Search Results (1,790)

Parking shortages and high costs in Chinese central business districts (CBDs) remain major urban challenges. Emerging automated vehicles (AVs) are expected to diversify parking options and mitigate these problems. However, AV users’ parking preferences and their influencing factors within existing urban zoning frameworks remain unclear. This study examines Nanjing as a representative case, proposing six distinct AV parking modes. Using survey data from 4644 responses collected from 1634 potential users, we employed nested logit models and random forest algorithms to analyze parking choice behavior. Results indicate that diversified AV parking modes would significantly reduce CBD parking demand. Users with medium- to long-term needs prefer home-parking, while short-term users favor CBD proximity. Key influencing factors include parking service satisfaction, duration, congestion time, AV punctuality, and individual characteristics, with satisfaction attributes showing the greatest impact across all modes. Comparative analysis reveals that random forest algorithms provide superior predictive accuracy for parking mode importance, while nested logit models better explain causal relationships between choices and influencing factors. This study establishes a dual analytical framework combining interpretability and predictive accuracy for urban AV parking research, providing valuable insights for transportation management and future metropolitan studies. Full article

Studies have shown that the iron concentration in the peritoneal fluid of women is associated with the severity of endometriosis. Therefore, investigation of iron metabolism-related genes (IM-RGs) in endometriosis holds significant implications for both prevention and therapeutic strategies in affected patients. Differentially expressed IM-RGs (DEIM-RGs) were identified by intersecting IM-RGs with differentially expressed genes derived from GSE86534. Mendelian randomization analysis was employed to determine DEIM-RGs causally associated with endometriosis, with subsequent verification through sensitivity analyses and the Steiger test. Biomarkers associated with IM-RGs in endometriosis were validated using expression data from GSE86534 and GSE105764. Functional annotation, regulatory network construction, and immunological profiling were conducted for these biomarkers. Single-cell RNA sequencing (scRNA-seq) (GSE213216) was utilized to identify distinctively expressed cellular subsets between endometriosis and controls. Experimental validation of biomarker expression was performed via reverse transcription–quantitative polymerase chain reaction (RT-qPCR). BMP6 and SLC48A1, biomarkers indicative of cellular BMP response, were influenced by a medicus variant mutation that inactivated PINK1 in complex I, concurrently enriched by both biomarkers. The lncRNA NEAT1 regulated BMP6 through hsa-mir-22-3p and hsa-mir-124-3p, while SLC48A1 was modulated by hsa-mir-423-5p, hsa-mir-19a-3p, and hsa-mir-19b-3p. Immune profiling revealed a negative correlation between BMP6 and monocytes, whereas SLC48A1 displayed a positive correlation with activated natural killer cells. scRNA-seq analysis identified macrophages and stromal stem cells as pivotal cellular components in endometriosis, exhibiting altered self-communication networks. RT-qPCR confirmed elevated expression of BMP6 and SLC48A1 in endometriosis samples relative to controls. Both BMP6 and SLC48A1 were consistently overexpressed in endometriosis, reinforcing their potential as biomarkers. Moreover, macrophages and stromal stem cells were delineated as key contributors. These findings provide novel insights into therapeutic and preventive approaches for patients with endometriosis. Full article

Background: Intracranial aneurysm (IA) rupture is a life-threatening cerebrovascular event with a mortality rate of up to 40%, affecting approximately 500,000 people globally each year. Although environmental pollutants such as 2,2′,4,4′-tetrabromodiphenyl ether (PBDE-47) have been implicated in the pathogenesis of IA, the causal relationship and underlying mechanisms remain unclear. This study aims to systematically explore the potential causal role of PBDE-47 in the development of IA by integrating multi-omics approaches. Methods: We utilized the UK Biobank Drug Proteomics Project (UKB-PPP) genome-wide association study (GWAS) data, including 2940 plasma proteins and 1400 metabolites, along with IA genetic data from 456,348 individuals, to perform a two-sample Mendelian randomization (MR) analysis. Instrumental variables were selected based on genome-wide significance (p < 5 × 10⁻⁸) or suggestive thresholds (p < 5 × 10⁻⁵). Analytical methods included inverse variance weighting (IVW), MR-Egger, weighted median, MR-PRESSO, and Steiger filtering for sensitivity analysis. Molecular docking and 100-nanosecond molecular dynamics simulations were used to evaluate interactions between PBDE-47 and proteins. Mediation analysis assessed the roles of plasma metabolites and miRNAs, and SMR-HEIDI tests were used to verify causal relationships. Results: MR analysis identified 93 plasma proteins potentially causally associated with IA, including 53 protective factors and 40 risk factors. By integrating PBDE-47 targets, IA-related genes, and metabolite-related genes, we identified 15 hub genes. Molecular docking revealed potential binding between PBDE-47 and F2R (binding energy: −5.516 kcal/mol), and SMR-HEIDI testing supported F2R as a potential causal risk factor for IA. Molecular dynamics simulations indicated the stability of the complex structure. Mediation analysis suggested that F2R may influence IA risk through eight plasma metabolites, and miR-130b-3p may indirectly promote IA development by upregulating F2R. Conclusions: Our findings suggest that exposure to PBDE-47 may have a potential causal relationship with IA risk, potentially mediated through the “PBDE–47–F2R–metabolite–miRNA” regulatory axis. These results provide preliminary evidence for early diagnostic biomarkers and targeted interventions for IA. The multi-omics analytical framework established in this study offers new insights into environmental determinants of neurovascular diseases, although further validation is needed to address potential limitations. Full article

First-trimester placental development comprises many critical yet understudied cellular events that determine pregnancy outcomes. Improper placentation leads to a host of health issues that not only impact the fetal period but also influence later-life offspring health. Thus, an experimental paradigm for studying early placental development is necessary and has spurred the development of new in vitro models. Organoid model systems are three-dimensional structures comprising multiple differentiated cell types that originate from a progenitor population. Trophoblasts are the progenitor cells that serve as the proliferative base for the differentiation and maintenance of the placenta. Due to research constraints, experimental studies on the causal mechanisms underlying pathological pregnancies cannot readily be performed in human subjects. The nonhuman primate (NHP) offers a solution to this problem as it circumvents the limitations of human pregnancy sampling. Importantly, NHPs share many developmental features of human pregnancy, including placenta type and a similar fetal growth trajectory, making longitudinal pregnancy studies feasible and relevant. Since perturbations made in vivo can be validated in vitro, an NHP model of early pregnancy would facilitate mechanistic studies of pregnancy disorders. Herein, we describe the methodology for the establishment of a first-trimester NHP placenta trophoblast organoid model system. Full article

Background: Depression has been identified as an important determinant of outcomes in hip and knee arthroplasty, but its impact on total ankle arthroplasty (TAA) remains unclear. Given the growing use of TAA as a treatment for end-stage ankle arthritis, understanding psychosocial risk factors is critical for optimizing surgical outcomes. This study aims to assess the effect of preoperative depression on clinical and functional outcomes following total ankle arthroplasty. Methods: A systematic review was conducted in accordance with PRISMA guidelines and prospectively registered with the Open Science Framework. PubMed, Cochrane Library, and CINAHL were searched through August 2025 for studies reporting outcomes of TAA stratified by depression status. Eligible designs included randomized trials, cohort studies and case series. Risk of bias was assessed using the Newcastle–Ottawa Scale (NOS). Given heterogeneity in study designs, depression definitions, and outcome measures, findings were synthesized narratively and summarized using a revised effect-direction plot. Results: Six unique studies involving approximately 9000 patients met inclusion criteria. Five studies were rated as good quality on the Newcastle–Ottawa Scale, while one study was judged to be of moderate quality. Four studies assessing pain outcomes consistently demonstrated worse postoperative pain or less improvement in patients with depression. Three of five studies assessing functional or disability outcomes reported reduced improvement, while two studies found no independent association. Two studies evaluating complications showed higher risks of adverse events, including prolonged hospital stay, non-home discharge, osteophytosis, and implant subsidence, among depressed patients. Revised effect-direction synthesis confirmed a consistent trend toward poorer outcomes across pain, function, and complication domains. Conclusions: Depression is associated with worse pain and higher complication rates following TAA, while its influence on functional recovery was not demonstrated uniformly. These findings support the importance of routine preoperative screening and targeted management of depression. Further prospective, multicenter studies and interventional trials are needed to clarify causality and optimize perioperative care. Full article

In the digitally saturated hospitality environment, research on digital transformation remains dominated by macro-level adoption trends and user-generated content, while the potential of micro-level web-behavioural data remains largely untapped. Recent systematic reviews highlight a fragmented body of literature and note that hospitality studies seldom address first-party behavioural data or big-data analytics capabilities. To address this gap, we collected clickstream, navigation and booking-funnel data from five luxury hotels in the Mediterranean and employed big-data analytics integrated with simulation modelling—specifically fuzzy cognitive mapping (FCM)—to model causal relationships among digital touchpoints, managerial actions and customer outcomes. FCM is a robust simulation tool that captures stakeholder knowledge and causal influences across complex systems. Using a case-study methodology, we show that first-party behavioural data enable real-time insights, support knowledge-based decision-making and drive digital service innovation. Across a 12-month panel, visitor volume was strongly associated with search traffic and social traffic, with the total-visitors model explaining 99.8% of variance. Our findings extend digital-transformation models by embedding micro-level behavioural data flows and simulation modelling. Practically, this study offers a replicable framework that helps managers integrate web-analytics into decision-making and customer-centric innovation. Overall, embedding micro-level web-behavioural analytics within an FCM framework yields a decision-ready, replicable pipeline that translates behavioural evidence into high-leverage managerial interventions. Full article

Using the “Policy Pressure-Innovation Alignment-Performance Transformation” theory, this paper looks at how ESG ratings, green innovation, and corporate dual-organizational performance are linked. This study uses a multi-period Difference-in-Differences (DID) model in conjunction with a conditional mediation effect model to examine how ESG ratings causally influence substantive green innovation, which in turn improves corporate financial and environmental performance. Regression results show that corporate ESG ratings have a big effect on the performance of both organizations. ESG ratings have a bigger effect on financial performance, while ESG scores have a bigger effect on environmental performance. Looking at the sub-dimensions shows that policy ratings have immediate effects on environmental performance and delayed effects on financial performance. The conclusion that the internalization response of corporate environmental costs is timely, while the market revaluation has a delayed transmission effect, holds true after being tested through parallel trend analysis and synthetic DID testing. More research shows that differences in ESG ratings hurt financial performance but help environmental performance. This means that differences in ESG ratings may lead to more real green innovation activities, which have a direct effect on the environment and, in the end, lead to bigger improvements in environmental performance. The moderating effect test shows that being aware of the environment makes substantive green innovation more focused on quality by making people feel responsible for their actions. Also, environmental management leads to more corporate green patents, which has resource displacement effects and makes green patent innovations less effective. Heterogeneity analysis shows that state-owned businesses use their institutional advantages to improve the “quality-quantity” of substantive green innovation, which helps their corporate green development performance. Declining businesses push for green innovation to fix problems that are already there, but mature businesses don’t like ESG rating policies because they are stuck in their ways, which stops them from making real progress in green innovation. This paper ends with micro-level evidence and theoretical support to solve the “greenwashing” problem of ESG and come up with “harmonious coexistence” policy combinations that work for businesses. Full article

This paper examines how shifts in sustainable capital markets influence societal well-being through the lens of a “Jazz Economy”, highlighting improvisation and adaptability in financial systems while grounding the analysis in empirical modelling. A panel of EUROSTAT indicators for 27 EU member states (2019–2022) was analyzed, including green bond issuance, market capitalization, environmental taxation, social spending, life expectancy, and subjective life satisfaction. Hierarchical clustering grouped these indicators into coherent patterns of “financial swings”, which were then linked to a composite quality-of-life index through an Adaptive Neuro-Fuzzy Inference System (ANFIS), with results benchmarked against linear regression and random forests. The inclusion of time lags between fiscal, financial, and social indicators strengthens the causal interpretation of the results, moving beyond simple correlations. Findings show that higher public environmental protection spending combined with a strong net international investment position consistently predicts greater life satisfaction, whereas income and longevity alone do not guarantee improvements in subjective well-being, reflecting nonlinear interactions among fiscal, financial, and social variables. Robustness checks, including the exclusion of pandemic years, confirm the stability of outcomes. The study concludes that cohesive fiscal–financial strategies, integrating environmental policy and macro-financial resilience, are essential for enhancing quality of life and that sustainable finance can deliver tangible social benefits beyond metaphorical framing. Full article

This study investigates the causal impact of board governance structures on firm profitability. We develop the Board Structure Influence (BSI) index, a composite metric that captures board independence, diversity, and role distribution—which we conceptualize as three structural pillars of Separation, Variety, and Disparity—to provide a comprehensive measure of governance effectiveness. Using a Difference-in-Differences (DiD) framework centered on the COVID-19 pandemic as an exogenous shock, we identify firms with strong governance and top BSI quartiles and compare their financial performance—measured by net profit margin—against firms with weaker board structures. Our results demonstrate that firms with higher BSI scores experience a statistically significant increase in profitability post-COVID-19. A Causal Forest analysis further reveals that this positive effect is heterogeneous, with the largest firms benefiting most significantly from strong board governance. Robustness checks—including placebo tests, parallel trends validation, and a SUTVA test—affirm the credibility of our findings. This research highlights the strategic importance of board structure for firm resilience during crises. It provides management insights for corporate leaders, investors, and policymakers aiming to align governance reform with financial profitability. Full article

This paper examines the high-frequency impact of tariff rhetoric on financial markets, a topic largely unexplored in existing literature. Unlike previous studies that focus on the long-term, macroeconomic effects of enacted trade policies, our research utilizes a novel, sentiment-based proxy variable for non-legislated tariff announcements. We demonstrate that political communication itself—not just formal policy changes—is a potent source of investor uncertainty and market volatility. Our analysis, employing a multi-model framework including VAR and EGARCH models, reveals several key findings. We find that trade-related shocks contribute significantly to market volatility by altering investor expectations and increasing perceived risk. A key discovery is a unique unidirectional causality where shocks to the S&P 500 preceded changes in our tariff variable, suggesting that market movements can influence policy rhetoric. Furthermore, our EGARCH analysis uncovers distinct volatility characteristics across asset classes, including an atypical positive asymmetry in the Chinese CSI 300. These results collectively provide robust empirical evidence that tariff rhetoric has a measurable and significant impact on asset prices and disproportionately increases market volatility, highlighting the need for policymakers to consider the financial market implications of their public statements. Full article

Using a panel of 3515 Chinese listed firms from 2011 to 2023, this study shows that the education level of the top management team (TMT) positively influences firm stock liquidity. The beneficial effect of TMT education on stock liquidity is stronger in settings with lower industry competition, higher information disclosure quality, and bull market periods. Mediation analysis indicates that analyst coverage provides a weak channel through which TMT education affects stock liquidity. Endogeneity concerns are alleviated by reverse causality tests, two-stage least squares regressions, propensity score matching, and generalized method of moments. The results are also robust to alternative liquidity measures and alternative definitions of TMT education. This study offers practical implications for investors, corporate executives, and policymakers seeking to promote market efficiency and liquidity. Full article

Nowadays, two major pathways seem to be responsible for the development and progression of atherosclerosis, namely, high levels of low-density lipoprotein-cholesterol (LDL-C) and low-grade vascular inflammation. Indeed, the concentration of C-reactive protein (CRP), mirroring low-grade systemic inflammation, has been recognized as a more powerful determinant of recurrent cardiovascular (CV) events, death, and all-cause mortality than LDL-C levels. Gut microbiota (GM) dysbiosis is a causal factor for the development of different inflammatory-based pathologies, such as CV disease (CVD). In addition, pre/probiotics showed beneficial effects on GM dysbiosis, by influencing both inflammation and immunity. It has been well documented that eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA) exert triglyceride (TG)-lowering and antithrombotic effects and play a seminal role in the resolution of inflammatory processes. We showed the recent studies indicating the relationship between pharmacological reduction in inflammatory cytokines and CV outcomes. The principal aim of our review is to highlight the anti-inflammatory and immune-modulatory activities of GM, EPA, and DHA. Then, we pointed out how developing patient-specific pre/probiotic and EPA/DHA interventions alongside the standard of care (SOC) is needed in order to answer several of the questions raised, ranging from diminishing drug toxicity to including frailty individuals. Therefore, hypothetical tailored clinical studies are presented, aiming to treat all the patients at high-risk of CV events, as well as aged people. Full article

This study addresses the growing importance of integrating innovation into corporate sustainability strategies by examining the financial and environmental performance of ten firms listed on the Borsa Istanbul Sustainability Index over a five-year period. The main objective is to develop and test a novel, data-driven analytical framework that reduces reliance on subjective expert judgments while providing actionable insights for sustainability-oriented decision-making. Within this framework, the entropy method from the Multi-Criteria Decision Making (MCDM) approach is first applied to calculate the objective weights of sustainability criteria, ensuring that the analysis is grounded in real performance data. Building on these weights, an innovative reverse Decision-Making Trial and Evaluation Laboratory (DEMATEL) model, implemented through a custom artificial neural network-based software, is introduced to estimate direct influence matrices and reveal the causal relationships among criteria. This methodological advance makes it possible to explore how environmental and financial factors interact with R&D expenditures and to simulate their systemic interdependencies. The findings demonstrate that R&D serves as a central driver of both environmental and financial sustainability, highlighting its dual role in fostering corporate innovation and long-term resilience. By positioning R&D as both an enabler and outcome of sustainability dynamics, the proposed framework contributes a novel tool for aligning innovation with strategic sustainability goals, offering broader implications for corporate managers, policymakers, and researchers. Full article

Water pumping stations are essential components of national water infrastructure, yet their construction involves complex, high-risk processes, and traditional risk management approaches often show significant limitations in practice. To address this challenge, this study proposes a Building Information Modeling (BIM)-based approach that integrates structured risk information into an interactive nD BIM environment. We first developed an extended Risk Breakdown Matrix (eRBM), which systematically organizes risk factors, assessment levels, and causal relationships. This is linked to the BIM model through a customized BIM–risk integration framework. Subsequently, the framework is further implemented and quantitatively validated via a Navisworks plug-in. The system incorporates three core components: (1) a structured risk information model, (2) a visualization mechanism for dynamic, spatiotemporal risk representation and (3) risk influence path analysis using the Decision-Making Trial and Evaluation Laboratory–Interpretive Structural Modeling (DEMATEL–ISM) method. The plug-in allows users to access risk information on demand and monitor its evolution over time and space during the construction process. This study makes contributions by innovatively integrating risk information with BIM and developing a data-driven visualization tool for decision support, thereby enhancing project managers’ ability to anticipate, prioritize, and mitigate risks throughout the construction lifecycle of water pumping station projects. Full article

Background/Objectives: In the age of digitalization, nomophobia has emerged as a relevant issue, especially among university students who utilize smartphones heavily for academic and social purposes. The Stressor–Strain–Outcome (SSO) framework explains the relationship between stressors, strain, and outcomes. Stressors such as nomophobia induce psychological strain. This strain subsequently influences outcomes like mindfulness. Nomophobia has been linked to higher distress, including depression, anxiety, and stress, that can negatively impact students’ focus. However, the mechanisms by which nomophobia impacts mindfulness remain less explored. Hence, this study aims to analyze the mediating effect of distress on the relation between student’s nomophobia and mindfulness. Methods: In this quantitative study, the researcher employed a structured close-ended survey to collect data from 723 students at the University of Ha’il in Saudi Arabia. Nomophobia was measured using the Nomophobia Questionnaire (NMP-Q). The level of distress was measured using the Depression, Anxiety, and Stress scale (DASS-21) Furthermore, the assessment of mindfulness was conducted using the Mindful Attention Awareness Scale (MAAS). Structural equation modeling was utilized to test the hypotheses of this study. Results: The results from PLS-SEM indicate that nomophobia did not directly reduce mindfulness, as its effect was statistically non-significant (β_1 = −0.052, p-value = 0.168). This suggests that nomophobia alone may not weaken focus. However, it significantly increased distress, particularly depression (β_2a = 0.327, p-value < 0.001), anxiety (β_2b = 0.294, p-value < 0.001) and stress (β_2c = 0.259, p-value < 0.001). In plain terms, students with higher nomophobia reported more depression and stress, which in turn reduced mindfulness. Anxiety, however, did not significantly affect mindfulness (β_3b = 0.006, p-value < 0.933), indicating its influence may be negligible or context-specific. Mediation analysis confirmed indirect effects of nomophobia on mindfulness through depression (β_4a = −0.096, p-value < 0.001) and stress (β_4c = −0.045, p-value < 0.020). Together, these mediators explained a substantial portion of the variance in mindfulness. Conclusions: The findings align with the SSO model, indicating that nomophobia acts as a stressor, exacerbating distress, which in turn reduces mindfulness. From a practical perspective, the results highlight the need for comprehensive student support. Universities should integrate digital wellness programs, stress-management resources, and mindfulness training into their services. Limitations and Future Research: The cross-sectional design and convenience sampling restrict causal inference and generalizability. Future studies should employ longitudinal research designs. They should also examine diverse cultural contexts. In addition, researchers should investigate potential mediators such as social support and sleep quality. Full article