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Knowledge of the ice thickness distribution of the world’s glaciers is a fundamental prerequisite for a range of studies. Projections of future glacier change, estimates of the available freshwater resources or assessments of potential sea-level rise all need glacier ice thickness to be accurately constrained. Previous estimates of global glacier volumes are mostly based on scaling relations between glacier area and volume, and only one study provides global-scale information on the ice thickness distribution of individual glaciers. Here we use an ensemble of up to five models to provide a consensus estimate for the ice thickness distribution of all the about 215,000 glaciers outside the Greenland and Antarctic ice sheets. The models use principles of ice flow dynamics to invert for ice thickness from surface characteristics. We find a total volume of 158 ± 41 × 103 km3, which is equivalent to 0.32 ± 0.08 m of sea-level change when the fraction of ice located below present-day sea level (roughly 15%) is subtracted. Our results indicate that High Mountain Asia hosts about 27% less glacier ice than previously suggested, and imply that the timing by which the region is expected to lose half of its present-day glacier area has to be moved forward by about one decade.The ice volume of glaciers outside the Greenland and Antarctic ice sheets totals about 158,000 km3, with about 27% less ice in High Mountain Asia than thought, according to multiple models that estimate ice thickness from surface characteristics.

The emergence of COVID-19 has brought the entire planet to a halt. Many countries, including India, were compelled to shut down most urban, industrial, social and other activities as a result of the pandemic. Due to a series of complete lockdowns imposed in India from March 24 to May 17, 2020, and state-wise local level restrictions afterward, have resulted in significant reduction of emissions of numerous atmospheric pollutants. The objective of this study is to analyse the change in concentration of various pollutants such as nitrogen oxide (NO 2 ), carbon monoxide (CO) and aerosol optical depth (AOD) due to lockdown and also to quantify the contribution of crop stubble burning to air pollution. The Sentinel-5P based NO 2 and CO observations for 2019 and 2020 and Moderate Resolution Imaging Spectroradiometer (MODIS)-based AOD observations for 2016–2020 were used for detecting the variations. The obtained results showed a significant decrease in NO 2 levels during various stages of lockdown. Small decrease in CO levels was observed across most part of the India. With a few exceptions, such as coastal and desert regions, there was a moderate decrease in AOD levels. Furthermore, to study the contribution of NO 2 , CO and AOD from crop stubble burning, MODIS observations on active fire events were obtained from Visible Infrared Imaging Radiometer Suite (VIIRS). The burning of crop stubble increased NO 2 emissions by 22 to 80%. CO levels, on the other hand, have risen by 7 to 25%. A considerable variation in AOD was reported, ranging from 1 to 426%.

In this study, we mapped land subsidence in the Ahmedabad urban region using the SBAS InSAR technique between 2020 and 2023 (approximately 3.5 years). A distinct pattern of average line of sight (LOS) land subsidence was observed at two key locations within the city: the Southwest and Southeast regions of Ahmedabad. The average LOS velocity in these areas ranged from −1.5 cm/year to −3.0 cm/year in the Southwest and −2 cm/year to −3.5 cm/year in the Southeast. Negative LOS velocities represent areas experiencing subsidence. Data from the Central Ground Water Board (CGWB) revealed that groundwater levels in the Southwest region dropped significantly from around 11 meters in mid-2005 to less than 2 meters by 2019. Similarly, in the Southeast, groundwater levels fell from approximately 42 meters in 2005 to around 28 meters in 2019. The observed land subsidence was strongly correlated with localized groundwater depletion. Additionally, groundwater data from multiple wells across the Ahmedabad district were analyzed over several years. In contrast to localized depletion, a substantial number of wells at the district level showed an increase in groundwater levels from 2014 to 2022, compared to the decadal average, suggesting an overall positive trend in groundwater availability. This indicates that the subsidence is likely due to localized over-extraction of groundwater and hydrogeological factors specific to these areas, which differ from broader regional trends.

This study presents a recent estimate (for year 2017) of ice thickness and volume of a small glacier called Patsio Glacier located in Western Himalayas. Also, the present study aims to examine whether the improvement in GlabTop2 based estimates obtained for Chhota Shigri Glacier through the use of relatively accurate and high-resolution Digital Elevation Model (DEM) and glacier specific model parameterisation is consistent and can be extended to other glaciers. The version of GlabTop2 model used in this study is GlabTop2_IITB (Glacier Bed Topography version 2_Indian Institute of Technology Bombay). For validation purpose, ground penetrating radar (GPR) survey-based ice thickness estimates available at four cross-section profiles collected during July 2017 was used. Root mean square error (RMSE) of the modelled ice thickness estimates is about 14 m. Average and the maximum thickness of the modelled glacier ice is about 45 and 129 m, respectively. The obtained results when compared with an earlier study carried out using velocity-based approach indicate a significant improvement in the modelling accuracy. Moreover, a 16 percentage points reduction in uncertainty of the estimated ice thickness is seen when compared with a previous study involving different version of GlabTop2 model for Himalaya–Karakoram region. This is perhaps due to the use of a relatively accurate and high-resolution DEM and model parameterisation scheme adopted in this study, thus confirming the consistency of the modelling approach for different glaciers. Based on the obtained ice thickness estimates, the modelled volume of the glacier stored ice was calculated to be 0.11198 ± 0.0162 km 3 in 2017.

The Normalised Difference Vegetation Index (NDVI) derived from optical satellite images plays a very important role in determining the state of plants' health. Also, it is an important parameter needed in various statistical/process-based models. However, the use of optical images is sometimes limited because of atmospheric conditions and cloud cover. On the other hand, synthetic aperture radar (SAR) remote sensing has been widely used for crop monitoring due to its high-resolution imaging and all-weather data acquisition capabilities. So, if the SAR backscatter response (σ0) and NDVI data could be correlated, it is possible to estimate NDVI (during complete or partial stages of crop development) under overcast situations. In this study, three different experiments have been performed to establish the relationship between NDVI-σ0VV, NDVI-σ0VH, and NDVI-σ0VV/σ0VH. Here, time-series σ0 (in VV and VH polarizations) and NDVI were extracted from Sentinel-1 and Senitnel-2, respectively. Based on the analysis, it is found that the NDVI is more closely correlated with the ratio σ0VV/σ0VH than it is with σ0VV and σ0VH when data points from the start of cropping season up to the start of the maturity stage of the crop, were considered (referred to as experiment 2 and experiment 3). This is opposed to experiment 1, which took into account all data points related to the crop's development i.e. start of cropping season up to the harvesting stage of the crop. The best results were obtained from experiment 3 in which higher-order polynomial regressions were developed between NDVI and σ0VV/σ0VH. A significant correlation ranging from R2 = 0.81 to 0.98 were observed for NDVI-σ0VV/σ0VH. The study was conducted on selected farms located in the same agro-climatic zone during the Rabi season of 2018–19.

Nutrient deficiency disorders due to malnutrition are rapidly increasing and are associated with numerous co-morbidities. In such a scenario, developing functional food and value-added products from pharmacologically, nutritionally, and therapeutically rich plants is essential. Hence, the present study aimed to develop a nutritionally rich and healthier functional food, i.e., spread from Cucumis callosus (CA) by blending with Malus domestica (MD). Various blends were prepared manually for MD: CA, i.e., C (100:0), T1 (50:50), T2 (25:75), and T3 (0:100). The developed Spread was stored at room temperature and further evaluated for nutritional, sensory, and shelf-life attributes for three months. The developed product indicated that the blending and storage period had a significant (p<0.05) impact on nutritional parameters. The TSS (68.22±0.06 to 69.83±0.050Bx), pH (3.24±0.13 to 4.97±0.00), titrable acidity (1.18±0.08 to 1.66±0.12%), pectin (0.28±0.02 to 0.83±0.03%), β-carotene (2.07±0.02 to 3.00±0.02mg/100gm), vitamin A (3.45±0.03 to 4.98±0.06 I.U.), anthocyanin (1.29±0.38 to 1.71±0.08mg/100gm), reducing sugar (19.88±0.18 to 27.73±0.24%), total sugar (55.01±0.10 to 60.14±0.07%), non-reducing sugar (30.30±0.63 to 34.44±0.15%), moisture (45.17±0.03 to 57.05±0.11%), and ash (0.50±0.02 to 0.56±0.01%) varied significantly. In terms of sensory evaluation, all the blends showed non-significant differences. However, the spread T3 (100% CA pulp) received the highest score, indicating its high sensory acceptability. This indicates that CA can be utilized to develop intermediate moisture food products, i.e., spread with nutritional richness and sensory acceptability.  

Recently Bramoulle and Kranton presented a model for the provision of public goods over a network and showed the existence of a class of Nash equilibria called specialized equilibria wherein some agents exert maximum effort while other agents free ride. We examine the efficiency, effort and cost of specialized equilibria in comparison to other equilibria. Our main results show that the welfare of a particular specialized equilibrium approaches the maximum welfare amongst all equilibria as the concavity of the benefit function tends to unity. For forest networks a similar result also holds as the concavity approaches zero. Moreover, without any such concavity conditions, there exists for any network a specialized equilibrium that requires the maximum weighted effort amongst all equilibria. When the network is a forest, a specialized equilibrium also incurs the minimum total cost amongst all equilibria. For well-covered forest networks we show that all welfare maximizing equilibria are specialized and all equilibria incur the same total cost. Thus we argue that specialized equilibria may be considered as a refinement of the equilibrium of the public goods game. We show several results on the structure and efficiency of equilibria that highlight the role of dependants in the network.

The linear complementarity problem is a continuous optimization problem that generalizes convex quadratic programming, Nash equilibria of bimatrix games and several such problems. This paper presents a continuous optimization formulation for the weighted independence number of a graph by characterizing it as the maximum weighted \\(\\ell_1\\) norm over the solution set of a linear complementarity problem (LCP). The minimum \\(\\ell_1\\) norm of solutions of this LCP is a lower bound on the independent domination number of the graph. Unlike the case of the maximum \\(\\ell_1\\) norm, this lower bound is in general weak, but we show it to be tight if the graph is a forest. Using methods from the theory of LCPs, we obtain a few graph theoretic results. In particular, we provide a stronger variant of the Lov\\'{a}sz theta of a graph. We then provide sufficient conditions for a graph to be well-covered, i.e., for all maximal independent sets to also be maximum. This condition is also shown to be necessary for well-coveredness if the graph is a forest. Finally, the reduction of the maximum independent set problem to a linear program with (linear) complementarity constraints (LPCC) shows that LPCCs are hard to approximate.