The journey towards better healthcare sustainability in Asian nations demands a comprehensive investigation into the impact of urban governance, poverty, and female literacy on infant mortality rates. This study undertakes a rigorous exploration of these key factors to pave the way for evidence-based policy interventions, utilizing data from a panel of six selected Asian countries: Pakistan, China, India, Indonesia, Malaysia, and the Philippines, spanning the years 2001 to 2020. The findings reveal that adequate sanitation facilities, higher female literacy rates, and sustained economic growth contribute to a reduction in infant mortality. Conversely, increased poverty levels and limited women’s autonomy exacerbate the infant mortality rates observed in these countries. The Granger causality analysis validates the reciprocal relationship between urban sanitation (and poverty) and infant mortality rates. Furthermore, the study establishes a causal relationship where female literacy rates Granger-cause infant mortality rates, and conversely, infant mortality rates Granger-cause women’s autonomy in these countries. The variance decomposition analysis indicates that sustained economic growth, improved female literacy rates, and enhanced women’s empowerment will likely impact infant mortality rates in the coming decade. Consequently, in low-income regions where numerous children face potentially hazardous circumstances, it is imperative to allocate resources towards establishing and maintaining accessible fundamental knowledge regarding sanitation services, as this will aid in reducing infant mortality rates.
Poverty is a major challenge caused by various situations as well as cultural, social, economic, and political interactions. Therefore, poverty alleviation programs and strategies require an integrated approach carried out in consistent and organized stages. It required the participation of all parties, both regional heads, Regional People’s Representative Assembly (RPRA) members, entrepreneurs, and other elements of society. This study aimed to investigate the effect of local spending efficiency on public welfare in Indonesia, using a quantitative and explanatory method. The analysis method used in this study is the panel data regression model. The research population in all provinces in Indonesia was 34 provinces, and a purposive sampling method was used, where a total of 26 provinces were selected. The research period is 2017–2021. The efficiency of local spending (education, health, and infrastructure) is estimated using the Stochastic Frontier Analysis (SFA) cost function approach. The results showed that the higher the efficiency of education spending, the more it will increase public welfare in Indonesia. Meanwhile, the health spending efficiency and the infrastructure spending efficiency do not affect public welfare. The implications of this study for the development of science are that the efficient allocation of education spending will be able to improve the quality of education which is a long-term solution to overcome poverty in Indonesia and for policymakers to be able to optimize education spending to achieve the expected educational goals.
This paper tries to understand economic, social and legal implications of the introduction and usage of MediSearch (AI search engine) in the Indian healthcare context. Discussing the economic ramifications, the paper highlights the potential for cost savings, the influence on healthcare accessibility, and the shifts in traditional medical paradigms. On the social side, the study explains ability of AI based platforms to bridge healthcare disparities, with a potential for enhancing general health literacy among the general population. From a legal standpoint, study highlights the concerns related to data privacy, regulatory issues, and possible malpractice implications. With the integration of these perspectives, the study also explains opportunities, challenges and future of MediSearch from the Indian health perspective.
This study examines the relationship between macroeconomic determinants and education levels in eight selected African oil-exporting countries (AOECs) over the period 2000–2022. Drawing on human capital theory, the paper scrutinizes the impact of factors such as income inequality, health outcome, economic growth, human development, unemployment, education expenditure, institutional quality, and energy consumption on education levels. Employing robust estimation techniques such as fixed effects (FE), random effects (RE), pooled mean group (PMG) and cross-section autoregressive distributed lag model (CS-ARDL), the study unveils vital static and dynamic interactions among these determinants and education levels. Findings reveal notable positive and significant connections between education levels and some of the variables—human capital development, institutional quality, government expenditure on education, and energy consumption, while income inequality demonstrates a consistent negative relationship. Unexpectedly, health outcomes exhibit a negative impact on education levels, warranting further investigation. Furthermore, the analysis deepens understanding of long-run and short-run relationships, highlighting, for example, the contradictory impact of gross domestic product (GDP) and unemployment on education levels in AOECs. Finally, the study recommends targeted human development programs, enhanced public investment in education, institutional reforms for good governance, and sustainable energy infrastructure development.
The COVID-19 pandemic prompted global crises and enforced strict measures like the Movement Control Order (MCO) in Malaysia, significantly impacting societal norms, particularly affecting secondary school students. The current study employs a qualitative methodology to determine how COVID-19 affects the life stress experienced by secondary school students. Secondary school students were recruited in Sabah, Malaysia, from April to August 2022, after Malaysia entered the endemic phase on 1 April 2022. As part of a larger survey, students were asked to respond to an open-ended question about life stressors they face as a result of the pandemic COVID-19 or during home-based teaching and learning (PdPR). A total of 1069 secondary school students from various backgrounds were included in the study. However, only 714 students responded to the open-ended question. The pattern of meaning across the texts was determined using Birks and Mills’s method of multilevel coding. The students’ perspectives on life stressors were classified into five broad categories: restriction stress, emotional stress, online study stress, family-related stress, and others-related stress. Restriction stress, which refers to being confined at home, restricted movement, hampered family, friendship, and outdoor activities, and no freedom were rated as the most significant life stressors associated with the COVID-19 pandemic by students. This research provides valuable insights for policymakers, educators, and parents, emphasizing the profound effect of pandemic-induced restrictions on student life and the essential role of targeted interventions in fostering resilience among students.
Naturally occurring radionuclides can be categorized into two main groups: primordial and cosmogenic, based on their origin. Primordial radionuclides stem from the Earth’s crust, occurring either individually or as part of decay chains. Conversely, cosmogenic radionuclides originate from extraterrestrial sources such as space, the sun, and nuclear reactions involving cosmic radiation and the Earth’s atmosphere. Gamma-ray spectrometry is a widely employed method in Earth sciences for detecting naturally occurring radioactive materials (NORM). Its applications vary from environmental radiation monitoring to mining exploration, with a predominant focus on quantifying the content of uranium (U), thorium (Th), and potassium (K) in rocks and soils. These elements also serve as tracers in non-radioactive processes linked to NORM paragenesis. Furthermore, the heat generated by radioactive decay within rocks plays a pivotal role in deciphering the Earth’s thermal history and interpreting data concerning continental heat flux in geophysical investigations. This paper provides a concise overview of current analytical and measuring techniques, with an emphasis on state-of-the-art mass spectrometric procedures and decay measurements. Earth scientists constantly seek information on the chemical composition of rocks, sediments, minerals, and fluids to comprehend the vast array of geological and geochemical processes. The historical precedence of geochemists in pioneering novel analytical techniques, often preceding their commercial availability, underscores the significance of such advancements. Geochemical analysis has long relied on atomic spectrometric techniques, such as X-ray fluorescence spectrometry (XRFS), renowned for its precision in analyzing solid materials, particularly major and trace elements in geological samples. XRFS proves invaluable in determining the major constituents of silicate and other rock types. This review elucidates the historical development and methodology of these techniques while showcasing their common applications in various geoscience research endeavors. Ultimately, this review aims to furnish readers with a comprehensive understanding of the fundamental concepts and potential applications of XRF, HPGes, and related technologies in geosciences. Lastly, future research directions and challenges confronting these technologies are briefly discussed.
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