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This paper investigates the relationship between conflict trajectories and years of schooling in India for girls and boys. It adopts propensity score matching methods on panel data from the India Human Development Survey (2004/05-2011/12) merged with conflict data from the South Asia Terrorism Portal. Conflict is measured according to the dynamic trajectory of Naxal violence-related fatalities at the district level, distinguishing areas of chronic conflict with those experiencing dynamism in conflict intensity over time. ATT estimates indicate that conflict is associated with a reduction in years of schooling for both genders, though relatively high for girls (by a quarter of a year for girls and by 0.16 of a year for boys), driven by large reductions in school accumulation for girls living in areas of chronic conflict. Results are consistent when adopting different methods, alternative measures of conflict fatalities, and accounting for other conflicts and selective migration. Examining transmission mechanisms suggest that household spending on girls' education may be de-prioritised amidst conflict, while conflict may also weaken or destroy school infrastructure. Results suggest that policy responses should prioritise girls' education in areas of chronic conflict, not only in 'fragile states' but in countries where conflict remains a subnational concern. [ABSTRACT FROM AUTHOR]

The ability to assess and evaluate the condition of existing bridges adequately and accurately is a critical aspect of bridge maintenance and management, which involves condition assessments. Multiple hazards can affect existing bridges, making them vulnerable or risky, and any decision support concerning their management requires special attention. A rational and systematic framework for making practical decisions about the hazards present in a region and the appropriate level of risk is presented in this paper. An analytical hierarchy process (AHP) framework is proposed to rank hazards in hierarchical order based on a region's characteristics and a suitable analysis range, which provides the degree of risk that could jeopardise bridges. The proposed method can assist decision makers in selecting appropriate strategies for improving existing bridges. As a result, bridge inspection costs can be significantly reduced, maintenance and repair funds can be more effectively allocated and the safety, mobility, longevity and reliability of highway transportation assets can be improved. The approach was used in a case study of existing reinforced concrete (RC) bridges in the Barak Valley region in Assam, India. Such an approach is novel to the Indian subcontinent. [ABSTRACT FROM AUTHOR]

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A declining trend in Indian summer monsoon precipitation (ISMP) in the latter half of the 20th century is a scientifically challenging and societally relevant research issue. Heavy aerosol loading over India is one of the key factors in modulating the ISMP. Using the state-of-the-state-of-the-art chemistry-climate model, ECHAM6-HAMMOZ, the impacts of South Asian anthropogenic sulfate aerosols on the Indian summer monsoon precipitation were investigated against: (1) 2010 La Niña (excess monsoon), (2) 2015 El Niño (deficit monsoon) in comparison to (3) normal monsoon 2016. Sensitivity simulations were designed with 48% enhancement in South Asian SO 2 emissions based on a trend estimated from Ozone Monitoring Instrument (OMI) satellite observations during 2006–2017. The model simulations showed that sulfate aerosols reduce ISMP by 27.5%–43.3 %, while simulations without sulfate loading enhanced ISMP by 23% in 2010 La Niña and reduction by 35% in 2015 El Niño. This paper reports that sulfate aerosols loading over India reduce precipitation by aerosol-induced direct and indirect effects by inducing atmospheric cooling, weakening in the convection, and reduction in moisture transport to Indian landmass. This paper emphasizes the necessity of alternate use of energy to reduce sulfate aerosol emissions to solve water issues in South Asia. [Display omitted] • Sulfate emission reduces Indian summer monsoon precipitation through aerosol-radiation and aerosol-cloud interactions. • Over 27% of the summer monsoon rainfall deficit in a normal year are linked to Asian anthropogenic sulfate emissions. • Sulfate-induced rainfall reduction is the maximum for La Niña year. • SO 2 loading increases atmospheric stability and weakens moisture transport to India. [ABSTRACT FROM AUTHOR]

South Asia's coastlines are the most densely inhabited and economically active ecosystems have already begun to shift due to climate change. Over the past century, climate change has contributed to a gradual and considerable rise in sea level, which has eroded shorelines and increased storm-related coastal flooding. The differences in estuary water quality over time, both seasonally and annually, have been efficiently controlled by changes in stream flow. Assessment requires digitized analytical platforms to lower the risk of catastrophes associated with climate change in coastal towns. To predict future changes in an area's vulnerability and waste planning decisions, a prospective investigation requires qualitative and quantitative scenarios. The paper concentrates on the development of a forecasting platform to evaluate the climate change and waste water impacts on the south coastal region of India. Due to the enhancement of Digitization, a multi-model ensemble combined with manifold learning is implemented on the multi-case models influencing the uncertainty probability rate of 23% and can be ignored with desired precaution on the coastal environmental. Because Manifold Learning Analysis results cannot be utilized directly in wastewater management studies because of their inherent biases, a statistical bias correction and meta-feature estimation have been implemented. Within the climate-hydrology modeling chain, the results demonstrate a wide range of expected changes in water resources in some places. Experimental statistics reveal that the forecasted rate of 91.45% will be the better choice to reduce the uncertainty of climatic change and wastewater management. • Development of Multi-Objective Neighborhood Embedding Ensemble Strategy (NEES) to predict waste water and climate change impacts. • Manifold learning with metafeatures estimator model to forecast the temperature index and oxygen depletion. • Enhanced Coastal Management system with multi-parameter reliability model for South Asia Coastal region to safeguard the environmental eco-stability. • Manifold predictor models for waste water impact and climatic influence with maximum data samples with optimized cost function. [ABSTRACT FROM AUTHOR]

Millions of skeletal remains from South Asia were exported in red markets (the underground economy of human tissues/organs) to educational institutions globally for over a century. It is time to recognize the personhood of the people who were systematically made into anatomical objects and acknowledge the scientific racism in creating and continuing to use them. [ABSTRACT FROM AUTHOR]

Endemic to the Indian subcontinent, the sloth bear (Melursus ursinus) is a threatened species, present in fragmented habitats across India. Field techniques such as direct observation and camera trapping alone are not sufficient and may not be explicit enough to understand a monomorphic species like the sloth bear at larger spatial scales. In this study, we looked into the genetic structure, variability and population demographics amongst the extant sloth bear populations in the highly fragmented Vidarbha landscape, using a panel of 13 microsatellite markers with a cumulative PID value of 1.48 × 10−5 PIDsibs. Our results revealed genetic clustering (K = 5) and moderate structuring amongst the study populations. Despite being geographically distant and placed in two different genetic clusters, sloth bears from the Melghat Tiger Reserve and Sahyadri Tiger Reserve shared genetic signatures, indicating connectivity, while migration was detected amongst other study areas as well. The findings from this study can serve as baseline assessment for future genetic monitoring of the species in the human-dominated landscape and assist in managerial decisions to step up protection of fragmented forest patches and reduce human–bear conflicts without compromising on the genetic connectivity. [ABSTRACT FROM AUTHOR]

The frequency and intensity of extreme precipitation events are on the rise worldwide. Despite extensive efforts, regional climate models still show significant biases for extreme precipitation events, often due to factors like improper physics, the choice of land surface model, and spatial domain. Thus, this study uses a Coupled Land–Atmosphere Regional Climate Model version 4.7 (RegCM4.7) to explore how the choice of land surface models (LSMs) and domain extent affects the simulation of extreme precipitation over India. In this regard, a total of four sensitivity experiments have been carried out using two LSMs (CLM4.5 and BATS) over each of the two domains (one over the bigger South Asia CORDEX domain and another for the smaller domain over the Indian region). The main objective is to provide a holistic idea for obtaining an optimum model domain and LSMs for precipitation extremes over India. The model performance is demonstrated for extreme precipitation and associated processes. The result shows the systematic discrepancy in simulating extreme precipitation with a strong inter-simulation spread, indicating the strong sensitivity of extreme precipitation on the LSMs as well as the model domain. The BATS configuration shows a significant overestimation of consecutive wet days and very low precipitation, partially associated with a deficiency in convection. By contrast, the considerable underestimation of intense precipitation can be attributed to the presence of frequent, light drizzle, which hinders the accumulation of moisture in the atmosphere to a sufficient degree to prevent extreme rainfall. Despite significant improvement, the best-configured model (CLM with Indian domain) still indicates substantial bias for extreme precipitation. This deficiency in the model could potentially be mitigated by enhancing both horizontal and vertical resolutions. Nevertheless, further research is needed to explore other physics parameterizations and dynamic mechanisms to address this issue. [ABSTRACT FROM AUTHOR]