Search Results (458)

English writing proficiency is pivotal to sustainable academic success and employability. In Chinese higher education, however, conventional instruction often constrains students’ self-regulation and access to individualized feedback. Drawing on self-regulated learning (SRL) and co-regulated learning (CoRL), this study investigates whether a CoRL-guided generative AI virtual teacher (CoRL-VT), designed as a “more capable other,” is associated with enhanced undergraduate writing outcomes relative to standard AI support. Using a 12-week quasi-experimental design with two intact classes (N = 61) in Anhui, China, we compared a control condition (standard AI) with an intervention (CoRL-VT). Writing proficiency was assessed via IELTS Writing Task 2 at pre- and post-test; three certified examiners scored all scripts with strong agreement (ICC = 0.87). Analyses adjusting for baseline yielded an estimated group difference favoring CoRL-VT. Teacher interview testimony aligned with the quantitative pattern, noting clearer macro-organization, richer lexical choices, and more teacherly formative feedback among CoRL-VT students. Taken together, these findings offer exploratory, descriptive evidence consistent with the potential of structured, CoRL-informed AI scaffolding in sustainable writing pedagogy and outline design principles for replicable CoRL-VT implementations in resource-conscious contexts. Full article

Background: This study aimed to analyze the patterns and underlying reasons associated with population movement across Sindh, Pakistan. Methods: Cross-sectional surveys were conducted in response to the detection of WPV1 in various districts in Sindh province, where genetic linkages with poliovirus isolates in Karachi had been identified. The surveys targeted union councils (UCs) contributing sewage to the environmental sample collection sites where WPV1 was detected. Results: In the Karachi division a total of 1392 participants were interviewed, and outside Karachi 1471 participants were included. A significantly higher proportion of female participants were interviewed in Karachi (n = 72, 55.0%) compared to other divisions of Sindh (n = 794, 45.0%) (p < 0.001). Linguistic distribution varied significantly between regions, with Pashto speakers predominating in Karachi (n = 336, 86.4%), and Sindhi in other divisions (n = 501, 79.4%) (p < 0.001). OPV coverage exceeded 90% across all districts, and over 85% of children received RI vaccines. Travel patterns also differed significantly; participants from Karachi (n = 686, 44.2%) were less likely to report travel compared to other divisions (n = 865, 55.8%), who frequently traveled for family events, business, or employment (p < 0.001). Conclusions: It is critical to redefine high-risk populations annually based on updated mobility data, social survey analyses, and virus detection via surveillance to better identify and reach unvaccinated children in the Pakistan polio program. In addition, strategically placed PTPs along both formal and informal travel corridors based on an updated risk framework will enhance vaccination, thereby reducing the risk of virus spread. Full article

This study focuses on the analysis of the simultaneous impact of inclined magnetohydrodynamic Carreau hybrid nanofluid flow over a stretching sheet, including microorganisms with the effects of chemical reactions in the presence and absence of slip conditions for dilatant $(n>1.0)$ and quasi-elastic hybrid nanofluid $(n<1.0)$ limitations. Meanwhile, the transfer of energy is strengthened through the employment of heat sources and bioconvection. The analysis incorporates nonlinear thermal radiation, chemical reactions, and Arrhenius activation energy effects on different profiles. Numerical simulations are conducted using the efficient Bvp5c solver. Motile concentration profiles decrease as the density slip parameter of the motile microbe and Lb increase. The Weissenberg number exhibits a distinct nature depending on the hybrid nanofluid; the velocity profile, skin friction, and Nusselt number fall when $(n>1.0)$ and increase when $(n<1.0)$. For small values of inclination, the 3D surface plot is far the surface, while it is close to the surface for higher values of inclination but has the opposite behavior for the 3D plot of the Nusselt number. A detailed numerical investigation on the effects of important parameters on the thermal, concentration, and motile profiles and the Nusselt number reveals a symmetric pattern of boundary layers at various angles $\left(\alpha \right)$. Results are presented through tables, graphs, contour plots, and streamline and surface plots, covering both shear-thinning cases $(n<1.0)$ and shear-thickening cases $(n>1.0)$. Full article

Background: Degenerative lumbar spine disease is a prevalent cause of chronic low back pain that significantly impairs daily function and quality of life. While conservative management is the first line of treatment, many patients ultimately require instrumented lumbar spine surgery. However, postoperative outcomes vary considerably, with emerging evidence suggesting that preoperative psychological factors such as anxiety, depression, and pain catastrophizing may influence recovery. The SAP-LD (Scale for Anxiety and Pain in Lumbar Degeneration) study was designed to assess the prognostic role of these psychological and physical parameters in surgical outcomes. Methods: This prospective observational study enrolled 70 adult patients with degenerative lumbar spine pathology scheduled for instrumented surgical treatment at the University of Brescia and ASST Spedali Civili di Brescia between March and December 2024. Preoperative assessments included demographic, clinical, and radiologic data along with validated scales: the Oswestry Disability Index (ODI), 36-Item Short Form Health Survey (SF-36), Visual Analogue Scale (VAS), Pain Catastrophizing Scale (PCS), and Hospital Anxiety and Depression Scale (HADS). Follow-up evaluations were performed at 45 days and at 6 months, and statistical analyses were conducted using correlation tests, ANOVA, and regression modeling. Results: The demographic analysis of the 70 enrolled patients shows a balanced gender distribution (38 females, 34 males) with a mean age of 61 years (range 23–81). The educational level distribution indicates that the majority of patients (44.29%) have a secondary education level, while 35.71% have a tertiary education level. Regarding employment status, 50% of the patients are retired or not working. Patients with clinically significant anxiety and/or depression showed higher levels of perceived pain, pain catastrophizing, and disability at baseline. These patients reported significantly worse scores on the Visual Analogue Scale (VAS), Pain Catastrophizing Scale (PCS), and Oswestry Disability Index (ODI). The Oswestry Disability Index (ODI) demonstrates a clinically significant improvement (reduction) in disability between the preoperative period (t0) and the 45-day follow-up (t2), with the median decreasing from 39.00 to 13.00. However, there is a partial regression at the 6-month follow-up (t3), with the median increasing to 27.00. For the SF-36 Health Survey, the General Health subscale shows an improvement between t0 and t2 (median increasing from 55.00 to 60.00), followed by a slight decrease at t3 (median 55.00). Similar patterns are observed in most other subscales, with initial improvement followed by partial regression. The Pain Catastrophizing Scale (PCS) shows a substantial reduction in catastrophizing between t0 and t2 (median decreasing from 16.00 to 3.00), followed by an increase at t3 (median 11.00), though still below baseline levels. Pain intensity as measured by the Visual Analogue Scale (VAS) shows a significant reduction at t2 (median decreasing from 5.00 to 3.00), but increases again at t3 (median 6.00), even exceeding the preoperative level. For the Hospital Anxiety and Depression Scale (HADS), no significant differences were observed across time points, with values indicating mild symptoms throughout the study period. Correlation analyses confirmed that higher preoperative anxiety and depression scores were predictive of poorer postoperative outcomes. Specifically, higher HADS scores at baseline are associated with higher ODI scores (increased disability) at all time points (p = 0.002), higher VAS scores (increased pain) at all time points (p = 0.015), and lower scores on SF-36 subscales, particularly Emotional Well-being (p = 0.00023) and Social Functioning (p = 0.002). Higher PCS scores at baseline are associated with higher ODI scores at all time points (p = 0.001), higher VAS scores at all time points (p = 0.008), and lower scores on SF-36 subscales, particularly Pain (p = 0.00023) and Physical Functioning (p = 0.04254). The mixed linear models analysis confirms these findings, showing that the ODI score decreases significantly between t0 and t2 (p = 0.00023) and increases between t2 and t3, though this increase is not statistically significant (p = 0.079). For VAS scores, there is a significant decrease between t0 and t2 (p = 0.00023) and a significant increase between t2 and t3 (p = 0.04254). Patients with elevated preoperative HADS scores tended to have slower recovery trajectories and reported lower satisfaction levels. These findings reinforce the prognostic value of psychological assessments in spine surgery and suggest that targeted psychological interventions could improve patient outcomes. Conclusions: By identifying psychological predictors of postoperative recovery, this study underscores the importance of integrating preoperative psychological screening into routine clinical practice. The results suggest that a multidisciplinary approach, including both surgical and psychological care, could enhance long-term functional outcomes and quality of life for patients undergoing instrumented lumbar spine surgery. Full article

ADHD and misophonia are developmental neurological disorders that are currently increasing in prevalence due to excessive acoustic and visual pollution. ADHD, which is characterized by a lack of attention and excessive impulsive hyperactivity, and misophonia, which is hypersensitivity to sounds accompanied by a severe emotional and psychological reaction, are both affected by the user’s spatial environment to a great extent. Spatial design can contribute to increasing or decreasing these unfavorable sensory triggers that affect individuals with ADHD and/or Misophonia. However, the role of architectural spatial design as a therapeutic approach to alleviate the symptoms of Misophonia and ADHD has never been proposed before in the literature, despite its accumulative and chronic effects on the user’s experience in everyday life in terms of well-being and productivity. Therefore, the current work discusses this problem of neglecting the potential effect of architectural spatial design on alleviating Misophonia and ADHD. Thus, the objective of the current work is to propose customized architectural spatial design as a therapeutic approach to alleviate Misophonia and ADHD through adopting the compatible architectural trends of minimal and metaphysical architecture. The methodology of the current work includes a theoretical proposal of this customized architectural spatial design for alleviating these two special neurological conditions. This includes introducing and analyzing these two neurological conditions and their relation to and interaction with architectural spatial design, analyzing minimal and metaphysical architectural trends employed in the proposed therapeutic architectural design, and then proposing augmented and virtual reality as auxiliary add-ons to the architectural spatial design to boost its therapeutic effect. Minimal architecture achieves the “no emotion” criteria through reduced forms, patterns, and colors and adopts simple geometry and natural materials to reduce sensory stressors or stimuli, in order to alleviate the loss of attention and distraction prevalent in those with ADHD, as well as allowing the employment of acoustic materials to achieve acoustic comfort and noise blockage for Misophonia relief. Metaphysical architecture leads the hierarchy of sensory experience through the symbolistic, dynamic, and enigmatic composition of forms and colors, which enhance the spatial analysis and cognitive capacities of the inhabitants. Meanwhile, the use of customized virtual and augmented reality environments is an effective add-on to minimal and metaphysical architectural spaces thanks to its proven therapeutic effect in alleviating various neurological disorders and injuries. At this level of intervention, VR/AR can be used as an add-on to minimal-architecture design, to simulate varied scenarios, as minimal design offers a clean canvas for simulating these varied virtual environments. The other option is to build these customized VR/AR scenarios around a specific architectural element as an add-on metaphysical architecture design to lead the sensory experience and enable the user to detach from the physical constraints of the space. AI-generated designs were used as a proof of concept for the proposed customized architectural spatial design following minimal and metaphysical architecture, as well as to provide AR and VR scenarios as add-on architecture to enhance the therapeutic effect of these architectural spaces for Misophonia and ADHD patients. Furthermore, the validity of VR/AR as a therapeutic approach, alongside the customized architectural design, was discussed, and it was concluded that this study proves the need for extended clinical studies on its efficiency in the long run, which will be conducted in the future. Full article

Background: Higher socioeconomic status (SES) is generally associated with lower engagement in health-risk behaviors, in part due to increased access to health information, preventive resources, and supportive environments. However, emerging evidence suggests that this protective pattern may not extend uniformly to all forms of substance use, including adolescent e-cigarette use, and may vary by gender. For instance, some studies have found higher rates of e-cigarette use among adolescents from higher SES backgrounds. Aim: This study examined whether the associations between family SES and tobacco use differ between girls and boys. We also explored whether these associations vary by age group. Methods: A cross-sectional survey was conducted among students (age 14–20) attending public high schools in Baltimore City. Family SES was assessed using three indicators: parental education, parental employment, and household income. Tobacco use was measured using self-reported past use of e-cigarettes and conventional cigarettes. Demographic covariates included age, sex, race/ethnicity, and household composition. Separate logistic regression models were estimated for each tobacco use outcome, adjusting for covariates. To examine subgroup differences, analyses were stratified by gender and age. Results: Higher parental education was associated with lower odds of e-cigarette use, but no SES indicators were significantly associated with conventional cigarette use. Subgroup analyses showed that the protective association of parental education against e-cigarette use was evident among girls but not boys and among older but not younger adolescents. Conclusions: These findings differ from previous studies that reported a positive association between SES and adolescent e-cigarette use. In this predominantly low-income, urban sample, higher parental education appeared to be protective for girls but not for boys. These results suggest that SES influences on tobacco use may be context- and subgroup-specific. Further research is needed to better understand how sociodemographic and contextual factors shape adolescent tobacco use behaviors. Full article

Multimodal transportation systems, particularly those combining metro and bikesharing, have become central to addressing the first- and last-mile connectivity challenges in urban environments. This study presents a comprehensive data-driven framework to analyze the spatiotemporal interplay between metro and dockless bikesharing usage using real-world data from Tianjin, China. Two primary methods are employed: K-means clustering is used to categorize metro stations and bike usage zones based on temporal demand features, and non-negative Tucker decomposition is applied to a three-way tensor (day, hour, station) to extract latent mobility modes. These modes capture recurrent commuting and leisure behaviors, and their alignment across modes is assessed using Jaccard similarity indices. Our findings reveal distinct usage typologies, including mismatched (misalignment of jobs and residences), employment-oriented, and comprehensive zones, and highlight strong temporal coordination between metro and bikesharing during peak hours, contrasted by spatial divergence during off-peak periods. The analysis also uncovers asymmetries in peripheral stations, suggesting differentiated planning needs. This framework offers a scalable and interpretable approach to mining multimodal travel patterns and provides practical implications for station-area design, dynamic bike rebalancing, and integrated mobility governance. The methodology and insights contribute to the broader effort of data-driven smart city planning, especially in rapidly urbanizing contexts. Full article

Global food systems have faced multiple shocks that threaten the implementation of their main functions. This article analyzes the most recent studies and aims to develop a socioeconomic resilience assessment dashboard for agriculture as a component of the food system and estimate the resilience of the Baltic states in 2013 and 2023. The selected years allow us to compare resilience before and after the most recent agricultural market crisis. The resilience assessment dashboard includes leading and lagging indicators and uses the distance to a reference measure normalization method to compare resilience indicators in individual countries with the EU average. Leading indicators, focusing on the ability of the system to implement changes, distinguish the Estonian case and suggest that structural patterns of this country could empower different actions to increase resilience compared to other Baltic states. Lagging indicators, focusing on the key functions of the system, suggest that the Baltic states have improved their nutritional security; however, this research identifies a high concentration of ex-EU imports for the fats and oils group, the animal products group, except for the CN03 category, and the vegetable products group, with the exception of the CN08 and CN09 categories, as an important resilience challenge of national food security. The results imply the importance of policy actions aiming at the further development of national trade networks and the diversification of import markets. Farm economic viability indicators, except for debt ratio, evidence annual instability and unfavorable resilience compared to the EU average, while, in Latvia and Lithuania, agriculture remains an important employer and contributes to the resilience of national economies. The analyzed leading indicators suggest that the Baltic states could prioritize different agricultural policy actions and budget allocation addressing national farm viability and agricultural employment challenges. Full article

The paper revisits Janssen’s proposal of Common Origin Inferences (COIs), a powerful and scientifically fruitful inference pattern that (causally) traces striking coincidences back to a common origin. According to Janssen, COIs are a decisive engine for rational theory change across disciplines and eras. After a careful reconstruction of Janssen’s central tenets, we critically assess them, highlighting three key shortcomings: its strong realist and ontological commitments, its restriction to (or strong penchant for) causal/ontic explanations, and its intended employment for conferring evidential-epistemic status. To remedy these shortcomings, we moot a natural generalisation and amelioration of Janssen’s original conception—COI*s: Constraint-Omnivorous Inferences. COI*s warrant inference to pursuit-worthy hypotheses: it is rational to further study, work on, elaborate/refine or test hypotheses that account for multiple constraints in one fell swoop. As a demonstration of the utility of COI* reasoning, we finally show how it sheds light on, and dovetails, the three most significant breakthroughs in recent cosmology: the Dark Matter hypothesis, the Dark Energy postulate, and the theory of cosmic inflation. Full article

This study examines regional disparities and convergence dynamics in paediatric healthcare accessibility across Poland’s 16 provinces between 2010 and 2023. A synthetic Paediatric Service Accessibility Index (PSA Index), constructed with Hellwig’s method, is combined with socio-economic indicators such as employment, urbanisation, and disposable income to evaluate the alignment between healthcare provision and regional development. The analysis employs non-parametric regional tests (Spearman’s rank correlation, Wilcoxon signed-rank test) and national panel regression models (Fixed and Random Effects). Results demonstrate significant spatial heterogeneity: economically advanced regions, including Mazowieckie and Małopolskie, show moderate to strong convergence between socio-economic progress and healthcare access, whereas structurally weaker regions such as Lubuskie and Podkarpackie reveal persistent divergence. Disposable income and urbanisation emerge as significant predictors of healthcare availability (p < 0.01), while employment is not statistically significant. The findings highlight enduring inequalities that are relevant in the context of the European Union’s (EU) cohesion policy and indicate that economic growth alone is insufficient to ensure equitable access to paediatric care. Comparative evidence from Romania, Bulgaria, and Spain points to similar patterns and emphasises the importance of EU Structural and Investment Funds in promoting healthcare equity. The study concludes that territorially sensitive, multidimensional interventions are necessary to advance social sustainability and to align healthcare infrastructure with the Sustainable Development Goals, particularly SDG 3 (Good Health and Well-Being) and SDG 10 (Reduced Inequalities). Full article

Background and Objectives: Professional burnout threatens special education teachers’ well-being and educational service quality through three psychological dimensions: emotional exhaustion, depersonalization, and personal achievement. Limited studies have employed behavioral data analysis to examine burnout patterns in special education and their relationships with demographic factors and contemporary stressors. This study aimed to (1) identify burnout levels among Greek special education teachers, (2) determine demographic risk factors, and (3) examine relationships between burnout dimensions and COVID-19 psychological impact. Materials and Methods: A cross-sectional study surveyed 114 special education teachers from Achaia and Aitoloakarnania prefectures, Greece (response rate: 87.7%), using the Maslach Burnout Inventory–Educators Survey (MBI-ES) and demographic questionnaires. Behavioral data analysis integrates traditional statistics with advanced techniques, including cluster analysis and classification modeling. Results: Four distinct burnout profiles emerged: Low Burnout (36.8%), Moderate Emotional Exhaustion (30.7%), High Risk (21.9%), and Depersonalization-Dominant (10.5%). Overall burnout prevalence was low, with 73.7% showing minimal depersonalization and 67.5% maintaining high personal achievement. Employment status emerged as the strongest predictor of burnout risk. Emotional exhaustion was the primary predictor of COVID-19 psychological impact (r = 0.547, p < 0.001), explaining 29.9% of pandemic-related distress variance. Male substitute teachers demonstrated the highest vulnerability to depersonalization, while experienced female permanent teachers showed resilience patterns. Conclusions: Behavioral data analysis revealed distinct burnout patterns enabling personalized interventions. Emotional exhaustion serves as both a key vulnerability factor and primary intervention target. These findings support targeted approaches to occupational health with implications for educational policy. Limitations include cross-sectional design and regional sampling. Future longitudinal studies should validate these patterns across diverse educational contexts. Full article

This study extends the post-Keynesian framework for cyclical economic growth, initially proposed by Goodwin in 1967, by integrating government intervention to stabilize employment amidst wage mismatches. Given the pressing challenges of unemployment and wage disparity in developing economies, particularly South Africa, this extension is necessary to better understand how policy interventions can influence labor market dynamics. Central to the study is the endogenous interaction between capital and labor, where class dynamics influence economic growth patterns. The research focuses on the competitive relationship between real wage growth and its effects on employment. Methodologically, the study measures the impact of intervention strategies using a system of coupled ordinary differential equations (Lotka–Volterra type), along with econometric techniques such as quantile regression, moving averages, and mean absolute error to measure wages mismatch. Results demonstrate the inherent contradictions of capitalism under intervention, confirming established theoretical perspectives. This work further contributes to economic optimality discussions, especially regarding the timing and persistence of economic cycles. The model provides a quantifiable approach for formulating intervention strategies to achieve long-term economic equilibrium and sustainable labor–capital coexistence. Full article

Persistent gender inequality in industrial employment continues to challenge inclusive labor systems worldwide. While education and labor market reforms have expanded opportunities for women, structural barriers remain deeply embedded in manufacturing sectors. This study adopts a systems-based perspective to investigate the institutional, demographic, and health-related factors shaping female employment in manufacturing across ten countries from 2013 to 2022. By integrating feminist political economy with interpretable machine learning techniques—including Random Forest, Gradient Boosting, and Extra Trees regressors—the study models non-linear and interactive relationships among thirteen structural indicators drawn from the World Bank’s World Development Indicators. The findings reveal that general female labor force participation is the strongest and most consistent predictor of women’s inclusion in manufacturing. Health-related variables, such as maternal mortality and fertility rates, exhibit strong negative effects, underscoring the continued influence of caregiving burdens and inadequate health systems. Education indicators show more variable impacts, suggesting that institutional context mediates their effectiveness. The use of SHAP and Partial Dependence Plots enhances the transparency of the models and supports a more nuanced understanding of how structural forces shape gendered labor outcomes. In addition to modeling structural inequalities, this study highlights how gender knowledges and cultures of equality are contextually produced and negotiated within the manufacturing sector. The findings underscore the importance of understanding both global systems and local cultural frameworks in shaping gendered employment outcomes. By linking interpretable machine learning with systems thinking, this research provides a holistic and data-driven account of industrial gender inequality. The results offer policy-relevant insights for designing more inclusive labor strategies that address not only economic incentives but also the social and institutional systems in which employment patterns are embedded. Full article

Residential mobility is not only a demographic process but also a mechanism that reshapes urban form, economic vitality, and spatial inequality. In South Korea, where rapid population decline and stark regional disparities pose urgent planning challenges, analyzing the determinants of residential in-migration provides critical insights into how cities and regions adapt to these demographic shifts. This study addresses the questions of why individuals relocate and how migration drivers vary across regional typologies and age cohorts. Using a Negative Binomial Regression framework applied to spatially disaggregated migration data, this study identifies several key patterns. Housing prices, population density, and network centrality consistently act as strong and positive predictors of in-migration across regions and cohorts. Even shrinking cities retain attractiveness through density, likely reflecting service accessibility and agglomeration benefits. Employment opportunities, school proximity, and road network density play crucial roles in peripheral regions. Katz centrality strongly shapes decisions among younger populations (≤39), while older adults (65+) prefer areas with lower economic intensity and better access to public transportation. These findings advance theoretical understandings of residential mobility and offer policy-relevant insights for age-sensitive and regionally differentiated urban planning. Full article

Access to business financing in Europe has historically been a challenge for small and medium-sized enterprises (SMEs), which represent a significant share of economic activity and employment in Europe. This issue has been significantly intensified since the global financial crisis, disproportionately affecting this segment. This study analyzes firm-level determinants influencing access to alternative financing sources, including crowdfunding, venture capital, and other non-bank channels, using data from the 2023 SAFE covering 15,855 firms across Europe. Results indicate that firm size significantly affects access, with larger, established firms more likely to secure such funding. However, younger, innovation-driven firms demonstrate a higher propensity to pursue equity and crowdfunding options, driven by their need for flexible and early-stage capital. Sectoral patterns also emerge: industrial firms more often obtain public grants, while service-sector firms lead in adopting equity-based and crowdfunding models. The findings highlight the critical role of innovation capacity and international orientation in broadening financial access. Digital platforms are identified as key enablers in democratizing funding, particularly for SMEs. This research advances understanding of SME financing dynamics within evolving financial landscapes and provides actionable insights for policymakers and practitioners aiming to promote inclusive and sustainable access to finance. Full article