Search Results (1,100)

Perceived employability is increasingly recognized as a core component of individuals’ capacity to build sustainable careers: occupational trajectories that remain viable, meaningful, and adaptive across the working lifespan. Within the broader framework of the United Nations Sustainable Development Goals, particularly SDG 4 (Quality Education) and SDG 8 (Decent Work and Economic Growth), higher education institutions play a strategic role in equipping students with the psychological resources needed for a successful and sustainable transition from education to employment. This study examined the university learning experience in relation to perceived employability, testing college satisfaction as a mediator between two key academic dimensions, good teaching and university commitment, and students’ occupational self-perception. A sample of 179 students (59.2% female; Mage = 24.40, SD = 5.95) enrolled at the University of Palermo completed self-report measures of all four constructs. A mediation model was tested on composite scale scores, with indirect associations estimated through bias-corrected bootstrapping (5000 resamples). Good teaching (b = 0.332, β = 0.338, p < 0.001) and university commitment (b = 0.250, β = 0.247, p = 0.001) were both positively associated with college satisfaction, accounting for 26.3% of its variance; college satisfaction, in turn, was positively associated with perceived employability (b = 0.258, β = 0.396, p < 0.001), with the full model accounting for 32.8% of the variance in perceived employability. College satisfaction fully accounted for the association between teaching quality and perceived employability, and partially accounted for the association between university commitment and perceived employability. These findings point to a consistent conclusion: a satisfying and supportive academic experience is not a peripheral feature of university life, but a key process through which students develop a confident sense of their own occupational potential. For universities, this translates into concrete levers, namely teaching quality and institutional belonging, that can meaningfully support students’ long-term and resilient integration into the labor market, while contributing more broadly to the sustainability of the higher education-to-work pipeline. Full article

Tuberculosis (TB) remains one of the most burdensome infectious diseases in Indonesia. One contributing factor is the environment, particularly issues related to household ventilation and lighting. TB control efforts do not solely rely on medical interventions but also require a community-based approach that emphasizes active community involvement in preventing and controlling environmental risks to TB transmission. This study aims to analyze risk factors, distribution patterns, and their implications for environmentally based TB transmission risk control strategies. A mixed-methods design was conducted in two stages: first, risk factor analysis (with a case–control approach) and disease distribution pattern determination on environmental variables were performed, followed by a multidimensional scaling model (by using the Rapid Appraisal for Fisheries (RAPFISH) method) according to sustainability dimensions (ecological, economic, social, institutional, and technological) based on the resulting significant variables/indicators. This research was conducted in 2024, in four villages/nagari in West Sumatra of Indonesia. For quantitative analysis, data were collected through interviews, physical measurements of the environment, and determination of the coordinates of the residences of people with TB. Data were analyzed using bivariate and multivariate analyses. For the distribution pattern, Nearest Neighbor Analysis (NNA) in the ArcView program version 3.1 was used. Meanwhile, for qualitative data collection, focus group discussion (FGD) was performed. This study found that poor ventilation, minimal lighting, and a lack of stigma competency significantly increased the risk of TB transmission. Varied distribution patterns between regions demand adaptive and locally based strategies. The community-triggering approach is key to building community awareness and participation in creating a healthy and TB-free home environment. Full article

Greenhouses in subtropical and tropical regions must be designed as agricultural engineering systems adapted to local climates, rather than simply replicating the “insulation” models of temperate areas. Under extreme climatic conditions such as persistent high temperatures, intense solar radiation, high humidity, heavy rainfall, and frequent extreme winds, greenhouses transform from enclosed insulation layers into selective climate filters, mitigating crop stress while maintaining close contact with the outdoor environment. This paper summarizes how these climate drivers are reshaping the use, structure, and control concepts of greenhouses, emphasizing that the performance of warm-zone greenhouses depends primarily on heat dissipation, humidity management, and biohazard control, rather than heating and insulation. In this review, we analyze the climatic boundary conditions that define warm-climate conservation cultivation, including long-term overheating risk, high UV radiation, vapor pressure deficit, and suppressed condensation tendency, as well as storm-induced uplift and dynamic loads. These constraints necessitate unique structural forms: tall, lightweight, well-ventilated building types with large roof and side openings, roof geometries that facilitate rainwater runoff, sophisticated drainage systems, and corrosion-resistant materials suitable for humid and coastal environments. Because insect netting significantly reduces ventilation, pest control and temperature regulation become co-design issues, requiring oversized vents, optimized airflow paths, and hybrid roof–mesh structures. Ventilation is considered the primary climate-control mechanism, supplemented by passive cooling measures such as shading and radiation/optical management (e.g., diffuse films and near-infrared-selective films). Active evaporative cooling is considered a conditional measure due to humidity limitations and disease risks. This paper also integrates the impacts on specific crops (fruits and vegetables, leafy greens, and orchids). It highlights emerging trends: typhoon-resistant and adaptive geometries, computational fluid dynamics (CFD)-based design, and sensor-rich IoT/digital twin control frameworks. These principles collectively establish a coherent design framework for achieving resilient, resource-efficient greenhouse production in warm climates. Full article

Background: Family caregivers of children with rare diseases are more likely to have symptoms of anxiety, depression, and post-traumatic stress disorder (PTSD). The WHO’s Group Problem Management Plus (Group PM+) is an evidence-based intervention providing psychological help for adults impaired by distress while exposed to adversity. Our objective was to adapt and beta test Group PM+ with family caregivers. Methods: Family caregivers were >18.0 years at enrollment experiencing psychological distress. Rare Group PM+ is five weekly sessions teaching stress management, problem solving, and building social support. Assessments were the PTSD Checklist for DSM-5 (PCL-5), Patient Health Questionnaire-9, and Generalized Anxiety Disorder-7. Paired Wilcoxon signed-rank tests measured the median baseline and 2-week follow-up values. Results: Sessions were reduced to 90 min and delivered through telehealth. Eight participants enrolled, including seven females with mean age of 40 years. Completion and retention rate were 100% (8/8). Participant-identified barriers to joining included: time constraints; concerns about re-traumatization; and confidentiality. PCL-5 decreased from a median of 29 to 17.5; GAD-7 from 11.5 to 4.5; and PHQ-9 median scores decreased but not significantly. Conclusions: Rare Group PM+ demonstrated initial acceptability and feasibility. Future research should examine initial efficacy in a larger rigorous pilot randomized controlled clinical trial. Full article

Pluvial flooding is intensifying in fast-growing coastal cities as rapid urbanization increases impervious surfaces and reduces natural infiltration, challenging planners to identify scalable and site-level mitigation strategies. Although statutory setbacks around institutional buildings are widely mandated for ventilation, safety, and accessibility, their contribution to urban flood resilience remains largely unexplored. This study develops the Flood Setback Performance Index (FSPI), a dimensionless indicator that integrates setback permeability and area-weighted runoff coefficients to quantify the flood-mitigation potential of mandatory setbacks. The framework was demonstrated using eight government school campuses in the Chennai, Chengalpattu, and Thiruvallur regions, which are part of a flood-prone coastal metropolis in India, following the extreme rainfall event of December 2025. Flood conditions were verified through post-event field surveys and visual evidence, while setback characteristics were extracted from satellite imagery and classified into permeable and impervious surfaces. The permeable fraction of setbacks and the FSPI values exhibited a strong inverse relationship with flood severity (Spearman’s ρ = −0.87, exact permutation p = 0.011). Ordinal logistic regression confirmed this gradient (likelihood-ratio χ² = 9.3–10.3, p ≤ 0.002, McFadden’s R² = 0.54–0.60), and campus rankings were made under saturated runoff coefficients. The findings demonstrate that statutory setbacks can function as nature-based flood-mitigation infrastructure with measurable hydrological benefits. Beyond the case study, the FSPI provides a simple, transferable, evidence-based tool for screening institutional sites by flood-mitigation performance and prioritizing where adaptation measures, such as increasing permeable-surface cover within statutory setbacks are needed, supporting climate-resilient urban planning and providing a regulatory reform decision-support tool with three applications: prioritizing the campus-level retrofit of permeable surfaces; screening building applications against setback surface standards; and identifying shelter-designated schools that require drainage upgrades. It thereby supports climate-resilient urban planning, regulatory reform, and progress toward Sustainable Development Goals 11 and 13. Full article

Buildings have significant impacts on the environment throughout their life cycle in terms of energy and water consumption, material usage, and waste generation. This study aims to evaluate the Sivas Train Station and Sivas High-Speed Train Station buildings, which were constructed in different periods and with different construction techniques, within the scope of sustainable renovation. In the study, the literature on sustainable architecture and building renovation approaches was reviewed; field observations, archival documents, interviews, and on-site measurements of temperature, thermal transmittance, and lighting were utilized. The buildings were compared based on criteria such as energy and water efficiency, material selection, and waste management. The findings indicate that the lack of insulation, old joinery, and absence of windbreaks in the Sivas Train Station, as well as the extensive glass surfaces, high user traffic, entrance layout, and operational issues with technical systems in the High-Speed Train Station, lead to energy losses. The lack of independent monitoring of water consumption in both buildings, the absence of systems for using rainwater, snow and graywater, and the inadequacy of waste separation practices have been identified as significant deficiencies. As a result of the study, different renovation strategies were proposed, preserving the original values of the historical structure and adapting the new structure to real usage conditions. It was concluded that sustainable renovation should be considered a continuous and holistic process that includes not only physical interventions but also building management, user training, regular monitoring, inspection, and certification. Full article

The rapid expansion of high-speed railway networks has increased the operational energy demand and indoor overheating risk of large-scale, high-volume railway station buildings. Natural ventilation is a climate-responsive passive strategy that can improve indoor environmental quality and reduce reliance on mechanical cooling. However, its contribution to the operational sustainability of large transportation buildings remains insufficiently quantified, particularly in hot-summer and cold-winter regions. This study investigates a seasonally adaptive window-opening strategy for Chengdu Station, with particular attention to major functional spaces such as waiting halls and commercial areas. A DesignBuilder model was used to simulate six ventilation scenarios, ranging from doors-only operation to fully open doors and windows. The effects of different window-opening ratios on hourly indoor temperature, relative humidity, adaptive thermal comfort, and annual building energy use were systematically evaluated. The simulation approach was further assessed against field measurements obtained from a comparable large railway station. The results reveal a pronounced nonlinear and seasonal response to the window-opening ratio. In winter, maintaining a very low opening ratio or keeping only the entrance doors open limits unnecessary heat loss. During the transitional seasons, opening ratios of 40–60% are sufficient to remove residual indoor heat while maintaining acceptable thermal conditions. In summer, the marginal improvement in ventilation performance becomes limited when the side-window opening ratio exceeds approximately 80%; therefore, an opening ratio of 80% was selected as a practical operating threshold rather than an absolute thermal optimum. Based on these seasonal characteristics, a month-by-month window-opening strategy was developed. Compared with the doors-only baseline, the proposed strategy reduced the annual high-temperature-hour ratio from 33.4% to 16.36%, corresponding to a decrease of 17.04 percentage points and a relative reduction of approximately 51.0%. Total annual building energy use decreased from 32,238.8 MWh to 25,923.8 MWh, representing an energy saving of 19.6%. These findings demonstrate that seasonally adaptive natural ventilation can simultaneously reduce overheating risk and operational energy demand while maintaining acceptable indoor thermal conditions. The proposed strategy provides a quantitative basis for the sustainable, energy-efficient, and intelligently managed operation of large-space railway stations in hot-summer and cold-winter regions. Full article

Background: Many studies have been carried out using scientific approaches, but the targets are uncertain due to variable environmental and human factors. Therefore, these two factors need to be integrated into modes, which represent combinations of devices in specific statuses. These modes should be changed in response to environmental conditions. To maximize the effectiveness of elemental technologies for environmental consideration, buildings must be designed alongside an operational method based on this mode changing, and the way of describing these operations must also be developed. In this paper, a logic of mode changing is established. The proposed design and operational method can be applied broadly to building design while being adaptable to individual cases. Methods: The design of a house based on the mode-changing theory is presented along with a provisional operational flow as a case study. To support the theory, CFD simulations of each mode’s configuration were conducted for comparison under the representative conditions. These conditions, which represent each mode, can be continuously changed to the other mode by occupants based on their personal comfort. After the house was built, mode-changing operations by the occupants themselves were monitored for a year for the purpose of an operational record. Results: The record of the modes manually selected by occupants, measurements of outdoor/indoor temperatures, and indoor illuminance are superimposed into an integrated graph. According to these records, an actual operational flow was extracted as a method for environmental adjustment. There are notable deviations between the provisional operational flow and the actual record. Based on the actual operational flow, the deviated behaviors are described in the flow, and reasons for the deviation are examined as conscious factors. Conclusions: The deviations from the provisional operational flow demonstrate the flexibility of the mode-changing design, which ultimately enhances occupant satisfaction. Further research is expected to develop a wider variety of modes. The cost analysis of the environmental adjustment devices, human contribution to mode changing, and energy saving ratio are verified as a case study providing a valuable reference for future projects. Full article

Optimizing outdoor thermal environments is essential for sustainable urban development and spatial resilience. Existing urban microclimate studies generally adopt the 1.5 m pedestrian height to represent outdoor thermal conditions. However, this widely accepted assumption has not been verified in multi-level campus spaces with terrace-induced complex three-dimensional environments, particularly in severe cold climate zones. This study investigates vertical thermal stratification and the relative influences of orientation, surface material, and height in Changchun, China. Field measurements at four levels were integrated with ENVI-met simulations calibrated against six independent validation sites. During summer peak hours, orientation dominates the thermal regime, outweighing both material and height. The peak thermal load shifts vertically from the south at lower elevations to the west at upper levels, generating a maximum air temperature difference of 1.66 °C compared to the consistently coolest east-facing terraces at 14:00. The vertical temperature profile does not follow a simple trend but varies with the surrounding geometry. Mid-level thermal trap appears near 3.5 m in the semi-enclosed building, where air temperature peaks before declining toward the roof. Moreover, an idealized model shows monotonic cooling with height, confirming that local obstructions cause the observed heat accumulation. During summer peak hours, surface material exerts a highly limited direct effect on ambient air temperature within these well-mixed three-dimensional spaces. Differences among concrete, asphalt, wood, and turf stay below 0.1 °C, roughly two orders of magnitude smaller than the orientation-driven contrast, because turbulent mixing and façade radiation overwhelm local surface heat fluxes. The findings highlight the inadequacy of evaluating thermal conditions at a single height, and challenge the conventional assumptions that material substitution is the primary heat mitigation measure in multi-level environments and that building orientation plays only a minor role in microclimate regulation. All quantitative outputs stem from ideal courtyard shapes and cloudless summer scenarios, reflecting mechanistic microclimate patterns instead of globally applicable predictive metrics. Local validation is mandatory before extending these conclusions to other seasons or building typologies. For sustainable summer thermal regulation on multi-level campuses, this work highlights orientation and adaptive shading as primary design measures, while material configuration acts only as auxiliary fine-tuning. Full article

Digital transformation is portrayed both as a lever of territorial convergence and as a driver of polarisation between urban cores and peripheries, yet its effect on regional economic resilience has rarely been measured systematically. This study transposes the Economic Resilience Index framework from the national to the regional scale, building a Regional Resilience Index (R-ERI) for 236 NUTS2 regions of the EU-27 from Eurostat indicators, anchored in the capacities of absorption, recovery, and adaptation and measuring resilience as a capacity rather than as a realised shock trajectory. Two complementary models are estimated: a spatial Durbin panel with two-way fixed effects (2018–2023), spanning the COVID-19 pandemic and 2022 energy shocks, and an exploratory cross-sectional difference model exploiting regional artificial intelligence (AI) adoption data disaggregated by NACE branch (2023–2025). The results show that resilience is strongly spatially autocorrelated (Moran’s I between 0.66 and 0.74; p = 0.001); that digital connectivity generates a positive indirect effect on neighbouring regions despite a negative own-region effect; and that the synergy hypothesis—that digitalisation yields more resilience when combined with traditional sectors—does not hold robustly, the interaction being null in the panel and only marginally positive in the AI layer (p = 0.10). We conclude that digital connectivity is not, on its own, an automatic convergence mechanism, and that cohesion policy should account for each region’s sectoral structure and peripheral position. Full article

Diagnosing faults across different smart homes is hard: sensor names, layouts, and daily routines differ from home to home, so a model trained in one home rarely works in another. We study an ontology-guided framework for cross-home fault diagnosis, but our main contribution is a benchmark-validity audit—a systematic check of whether the datasets used to evaluate such systems actually measure fault detection. Using the public Center for Advanced Studies in Adaptive Systems (CASAS) smart-home datasets (homes hh101–hh110) and real household power data (HomeC, UMass Smart*), we show that much of the high cross-home accuracy reported on these benchmarks is an artifact of features that re-encode the labelling rules rather than evidence of transfer: when those features are removed, the macro-averaged F1 score (macro-F1) collapses toward the level obtained with randomly permuted labels. We therefore treat these datasets as semantic-transfer and benchmark-validity studies, not fault-detection results. The framework’s distinguishing component is a counterfactual calibration layer that returns a probability for its recommended intervention; on a controlled structural causal model with known interventions, it achieves a Brier skill score of $0.369$ for intervention-success probabilities. Separately, on the simulation-derived LBNL Fan Coil Unit benchmark, a conventional gradient-boosted multiclass fault classifier achieves accuracy comparable to a random forest but about six times lower expected calibration error ($0.026$ vs. $0.159$) under a scenario-matched split. This calibration advantage does not generalize to held-out simulation scenarios, where the calibration error rises to $0.372$; we report this negative result as a limitation. We are explicit about scope: the ontology reasoner and the real-stream causal graph are only partially implemented, and the counterfactual recommendations are validated only under controlled or simulated conditions, not in deployed homes. The results are intended for researchers who build or benchmark sensor-based fault-diagnosis models, for dataset curators, and for practitioners who need calibrated rather than merely accurate outputs. All code, the proxy-label rules, and the leakage audit are released. Full article

Background/Objectives: Healthcare specialists are fundamental to the healthcare system, so ensuring their fair distribution is essential for providing sustainable, equitable services. This study aimed to evaluate geographical inequity in the distribution of healthcare specialists across Poland’s macro-regions from 2018 to 2024. Methods: Data were obtained from Statistics Poland. Healthcare specialist availability was measured as density rates per 10,000 population and per km². Population- and geographic-based inequalities were assessed using the unitless Gini coefficient (0–1), and the unitless Theil index. Results: The analysis yielded several key findings. Firstly, the spatial distribution of healthcare specialists is considerably less equitable than their distribution relative to population size, with clear differences between macro-regions. Access to oncologists and cardiologists was particularly unequal. These patterns demonstrate persistent structural imbalances in specialist availability. Conclusions: The results of this study can inform more effective policies aimed at achieving a fairer distribution of specialist care across the country. Other countries characterized by similar issues can build on these findings and adapt them to their own contexts. Full article

With heatwaves becoming increasingly frequent and intense in recent years, summer comfort is now a major issue for the design of low-energy buildings. Currently, most French homes are not equipped with air conditioning. To prevent the widespread adoption of this energy-intensive equipment while limiting indoor thermal discomfort during heatwaves, it is crucial to accurately design and assess climate adaptation measures. Occupants actively employ various strategies to limit overheating inside their dwellings, adapting their actions on the specific constraints they face. However, they are still frequently treated as passive entities in building performance simulations. This paper introduces an agent-based model, MOBAPY, developed to simulate the summer adaptive behaviour of households in urban dwellings. Grounded in qualitative data derived from semi-structured interviews, the model integrates commonly reported actions for one occupant profile, including the operation of windows, solar shading devices, air conditioning, and fans, alongside clothing adjustments. MOBAPY is applied to one case study: an urban dwelling, simulated under multiple climate scenarios and varying behavioural constraints within a building energy modelling framework. The results highlight the significant impact of occupant behaviour on summer comfort results for this occupant profile in a well-insulated dwelling. Notably, under the most severe future climate scenario, the percentage of uncomfortable occupied time drops to 20% when behaviour is unconstrained, whereas it surges to 68% under highly constrained conditions. Full article

This exploratory case study assesses ecotourism adaptability across three zones within the proposed Southwest Karst National Park (Guangxi), where UNESCO-recognised geological heritage intertwines with diverse ethnic cultures. To fill the gap in zone-specific integrated assessment frameworks, we employed a two-stage entropy-weighted TOPSIS method—calibrated via Delphi-AHP adjustments within a Social-Ecological Systems framework—using 2023–2024 data, complemented by ethnographic observations. Preliminary results indicate divergent trajectories: the Tiankeng zone exhibits high geological uniqueness and market appeal (composite score 0.74); the Mulun zone shows relatively balanced social–ecological coupling (0.58); and the Underground River zone displays pronounced asymmetry between vulnerability and development potential (0.16). Accordingly, tentative daily visitor caps of 3000, 8000, and 14 persons, respectively, and a pilot adaptability alert threshold of 0.20 for this specific case are proposed. These findings reveal a “vulnerability–capacity inverse matching” dynamic, informing differentiated governance: high-adaptability zones may allow moderate tourism with real-time monitoring, whereas low-adaptability zones require strict conservation-first measures and phased institutional capacity-building prior to any development. This preliminary framework offers actionable insights for sustainable management, conceptually aligned with SDG 11.4 and SDG 15.9. Full article

Adaptive reuse is widely used to extend the life of heritage and industrial heritage buildings, but its assessment remains divided between reuse potential, alternative selection, sustainability, post-occupancy performance, and conservation-based evaluation. This article develops the Adaptive Reuse Success Index (ARSI), a literature-derived framework for assessing adaptive reuse success as a multidimensional architectural condition. The framework was developed through a structured framework-development review and full-text coding of 31 studies, supported by a documented Scopus audit trail. Assessment concepts were extracted, normalized into codes, synthesized into themes, and translated into measurable indicators. ARSI comprises eight dimensions: Heritage Conservation Value, Functional Compatibility, Technical/Physical Performance, Environmental/Circular Performance, Economic Viability, Social and Community Value, Urban Integration and Regeneration, and Governance and Implementation Capacity. These dimensions are operationalized through a 40-indicator matrix with equal-weight scoring, literature-prominence sensitivity weighting, and non-compensatory safeguards. An illustrative application to Santralistanbul shows that the framework can separate strong heritage, functional, and urban performance from weaker or insufficiently evidenced social, economic, technical, and governance conditions. ARSI is proposed as an initial diagnostic framework rather than a validated universal index, offering a structured basis for comparative assessment and post-reuse evaluation in industrial heritage contexts. Full article