Does urban-rural integration contribute to environmental health? Exploring the interplay between urban-rural integration and air quality dynamics in Yangtze River middle reaches city cluster.

Background: Exploring the coordinated relationship between urban-rural integration and air quality has significant implications for promoting urban-rural development, preventing air pollution and ensuring residents' health. This study takes Yangtze River middle reaches city cluster as a case study, calculates the levels of urban-rural integration and air quality development, analyzes their coupled coordination relationship and driving factors, and explores the path of coordinated development.

Methods: This study constructs a coupling coordination degree model to analyze the relationship between the urban-rural integration development level and air quality development level.

Through restful waters and deep commotion: A study on burnout and health impairment of Italian seafarers from the JD-R model perspective.

Background: The work experience of seafarers differs significantly from other land-based occupations due to several factors, particularly remoteness and the restricted work environment. This study seeks to examine the impact of burnout and health impairment in the maritime industry, using the Job Demand-Resources theory as a framework.

Methods: To investigate these phenomena, an online questionnaire was sent to 239 Italian seafarers (94.

Characterising a New Sheep Model of Parkinson's Disease Using Unilateral Intracerebral Injection of 6-Hydroxydopamine Into the Substantia Nigra.

New therapeutic agents developed for treating neurological disorders are often tested successfully on rodents. Testing in an appropriate large animal model where there is longer lifespan and comparable brain size to humans should improve translational success and is frequently expected by regulatory bodies. In this project, we aimed to establish a novel sheep model of Parkinson's disease as a large-brained experimental model for translational research.

Demographic disparities in access to COVID-19 clinical trial sites across the United States: a geospatial analysis.

Throughout the COVID-19 pandemic, underserved populations, such as racial and ethnic minority communities, were disproportionately impacted by illness and death. Ensuring people from diverse backgrounds have the ability to participate in clinical trials is key to advancing health equity. We sought to analyze the spatial variability in locations of COVID-19 trials sites and to test associations with demographic correlates.

A two-stage robust optimization model for emergency service facilities location-allocation problem under demand uncertainty and sustainable development.

Under the backdrop of frequent emergencies, the rational layout of emergency service facilities (ESF) and the effective allocation of emergency supplies have emerged as crucial in determining the timeliness of post-disaster response. By adequately accounting for potential uncertainties and carrying out comprehensive pre-planning, the robustness of location-allocation decisions can be significantly improved. This paper delves into the ESF network design problem under demand uncertainty and formulates this problem as a two-stage robust optimization model.

Asymmetric role of board diversity on green growth mechanism: Evidence from COP27 framework.

Corporate governance has an ethical and legal obligation to safeguard environment from the effects of business operations. In this vein, our study examines the role of board diversity in green growth, renewable energy, social inclusion, and natural capital protection. A green growth index was created using indicators endorsed by the Global Green Growth Organization to accomplish the research objectives.

Modeling of lifetime scenarios with non-monotonic failure rates.

The Weibull distribution is an important continuous distribution that is cardinal in reliability analysis and lifetime modeling. On the other hand, it has several limitations for practical applications, such as modeling lifetime scenarios with non-monotonic failure rates. However, accurate modeling of non-monotonic failure rates is essential for achieving more accurate predictions, better risk management, and informed decision-making in various domains where reliability and longevity are critical factors.

The impact of social networks on rural residents' engagement in living environment upgrade: An integrated analysis drawing on social network theory and the theory of planned behavior.

The issue of rural living environment is a critical concern for China and the global community, intricately intertwined with regional economic development. The proactive involvement of rural residents, who are both beneficiaries and influencers of the environment, constitutes a cornerstone in improving environmental standards. Therefore, the factors that shape rural residents' participation in living environment upgrade must be explored.

Life satisfaction around the world: Measurement invariance of the Satisfaction With Life Scale (SWLS) across 65 nations, 40 languages, gender identities, and age groups.

The Satisfaction With Life Scale (SWLS) is a widely used self-report measure of subjective well-being, but studies of its measurement invariance across a large number of nations remain limited. Here, we utilised the Body Image in Nature (BINS) dataset-with data collected between 2020 and 2022 -to assess measurement invariance of the SWLS across 65 nations, 40 languages, gender identities, and age groups (N = 56,968). All participants completed the SWLS under largely uniform conditions.

Final Analysis of Post-Marketing Surveillance for Avelumab + Axitinib in Patients With Renal Cell Carcinoma in Japan.

Introduction: Avelumab, an anti-programmed death ligand 1 antibody, was approved in combination with axitinib for curatively unresectable or metastatic renal cell carcinoma (RCC) in Japan in December 2019. Because the pivotal JAVELIN Renal 101 study included a limited number of Japanese patients, post-marketing surveillance (PMS) was required to evaluate outcomes (safety and effectiveness) in patients with RCC who received avelumab + axitinib treatment in clinical practice in Japan.

Materials And Methods: We report data from prospective, noncomparative, multicenter, observational PMS in patients with RCC who received ≥ 1 dose of avelumab.

Can household energy efficiency dampen crude oil price volatility in the United States?

Even though the effect of oil price shocks on macroeconomics has been extensively investigated, the literature on how efficiency in household energy use affect crude oil price volatility is yet explored. This study unveils whether household energy efficiency lower crude oil price volatility asymmetrically in the United States using the historical and forecast dataset that spans from 1970:Q1-2040:Q1. Applying the multivariate case of Quantile-on-Quantile Regression, the empirical results show that household energy efficiency dampens crude oil price volatility with a stronger connection in quantiles before the median quantiles of crude oil price volatility.

Unlocking emotional well-being: Evaluation of a stress mindset intervention with a metacognitive approach.

Although there is a growing body of research on the effects of a stress mindset on health and well-being, knowledge of the effectiveness of stress mindset interventions in real-world situations is limited and primarily supported by evidence from Western cultural contexts. We examined the effects of a stress mindset intervention with a metacognitive approach on emotional well-being (negative affect, positive affect, anxious affect, and life satisfaction) over 4 months (i.e.

Curcumin encapsulated in PAMAM dendrimers for the therapeutic treatment of ischemic stroke in rats.

Introduction: Ischemic stroke is a devastating neurovascular condition that occurs when cerebral tissue fails to receive an adequate supply of oxygen. Despite being a leading cause of death and disability worldwide, therapeutic interventions are currently limited. Polyamidoamine (PAMAM) dendrimers are nanomolecules commonly used in biomedical applications due to their ability to encapsulate small-molecules and improve their pharmacokinetic properties.

How do staff work in NHS hospital operations management meetings to support resilience in everyday service delivery? A qualitative study.

Background: Operations Management meetings in NHS hospitals provide an opportunity for operational and clinical staff to monitor demand and capacity and manage patient flow. These meetings play an important role in the achievement of resilient performance over time. However, little is known about the work that takes place within these meetings in the United Kingdom's National Health Service.

Machine learning-driven prediction of medical expenses in triple-vessel PCI patients using feature selection.

Revascularization therapies, such as percutaneous coronary intervention (PCI) and coronary artery bypass grafting (CABG), alleviate symptoms and treat myocardial ischemia. Patients with multivessel disease, particularly those undergoing 3-vessel PCI, are more susceptible to procedural complications, which can increase healthcare costs. Developing efficient strategies for resource allocation has become a paramount concern due to tightening healthcare budgets and the escalating costs of treating heart conditions.

Trust in scientists and their role in society across 68 countries.

Science is crucial for evidence-based decision-making. Public trust in scientists can help decision makers act on the basis of the best available evidence, especially during crises. However, in recent years the epistemic authority of science has been challenged, causing concerns about low public trust in scientists.

Long-term outcomes and lymph node metastasis following endoscopic resection with additional surgery or primary surgery for T1 colorectal cancer.

Optimal management of T1 colorectal cancer (CRC) remains controversial. This study compared the long-term outcomes of endoscopic resection with additional surgical resection (ER + ASR) versus primary surgical resection (PS) in patients with T1 CRC and identified risk factors for lymph node metastasis (LNM). This retrospective cohort study included 373 patients with T1 CRC who underwent ER + ASR or PS between January 2010 and December 2020 at a tertiary center in Taiwan.

Perceptions of science, science communication, and climate change attitudes in 68 countries - the TISP dataset.

Science is integral to society because it can inform individual, government, corporate, and civil society decision-making on issues such as public health, new technologies or climate change. Yet, public distrust and populist sentiment challenge the relationship between science and society. To help researchers analyse the science-society nexus across different geographical and cultural contexts, we undertook a cross-sectional population survey resulting in a dataset of 71,922 participants in 68 countries.

Parallel systems in healthcare: Addressing Indigenous health equity in Canada.

The Canadian public healthcare system faces significant challenges in performance. While the formal healthcare system addresses funding, access and policy, there is a critical need to prioritise the informal system of community-oriented networks. This integration aligns with the World Health Organization's primary health care approach, emphasising a whole-of-society strategy for health equity.

Causal inference of whole-grain foods' risk based on a generative adversarial network and Bayesian network.

Whole-grain foods (WGFs) constitute a large part of humans' daily diet, making risk identification of WGFs important for health and safety. However, existing research on WGFs has paid more attention to revealing the effects of a single hazardous substance or various hazardous substances on food safety, neglecting the mutual influence between individual hazardous substances and between hazardous substances and basic information. Therefore, this paper proposes a causal inference of WGFs' risk based on a generative adversarial network (GAN) and Bayesian network (BN) to explore the mutual influence between hazardous substances and basic information.

Controlling shareholders' equity pledge and corporate innovation investment-empirical analysis based on pharmaceutical manufacturing.

Enterprise innovation investment is influenced by the actions of innovation subjects, whereas regulating shareholders' equity pledge behavior facilitates innovation investment and finance but also carries dangers and affects enterprise innovation investment. Methods:This paper builds an unbalanced panel model to empirically analyze the impact of controlling shareholders' equity pledges on corporate innovation and its heterogeneous characteristics. It also looks at the moderating role of corporate financing constraints and the mediating role of equity incentives, using data from A-share listed companies in China's pharmaceutical manufacturing industry from 2015 to 2022.

The impact of platform leadership on employee deviant innovation in digital transformation enterprises.

Platform leadership (PL) has been increasing in digital transformation enterprises. This study explores the effects, pathways, and boundary conditions of PL on employee deviant innovation (EDI). In this study, 444 valid questionnaires were collected from ten digital transformation enterprises.

Proteomic analysis reveals the roles of silicon in mitigating glyphosate-induced toxicity in Brassica napus L.

Glyphosate (Gly) is a widely used herbicide for weed control in agriculture, but it can also adversely affect crops by impairing growth, reducing yield, and disrupting nutrient uptake, while inducing toxicity. Therefore, adopting integrated eco-friendly approaches and understanding the mechanisms of glyphosate tolerance in plants is crucial, as these areas remain underexplored. This study provides proteome insights into Si-mediated improvement of Gly-toxicity tolerance in Brassica napus.

Driver identification in advanced transportation systems using osprey and salp swarm optimized random forest model.

Enhancement of security, personalization, and safety in advanced transportation systems depends on driver identification. In this context, this work suggests a new method to find drivers by means of a Random Forest model optimized using the osprey optimization algorithm (OOA) for feature selection and the salp swarm optimization (SSO) for hyperparameter tuning based on driving behavior. The proposed model achieves an accuracy of 92%, a precision of 91%, a recall of 93%, and an F1-score of 92%, significantly outperforming traditional machine learning models such as XGBoost, CatBoost, and Support Vector Machines.

Machine learning-based assessment of morphometric abnormalities distinguishes bipolar disorder and major depressive disorder.

Introduction: Bipolar disorder (BD) and major depressive disorder (MDD) have overlapping clinical presentations which may make it difficult for clinicians to distinguish them potentially resulting in misdiagnosis. This study combined structural MRI and machine learning techniques to determine whether regional morphological differences could distinguish patients with BD and MDD.

Methods: A total of 123 participants, including BD (n = 31), MDD (n = 48), and healthy controls (HC, n = 44), underwent high-resolution 3D T1-weighted imaging.