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Abstract Indian pulp and paper industry is one of the fastest emerging business sector of the country which has shown tremendous growth in last few years. Governments policies are creating sustain pressure on paper industries to preserve the clean and pollution free environment at any price. As a result industries are pondering to replace the chemical bleaching processes with facile bio-based cost effective technologies. Eco-friendly bleaching enzymes like xylanases and laccases have the potential for biobleaching of wood and agro-based pulps at industrial scale. In India, enzymatic prebleaching of pulp is widely being investigated and has achieved favorable outcomes but at laboratory scales only and commercial application of enzymes for the delignification of pulp is still at budding stage. This article tends to draw the attention on significant efforts which have been continually attributed by indigenous research laboratories and industries to replace the chemical bleaching with enzymes. [ABSTRACT FROM AUTHOR]

Indigenous communities and their way of life are facing significant challenges due to globalisation, industrialisation and urbanisation, which have forced them to gradually adopt the architecture, lifestyle, and culture of mainstream society. This paper proposes a Smart Vernacular Architecture (SVA) framework and applies it to the indigenous dwellings of the Todas, a tribal community living in India's Nilgiri mountains. The architecture and indoor space quality of these dwellings are investigated in this paper based on specific thermal comfort parameters like the interior temperature and airflow. The indoor temperatures of Toda dwellings are simulated for the predicted climate of 2100 to evaluate their climate resilience. Finally, the paper illustrates the usage of virtual reality (VR) to explore and visualise the Toda settlement and the interior environment parameters of a Toda dwelling to effectively convey and preserve the knowledge of vernacular architecture. In a nutshell, this paper elucidates the advantages of vernacular architecture and construction methods to arouse the interest of academics, policymakers, students, and professionals in preserving architecture, culture, and indigenous knowledge. [ABSTRACT FROM AUTHOR]

Fungal diseases are a serious threat to Eucalyptus spp., which are cultivated worldwide for pulp and paper. Robust and timely detection of Eucalyptus pathogens is thus a crucial step in disease prevention and control. In 2022 , leaf spots were observed on Eucalyptus trees in Karnal, northern India. Fungal isolates displaying morphological characteristics similar to Neofusicoccum mangiferae were consistently recovered from the infected leaves. The morphological identification was validated by phylogenetic analysis employing internal transcribed spacer (ITS), partial translation elongation factor-1α (tef1) and partial β-tubulin (tub2) regions. Finally, Koch's postulates for N. mangiferae as a foliar pathogen of Eucalyptus were fulfilled. This is the first confirmed report of N. mangiferae affecting Eucalyptus trees in India. [Display omitted] • This study first time reports Neofusicoccum mangiferae as a foliar pathogen of Eucalyptus in India. • The pathogen was identified based on microscopic features, multilocus phylogenetic analysis and pathogenicity tests. • This is a new taxonomic addition to the diversity of Botryosphaeriaceae affecting Eucalyptus in India. • This study provides future directions to decipher the diversity of Neofusicoccum spp., their host range and testing of Eucalyptus germplasm for disease-resistance. [ABSTRACT FROM AUTHOR]

This paper describes the monitoring and evaluation of three improved cookstove dissemination projects implemented between 2004 and 2006 by non-governmental organizations (NGOs) in India and Mexico. The projects assessed stove performance using lab-based water boiling tests (WBTs), which yield a number of performance indicators including time to boil water, specific fuel consumption, and energy efficiency when the stove is operated at both high and low power output. They also conducted field-based kitchen performance tests (KPTs), which yield daily per capita fuel consumption in real cooking conditions. In addition, one NGO utilized a controlled cooking test, which combined elements of lab- and field-based tests. In all cases, improved cookstoves (ICSs) were compared to local traditional cookstoves (TCSs). The results of the WBTs were mixed. Although the improved stoves generally showed some improvement in efficiency for the low-power simmering phases, the stoves were less efficient than traditional stoves in high-power water-boiling phases. The results from the KPTs were much less ambiguous. Three ICS models were tested for fuel consumption during real household use. All ICSs showed statistically significant reductions (p < 0.05) in average daily per capita fuel use ranging from 19 to 67%. We also explore the correlations between the outcomes in lab-based tests and field-based tests in order to understand the relationships between the two assessment methods. Only fuel consumption in the low-power phase of the WBT showed a strong correlation with fuel consumption in the field (r2 = 0.83, p = 0.01). We discuss the implications of this association as well as the other outcomes and present some policy recommendations for monitoring and evaluation of large-scale stove interventions. [Copyright &y& Elsevier]

Summary: Objective: Aim of the study was to determine the prevalence of Acanthosis Nigricans (AN) in a central Kerala south Indian population and to evaluate its correlations with diabetes, obesity, insulin levels and other factors. Methods: A cross-sectional community survey including physical examination and biochemical evaluation was conducted among adults above the age of 18 years in central Kerala In the first phase of the study 3069 participants were surveyed using questionnaires regarding socioeconomic status and medical details. Among them 986 subjects were evaluated in the second phase of the study which included anthropometric measurements, examination for blood pressure and Acanthosis Nigricans, blood tests such as blood glucose, fasting lipids. Fasting serum insulin level was measured for all non-diabetic subjects. Statistical analysis was done using SPSS 11.0 version software. Results: Results of the study showed that 16.1% of population had AN and it was significantly higher among females (19.6%) than males (11.4%). Prevalence of AN was highest in 30–40 year age group and it decreased with the age. Prevalence of AN correlated positively with female gender, obesity, high triglyceride levels and presence of diabetes. Presence of AN was significantly associated with higher fasting insulin levels. Males with AN had significantly higher insulin values than females with AN. Conclusion: AN has stronger clinical relevance among males than females and it can be used as a marker of insulin resistance in south Indian population especially if obesity and family history of diabetes are also present. [Copyright &y& Elsevier]

Using a discounted cash flow methodology, we have performed a detailed analysis of the current costs of electricity from two Indian nuclear reactors. We compare these costs to that from a recently constructed coal-based thermal power plant of similar size. Our results show that for realistic values of the discount rate, electricity from coal-based thermal power stations is cheaper than nuclear energy. [Copyright &y& Elsevier]

The women-energy nexus involves the challenge of engendering energy and the challenge of empowering women through energy. The first challenge arises from the gender disaggregation of energy consumption patterns. A quantitative account of the share of women in these patterns is presented through a description of the rural energy consumption pattern of the village of Pura in South India. The results indicate that women work more hours than men. Women also perform the back-breaking tasks and are displaced by agricultural mechanisation. The energy output-input imbalance is aggravated by the fact that, in developing countries, women traditionally eat last and least in a family – women therefore take in less food energy than men. The gender distribution of labour results in negative health impacts. The scarcity of energy services in rural areas has serious social and gender impacts. Tackling them requires energy interventions to improve the quality of life for women. Examples of such energy interventions are the community biogas plant at the village of Pura and the multi-purpose platforms of the Mali project. Since technological opportunities exist for such energy interventions, attention is turned to the second challenge of empowering women through energy entrepreneur ship. This requires a change of mind-set on the part of energy planners and activists – they must promote the notion of women as managers and entrepreneurs, and not just beneficiaries, of improved energy services. The idea is to push the following sequence: women as deprived in energy consumption patterns → women as beneficiaries of energy interventions → women as managers of enterprises → women as energy entrepreneurs. This is nothing short of a paradigm shift – but once achieved and implemented, the results will speak for themselves. Such an approach will engender energy by converting it into a force for improving the quality of life as well as enhancing productive capacities – a virtuous circle of energy for women and women for energy. [Copyright &y& Elsevier]

Oral submucous fibrosis (OSF) affecting populations is considered a public health issue in South/Southeast Asia. The purpose of this study was to analyze the scientometric characteristics and research trends of OSF. All the papers on OSF were comprehensively retrieved from the Scopus database. Regional comparison (India versus outside of India) and chronological comparison (before 2015 versus after 2015) were performed. Among all the 1357 papers on OSF, 930 (68.5%) were from India. In India, biology research on antioxidant, oxidative stress, angiogenesis, and extracellular matrix were distinctive keywords. Risk factors of smokeless tobacco and gutkha and the roles of saliva and blood sampling were also distinctive keywords in India. In outside of India, biology research on myofibroblast, alpha smooth muscle actin, microRNA, long untranslated RNA, and protein p53 were distinctive keywords. The trend of biology research on connective tissue, genotype, genetic predisposition, messenger RNA, and cytology before 2015 has changed to research on myofibroblast, biological marker, microRNA, epithelial mesenchymal transition, extracellular matrix, and oxidative stress after 2015. The trend of clinical aspects of surgery and mouth hygiene before 2015 has changed to the aspects of adverse event/effects, complication, and quality of life after 2015. This scientometric study elucidated the current scenario and research trends of OSF, and would help in improving in reciprocal collaboration and communication for this disease control in South/Southeast Asia. [ABSTRACT FROM AUTHOR]

This paper foregrounds the work of the labourer in infrastructural projects. It draws upon over 6 years of ethnographic study with road construction labourers in the upper Himalayas positioning them as subaltern subjects within discourses of national development. While the subaltern studies project of the 1980s emphasized the 'writing back into history' of the non-elite, primarily peasants, tribal populations and women who too contributed to the imagination of the nation; at the contemporary moment where infrastructure defines national development we need to revisit the subaltern project to draw attention to the forgotten labourers who literally construct the nation and its infrastructure. After arguing for recognition of the labour as intrinsic to infrastructural and national constructions, I discuss possibilities for a dialogic engagement with the subaltern. Pushing the debates within subaltern geographies on the politics of representation, I argue that perhaps the way forward is not about giving voice but about making space. [ABSTRACT FROM AUTHOR]

The article discusses the airway pressure for infants with meconium aspiration syndrome which includes mechanical ventilation and medical care .

Blueprint provides a base for assessment by assigning proportionate weightage to various content areas and helps the paper setter to construct a uniform and valid assessment. This study aimed to design and validate a blueprint for theory in Community Medicine as per the new curriculum for Medical Undergraduates in India. Blueprint in community medicine was designed by assigning impact score (I) and frequency score (F) for the competencies. Blueprint was validated using the Content Validity Index (CVI), and inter-rater agreement for subject experts using Fleiss' kappa statistics was calculated. Feedback from faculty and students was obtained afterward to assess the postimplementation response. Blueprint was designed by an expert group where impact score and frequency score were assigned to 146 competencies in the theory of Community Medicine. In Delphi survey I, 63.2% of subject experts responded, while in Delphi survey II, a response rate of 58.3% was achieved. Value of the Fleiss' Kappa test for an inter-rater agreement was 0.68, i.e. "substantial agreement," while CVI among the raters came out to be 0.86, i.e. overall valid assessment. Feedback of faculty (n = 11) suggested that the blueprint was helpful and standardized the paper setting, whereas feedback from students (n = 138) depicted that it helped in preparing for exams, and they would recommend it to other students. Validated blueprint by consensus of subject experts has impact score and frequency score along with topic-wise distribution of marks for the convenience of faculty and its utility is well proven among learners too. [ABSTRACT FROM AUTHOR]

The global problem of climate change and difficulties related to energy access, air pollution, and water pollution in India (and other developing countries) necessitate the need to look for alternative clean, local, and low-carbon energy sources for displacing fossil fuels. This paper analyses the existing waste-to-biomethane potential of the sericulture, fisheries, and agro-industrial sectors in India, which have mostly been neglected previously in India's waste-to-energy assessments. In the process, the volume of wastewaters generated from India's agro-industries are also estimated, data on which are scarce in the academic and grey literature. India's annual biomethane potentials (for 2018–19) were found to be 88 million m3, 207 million m3, and 3514 million m3 from the three sectors, respectively. To assess the energy generation potential of these wastes, a comprehensive literature review was conducted and data on residue-to-product ratios, results of proximate analyses, and specific biomethane yields were either compiled or calculated. The gross thermal energy and electricity generation potentials are 132 PJ and 22 TWh respectively; between 19 and 95 million people can benefit from such waste-to-energy production, depending on the end use of the biomethane for electricity generation or as a domestic cooking fuel. The corresponding mean removal of organic pollution from India's surface waters can be between 5.5 and 9.3 million tonnes of chemical oxygen demand. For the end uses of biomethane in electricity generation and cooking, the cumulative GHG abatements attributable to these industries are 11.4 million tonnes and 6.8 million tonnes of carbon dioxide-equivalent respectively. Besides the numeric results reported, this paper also contains a comprehensive compilation of data on waste characteristics and biomethane productions. The present status of biogas generation and related policy implementation in India are reviewed and discussed. Overall, our findings indicate that biomethane from these wastes and wastewaters can generate substantial energy for India, is in line with recent government policies, and can aid India in achieving six Sustainable Development Goals of the United Nations. • Annual estimates of wastes from India's sericulture, fisheries and agro-industries • The corresponding annual biomethane generation potential is 3810 million m3. • Clean electricity or cooking gas for 19 and 95 million people respectively • Quantitative estimates of atmospheric GHG and surface water COD removals • Biomethane data compilation and a review of present status and policies in India [ABSTRACT FROM AUTHOR]

A comprehensive case study of Mumbai (Bombay), India was undertaken to investigate the economic, social and environmental impact of international trade of waste paper for recycling purposes between industrialized and developing countries. Analysis of a Western approach vis-a-vis informal policy for waste paper recovery concludes that employment is maximum under informal policy measure and public response playsan important role in maintaining environmental quality. The study further shows that income inequality is more under informal policy, andwithout policy public cost will increase continuously in the future.The net present value of the informal policy is found to be higher than that for the formal policy. Econometric study on input substitution in the Indian paper industry suggests limited substitution possibilities between domestic and imported waste paper. Results from a static material balance flow model indicate that environmental impacts are less with increased trade and economically the paper sector in India benefits from free trade. Based upon the results of the study, somepolicy recommendations have been made that may enhance the efficiency of waste paper recycling in India. [ABSTRACT FROM AUTHOR]

Dry root rot (DRR), caused by Macrophomina phaseolina , is a prevalent disease of mungbean in Myanmar, and an emerging problem in South Asia. The pathogen is a polyphagous necrotroph, survives in the soil for many years that results disease mitigation difficult. Managing DRR in mungbean through an integrated approach has been suggested, and the use of resistant varieties is one of the economical methods. The present study aimed to identify sources of resistance against DRR from a mungbean mini-core collection and to characterize the associated M. phaseolina isolates from India and Myanmar. Evaluation of the 296 mungbean mini-core accessions against the isolate MP1 by paper towel method identified 29 accessions with DRR resistance (disease scores: ≤ 3), and 18 of them with the consistent resistance in the repeated experiment. During the screening of 18 resistant accessions in the glasshouse, nine accessions were found DRR resistance in repeated sick pot experiments with ≤10% disease incidence. A subset of 30 accessions was selected from the mini-core collection based on their in vitro DRR reactions. These accessions were evaluated for DRR resistance in the field in Yezin, Myanmar in 2018 and 2019. Out of the 30 accessions, ten accessions were found DRR resistance with ≤10% disease incidence in both years of evaluations. Pooled analysis of percent disease incidence data of 15 accessions common in both glasshouse and field revealed the stability of accessions VI001509AG, VI001244AG, and VI001400AG for DRR resistance across years and locations. The three resistant accessions along with a susceptible check VC693088 were re-evaluated by paper towel method against nine additional M. phaseolina isolates from India (MP3-MP11). The accessions VI001509AG and VI001400AG were resistant to all nine isolates, while accession VI001244AG was resistant to MP5, MP6, and MP7 isolates. These accessions could be used in mungbean DRR resistance breeding programs. • Macrophomina phaseolina isolated from mungbean from different regions showed morpho-cultural and pathological variability. • In vitro screening of 296 mungbean mini-core accessions against DRR identified 29 accessions with resistance. • Nine accessions in the glasshouse and ten accessions in the field showed DRR resistance. • GGE biplot analysis revealed that accessions VI001509AG, VI001244AG, and VI001400AG with stable DRR resistance. • Accessions VI001509AG and VI001400AG showed resistance against nine M. phaseolina isolates from India. [ABSTRACT FROM AUTHOR]

Municipal solid waste generation in India is increasing as a result of rapid urbanisation and a growing population. Due to gaps in the existing waste collection, treatment and recovery methods, large-scale unscientific disposal and lesser waste recovery have been observed. Insufficient source segregation, unorganised efforts, less awareness and indifference towards malpractice, and a lack of strict implementation were identified as the causes through literature review, surveys and interviews, Therefore, there is a need for a system of interventions, which organises efforts toward waste management and reduces the tolerance for source segregation errors. This paper aims to provide a solution that increases community participation and prevents the generation of mixed waste to ensure waste recovery. The proposed framework integrates municipal solid waste, human elements, and technology into an intelligent app-based system. This includes a smart bin that segregates waste at the source through image classification and an application for communication and data collection. [ABSTRACT FROM AUTHOR]

At the heart of India's livelihood lies agriculture, a foundational and ever-evolving sector. The realm of agriculture faces modern challenges, encompassing unpredictable climate fluctuations, insufficient irrigation infrastructure, and erratic weather conditions. Amidst these challenges, machine learning has emerged as a valuable tool for evaluating soil fertility and Crop assessment in agriculture. Ensemble machine learning methodologies have garnered attention for their potential to enhance predictive capabilities. These techniques involve constructing meta-classifiers that collectively contribute to improved predictive accuracy. This paper centers on the analysis of soil data acquired from testing laboratories, to predict fertility based on a comprehensive dataset. The study employs prominent ensemble machine learning algorithms, specifically focusing on boosting techniques, to elevate predictive accuracy and ensure heightened consistency. The assessment of soil fertility categories involved the examination of 12 carefully chosen attributes. Diverse soil parameters were measured to facilitate the prediction of soil fertility levels. The outcomes of the experimentation revealed that the application of the boosting technique using the Xgboost algorithm yielded superior accuracy compared to alternative ensemble classifiers, achieving a remarkable 96% accuracy rate. [ABSTRACT FROM AUTHOR]

Recognizing specific characters from a large set of handwritten characters is called off-line character recognition. Devanagari, the reading and writing script, is widely used in a broad region of India. This paper proposes using the modified LeNet-5 architecture for recognizing Devanagari off-line handwritten characters using the Devanagari Handwritten Character Dataset (DHCD). The dataset comprises 46 distinct character classes, each with 2000 images. The proposed modified Lenet-5 Base Architecture (MLCNN8) uses more filters and kernels of small sizes with batch normalization. The proposed modified Lenet-5 Base Architecture (MLCNN8) outperformed the Lenet-5 Base Architecture (LCNN) with an accuracy of 99.21% in 53 epochs, whereas LCNN achieved an accuracy of 94.50% in 48 epochs. Hence, the proposed modified Lenet-5 architecture outperforms the Lenet-5 Base Architecture. The proposed model's results were compared with other state-of-the-art and found that it also has an edge for recognizing the Devanagari handwritten characters. [ABSTRACT FROM AUTHOR]

Mushrooms are fungi that play significant roles in ecosystems, food, and medicine. However, distinguishing toxic mushrooms from non-toxic ones is challenging, as their visual characteristics can be misleading. Deep learning, a subset of artificial intelligence, offers a promising approach to detecting and classifying mushrooms based on their toxicity. By training deep neural networks on datasets of labelled mushroom images, it becomes possible to create models capable of accurately differentiating between toxic and non-toxic mushrooms. Mushrooms are fungi that play significant roles in ecosystems, food, and medicine. However, manually distinguishing toxic mushrooms from non-toxic ones is a challenging and time-consuming task. This research work is to help the local farmers and exporters to identify the difference between the toxic and the edible mushroom which will eventually boost production and will directly have an impact on the economic growth in India. This paper compared different deep learning algorithms such as Support Vector Machine (SVM), Resnet50, YOLO V5 and Alexnet, which have been found to be the most useful in classifying the mushrooms effectively as toxic and non-toxic respectively. The patterns in the images of the mushrooms have been predicted through the above classifiers. The validation techniques show SVM to be the most effective with an accuracy of 83%. [ABSTRACT FROM AUTHOR]

Due to the cultural and traditional diversity of the Indian environment, the successful implementation of self-automated and smart architectures is very challenging. As the IoT expands the network of devices, it also increases the hazards with increasing demands. This paper aims to propose an efficient model with the combination of interdisciplinary aspects of Indian building automation and numerous factors of Indian cultural differences. The proposed fuzzy-colored Petri-nets-based ubiquitous framework utilizes the capabilities of ubiquity for the diversified culture of Indian Building Automation systems. The proposed algorithms establish the Wi-Fi component connectivity and the working of the LED pin. Further, the modules of the Wi-Fi component connectivity, set up function and get values function to illustrate the working principle of the proposed model. Lastly, the integrated system using the FCPN tools. The significance of developing the proposed model is in its usefulness, usage of maximum ideas of different modeling techniques, cultural support, and its conversion into a formal qualitative and quantitative model. [ABSTRACT FROM AUTHOR]

Municipal solid waste generation in India is increasing as a result of rapid urbanisation and a growing population. Due to gaps in the existing waste collection, treatment and recovery methods, large-scale unscientific disposal and lesser waste recovery have been observed. Insufficient source segregation, unorganised efforts, less awareness and indifference towards malpractice, and a lack of strict implementation were identified as the causes through literature review, surveys and interviews, Therefore, there is a need for a system of interventions, which organises efforts toward waste management and reduces the tolerance for source segregation errors. This paper aims to provide a solution that increases community participation and prevents the generation of mixed waste to ensure waste recovery. The proposed framework integrates municipal solid waste, human elements, and technology into an intelligent app-based system. This includes a smart bin that segregates waste at the source through image classification and an application for communication and data collection. [ABSTRACT FROM AUTHOR]

The paper revisits the Porter-Wagner dilemma about the association between environmental management (EM) and firm performance (FP). The context of informal Micro, Small and Medium Enterprises (MSMEs) provides an interesting case since they are away from regulatory scrutiny or corporate/social obligations. The study resorts to labor productivity as the measure of FP and EM is represented by the various solid waste management practices (WMPs) adopted by the informal enterprises. Using the latest available cross-sectional data on un-incorporated firms by National Sample Survey Office (NSSO) 73rd round 2015-16, we found the positive impact of WMPs was higher in the case of more productive firms in the quantile, indicating the relevance of the Porter-Wagner dilemma. The direction of causality was further validated using the propensity score matching technique by decomposing the average treatment effect. [ABSTRACT FROM AUTHOR]

Social innovation has come to be identified as a key aspect of development. Objectives related to personal and socioeconomic development often inspire this type of innovation. Relevant goals can drive societies to fulfil citizens' needs while promoting overall empowerment and inclusion. This paper analyses the emergence and development of social innovation in rural territories in the opposing socioeconomic settings of Portugal and India. By addressing social innovation in rural territories, the paper contributes to the research and provides empirical evidence from contexts and analytical frameworks that have been neglected by most innovation scholars. The paper acknowledges the context of innovation processes and dynamics - rural territories in western and non-western countries. The consideration of two different, contrasting socioeconomic contexts provides a privileged framework to analyse the dynamics involved in the emergence and development of social innovation, namely the top-down and bottom-up approaches that characterize it. • There are contrasting realities concerning the SI processes in Portugal and India. • Depending on the context, SI takes place under top-down, bottom-up or mixing the two approaches. • It is important to open the 'black box' of SI and understand the concrete modes of its emergence and development. [ABSTRACT FROM AUTHOR]

• Caste is an important and unique axis of inequality in India. Caste based digital divide can exacerbate the existing socioeconomic divisions between different caste groups. • Using non-linear decomposition method, the present paper explains the digital divide between disadvantaged and other caste groups. • We find that there is a considerable first level and second level digital divide between the disadvantaged caste groups and Others in India. • The caste-based digital divide is largely explained by the differences in education and income between the caste groups. • The study foregrounds the importance of bridging the caste-based digital gap by closing the gap between the educational attainments of the disadvantaged and other caste groups. With the increasing importance of information and communication technologies in access to basic services like education and health, the question of digital divide based on caste assumes importance in India where large socioeconomic disparities persist between different caste groups. Studies on caste-based digital inequality are still scanty in India. Using nationally representative survey data, this paper analyzes the first-level digital divide (ownership of computer and access to the Internet) and the second-level digital divide (individuals skills to use computer and the Internet) between the disadvantaged caste groups and Others. Further, this paper identifies the caste-based differences in socioeconomic factors that contribute to the digital divide between these groups using a non-linear decomposition method. The results show that there exists large first-level and second-level digital divide between the disadvantaged caste groups and Others in India. The non-linear decomposition results indicate that caste-based digital divide in India is rooted in historical socioeconomic deprivation of disadvantaged caste groups. More than half of the caste-based digital gap is attributable to differences in educational attainment and income between the disadvantaged caste groups and Others. Findings of this study highlight the urgent need for addressing educational and income inequality between the different caste groups in India in order to bridge the digital divide. [ABSTRACT FROM AUTHOR]

Challenged by complex problems and the speed of technological, social, and environmental change, the joint approach of Lean Management and the Agile Mindset has been explored in business as a management model. This paper aimed to carry out a bibliometric analysis of Lean Agile Management, pointing out trends in scientific research. To this end, an exploratory and descriptive study was developed, with a quantitative approach and based on secondary data from the Web of Science and Scopus, between 1994 and 2022. Bibliometric indicators pointed to 1808 different papers in 897 sources, with 18 citations per paper, and higher scientific productivity of U.S. (276), India (221), and UK (191), with production peaks in 2018 and 2021, suggesting the diffusion and contemporaneity of the research topic. The laws of bibliometrics were not met for this research subject, and dense networks of collaboration and co-citation among researchers were identified, mainly in four application domains, including supply chain, manufacturing, sustainability, and software development as corroborated by the word network. [ABSTRACT FROM AUTHOR]

Agriculture and its allied sector provide the livelihoods of vast rural areas in India. It also plays a vital role in the growth of developing countries like India. Rice, one of the primary components of Indian agriculture plays a significant role in the food security of the country and the world. However, it is stricken by many diseases that affect the quality and quantity of rice yield. This paper proposes a custom CNN architecture for detecting and classifying common diseases found in rice plants by reducing the number of parameters associated with the network. The proposed CNN architecture has been trained using a dataset of four types of common rice plant diseases. In addition, 1400 on-field images of a healthy rice leaf image dataset have been introduced in the paper for the detection of disease-free plants as well. Independent experiments were carried out with and without the inclusion of the healthy leaf image dataset. The performance of the proposed model is evaluated with the use of Stochastic Gradient Descent with Momentum (SGDM) and Adaptive Moment Estimation (Adam) optimization techniques using several performance matrices. Experimental results from the dataset for the classification of four rice plant diseases show that the model using SGDM optimization gives maximum accuracy of 99.66% and the model using the Adam optimization gives maximum accuracy of 99.83% on the test set in the 7th epoch respectively. However, the model with Adam optimizer performed better than the model with SGDM optimizer when the healthy leaf image dataset is included giving a maximum accuracy of 99.66% and 97.61% in the 7th epoch respectively. [ABSTRACT FROM AUTHOR]

For the very first time, on 22-March-2020 the Indian government forced the only known method at that time to prevent the outburst of the COVID-19 pandemic which was restricting the social movements, and this led to imposing lockdown for a few days which was further extended for a few months. As the impact of lockdown, the major causes of air pollution were ceased which resulted in cleaner blue skies and hence improving the air quality standards. This paper presents an analysis of air quality particulate matter (PM)2.5, PM10, Nitrogen Dioxide (NO2), and Air quality index (AQI). The analysis indicates that the PM10 AQI value drops impulsively from (40–45%), compared before the lockdown period, followed by NO2 (27–35%), Sulphur Dioxide (SO2) (2–10%), PM2.5 (35-40%), but the Ozone (O3) rises (12–25%). To regulate air quality, many steps were taken at national and regional levels, but no effective outcome was received yet. Such short-duration lockdowns are against economic growth but led to some curative effects on AQI. So, this paper concludes that even a short period lockdown can result in significant improvement in Air quality. [ABSTRACT FROM AUTHOR]

Informal public transport is generally understood as transport services that are provided in absence or violation of state regulations. This paper argues that attempts to define the informality of public transport through such liberal economic lenses are insufficient in explaining the processes which lead to production of informalities. Discussing the operation of Vikrams (individually-owned and privately-operated shared autorickshaws plying on fixed routes) in Dehradun, India, this paper uncovers the multifaceted role of the state in producing and sustaining informalities in public transport provisions. It offers a more nuanced view of informality in transport studies than its commonplace understanding as a spontaneous, self-regulating, entrepreneurial aggregate. The paper argues that informality in transport studies should be understood as a heterogeneous practice that is a product of wider structural contexts situated in the politico-historical understandings of public transport in evolving spatio-temporal moments. In the case presented in this paper these include imperial legal legacies and its intersections with shifting postcolonial political economies and territorial structures. [ABSTRACT FROM AUTHOR]

The impact of COVID-19 on the Global scale is tremendously drastic. There are several types of research going on across the world simultaneously to understand and overcome this dire pandemic outbreak. This paper is purely a statistical study on a distinct set of datasets regarding COVID-19 in India. The motivation of this study is to provide an insight into the rapid growth of confirmed COVID-19 cases in India. The rapid growth of COVID-19 cases in India started in March 2020. The main objective of this paper is to provide a solid statistical model for the policymaker to handle this kind of pandemic situation in the near future with nonlinear data. In this paper, the data was got from 1st April to 29th November 2020. To come up with a solid statistical model, various nonlinear data such as confirmed COVID-19 cases, maximum temperature, minimum temperature, the total population (state-wise), the total area in km2 (state-wise), and the total rural and urban population count (state-wise) have been analyzed. In this paper, six different Generalized Additive Models (GAM) was identified after a thorough analysis of other researchers' (Xie and Zhu, 2020; Prata et al., 2020) findings. In all perspectives, the results were identified and analyzed. The GAM model regarding total COVID-19 confirmed cases, total population, and the total rural population provides the best average fit of R2 value of 0.934. As the population value is quite high, the author has concise it using logarithm to provide the best p -value of 0.000542 and 0.001407 for a relation between the total number of COVID-19 cases regarding the total population and total rural population respectively. [ABSTRACT FROM AUTHOR]

The rise of plastics in the 20th century revolutionized modern life but inadvertently exacerbated the marine litter crisis. The proliferation of wastes such as single-use plastics has escalated pollution along the coastline, demanding coordinated, decisive, and unified action. While the absence of specific national marine litter policies is concerning, there is growing recognition of urgency to address this issue. A group of experts and stakeholders was involved through a multi-staged workshop to assess the generated information based on scientific evidence and formulate a framework for the National Marine Litter Policy (NMLP). This paper proposes policy options (4 targets & 20 strategies) to address marine litter pollution, especially plastics, and aims to elucidate the urgency and significance of implementing an NMLP as a comprehensive strategy to combat plastics pollution. Implementing dedicated policies and action plans tailored to the unique challenges faced by each country is a vital step towards sustainable oceans. [Display omitted] • This paper explores and evaluates policy options for tackling marine litter pollution. • The proposed NMLP framework features 4 key targets and 20 strategic initiatives. • Science-Policy-based tailored solutions designed for the Indian context • Source and sector-specific measures are the focal points. [ABSTRACT FROM AUTHOR]

Debate about the causes and consequences of regional deforestation in India has paved the way for calls to action and intervention, and state-sponsored afforestation has led to government claims of progressagainst land degradation. Census statistics from the arid state of Rajasthan show a tide of forests reclaiming the land. These trends obscure crucial realities that continue to undermine the claims of the state: forest ecosystems continue to disappear, expanding cover is characterized by an ecologically narrow range of species, and forest management remains rooted in a decision structure that fails to educe local knowledge and experience. More fundamentally, the flaws in the Rajasthani forest campaign reflect an entrenched pattern that has long guided authorities in the region; to govern the landscape, the state must quite literally construct forests as mental categories, discursive tropes, and material realities where none have existed before. The material conditions of tree cover are, in this way, influenced by the discursive forms of forest imported into the region. This paper surveys the contradictory trends in Rajasthani land cover, interrogating the relationship between the forests that expand on paper and those that dwindle on the ground. In the process, the paper contributes to ongoing work in post-structural political ecology by asking how discourse matters in the reconstitution of material ecologies and by linking the construction of ecological categories to the formation of landscapes. [ABSTRACT FROM AUTHOR]

An increasing number of organizations are encouraging and accepting the research information management system in the institute level to assess the research progress of the organization and bring out a report on scholarly communication activities. Open and commercial product on the Current Research Information System (CRIS) is emerging in the last decade. The Directory of Current Research Information system listed 25 CRIS system across European countries. The European Current Research Information System (euroCRIS) support the CRIS thought the European countries through the conference, working group and pioneer in the advocacy since 2002. This paper considers the recent development in the CRIS related activities around the world and recent progress in India. This paper describes the various challenges to setting up the RIM for the higher education institutions including identification of nodal officers, collecting faculty profile information, retrieving scholarly communication activities from internal and external sources, etc. Also, discuss the training programme to the nodal officer level and institute level to promote the academic identities and their importance. The paper also discusses the impact of the IRINS in the higher education system in India and its use case with different stakeholders such as students, scholars, faculty members, scientists, research administrators, funding agencies and policymakers, etc. [ABSTRACT FROM AUTHOR]

Mortality statistics are fundamental to understand the magnitude of the COVID-19 pandemic. Due to limitation of real-time data availability, researchers had used mathematical models to estimate excess mortality globally during COVID-19 pandemic. As they demonstrated variations in scope, assumptions, estimations, and magnitude of the pandemic, and hence raised a controversy all over the world. This paper aims to review the mathematical models and their estimates of mortality due to COVID-19 in the Indian context. The PRISMA and SWiM guidelines were followed to the best possible extent. A twostep search strategy was used to identify studies that estimated excess deaths from January 2020 to December 2021 on Medline, Google Scholar, MedRxiv and BioRxiv available until 0100 h, 16 May 2022 (IST).We selected 13 studies based on a predefined criteria and extracted data on a standardised, pre-piloted form by two investigators, independently. Any discordance was resolved through consensus with a senior investigator. Estimated excess mortality was analysed using statistical software and depicted using appropriate graphs. Significant variations in scope, population, data sources, time period, and modelling strategies existed across studies along with a high risk of bias. Most of the models were based on Poisson regression. Predicted excess mortality by various models ranged from 1.1 to 9.5 million. The review presents a summary of all the estimates of excess deaths and is important to understand the different strategies used for estimation, and it highlights the importance of data availability, assumptions, and estimates. [ABSTRACT FROM AUTHOR]

Sustainability issues at the interface of science, policy and practice are complex and in an urgent need of sound interventions. Producing science without assessing the nature of the conservation challenge can result in science getting undervalued and even ignored. While several models have been developed, they do not provide a blueprint for action. Without adequate guidance, the approaches adopted by stakeholders may be out of touch with the nature of the problem and may result in suboptimal outcomes. What are the types of sustainability challenges in the place-based, knowledge-action interface and how to tackle them? To address this gap, we build on scholarly work, to classify sustainability challenges into four idealized categories: namely, knowledge gap, multifaceted, hegemonic alliance and wicked problem. Then by assimilating insights from sustainability science studies we show that it is possible to suggest a suitable approach to these problems. Using this framework, we analyze case studies from India and show how it can enhance the ability of actors to tackle real-life sustainability issues. The unique contribution of this paper lies in constructing a schematic process for diagnosis and intervention when confronted with complex sustainability challenges. Future studies can further test, expand and refine this framework to make it more comprehensive and practice-based. • Often stakeholders operating on the science, policy and practice interface (SPPI) have to tackle complex issues. • While SPPI models have been deliberated, what is lacking is a consolidation of the SPPI problems and approaches. • By building on existing scholarship we developed a conceptual framework to aid in diagnosis and intervention. • Using this frame, we analyse ten sustainability case studies from India and show the potential of this framework. • We opine that this conceptual framing can guide SPPI stakeholders to make their interventions more impactful. [ABSTRACT FROM AUTHOR]

• First longitudinal study of a FinTech ecosystem on a global, national and city level. • Network visualization of foreign and domestic investments in FinTech. • Documenting Bangalore's emergence as India's FinTech capital and the rise of New Delhi. • Demonstrating how Mumbai and Bangalore structure India's financial geography as complementary ecosystems. • Conceptualizing FinTech in India as a "Tech-Fin-State" ecosystem. This paper explores the potential of FinTech to change the geography of finance and financial centres through a longitudinal and multiscalar analysis of FinTech in India. Using a financial ecology approach, we combine quantitative data on firm creation and funding with insights from corporate interviews to unpack and examine the key elements of the Indian FinTech ecosystem. At the national scale, our results highlight how the export-oriented ICT sector, the implantation of large-scale, open digital infrastructures and enabling regulatory frameworks have enabled and shaped the growth of FinTech as a state-supported, tech-driven "Tech-Fin-State" ecosystem. At a city scale, the paper demonstrates how FinTech transforms India's financial geography in two directions. First, locational patterns and investment networks have established New Delhi and Bangalore as international FinTech hubs, ahead of Mumbai. Second, the re-intermediation of finance by FinTech firms should be understood as the connection between the two distinct yet complementary ecosystems of Bangalore, India's FinTech capital, and Mumbai, the incumbent financial capital, while advancing regional integration beyond India. [ABSTRACT FROM AUTHOR]

Recently, biomass is gaining a position as a renewable energy source. Considering its availability, India is a biomass-rich country and the second-largest sugarcane producer in the world. However, shifting towards biofuel and its strategic implementation requires thorough analysis. This paper gives a detailed analysis and case studies associated with fuel blending and its environmental impacts. It proposes a novel strategy for achieving the Indian government's target of 20 % ethanol blending with petrol from sugarcane. This paper provides the modalities to decide on the proportion of sugarcane juice and, B molasses and C molasses to be used for making ethanol. Additionally, the life cycle analysis of greenhouse gas emissions is worked out. The paper uses stoichiometry relation to obtain the carbon imprint for different cases, and the results show that the carbon emission can be reduced to a more considerable extent with the proposed strategies. • Biomass is a renewable source of energy which can help for emission reduction. • The fuel blending can bring an impact on emission reduction. • Sugarcane is the major source for producing ethanol in India. • The Government of India has target to achieve 20 % ethanol blending by 2025–26. [ABSTRACT FROM AUTHOR]

• This paper examines land formalization in the former enclaves of India inside Bangladesh. • Drawing on ethnographic research methods, it sheds light on the ambiguities of land ownership and negotiations. • It offers a lens of flexible land to comprehend such ambiguities. • It argues that attention must be paid to legibility, sovereignty, and negotiation in a post-colonial context. The former enclaves of Bangladesh and India existed as de facto stateless spaces for almost seventy years before they were exchanged and merged with the host state territories in 2015. Because of their extra-territorial existence, land ownership and transactions remained effectively a local affair in the enclaves. After the exchange, however, enclaves became regular parts of the state territory, and the host state officially recognized private ownership of enclave land. Drawing on fourteen months of ethnographic research in India's ex-enclaves inside Bangladesh, in this paper, I shed light on the complex and multi-layered process of land formalization. As such, I offer a lens of flexible land to comprehend how the state and the citizens employ numerous resources and tactics in claiming and formalizing land that becomes the simultaneous reasons and results of its flexibility. In so doing, I argue that the key to our understanding of flexible land lies in an attentive reading of legibility, sovereignty, and negotiation in a post-colonial context, especially in South Asia. Thus, flexible land becomes an innovative lens, explained and developed throughout this paper, to address how flexibility functions as an embodiment of land formalization for the citizens and the state in the former enclaves of India inside Bangladesh. [ABSTRACT FROM AUTHOR]

• Builds an analysis of 'political crops' under contemporary capitalism. • Explains the political ecology of cotton and paddy in the Indian Punjab. • Focuses on labour relations and market structure of the two crops. • Analyzes the nature of change in agrarian capitalism in the Indian Punjab. Unlike the rest of the state of Punjab in India, cotton remained the dominant monsoon crop in the southwest region till the 1990s. As it has been increasingly replaced by paddy in recent decades, this paper asks what this shift in cropping pattern reflects about the state's agrarian capitalism. Towards an analysis of this question, it builds on James Scott's idea of 'political crops' in the earliest states and places it in conversation with scholarship in critical agrarian studies, political ecology and commodity studies to account for relations of power under contemporary capitalism. Drawing on intensive primary research in the region, the paper contrasts the power relations generated by the production and circulation of the two crops. It shows that larger farmers are more likely to cultivate paddy due to better access to irrigation, and that the shift to paddy is threatening to make redundant the labour of landless Dalit women, who do cotton-picking, and increasing dependence on migrant male labour for paddy-transplanting. It also demonstrates how the different end uses of the two crops and the predominance of the private sector in the cotton markets versus the hitherto state-led nature of the paddy markets produce differential risks for farmers and traders. The paper concludes by suggesting that the shift from cotton to paddy represents capital intensification in response to Punjab's mature capitalist conditions in agriculture but also results in new contradictions and axes of political struggle. [ABSTRACT FROM AUTHOR]

The World Wide Web Consortium (W3C) has provided the most important set of guidelines for web accessibility which is popularly known as Web Content Accessibility Guidelines (WCAG). The accessibility analysis of higher education websites becomes paramount important to make them inclusive considering the growing number of enrollments of persons with disabilities (PwDs) in higher education, in countries such as India. This paper presents the accessibility analysis of higher education websites with the case study of college websites (N = 44) affiliated with the University of Kashmir and Cluster University Srinagar. The study has been carried out with two major accessibility evaluation tools called web accessibility test, denoted as TAW and the accessibility engine powering browser extensions called the accessibility engine, denoted as aXe. This paper lists the major accessibility barriers exposed by these sites in terms of metrics such as a number of problems, warnings and a status of success criteria violations. With respect to TAW tool, a number of problems observed were 2646, a large number of warnings to the scale of 15995 and the not reviewed items were 1356. With aXe tool, the total violations observed were 1951 and items needing review were 1733. Findings of the statistical analysis are also presented in this paper. This paper presents a roadmap of steps for making these websites inclusive and barrier-free for PwDs. [ABSTRACT FROM AUTHOR]

Environmental policy debates often get polarized along binaries of environment versus economic development or conservation versus rights. Sustainability scientists and practitioners generally suggest finding common grounds as a pathway for building consensus among the diverse perspectives involved in polarized environmental policy discussions. This paper takes a critical stance towards such calls for common grounds by calling attention to the implicit assumptions that underlie these discourses. We study the case of the Forest Rights Act (FRA) in India, which has polarized the forest policy discourse between conservationists and rights activists in India. We examine scientific publications on the FRA using discourse and framing analysis and show that scholarly discourses on FRA lie along a spectrum characterized by underlying epistemic and normative practices. We identify five groups of scholars based on the unique positions they have taken on FRA: a) advocacy-centric, b) welfare-centric, c) community-centric, d) dialogue-centric, and e) techno-centric scholars. We find that negative framings of the forest dweller community lead to scientific endorsement of policy prescriptions that empower socio-political institutions that are external to these communities. We argue that scholarly calls for common grounds often assume uniform or neutral framings for the stakeholders involved. We conclude that recognizing the polarization spectrum in environmental policy discourses can help us move towards pluralistic approaches to environmental governance. • Scientific polarization on Indian forest policy discourses lies along a spectrum. • Epistemic and normative practices shape scientific positions on forest policies. • Negative framings of traditional communities tend to empower external institutions. • Calls for dialogue often do not specify framings for the stakeholders involved. • Recognize the polarization spectrum for enabling pluralistic environmental governance. [ABSTRACT FROM AUTHOR]

This paper examines the effectiveness of the monetary policies undertaken by the central bank on economic growth during COVID-19 uncertainty in case of India and Indonesia. We use an innovative framework of Growth-at-Risk as oppose to standard macroeconomic models, which can predict the growth in a much robust way particularly when an economy is facing shocks like COVID-19. The empirical results based on Growth-at-Risk model clearly reveal that effect of COVID-19 pandemic on economic growth is much adverse in comparison to actual declines. Further, this study shows the effectiveness of monetary and financial policies undertaken by the central banks of both India and Indonesia, which have actually subsided the adverse impact of COVID-19. [ABSTRACT FROM AUTHOR]

Growing organic waste in India is posing a challenge in its effective management. Open degradation of this organic waste pollutes environment, as well as causes a slew of diseases. Situation may be handled effectively using biogas plants employing anaerobic digestion process. However, performance of these plants is dependent upon various environmental factors and feed types. In this paper, the feasibility analysis of a biogas plant for the northern plains of India has been conducted. A new modified anaerobic digestion model (MAD1) has been designed for the analysis. It is evident from the analysis that the northern plains of India have a large potential for biogas production as they generate a large amount of organic waste. Furthermore, analysis reveals that, if the biogas plant is operated at a thermophilic temperature ranging from 44 °C to 55 °C, the profit can be maximised. However, if the biogas plant is operated at 37 °C, the significant profit will begin after 3–4 years, depending on the type of feedstock. Complete analysis has been conducted in MATLAB Simulink environment. • Conducted sensitivity analysis of the parameters of anaerobic digestion process • Conducted feasibility analysis of biogas plant for Northern Indian states. • Conducted economic analysis of biogas plant to maximize profit • Modelled a modified anaerobic digestion model (MAD1) for realistic output [ABSTRACT FROM AUTHOR]

Quantitative evidence on the impact of social protection such as livelihood programs (LPs) on reducing vulnerability to poverty (VtP) is scant. Therefore, this paper aims to estimate VtP and the ability of LPs to reduce it. The analysis is based on the primary data collected in 2018–19 from 479 households in a tribal region of eastern India. First, household VtP was estimated using the feasible generalized least squares (FGLS) method. Households were categorized into four groups based on their current and predicted future poverty status: chronic poor, transient poor, escaped poverty, and non-poor. Second, factors influencing this movement of households from current to future poverty states were determined using multinomial logistic regression. Third, the impact of the LP on VtP was investigated using the endogenous switching regression (ESR) approach. The FGLS estimates show that 34.7% of households are vulnerable to future poverty, which exceeds the actual poverty rate of 28.6%. The major factors responsible for exacerbating chronic poverty and causing transient poverty are chronic illness, climate shocks, and the sale of assets. The ESR results indicate that a household's VtP is reduced by 3% for those that participate in LPs. Although the LP evaluated in this study has an average positive impact in reducing vulnerability, there is wide heterogeneity among the beneficiaries as the geographically disadvantaged communities lag behind the others. Therefore, the study suggests strengthening such LPs with a particular focus on disadvantaged and vulnerable communities. [ABSTRACT FROM AUTHOR]

Agriculture is the major occupation and the main origin of income in India, and most of the population depends on agriculture for their living. The smart farming system's foremost goal is to monitor farmlands by automatically rinsing the lands with appropriate water and a pest detection framework. The conventional agricultural methods lack higher crop productivity with increased human efforts. Hence, the paper proposes an IoT-based solution for smart farming. The proposed system focuses on automatic irrigation of water and plant disease detection. It uses machine learning algorithms to accurately predict adequate water required by the fields and automatic pest identification based on the requirements of the farmland. K-Nearest Neighbour and support vector machine learning algorithms in the pest detection module are used to precisely predict plant diseases. The convenient features from the leaves of the plants were obtained. Then the obtained features are used for classification purposes. Extracting the suitable features and classifying them helps detect whether the plant is pest infected or not. The proposed system monitors, analyses, assesses and controls agricultural fields for the automatic irrigation of the water and disease identification of the plants. The numerical analysis of the machine learning algorithms and the significance of the classification with accuracy are investigated. From the numerical results, it is demonstrated that an accuracy of 84 % is achieved. [ABSTRACT FROM AUTHOR]

Crop disease in the plant is a significant issue in the agriculture sector, and it is currently very difficult to detect these illnesses in crop leaves. The foundation of the global economy is agriculture. India ranks second in the production of tomatoes worldwide. The tomato crop is affected by various diseases which lead to a reduction in product quality and quantity. The advancement in computer vision and deep learning opens up the door for predicting diseases that appear in the crops. The aim of this paper is classification among 10 different categories of tomato plant leaves using the proposed novel TomConv model which deploys an improved Convolutional Neural Network (CNN). For this purpose, the publicly available dataset called PlantVillage comprising of more than 16000 images of tomato leaves, both diseased and healthy was used for the experimentation purpose. The proposed model is the simplest model among all the available state-of-the-art models. The tomato leaf images were preprocessed for reducing the size in 150 × 150 dimension. The model constitutes four layered CNN followed by a max pooling layer. The model splits the corpus into training and validation datasets in 80:20 ratio, is trained under 105 epochs for tomato leaf images, and achieved an accuracy of 98.19%. The proposed model is compared with existing models under different parameters such as no. of classes, no. of layers, and accuracy. The results are promising as they outperform all the available state-of-the-art models. [ABSTRACT FROM AUTHOR]

Agricultural sector is one of the main sectors in India. Productive growth and high yield production of fruits is important and required for the agricultural industry. Application of computer vision and image processing has aid agriculture to boost yield rating, disease spotting, irrigation, fruit classification and maturity grading. Computer vision and image processing approach can be used to lower the time utilization and has made it economical. A convolutional neural network (CNN) is a type of artificial neural network used in image identification and processing that is mainly planned to process pixel data. This paper utilized a convolutional neural network (CNN) to classify bananas into raw or ripe without requiring labour. Bananas were classified by their colour appearance in the CNN classification and not only this it can be also used to classify many other types of fruits and vegetables. [ABSTRACT FROM AUTHOR]

Agriculture is a significant contributor to India's economic growth. The rising population of country and constantly changing climatic conditions have an impact on crop production and food security. A variety of factors influence crop selection, including market price, production rate, soil type, rainfall, temperature, government policies, etc. Many changes are required in the agricultural sector in order to enhance the Indian economy. In this research work authors have implemented various machine learning techniques to estimate the crop yield in Rajasthan state of India on five identified crops. The results indicate that among all the applied algorithms; Random Forest, SVM, Gradient Descent, long short-term memory, and Lasso regression techniques; the random forest performed better than others with 0.963 R2, 0.035 RMSE, and 0.0251 MAE. The results were validated using R2, root mean squared error, and the mean absolute error to cross-validation techniques. This paper intends to put the crop selection method into practice to help farmers solve crop yield problems. [ABSTRACT FROM AUTHOR]

Good health and well being is one of the most essential targets of the Sustainable Development Goals (SDGs). This paper primarily focuses on Preventive and Diagnostic care of Women Health because even today, women are disadvantaged by discrimination in many societies especially in rural sectors. Two main health issues, fetal abnormality in pregnant women and cervical cancer in women are analyzed so that the doctors and patients can be given early signals to take proactive measures. As per National Health Portal of India, around 1.7 million birth defects occur in India every year. So Antenatal Care(ANC) should be given utmost importance during Pregnancy in a woman's life. Cervical cancer is another issue prevalent amongst women, especialy over the age of 30. It's critical to catch it early and eliminate any risks that come with it. Here arises the need to develop a system that can analyze and predict the aforementioned anomalies at an early stage. This work proposes approximate query processing using different dynamic machine learning algorithms to analyze and predict the abnormalities. Further, a web application is built to facilitate the stakeholders, especially doctors, to interact with the system and iteratively query the system to understand the relationships amongst the various data variables and get appropriate predictions about fetal anomaly from CTG scans as well as presence of cervical cancer from various demographic information, habits, and historic medical records. Approximate Query Processing is accomplished using Correlation analysis, linear, and logistic regression algorithms in a dynamic, interactive, and iterative manner. [ABSTRACT FROM AUTHOR]

Wind power constitutes one of the largest forms of renewable energy in India. Many operational models have predicted wind energy in India, but most rely on satellite reanalysis data. In contrast, this paper examines historical generation data at an unprecedented granularity to understand its potential and variance. We find actual wind capacity factor (CF) during the Indian Summer Monsoon to be less than half that predicted in NREL's recent landmark production cost modeling study. Further, we find that the yearly moving average of aggregated CF exhibits a +0.640 correlation with the ENSO SOI, a widely-used climatological parameter. At the feeder level, we confirm an expected exponential relationship between average CF and turbine hub height. However, this effect is 261% more pronounced during the monsoon, a finding with troublesome implications for grid planning. We also test the assumption that higher wind turbines perform proportionately better outside of the monsoon and find no evidence to support it. Finally, we present a new method to measure the geographic smoothing effect that reduces inherent variability by 18% when compared to normalized standard deviation. We find limits to the effect of decreasing variability through geographic diversity; the effect mostly disappears at about 125 km. • Historical wind energy capacity factor is half that predicted by recent models. • Wind energy in Karnataka exhibits strong correlation with El Nino cycles. • Higher hub height leads to higher capacity factor, disproportionately during the monsoon. • New method improves method of measuring geographic smoothing effect. • Geographic smoothing in Karnataka disappears at about 125 km. [ABSTRACT FROM AUTHOR]

• Pollution governance in India. • Caste. • Disasters. • Kerala. This paper draws on fieldwork conducted in the agriultural village of Kathikudam in the South Indian state of Kerala. The paper looks at the ways in which the production of knowledge of contemporary pollution governance in India is configured through the reproduction of marginalization through the devluation of knowledge held by racialized and caste/d subsistence women farmers in Kathikudam. This paper also illuminates how this production of knowledge and the attendant marginality it produces creates a sedimented form of disaster in the community. [ABSTRACT FROM AUTHOR]

This paper, based on a qualitative study, explores the home-making activities of older adults living in a non-profit, welfare-based institutional care home in Kerala, India. We employed in-depth interviews and observation to obtain rich data on various home-making practices of older adults. Contrary to the stigmatization in India of care homes as places of abandonment and desertion, this study illustrates: (1) the important role of non-profit care homes in protecting neglected older adults especially in non-western contexts; and (2) the performative roles of older adults who utilize, modify, and recreate home in formal care spaces. Our empirical results show that daily rhythmic activities, gender roles, kinning, and cultural practices in a formal care setting contribute to establishing new familial ties and continuity in life as well as a sense of insideness in a formal care home. This paper contributes to the emerging dialogue on the role of rhythm, kinning, and culture in home-making practices in formal care spaces in a non-western context. [ABSTRACT FROM AUTHOR]