Search Results (6,715)

In the context in which on-demand mobility services are rapidly gaining popularity in the transportation sector, this article provides a literature review focusing on the emerging research topics related to ride-hailing. Based on a comprehensive review of the existing scientific literature, ten main research areas are identified, covering aspects ranging from operational algorithms to macro-level policy impacts enforced by local authorities. Each topic is discussed and analyzed based on available published research. This work analyzes state-of-the-art research directions such as demand forecasting, passenger–driver matching algorithms, pricing strategies, electric vehicle integration, trust and security aspects, quality of service and user satisfaction, integration with public transportation, and robotaxi integration. The solutions identified pave the way for new, evolving technologies related to on-demand mobility services and ride-hailing, a domain at the intersection of data science, artificial intelligence, and futuristic urban planning. Finally, the main results of this work are focused on the integration of AI, the optimization of the latency–security trade-off, and the development of unified global transportation standards that better address the balance between technological efficiency, sustainability, environmental protection, and social equity. Full article

Water systems experience increasing sustainability challenges from climate variability, aging infrastructure, and energy and chemical intensity demands, but AI has typically been assessed against prediction accuracy rather than demonstrated operational success. This PRISMA 2020 systematic review analyzed the role of AI solutions on sustainability in distribution, treatment, and basin management. The database search identified 920 records; after deduplication (n = 185), screening was conducted on n = 735 titles/abstracts and examination of the full text for n = 85, providing a total of n = 41 included peer-reviewed studies for qualitative synthesis and n = 38 for quantitative/bibliometric synthesis with the additional analysis of seven grey-literature sources. Evidence mapping reveals high growth post-2020, and distribution and wastewater operations are dominated by a few companies. The most deployable evidence is found with monitoring, anomaly/leak detection, and short-term forecasting, while optimization and reinforcement-learning control are primarily simulation validated with limited field applications. While accuracy metrics are often reported, transformation into water saved, kWh/m³, chemicals, compliance/reliability/resilience/equity measures are inconsistently and less frequently operationalized. In general, AI is most believable when it is part of analysis-ready workflows, bounded decision support, and measurement-and-verification. Full article

This phenomenological study explores the experiences of Black males in U.S. public schools and draws parallels between Black millennials and the “indignant generation,” a term Lawrence Jackson uses to describe African American life between 1934–1960. While the purview of school discipline discourse is saturated with conversations on racial disparities, the exigent problem still remains. As such, this research provides a nuanced probe into concepts of discontent and indignation within Black students. In doing so, this study recasts Black male students as experts, not observers, within educational research. Using counter-storytelling as the theoretical and analytical framework, this study examines both student engagement and school disaffection through the lens of “Black male positionality.” Participants (Black males, ages 25–35, n = 9) provide individual reflections of their past schooling experiences and also detail critical needs in educational reform. Using semi-structured interviews, participants provide in-depth, retrospective perspectives of schooling and reconceptualize renewed possibilities of educational reform for Black students today. The study’s major findings demonstrate school carcerality was evident via counterproductive discipline policies and semblances of “untapped potential” among students. The study’s findings surface important topics in Black education and help to broaden the scope of research to explore concepts of Blackness, being, and belonging within phenomenological studies. Full article

Background/Objectives: Early Childhood Intervention (ECI) services are critical for supporting children with developmental needs and their families. Despite an established legislative framework, challenges related to accessibility, equity, resources, and standardization of practices persist. This study aimed to describe the perspectives of early intervention professionals in Portugal regarding current barriers, facilitators, and priority areas for improvement within the system. Methods: A descriptive study was conducted involving 82 professionals working in early intervention in Portugal. Data were collected using a survey specifically developed by the research team, grounded in a comprehensive literature review and professional expertise. The instrument was validated through a Delphi Panel with two rounds involving six experts in ECI. Data from open-ended questions were analyzed using content analysis, identifying categories and sub-categories to describe the responses, and descriptive statistics for the closed-ended questions. Results: Professionals highlighted the need to update the National ECI System (SNIPI), improve accessibility, and ensure equitable access to early intervention services. Participants reported limited resources, a lack of standardization in practices, and emphasized the importance of professional training and continuous professional development. The findings also pointed to the urgent need for investment and functional and structural restructuring of early intervention services. Various barriers and facilitators were identified. Conclusions: The study provides valuable insights into the perspectives of early intervention professionals, identifying critical areas for policy improvement, resource allocation, and practice standardization. Full article

This article conceptualizes active tourism as a strategy for promoting physical activity (PA) among children and adolescents and examines the literature that has analyzed its different modalities and their application across diverse settings and contexts. A systematic review (2015–2025) was conducted in accordance with PRISMA 2020, with searches performed in PubMed, Scopus, and Web of Science. Predefined inclusion and exclusion criteria were applied, alongside rigorous screening procedures and methodological quality assessment. Twelve studies were included, covering experiential and knowledge-oriented modalities implemented in curricular, extracurricular, family, and community contexts. The results show that active tourism increases PA frequency, duration, and intensity, and enhances physical fitness indicators as well as psychosocial variables (intrinsic motivation, enjoyment, autonomy, and competence). Experiential modalities and rural/natural environments predominate, generally yielding stronger effects than urban or mixed settings; however, these latter contexts broaden reach and equity by integrating activities into daily routines. Conceptual heterogeneity and the scarcity of longitudinal studies limit the estimation of sustained effects and the comparison across modalities. At present, active tourism emerges as a transversal approach to promoting meaningful PA in children and adolescents, integrating movement, learning, and well-being. Comparative and longitudinal designs capable of quantifying dose–response patterns by modality and setting are recommended, as well as policies that strengthen school–family–community linkages to enhance adherence and reduce inequalities in access to active opportunities. Full article

Opioid-related iatrogenic harms, including opioid use disorder, overdose, and opioid-induced respiratory depression, constitute a major patient safety challenge. Although clinicians document key safety signals in unstructured clinical narratives, many of these indicators are not readily captured by conventional surveillance approaches that rely on structured administrative data. This clinically focused narrative review synthesizes 47 empirical studies published between 2009 and 2025 that applied artificial intelligence (AI) methods to identify opioid-related harms from clinical text and to address the resulting ascertainment gap. Across studies, administrative coding systems, including ICD-10, often under-ascertain opioid-related events, whereas text-based AI can identify additional cases and contextual details often documented primarily in narrative records, such as fluctuating mental status, suspected drug causality, and responses to naloxone. Methodologically, the literature has progressed from interpretable rule-based lexicons to machine learning and deep learning models and, more recently, to transformer-based approaches, including large language models (LLMs) for classification and schema-driven extraction. Rule-based systems established the feasibility of transparent surveillance and frequently recovered clinically documented cases missed by billing codes. Subsequent supervised and deep learning approaches expanded scalability and, in a smaller subset of studies, were integrated into electronic health record workflows with operational metrics reported. More recent transformer- and LLM-based studies emphasize richer extraction schemas and benchmark development, including characterization of overdose context and intentionality and identification of potential prodromal neurocognitive signals, although external validation, calibration, and prospective outcome evaluation remain inconsistently reported. Given that the evidence base is predominantly retrospective and that clinical workflow studies remain comparatively few, a pragmatic near-term clinical role is to provide detection-to-triage decision support rather than autonomous diagnosis, in which systems surface candidate cases with reviewable evidence for clinician adjudication. Future progress will require greater standardization of phenotype definitions, routine equity auditing and subgroup reporting, stronger external validation and calibration at operational thresholds, and a shift from retrospective discrimination metrics toward prospective assessments of the clinical workflow impact, clinical utility, and patient-centered outcomes. Full article

Accurately assessing urban green perception is crucial for sustainable urban development and human well-being, yet conventional approaches often depend on simplistic objective metrics and non-immersive, screen-based subjective surveys, undermining ecological validity. This study develops and validates a multidimensional assessment framework that integrates Large Vision Models (LVMs) and Mixed Reality (MR) to couple objective environmental features with immersive human perception. The framework comprises 30 objective and 6 subjective indicators; state-of-the-art LVMs including DINOv2 and Depth Anything were applied to accurately extract objective features from Street View Imagery (SVI); and the MR device, Meta Quest 3, was utilized for the immersive collection of high-quality subjective data. In an empirical study with 74 volunteers in Shenzhen, China, machine learning models trained on MR-based data achieved 20–50% higher R² for subjective perception than models trained on traditional screen-based data. The validated framework was then applied to 61,131 SVIs citywide to map the spatial distribution of multidimensional green perception and to quantify relationships between objective and subjective indicators. Going beyond technical validation, this study demonstrates how the framework serves as a critical tool for urban planning and landscape upgrading. By diagnosing perceptual deficits where greening quantity does not translate into quality experiences, the framework supports a paradigm shift from quantity-oriented greening to perception-oriented spatial optimization. These findings offer actionable insights for policymakers to prioritize interventions that effectively enhance public health and environmental equity in high-density cities. Full article

In Peru, where socioeconomic inequalities remain a critical challenge, responsible consumption has shifted from individual decisions to organizational strategies with the potential to reduce structural disparities. This study adopted an exploratory–descriptive qualitative design to gain an in-depth understanding of organizational initiatives for responsible consumption and their contributions to social equity. Using documentary analysis, the READ protocol (Read, Extract, Analyze, Distill) was applied to systematically examine public information from 104 Perú Sustainable-affiliated organizations across 16 economic sectors. The analysis identified six categories of initiatives: eco-efficient management, circular economy, sustainable supply chains, education and awareness, sustainable products, and green financing that are linked to five dimensions of equity: economic inclusion, access to essential services, gender equality, inclusion of vulnerable populations, and capacity building. The circular economy (54.8%) and sustainable supply chains stood out for their greater potential to include vulnerable groups by integrating them into formal value chains. The reported impacts ranged from 100 to over one million beneficiaries, in addition to environmental reductions of 30–50%, although methodological heterogeneity limited comparability. Financial constraints (67.3%), along with cultural resistance and institutional barriers, were identified as the main obstacles. Overall, the findings show that responsible organizational consumption can be an effective mechanism for reducing inequality if designed using systemic and integrated approaches, reinforcing the need for public policies, specialized financial instruments, and regulatory frameworks that enhance its transformative impact in favor of inclusive development in the country. Full article

Background: Healthcare workers are at the forefront of the global battle against COVID-19. Their vaccination perspectives, particularly in regions like Sierra Leone that have faced health crises such as the Ebola outbreak, are essential for shaping public health strategies in low-income countries that routinely face infectious disease outbreaks. Objective: This research sought to understand the perceptions and experiences of Sierra Leone’s healthcare workers concerning COVID-19 vaccination and booster doses, set against the backdrop of global health resource disparities and regional vaccine distribution challenges. Methods: Utilizing a mixed-methods approach, the study analyzed data from an online survey, which saw 1001 complete responses from 2060 participants across six Ebola-impacted districts (October–November 2022), and in-depth interviews with 24 health workers from three of these districts (February–July 2022). Results: Approximately 80% of respondents reported having received a COVID-19 vaccine, predominantly Sinopharm and AstraZeneca, yet only 34% of vaccinated participants had received a booster dose. In multivariable analyses, personally knowing someone who experienced serious COVID-19 illness or death was associated with higher odds of both initial vaccination and booster uptake (p < 0.05). By contrast, prior Ebola-related experiences were not consistently associated with vaccination outcomes. Qualitative findings contextualized these patterns, highlighting the roles of professional exposure, limited booster-related information, and inequities in vaccine availability and distribution. Conclusion: These findings indicate that vaccination strategies must move beyond initial rollout to address barriers to sustained engagement, particularly for booster uptake among healthcare workers. They also emphasize the need for equitable vaccine access and transparent, locally tailored communication to mitigate structural and informational constraints in low-income settings. Full article

Engineering education is increasingly shaped by two converging developments: accelerating sustainability transitions and rapid advances in artificial intelligence (AI). However, in many application-oriented undergraduate programs, sustainability learning remains fragmented, methodologically limited, and weakly connected to authentic engineering decision-making. To address this gap, this study proposes AI-SEE (Artificial Intelligence-Integrated Sustainable Engineering Education), a pedagogical framework that integrates AI across the curriculum as both a cognitive scaffold and a resource for system-level analysis. Emphasizing human–AI collaboration, AI-SEE is designed to be feasible and scalable within application-oriented higher education contexts. The framework comprises four interrelated pillars: intelligence-driven, green-empowered, responsibility-leading, and practice-integrated. Drawing on an empirical case from transportation-related programs at Nantong University, the study employs a qualitative comparative design and conducts semi-structured interviews with 144 undergraduates at the end of their eighth semester (control group n = 70; pilot group n = 74). Interview data were analyzed using thematic analysis informed by constructivist grounded theory and the Gioia coding approach. The findings suggest that participation in AI-SEE is associated with differentiated patterns of sustainability consciousness. At the knowledge level, students reported more systematic and interdisciplinary understandings that extended beyond environmentally reductionist perspectives to include life-cycle thinking, social equity, and long-term considerations. At the attitudinal level, students described enhanced ethical reflexivity and evolving professional self-concepts, shifting from a focus on technical execution toward broader value-oriented roles. At the behavioral level, students reported more extensive knowledge-to-action translation across personal, academic, and career-related domains. Overall, AI-SEE provides a transferable pedagogical pathway for integrating AI into engineering education to support the development of sustainability consciousness in higher education. Full article

This paper investigates the relationship between institutional ownership and firm-level idiosyncratic volatility across European equity markets, with a particular focus on the moderating role of dividend policy. Using a sample of STOXX Europe 600 constituents from 2005 to 2025, we estimate idiosyncratic volatility via the Fama-French three-factor model and employ fixed-effects regressions with clustered standard errors. Our empirical results reveal a positive and statistically significant association between institutional ownership and idiosyncratic volatility, suggesting a destabilizing rather than stabilizing role in European markets. This volatility-enhancing effect is significantly more pronounced among dividend-paying firms and is primarily driven by transient institutional investors with high portfolio turnover. Furthermore, we find that: (1) larger firm size (market capitalization) and higher leverage (debt-to-capital ratio) are positively associated with heightened volatility; (2) growth-oriented firms (high market-to-book ratios) exhibit increased volatility, particularly among non-dividend payers; and (3) higher profitability (ROE) and favorable analyst coverage (buy recommendations) act as stabilizers, reducing idiosyncratic risk. These findings persist in both contemporaneous and lagged specifications. This study contributes to the literature by identifying dividend policy as a key channel through which institutional trading behavior amplifies firm-specific risk, providing novel evidence on the asset class effect within major European benchmark indices. Full article

Background: Despite advances in the management of acute coronary syndrome (ACS), women continue to experience higher long-term mortality and lower access to secondary prevention compared with men. Objective: This study aimed to assess whether a universally inclusive, nurse-led secondary prevention program implemented at a University Hospital improved post-ACS outcomes and reduced gender disparities in risk factor control and mortality. Methods: This retrospective, observational study compared two cohorts of ACS survivors discharged from Bellvitge University Hospital: a pre-intervention cohort (2018) and a post-intervention cohort (2022). The nurse-led program included universal enrollment of all ACS patients, early follow-up, pharmacological optimization, therapeutic exercise, lifestyle counseling, and coordination with primary care. Outcomes included lipid and glycemic control and 18-month mortality, stratified by sex. Results: A total of 409 patients were included (2018: n = 200; 2022: n = 209), of whom 130 were women. Women were older and had more comorbidities. Post-program implementation, the proportion of patients without post-discharge blood testing dropped from >50% to <17% in both sexes. Lipid and glycemic control improved significantly at both early (1–4 months) and late (9–18 months) follow-up. Early differences favoring men disappeared by 18 months. Mortality decreased by 27.5% in men and 47.6% in women, representing a significantly greater relative reduction among women (p = 0.0001). Conclusions: A structured, nurse-led secondary prevention program with systematic inclusion improved clinical outcomes and significantly narrowed the gender gap in cardiovascular mortality. These findings demonstrate that equitable, protocolized care led by advanced practice nurses can reduce systemic inequities in cardiovascular health. Full article

Despite the economic relevance of climate-transition risk, firm-level carbon exposure often fails to appear as a robustly priced factor when ESG measures and sustainability shocks are conflated. This study examines whether carbon exposure is conditionally priced in European equity returns using a strongly balanced quarterly panel of 238 firms from the MSCI Europe ESG Leaders universe (2018–2024). Total greenhouse gas emissions act as a proxy for carbon exposure, mapped to within-year percentiles and standardized by sector-year. Regressions control for ESG scores and controversies and include firm and quarter fixed effects with firm-clustered, dependence-robust standard errors. The linear carbon coefficient is small and statistically indistinguishable from zero, indicating no stable return premium from within-firm changes in carbon exposure. Functional-form tests reject linearity: quadratic and quintile specifications reveal curvature and a non-monotonic pattern, with return differences concentrated in the middle of the carbon distribution. Conditioning on macro-financial stress, measured by the ECB Composite Indicator of Systemic Stress, yields limited evidence of a uniform carbon penalty. However, high-controversy states are associated with lower returns, while ESG scores show negative associations under dependence-robust inference. Overall, carbon-related pricing appears to be nonlinear and state-dependent, whereas controversy risk is the most robust sustainability predictor of returns. Full article

For historically marginalized groups and residents of low-resource rural communities, contact tracing is a critical tool for controlling the spread of communicable diseases. To improve its effectiveness, more research on identifying factors that influence an individual’s willingness to comply with contact tracers is needed. Therefore, we examined the association of race/ethnicity, contextual factors, and willingness to engage in contact tracing during the COVID-19 pandemic. The sample included 337 adults (56% Black/African American and 66% female). Approximately 80% of the participants indicated they would disclose the names of contacts. The results from the multivariate logistic regression analyses indicated lack of access to COVID-19 testing sites (aOR = 2.20; 95% CI = 1.08–4.48) and trust in health care providers (aOR = 7.57; 95% CI = 3.82–14.88) were significantly associated with willingness to share information with contact tracers. Race did not moderate the relationship between trust and engaging with contact tracers. The results suggest contact tracing is a viable strategy for mitigating disease transmission in rural communities, particularly when trust in health care providers is high and access to testing is limited, regardless of race. Public health officials should invest in maintaining contact tracing teams that include medical providers and prioritize building trusting relationships with all community members. Full article