Search Results (74,351)

University students face academic demands that may be associated with reduced use of active coping when perceived as stressful. This study examined whether feedback seeking, cooperative work, time management, and active learning moderated the association between perceived academic stressors and active coping. A cross-sectional, non-experimental design was used with 1014 undergraduates from the University of Extremadura. Participants completed measures of perceived academic stressors (E-CEA), active coping (A-CEA), and good practices (IBPEU). Four separate moderation models were estimated using PROCESS Model 1 with 5000 bootstrap resamples, adjusting for age, gender, year of study, and field of study. Perceived academic stressors were negatively associated with active coping, whereas all four good-practice dimensions were positively associated with it. All interaction terms were positive and statistically significant (B = 0.058–0.086, p = 0.017–0.046), but each accounted for only 0.34–0.49% of additional explained variance. Across all four models, higher reported levels of the corresponding good-practice dimension were associated with a less pronounced negative association between perceived academic stressors and active coping. The findings may inform the development and evaluation of student-support and instructional initiatives focused on feedback literacy, cooperative skills, time planning, and active engagement with learning. They also point to the relevance of educational conditions that may facilitate these practices within university learning environments. Full article

Proximity-based planning frameworks such as the 15 min city and community life circle (CLC) are widely promoted to improve age-friendly access to essential resources, based on the assumption that enlarging spatial scale improves access. This assumption remains largely untested in high-density aging cities, where neighborhood-level deprivation may persist even as aggregate access improves. Using 3737 residential communities in central Tianjin, China, this study jointly evaluates food and physical activity environments across 5, 10, and 15 min walking thresholds. We apply a three-dimensional demand–matching–spatial association framework that combines health-weighted accessibility, location quotient matching, and bivariate spatial autocorrelation. Food access shows a continuous core–periphery gradient, whereas physical activity access is fragmented and facility-dependent. Supply–demand matching shows divergent scale responses across resource domains. Aggregate accessibility increased as the CLC scale expanded. However, 45.88% of communities classified as LL at the 10 min scale remained LL at 15 min, substantially exceeding the overall LL proportion of 18.70% at the 15 min scale. Only 5.42% of communities classified as HL or LH transitioned to HH. This divergence between aggregate accessibility improvement and persistent local disadvantage is defined as ineffective expansion. Eight diagnostic types reveal a clear divide between deprived peripheries and advantage-maintenance conditions in the urban core. These findings suggest that age-friendly CLC planning should move beyond uniform service-area expansion toward type-specific, place-based interventions. Full article

Trajectory planning, which determines a route from a starting position to a target position within a given airspace, is critical to unmanned aerial vehicle (UAV) mission execution. Many existing meta-heuristic approaches to three-dimensional (3D) trajectory planning aggregate competing requirements into a weighted cost and may suffer from limited adaptability when the environment changes. This paper formulates 3D UAV trajectory planning in dynamic multi-threat environments as a dynamic bi-objective optimization problem and proposes a multi-swarm dynamic multi-objective crow search algorithm (MDMCSA). The proposed method organizes objective-oriented swarms within a cooperative search framework and facilitates information exchange through archive sharing, thereby coordinating the search process among different objectives. The memory-time and diverse behavior strategies adjust search behaviors and solution perturbation to balance convergence and diversity. A hybrid change response strategy combines historical information reuse with diversity restoration after dynamic changes. Comparative experiments on dynamic benchmark problems and UAV trajectory planning scenarios demonstrate competitive convergence and adaptation performance, together with a favorable trade-off between solution quality and computational cost. Incremental ablation and parameter-sensitivity analyses further indicate the cumulative benefit of the integrated design and the stable performance of the selected parameter configuration across the tested settings. Full article

Municipal records of human–wildlife conflict are widely available but remain underused for identifying conflict-prone urban interfaces and supporting preventive management. This study compared reported human–wild boar (Sus scrofa) conflict patterns and the land-use composition of high-density report zones in Olsztyn, Poland, in 2010 and 2020. Municipal records of wild boar presence, complaints, and interventions were matched to street-network features and integrated with harmonized land-use data in a geographic information system. Kernel density estimation delineated high-density report zones, Getis–Ord Gi* analysis characterized street-segment clustering, and land-use overlay and descriptive compositional metrics quantified differences between years. High-density zones shifted from an extensive, peripheral configuration in 2010 to a markedly more compact pattern integrated into the urban fabric in 2020. Proportional shares increased for transport (+12.64 percentage points), residential (+10.12), and recreational areas (+2.40), while industrial and wasteland areas (−13.13), grasslands (−6.33), and forests (−4.85) decreased. These findings indicate a reorganization of reported conflict geography, not changes in wild boar abundance, habitat preference, movement behavior, or synurbization. Routinely collected municipal records can support targeted monitoring, traffic-risk mitigation, waste management, green-space planning, and preventive urban wildlife management. Full article

Background/Objectives: The basis for treatment of sarcoma is surgical resection. However, since the introduction of limb salvage surgery, guidelines recommend radiation as a complement to surgery for high-grade sarcomas. The aim of the present narrative review was to provide a comprehensive update about the role of surgery and radiotherapy (RT) for extremity soft tissue sarcoma (ESTS), to increase both surgeons’ and oncologists’ understanding of radiation as an adjuvant to sarcoma surgery and to illuminate areas of uncertainty that requires further research. Methods: A search on PubMed using relevant MeSH terms was performed, focusing on original research, meta-analyses and review articles. Related articles were identified through snowballing. Results: The support for the use of radiotherapy in conjunction with limb salvage is strong. Complication profiles differ between pre- and postoperative RT and attempts to further limit these are both technological and surgical. Preoperative radiotherapy provides the best results regarding long-term complications so far. Hypo-fractionation is showing promise, but awaiting long-term results for complications remains an area of research rather than clinical practice. Particle beam therapy and internal radiation show effects on control, but due to technical and availability issues, their role is mainly in previously irradiated or inoperable tumors. Conclusions: Upcoming research into adjusted deliveries, doses and planning is anticipated. To further personalize treatment, studies into sarcoma subtypes are indicated. Full article

Background: Although extreme heat is associated with adverse cardiovascular outcomes, the relationship between heat-alert-threshold days, acute myocardial infarction (AMI) admissions, and post-AMI mortality remains uncertain. We aimed to evaluate the association between temperature-defined heat-alert-threshold days and (i) daily AMI admissions and (ii) cumulative all-cause mortality after hospitalized AMI in Hungary. Methods: We conducted a nationwide registry-based study using data from the Hungarian Myocardial Infarction Registry (HMR). All AMI admissions between 1 January 2018 and 31 December 2019 were eligible, with mortality follow-up through 16 June 2021. Heat-alert-threshold days were defined using the temperature criterion applied in the Hungarian national heat-health action plan (daily mean temperature ≥25 °C). AMI admissions were analyzed using adjusted quasi-Poisson regression models and cumulative mortality using stratified Cox proportional hazards models. This operational temperature threshold was used as the exposure definition and does not represent linkage to administrative heat-alert declarations. Results: The cohort included 30,883 AMI events from 29,596 unique patients (mean age, 67.2 [SD 12.8] years; 60.3% male). Patients admitted on heat-alert-threshold days had baseline clinical characteristics similar to those admitted on non-alert days (all standardized mean differences <0.10). Heat-alert-threshold days were associated with fewer recorded AMI admissions during summer (adjusted incidence rate ratio [aIRR] 0.93, 95% CI 0.90–0.97). In contrast, no association was observed between heat-alert-threshold exposure and subsequent all-cause mortality after AMI hospitalization (adjusted hazard ratio [aHR] 0.96, 95% CI 0.87–1.05). These findings remained consistent across sensitivity analyses. Conclusions: In this nationwide Hungarian registry-based study, temperature-defined heat-alert-threshold days were associated with fewer recorded AMI admissions during summer but not with differences in post-AMI mortality among hospitalized patients. The observed inverse association should not be interpreted as evidence of a protective effect of heat exposure. Alternative explanations include behavioral adaptation, delayed care-seeking, exposure misclassification, residual confounding, and the possibility of unmeasured out-of-hospital cardiovascular events, which were not captured by the registry. Because administrative heat-alert declarations were not linked to the analytic dataset, the findings should be interpreted as associations with temperature-defined heat-alert-threshold days rather than evaluations of the effectiveness of the Hungarian heat-alert system. Full article

In fragile economies where formal employment is constrained and conventional entrepreneurial pathways are structurally limited, universities represent one of the few institutional actors capable of cultivating digital entrepreneurial intention at scale and contributing to local economic resilience and sustainable development. Yet the mechanisms through which digital entrepreneurship education is associated with intention remain inadequately understood, particularly the institutional and cognitive pathways that education activates. Grounded in the Theory of Planned Behavior, Social Cognitive Theory, Digital Transformation Theory, and Human Capital Theory, this study proposes and tests a moderated serial mediation model in which perceived university digital transformation and digital entrepreneurial knowledge sequentially mediate the education-to-intention relationship, with digital mindset moderating the knowledge-to-intention path. Survey data from 344 Palestinian university students were analyzed using partial least squares structural equation modeling. All nine hypotheses are supported and the model accounts for 77.0% of the variance in digital entrepreneurial intention, a result that should be interpreted with caution given the single-source cross-sectional design. The indirect association of digital entrepreneurship education with intention through perceived university digital transformation is comparable in magnitude to the direct effect, indicating that the university’s institutional digital environment carries approximately as much of education’s influence on entrepreneurial intention as the direct attitudinal channel. The serial indirect path through both mediators is significant, confirming that institutional digital transformation and entrepreneurial knowledge are associated with intention in sequence rather than in parallel. Digital mindset significantly strengthens the knowledge-to-intention association, constituting a dispositional boundary condition. The findings advance understanding of how universities build digital entrepreneurial capacity in fragile contexts and carry implications for institutional digital investment, curriculum design, and higher education policy in resource-constrained settings aligned with SDG 8 and SDG 9. Full article

Airport Economic Zones (AEZs) in China are largely guided by central and local government planning, and official planning documents provide important textual signals of industrial priorities. To identify these priorities, this study examines 17 national-level Airport Economic Demonstration Zones (AEDZs) and collects official documents on industrial development issued by central authorities and relevant local governments. Using dictionary-based named entity recognition, word-frequency analysis, clustering, and association rule mining, we quantitatively analyze stated governmental preferences in AEDZ industrial planning, focusing on emphasized industries and their combinations. The results show that local governments frequently emphasize industries prioritized by the central government, including aviation equipment manufacturing and maintenance, electronic information, aviation logistics, professional exhibitions, and e-commerce. They also tend to combine high-end intelligent manufacturing, electronic information technology services, and air cargo transportation in planning narratives. These patterns indicate policy alignment across AEDZs, while high similarity in stated industrial priorities may signal potential risks of redundant construction and resource misallocation if not matched with differentiated implementation. The findings are interpreted as textual policy signals rather than evidence of actual implementation or industrial performance. Full article

Post-disaster emergency communication recovery is not merely a link-repair task but a high-level planning problem constrained by service priorities, inter-object dependencies, resource budgets, and time windows. Existing restoration optimization methods generally rely on fully structured inputs, whereas direct large language model (LLM) planning may produce fluent candidates that violate encoded prerequisites, stage-order relations, budget limits, or temporal constraints. To address this challenge, we propose ICG-Restore, an intent-constrained, graph-enhanced LLM planning framework with rule-consistent minimal-edit repair. ICG-Restore transforms mixed restoration requests and structured network observations into task packages that can be checked for validator-level feasibility under an encoded high-level constraint model and evaluated by downstream abstract executors or schedulers. The framework compiles natural-language requests, structured observations, and operational rules into a task-intent object; retrieves task-relevant context from a heterogeneous scenario graph and a restoration knowledge graph; generates stage-wise restoration candidates; and applies bounded local corrections to candidates that violate encoded constraints. In this paper, “minimal-edit” is a descriptive label for a bounded local repair principle that prioritizes less disruptive corrections. Candidates accepted by the validators are evaluated and ranked by a safety-aware agent executor operating in an abstract restoration action space. Experiments on controlled abstract topologies covering three scales, four restoration tasks, and five environmental evolution modes show that ICG-Restore improves validator-level constraint satisfaction and benchmark-estimated recovery utility. Compared with Direct-LLM, it improves CSR and CRS by 1.99% and 24.56%, respectively; benchmark-specific WCTC@5 structural-alignment diagnostic increases by 38.87%. Full article

In recent years, the wild boar population has increased in Italy. Wild boar is one of the most problematic species from a sanitary point of view because it represents a dangerous reservoir of pathogens and viruses. The aim of this study was to investigate the circulation of coronaviruses in wild boars, a group of viruses known for their ability to spill over between species. As part of the wild boar population control plan established by the Basilicata region relating to this species, 625 animals were analyzed from May 2024 to January 2026. Nasal swabs were collected at the slaughterhouse in the province of Potenza. Screening was conducted using pan-coronavirus PCR through a nested PCR assay targeting the conserved RNA-dependent RNA polymerase (RdRp) region. Out of all samples analyzed, 1.9% were positive for Porcine Hemagglutinating Encephalomyelitis Virus (PHEV), marking the first identification of this neurotropic coronavirus in wild boars in Italy. The detection of PHEV in free-ranging populations highlights the potential for viral circulation at the wildlife–livestock interface and underlines the importance of integrated surveillance systems to prevent possible interspecies transmission and minimize the risk of spillover to domestic pig herds. Full article

Traffic scenario initialization is a key component of autonomous driving simulation. The generated initial traffic states directly affect downstream motion prediction, planning evaluation, closed-loop simulation, and safety assessment. Existing traffic scenario generators usually rely on structural and interaction priors, but these priors are commonly treated as deterministic and fully reliable during both training and deployment. In practical autonomous driving systems, however, such priors are reconstructed from heterogeneous perception pipelines involving sensors, localization, tracking, online mapping, map alignment, and behavior estimation. Their reliability may therefore vary continuously because of sensing noise, localization drift, incomplete observations, occlusion, tracking instability, and imperfect interaction inference. To address this issue, this paper proposes PriorAug, a reliability-aware prior augmentation framework for robust traffic scenario initialization under sensor-perceived prior uncertainty. PriorAug formulates traffic scenario initialization as conditional generation over sensor-perceived priors and introduces a two-dimensional reliability space to characterize structural reliability and interaction reliability separately. Based on this space, reliability-conditioned prior operators are designed to construct diverse prior configurations during training, enabling the generator to learn from continuously varying perception conditions without modifying the underlying generation architecture or introducing additional learnable inference modules or iterative decoding stages. Experiments on the Waymo Open Motion Dataset show that PriorAug maintains competitive full-set distribution fidelity, improves robustness under shifted-prior conditions and traffic density variations, and improves the physical plausibility of generated initial states. Reliability landscape analysis further demonstrates that coverage-oriented prior augmentation yields smoother performance transitions across the reliability space. These results indicate that explicitly modeling sensor-perceived prior reliability provides an effective and practical route to robust traffic scenario initialization for autonomous driving simulation. Full article

The Levelized Cost of Energy (LCOE) is the standard metric for evaluating renewable energy project economics; however, conventional formulations inadequately represent the dynamic effects of logistics performance, supply chain disruptions, geopolitical risk, and institutional constraints on project costs. This study addresses this gap by proposing the Integrated Levelized Cost of Energy (I-LCOE), a conceptual framework designed for macro-level renewable energy planning and policy analysis. An interpretivist qualitative research design was adopted, combining a systematic literature review with twelve semi-structured interviews involving renewable energy, logistics, regulatory, and academic experts from the MENA and GCC regions. Thematic analysis identified five recurring challenges: limited knowledge management, weak integration of logistics within conventional LCOE models, fragmented sustainability metrics, stakeholder coordination inefficiencies, and reliance on tacit knowledge. The findings indicate that transportation delays, customs bottlenecks, infrastructure limitations, and geopolitical disruptions generate dynamic risk premiums that are insufficiently reflected in existing macro-level cost assessment approaches. In response, the study develops the four-layer I-LCOE framework, supported by an operational proxy variable mapping framework, a comparative assessment against established uncertainty methods, and an integrated digital knowledge management platform. The proposed framework provides a structured approach for incorporating logistics-induced uncertainty into renewable energy cost assessment, supporting more informed strategic planning, investment prioritization, and policy development aligned with Sustainable Development Goal 7 and the Paris Agreement. Full article

Industrial Internet of Things (IIoT) production environments rely on automated communication between control systems and embedded devices while operating under strict availability constraints that limit the deployment of conventional IT security controls. Despite extensive research on intrusion detection systems, empirical studies based on long-term observations of real industrial networks remain scarce. This paper presents a longitudinal 92-day passive monitoring study of a production-line IIoT network comprising 22 monitored devices. A containerised instance of Zeek was deployed in promiscuous mode to collect flow-level and application-layer telemetry without interfering with operations. The resulting dataset contains more than 41.5 million network flows and 520.5 million packets, represented by 48.48 GB of structured Zeek logs. The results reveal highly deterministic communication patterns dominated by periodic HTTP polling between a central server and distributed devices. In particular, the hourly mean HTTP response size remained highly stable at 132.76 bytes, with a standard deviation of 1.37 bytes and a coefficient of variation of 1.0%. Although no confirmed malicious activity was observed, transient deviations were identified and attributed to planned production stoppages restart periods, which caused temporary traffic reductions and short-lived packet bursts. These findings demonstrate that production-line IIoT networks can exhibit predictable behaviour regimes suitable for statistical anomaly detection. The study contributes a longitudinal empirical characterisation of a real operational IIoT network, a reproducible methodology for behavioural baseline extraction using passive telemetry, and practical insights for safe monitoring deployment. Full article

The increasing severity of heat waves in cities requires the integration of spatial morphology with temperature-resilient design; however, comparisons of multi-city systems are scarce. The aim of this article is to assess the potential thermal resilience of Poland’s largest cities, taking into account local climate zones (LCZs), which aligns with the framework of sustainable urban development. The use of LCZs allows for a comparison of the resilience of cities without being influenced by their historical development, providing a diagnostic basis for climate adaptation. The proposed potential thermal resilience index ($R_c$) integrates exposure, sensitivity, and adaptive capacity, serving as the operational inverse of structural vulnerability to heat (urban heat vulnerability). The results indicate that 62.5% of the cities are characterized by moderate potential thermal resilience; 31.3% of cities have low resilience, and only 6.2% of cities have high resilience. High potential thermal resilience is associated with a large proportion of LCZs A, B, and D, as well as a reduction in both high-density and low-density development, which provides practical guidance for land-use planning. The index shows geographical variation—higher values were found in southern and southwestern Poland. The results suggest the need to correlate physical interventions with social vulnerability and the macroclimate when designing blue-green infrastructure as a key element of sustainable adaptation. Full article

Objectives: The aim of this study was to evaluate the influence of systemic lutein (LT) supplementation on the progression of experimental periodontitis (EP) and its impact on mechanical periodontal therapy (SRP) in rats. Methods: A total of 120 male Wistar rats were used, and EP was induced by placing a ligature around the left mandibular first molar. The animals were allocated into four groups: NT (no treatment)/VEH (vehicle), NT/LT, SRP/VEH and SRP/LT. Supplementation was administered daily by oral gavage (0.7 mL/kg of vehicle or 250 mg/kg of LT). Animals were euthanized at 7, 15 and 30 days, and the hemimandibles were collected for histomorphometric analysis of the percentage of bone in the furcation region (PBF), histopathological assessment and immunohistochemical detection of inflammatory mediators (tumor necrosis factor-alpha, interleukin-1β and interleukin-10) and bone markers (tartrate-resistant acid phosphatase and osteocalcin). Results: Systemic LT supplementation, particularly when associated with scaling and root planning (SRP/LT), reduced the intensity and extent of the inflammatory infiltrate, partially decreased immunolabelling for IL-1β and TNF-α, and promoted greater organization of the connective tissue. Higher PBF values and fewer TRAP-positive cells were observed in LT-treated groups. Conclusions: Systemic LT supplementation reduced inflammation and alveolar bone resorption and enhanced the effects of mechanical periodontal therapy. Full article