Search Results (10,442)

The intensifying global warming and the increasing frequency of extreme weather events have created an urgent need for targeted resilience building in mountainous villages. This study focuses on three typical villages in the Hengduan Mountains region. From the perspective of individual villagers, a disaster resilience evaluation index system was constructed, encompassing four dimensions: disaster prevention capacity, disaster resistance capacity, disaster relief capacity, and recovery capacity. Using the entropy method and a village disaster resilience assessment model, the disaster resilience levels of each village were quantitatively evaluated. The results indicate the following: (1) Disaster resistance capacity is the key factor constraining the disaster resilience level of mountain villages. (2) The overall disaster resilience of mountain villages is at a medium level, with minor differences among villages. (3) Significant disparities exist in capacity dimensions across villages: Qina Village demonstrates the strongest disaster resistance capacity, while Xiamachang Village excels in disaster prevention capacity but shows relative weakness in recovery capacity. (4) Household material endowment has a significant positive impact on disaster prevention, resistance, relief, and recovery capacities, while individual self-rescue capability and individual–government collaboration capacity also significantly enhance disaster prevention, resistance, and relief capacities. We propose the following: Leveraging the rural revitalization strategy as a pivotal point, this approach promotes the diversified development of the village economy. It facilitates the increase in villagers’ income through the implementation of employment skill training programs, thereby strengthening household material foundations to enhance individual disaster resilience. By relying on the mass monitoring and mass prevention mechanism and a disaster information sharing platform, real-time exchange of disaster situation information is achieved, which enhances communication and collaboration between villagers and the government, consequently improving the synergistic efficiency between individuals and governmental bodies. Simultaneously, a villager-centered disaster prevention system is constructed. Through measures such as disaster prevention publicity and practical disaster response drills, villagers’ awareness of disasters and their capabilities for self and mutual rescue are elevated, ultimately strengthening the overall disaster resilience of rural areas in the Hengduan Mountains region. Full article

Enterocytozoon bieneusi is the most frequently diagnosed microsporidian parasite in humans and a recognized cause of diarrheal disease, particularly in immunocompromised individuals. Its broad host range, which includes livestock, companion animals, and wildlife, highlights its zoonotic potential and warrants careful epidemiological assessment. This narrative review synthesizes available data on the occurrence and genetic diversity of E. bieneusi in European domestic ungulates (cattle, pigs, sheep, goats, horses, and water buffaloes) and pets (dogs and cats), aiming to provide an integrated perspective on animal reservoirs and their relevance for public health. Publications retrieved from the Web of Science Core Collection database were systematically screened, and country-specific results were extracted, emphasizing prevalence rates, genotype distributions, and zoonotic implications. Across Europe, cattle and pigs emerged as the most studied hosts, frequently harboring zoonotic group 1 genotypes such as I, J, BEB4, BEB6, and EbpA, while small ruminants, horses, and buffaloes remain comparatively undocumented. In pets, the dog-adapted genotype PtEb IX was predominant, but several zoonotic genotypes were also identified. Overall, the current evidence confirms the wide host range of E. bieneusi in Europe but also reveals significant data gaps compared to regions such as China, underlining the need for broader surveillance and harmonized molecular approaches within a One Health framework. Full article

The widespread adoption of virtual classrooms during the COVID-19 pandemic accelerated the integration of Learning Management Systems (LMSs) into Higher Education, positioning them as essential tools in blended learning environments. LMSs provide teachers with a wide range of tools and functionalities, generating heterogeneous teaching strategies and providing many useful indicators for analysis. However, the complexity of log data combined with the intricacies of hybrid environments presents a significant challenge. This paper presents a quantitative approach to analysing LMS log data in Higher Education, with a specific focus on identifying and characterising teaching strategies implemented in the post-pandemic context. It seeks to examine the extent to which virtual classrooms have been effectively integrated into teaching practices and to assess how different techno-pedagogical approaches influence students’ academic performance. Moreover, we try to develop and define a comprehensive methodology for data treatment, including selection of analytical variables, the identification and clustering of usage profiles based on LMS interactions, and a comparative interpretative analysis of the findings. Our results suggest that the techno-pedagogical strategies are not uniformly effective across all areas of knowledge. This highlights the need for a more nuanced understanding of how these strategies interact with disciplinary traditions, pedagogical practices, and student profiles. Full article

In response to the urgent need for sustainable energy solutions and efficient fossil resource utilization, the current research is conducted to examine the catalytic co-pyrolysis of four typical Chinese oil shales. The study assesses the ability of synergistic interactions, which are the result of organic and inorganic components, to improve the aspect of thermal behavior, decrease the activation energy and improve the shale oil quality. Thermogravimetric analysis in conjunction as Flynn–Wall–Ozawa (FWO), Kissinger–Akahira–Sunose (KAS) and integral master-plots approaches showed that there were low activation energies and better reaction kinetics in blended systems. Fischer assay and GC-MS were utilized in product distribution and product composition evaluation, respectively. Optimization increased gas yield and oil composition stabilization in the blended gas, which is found due to the catalytic functions of AAEMs and clay minerals. This contribution facilitates the development of catalytic co-processing solutions where better conversion and reduced carbon intensity are achieved in the production of fossil-based energy. Full article

Background: Peripheral neuropathy (PN) refers to a spectrum of symptoms resulting from dysfunctions of the peripheral sensory, motor, and autonomic neurons. PN is associated with significant balance impairments and an increased risk of falls, contributing to reduced functional independence and quality of life. Although diabetic PN has been extensively investigated, there remains a lack of synthesized evidence regarding rehabilitation approaches for individuals with non-diabetic PN. This systematic review aims to evaluate the effectiveness of stabilometric platforms incorporating virtual reality (VR) and feedback (FB) in improving balance and related outcomes in patients with PN of various etiologies. Methods: This systematic review was conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines and the protocol registered in PROSPERO (CRD420251086625). Seven major databases (PubMed, Scopus, ScienceDirect, Cochrane, Web of Science, Springer, and Wiley) were searched from inception to April 2025. Studies including adult patients with non-diabetic PN undergoing balance rehabilitation using stabilometric platforms with VR and FB were considered. The methodological quality of the included studies was assessed using the PEDro scale, RoB2, and ROBINS-I V2 tools. Results: A total of six studies met the inclusion criteria, encompassing 133 participants with non-diabetic PN. Interventions involving specialized balance training platforms incorporating VR and FB demonstrated significant improvements in both static and dynamic balance and postural control, as well as a reduction in the risk of falling. These systems also showed favorable adherence rates to rehabilitation programs. However, variability in intervention protocols and outcome measures limited the ability to perform direct comparisons across studies. Conclusions: The use of stabilometric platforms appears to be a promising approach for balance rehabilitation in patients with non-diabetic PN. Despite the limited number of included studies, the results support their integration into rehabilitation programs for this patient population. Further large-scale, high-quality studies are needed to establish standardized protocols and confirm long-term efficacy. Full article

Currently, an active debate is underway among the academic community, urban planners, and policymakers regarding optimal models of urban development, given that the majority of the population now resides in cities. One concept under discussion is the 15 min city, which posits that all urban residents should be able to reach key, frequently used services within a 15 min walk or cycle. Although the literature suggests numerous potential benefits, debate persists about whether such cities would be optimal from the standpoint of sustainable development objectives and residents’ quality of life. The ongoing discussion also concerns the extent to which existing cities are capable of aligning with this concept. This is directly linked to the actual spatial distribution of individual services within the city. The literature indicates a research gap arising from a shortage of robust case studies that would enable a credible assessment of the practical implementation of this idea across diverse cities, countries, and regions. This issue pertains to Poland as well as to other countries. A desirable future scenario would involve comprehensive mapping of all cities, with respect to both the spatial distribution of specific services and related domains such as the quality and coherence of linear infrastructure. This article presents an analysis of the spatial accessibility of basic urban services in the context of implementing the 15 min city concept, using the city of Koszalin (Poland) as a case study. This city was selected due to its representative character as a medium-sized urban centre, both in terms of population and area, as well as its subregional functions within Poland’s settlement structure. Koszalin also exhibits a typical spatial and functional layout characteristic of many Polish cities. In light of growing challenges related to urbanisation, climate change, and the need to promote sustainable mobility, this study focuses on evaluating access to services such as education, healthcare, retail, public transport, and green spaces. The use of Geographic Information System (GIS) tools enabled the identification of spatial variations in service accessibility across the city. The results indicate that only 11% of Koszalin’s area fully meets the assumptions of the 15 min city concept, providing pedestrians with convenient access to all key services. At the same time, 92% of the city’s area offers access to at least one essential service within a 15 min walk. Excluding forested areas not intended for development increases these values to 14% and 100%, respectively. This highlights the extent to which methodological choices in assessing pedestrian accessibility can shape analytical outcomes and the interpretations drawn from them. Moreover, given this article’s objective and the adopted analytical procedure, the assumed pedestrian walking speed is the key parameter. Accordingly, a sensitivity analysis was conducted, comparing the reference scenario (4 km/h) with alternative variants (3 and 5 km/h). This approach demonstrates the extent to which a change in a single parameter affects estimates of urban-area coverage by access to individual services reachable on foot within 15 min. The analysis reveals limited integration of urban functions at the local scale, highlighting areas in need of planning intervention. This article proposes directions for action to improve pedestrian accessibility within the city. Full article

To enhance the objectivity and precision of quality evaluation in flight training, this study proposes an assessment method for the landing flare phase based on time-series flight parameter data from Secure Digital (SD) card. By analyzing landing flare data from flight instructors and trainees, a standard sequence model was established, and the Dynamic Time Warping (DTW) algorithm was employed to calculate the similarity between individual trainee sequences and the standard sequence. Using K-means clustering, the landing flare quality was categorized into four distinct levels: Excellent (22.5%), Good (25.5%), Qualified (23.5%), and Improvement Needed (28.5%). The results demonstrated significant consistency with instructor evaluations (Spearman correlation coefficient 0.71). Furthermore, through the identification of weak parameters, specific technical deficiencies in areas such as airspeed control and pitch attitude maintenance could be accurately pinpointed. This approach not only effectively validates and supplements instructor assessments but also provides data-driven support for developing personalized training programs, thereby improving the quality and efficiency of flight training. Full article

Harmful algal blooms (HABs) caused by the dinoflagellate Karenia brevis present serious ecological and public health concerns due to the production of brevetoxins (BTX). Clay flocculation and sedimentation of cells, particularly with polyaluminum chloride (PAC)-modified clays, is a promising HAB mitigation approach. This study evaluated the efficacy of Modified Clay-II (MCII), a PAC-modified kaolinite clay, in reducing K. brevis cell abundance in mesocosm experiments and examined the bioavailability of BTX potentially released from settled floc back into the water column and sediment over the first 72 h after treatment. Additionally, we quantified trace metals in benthic clams (Mercenaria mercenaria) exposed to the floc post-treatment to assess metal accumulation and potential toxicological effects from MCII application. MCII treatment (0.2 g/L) resulted in a 91% reduction in K. brevis cell density and a 50% decrease in waterborne brevetoxins after 5 h. Brevetoxins accumulated in sediment post-flocculation, with BTX-B5 emerging as the dominant congener. Clams exposed to MCII-treated floc showed comparable tissue BTX levels to controls and significantly elevated aluminum concentrations, though without mortality. The aluminum accumulations in this study do not raise concerns for the health of the clams or the humans who eat them, given other dietary exposures. These findings support the potential of MCII for HAB mitigation while underscoring the need for further evaluation of exposure risks to all benthic species. Full article

Background/Objectives: Intermittent fasting (IF), such as Ramadan fasting, is common among pregnant women despite religious exemptions. The possible impact of fasting on pregnancy outcome and, in particular, on birthweight is uncertain and was documented with conflicting evidence. Methods: The aim of this meta-analysis and systematic review was to investigate the association between intermittent fasting during pregnancy and neonatal birthweight, along with low birthweight (LBW, <2500 g) risk. Studies evaluating fasting during pregnancy with reported neonatal outcomes were included. We searched (PubMed, Scopus, Web of Science) from 2004 through June 2025. All contributing studies were observational in design; no randomized trials were identified. The risk of bias was assessed using the Newcastle-Ottawa Scale. The pooled relative risks (RR) and mean differences (MD) were calculated according to random-effects models (DerSimonian–Laird method) and heterogeneity was quantified with the I² statistic. Results: Nineteen studies, all observational in design, were included for qualitative synthesis, and six studies yielded quantitative data to conduct meta-analyses. No randomized controlled trials were identified. Intermittent fasting during pregnancy, encompassing more than 1.3 million pregnancies, was associated with a small but statistically significant reduction in neonatal birth weight. The pooled mean difference was −94 g (95% CI: −176 to −12 g; p = 0.03; I² = 70%), indicating a minor but statistically significant effect that is unlikely to be clinically meaningful. The pooled RR for LBW was 0.96 (95% CI: 0.88–1.05; p = 0.38; I² < 10%), showing no association between fasting and low birthweight risk. Sensitivity analyses reduced heterogeneity (I² ≈ 55%) and confirmed the robustness of these findings. According to the GRADE approach, the certainty of evidence was moderate for birthweight and high for LBW. Conclusions: Intermittent fasting during pregnancy, including Ramadan fasting, was associated with a minor but statistically significant reduction in neonatal birthweight without increasing the risk of low birthweight. This difference was small and clinically negligible. Further prospective studies are needed to clarify trimester-specific effects and long-term developmental outcomes. Full article

Understanding and accurately estimating cognitive workload is crucial for the development of adaptive, user-centered interactive systems across a variety of domains including augmented reality, automotive driving assistance, and intelligent tutoring systems. Cognitive workload assessment enables dynamic system adaptation to improve user experience and safety. In this work, we introduce a novel framework that leverages smooth pursuit eye movements as a non-invasive and temporally precise indicator of mental effort. A key innovation of our approach is the development of trajectory-independent algorithms that address a significant limitation of existing methods, which generally rely on a predefined or known stimulus trajectory. Our framework leverages two solutions to provide accurate cognitive load estimation, without requiring knowledge of the exact target path, based on Kalman filter and B-spline heuristic classifiers. This enables the application of our methods in more naturalistic and unconstrained environments where stimulus trajectories may be unknown. We evaluated these algorithms against classical supervised machine learning models on a publicly available benchmark dataset featuring diverse pursuit trajectories and varying cognitive workload conditions. The results demonstrate competitive performance along with robustness across different task complexities and trajectory types. Moreover, our framework supports real-time inference, making it viable for continuous cognitive workload monitoring. To further enhance deployment feasibility, we propose a federated learning architecture, allowing privacy-preserving adaptation of models across heterogeneous devices without the need to share raw gaze data. This scalable approach mitigates privacy concerns and facilitates collaborative model improvement in distributed real-world scenarios. Experimental findings confirm that metrics derived from smooth pursuit eye movements reliably reflect fluctuations in cognitive states induced by working memory load tasks, substantiating their use for real-time, continuous workload estimation. By integrating trajectory independence, robust classification techniques, and federated privacy-aware learning, our work advances the state of the art in adaptive human–computer interaction. This framework offers a scientifically grounded, privacy-conscious, and practically deployable solution for cognitive workload estimation that can be adapted to diverse application contexts. Full article

Colorectal cancer (CRC) is the leading cause of cancer-related death in Puerto Rico, a U.S. territory with noted disparities in CRC incidence, particularly among those with early-onset disease (EOCRC). Although EOCRC incidence has been consistently increasing in the U.S. mainland, and a disparate burden has been reported among Hispanics, EOCRC mortality and survival are yet to be assessed among Hispanics living in Puerto Rico (PRH). In this study, we analyzed EOCRC mortality and survival trends in PRH and compared these to those of other U.S. populations. Mortality data were obtained from the Puerto Rico Central Cancer Registry and the Surveillance, Epidemiology, and End Results (SEER) program. Descriptive characteristics and temporal trends were derived via SEER*Stat software (version 9.0.42) and Joinpoint regression models, respectively. Relative survival was estimated using the Actuarial method and the Ederer II approach. Overall, CRC mortality trends showed a decline, but an increase in EOCRC mortality among Hispanics. PRH exhibited the lowest 5-year survival in regional cancers (54.10%), with NHB having the lowest survival among younger individuals. This study highlights significant disparities in EOCRC mortality trends and underscores an urgent need for targeted public health strategies and research efforts to address the disproportionate burden of EOCRC among PRH. Full article

This research pioneers the incorporation of grape pomace (GP) as a sustainable additive in unfired adobe construction materials, establishing a novel circular pathway that valorises agro-waste in zero-emission, low-energy building components. Five mix designs were developed with GP contents of 0%, 2.5%, 5%, 7.5%, and 10% by weight, using a soil matrix composed of 15% clay, 25% silt, and 60% sand with a 20% water content. Comprehensive characterization included physical properties, mechanical performance, thermal behavior, acoustic properties, and durability assessment. The incorporation of GP demonstrated dose-dependent effects on all measured properties. Bulk density decreased linearly from 1951 kg/m³ (0%GP) to 1595 kg/m³ (10%GP), representing an 18.3% reduction. Optimal mechanical performance was achieved at a 2.5–5% GP content, with compressive strength ranging from 1.51–1.64 MPa and flexural strength of 0.56–0.80 MPa, while higher GP contents resulted in significant strength reductions. Thermal conductivity improved substantially, decreasing from 0.99 to 0.25 W/Mk (66% RH) with increasing GP content, indicating enhanced insulation properties. The sound insulation performance showed a single-value sound reduction index (Rw) of 41–43 dB for all compositions, making them suitable for facade applications. Statistical analysis revealed significant correlations between GP content and material properties. The results indicate an optimal GP content of around 5%, which balances mechanical integrity, thermal performance, and durability while providing environmental benefits through the valorization of agro-waste. This research offers a sustainable approach for producing low-energy, eco-friendly building materials by incorporating grape pomace into unfired adobe, promoting waste valorization and improved thermal and acoustical insulation for green construction. Further research is needed to assess durability performance, standardize production methods, and evaluate large-scale implementation. Full article

The high cost of wind turbine maintenance has intensified the need for reliable fault detection and condition monitoring methods. While Supervisory Control and Data Acquisition (SCADA) systems provide valuable operational data, the raw signals often contain noise, outliers, and missing or redundant entries, which can compromise analysis accuracy. This study presents a novel cluster-based outlier removal approach for SCADA data preprocessing, featuring a unique flexibility to include or exclude negative power values—a factor rarely investigated but potentially critical for fault detection performance. The method applies the K-Means++ unsupervised clustering algorithm to group data points along the wind speed–power curve. The number of clusters is determined heuristically using the elbow method, while outliers are identified through Mahalanobis distance with thresholds derived from Chebyshev’s inequality theorem. The approach was validated using SCADA data from a wind farm in Portugal and further assessed with a CUSUM test-based structural change detection method to study how preprocessing choices—outlier thresholds (5% vs. 1%) and inclusion/exclusion of negative power values—affect early fault identification. Results demonstrate reliable fault detection up to 14 days before failure, retaining over 99% of the original dataset. This work provides key insights into preprocessing impacts on model reliability and offers an open-source Python implementation for reproducibility. Full article

Current research and development in understanding road users’ driving behaviors play a key role in improving traffic safety. Recently, several driving simulators have been employed as a suitable approach to investigate several drivers’ responses in challenging traffic scenarios. Although professional drivers represent a particular category among driving populations, the body of literature about their comparative behavioral and psychological characteristics remains limited. This study examined the differences in driving performance and visual and physiological responses between civilian and professional drivers in a simulated environment. A total of 30 drivers, with an equal split between professional and civilian categories, took part in a series of driving simulations. The simulations incorporated various infrastructure types, including four cone avoidance tasks and a high-speed motorway task. This study collected comprehensive data on performance metrics, hand usage, heart rate, and eye movements. Eye-tracking technology was used to measure visual attention. The findings revealed that during cone avoidance scenarios, civilian drivers exhibited a similar performance, visual behavior, and physiological response, except for the speed, experiment duration, and throttle, to professional drivers. In the motorway scenario, all metrics showed no significant difference between the two driver groups. These results highlight the need for cautious interpretation, particularly given the limitations of the sample. Revalidation is needed in larger studies, especially for understanding the differences between drivers’ metrics, which is crucial to elevate drivers’ safety, and assessing training programs in Hungary. Full article

Highway–rail grade crossings (HRGCs) remain a critical safety problem despite decades of infrastructure investment. Moreover, the relationship between specific driver behaviors and crash severity across different geographic contexts remains poorly quantified. This study aimed to conduct a systematic review to (1) synthesize existing evidence on behavior-specific crash outcomes at HRGCs and (2) empirically validate findings from crash datasets. The study was conducted following PRISMA 2020 guidelines, identifying peer-reviewed studies (2015–2025) through structured searches of electronic databases. Inclusion criteria required studies to report quantitative associations between driver behavior and crash severity at HRGCs. In addition, crash records from two U.S. states (New Jersey and Texas; 2013 to 2022) were analyzed using multinomial logistic regression to assess empirical validity. Multinomial logistic regression analysis reveals that highway user action (HAU = 1) “going around gates” significantly increase the fatal risk. Empirical analysis confirmed these trends but revealed geographic variation: New Jersey showed a fatality odds ratio of 4.490 versus Texas’s 3.686 for a fatal risk, i.e., severity level 1. In addition, gender emerged as a significant factor in fatal crash risk, with female drivers facing elevated odds of fatal injury compared to male drivers: 1.464 in New Jersey and 1.817 in Texas. Despite these findings, three critical gaps remain in HRGCs: (1) predictive models focus on crash frequency rather than behavior forecasting, (2) data quality issues compromise of risk predictions, and (3) machine learning approaches lack interpretability for practitioners. This review demonstrates that identical driver behaviors produce different crash outcomes across geographic regions. Effective safety interventions need to address local risk factors instead of relying on a uniform national approach. Full article