1961 to 2021. To enhance GDP prediction performance, we implement a parameter transfer approach, fine-tuning the parameters learned from Dataset A on Dataset B. Moreover, in this study, a preprocessing stage that includes median imputation and data normalization is performed. Mean Square Error, Mean Absolute Error, Root Mean Square Error, Mean Absolute Percentage Error, Median Absolute Error, and determination coefficient (R2) evaluation metrics are utilized in this study to demonstrate the performance of the proposed model. The experimental results demonstrated that the proposed model gave better results than other regression models used in this study. Also, the results show that the proposed model achieved the highest results for R2, with 99.99%. This paper addresses a critical research gap in the domain of GDP prediction through artificial intelligence (AI) algorithms. While acknowledging the widespread application of such algorithms in forecasting GDP, the proposed model introduces distinctive advantages over existing approaches. Using PC-LSTM-RNN which achieves high R2 with minimum error rates. [ABSTRACT FROM AUTHOR]

The scenario of developed and developing countries nowadays is disturbed due to modern living style which affects environment, wildlife and natural habitat. Environmental quality has become or is a subject of major concern as it is responsible for health hazard of mankind and animals. Measurements and prediction of hazardous parameters in different fields of environment is a recent research topic for safety and betterment of people as well as nature. Pollution in nature is an after-effect of civilization. To combat the damage already happened, some processes should be evolved for measurement and prediction of pollution in various fields. Researchers of all over the world are active to find out ways of predicting such hazard. In this paper, application of neural network and deep learning algorithms is chosen for air pollution and water pollution cases. The purpose of this review is to reveal how family of neural network algorithms has applied on these two pollution parameters. In this paper, importance is given on algorithm, and datasets used for air and water pollution as well as the predicted parameters have also been noted for ease of future development. One major concern of this paper is Indian context of air and water pollution research, and the research potential presents in this area using Indian dataset. Another aspect for including both air and water pollutions in one review paper is to generate an idea of artificial neural network and deep learning techniques which can be cross applicable for future purpose. [ABSTRACT FROM AUTHOR]

A smart home energy management system plays an important role in improving the efficiency of an energy distribution system and also helps to reduce the carbon footprint of the power utility company. For a developing country like India, one of the main challenges faced while integrating an energy management system and renewable energy technology is the migration cost faced by the user from the existing system. The existing energy policy of the nation or the community should be reformed in such a way that the user who is willing to adapt to an energy management system should be properly rewarded. Smart appliances and IoT-enabled devices reduce wiring complexity in any conventional home and the smart metering facility aids in the bidirectional communication between consumers and utility companies. But how does it take care of user privacy? What are the reasons behind the user's negligence on-demand response schemes in India? Through a case study, it was observed that the power consumption of domestic consumers in India increased over the years. It was also observed through an energy survey of 200 low-tension domestic consumers that a simple reengineering of lighting loads can save up to 4.68 Megawatt-hour of energy in a year. The paper also identified the negative impact of the inclining block rate billing scheme by comparing the bimonthly energy consumption pattern of consumers and also proposed a new billing scheme. The paper also reviews the types of optimization methods available for load scheduling. This paper is an attempt to enlighten readers on the importance of adopting a sustainable home energy management system, as a socio-economic commitment towards a green future. Highlights: The connected loads in Indian homes are increasing day by day and so the electricity bill A smart green HEM system helps to reduce the carbon footprint Novel demand response programs policies should be formulated Harvesting renewable energy will have multiple applications in a home Dimming lighting loads considerably reduces usage cost [ABSTRACT FROM AUTHOR]

Pines play a significant role in forest biodiversity globally and generate huge forest litter. Dry pine needles due to low ignition temperature and high frictional force with the ground catch fire quickly. Annual forest fires in the northern states of India greatly impact the Indian economy besides causing huge loss to biodiversity, livelihood, and environment. Pine needles are also considered unfit for fodder consumption due to presence of tannins. Although the presence of softwood lignin in pine needles makes it difficult to degrade easily, the presence of holocellulose (68.5%) containing 45–51% cellulose makes this biomass a potential substrate to be used in pulp-making industries for low-grade paper sheets. The good fiber length of pine needles (1.3–1.4 mm) with a diameter of 30–32 μm, maybe considered important property for paper making. The use of pine needles in the pharmaceutical and food industries are due to the presence of secondary metabolites (α-pinene, β-pinene, caryophyllene etc.). The various other potential applications of pine needles are for producing bio-ethanol (yield, 3.98%; purity, 94%), biogas (yield, 23.1 L kg−1), smokeless briquettes (calorific value, 18.77 MJ kg−1), biochar (calorific value, 25.6 MJ kg−1), bio-composites (tensile strength, 21–60 MPa), and bio-pesticides. This paper comprehensively reviews the current applications of pine needles along with its future prospective applications that can have the dual advantage of providing employment opportunities to the people along with environmental protection. [ABSTRACT FROM AUTHOR]

The lie-detection tests are traditionally carried out by well-trained experts using polygraph machines. However, it is time-consuming, invasive, and, overall, a cumbersome process, not admissible by the court of law. Trained individuals can easily flaunt these tests. On the other hand, facial thermal imaging could be more effective as it is noninvasive and could be a stealth method of tracking the facial blood flow patterns, which have been proven to detect deceit. This paper presents a method based on facial thermal imaging to detect deception in human subjects. The major issue in such research is the lack of proper real-life databases which emulate the crime scenes. In this paper, first, we have developed a database based on almost real-life theft incidents with due diligence using isolated subjects over a period of time at a government hospital under the plea of free health checkup. The experiment has been conducted at Midnapore Medical College and Hospital, West Bengal, India, with proper ethical committee approval. The participants are selected at the behest of the police department with habitual crime records. Most of them have been repeatedly charged with petty crimes of pick-pocketing and stealing. They are invited individually at different instances of time under the plea of medical checkup where they have been enticed to steal cash. It is followed by a two-stage process, a friendly interaction followed by a slightly tougher interrogation. Their forehead and periorbital region skin surface temperature are recorded by a hidden thermal camera. Upon analysis, conspicuous changes in the temperature profile and blood flow pattern have been observed in the individuals who stole money and those who did not. [ABSTRACT FROM AUTHOR]

The paper aimed to investigate the cyclical dynamics of the business, credit, and investment sectors in India. This was achieved by utilizing annual data from 1980 to 2021 and investigating the impact of domestic and global financial cycles on the business cycle. The cycles were derived using the Hodrick–Prescott filter, and structural vector autoregression (SVAR) and Granger causality tests were employed to establish the dynamic interactions among these cycles. The results of the study revealed a clear divergence between domestic and global financial cycles. Additionally, the SVAR analysis confirmed the presence of a long-run relationship between business, investment, and credit cycles. Notably, the findings suggest that credit cycles can provide valuable insights to manage business cycles in India. Finally, robustness checks were conducted to confirm the reliability of SVAR findings. [ABSTRACT FROM AUTHOR]

Introduction: The emergence of artificial intelligence (AI) chat programs has opened two distinct paths, one enhancing interaction and another potentially replacing personal understanding. Ethical and legal concerns arise due to the rapid development of these programs. This paper investigates academic discussions on AI in medicine, analyzing the context, frequency, and reasons behind these conversations. Methods: The study collected data from the Web of Science database on articles containing the keyword "ChatGPT" published from January to September 2023, resulting in 786 medically related journal articles. The inclusion criteria were peer-reviewed articles in English related to medicine. Results: The United States led in publications (38.1%), followed by India (15.5%) and China (7.0%). Keywords such as "patient" (16.7%), "research" (12%), and "performance" (10.6%) were prevalent. The Cureus Journal of Medical Science (11.8%) had the most publications, followed by the Annals of Biomedical Engineering (8.3%). August 2023 had the highest number of publications (29.3%), with significant growth between February to March and April to May. Medical General Internal (21.0%) was the most common category, followed by Surgery (15.4%) and Radiology (7.9%). Discussion: The prominence of India in ChatGPT research, despite lower research funding, indicates the platform's popularity and highlights the importance of monitoring its use for potential medical misinformation. China's interest in ChatGPT research suggests a focus on Natural Language Processing (NLP) AI applications, despite public bans on the platform. Cureus' success in publishing ChatGPT articles can be attributed to its open-access, rapid publication model. The study identifies research trends in plastic surgery, radiology, and obstetric gynecology, emphasizing the need for ethical considerations and reliability assessments in the application of ChatGPT in medical practice. Conclusion: ChatGPT's presence in medical literature is growing rapidly across various specialties, but concerns related to safety, privacy, and accuracy persist. More research is needed to assess its suitability for patient care and implications for non-medical use. Skepticism and thorough review of research are essential, as current studies may face retraction as more information emerges. [ABSTRACT FROM AUTHOR]

In this paper based on original fieldwork, I seek to contribute to critical scholarship in international law by providing an investigation into the engagement with international law by actors in civil society working against son preference primarily in Tirupati, India. I suggest that the turn to the international legal order by civic actors should be theorized as something else than as merely coming 'from above', 'from below' or as a 'translation' of 'global' law to 'local' conditions. Instead, I propose that the mobilization of international law within Tirupati's civil society should be seen as an emancipatory undertaking, an act of resistance with the overarching ambition to reclaim the zenana. In that, I argue, the strategies within Tirupati's civil society are more appropriately understood as critical international law put into practice. [ABSTRACT FROM AUTHOR]

This paper seeks to design the least-cost delivery routes relating to the distribution of geotowns through the shortest distance matrix estimated by the multiple traveling salesman problems. We construct the initial distance matrix based on road distance considering all the nodes. Based on the adjacency matrix, we use the R package "sna" to calculate the different measures of centrality in the network. Next, we apply the traveling salesman problem to connect all the nodes at once for planning the trip in the proposed circuit. Finally, we use the Louvain community detection algorithm to cluster geotowns for better tourism planning and ease of travel. Based on the proposed geoheritage sites in Northeast India, the tourist spots may be organized and interconnected. This paper promotes and develops an approach to incorporating national geosites with national geoheritages and moves towards geoparks, keeping in view conservation measures of appropriate international impartial organizations. [ABSTRACT FROM AUTHOR]

China, India, and the USA are the countries with the highest energy consumption and CO2 emissions globally. As per the report of datacommons.org, CO2 emission in India is 1.80 metric tons per capita, which is harmful to living beings, so this paper presents India's detrimental CO2 emission effect with the prediction of CO2 emission for the next 10 years based on univariate time-series data from 1980 to 2019. We have used three statistical models; autoregressive-integrated moving average (ARIMA) model, seasonal autoregressive-integrated moving average with exogenous factors (SARIMAX) model, and the Holt-Winters model, two machine learning models, i.e., linear regression and random forest model and a deep learning-based long short-term memory (LSTM) model. This paper brings together a variety of models and allows us to work on data prediction. The performance analysis shows that LSTM, SARIMAX, and Holt-Winters are the three most accurate models among the six models based on nine performance metrics. Results conclude that LSTM is the best model for CO2 emission prediction with the 3.101% MAPE value, 60.635 RMSE value, 28.898 MedAE value, and along with other performance metrics. A comparative study also concludes the same. Therefore, the deep learning-based LSTM model is suggested as one of the most appropriate models for CO2 emission prediction. [ABSTRACT FROM AUTHOR]

Mathematics education in India is offered in one of the 22 officially recognized state languages or in English even though there are at least 270 languages with more than 10,000 speakers each. Caste, a deep-rooted structure that stratifies Indian society, is integrally linked to shaping state languages. There is minimal research from India that looks at language and mathematics education and practically none that factors in caste. Focusing on Tamil Nadu, a state with a history of anti-caste movement on the one hand and pure Tamil movement (a movement that sought to create a Tamil language with no words from other languages) on the other, this conceptual paper seeks to explore this dimension. More specifically, by using caste as an analytical framework, and by drawing on examples from the mathematics textbooks published by the Tamil Nadu State Board of Education and the experience of a few teachers and learners, the paper seeks to make a theoretical argument that the use of pure Tamil in mathematics textbooks has negative implication for socio-culturally and economically marginalized students who are solely dependent on textbooks as the only source for learning mathematics. There is a strong need for carrying out empirical work that would highlight the nuances and complexities involved in realizing 'mother tongue' education in mathematics, particularly for those who belong to marginalized caste-class backgrounds, and we hope that such work would emerge in the future. [ABSTRACT FROM AUTHOR]

This research paper delves into the intricate domain of policy science, focusing on the policy-making process itself. Existing theoretical frameworks in policy science often overlook essential nuances, particularly the role of political willingness causing non-linearity in the policy-making process. Three fundamental questions drive the research at hand. First, the research delves into the adequacy of existing policy frameworks in effectively elucidating the complexities of policymaking in the context of large democracies, with a particular focus on India. Second, it investigates the significant role of political willingness in shaping the trajectory of policymaking, particularly within democratic systems. Lastly, the research aims to construct a comprehensive framework capable of accommodating and explaining the non-linear dynamics introduced by the influence of political willingness throughout the policy-making process. Through an analysis of India's Data Protection Regulation formulation process, this paper attempts to map the existing gap and way forward. As an outcome of the case study analysis, the proposed framework introduces political willingness as a central element extending the policy formulation cycle and showcases its influence on agenda setting, policy formulation, adoption, implementation, and evaluation. This research contributes to the field of policy science by providing a comprehensive framework that accounts for the complexities of policymaking, especially in the Indian context. By acknowledging the pivotal role of political willingness, this framework seeks to bridge the gap in existing theoretical models, offering a more holistic understanding of policy formulation and analysis. This research lays the foundation for a paradigm shift in the study of policy science, addressing the challenges posed by evolving governance mechanisms and the rising influence of political agendas in the modern world. [ABSTRACT FROM AUTHOR]

The debate over the Uniform Civil Code (UCC) is mired in the conflict between the right to freedom of religion and the right to gender-based equality. The retraction of the UCC also hinges on legal pluralism. This paper argues for shifting the foci of the debate towards gender-based violence as rightly suggested by the feminist argument in India. In order to do so, this paper argues that the debate over the UCC needs to be restructured around the Due Diligence Obligation (DDO) to the Convention on the Elimination of all forms of Discrimination Against Women (CEDAW). This paper presents the argument that the absence of a UCC creates a normative vacuum that is currently filled by an intersubjective climate on patriarchy which primes the average Indian mindset. This intersubjective mindset requires to be replaced by the normative language of the DDO to the CEDAW. This process of norm effectuation also ties into the question of how international norms are implemented in domestic contexts and reiterates the causal chain propounded therein. [ABSTRACT FROM AUTHOR]

This paper deploys the containment principle by Della Croce and Nicole-Berva (2021) to adjudicate COVID-19 non-conformity in India. The paper argues that the containment principle offers a guide to evaluating pandemic legislation and outlines the duties of the state. It then evaluates the Indian Pandemic response and legislation against the containment principles and finds it arbitrary, arguing that the discretionary power vested in the state enables it to treat two instances of COVID-19 non-conformities, the Tablighi Jamaat and the Kumbh, differently. The non-conformity of the devotees and the deviance of the state can be read within a framework of exceptionalism, collective irrationality, and conspiracy theories that firstly enables the devotees to maintain a sense of invulnerability, and secondly, allows the state to blame the minority community for threatening its exceptional status. These acts of non-conformities constitute disobedience against containment principles that are unjustifiable and demonstrate a moral failure to not harm others and a failure of the state to equally distribute benefits and burdens of pandemic policies. [ABSTRACT FROM AUTHOR]

The paper defines a new model for Takri touching text segmentation (T3S), which uses simpler statistical operations to locate exact segmentation column and generate faster results. An analysis of existing Indian scripts touching text segmentation techniques is also provided in the paper. The analysis inferred higher accuracies with recognition-based approaches which are computationally and time extensive and, work better with huge datasets. Also, most of these have been developed for headline Indian scripts only. The proposed T3S model provides significant segmentation accuracy using a statistical approach thus, generating faster results. Also, it works well with small datasets, which is feasible with the diverse ancient low-resource scripts of India like Takri. The model has been implemented on Takri text, a class of non-headline Indian regional scripts. Thus, it provides a benchmark algorithm for conducting further research in the field. A dataset of 1465 touching consonant pairs in printed Takri script is prepared using connected component segmentation for segmenting Takri text from the manually collected archival data in printed Takri script. The T3S technique is implemented on the dataset prepared and the results are critically analyzed with the existing Indian scripts touching text segmentation approaches, based on the accuracy achieved. [ABSTRACT FROM AUTHOR]

This paper examines the intersection of regional geopolitics and the governance of transboundary rivers using the case studies of multipurpose reservoirs in Himalayan South Asia. It uncovers the various ways Indian hydrocracy uses its institutional and technical expertise to strengthen India's centrality in Nepal's water and hydropower sectors. The practices of security undertaken by the hydrocrats are classified as structural, institutional, and statutory acts. By focusing on practices of an epistemic community like hydrocrats, this paper addresses longstanding weaknesses of the securitisation theory of being elitist and ignoring the agency of mid-level bureaucrats. It also highlights the constructivist nature of international politics. The findings contribute empirically to securitisation theory's 'Paris School' of thought. [ABSTRACT FROM AUTHOR]

Mining is an important enterprise that will supply essential minerals for the country's infrastructural development. Mining is a key industry and a development engine in the Indian economy. The epidemic has had both immediate and long-term effects on the labour and industries in India. Short-term effects include the cessation of mineral production, salary loss due to absenteeism and pandemic limitations, unemployment, and the selling of minerals on the market. The reputation and economic health of industries, fresh mineral deposit exploration, and new mining complex development have all been impacted in long-term. Aside from the mining industry-specific impact of COVID-19, the social fabric of the mining workers has been impacted since they are living in an environment of fear and uncertainty. This paper attempts to analyse the effect of COVID-19 on extractive industries in India. It also focuses the steps which taken by the Indian government. The paper concluded with the negative effect of COVID-19 which disrupts the mining sector and the contribution declined during COVID-19. However, for instance from mineral rich-Odisha, the mining sector takes up by its growth in post COVID-19 period with remarkable increment from negative growth to high positive rate. [ABSTRACT FROM AUTHOR]

Socioeconomic situations in young people's families and communities make them more vulnerable to suicidal ideations. The Youth Helpline has made a significant difference in youth's lives and livelihoods by addressing their social and economic needs with positive mental health support. The quantitative and qualitative data validate the micro- and macro-level impact of the Youth Helpline in Puducherry. However, the multi-stakeholder model faces challenges in ensuring accountability, particularly from government partners. This paper highlights how direct intervention on the socio-economic determinants of youth suicidal ideation has positively affected youth mental health and reduced suicidal ideation in Puducherry. Social identity-based inequalities and access and affordability to mental health services are the major contributors to youth mental health problems. This paper critically discusses the Youth Helpline's multi-stakeholder process and youth-led approach to addressing socio-economic determinants, as well as the Helpline's impact on youth mental health. [ABSTRACT FROM AUTHOR]

In this paper, I examine how an organization narratively constructs its prototypical disabled employee. Data comprise public narratives of the Government of India, the country's largest employer of disabled persons. Narratives during 2008–2016 were considered as this timespan witnessed the design of inclusive legislation that emphasized defining disabled persons and their entitlements. Findings indicate that the label of "disadvantage" was consistently used to portray the target employee. Alongside other narrative material suggesting, for example that the target employee was someone who required employment assistance, this label was supplied to external audiences to convert them into potential partners. This supply of narrative material further reinforced the portrayal of the target employee. Consistent use of this expansive label subsumed changing definitions of who is a disabled person, allowed for aggregations with diverse disadvantaged collectives, and accommodated changes in employment entitlements and ecosystem partners, thereby allowing the reading of change in stable narratives. The contributions of this paper lie in highlighting how the consistent use of an expansive label can cast narrative stability and change as complementary, and in suggesting that narrating a prototypical employee entails shaping the setting outside the employing organization toward employee categorization. [ABSTRACT FROM AUTHOR]

In response to the beginnings of the COVID-19 pandemic, India's government instituted a severe nationwide lockdown in late March 2020. In this paper, we analyze household survey data on income from an Indian state, Punjab. We analyze the impacts of the pandemic and lockdown on total household income, as well as its components, including wages, business income and transfers. This paper innovates in this area by using Poisson Pseudo Maximum Likelihood estimation to deal with the skewed distributions of various income components, as well as quantile regressions to examine differential impacts across the income distribution. We examine the differences between rural and urban households, differential impacts on female-headed and laborer households, and the time pattern of impacts. We find that rural households experienced more persistent income declines than urban households, and their wages suffered relatively more. Households with daily laborers were most badly affected, and this was especially true at the bottom of the income distribution. [ABSTRACT FROM AUTHOR]

The International Journal of Tropical Insect Science (Int J Trop Insect Sci) is a peer-reviewed journal established in 1980 to promote insect science mainly in the tropics. This study aimed to provide a Bibliometric overview of Int J Trop Insect Sci publications and citations between 2012 and 2020, ending September 2020. A sample of 488 documents extracted from the Web of Science (WoS) was analysed using widely used bioclimatic indicators. The articles were written by 1726 authors. During this period, the most productive authors comprised S Roy, followed by S Ekesi, S Subramanian and M Tamo. The dominant keyword was 'resistance', followed by 'Homoptera'. India took a leading position in Single Country Publications (SCP) while Kenya took the lead in Multiple Country Publications (MCP). Bibliometric analysis reveals vibrant collaboration between African and Western countries and active publication of multi-country authored articles. We conclude that there is an increasing trend for collaboration among different countries on the general topic of insect science. Research in insect science has the potential to impact both academic researchers and practitioners the knowledge use chain. This study will help researchers, journal editors, science policy makers managers, and others working in the biodiversity space and potential research gaps needing for further studies. [ABSTRACT FROM AUTHOR]

This paper focuses on the spatiality of cricket played over public grounds. The paper uses the concepts of space, place and sportscape (Appadurai in Playing the modernity: The decolonisation of Indian Cricket, University of Minnesota Press, 1995) to derive meanings of the way the game is played and experienced. The study is organised under three scales conceptualised as landscape, territory and anthropocentric levels which are interlinked to each other. Drawing insights from the geography of sports literature, the paper extends the boundaries of knowledge about cricket beyond historical and sociological studies of the sport. A combination of methods, namely, ethnographic observations, interviews and focused group discussions were employed to deduce the spatial connection of cricket to urban spaces in India. For this purpose, Nirankari Grounds in North Delhi has been selected as the study area. The location of Nirankari Grounds at the crossroads of a densely populated residential area and the University of Delhi makes it an important site for the study. The paper contributes to the study of geography by expanding the geographical understanding of the sport. At the same time, it attempts to fill in the gaps in literature in domain of sports geography by analysing spatial aspects of sports when the game is in play. [ABSTRACT FROM AUTHOR]

Self-Help Groups (SHGs), the credit based voluntary groups in India are widely known for their potential to alleviate poverty and empower women. This research article explores a lesser-known theme. It tries to analyze the possibility of utilizing the current SHG model of the Indian Government to build and strengthen resilience of the SHG members in case of an external shock like financial stress, food insecurity, dispute in home for joining SHG, and difficulty to repay loan amidst lockdown due to the COVID-19 pandemic. This article also focuses on their coping mechanisms and attitude towards these crises. By utilizing primary data collected from 320 SHG members in one of the aspirational districts in West Bengal, India, the present paper tries to fulfill its objective. It provides a comprehensive understanding of the problems faced by the SHG members by combining both quantitative and qualitative techniques. The findings reveal that from organizing vocational trainings to relaxing loan repayment, SHGs and its women members overcame various adversities with tenacity, especially during the COVID-19 pandemic. Based on the study findings, it is reasonable to conclude that the current SHG model in India presents a promising avenue for enhancing the resilience of its members in the face of external shocks. Article Highlights: Idiosyncratic stress like financial stress and systemic stress like the COVID-19 pandemic were ranked the top two crises faced by the SHG members. Recognizing financial stress and stress due to the COVID-19 pandemic as the top challenges faced by SHG members implies the need for immediate support (that includes access to financial resources, and assistance in adapting livelihood strategies to withstand external shocks), resilience-building efforts (by providing members with skills to diversify their income sources, creating emergency funds, and fostering community solidarity to collectively address crises), and policy attention (implementing policies that provide targeted assistance, such as social safety nets, healthcare access, and economic stimulus). The SHG members mostly had an active attitude towards the crises faced demonstrating their remarkable resilience and adaptive capacity. This highlights the most dominant role of SHGs in their ability to foster a sense of solidarity and collective problem-solving. Members often share experiences, skills, and resources, which can be invaluable during times of crisis. Additionally, the group dynamic encourages mutual support and encourages members to take proactive steps to address challenges rather than feeling overwhelmed by them. Moreover, participating in SHGs often empowers individuals to develop skills, build confidence, and access resources that enable them to better cope with crises. Thus, it implies the importance of community-based approaches like the SHGs to resilience-building. The primary role of SHGs in strengthening resilience among its members, particularly during challenging times like the COVID-19 pandemic was preventive measures (organizing COVID awareness programs), followed by promotional measures (organizing vocational trainings) and protective measures (distribution of food grains). By engaging in these preventive, promotional, and protective measures, SHGs bolstered the resilience of their members by equipping them with knowledge, skills, and resources to navigate challenges effectively. Overall, the implication is that SHGs have played a multifaceted role in supporting their members through the COVID-19 crisis, by focusing on prevention, promotion, and protection measures to enhance their resilience and mitigate the adverse effects of the pandemic on their well-being. [ABSTRACT FROM AUTHOR]

The Cauvery Basin is one of the prolific hydrocarbon-producing basins of southern India. The pericratonic basin has five sub-basins separated by five basement and structural highs formed by granitic and gneissic rocks of the Archaean Southern Granulite Terrane. The sub-basins have excellent Cretaceous source rocks and hydrocarbon-bearing reservoirs of different geological ages. Commercial hydrocarbons are produced from the Archean basement highs, specifically from the Kumbakonam–Madanam palaeo-highs of the Cauvery basin. The paper addresses basement characterisation using conventional as well as advanced well logs for accurate characterisation of the basement reservoirs. Basement reservoirs are challenging in terms of sporadic porosity and permeability distribution. Most of the porosities and permeability are attributed to secondary generation by fracturing and weathering. The present work aims to understand and compare the petrophysical attributes of two kinds of basement reservoirs (fractured basement and weathered basement) on the Kumbakonam–Madanam High. Two wells from each type lying on either side of the Madanam High were selected. Well log data, including gamma-ray, resistivity, porosity (neutron and bulk density), acoustic logs and advanced logs, such as resistivity images and dipole acoustic and elemental capture spectroscopy logs, from these four wells were analysed for their petrophysical understanding. Furthermore, image and acoustic log data were integrated to characterise the fracture geometry and fracture permeability of the basement reservoirs. Conventional log suites showing low GR, low resistivity, high density, and high neutron porosity are indicative of intricate lithologies, possibly mafic rocks. A notable negative crossover in density and neutron log along with excess Si concentration indicates weathering. A higher fracture density with a crisscross fracture/mesh fracture pattern is indicated by the analysis of image logs, shear wave anisotropy, and Stoneley fractures. Thus, a comparison of the petrophysical attributes of both fields is attempted to understand the fractured and weathered basement reservoirs and their geological characteristics. In conclusion, the basement reservoirs of the Madanam High Field are of interest because of their hydrocarbon-producing ability, and proper synthesis of petrophysical attributes will help develop activities in the basement reservoirs. [ABSTRACT FROM AUTHOR]

In an area like India, where a large number of people are dependent upon agriculture, soil erosion assumes the role of a silent killer. A comprehensive soil management plan requires systematic development and planning at the scale of the natural boundaries, i.e., the watersheds. These watersheds are now actively encouraged to become the planning unit for a wide range of natural resource management. Sub-basin prioritisation with respect to erosion susceptibility, therefore, has become increasingly popular in the last few decades as this helps in optimal distribution, especially in a country like India, where the availability of resources is scarce. Erosion is a complex problem wherein a large number of factors play an important role in influencing this process. Therefore, multi-criteria decision-making (MCDM) techniques are becoming more popular in this domain. However, there are a myriad of MCDM models in literature, and a proper and systematic comparison between such MCDM models may help in deciding on the best possible model in the given categories. This paper has tried to make such a comparison for morphometry-based sub-basin prioritisation in the rocky terrain of the Chaka River Basin, Eastern India. The MCDM models that have been investigated include technique for order of preference by similarity to ideal solution (TOPSIS), VlseKriterijumsk Optimizacija Kompromismo Resenje (VIKOR), multi-objective optimisation on the basis of ratio analysis (MOORA), compound factor (CF), weighted sum model (WSM), weighted product model (WPM) and weighted aggregated sum product assessment (WASPAS). These results were compared with respect to the RUSLE-based annual soil loss of the Chaka Basin with the help of the ROC curve. Results reveal that the MOORA MCDM method is the most reliable (AUC = 0.711), whereas the TOPSIS is the least authentic (AUC = 0.378). The middle domain of the Chaka Basin appears to be highly prioritised as compared to the lower domain. [ABSTRACT FROM AUTHOR]

Traditional multiple discrete–continuous (MDC) choice models impose tight linkages between consumers' discrete choice and the continuous consumption decisions due to the use of a single utility parameter driving both the decision to choose and the extent of choice. Recently, Bhat (Trans Res Part B Methodol 110:261–279, 2018) proposed a flexible MDCEV model that employs a utility function with separate parameters to determine the discrete choice and continuous consumption values. However, the flexible MDCEV model assumes an independent and identically distributed (IID) error structure across the discrete and continuous baseline utilities. In this paper, we formulate a flexible non-IID multiple discrete–continuous probit (MDCP) model that employs a multivariate normal stochastic distribution to allow for a more general variance–covariance structure. In doing so, we revisit Bhat (Trans Res Part B: Methodol 109: 238-256, 2018) flexible utility functional form and highlight that the stochastic conditions he used to derive the likelihood function are not always consistent with utility maximization. We offer an alternate interpretation of the model as representing a two-step decision-making process, where the consumers first decide which goods to choose and then decide the extent of allocation to each good. We demonstrate an application of the proposed flexible MDCP model to analyze households' expenditure patterns on their domestic tourism trips in India. Our results indicate that, if the analyst is willing to compromise on the strict utility-maximizing aspect of behavior, while also enriching the behavioral dimension through the relaxation of the tie between the discrete and continuous consumption decisions, the preferred model would be the flexible non-IID MDCP model. On the other hand, if the analyst wants the model to be strictly grounded on utility-maximizing behavior (which may also have benefits by way of welfare measure computations), and is willing to assume a very tight tie between the discrete and continuous consumption decision processes, the preferred model would be the non-IID traditional MDCP model. [ABSTRACT FROM AUTHOR]

India houses the third biggest Muslim population in the world but over the years it has experienced massive segregation of people based on their religious identities. This large-scale forced and systemic 'ghettoization' of Muslims is a recent trend largely ascribed to the frequent communal' violence and state's negligence towards minorities. In this backdrop, the paper discusses the communal ghettoization of Muslims and uses the Juhapura area of Ahmedabad as illustration to explain the same. This study is essentially based on field observations and literature to comprehend communal tone of ghettoization process. Muslims in India are a minority (15 percent of total population) and suffer most in case riots occur. In the last few decades, following the 1985, 1992 and 2002 riots, Gujarat emerged as a hotbed of communal tension, forcing the Muslim population to migrate from their original locations and seek refuge in other parts of the state. Residents of these newly populated ghettos such as Juhapura are forced to endure these conditions due to fear, lack of choice and state apathy. These localities are largely ignored and lack all forms of socio-economic and physical infrastructure for a decent living. [ABSTRACT FROM AUTHOR]