Assessing groundwater recharge rates, water quality changes, and agricultural impacts of large-scale water recycling.

The over-exploitation and insufficient replenishment of groundwater (GW) have resulted in a pressing need to conserve freshwater and reuse of treated wastewater. To address this issue, the Government of Karnataka launched a large-scale recycling (440 million liters/day) scheme to indirectly recharge GW using secondary treated municipal wastewater (STW) in drought-prone areas of Kolar district in southern India. This recycling employs soil aquifer treatment (SAT) technology, which involves filling surface run-off tanks with STW that intentionally infiltrate and recharge aquifers. This study quantifies the impact of STW recycling on GW recharge rates, levels, and quality in the crystalline aquifers of peninsular India. The study area is characterized by hard rock aquifers with fractured gneiss, granites, schists, and highly fractured weathered rocks. The agricultural impacts of the improved GW table are also quantified by comparing areas receiving STW to those not receiving it, and changes before and after STW recycling were measured. The AMBHAS_1D model was used to estimate the recharge rates and showed a tenfold increase in daily recharge rates, resulting in a significant increase in the GW levels. The results indicate that the surface water in the rejuvenated tanks meets the country's stringent water discharge standards for STW. The GW levels of the studied boreholes increased by 58-73 %, and the GW quality improved significantly, turning hard water into soft water. Land use land cover studies confirmed an increase in the number of water bodies, trees, and cultivated land. The availability of GW significantly improved agricultural productivity (11-42 %), milk productivity (33 %), and fish productivity (341 %). The study's outcomes are expected to serve as a role model for the rest of Indian metro cities and demonstrate the potential of reusing STW to achieve a circular economy and a water-resilient system.

SegPC-2021: A challenge & dataset on segmentation of Multiple Myeloma plasma cells from microscopic images.

Multiple Myeloma (MM) is an emerging ailment of global concern. Its diagnosis at the early stages is critical for recovery. Therefore, efforts are underway to produce digital pathology tools with human-level intelligence that are efficient, scalable, accessible, and cost-effective. Following the trend, a medical imaging challenge on "Segmentation of Multiple Myeloma Plasma Cells in Microscopic Images (SegPC-2021)" was organized at the IEEE International Symposium on Biomedical Imaging (ISBI), 2021, France. The challenge addressed the problem of cell segmentation in microscopic images captured from the slides prepared from the bone marrow aspirate of patients diagnosed with Multiple Myeloma. The challenge released a total of 775 images with 690 and 85 images of sizes 2040×1536 and 1920×2560 pixels, respectively, captured from two different (microscope and camera) setups. The participants had to segment the plasma cells with a separate label on each cell's nucleus and cytoplasm. This problem comprises many challenges, including a reduced color contrast between the cytoplasm and the background, and the clustering of cells with a feeble boundary separation of individual cells. To our knowledge, the SegPC-2021 challenge dataset is the largest publicly available annotated data on plasma cell segmentation in MM so far. The challenge targets a semi-automated tool to ensure the supervision of medical experts. It was conducted for a span of five months, from November 2020 to April 2021. Initially, the data was shared with 696 people from 52 teams, of which 41 teams submitted the results of their models on the evaluation portal in the validation phase. Similarly, 20 teams qualified for the last round, of which 16 teams submitted the results in the final test phase. All the top-5 teams employed DL-based approaches, and the best mIoU obtained on the final test set of 277 microscopic images was 0.9389. All these five models have been analyzed and discussed in detail. This challenge task is a step towards the target of creating an automated MM diagnostic tool.

Point of Care Tests: Changing Paradigms in the Diagnosis of SARS-CoV-2.

Background: Point of care tests provide rapid information about the patient's condition, with a turnaround time of 15 min. During the COVID-19 pandemic, many such point of care tests were developed, to aid in the rapid diagnosis of SARS-Cov-2 infection. Aim: To describe and synthesize the available literature on point of care tests for diagnosis of SARS-CoV-2. Methodology: This narrative review was done through online literature search, using Google Scholar and PubMed. Result: There were 51 point of care tests for diagnosis of SARS-CoV-2 which were validated using different samples, such as such as nasopharyngeal swabs(42), oropharyngeal and naso-pharyngealswabs(2), oropharyngeal swab in VTM(1) nasal swabs(5) and throat swab(1). Conclusion: There was global developement of point of care tests on a war footing. The Indian states of Delhi, Maharashtra, Gujarat, Uttar Pradesh, Tamil Nadu, Karnataka, Haryana, Rajasthan, Kerala, Himachal Pradesh, Goa and Uttarakhand, were in the forefront of these developments, as also the USA, Belgium, Taiwan, Korea and South Korea.

Air pollution perception in ten countries during the COVID-19 pandemic.

As largely documented in the literature, the stark restrictions enforced worldwide in 2020 to curb the COVID-19 pandemic also curtailed the production of air pollutants to some extent. This study investigates the perception of the air pollution as assessed by individuals located in ten countries: Australia, Brazil, China, Ghana, India, Iran, Italy, Norway, South Africa and the USA. The perceptions towards air quality were evaluated by employing an online survey administered in May 2020. Participants (N = 9394) in the ten countries expressed their opinions according to a Likert-scale response. A reduction in pollutant concentration was clearly perceived, albeit to a different extent, by all populations. The survey participants located in India and Italy perceived the largest drop in the air pollution concentration; conversely, the smallest variation was perceived among Chinese and Norwegian respondents. Among all the demographic indicators considered, only gender proved to be statistically significant.

Impact of COVID-19 pandemic on mobility in ten countries and associated perceived risk for all transport modes.

The restrictive measures implemented in response to the COVID-19 pandemic have triggered sudden massive changes to travel behaviors of people all around the world. This study examines the individual mobility patterns for all transport modes (walk, bicycle, motorcycle, car driven alone, car driven in company, bus, subway, tram, train, airplane) before and during the restrictions adopted in ten countries on six continents: Australia, Brazil, China, Ghana, India, Iran, Italy, Norway, South Africa and the United States. This cross-country study also aims at understanding the predictors of protective behaviors related to the transport sector and COVID-19. Findings hinge upon an online survey conducted in May 2020 (N = 9,394). The empirical results quantify tremendous disruptions for both commuting and non-commuting travels, highlighting substantial reductions in the frequency of all types of trips and use of all modes. In terms of potential virus spread, airplanes and buses are perceived to be the riskiest transport modes, while avoidance of public transport is consistently found across the countries. According to the Protection Motivation Theory, the study sheds new light on the fact that two indicators, namely income inequality, expressed as Gini index, and the reported number of deaths due to COVID-19 per 100,000 inhabitants, aggravate respondents' perceptions. This research indicates that socio-economic inequality and morbidity are not only related to actual health risks, as well documented in the relevant literature, but also to the perceived risks. These findings document the global impact of the COVID-19 crisis as well as provide guidance for transportation practitioners in developing future strategies.

A survey dataset to evaluate the changes in mobility and transportation due to COVID-19 travel restrictions in Australia, Brazil, China, Ghana, India, Iran, Italy, Norway, South Africa, United States.

COVID-19 pandemic has heavily impacted the global community. To curb the viral transmission, travel restrictions have been enforced across the world. The dataset documents the mobility disruptions and the modal shifts that have occurred as a consequence of the restrictive measures implemented in ten countries: Australia, Brazil, China, Ghana, India, Iran, Italy, Norway, South Africa and the United States. An online questionnaire was distributed during the period from the 11st to the 31st of May 2020, with a total of 9 394 respondents. The first part of the survey has characterized the frequency of use of all transport modes before and during the enforcement of the restrictions, while the second part of the survey has dealt with perceived risks of contracting COVID-19 from different transport modes and perceived effectiveness of travel mitigation measures. Overall, the dataset (stored in a repository publicly available) can be conveniently used to quantify and understand the modal shifts and people's cognitive behavior towards travel due to COVID-19. The collected responses can be further analysed by considering other demographic and socioeconomic covariates.

Survey data regarding perceived air quality in Australia, Brazil, China, Ghana, India, Iran, Italy, Norway, South Africa, United States before and during Covid-19 restrictions.

The dataset deals with the air quality perceived by citizens before and during the enforcement of COVID-19 restrictions in ten countries around the world: Australia, Brazil, China, Ghana, India, Iran, Italy, Norway, South Africa and the United States. An online survey conveniently translated into Chinese, English, Italian, Norwegian, Persian, Portuguese collected information regarding the perceived quality of air pollution according to a Likert scale. The questionnaire was distributed between 11-05-2020 and 31-05-2020 and 9 394 respondents took part. Both the survey and the dataset (stored in a Microsoft Excel Worksheet) are available in a public repository. The collected data offer the people's subjective perspectives related to the objective improvement in air quality occurred during the COVID-19 restrictions. Furthermore, the dataset can be used for research studies involving the reduction in air pollution as experienced, to a different extent, by populations of all the ten countries.