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Experiments in the field of high energy physics make use of very complex detector systems. Extraction of meaningful results from these experiments needs a deep understanding of the detector performance. The most important tool in the process of understanding is the use of simulation of some known physics processes. Tools were being developed from late 1970s with more and more improved modeling of electromagnetic and strong interaction of particles with matter. These tools are also used to design a detector system of present day high energy physics experiment. Design and construction of detectors for the experiments at the Large Hadron Collider (Lhc) took nearly two decades. Detector simulation played an important role in these designs. One of the most important toolkits and its use in one of the experiments at the Lhc are described in this paper. [ABSTRACT FROM AUTHOR]

Solar still is the easiest method to purifying the saline water for domestic usage, but this method needs much improvement for better performance since it has lower productivity. In this paper, an experimental investigation is completed to analyse the semi cylindrical solar productivity still. The semi-cylindrical still is incorporated with direct atomizer and scrap used as an energy storage medium. Experiments are carried out during March 2020 in Kovilpatti, the southern part of India, with a depth of 2 and 4 cm saline water. Comparative performance analysis is made for conventional semi-cylindrical still, semi-cylindrical still with an atomizer, and semi-cylindrical still with atomizer and storage materials. The experimental study shows that the productivity of still increases while decreasing the water depth. Compared with 2-cm and 4-cm depth, solar still with 2-cm depth gives promising distillate productivity. The solar productivity still having 4-cm depth of water without atomizer gives only 2670 ml; on the other side, 2-cm water depth without atomizer gives 3100-ml productivity. The maximum productivity of solar still is found on a semi-cylindrical solar still combined with atomizer and energy storage medium having 2-cm water depth. Results revealed a higher freshwater production rate of 3610 ml found while incorporating atomizer and energy storage with the solar still. The system efficiency improved up to 35.20% compared to conventional semi-cylindrical still with 4 cm of saline water depth. [ABSTRACT FROM AUTHOR]

The future of agriculture may be fully realized using knowledge of artificial intelligence (AI) accumulated by human expertise. With increasing climate change and population pressure challenges, new technologies, such as AI and RS in vital sectors like agriculture is urgently required to assess agricultural suitability, optimize productivity, and then support sustainable development. This paper presents bibliometric and review analyses on AI and geospatial analysis applied to the agricultural field. Based on the prestigious database, Scopus, thousands of documents were retrieved in the period 1992–2021 and processed using Scopus online tool and VOSviewer software. The results show a growing trend in the number of publications during this period. Earth and Planetary Sciences is the top domain, remote sensing (RS) is the leading source, while the United States and India are the most influential countries. RS, machine learning (ML), GIS, land-use, decision-making, decision trees, and satellite imagery are the most occurring topics in this search. Otherwise, research in this field is turning toward ML and deep learning techniques, whereas agricultural robots and antennas are the top trending tools. The current study provides specific information about the connections between artificial intelligence, geospatial analysis, and agriculture in the period 1992–2021, the fruitful period where the AI coupled to geospatial technologies is in full development. [ABSTRACT FROM AUTHOR]

Based on the data from the Periodic Labour Force Survey (PLFS) and multiple rounds of the Consumer Pyramids Household Survey from Centre for Monitoring Indian Economy (CMIE), the paper summarises evidence on changes in the employment–unemployment scenario since the onset of the COVID-19 pandemic and related curbs on economic activity since April 2020. The paper presents evidence on how the pandemic affected pre-existing gender, caste gaps and patterns of employment by sector of production (agricultural, manufacturing, and services). The paper situates these shifts in a longer arc, comparing them to the pre-COVID employment scenario, to understand the long-term impact of the pandemic on the Indian labour market. The data show that the pandemic reinforced and deepened many of the pre-existing schisms. As economic activity is recovering, employment is increasing, but is yet to return to the pre-pandemic levels. The employment challenge is bigger than just achieving the pre-pandemic levels: there is an urgent need to boost job creation and rectify pre-pandemic deep-rooted inequalities. [ABSTRACT FROM AUTHOR]

The paper discusses the work of early Indian professional economists in the field of labour. They undertook wide-ranging studies of labour in factories, mines, and plantations as well as of the condition of rural and agricultural labour and of urban labour outside of industry. Between 1918 and 1930, a major body of work had emerged on Indian labour, with contributions by both Indian and foreign scholars. This work was mostly based on government data, but, in addition, and with telling effect, some scholars also conducted field investigations and came up with disquieting findings. The latter part of the paper examines the contributions of a British statistician-economist, George Findlay-Shirras, and of an Indian labour economist, Rajani Kanta Das. The former, despite some excellent work, was probably responsible for giving a misleading picture of rising agricultural wages, perhaps to suit the views of the colonial government. R.K. Das, through his extensive work on labour economics, before and during his service with the International Labour Organization (ILO), contributed much to the work of the Royal Commission on Labour (1931), but this went unacknowledged. Also, his work on plantation labour in India earned the ire of a British official in the department of industries and labour probably, for highlighting the negative role played by foreign (British) capital. Given his numerous substantive contributions to Indian labour economics, the paper concludes that R.K. Das should be given due recognition for his pioneering role in the development of labour economics in India. [ABSTRACT FROM AUTHOR]

One of the most speedy and substantial social shifts in human history has been the evolution of gender relations since the turn of the 20th century. Even though female health, literacy and women participation in workforce have significantly improved, the status of women in Indian society is not very satisfactory leading to gender disparities. It is in this background that this paper attempts to analyse the role of education, labour market and health in reducing gender disparities across the states over the period of time. To analyse the impact of these variables, Gender Disparity Index (GDI) has been constructed utilising the data from Periodic Labour Force Survey (PLFS) and Sample Registration System (SRS) to measure gender disparities in 20 major states and union territories (UTs) of India. For the construction of GDI, we have used three dimensions, namely health, empowerment and labour market participation. The index is prepared to make a decadal comparative study for the years 2011–12 and 2020–21. The statistical results indicate that there is a significant difference in mean of the GDI scores for 2020–21 and 2011–12. The paper concludes with certain policy implications suggesting that there is a need to put more effort into creating infrastructure and cutting-edge policies to improve the health and education systems. The focus should also be to create more employment opportunities for females, helping them to raise their standard of living so as to enhance their contribution towards economic growth. [ABSTRACT FROM AUTHOR]

Despite much impetus on economic growth, educational expansion, health and infrastructural development, women participation in labour force market is not improving. Women participation in politics, leadership positions, national parliaments and local government, judiciary and police force is very essential for achieving Sustainable Development Goals (SDGs) by 2030. The said target is clearly mentioned as SDG 5.5 which entails—"Ensure women's full and effective participation and equal opportunities for leadership at all levels of decision-making in political, economic and public life". In India, percentage of female elected representatives in parliament rose from 9.0% in 1999 (13th Lok Sabha general elections) to 14.4% in 2019 (17th Lok Sabha general elections) as per the statistical reports published by the Election Commission of India. Thus, the paper tries to study the relationship between women in parliament (MP) and female labour force participation rates (FLPR) using panel data across Indian states for the period 1999 to 2019. The objective of the paper is to empirically examine the relationship between female (elected) political representation and FLPR, using fixed effect panel data model across 15 Indian states excluding Union Territories (UTs), North-Eastern States (NEs), Delhi, Goa, and Jammu & Kashmir (J&K). The panel data is created by taking data of female elected candidates of different states from the statistical reports of general elections published by Election Commission of India and that of FLPR is extracted from various rounds of National Statistical Office (NSO) and Periodic Labour Force Survey (PLFS) reports, respectively. The empirical results suggest that higher political representation of women is associated with favourable female labour outcomes. Our result implies that Female Political Representation (FPR) has a positive and significant effect on FLPR under fixed effect model. However, the random effect model suggests net state domestic product (NSDP) per capita has a negative and significant effect on FLPR, while, Fixed effect model suggests that female literacy rate has a negative and significant effect on FLPR which are consistent with the established literature. [ABSTRACT FROM AUTHOR]

This paper examines the impact of structural change, economic growth, hydro energy consumption, and coal energy consumption on ecological footprint, in the case of India. We employ a novel dynamic autoregressive distributed lag (DYNARDL) method to improve the existing studies' limitations and weaknesses. Thus, the current research contributes empirically and methodological to the literature. The study used the newly proposed DYNARDL simulation method and frequency domain causality using data from 1970–2017 to inspect the impact of structural change, economic growth, hydro energy consumption, and coal energy consumption on ecological footprint in the case of India. Empirical results reveal that institutional structural change decreases ecological footprint in the short and long term, whereas hydropower usage decreases ecological footprint only in the long term. Conversely, economic growth positively affects ecological footprint in both the short and long term. Likewise, coal energy usage increases ecological footprint in the long term. In addition, the findings confirm the validity of the environment Kuznets curve (EKC) hypothesis in India. Furthermore, the results of the frequency domain causality test revealed that structural change, hydro-energy usage, and coal consumption could predict ecological footprint in the long term. In contrast, economic growth can predict the medium- and long-term ecological footprint. We observed that as India's production level continues to surge, so does environmental deterioration, which is associated with the scale effect. [ABSTRACT FROM AUTHOR]

A country that relies on developing industrialization and GDP requires a lot of energy. Biomass is emerging as one of the possible renewable energy resources that may be used to generate energy. Through the proper channels, such as chemical, biochemical, and thermochemical processes, it can be turned into electricity. In the context of India, the potential sources of biomass can be broken down into agricultural waste, tanning waste, sewage, vegetable waste, food, meat waste, and liquor waste. Each form of biomass energy so extracted has advantages and downsides, so determining which one is best is crucial to reaping the most benefits. The selection of biomass conversion methods is especially significant since it requires a careful study of multiple factors, which can be aided by fuzzy multi-criteria decision-making (MCDM) models. This paper proposes the normal wiggly interval-valued hesitant fuzzy-based decision-making trial and evaluation laboratory model (DEMATEL) and the Preference Ranking Organization METHod for Enrichment of Evaluations II (PROMETHEE) for assessing the problem of determining a workable biomass production technique. The proposed framework is used to assess the production processes under consideration based on parameters such as fuel cost, technical cost, environmental safety, and C O 2 emission levels. Bioethanol has been developed as a viable industrial option due to its low carbon footprint and environmental viability. Furthermore, the superiority of the suggested model is demonstrated by comparing the results to other current methodologies. According to comparative study, the suggested framework might be developed to handle complex scenarios with many variables. [ABSTRACT FROM AUTHOR]

The study is undertaken to examine international trade and tourism nexus in case of India and SAARC countries. To achieve the objective, panel cointegration is employed over the period of 22 years (1997 to 2018). The results from both first and second generation cointegration tests indicated the existence of long run equilibrium among tourism, export, and import. Albeit there are differences between short-term and long-term associations, the findings from autoregressive distributed lag approach indicates strong long-term linkages between trade and tourism. A possible channel of exports exerting a positive influence on tourist arrival is that the products in foreign markets increase the recognition and image of a country eventually leading to more tourists. Moreover, increased exports are expected to increase business trips further increasing the leisure trips and hence a strong linkage between export and tourism. On the other hand, a possible explanation of positive effect of imports on tourism could be that the destination countries which provide tourists with products according to their home taste encourage tourists to travel to these countries. The findings provided in the paper have strong implications for expanding India's tourism footprint in the region. [ABSTRACT FROM AUTHOR]

This research paper aims to examine the spatial heterogeneity of malnutrition across districts in India and identify the contributing factors. Previous studies have focused on individual and household determinants of malnutrition, but limited research has explored the spatial distribution of malnutrition and its association with diverse factors at the district level. This study utilizes data from the National Family Health Survey round five (NFHS-5) and creates a district-level dataset with relevant socio-demographic, economic, and nutritional indicators. The analysis employs descriptive statistics, spatial autocorrelation measures, bivariate analyses, and regression models to assess the spatial patterns and determinants of malnutrition. The results reveal significant spatial variations in the prevalence of stunting, wasting, and underweight across districts in India. Economically disadvantaged states such as Bihar, Chhattisgarh, Madhya Pradesh, Jharkhand, and Uttar Pradesh have higher rates of malnutrition, but certain districts in relatively affluent states also exhibit elevated malnutrition rates. The analysis identifies factors such as asset ownership, BMI, women's education, institutional birth, and access to basic amenities as important determinants of malnutrition. The study highlights the spatial clustering of malnutrition indicators and provides insights for targeted interventions and policy formulation to address malnutrition at the district level in India. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic was not only a global health emergency but an economic crisis, adversely impacting global economic activities and posing a long-term impact on human livelihood. The pandemic also disturbed the earning competencies of the population, among which the marginalized communities were tremendously affected. In this respect, informal sector workers are marginalized and badly affected by the pandemic. This paper examines the impact of the COVID-19 pandemic on the livelihoods of informal workers in the Kolkata, the third most populated urban agglomeration in India, which was one of the epicenters of COVID-19 in the country. The study mainly based on primary field survey data collected through a well-designed questionnaire and in-depth interviews. A total of 90 participants were selected using purposive sampling, which consisted of six groups of informal workers, i.e., train hawkers, street food vendors, domestic helps, workers in medicine shops, vegetable sellers, and fish sellers were selected. Out of the six groups of informal workers, the first three are from non-essential services, and rest of three are from essential services. For measuring the impact of the pandemic on the livelihood of informal workers, a Livelihood Vulnerability Index (LVI) was prepared by modifying the DFID's Sustainable Livelihood Framework. The LVI is a cumulative outcome of three sub-indices, i.e., Adaptive capacity Index, Sensitivity Index and Exposure Index, comprised of sixteen variables. The results reveal that workers engaged in non-essential services suffered more due to the pandemic, and their livelihood became more vulnerable in comparison to the workers engaged in essential services. Another striking observation is that female informal workers are more vulnerable than their male counterparts, irrespective of the nature of services. The study emphasizes the need for livelihood security policies to protect informal workers from similar future crises. [ABSTRACT FROM AUTHOR]

Numenes grisa Chao, 1983, previously recorded only from China, Laos and Thailand, is recorded from India for the first time. Comments on the other two species, N. flagrans Tams, and N. siletti Walker, that are known from India are provided with live habitus images. N. flagrans Tams, 1928 has been rediscovered from India after 95 years since its original description. A provisional checklist of Numenes species that are described so far is also provided in this paper. [ABSTRACT FROM AUTHOR]

The increasing amount of air pollution on a global scale is a major source of worry. The elevated levels of pollution are affecting the health of urban dwellers and motorists to a great extent. Since the situation has become so dire, it has become an absolute necessity to find effective ways to reduce air pollution and mitigate the negative effects of air pollution on human health. In this paper, the task of determining the least polluted route is addressed and how this can be used to curb pollution is discussed. The proposed work uses Dijkstra's algorithm, suggests a weight selection metric for air pollution parameters and analyzes the efficacy of the proposed algorithm in determining the least polluted route. The algorithm is tested on real-time data extracted from the Central Pollution Control Board, a statutory organization under the Ministry of Environment, Forest and Climate Change, Government of India. From the results obtained, it is found that the least polluted routes between a given source location and other different locations of a city can be determined using Dijkstra's algorithm accurately and the algorithm has a time complexity of O(V2). Further, using a least polluted route map will help motorists take less polluted routes, diverting air pollution off congested streets and enabling national governments to create policies like constructing flyovers or widening roads in increasingly polluted areas. [ABSTRACT FROM AUTHOR]

The cement industry is undeniably critical for the global economy. However, they are also the largest energy consumers in the world. The clinker manufacturing process causes gaseous emissions like nitrogen oxides, sulfur dioxide, carbon dioxide and particulate matter. There is scope for various technologies to be used in the cement manufacturing process for reducing emissions and energy consumption. This paper presents an analysis of various emission reduction approaches using alternative techniques/raw materials, energy saving (thermal and electrical) methods, process optimization/modifications, carbon capture and storage. However, financial and technical challenges remain significant barriers against sustainability initiatives in the clinker manufacturing process. Practical and feasible methods were applied to reduce nitrogen oxides, carbon dioxide and particulate matter emissions during the clinker manufacturing process. This study also shows the application of pinch technology for more economical energy usage. This study was conducted in the premises of Emami Cement Limited, Balodabazar (Chhattisgarh State), India. [ABSTRACT FROM AUTHOR]

In this paper, we contend that urban middle-class older Indians engaged in "serious leisure" as a way to reimagine and reconfigure the structure of everyday life during the pandemic-led epochal downtime. In particular, we heuristically show that leisure activity patterns and constraint negotiation strategies among older Indians followed conceptual semblances with the dominant leisure-based typology of Serious Leisure Perspective. By thematically analysing household surveys (n = 71), time-use diaries and in-depth interviews (n = 15) of middle to upper middle-class individuals (55–80 years), we show how both men and women distinguished between serious leisure that is marked by motivation, agency and perseverance with that of unstructured, routinized free-time (or causal leisure). Time-use diaries suggested that despite the changed realities of heightened domestic time available to both genders due to the pandemic, women recorded higher proportion of their daily hours in household management and caregiving. Although women were governed by moral-cultural self-descriptions in their engagement with leisure, it was often associated with an enhanced sense of self-actualisation, self-management and identity. Overall, we show how the social codes of age and gender were inextricably linked with the practice of leisure during the pandemic. [ABSTRACT FROM AUTHOR]

Signature is a biometrics trait widely used for personal verification in financial and most other organizations where financial and relevant types of transactions are done manually with signed authorized papers. A signature verification system aims to verify the minor structural differences between genuine and forged signatures, as most skilled forgery signatures look similar to their respective genuine signatures with specific deformations. Signature verification in a multi-cultural country like India is challenging in both writer-independent and script-independent scenarios where the Indian population uses multiple scripts to write their signatures. This paper reports a writer-independent offline signature verification system that uses Convolutional Neural Network (CNN) architecture for feature extraction and classification. The objective of the proposed work is to model a CNN-based adaptable system to verify multi-scripted offline signatures. The model has been trained and tested on two publicly available databases, viz. CEDAR and BH-Sig260, which consist of Hindi, Bengali, and English signatures. Individual signature classes of unique scripts and a combination of these scripts have been considered for testing the proposed model that determines verification accuracies of 90%, 95%, 98.33%, and 93.33%, respectively. Experimental results are compelling, and the proposed model outperforms the verification accuracies of some well-known models. [ABSTRACT FROM AUTHOR]

The use of explosive materials by terrorists for mass killing, creating chaos and producing threat to people initiated the research for developing the techniques and equipments which can detect explosives. Recently a vehicle borne suicide bomber attacked CRPF convoy at Lethpora in Pulwama district in India on 14th February 2019, which killed 40 CRPF personnel. From decades, real-time detection and identification of traces of explosives at a standoff distance has been an ongoing challenge and critical problems in public safety, defense and counter terrorism. A number of methods has been successfully developed and used commercially and by defense which involves fluorescence quenching sensor, colorimetric kits and ion mobility spectrometers. While several methods are under investigation for explosive trace detection. The ideal trace detection of explosives is which can detect traces from a standoff distance and ensures personnel safety. This paper provides study of explosive detection methods, standoff spectroscopy based methods, LIBS and compares the existing methods for trace detection. Also the paper provides review of world's smallest drone made by Israel (Spectrodrone) which can sniff explosives and drugs from 2.8 km. [ABSTRACT FROM AUTHOR]

There is a debate surrounding the nexus between poverty and environmental degradation. While the predominant school of thought argues that poverty is directly responsible for environmental degradation, another school of thought argues that poor do not have the resources which would force them cause environmental degradation. Empirical support for both the arguments, however, is based mostly on macro data. Using micro level data, this paper makes an attempt to examine whether poverty is a factor determining forest degradation in the state of Odisha in India. The study is carried out in two districts, divergent from each other in incidence of poverty, forest coverage and percentage of Scheduled Tribe population. The study finds no empirical evidence that poverty affects degradation of forest. On the other hand, there is evidence of forest degradation with the increase in income, though region specific. Hence, it is non-poor households than poor one who could be responsible for forest degradation. This result therefore does not support the downward spiral hypothesis and questions the assumption that poverty alleviation is an essential part of avoiding forest degradation. However, importance of poverty reduction cannot be overlooked, and effective forest management can be a way to address poverty. [ABSTRACT FROM AUTHOR]

Water contains many chemical constituents, some of which are harmful to human beings. Epidemiological and hydrochemical studies identified those chemical characteristics, and administrators brought out drinking water standards to ensure a safe water supply. Though well-laid down procedures and regulations exist at different levels, people still suffer from scores of waterborne diseases due to violation or non-compliance of such regulations by people engaged in the water supply. Similarly, it can be noticed that inter-disciplinary researchers involved in water chemistry and human health misquote the drinking water standards leading to the propagation of distorted information. Ignorance or lack of complete knowledge on specific fine points about the drinking water specifications (DWS) could cause these inadvertent omissions. Intricacies and fine print of drinking water guidelines/regulations/standards of World Health Organization (WHO) and India are discussed. Discrepancies in using these standards by different user agencies and researchers are illustrated. Ambiguities in the drinking water standards that could confuse are deliberated. The review paper intends to bring to light the shortcomings in the implementation of DWS. It also aimed to encourage scientists and experts to use the information about DWS with absolute care and utilize the latest and genuine DWS obtained from an authentic source. The Paper also emphasizes the necessity for impetus in research on water contamination and adverse effects on human beings in the light of tremendous progress in analytical chemistry and medical sciences. The findings can be used to update the DWS at regular intervals. [ABSTRACT FROM AUTHOR]

Economic recession and global health crisis have surged the public debt levels across nations to an unsustainable level. Debt can be productive provided nation-states utilize it for rapid growth and servicing the cost of loans. It can be unproductive if spent on wasteful expenditure. Thus, a relevant question is—does public debt hinder or promote growth? Reinhart and Rogoff's (American Economic Review, 100: 573–578, 2010) empirical analysis observed a non-linear relation between debt and growth in developed countries. Kaur and Mukherjee's (Reserve Bank of India, Occasional Papers, 33:1–37, 2014) analysis of the Indian economy determined a statistically significant non-linear relationship between debt and growth at state levels. Given this overview, this research examines the temporal and spatial patterns of state debt in India utilizing a statistical analysis. Geographical data are utilized to study state liability in India for 29 states and 2 union territories i.e. National Capital Territory of Delhi and Puducherry. The following three questions are addressed in this paper: (1) what is the relationship between public debt, regional inequality, and development? (2) what are the trends of public debt and regional inequality in India? (3) what are the determinants of outstanding center and state liabilities in India during 1980–81 and 2019–20? Descriptive statistics (dispersion, Gini coefficient, moving averages, and Theil entropy) reveal a declining inequality during each decade as well as considerable inter-state inequality for the period. A time series regression analysis suggests lending rate, GDP growth and trade balance are negatively related to total liability at the center and state levels; net FDI flows, GDP, trade balance, and foreign exchange reserves, are positively related. Prediction maps suggest both the lagging and developed states would incur high public debts, wherein the former would utilize debt for servicing interest cost and non-plan expenditure, and the latter will utilize debt for servicing interest cost and planned expenditure. [ABSTRACT FROM AUTHOR]

Regional disparities are prevalent in almost all nations globally irrespective of whether being developed, developing, or under-developed. With the recent shift of focus towards human development, the presence of inequalities in social development is one of the major issues faced by developing nations and hence becomes the underlying theme of this paper. It attempted to explore the spatial inequalities in the social development of a selected region within and representing Kerala state, India. This research attempted to address the following question: whether a state which has been performing socially well has inequalities present among its regions. A set of relevant variables were shortlisted from a holistic literature review and further screened using various criteria followed by an expert opinion survey. Subsequently, spatial analysis of regional disparities was conducted in two stages. Firstly, a composite index to measure the development of settlements was constructed by adopting the principal component analysis approach. Secondly, the settlements were grouped into three homogenous clusters by k-means cluster analysis and named accordingly. The results revealed that, in terms of reduced inequalities, the settlements performed well in social infrastructure development followed by road infrastructure. At the same time, the performance of the settlements in social characteristics was poor. Significant variations were also found in employment and housing infrastructure development. While the composite index helped compare the development status of settlements, the classification of settlements aided in identifying regions and sectors that were backward in terms of social development. Accordingly, solutions and strategies were proposed for balanced regional development. [ABSTRACT FROM AUTHOR]

An ever-increasing use of pesticides in agricultural fields has led to a catastrophic decline in crop quality and, ultimately soil fertility. To control various pests, quinalphos is commonly used in India's tea plantations. This study aims to investigate the effects of the Quinalphos organophosphate insecticide on the non-target beneficial organism Eudrilus eugeniae earthworms and the biomarkers that respond to its effects. Earthworm species, especially E. eugeniae, remains as the most trustworthy and well-suited model organism for conducting a wide variety of environmental studies. The median lethal concentration (LC50) was identified as 3.561 µg cm−2 (contact filter paper) and 1.054 mg kg−2 (artificial soil toxicity). The 5% and 10% of LC50 value 3.561 µg cm−2 was exposed to earthworm to analyze the sublethal effects at pre-clitellum, clitellum, and post-clitellum segments. Specific enzymatic activities of neurotransmitter enzyme acetylcholinesterase; antioxidant enzymes such as lipid peroxidase, superoxide dismutase, and catalase; and detoxification enzymes including glutathione S transferase, reduced glutathione, carboxylesterase, and Cytochrome P450 were analyzed. Exposure of E. eugeniae earthworm to subacute exposures of pesticides caused significant alterations in these stress markers in a concentration-dependent manner. Morphological abnormalities like bulginess, coiling, and bleeding were observed after exposure of the insecticide treatments. Histological cellular disintegration, a reduced NRRT time, and an inhibited proteolytic zone were also identified in pesticide-exposed earthworms. Studies demonstrate that the organophosphate insecticide quinalphos causes acute toxicity in E. eugeniae; hence, it is suggested that non-target eco-friendly E. eugeniae earthworms may be at risk if exposed to the excessive concentrations of quinalphos organophosphate insecticide in soil. [ABSTRACT FROM AUTHOR]

All landscapes, including estuarine islands, normally try to restore their geomorphic isostasy in all anthropogenic interventions on land dynamics. Munroe Island has been experiencing drastic environmental degradation, such as land subsidence, severe tidal/monsoon flooding, subsidence of build-ups and a drastic decay in agricultural productivity. This paper examines the role of anthropo-geomorphic interventions causing for the land degradation in Munroe Island through a multidisciplinary approach. Multidated, multiresolution satellite products and published maps, spanning a period of about six decades from 1960 to 2021, were used to understand the different geomorphic and geographical processes in the study area. Evaluation of the temporal bathymetric datasets, salinity measurements of the river and estuary, borehole data logs of the area and electrical resistivity surveys of the island were analyzed to find out the causative factors for the disturbances in the land neutrality, along with the tidal hydrodynamic changes in the region. The study shows about 14% of the total land area was vanished during the study period, and more than 25% of the area is under stress, leading to further land degradation. More than 500 households are forced to vacate their residence due to land subsidence/flooding. Lack of required freshwater and sediment supply from the Kallada river after the construction of the Thenmala reservoir in the Kallada river as well as the uncontrolled sand mining prevailed are the key factors for the environmental degradation of Munroe Island. The paper describes the role and colinkages of human-induced hydrogeomorphic interventions on a geomorphic system, in charge of the environmental degradation and land subsidence crisis of an estuarine island ecosystem and discusses the concerns related to the management strategies of such region. [ABSTRACT FROM AUTHOR]

This study estimates the contribution of gendered social norms in explaining the gender gap in productivity of unorganised manufacturing firms. Restrictions on mobility and burden of household work mean that female firm-owners primarily operate from their household premises. Using data from unorganised firms operating in the manufacturing sector in India, this paper finds gender gap in firm productivity. The Blinder-Oaxaca decomposition at mean show that despite controlling for size of the firm, assets and other conventional factors, the location of a female proprietary firm within the household premises of the owner explains 19% of the observed gender gap in productivity. The RIF decomposition results show that at the different quartiles, this contribution varies from 19 to 36% of the composition effect. The evidence suggests that the persistence of the gender gap in firm productivity is associated with the persistence of gendered social norms. Plain English Summary: Almost 95% of female owned firms in the unorganised manufacturing sector in India operate from within the household premises, due to prevalent gendered social norms. These norms put the responsibility of unpaid household work solely on women and impose mobility restrictions. This paper examines whether restrictive social norms contribute towards the gender gap in firm productivity. I find that that the location of these firms within the household restricts them from expanding, as well as contribute to prevalent the gender gap in productivity and incomes generated from proprietary firms operating in the unorganised manufacturing sector. Newer policies supporting women's mobility and paid work that supplement conventional policies to improve entrepreneurship are required. However, as social norms involve coordinated actions and fear of sanction in case of noncompliance, these policies would work effectively if they are targeted towards both genders and entire neighbourhoods. [ABSTRACT FROM AUTHOR]

A court of a country is the main source of justice, to the respective country's citizens. Every individual approaches courts to seek justice when his/her rights are violated. The main power house of these courts is the supreme court and each country has its own respective supreme court, in a country like India with a huge population every day hundreds and hundreds of new and appeal cases have been filed to the supreme court and seek justice. The objective of this paper is to classify the cases and to predict the behavior of the court (whether the appeal case will be accepted or dismissed by the Supreme Court). This paper gives the individual an ideology about how the case will be taken and treated by the court. The model considers past 20 years of cases from the Supreme Court of India database containing all types of cases to predict leave granted and Disposed off parameters. The proposed model is tested as three modules (i) classification module (ii) prediction module and (iii) baseline module and also compares various ML algorithms using Accuracy and F-measure as performance metrics. [ABSTRACT FROM AUTHOR]

Energy and waste management sectors are considered important for the country's progress towards adopting sustainable consumption and production (SCP) practices and achieving Sustainable Development Goals. However, the rapid pace of urbanization, energy-intensive growth approaches, and generation of large quantities of waste have led to severe environmental degradation of cities in India. While the government has taken several initiatives for increasing resource efficiency, limited research has been done in an Indian context to explore the policy and institutional factors. The paper focuses on challenges relating to policy enablers within the energy management in buildings and construction and demolition waste sectors; 28 semi-structured interviews were conducted with stakeholders associated with both these sectors. The findings indicate that though India has been integrating climate change measures into its national policies and enhancing the domestic market's readiness for a circular economy, successful implementation of policy framework(s) urgently requires lifestyle and behavioural changes in the society. The study further identified the role of key stakeholders including government, businesses, and consumers, for transition to a low-carbon economy for both these sectors. This paper presents a bottom-up approach to understand the changes required in the enabling environment for the uptake of SCP practices that can be adapted by other emerging economies in the Asia Pacific region for building resource efficiency. The importance of soft factors relating to institutional capacities and governance structure is raised by the analysis in this paper. [ABSTRACT FROM AUTHOR]

While the extant literature suggests that an individual's occupational choice depends on the level of economic development, little is known about how the dynamics of education and social identity impact self-employment choice over time in a developing country setting. The pseudo-panel regression results presented here suggest that higher education decreases the likelihood of individuals' choice of self-employment over time in India, but increases it in most developed cohorts. Such transitional dynamics are more prominent amongst individuals who belong to historically determined backward classes. Furthermore, the results suggest sectoral differences in self-employment choice—individuals with higher education and wealth have a greater likelihood of transiting into self-employment over time in agriculture while similar individuals in non-agriculture exit self-employment. In both sectors, however, education moderates the impact of social identity on self-employment choice. The paper underscores the need for policy shifts towards entrepreneurship along the path of economic development. Plain English Summary: University education helps overcome social barriers to self-employment in India. While it reduces the transition into self-employment over time, educated individuals are more likely to move back into self-employment in the most developed cohorts. We examine the occupational dynamics over ten years using large-scale databases by tracking self-employment in cohorts of individuals across India. The results suggest that university education enables individuals from socially backward classes to overcome barriers to self-employment in both non-agricultural and agricultural sectors. Although university education decreases the likelihood of self-employment over time, it increases self-employment in the most developed cohorts. The paper suggests that public policy should focus on facilitating industrial development in the initial stages of development as individuals are motivated to invest in professional human capital during these periods while encouraging entrepreneurial activities when a more developed economy can provide opportunities for greater returns in self-employment. [ABSTRACT FROM AUTHOR]

The road is the most commonly used means of transportation and serves as a country's arteries, so it is extremely important to keep the roads in good condition. Potholes that happen to appear in the road must be repaired to keep the road in good condition. Spotting potholes on the road is difficult, especially in a country like India where roads stretch millions of kilometres across the country. Therefore, there is a need to automate the identification of potholes with high speed and real-time precision. YOLOX is an object detection algorithm and our main goal of this article is to train and analyse the YOLOX model for pothole detection. The YOLOX model is trained with a pothole dataset and the results obtained are analysed by calculating the accuracy, recall and size of the model which is then compared to other YOLO algorithms. The experimental results in this article show that the YOLOX-Nano model predicts potholes with higher accuracy compared to other models while having low computational costs. We were able to achieve an Average Precision (AP) value of 85.6% from training the model and the total size of the model is 7.22 MB. The pothole detection capabilities of the newly developed YOLOX algorithm have never been tested before and this paper is one of the first to detect potholes using the YOLOX object detection algorithm. The research conducted in this paper will help reduce costs and increase the speed of pothole identification and will be of great help in road maintenance. [ABSTRACT FROM AUTHOR]

This paper introduces Development Led Inquiry (DLI) as an approach to improve situations incorporating relationships between third sector organisations (TSOs) and agricultural scientists, universities, and the public-sector agricultural establishment. There is limited scholarly work on the role of TSOs in agricultural research. Current approaches appear premised on TSOs being researched upon, and recipients of research outcomes rather than partners in generation and application of new knowledge. DLI expands the boundaries of research systems and roles of TSOs as supporters within them. DLI builds on partnerships between NGOs, farmers' organisations, and women's associations; it integrates researchers and research organisations to develop, manage and report knowledge generation and application. DLI is dynamic and developmental with learning for all participants central to the process. DLI unsettles current power structures within research systems and sees research and knowledge generation as a supporter rather than leader of development. DLI is embedded in an inquiring systems approach and applies six interrelated conceptual systems thinking tools. The approach emerged from, and was applied in, a twelve-year agricultural research project in India, and was subsequently introduced to, and further developed in a research project in Pakistan. [ABSTRACT FROM AUTHOR]

Hearing impairment is most frequent sensory deficit present in infants at birth and unaddressed hearing impairment causes severe damages to both infants and their families. In India 77,756 live children are born per day which accounts for about 25 million children annually among them approximately 1.5 lacs (@ 6 per1000) children born with hearing impairment. These children have no prospects of early identification & intervention. As a result, majority of these children suffers from oral communication difficulties, poor academic performance, reduced psychosocial & cognitive development, socioeconomic insufficiency, deprived vocational opportunities & employability. However, consequences of hearing impairment are ameliorable if timely hearing screening and effective intervention strategies are instituted. Unfortunately, India has not yet envisaged any dedicated early identification and intervention program for children with hearing impairment. However, there are ample of opportunities for implementing such program. Hence, this paper endeavours to address the necessity to plan and to implement the early identification of hearing impairment by discussing burden of disorder, suggesting means to overcome the challenges and to explore and emphasize the opportunities of purposeful utilization of available infrastructure and resources. This paper also intends to suggest a conceptual framework for planning and implementing of National Infant Screening for Hearing Program to deal with serious consequences of hearing impairment in India. [ABSTRACT FROM AUTHOR]

Even after scavenging the existence of mankind for the past year, the wrath of CoVID-19 is yet to die down. Countries like India are still getting haunted by the devastating conundrum, with coronavirus ripping through its citizens in the concurrent second wave. The surge of cases has prompted rapid intervention, with medical authorities pushing it to the limit to curve a roadblock to its aggressive growth. But, even after effortless work, human intervention remains slow and insufficient. Furthermore, relevant testing methodologies have shown weakness while detecting threats, with the recent growth of post-Covid complexities, thereby leaving a painful mark. This as such created a major requirement for technological advancements, which can cater to the mass. The growth of computational prowess in the past decade made the field of Deep Learning a major contributor in curving out algorithms to solve this. Adding to the excellent foundation of Deep Learning, this paper, proposes a novel CoWarriorNet model for rapid detection of CoVID-19, via chest X-ray images, which adds in an extra layer of precision and confirmation in the detection of cases in both pre-Covid and post-Covid conditions. The proposed classification model curves out an excellent accuracy of 97.8%, with the major eye-candy being the sensitivity rate of 0.99 when detecting CoVID-19 cases. This model introduces a new concept of Alpha Trimmed Average Pooling, which along with the novel architecture adds a subtle touch to its high efficiency, thereby giving a much-needed solution to the medical experts. The two-mouthed architecture provides the added benefit of a confidence score, deducing human aid in case of discrepancy. [ABSTRACT FROM AUTHOR]

The Covid pandemic has become a serious public health challenge for people across India and other nations. Nowadays, people rely on the online reviews being shared on different review sites to gather information about hospitals like the availability of beds, availability of ventilators, etc. However, since these reviews are large in number and are unstructured, patients struggle to get accurate and reliable information about the hospitals, due to which they end up taking admission into a hospital which might not be appropriate for the specific treatment they require. This paper employs the use of sentiment analysis to understand various online reviews of hospitals and provide valuable information to the patients. Approximately 30,000 + reviews were collected from more than 500 hospitals. The broad objective of the study is to give the patients a comprehensive and descriptive rating of the hospitals based on the online reviews given by different patients. In addition to providing a comprehensive summary, the study has conducted aspect-based analysis where it compares the hospitals based on four different aspects of the hospital viz. "Doctors' services", "Staff's services", "Hospital facilities", and "Affordability". The database containing aspect-based ratings of the hospitals will be of great value to the patients by allowing them to compare and select the best hospital based on the optimum fit of the aspects of their preference. [ABSTRACT FROM AUTHOR]

The present study explored district-wise monthly rainfall of two climatic regimes (1960–1990 and 1991–2020) of the West Bengal state of India, which receives an annual rainfall of about 1500 mm with huge seasonal rainfall variability. A simple time series analysis does not show any noticeable trend. However, decomposing rainfall parameters into several indicators may explore the change. From this perspective, the present paper intends to explore the nature, degree, and direction of rainfall alteration. The range of variability approach (RVA) considered 29 indicators was adopted for unveiling it. RVA explored that in the 1991–2017 phase, the rainfall failure rate above the upper threshold (75th percentile) is 33% which is 10% greater than in 1961–1990. Seasonal variation in failure rate was detected, but overall larger area of the state recorded failure rate (FR) above the threshold. This result leads to increasing wetness conditions. Very low to moderate (< 0.4) degree of impact of rainfall alteration (DIRA) was found in the recent period. The areal occupation of moderate DIRA was considerable in pre-monsoon, post-monsoon, and winter seasons. Time series rainfall data-based flow duration curves (FDCs) indicated the dominance of the eco-surplus rainfall state over greater parts of the state (72–84%) in all the seasons except winter (49%). Such surplus rainfall may be beneficial to the ecological and agricultural perspective of the state. [ABSTRACT FROM AUTHOR]

Servant leadership has emerged as a novel area of Management research. One of the most debated leadership styles is servant leadership, which indicates that a person must first be a human and then a leader. This literature review comprehensively examines the historical origins of servant leadership, its core attributes, the measurements that have been developed, and the findings obtained from pertinent empirical investigations. The primary objective of the present paper is to study the leadership style using various analyses, evaluations, and research from available sources to identify proposed facts about leadership activities using bibliometric analysis of servant leadership theory. [ABSTRACT FROM AUTHOR]

In this paper, we examine how religious mandates of the holy month of Ramadan affect the gendered distribution of time use within Muslim households in India. Using rich data on time use from a nationally representative time use survey and employing a difference-in-differences methodology, we test if Ramadan accentuates gender differences in time use. We find that, contrary to popular belief, Ramadan moderates the gender disparities in intra-household time use for Muslim households. The moderating influence is stronger in districts with a higher Muslim proportion. We find that the reduction in gender differences is due to declines in gender-specific time use in employment, learning activities, domestic work and self-care. Reduction in domestic work time for women, especially food preparation time, is more pronounced in districts with a high Muslim proportion, suggesting 'communalisation of domestic work' due to Ramadan. [ABSTRACT FROM AUTHOR]

Reports that the Indian government has been asked by the Indian Department of Science and Technology to re-examine a 30-year-old policy banning the publication of Indian editions of foreign science and technology periodicals in order to protect local publishers. Opinion poll to be carried out; Opposing views.

Diabetes is one of the most prevalent non-communicable diseases and is the 6th leading cause of death worldwide. It's a chronic metabolic disorder which has no cure, however, it is a highly treatable condition, if diagnosed and managed on time to avoid its complications. This paper explores and compares various machine learning (ML) approaches that can help in determining the risk of diabetes at an early stage and aid in improving the medical diagnosis of diabetes. The paper considers two real-world datasets one is a diabetic clinical dataset (DCA) collected from a medical practitioner in the state of Assam, India during the year 2017–2018 and other is public PIMA Indian diabetic dataset. To analyze the various machine learning techniques on DCA and PIMA Indian diabetic datasets for the classification of diabetic and non-diabetic patients, different classifiers like perceptron, Gaussian process, linear discriminant analysis, quadratic discriminant analysis, statistical gradient descent, ridge regression classifier, support vector machines, k-nearest neighbors, decision tree, naïve Bayes, logistic regression, random forest and ELM for multiquadric, RBF, sigmoid activation functions are used. The results of numerical experiments suggested that logistic regression yields better performance in comparison to the other techniques. [ABSTRACT FROM AUTHOR]

A comprehensive and satisfying route- guidance system is considered valuable for citizens and tourists worldwide. An effective route-guidance system is essential because of the sophisticated city formation and transportation system in India. For better utilization of route-guidance systems. It needs to be easy to use and informational but to be more sensible to give optimal route options in terms of low cost and low time in various situations (Such as climate conditions, traffic jam, road structure). This paper aims to comprehend the research trend in the route guidance system and easily observe the various technique of route guidance. Different impressive findings have come out of this study, supporting current and future researchers to evaluate and set their research roadmap. This paper also explains the existing approaches for route guidance systems in simple language, which will be fruitful for researchers. Furthermore, this paper also envisions the future of RGs, which may open up new research directions in this domain. [ABSTRACT FROM AUTHOR]

Waste foundry sand (WFS) is the by-product of the foundry industry, which is produced about 0.6 tons per 1 ton of foundry industry production. While it cannot be recycled or reused, it will be disposed of in landfills. Today, with increasing attention to environmental issues, the reuse and recycle of materials because of limited resources have been considered. Due to the desirable properties of WFS, many studies have been done on the properties and performance of its use in various industries, especially in concrete technology. The purpose of this paper is to conduct a bibliometric analysis of foundry sand research during the years 1971-2020. Various aspects, such as document types, languages, major journals, key countries, authors, and keywords, have been examined. The collaborations among authors and countries were constructed, visualized, and evaluated through the application of the social network analysis method based on co-authorship relations. Also, keyword cluster analysis has been performed using co-occurrence relations to discover the most prominent issues related to WFS. The results showed that the number of publications (TP) has improved significantly in recent years, especially in 2018-2020. It has increased from 1 in 1971 to 38 in 2020. The engineering subdivision with 33% has had the highest number of papers. Also, India, China, and the USA have the highest number of publications, respectively. Statistical data from the author keyword study showed that in general, papers can be classified into three categories in terms of subject: first, characteristics of WFS and its importance; second, the use of WFS in concrete and the study of mechanical and physical properties as one of its applications; and the third, investigation on environmental effects and damage caused by disposal and landfill of WFS and efforts to find solutions for recycling and reuse. The keywords "Waste Foundry Sand," "Foundry Sand," and "Compressive Strength" with a growth rate of 2700%, 1900%, and 1100%, respectively, are important topics in the field of WFS research. [ABSTRACT FROM AUTHOR]

The paper pertains to the studies carried out on the eclogitic xenoliths of KL-2 kimberlite of Kalyandurg kimberlite cluster in south India. Petrographic studies revealed bi-mineralic and kyanite-bearing eclogitic xenoliths in KL-2 kimberlite. The bimineralic and kyanite-bearing eclogites of Kalyandurg KL-2 kimberlite pipe show variation in modal proportion of garnet, omphacite, clinopyroxene and kyanite. The paper reports discovery of native gold grains and Au-Pt alloy in the kyanite-bearing eclogite xenoliths of KL-2 kimberlite. The flaky gold grains occurring in the matrix of kyanite-bearing eclogite are homogeneous and two grains of Au-Pt alloy with Au and Pt in the proportion of 9.8:1.2 are also present. This is the first report of gold and gold-platinum alloy specs from eclogitic xenoliths of Indian kimberlites. [ABSTRACT FROM AUTHOR]

Moebius Syndrome is a rare congenital neurological condition characterized by paralysis of several cranial nerves, commonly the VI(Abducens) and VII(Facial) cranial nerves which causes lateral gaze strabismus and internal strabismus & classical mask like appearance respectively. Other cranial nerves such as V, VII, IX, X, XI, XII are rarely affected. Von Graefe and German neurologist Moebius (1888), after whom the syndrome was eventually named, provided the earliest descriptions of it. Although the etiopathogenesis is unknown, it appears to occur sporadically in the majority of cases, and some documented cases show hereditary predisposition. This paper presents a rare instance of trigeminal neuralgia associated with Moebius syndrome. According to the author's research, this is the first case of Poland Moebius syndrome with trigeminal neuralgia documented from India. [ABSTRACT FROM AUTHOR]

While India is entering the period of demographic dividend, female labour participation rates remain very low. This paper aims to provide the very first labour force projections for India and its regions up to the year 2060. Projections are achieved using a discrete-time microsimulation model in which changes in population size and composition come from the interaction between demographic characteristics, educational attainment, and secular tendencies. Labour force participation rates are estimated at the individual level using personal characteristics as predictors. Results show that under constant labour force participation rates, the labour force dependency ratio (non-workers/workers) is very unlikely to attain favourable levels, which compromises the potential demographic dividend that the country could gain from its favourable age-structure. At the subnational level, the forecast yields the most favourable dependency ratio in 2060 in the regions that combine both a low-age dependency ratio and a higher participation of women. Results moreover suggest that female labour force participation is a better driver of the labour force dependency ratio than the age composition. [ABSTRACT FROM AUTHOR]

Over the past decade, extensive research on stock market prediction using machine learning models has been conducted. In this framework, different approaches for data standardisation methods have been used for financial time series analysis and to assess the impact of data standardisation on the final prediction outcome. The paper uses the feature-level optimal rolling-window batch data standardisation method to improve the machine learning model's predictive power significantly. Along with the standardisation method, the paper explores the performance of the automated feature interactions learner (Deep Cross Networks) effect on a plethora of technical indicators aiming at predicting the movements of the NIFTY50 index in India, as these predicted changes are reflected in options contracts. Feature-level optimal rolling window data standardisation can identify the optimal window of time such that the correlation between features and the response variable is maximized, with most features correlating at 0.7. In the experiment, 48% of important technical indicators negatively correlated with the response variable. The Deep Cross Network regression model combined with the optimal rolling window batch data standardisation method outperformed all other model configurations at weekly and monthly data frequency. It achieved a directional hit rate of 69.52% (weekly) and 79.17% (monthly) and root mean square error of 2.82 (weekly) and 5.01 (monthly), generating a profit 5.5 times (weekly) and 2.85 times (monthly) greater than the benchmark buy-and-hold strategy providing opposing evidence to the sub-martingale model. [ABSTRACT FROM AUTHOR]

This paper compares the Cīvaravastu of the Mūlasarvāstivāda Vinaya with its counterparts in the other four Sthavira Vinayas, namely the Cīvarakkhandhaka/Cīvaradharma[ka] sections of the Vinayas of the Theravādins, Dharmaguptakas, Mahīśāsakas and Sarvāstivādins. It demonstrates that a significant number of stories and rules in the Cīvaravastu have no parallel in the other Sthavira Vinayas. Even those stories and rules that have parallels or partial parallels in the other Sthavira Vinayas can still offer us glimpses into the distinctive concerns of the Mūlasarvāstivādin jurists who wrote or redacted this text. Based on three comparative tables and two examples, this paper argues that the Mūlasarvāstivādin authors/redactors of the Cīvaravastu, contrasted with the jurists of other Sthavira sects or schools, displayed at least five characteristics. First, they shared some common narrative lore with the Śvetāmbara Jainas, which is not found in the other Sthavira Vinayas. Second, they showed a stronger predilection for including past-life stories. Third, they repeatedly used the learned-but-greedy monk Upananda to create comic effect. Fourth, they were strongly and explicitly concerned with a wider range of legal issues related to Buddhist monastic inheritance, and came up with detailed solutions to such issues. Fifth, they showed a more acute awareness of the connection between monastic clothing and public image, as well as the need for thoroughly differentiating the appearance of Buddhist monks from that of other religious groups in ancient India. [ABSTRACT FROM AUTHOR]

The recent United Nations Educational, Scientific and Cultural Organization (UNESCO) survey states that India has 197 endangered languages. Himachal Pradesh, a state in India, has topped the list with seven definitely endangered languages, and Kinnauri-Pahari being the one. Due to the lack of availability of digitized resources, the corpus compilation is a bit difficult. This paper presents and releases the Kinnauri-Pahari (ISO-639-3:kjo) dataset, consisting of the 43,362 Monolingual and 20,307 Parallel sentences in version_0.1. The dataset was tested on the Statistical, and Neural Machine Translation and their results were evaluated using different evaluation metrics. The corpus is freely available for non-commercial usage and research (https://github.com/phildani7/dlnith/tree/master/Kinnauri-Pahari). [ABSTRACT FROM AUTHOR]

India has approximately 23 million children without parental care, who need alternative forms of care (MOSPI, 2018). Udayan Care, an NGO, designed an innovative group care model for children and youth in need of care and protection, implementing the indigenously developed LIFE (Living in Family Environment) strategy in 17 Udayan Ghars. (Sunshine Homes). With child participation as a core pillar, Udayan Care developed a Questionnaire to Assess the Needs of Children in Care (QANCC) in 2011, which is to be filled up by children annually, as a longitudinal study. The tool is conceived to ascertain whether children in the Ghars perceived if their rights were being fulfilled and that their needs were being addressed. With "meaningful participation" of children stipulated by the United Nations Convention on the Rights of the Child (UNCRC), the objective was to develop an evidence-based tool to assess the views of children on the services meted out to them, from their standpoint, and inform actual care practices annually. The self-assessment tool consists of questions, assessing the four dimensions of basic/fundamental, emotional, educational, and interpersonal needs, on a four-point Likert rating scale. A convenient purposive sampling is done on children, aged 10 to 18 years, who receive care and protection at the Ghars, and have resided there for a minimum of 6 months. This paper has two objectives, where at one end, the deductions of the previous years' data are made (2011–12 to 2016–17) with demarcating the differences with year 2018–19 data and at the second level, there is an update on the efforts made to establish the reliability and validity of the tool and create a standardized tool that can be implemented by other child care organizations in India. The paper illustrates how listening to direct voices of children and incorporating their inputs into actual care practice, can go a long way in improving the holistic wellness of children living in an alternative care setting. The results indicate that all needs of the majority of the children in Udayan Ghars. [ABSTRACT FROM AUTHOR]

There is growing evidence of ride-hailing platforms' adverse impact on drivers. Nonetheless, hundreds of thousands of drivers continue to work on these platforms. Why? The key contribution of this paper is to show that workers in technology-mediated labour markets come to be increasingly dependent on the technology-provider in order to connect with the customers. As more and more customers choose to get various tasks done via intermediary platforms, for workers who perform such tasks for a living, this translates into growing dependencies on these infrastructuralized platforms for their livelihoods and thus increased vulnerabilities to the impact of platform design and policies. These 'new dependencies', therefore, make it critical for us not to conflate workers' continued use of platforms with their experiencing benefits. By drawing upon a qualitative study with auto-rickshaw drivers using Ola, a ride-hailing platform similar to Uber in India, the paper shows that a consequence of 'new dependencies' for drivers is that they are stuck 'between a rock and a hard place' whereby: a) on the one hand, the platform design heightens their precarity, provides them with little benefit, and often leads to tensions with customers, b) on the other, a shift of more and more customers from street-hailing to app-based hailing over time exacerbates dependencies for drivers on these very platforms, leaving them with little choice but to continue to use them for work. [ABSTRACT FROM AUTHOR]

The horrifying and fast spreading COVID-19 pandemic has shocked India and in fact the entire world to its core. Indian Government has taken all the possible preventive steps to contain the wider spread of this highly contagious disease but the second wave in the month of April, 2021 has turned this strong country in a helpless position. In this paper, the effect of environmental factors like temperature and air quality index on the new confirmed cases along with recovered cases has been seen in Bengaluru Urban district of Karnataka State of India. Regression analysis has been carried out with the help of SPSS software. The outcomes from the paper will definitely give some valuable insights for the researchers around the world in their future combat measures. [ABSTRACT FROM AUTHOR]

It has been found that people with disabilities remain at the margin as far as the different aspects of their lives are concerned. This paper tests the hypothesis that disability leads to lower quality of life among older adults in low and middle-income countries. The data from the Study on Global Ageing and Adult Health (SAGE) was used in this study which was conducted in Ghana, China, India, Russia, South Africa and Mexico. The disability scores have been made utilising Item Response Theory, Partial Credit Model and are centered on eight functioning and health areas. Bivariate analysis, binary logistic regression and pooled regression analysis have been used to fulfil the objectives of the paper. The findings reveal that disability acts as a hindrance in attaining a high quality of life (HQOL) amongst the older adults in the above mentioned low and middle-income countries. The older adults with disability are as much as 60% less likely to enjoy an HQOL with respect to the older adults without disability. Better socio-economic development like improved health care for disabled older adults with disability enhanced living standards for both abled and disabled, efficient pension schemes for older adults with disability and effective social service schemes would be very much essential to improve overall QOL among older adults. [ABSTRACT FROM AUTHOR]