Urban Churches Show an Increase in Attendance, Donations, and Finances During the COVID-19 Pandemic in the USA: Evidence from the United Methodist Church.

The COVID-19 pandemic has had a significant impact on religion and its practice. This paper aims to examine how the pandemic affects religious activities, donations, and finances over time and across regions within the United Methodist Church (UMC) in the USA. To address this question, we analyze survey data collected during the pandemic from 2963 churches in the USA by United Methodist Communications. Our analysis utilizes several quantitative techniques, including Z-tests, one-way analysis of variance (ANOVA), and multinomial logistic regressions. The results indicate a decrease in church attendance over time, with a more pronounced effect observed in non-urban areas (suburban, small town, and rural). Similarly, while church donations and finances mitigate over time across churches, churches in urban areas experience a quicker rebound compared to those in non-urban areas. Lastly, we find that church attendance and donations positively affect finances. These findings hold important implications for churches in various regions, offering insights to develop strategies for navigating the challenges posed by the COVID-19 pandemic.

ChatGPT in finance: Applications, challenges, and solutions.

The emergence of ChatGPT, a generative artificial intelligence tool, has sparked a revolution in the finance industry, enabling individuals to interact with technology in natural language. However, the use of ChatGPT in finance presents a profound array of ethical considerations that demand careful scrutiny to ensure its responsible and ethical use. After a concise exploration of ChatGPT's applications in finance, this policy article delves into the ethical challenges arising from the use of ChatGPT in finance, including outcomes contaminated with biases, incorporation of fake information in the financial decisions, concerns surrounding privacy and security, lack of transparency and accountability in the decision-making processes and financial services, human job displacement, and the intricate web of legal complexities. Our article asserts that financial institutions employing ChatGPT must proactively devise strategies to confront these burgeoning challenges, mitigating their adverse effects on both individuals and society as a whole. Additionally, we propose relevant policies to tackle these ethical quandaries head-on. In essence, this article illuminates the imperative need for a meticulous ethical framework, facilitating an informed and responsible use of ChatGPT in the realm of finance, safeguarding the welfare of individuals and society. While our work significantly contributes to the research and practice of finance, we also identify future research avenues.

Investigating the relationship of COVID-19 preventive and mitigation measures with mosque attendance in Pakistan.

Social distancing served as a principal strategy to curtail the spread of COVID-19. However, congregational activities in mosques made it challenging to practice social distancing and led to a rapid surge in virus infections in several Muslim countries. This study uses nationally representative cross-sectional data from Pakistan, a Muslim-majority country, to examine the relationship of practicing preventive measures (such as social distancing, wearing mask and hand washing) and mitigation measures (like avoid going to the market, social gatherings, healthcare seeking, use of public transport, and long-distance travel) with mosque visits by utilizing logistic regressions. The results show that individuals adhering to preventive and mitigation measures also avoid visiting mosques and other religious gatherings. From a policy perspective, these results suggest that the government of Pakistan can avoid direct religious confrontation when it needs to minimize mosque visits to curtail the spread of the virus by implementing preventive and mitigation measures.

When neuro-robots go wrong: A review.

Neuro-robots are a class of autonomous machines that, in their architecture, mimic aspects of the human brain and cognition. As such, they represent unique artifacts created by humans based on human understanding of healthy human brains. European Union's Convention on Roboethics 2025 states that the design of all robots (including neuro-robots) must include provisions for the complete traceability of the robots' actions, analogous to an aircraft's flight data recorder. At the same time, one can anticipate rising instances of neuro-robotic failure, as they operate on imperfect data in real environments, and the underlying AI behind such neuro-robots has yet to achieve explainability. This paper reviews the trajectory of the technology used in neuro-robots and accompanying failures. The failures demand an explanation. While drawing on existing explainable AI research, we argue explainability in AI limits the same in neuro-robots. In order to make robots more explainable, we suggest potential pathways for future research.

Estimating a panel MSK dataset for comparative analyses of national absorptive capacity systems, economic growth, and development in low and middle income countries.

Within the national innovation system literature, the low- and middle-income countries (LMICs) eligible for the World Bank's International Development Association (IDA) support, are rarely part of empirical discourses on growth, development, and innovation. One major issue hindering empirical analyses in LMICs is the lack of complete data availability. This work offers a new full panel dataset with no missing values for IDA-eligible LMICs. I use a standard, widely respected multiple imputation method (specifically, Predictive Mean Matching) developed by Rubin in the 1980s, which conforms to the structure of multivariate continuous panel data at the country level. The incomplete input data consisting of many variables come from publicly available established sources. These variables, in turn, capture six crucial country-level capacities: technological capacity, financial capacity, human capital capacity, infrastructural capacity, public policy capacity, and social capacity. Such capacities are part and parcel of the National Absorptive Capacity Systems (NACS). The dataset (MSK dataset) thus produced contains data on 47 variables for 82 LMICs between 2005 and 2019. The dataset has passed a quality and reliability check and can therefore be used for comparative analyses of national absorptive capacities and development, transition, and convergence among LMICs.

Explainable AI: A Neurally-Inspired Decision Stack Framework.

European law now requires AI to be explainable in the context of adverse decisions affecting the European Union (EU) citizens. At the same time, we expect increasing instances of AI failure as it operates on imperfect data. This paper puts forward a neurally inspired theoretical framework called "decision stacks" that can provide a way forward in research to develop Explainable Artificial Intelligence (X-AI). By leveraging findings from the finest memory systems in biological brains, the decision stack framework operationalizes the definition of explainability. It then proposes a test that can potentially reveal how a given AI decision was made.

Biofixation of atmospheric nitrogen in the context of world staple crop production: Policy perspectives.

The extensive use of nitrogen (N) fertilizers implicates a paradox: while fertilizers ensure the supply of a large amount of food, they cause negative environmental externalities, including reduced biodiversity, and eutrophic streams and lakes. Moreover, such fertilizers may also result in a major public health hazard: increased antibiotic resistance. This article discusses the critical implications of perturbations in N cycle caused by excessive use of fertilizers and resulting policy implications as they relate to ecosystem services. While there are solutions such as cover crops, these solutions are expensive and inconvenient for farmers. We advocate the use of biological fixation (BF) for staple crops-microbiome mediated natural supply of fixed N. This would involve engineering a microbiome that can be grown cheaply and at industrial scale. Fertilizers resulting from such innovation are termed as "biofertilizers" in this article. Following a qualitative cost-benefit analysis broken down by key stakeholders and a quick exploration of policy frameworks as they relate to the advancement of biofertilizers, we propose a practical pathway of where and how research investments should be directed to make such a solution feasible. We make five policy recommendations for decision-makers to facilitate a successful trajectory for this solution: (1) Future agricultural science should seek to understand how BF might be employed as a practical and efficient strategy. This effort would require that industry and the government partner to establish a pre-competitive research laboratory equipped with the latest state-of-the-art technologies that conduct metagenomic experiments to reveal signature microbiomes and form novel symbiotic connections. (2) To have a smooth ride in the market, ag-bio companies should: (i) create awareness among farmers; (ii) impart skills to farmers in testing and using biofertilizers, and (iii) conduct extensive field tests and more research in studying the scalability potential of such fertilizers. (3)The United States Department of Agriculture (USDA) and state governments should provide research and development (R&D) tax credits to biotech companies specifically geared towards R&D investments aimed at increasing the viability of BF and microbiome engineering. (4) To control agricultural pollution in the biosphere, federal governments should consider passing a Clean Agriculture Act (CAA), including a specific clause that regulate the use of chemical fertilizers. (5) Governments and the UN Food and Agriculture Organization (FAO) should coordinate Biological Advanced Research in Agriculture (BARA)-a global agricultural innovation initiative for investments and research in biological fixation and ethical, legal, and social implications of such innovation. While biological fixation will be central in BARA, we envision it to conduct research around other agricultural innovations as well, such as increasing photosynthetic efficiency.