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Objectives: The aim of this study is to assess the occurrence, reasons, and consequences of Emergency Peripartum Hysterectomy (EPH) at a particular institution. It seeks to identify risk factors, examine complications, and offer insights for interventions to enhance maternal and fetal outcomes in obstetric emergencies. Methods: The study was conducted at a tertiary care centre and the data analysis covered a period of 1 year. This study retrospectively analyzed Emergency Peripartum Hysterectomy (EPH) cases at a specific institution, reviewing patient demographics, obstetric history, booking status, referral patterns, EPH indications, delivery mode, and maternal-fetal outcomes. Results: The study revealed that the majority of patients (80.3%) belonged to rural backgrounds, with 89.3% being unbooked cases. Furthermore, 64.3% of cases were referred, and 85.7% of patients were in the P2,3,4 group. The most common indication for Emergency Peripartum Hysterectomy (EPH) was uterine rupture (53.6%), with a statistically significant association between the type of hysterectomy and indications for EPH (P value < 0.05). Subtotal hysterectomy was performed in 82.1% of cases, and maternal complications included febrile illness (51.8%) and wound infection (37.5%). Conclusion: This study highlights the imperative to address the elevated incidence of Emergency Peripartum Hysterectomy (EPH) in rural healthcare in India. The findings stress the pressing need for targeted interventions, including improving female literacy, increasing contraception prevalence, and enhancing antenatal care accessibility and quality. Strengthening peripheral healthcare, ensuring timely referrals for high-risk pregnancies, and proper documentation are essential for mitigating maternal morbidity, mortality, and foetal complications. [ABSTRACT FROM AUTHOR]

Background: The health challenges faced by the homeless are widely unaccounted for in the global south. In India, the lack of a primary healthcare sector in urban areas has led informal healthcare providers, such as Street Medicine, to step in. Methods: By compiling data collected by the Centre for Equity Studies’ Street Medicine teams from June 2016 to October 2018 (n =16,635), this study provides the first empirical assessment of the homeless disease burden in a global south country, while limited to only the people experiencing homelessness that the teams treat, hence being a burden of treatment. Our analysis quantifies this burden among those who seek care from Street Medicine teams and identifies variations in this burden’s distribution across demography and time. Results: The majority (n = 13,557; 81.5%) of Street Medicine cases can be attributed to 19 diagnoses or symptoms, which are mostly therapeuticallysimple conditions. The distribution of disease seems to be affected by different configurations of three characteristics: demographics (age and sex), urban geography (where homeless reside), and season. Conclusion: The Street Medicine teams must reflect on the balance they wish to achieve by addressing the relatively common and mild conditions documented in the dataset, and more severe and established diseases within homeless communities. Rapid diagnostic tests for resource-constrained settings could be integrated into Street Medicine practice in order to strengthen the data on which resource allocation decisions are made and improve assessments of homeless disease burden. [ABSTRACT FROM AUTHOR]

To deliver the full science potential of the square kilometer array (SKA) telescope, several SKA regional centres (SRCs) will be required to be constructed in different SKA member countries around the world. These SRCs will provide high performance compute and storage, for the generation, of advanced science data products from the basic data streams generated by the SKA science data handling and processing system, critically necessary to the success of the key science projects to be carried out by the SKA user community. They will also provide support to astronomers to enable them to carry out analysis on very large SKA datasets. Construction of such large data centre is a technical challenge for all SKA member nations. In such a situation, each country plans to construct a smaller SRC over the next few years (2022 onwards), known as a proto-SRC. In India, we propose to construct a proto-SRC, which will be used for the analysis of data from SKA pathfinders and precursors with strong Indian involvement, such as uGMRT, Meerkat and MWA. We describe our thinking on some aspects of the the storage, compute and network of the proto-SRC and how it will be used for data analysis as well as for carrying out various simulations related to SKA key science projects led by Indian astronomers. We also present our thoughts on how the proto-SRC plans to evaluate emerging hardware and software technologies and to also begin software development in areas of relevance to SKA data processing and analysis, such as algorithm implementation, pipeline development and data visualisation software. [ABSTRACT FROM AUTHOR]

Farming has a plethora of difficult responsibilities, and plant monitoring is one of them. There is also an urgent need to increase the number of alternative techniques for detecting plant diseases, which is now lacking. The agriculture and agricultural support sectors in India provide employment for the great majority of the country's people. In India, the agricultural production of the country is directly connected to the country's economic growth rate. In order to sustain healthy plant development, a variety of processes must be followed, including consideration of environmental factors and water supply management for the optimal production of crops. It is inefficient and uncertain in its outcomes to use the traditional method of watering a lawn. The devastation of more than 18% of the world's agricultural produce is caused by disease attacks on an annual basis. Because it is difficult to execute these activities manually, identifying plant diseases is essential to decreasing losses in the agricultural product business. In addition to diagnosing a wide range of plant ailments, our method also includes the identification of infections as a prophylactic step. Below is a detailed description of a farm-based module that includes numerous cloud data centers and data conversion devices for accurately monitoring and managing farm information and environmental elements. This procedure involves imaging the plant's visually obvious signs in order to identify disease. It is recommended that the therapy be used in conjunction with an application to minimize any harm. Increased productivity as a result of the suggested approach would help both the agricultural and irrigation sectors. The plant area module is fitted with a mobile camera that captures images of all of the plants in the area, and all of the plants' information is saved in a database, which is accessible from any computer with Internet access. It is planned to record information on the plant's name, the type of illness that has been afflicted, and an image of the plant. In a wide range of applications, bots are used to collect images of various plants as well as to prevent disease transmission. To ensure that all information given is retained on the Internet, data is collected and stored in cloud storage as it becomes essential to regulate the condition. According to our findings from our research on wide images of healthy and ill fruit and plant leaves, real-time diagnosis of plant leaf diseases may be done with 98.78% accuracy in a laboratory environment. We utilized 40,000 photographs and then analyzed 10,000 photos to construct a DCDM deep learning model, which was then used to train additional models on the data set. Using a cloud-based image diagnostic and classification service, consumers may receive information about their condition in less than a second on average, with the process requiring only 0.349 s on average. [ABSTRACT FROM AUTHOR]

Background & objectives: The World Health Organisation recommended immediate initiation of antiretroviral therapy (ART) in all adult human immunodeficiency virus (HIV) patients regardless of their CD4 cell count. This study was undertaken to ascertain the cost-effectiveness of implementation of these guidelines in India. Methods: A Markov model was developed to assess the lifetime costs and health outcomes of three scenarios for initiation of ART treatment at varying CD4 cell count <350/mm³, <500/mm³ and test and treat using health system perspective using life-time horizon. A few input parameters for this model namely, transition probabilities from one stage to another stage of HIV and incidence rates of TB were calculated from the data of Centre of Excellence for HIV treatment and care, Chandigarh; whereas, other parameters were obtained from the published literature. Total HIV-related deaths averted, HIV infections averted and incremental cost-effectiveness ratio per quality adjusted life years (QALYs) gained were calculated. Result: Test and treat intervention slowed down the progression of disease and averted 18,386 HIV-related deaths, over lifetime horizon. It also averted 16,105 new HIV infections and saved 343,172 QALYs as compared to the strategy of starting ART at CD4 cell count of 500/mm³. Incremental cost per QALY gained for the immediate initiation of ART as compared to ART at CD4 cell count of 500/mm³ and 350/mm³ was ₹ 46,599 and 80,050, respectively at reported rates of adherence to the therapy. Interpretation & conclusions: Immediate ART (test and treat) is highly cost-effective strategy over the past criteria of delayed therapy in India. Cost-effectiveness of this policy is largely because of reduction in the transmission of HIV. [ABSTRACT FROM AUTHOR]

The heatwave is a disastrous hazard having significant impacts on health and society. This study analyses the heatwave hazards and risk for India's current and future scenarios using socioeconomic vulnerability and temperature datasets during the summer (April–June) season. The Census of India (CoI) 2011 datasets were considered to assess current vulnerability and projected from the SocioEconomic Data And Application Center (SEDAC) population at Shared Socioeconomic Pathway (SSP) 4 for future vulnerability. Whereas IMD temperature data used for hazard assessment for the present scenario (1958–2005) while projected temperature data from regional earth system model REMO-OASIS-MPIOM (ROM) were used for the future (2006–2099) scenario. The study exhibited the most hazardous, vulnerable, and risk-prone regions identified as the south-eastern coast and Indo-Gangetic plains and some populous districts with metropolitan regions (Mumbai, Delhi, and Kolkata) under the current scenario. The coupled model ROM has efficiently captured the critical districts with higher and lower risk, showing its future projection capability. The study highlighted that the heatwave hazard-risk would significantly worsen in future scenarios in all districts under enhanced global warming and largely affecting the districts in the eastern and middle Indo-Gangetic plains and Malabar region. The present study will provide sufficient insights into designing mitigation strategies and future adaptive planning for the heatwave risk, which is one of the targets under Sustainable Development Goal 13 (Goal 13: Climate Action). • The present and future vulnerability and risk are assessed over India using a regional earth system model ROM. • The ROM efficiently captured the high and low heatwave risk districts of India. • Southern coastal regions and Indo-Gangetic plains are at higher risk during the baseline period 1980–2005. • The heatwave risk will exacerbate in all districts of India with the highest increment over Indo-Gangetic plains. [ABSTRACT FROM AUTHOR]