The influence of green human resource management on university sustainability in higher education: the role of mediating environmental performance and green commitment.

The purpose of the research is to examine how green human resource management (GHRM) contributes to the sustainability of the university. This study also focuses on how environmental performance and dedication to sustainability can act as mediators. Additionally, it seeks to examine the interplay between GHRM practice and university sustainability and how green environmental success and green dedication moderate that interaction.

Transitioning from gridlock to sustainability: advancing transport strategies for eco-friendly solutions in high-income countries.

The study aims to comprehend sustainable behaviors in high-income nations, where human-environment interactions are crucial. Increased transportation needs in industrialized countries highlight the importance of environmental challenges affecting human well-being. Railway passenger carrier, automobile energy efficiency, technology breakthroughs, financial incentives, and public-private partnerships (PPPs) affect congestion and sustainability, which the study analyses for sound policy inferences in a panel of 28 high-income nations from 2000 to 2022.

Corrigendum: Role of dietary fiber and lifestyle modification in gut health and sleep quality.

[This corrects the article DOI: 10.3389/fnut.2024.

Pay-for-performance in Taiwan: A systematic review and meta-analysis of the empirical literature.

Objectives: This study aimed to assess the impact of pay-for-performance (P4P) programmes on healthcare in Taiwan.

Study Design: This was a systematic review and meta-analysis.

Methods: A systematic literature search was performed using the PubMed, Medline, Embase, Cochrane review, Scopus, Web of Science and PsycINFO databases up to July 2023.

Digital transformation and corporate tax avoidance: An analysis based on multiple perspectives and mechanisms.

Promoting the seamless integration of the digital economy with the real economy, mitigating the adverse impacts of widespread corporate tax avoidance, and optimizing tax governance are critical imperatives in the era of digital economy. This study examines all A-share listed companies from 2007 to 2022 as research samples. It utilizes multiple perspectives including signal theory, information asymmetry theory, and the T-O-E (Technology-Organisation-Environment) framework to investigate the primary impacts of digital transformation on corporate tax avoidance, along with the intermediate mechanisms and foundational conditions that influence its effectiveness.

An examination of the curvilinear relationship between person-job fit and innovative behavior: the moderating role of abusive supervision in South Korea.

Although literature suggests that a higher person-job fit leads to more innovative behavior, some recent studies have shown inconsistent results with the assumption of such a linear relationship between the two constructs. Considering these inconsistent findings, the present study aims to examine a curvilinear relationship between person-job fit and innovative behavior. Innovative behavior represents an individual's actions that come up with, realize, and apply novel ideas within the job environment, and person-job fit, which pertains to the value congruence between the job and individual, can be a critical predictor of innovative behavior.

Comorbidity progression analysis: patient stratification and comorbidity prediction using temporal comorbidity network.

Objective: The study aims to identify distinct population-specific comorbidity progression patterns, timely detect potential comorbidities, and gain better understanding of the progression of comorbid conditions among patients.

Methods: This work presents a comorbidity progression analysis framework that utilizes temporal comorbidity networks (TCN) for patient stratification and comorbidity prediction. We propose a TCN construction approach that utilizes longitudinal, temporal diagnosis data of patients to construct their TCN.

Biocrude from hydrothermal liquefaction of indigenous municipal solid waste for green energy generation and contribution towards circular economy: A case study of urban Pakistan.

In this study, biocrude was successfully produced by the hydrothermal liquefaction of municipal solid waste collected from the landfill site of Lahore, the capital of Punjab, Pakistan, boasting a population of 12 million and an annual waste collection of 10 million tons. The hydrothermal liquefaction process was performed at reaction parameters of 350 °C and 165 bars with 15 min of residence time. The solid waste was found to have 78 % dry matter, 22 % moisture contents, 22.

The effect of eco-friendly and financial technologies on renewable energy growth in emerging economies.

Successfully integrating renewable energy sources depends on eco-friendliness, financial technology, and economic growth (GDP). This paper examines the dynamic effect of innovative financial and green technology on renewable energy for 38 emerging economies from 2006 to 2021. Using the dynamic First-difference Generalized Method of Moments (FD-GMM) model, the analysis identifies a critical GDP threshold of 1831.

Digital finance and sustainable development: Evidence from developing nations.

Objectives: This paper investigates the role of digital finance in promoting environmental sustainability within a group of 52 developing economies from 2010 to 2019. Specifically, it examines whether digital finance effectively contributes reducing CO emissions in these nations.

Methods: This paper is a quantitative study which employs the IV-GMM (instrumental variable generalized methods of moment) approach that tackles any potential endogeneity.

Dynamic factors driving PM2.5 concentrations: Fresh evidence at the global level.

This paper analyzes the dynamic impact of economic, social, and governance factors on PM2.5 concentrations in 89 countries from 2006 to 2019. Using the GMM-PVAR approach and Impulse-Response Functions, we examine how shocks to specific variables affect PM2.

Emerging research trends in artificial intelligence for cancer diagnostic systems: A comprehensive review.

This review article offers a comprehensive analysis of current developments in the application of machine learning for cancer diagnostic systems. The effectiveness of machine learning approaches has become evident in improving the accuracy and speed of cancer detection, addressing the complexities of large and intricate medical datasets. This review aims to evaluate modern machine learning techniques employed in cancer diagnostics, covering various algorithms, including supervised and unsupervised learning, as well as deep learning and federated learning methodologies.

Fostering resilience and post-traumatic growth in overseas Chinese left-behind children: The role of autonomy, competence, and relatedness.

Objective: This study examines the impact of parental migration on the psychological well-being and development of left-behind children (LBCs) in Zhejiang, China, within the broader context of the country's rural transformations and urban migration. It investigates how intellectual and relational engagement (RE), autonomy (AUT), competence (COM), and relatedness (RES) contribute to resilience (REL) and post-traumatic growth (PTG) in these children, reflecting on the shift from viewing parental separation merely as a source of trauma to recognizing its potential to foster significant personal growth.

Methods: Utilizing a cross-sectional design, the research was conducted in April and May 2023 with 1348 LBCs from a total sample of 4049 students inZhejiang.

An explainable Artificial Intelligence software system for predicting diabetes.

Implementing diabetes surveillance systems is paramount to mitigate the risk of incurring substantial medical expenses. Currently, blood glucose is measured by minimally invasive methods, which involve extracting a small blood sample and transmitting it to a blood glucose meter. This method is deemed discomforting for individuals who are undergoing it.

Construction of improved comprehensive classes of estimators for population distribution function.

The primary purpose of this article is to examine the issue of estimating the finite population distribution function from auxiliary information, such as population mean and rank of the auxiliary variables, that are already known. In order to better estimate the distribution function (DF) of a finite population, two improved estimators are developed. The bias and mean squared error of the suggested and existing estimators are derived up to the first order of approximation.

The Psychological Impact of COVID-19: A Comparative Analysis of Pre-Lockdown and During-Lockdown Periods Among Saudi General Population.

Background: Prior research has revealed substantial psychological impacts of COVID-19 among the general population. However, there is a noticeable gap in studies addressing the enduring anxiety levels before and during lockdown periods of the COVID-19 pandemic.

Objective: The study assessed and compared the psychological impact of the COVID-19 pandemic before and during lockdown periods among the general population in Saudi Arabia.

Associations Between Telemedicine Use Barriers, Organizational Factors, and Physician Perceptions of Care Quality.

Evaluating physician perceptions of telemedicine use and its impact on care quality among physician providers is critical to sustaining telemedicine programs, given the uncertainty of reimbursement policy, preferences, inadequate training, and technical difficulties. Physicians reported technical barriers to effectively practicing integrated medicine using telemedicine as patient volumes increased during the pandemic. The objective of this work was to examine whether perceived practice barriers and facilitators were associated with physician respondents' perceptions of telemedicine care quality compared with in-person care.

Exploring factors influencing sustainable human capital development: Insights from Saudi Arabia.

This study investigates the critical factors influencing Saudi Arabia's sustainable human capital development. It primarily aims to explore the correlations among the postulated variables and how each variable influences the development of a skilled, adaptable, and socially conscious workforce, in alignment with the objectives of the Saudi Vision 2030. This study utilizes a quantitative approach, employing partial least squares structural equation modeling to analyze the data collected from 203 public personnel in Saudi Arabia through an online questionnaire.

Crystal structure of Kunitz-type trypsin inhibitor: Entomotoxic effect of native and encapsulated protein targeting gut trypsin of Herbst.

Trypsin inhibitors are known to act against insect pests by inhibiting proteases of the digestive tract. In this study, we report structural and functional characterization of ∼ 19 kDa Kunitz-type trypsin inhibitor (ApKTI) protein with potential bio-insecticidal applications. Crystal structure of ApKTI protein has been refined to 1.

Participatory leadership and supportive organisational culture Panacea for job satisfaction regulatory role of work-life balance.

This study examines the direct influence of participatory leadership (PL) and supportive organisational culture (SOC) on employee job satisfaction (JC). Additionally, the research delves into the mediating role of work-life balance in the relationship between PL, SOC, and job satisfaction. Data was collected using 450 questionnaires through random sampling from hotels managing food security in Saudi Arabia.

Moving toward sustainable goals 7 and 13: An inclusive mechanism to achieve environmental sustainability through digitalization and energy transition in OECD countries.

In line with Sustainable Development Goals (SDGs) 7 and 13, this study proposes a policy framework while considering digitalization as a critical tool in shaping the energy transition process to attain environmental suitability in OECD countries. The study employed multifaceted empirical techniques, including Method of Moment Quantile Regression (MMQR), Fully Modified Ordinary Least Squares (FMOLS), and Dumitrescu and Hurlin (D-H), augmented with robustness tests over the period 2000 to 2021. The results indicate that digitalization augments energy transition and green finance to attain environmental sustainability.

Navigating the impact of remittances on environmental quality in Africa: The crucial role of institutional quality.

The Sub-Saharan African (SSA) region remains the world's largest recipient of remittances. Due to growing concerns over climate change issues, recent studies have examined how these financial flows have affected environmental quality. Sundry variables were controlled in such studies concerning the remittances-environment nexus, including institutional quality.

Exploring impact of green finance and natural resources on eco-efficiency: case of China.

China ranks 160 out of 180 countries in terms of ecological efficiency, with an EPI score of 28.40 and a 10-year average change in score of 11.40.