Electromgnetic-gravitational cross-sections in external elctromagnetic fields

The classical processes: the conversion of photons into gravitons in the static electromagnetic fields are considered by using Feynman perturbation techniques. The differential cross sections are presented for the conversion in the electric field of the flat condesor and the magnetic field of the selenoid. A numerical evaluation shows that the cross sections may have the observable value in the present technical scenario.Comment: 11 pages, LATEX, no figure

死亡率に対する温度の時空間短期影響：いくつかのアジアの都市における時系列分析

この博士論文は内容の要約のみの公開（または一部非公開）になっています筑波大学 (University of Tsukuba)201

COMMUTERS' EXPOSURE TO PARTICULATE MATTER AND CARBON MONOXIDE IN HANOI : A PILOT STUDY

Joint Research on Environmental Science and Technology for the Eart

Subsampling MCMC - An introduction for the survey statistician

The rapid development of computing power and efficient Markov Chain Monte Carlo (MCMC) simulation algorithms have revolutionized Bayesian statistics, making it a highly practical inference method in applied work. However, MCMC algorithms tend to be computationally demanding, and are particularly slow for large datasets. Data subsampling has recently been suggested as a way to make MCMC methods scalable on massively large data, utilizing efficient sampling schemes and estimators from the survey sampling literature. These developments tend to be unknown by many survey statisticians who traditionally work with non-Bayesian methods, and rarely use MCMC. Our article explains the idea of data subsampling in MCMC by reviewing one strand of work, Subsampling MCMC, a so called pseudo-marginal MCMC approach to speeding up MCMC through data subsampling. The review is written for a survey statistician without previous knowledge of MCMC methods since our aim is to motivate survey sampling experts to contribute to the growing Subsampling MCMC literature.Comment: Accepted for publication in Sankhya A. Previous uploaded version contained a bug in generating the figures and reference

Examining the Nursing Workforce Shortage in Vietnam : Implications for Nursing Education

This study examines the nursing human resource crisis in Vietnam that emerged in the wake of the COVID-19 pandemic. A literature review encompassing policy documents, statistics, reports, guidelines, news, media, and academic publications was conducted. Even before the pandemic, Vietnam grappled with a nursing shortage, with a nurse-to-population ratio significantly below the global average. The shortage of nurses jeopardizes nurse-to-patient ratios, patient safety, and equitable access to high-quality healthcare services. The nursing human resource crisis in Vietnam is further exacerbated by the limited capacity of nursing education institutions. Without substantial investments in nursing education, projections indicate that Vietnam may face a crisis of lacking nursing professionals in the near future. The post-COVID-19 nursing crisis in Vietnam underscores the urgent need for reforms in nursing education. Policy interventions should prioritize strategic workforce planning and increased financial investments in nursing education and training programs

On Throughput for UAV Relay Assisted for Use in Disaster Communications

In this paper, the system performance of an energy harvesting (EH) unmanned aerial vehicle (UAV) system for use in disasters was investigated. The communication protocol was divided into two phases. In the first phase, a UAV relay (UR) harvested energy from a power beacon (PB). In the second phase, a base station (BS) transmitted the signal to the UR using non-orthogonal multiple access (NOMA); then, the UR used its harvested energy from the first phase to transfer the signal to two sensor clusters, i.e., low-priority and high-priority clusters, via the decode-and-forward (DF) technique. A closed-form expression for the throughput of the cluster heads of these clusters was derived to analyze the system performance. Monte Carlo simulations were employed to verify our approach

Market Competition and Innovation Premium Before and After the Financial Crisis: Evidence from Taiwan

This study explores the influence of innovation and market competition on stock returns in Taiwan before and after the 2008 financial crisis. This study offers marginal contributions to the important topic of innovation investment which is a vital driver of competitiveness and growth. The study employs Fama Macbeth regression and a sorting portfolio to examine a sample of 121,913 firm-month observations from 1991 to March 2021. A Two-Stage Least Squares estimation is also employed to address unobserved endogeneity issues. The empirical findings suggest that innovation premiums persist in Taiwan. However, the findings also report that higher market concentration reduces stock returns in Taiwan. The results support the information asymmetry theory and the resource-based view theory. This study can support policymakers and managers in developing innovative activities sustainably in emerging markets, while also helping individual investors to optimize their investment portfolios. &nbsp