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INTRODUCTION: Tribal entrepreneurship can be understood as infusing the knowledge of commerce and trade into the tribal groups and thereby exploring their products and known for their economic betterment and social advancement. An accumulating body of research has demonstrated that artificial intelligence (AI) is an indistinguishable feature of the fourth industrial revolution. This study integrates the literature on AI and new technologies to examine the constraining and facilitating forces for developing and scaling-up AI-enabling technologies in Africa. This article proposes an integrated conceptual model to elucidate the range of external drivers encompassing global competitive drivers, and market and industry drivers. The internal drivers include the potential to enhance product development speed, improve quality, drive production cost down, and minimise errors and manual processes in organisations. OBJECTIVES: In this study, socio-economic status of tribal population has been taken as a reference in order to see whether there is any impact of economic wellbeing on their livelihood [1]. The study is an endeavour to examine the role of micro enterprises for social and economic empowerment of tribal community in Odisha and Andhra Pradesh and role of AI. RESULTS: The main results obtained in this paper are the following SEM identified that there is a lower degree of positive impact of "Tribal entrepreneurship" on "Economic Empowerment" and "women Empowerment" and lower degree of negative impact on "Social Empowerment". It is also concluded that Economic Empowerment of tribal entrepreneurs through micro-enterprises has reduced the dependency on private money lenders the most. Women Empowerment of tribal entrepreneurs has helped the women to achieve gender equality and the social Empowerment aids in the development of competency and technical skills through micro-enterprises. CONCLUSION: The tribal communities in Odisha are regarded as the most disadvantageous group of people in terms of their socio-economic status. The present research makes some pivotal contributions to the current AI literature. First, in spite of the growing recognition that development of new industries and new-business development is increasingly predicated on the adoption of new technologies (Krasniqi and Hajrizi Citation2016), there is a paucity of studies examining contemporary challenges faced by developing nations and their inability to capitalise on such ample and obvious opportunities. [ABSTRACT FROM AUTHOR]

Modeling surface water quality has become crucial in providing better strategies for managing surface water resources, and adequate findings need accurate and geographically dispersed data. Hydrogeological modeling of these data sets is possible using empirically-based models. The other statistical models are also an alternative approach. In this study, a process with maximum probability is considered with the help of machine learning tools (MLT) to have optimized and valid output. The proposed method combines remote sensing and geographic information systems (RS and GIS) and MLT, which are appropriate for the predicament of neither small, large scale, nor long-term simulations. MLT methods such as VAR and ARIMA are developed in the Python programming with Jupyter notebook and tested according to the data in the spatial prediction for surface water quality parameters such as Tr, pH, Ec, TDS, AL, Ca++, NO−3, So, Cl, F−, Fe, and Mg2+ in the Krishna District, Andhra Pradesh, India—lower delta part. The delta with susceptible zones was identified using RS and GIS as those areas are prone to direct exposure to surface water contaminants from aquaculture, agricultural runoff, small- and medium-scale businesses, and household trash. Achieving effective surface water management for this ecosystem is critical for regional water management. The geographical information about the concentrations acquired via the RS and GIS was compared to the statistical modeling findings and verified using real-time measurements. MLT modeling seems more realistic than the experimental setting; data from the previous 20 years (2000–2020) were used for modeling, and the predicted values presented in the paper are predicted for the year 2021. The computed R2 value of ranges between 0.75 and 0.96% is recorded with ARIMA, and VAR posted range between 0.56 and 0.75% with the trained and tested data. The findings show the potential for MLT of geographically dispersed hydrogeological data to be used for pollution-free surface water management. From the surface water management perspective, combining RS and GIS and MLT offers an alternate data analysis approach for obtaining quick results utilizing a less laborious process that produces acceptable results. [ABSTRACT FROM AUTHOR]

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Cement clay interlocking (CCI) hollow bricks have been used as a construction material in many developed and developing countries. Many emerging and underdeveloped nations have utilised cement clay interlocking (CCI) hollow bricks as building materials. In India, Andhra Pradesh local makers prepare these cement clay interlocking (CCI) hollow bricks by simply mixing clay, cement, and sand in a traditional method, without following strict design criteria or rules. Previous research has demonstrated that the mechanical characteristics of CCI hollow bricks gathered from various locations in detailed manner respect to hand books on Civil Engineering as per Indian Standards. Bricks from one region had compressive strengths that were significantly lower than the other region Indian Community Standards. Various methods were employed in this investigation to enhance the mechanical characteristics of CCI bricks. New mix patterns were created with the use of sand, cement, and fly ash in this research paper. [ABSTRACT FROM AUTHOR]

The Covid-19 pandemic is the most recent—and most severe—crisis to face the microfinance/financial inclusion sector, but it was far from the first. From its earliest years, crises have appeared throughout the modern history of microfinance, and the responses they engendered have included some of the most significant reforms and innovations in the sector. In this paper, we describe selected historical crises—Peru in the 1980s, Grameen in the 1990s, and Andhra Pradesh and others in the 2007–2010 period—through their legacy and impact on the sector's activities and priorities. We then examine some of the pressures on institutions during the pandemic, through interview data with MFI leaders from the Sentinel Project conducted during 2021–22. We argue that the resilience of the sector to the unprecedented pressures of the pandemic can be traced to many of these historical post-crisis reforms—and consider what this means for future crisis responses. [ABSTRACT FROM AUTHOR]

Background: Coastal areas are subject to various anthropogenic and natural influences. In this study, we investigated and compared the characteristics of two coastal regions, Andhra Pradesh (AP) and Goa (GA), focusing on pollution, anthropogenic activities, and recreational impacts. We explored three main factors influencing the differences between these coastlines: The Bay of Bengal's shallower depth and lower salinity; upwelling phenomena due to the thermocline in the Arabian Sea; and high tides that can cause strong currents that transport pollutants and debris. Results: The microbial diversity in GA was significantly higher than that in AP, which might be attributed to differences in temperature, soil type, and vegetation cover. 16S rRNA amplicon sequencing and bioinformatics analysis indicated the presence of diverse microbial phyla, including candidate phyla radiation (CPR). Statistical analysis, random forest regression, and supervised machine learning models classification confirm the diversity of the microbiome accurately. Furthermore, we have identified 450 cultures of heterotrophic, biotechnologically important bacteria. Some strains were identified as novel taxa based on 16S rRNA gene sequencing, showing promising potential for further study. Conclusion: Thus, our study provides valuable insights into the microbial diversity and pollution levels of coastal areas in AP and GA. These findings contribute to a better understanding of the impact of anthropogenic activities and climate variations on biology of coastal ecosystems and biodiversity. [ABSTRACT FROM AUTHOR]

A house can be defined as an interpretation of perceptions of the society, inculcated within it, in a direct or indirect method. The social cycle of creation of space depends on parameters of site, settings, cultural history, and traditions. Therefore, it’s not only the house form or architectural elements of the space, which encapsulates the whole idea behind its invention but also the symbolic dimension added to it, defining its significance and identity. The study analyses the association of toy-making process of Kondapalli Village (Andhra Pradesh) with its impact on the built environment of the inhabitants over years. The following study attempts to analyze the toy-making process of Kondapalli Village and its impact on the built environment of the houses. The study is threefold, firstly it attempts to understand the traditional knowledge in the process of wooden toy making in Kondapalli; secondly, the spatial analysis of different house forms ranging from vernacular to modern house and their inter-relationship with the art form deduced to examine the sequential evolution of forms and functions; lastly, an establishment of the symbolic relationship of the toy-making process with the community. Therefore, the study helps to analyse and establish an inter-connection between the house forms, occupational practices and the community. [ABSTRACT FROM AUTHOR]

Background: Children form the most vulnerable strata of the society and the tobacco industry is known to target them. Article 16 of the Framework Convention of Tobacco Control (FCTC) calls for prohibition of tobacco sales to and by minors. Although interventions to stop such sales are based on sound science, it is widely acknowledged that many countries find implementation, full of challenges. In India, sales near educational institutions are banned by law, Section 6b of the Cigarettes & Other Tobacco Products Act (COTPA). We conducted a survey of violations in four states [Andhra Pradesh (AP), Karnataka (KA), Meghalaya (ML), Uttar Pradesh (UP)] of India to report the number of violations and to assess if there was an association between the schools with violations and variables such as gender, size, category, location of schools. Methods: Schools in these States were asked to report the number of shops selling tobacco within 100 yards on an App circulated to all schools (289,392 in number). Chi-square tests, univariate and multivariate logistic regression performed to find association between schools with violations by Category of School, Size of School, Gender of students and location (Urban/Rural). Findings: Responses were received from 61,748 (21.3%) schools of which 16,193 (26.2%) reported violations. It was observed that the percentages of the schools with violations were similar to the prevalence of tobacco usage in the state. Four states AP, KA, ML, UP reported violations 22.2%, 17.5%, 42.9% and 31.4% respectively. On chi-square tests, there was a significant association for the states of KA and ML with regards to variables like size, category, location of schools (p-value <0.001). For AP, all variables were significantly different (p-value <0.001) while for UP variables like size and gender were significant. On logistic regression, there was significant association between the variables like size (>100), category (Upper Primary) and location (urban) for tobacco shops violations in both KA and ML except for the school category that was secondary in ML. While for AP and UP, only size (>100), location (urban) of schools have a significant association with the violations of tobacco shops. Logistic regression of pooled data of four states school size (>100) and school category (primary) and location (urban) had significantly higher association of violation of tobacco shops. Interpretation: This is the first large survey with responses from almost all parts of the four states in India. This study shows significant association with the size, category and location of schools. We anticipate that the lists of schools which have such violations can be used by enforcement agencies to take focused action. Such models will help develop effective tobacco control policies in developing countries with large populations where implementation remains a big challenge. [ABSTRACT FROM AUTHOR]

Purpose: According to the 4th and 5th rounds of National Family Health Survey (NFHS), there is high prevalence of hysterectomies in the three states of Andhra Pradesh Telangana and Bihar. The three said states have more than double the number of hysterectomies taking place than the national average. Our purpose is to analyse whether these rates are increasing, decreasing or have stabilized and their reasons thereof. Such an analyses will help the policy makers in recommending good clinical practices within their states. Material and methods: We used data from NFHS-4 (2015-16) and NFHS-5 (2019-2021) rounds. We calculated the differences in predicted probabilities for various factors, performed a Fairlie Decomposition analyses to quantify the positive and negative contributors in the prevalence of hysterectomy across the three states over two time points, and assessed the association of various socio-demographic characteristics to hysterectomy through a multilevel logistic regression model. Results and conclusion: The results show that out of a total of 80,976 eligible respondents from the states under study, 5826 respondents self-reported that they had a hysterectomy done. It was found that older age, living in rural areas, belonging to other backward classes and higher wealth quintile, and higher parity positively contributed to the increased prevalence of hysterectomies in the three states. Higher educational attainment and previous use of family planning methods acted as protective factors. Characteristics at the household level had the highest intra-class correlation value in the prevalence of hysterectomy among women, followed by the Primary Sampling Unit and District levels, indicating high clustering in the prevalence of hysterectomy at the household level in all three states. Heavy menstrual bleeding/pain was the leading cause of hysterectomies in all three states, followed by fibroids/cysts in Andhra Pradesh and Telangana and Uterine disorder/ prolapse in Bihar. Over 80% of hysterectomies took place in the private hospitals. Recommendations: The study recommends better, more efficient and accountable hysterectomy surveillance to ensure more sustainable woman's reproductive health services in India. Government should adopt and implement standard regulatory guidelines to prevent provider-driven avoidable hysterectomies. Moreover, we recommend informing primary care professionals about the long-term health effects of hysterectomy and promoting alternate therapies for treating uterine fibroids and heavy bleeding. [ABSTRACT FROM AUTHOR]

Introduction: The Coronavirus Disease-2019 (COVID-19) pandemic, which started in December 2019, has rapidly spread across the globe. Although the prevalence of COVID-19 disease has significantly decreased, there are cases of post-COVID-19 complications affecting multiple organ systems, including the eyes. Aim: To evaluate ocular diseases presenting in post-COVID-19 patients and their association with demographic profiles, duration of post-COVID-19, and the type of treatment received. Materials and Methods: A descriptive cross-sectional study was conducted over a four-month period (August 2021 to November 2021) in the Department of Ophthalmology at AIIMS, Mangalagiri, Guntur, Andhra Pradesh, India. The study focused on post-COVID-19 patients who had been affected by COVID-19 no more than three months prior. Patients who were not post-COVID-19 and those who had contracted COVID-19 during the first wave were excluded from the study. The patients' clinical history and symptoms were documented. Visual acuity, intraocular pressure, and detailed anterior and posterior segment findings were recorded for all patients. The study aimed to assess post-COVID-19 ocular complications and any potential associations with hospital stays, steroid intake, or oxygen inhalation on eye diseases. Mean and median calculations were performed for continuous variables, and a Chi-square test was used to study associations. Statistical Package for Social Sciences (SPSS) version 25.0 was employed, and a p-value <0.05 was deemed significant. Results: In the present study, males constituted 41 (62.1%) and females constituted 25 (37.9%), with a male-to-female ratio of 1.64:1. The majority of patients 23 (34.8%) were above 50 years old. Most patients 24 (36.4%) developed eye diseases one month after their COVID-19 infection. Out of 66 patients, 11 (16.7%) were diabetic, 8 (12.1%) were hypertensive, and 40 (60.6%) had no associated co-morbidities. During their COVID-19 illness, 53 (80.3%) patients underwent home isolation and received supportive treatment, while 13 (19.7%) patients were hospitalised. The most common ocular disease observed was conjunctivitis 39 (59.1% of patients) following post-COVID-19. Additionally, 4 (6%) patients developed central serous chorioretinopathy, 4 (6%) developed refractive errors, 5 (7.6%) experienced persistent headaches, and 2 (3%) developed orbital mucormycosis. Conclusion: The present study presents ophthalmic manifestations in post-COVID-19 patients. Conjunctivitis was found to be the most common ocular disease, more prevalent one month after the COVID-19 infection. COVID-19 retinopathy was the most common posterior segment complication, especially in patients above 50 years old and three months post-COVID-19. [ABSTRACT FROM AUTHOR]

Purpose: The World Report on Vision highlights that health information systems (HIS) should collect information on the determinants of eye conditions and vision impairment (VI) as a step toward integrated people-centered eye care (IPEC). Thus, this retrospective study aims to elucidate VI trends across age and gender of the patients who visited our centres in southern and eastern India. Methods: Electronic medical records of all new patients who visited the network were included. VI was defined as visual acuity less than 6/12; unilateral VI was based on the worse presenting eye (the other eye being normal), and bilateral VI was based on the better eye. "Total VI" includes both unilateral and bilateral VI. Results: The records of 7,31,307 patients from January to December 2019 were extracted. Males were 54%. The mean age was 40 years (SD: 19.16 years). The majority of patients (46.54%) visited a primary care centre. Centres in Andhra Pradesh saw the largest number of patients (46%). Approximately 65% of all patients presented had no VI in either eye. Total VI was 23.5% at the primary-centre level and approximately 45% at other levels, the highest being in Odisha. More females accessed care at primary and secondary centres (46.6%) than at higher levels of care (44%). Odisha had the lowest number of females accessing care (43.01%). Conclusion: Non-visually impairing conditions form an important reason for patients visiting our eye care facilities. Strategies focusing on improving access to eye care for females should be planned at all levels, especially in Odisha. [ABSTRACT FROM AUTHOR]

Agriculture is significantly impacted by the variability in weather patterns, imposing substantial constraints on farmers’ ability to make informed tactical and strategic decisions regarding their crops. Seasonal climate projections have shown potential for informing agricultural decisions, but the actual adoption of climate information by farmers has been relatively slow and limited. The present study was conducted with the objective of investigating the characteristics of adopters, the communication network, and the level of farmer’s satisfaction concerning the adoption and continued use of Agromet Advisories Services (AAS). Two semi-arid districts, namely Kurnool and Anantapur in Andhra Pradesh, were purposively selected, wherein 280 farmers constituted the sampling frame. In this study, social network analysis (SNA) was conducted to examine the peer-to-peer communication patterns, while importance-performance analysis (IPA) was employed to evaluate farmer’s satisfaction, contributing to the continued adoption of AAS. The findings revealed that with regard to personality and communication characteristics, farmers were in the low category for their ability to cope with uncertainties and risk and even for their information-seeking behavior. Furthermore, the results showed farmers to be highly satisfied with the overall adoption of AAS. However, the IPA matrix revealed that among the nine attributes, the credibility of the forecasts needed refinement to promote sustained adoption. Excessive emphasis was placed on attributes such as the frequency of forecasts, which could be channeled into other initiatives. Peer-to-peer communication emerged as a crucial strategy in the adoption of AAS. Governments, non-governmental organizations, and extension functionaries should make a concerted effort to enhance the continued adoption of AAS by involving local stakeholders in sharing and participating in climate information production, forming farmer’s groups, and focusing on farmers’ literacy toward AAS. [ABSTRACT FROM AUTHOR]