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Background: In the past decade, scrub typhus cases have been reported across India, even in regions that had no previous history of the disease. In the North-East Indian state of Mizoram, scrub typhus cases were first recorded only in 2012. However, in the last five years, the state has seen a substantial increase in the scrub typhus and other rickettsial infections. As part of the public health response, the Mizoram Government has integrated screening and line listing of scrub typhus and other rickettsial infections across all its health settings, a first in India. Here we detail the epidemiology of scrub typhus and other rickettsial infections from 2018–2022, systematically recorded across the state of Mizoram. Methodology/principal findings: The line-listed data positive for scrub typhus and other rickettsial infections identified by rapid immunochromatographic test and/or Weil-Felix test from 2018–22 was used for the analysis. During this period, 22,914 cases of rickettsial infections were recorded, out of which 19,651 were scrub typhus cases. Aizawl is the worst affected, with 10,580 cases (46.17%). The average incidence of rickettsial infections is 3.54 cases per 1000 persons-year, and the case fatality rate is 0.35. Only ∼2% of the reported scrub typhus cases had eschar. Multivariate logistic regression analysis indicate patients with eschar (aOR = 2.5, p<0.05), occupational workers [farmers (aOR:3.9), businessmen (aOR:1.8), construction workers (aOR:17.9); p<0.05], and children (≤10 years) (aOR = 5.4, p<0.05) have higher odds of death due to rickettsial infections. Conclusion: The integration of systematic surveillance and recording of rickettsial diseases across Mizoram has shed important insights into their prevalence, morbidity, and mortality. This study underscores the importance of active surveillance of rickettsial infections across India, as the burden could be substantially higher, and is probably going undetected. Author summary: Even though scrub typhus and other rickettsial infections are continuously being recorded across India, there has been no systematic surveillance and reporting of the disease in any state. Mizoram, the North-East Indian state sandwiched between Bangladesh and Myanmar has integrated screening and systematic line listing of rickettsial infections across all its health centers. An important outcome of this effort is the very low case fatality rate (CFR); at 0.35, the CFR of rickettsial infections in Mizoram is very low when compared to the median CFR of ∼6% reported from other locations. These findings could serve as a template that could be replicated in other regions across India to prevent and control this neglected disease of huge public health importance. [ABSTRACT FROM AUTHOR]

With the wave of digitalisation, institutions across countries are pushing for the creation of open data and their governance. FAIR Data Principles have initiated the publishing of open research data to the key stakeholders and practitioners in the low- and middle-income countries to meet their developmental goals through practical usage in problem-solving. Open Data, which is part of the Open Science movement, has transformed the regime structure at a transnational level for the governance of critical issues surrounding water and energy. This paper provides a baseline survey to look into the various open data initiatives in the areas of water and clean energy across countries in general and India in particular. Given the multifaceted challenges around the water-energy nexus existing in India, it is critical to identifying the open data initiatives and studying their governance at the country level. Since governance requires the participation of various institutions and multiple stakeholders, the research aims at highlighting the various initiatives such as participation of institutions and the application of Creative Commons (CC) licensing terms in the open data governance for clean energy and water sectors in India. [ABSTRACT FROM AUTHOR]

Background: Childhood trauma encompasses neglect, abuse, abandonment, witnessing abuse, and having mentally ill and/or parent(s) engaged in substance abuse. Survivors of trauma are more likely to report insecure attachment styles. Thus, the current study aimed to investigate the indirect pathways underlying the relationship between childhood trauma and romantic attachment among adults in India. Methods: This study used a correlational research design and a cross-sectional, survey method for data collection. The data were collected through an online survey in Tier 1 cities in India. A total of 397 responses were collected using purposive sampling, from which 104 respondents were selected after data cleaning. The research tools included the childhood trauma questionnaire–short-form, the experience in close relationship scale, Rosenberg’s self-esteem scale, and trust in close relationships scale. Descriptive and inferential analysis was done using SPSS software, version 25. Pearson correlation coefficient, regression analysis, and mediation analysis were done to analyze data. Results: The results indicated a high level of trauma in the participants, and consequently, insecure romantic attachment styles, and also low levels of trust at a 0.05 significance level. Self-esteem had a significant negative correlation with romantic attachment (r=-0.225, P=0.001), but did not mediate the relationship between childhood trauma and romantic attachment. Trust also had a significant negative correlation with romantic attachment (r=-0.312, P=0.001) and also mediated the relationship between childhood trauma and romantic attachment (β=0.102, P=0.041). Conclusion: This study provides evidence that childhood trauma affects romantic attachment, self-esteem, and trust. In light of these findings, therapists should adopt an integrated approach that addresses these interconnected variables through trauma-focused, attachment-focused, and evidence-based therapies to help trauma survivors. Since trust was identified as a mediating factor in the relationship between childhood trauma and romantic attachment, it provides a novel insight for therapists to prioritize interventions that focus on building trust. [ABSTRACT FROM AUTHOR]

We develop an enhanced accident occurrence prediction model which depends on the heterogeneous ensemble learning to tackle the topic of a accident period prediction in the early stages of the tragedy using millions of the traffic accident information's from the India. In order to start with, we concentrate on the early stages of development of accidents and choose few useful data from five categories: location, the traffic, climate, objects, and the time field. Further, we implement data cleansing, processing of outlier, and the missing value of processing to raise the quality of the data. Data mining methods can support in foreseeing the factors that are influential in concern to make severe damages. The research has significant factors that are closely connected through the severity of accidents on thruways are identified by Random Forest. Top elements influencing unintentional seriousness include temperature, distance, wind Chills, moisture, direction of wind and visibility. The main aim of this research work is to give a architecture to anticipate road crashes gathering data from the social media handles and the open access data, by implementing a ensembled Deep Learning Model. After which the result shows decent outcomes as a resort to the problem and fulfills the objective of prediction model based on algorithms and deep Learning models. [ABSTRACT FROM AUTHOR]

Business management teaching schools (B-schools) are one of the fastest growing sectors in the realm of higher education in India. Knowledge sharing is an integral part of educational organizations. The concepts of knowledge sharing and turnover intention show that these are complex behaviors that more often than not surprise the research community by showing "chalk and cheese" results. Both these variables have been widely investigated as an antecedent to the turnover intention in the existing literature, but, surprisingly, the mediating effect of job satisfaction on knowledge sharing and, thereafter, the employee's turnover intention has been relatively less investigated. This study examined the mediating effect of job satisfaction on knowledge sharing and turnover intention of the faculty in Indian B-schools. Data was collected using the convenience sampling method across five states in India. After data cleansing, 339 responses were analyzed through factor analysis and correlational analysis. Furthermore, path analysis was used to test the mediating effect of job satisfaction. The findings suggested a positive correlation between job satisfaction and knowledge sharing and an inverse correlation between both the variables and turnover intention. Path analysis also showed that knowledge sharing was enhanced through job satisfaction, whereas turnover intention was reduced significantly. [ABSTRACT FROM AUTHOR]