Search Results (1,399)

Since its first appearance as a human pathogen in 1976, Legionella pneumophila has been identified as a causative agent of community-acquired pneumonia (CAP). It survives in rivers, bays, lakes, and water reservoirs, and it is categorized as the fourth most common causative agent of CAP leading to hospitalization. We aimed to investigate patterns in which environmental, seasonal and regional factors may affect the prevalence of Legionnaires’ disease in Crete during the last two decades (2000–2022).The data used originated from the national surveillance database and included any person reported with travel-associated Legionnaires’ disease (TALD) between January 2000 and December 2022. Meteorological data were collected from the National Weather Service. The meteorological variables included (max) temperature (in °C), cloudiness (in octas), wind speed (in knots), and relative humidity (RH) (%). The statistical analysis was based on a case-crossover design with 1:1 matching characteristic. We revealed both seasonal and regional effects on the incidence of Legionnaires’ disease. Cases are significantly more frequent in autumn, in comparison to the other three seasons, while Rethymnon is the prefecture with fewer cases in comparison to Chania or Heraklion. In addition, our research showed that the majority of cases occurred during the years 2017–2018. TALD in Crete is significantly associated with temperature in °C and wind speed in knots. Our research suggests that temporal and spatial factors significantly influence disease cases. These results are in line with studies from foreign countries. The study results aspire to expand our knowledge regarding the epidemiological characteristics of Legionnaires’ disease in relation to local, geographical and meteorological factors on the island of Crete. Full article

This study assesses future agricultural drought risk in the Ganjiang River Basin under climate change and land use change. A coupled analysis framework was established using the SWAT hydrological model, the CMIP6 climate models (SSP1-2.6, SSP2-4.5, SSP5-8.5), and the PLUS land use simulation model. Key methods included the Standardized Soil Moisture Index (SSMI), travel time theory for drought event identification and duration analysis, Mann–Kendall trend test, and the Pettitt change-point test to examine soil moisture dynamics from 2027 to 2100. The results indicate that the CMIP6 ensemble performs excellently in temperature simulations, with a correlation coefficient of R² = 0.89 and a root mean square error of RMSE = 1.2 °C, compared to the observational data. The MMM-Best model also performs well in precipitation simulations, with R² = 0.82 and RMSE = 15.3 mm, compared to observational data. Land use changes between 2000 and 2020 showed a decrease in forestland (−3.2%), grassland (−2.8%), and construction land (−1.5%), with an increase in water (4.8%) and unused land (2.7%). Under all emission scenarios, the SSMI values fluctuate with standard deviations of 0.85 (SSP1-2.6), 1.12 (SSP2-4.5), and 1.34 (SSP5-8.5), with the strongest drought intensity observed under SSP5-8.5 (minimum SSMI = −2.8). Drought events exhibited spatial and temporal heterogeneity across scenarios, with drought-affected areas ranging from 25% (SSP1-2.6) to 45% (SSP5-8.5) of the basin. Notably, abrupt changes in soil moisture under SSP5-8.5 occurred earlier (2045–2050) due to intensified land use change, indicating strong human influence on hydrological cycles. This study integrated the CMIP6 climate projections with high-resolution human activity data to advance drought risk assessment methods. It established a framework for assessing agricultural drought risk at the regional scale that comprehensively considers climate and human influences, providing targeted guidance for the formulation of adaptive water resource and land management strategies. Full article

Compared to commuting, grocery shopping trips, despite their profound implications for mixed land use and transportation planning, have received limited attention in travel behavior research. Drawing upon a travel diary survey conducted in a fast-growing metropolitan region of the United States, i.e., Salt Lake County, UT, this research investigated a variety of influential factors affecting mode choices associated with grocery shopping. We analyze how built environment (BE) characteristics, measured at seven spatial scales or different ways of aggregating spatial data—including straight-line buffers, network buffers, and census units—affect travel mode decisions. Key predictors of choosing walking, biking, or transit over driving include age, household size, vehicle ownership, income, land use mix, street density, and distance to the central business district (CBD). Notably, the influence of BE factors on mode choice is sensitive to different spatial aggregation methods and locations of origins and destinations. The straight-line buffer was a good indicator for the influence of store sales amount on mode choices; the network buffer was more suitable for the household built environment factors, whereas the measurement at the census block and block group levels was more effective for store-area characteristics. These findings underscore the importance of considering both the spatial analysis method and the location (home vs. store) when modeling non-work travel. A multi-scalar approach can enhance the accuracy of travel demand models and inform more effective land use and transportation planning strategies. Full article

Land use significantly influences mobility dynamics, affecting both travel behavior and mode choice. Traditional indicators such as the Floor Area Ratio, Land-Use Mix Index, and Built-up Area Ratio are widely used to describe settlement patterns; yet, they often fail to capture their functional impacts on road networks. This study introduces two complementary indicators—Settlement Ratio (SR) and Settled Area (SA)—developed through a spatial analysis framework integrating GIS data and MATLAB processing. SR offers a continuous typological profile of built-up functions along the road axis, while SA measures the percentage of anthropized land within fixed analysis windows. Applied to two Italian state roads, SS14 and SS309, in the Veneto Region, the dual-indicator approach reveals how the intensity (SR) and extent (SA) of settlement vary across different territorial contexts. In suburban segments, SR values exceeding 15–20, together with SA levels between 10% and 15%, highlight the significant spatial impact of isolated development clusters—often not evident from macro-scale observations. These findings demonstrate that the SR–SA framework provides a robust tool for analyzing land use in relation to road function. Although the study focuses on spatial structure and indicator design, future developments will explore correlations with traffic flow, speed, and crash data to support road safety analyses. Full article

The study of historical monuments within both architectural and literary frameworks reveals a dynamic interplay between scientific observation and artistic interpretation—a vital characteristic of travel writing/the travelogue. This approach, exemplified by British traveler and writer Henry Finnis Blosse Lynch (1862–1913), reflects how factual detail and creative representation are seamlessly integrated in depictions of sites, landscapes, and cultural scenes. This case study highlights Lynch as a pioneering explorer who authored the first comprehensive volume on Armenian architecture and as a writer who vividly portrayed Armenian monuments through both verbal description and photographic imagery, becoming the first traveler to document such sites using photography. Additionally, this paper emphasizes the significance of Lynch’s detailed accounts of architectural monuments, churches, monasteries, cities, villages, populations, religious communities, and educational institutions in vivid language. The careful study of his work can contribute meaningfully to the investigation of the travelogue as a literary genre and to the preservation and protection of the architectural heritage of historical and contemporary Armenia, particularly in regions facing cultural or political threats. Full article

Accurately predicting the next location of urban individuals is a central issue in human mobility research. Human mobility exhibits diverse patterns, requiring the integration of spatiotemporal contexts for location prediction. In this context, multi-view learning has become a prominent method in location prediction. Despite notable advances, current methods still face challenges in effectively capturing non-spatial proximity of regional preferences, complex temporal periodicity, and the ambiguity of location semantics. To address these challenges, we propose a representation-enhanced multi-view learning network (ReMVL-Net) for location prediction. Specifically, we propose a community-enhanced spatial representation that transcends geographic proximity to capture latent mobility patterns. In addition, we introduce a multi-granular enhanced temporal representation to model the multi-level periodicity of human mobility and design a rule-based semantic recognition method to enrich location semantics. We evaluate the proposed model using mobile phone data from Fuzhou. Experimental results show a 2.94% improvement in prediction accuracy over the best-performing baseline. Further analysis reveals that community space plays a key role in narrowing the candidate location set. Moreover, we observe that prediction difficulty is strongly influenced by individual travel behaviors, with more regular activity patterns being easier to predict. Full article

This study investigates the factors influencing school trip mode choice among senior high school students in the Chiang Rai urban area, Chiang Rai, Thailand, under normal and adverse weather conditions. Utilizing data from 472 students across six extra-large urban schools, a Multinomial Logit (MNL) regression model was applied to examine the effects of socio-demographic attributes, household vehicle ownership, travel distance, and spatial variables on mode selection. The results revealed notable modal shifts during adverse weather, with motorcycle usage decreasing and private vehicle reliance increasing, while school bus usage remained stable, highlighting its role as a resilient transport option. Car ownership emerged as a strong enabler of modal flexibility, whereas students with limited access to private transport demonstrated reduced adaptability. Additionally, increased waiting and travel times during adverse conditions underscored infrastructure and service vulnerabilities, particularly for mid-distance travelers. The findings suggest an urgent need for transport policies that promote inclusive and climate-resilient mobility systems, particularly in the context of Chiang Rai, including expanded school bus services, improved first-mile connectivity, and enhanced pedestrian infrastructure. This study contributes to the literature by addressing environmental variability in school travel behavior and offers actionable insights for sustainable transport planning in secondary cities and border regions. Full article

The structural design of rail vehicle bodies significantly influences rail vehicle performance, passenger comfort, and operational efficiency. This study presents a comparative analysis of three key concepts of a rail vehicle body, namely a differential, an integral, and a hybrid structure, with a focus on their structural principles, material utilization, and implications for manufacturability and maintenance. Three rail vehicle body variants were developed, each incorporating a low-floor configuration to enhance accessibility and interior layout flexibility. The research explores the suitable placement of technical components such as a power unit and an air-conditioning system, and it evaluates interior layouts aimed at maximizing both passenger capacity and their travelling comfort. Key features, including door and window technologies, thermal comfort solutions, and seating arrangements, are also analyzed. The study emphasizes the importance of compromises between structural stiffness, reparability, production complexity, and passenger-oriented design considerations. A part of the research includes a proposal of three variants of a rail vehicle body frame, together with their strength analysis by means of the finite element method. These analyses identified that the maximal permissible stresses for the individual versions of the frame were not exceeded. Findings contribute to the development of more efficient, accessible, and sustainable regional passenger rail vehicles. Full article

Amid ongoing societal development, tourists’ travel behavior patterns have been undergoing substantial transformations, and understanding their evolution has emerged as a key area of scholarly interest. Taking Beijing as a case study, this research aims to uncover the spatiotemporal evolution patterns of tourist flows and their underlying driving mechanisms. Based on digital footprint relational data, a dual-perspective analytical framework—“tourist perception–tourist flow network”—is constructed. By integrating the center-of-gravity model, social network analysis, and regression models, the study systematically examines the dynamic spatial structure of tourist flows in Beijing from 2012 to 2024. The findings reveal that in the post-pandemic period, Beijing tourists place greater emphasis on the cultural connotation and experiential aspects of destinations. The gravitational center of tourist flows remains relatively stable, with core historical and cultural blocks retaining strong appeal, though a slight shift has occurred due to policy influences and emerging attractions. The evolution of the spatial network structure reveals that tourism flows have become more dispersed, while the influence of core scenic spots continues to intensify. Government policy orientation, tourism information retrieval, and the agglomeration of tourism resources significantly promote the structure of tourist flows, whereas the general level of tourism resources exerts no notable influence. These findings offer theoretical insights and practical guidance for the sustainable development and regional coordination of tourism in Beijing, and provide a valuable reference for the spatial restructuring of urban tourism in the post-COVID-19 era. Full article

This study investigates the friction stir joining of AA6082-T6 aluminum alloy and Noryl GFN2 polymer in a buttstrap configuration, targeting the development of lightweight cylindrical-shaped structures where the polymer provides thermal, chemical, and electrical insulation, while the aluminum ensures mechanical integrity. A parametric analysis was carried out to assess the ability to produce friction stir buttstrap composite panels in a single processing step and assess the resulting tensile and flexural behavior. To that end, travel and rotating speeds ranging from 2150 to 2250 rpm, and 100 to 140 mm/min, respectively, were employed while keeping plunge depth and the tilt angle constant. A total of nine composite joints were successfully produced and subsequently subjected to both tensile and four-point bending tests. The tensile and flexural strength results ranged from 80 to 139 MPa, and 39 to 47 MPa, respectively. Moreover, the microstructural examination revealed that all joints exhibited a defect within the joining region and its size and shape had a significant effect on tensile strength, whereas the flexural strength was less affected with more uniform results. The joining region was also characterized by a decrease in hardness, particularly in the pin-affected region on the aluminum end of the joint, exhibiting a W-shaped pattern. Contrarily, on the polymeric end of the joining region, no significant change in hardness was observed. Full article

Plasmodium falciparum malaria remains a major cause of morbidity and mortality, particularly in endemic regions. We report the case of a 21-year-old male with recent travel to an endemic area (Guapi, Colombia), who presented with febrile symptoms, severe respiratory distress, and oxygen saturation below 75%, necessitating orotracheal intubation. During the procedure, he developed pulseless electrical activity cardiac arrest, achieving return of spontaneous circulation after advanced resuscitation. Diagnosis was confirmed by thick blood smear, demonstrating P. falciparum infection. The patient progressed to multiorgan failure, including acute respiratory distress syndrome with capillary leak pulmonary edema, refractory distributive shock, acute kidney injury with severe hyperkalemia, and consumptive thrombocytopenia. Management included invasive mechanical ventilation, vasopressor support, sedation-analgesia, neuromuscular blockade, methylene blue, unsuccessful hemodialysis due to hemorrhagic complications, and platelet transfusions. Despite these interventions, the patient experienced a second cardiac arrest and died. This case highlights the severity and rapid progression of severe malaria with multisystem involvement, underscoring the critical importance of early diagnosis and intensive multidisciplinary management. It also emphasizes the need for preventive strategies for travelers to endemic areas and the development of clinical protocols to improve outcomes in complicated malaria. Full article

The rapid development of the logistics industry has underscored the urgent need for efficient and sustainable urban freight systems. As a core component of freight systems, heavy-duty trucks (HDT) have been researched regarding surface-level descriptive statistics of their heterogeneities, such as trip volume, frequency, etc., but there is a lack of in-depth analyses of the spatial interaction between freight travel and freight functional clustering, which restricts a systematic understanding of freight systems. Against this backdrop, this study develops a data-driven framework to analyze HDT behavioral heterogeneity and its spatial interactions with a freight functional zone in Shanghai. Leveraging the high-frequency trajectory data of nearly 160,000 HDTs across seven types, we construct a set of regional indicators and employ hierarchical clustering, dividing the city into six freight functional zones. Combined with the HDTs’ application scenarios, functional characteristics, and trip distributions, we further analyze the spatial interaction between the HDTs and clustered zones. The results show that HDT travel patterns are not merely responses to freight demand but complex reflections of urban industrial structures, infrastructure networks, and policy environments. By embedding vehicle behaviors within their spatial and functional contexts, this study reveals a layered freight system in which each HDT type plays a distinct role in supporting economic activities. This research provides a new perspective for deeply understanding the formation mechanisms of HDT trip distributions and offers critical evidence for promoting targeted freight management strategies. Full article

(1) Background: Evidence from non-human animal and spaceflight analog studies have suggested that traveling to outer space could have a significant impact on the structural properties of the hippocampus, a brain region within the medial temporal lobe that is critical for learning and memory. Here, we tested this hypothesis in a group of astronauts who participated in a six-month mission in the International Space Station (ISS). (2) Methods: We collected magnetic resonance imaging (MRI) scans from a sample of 17 (9 males, 8 females) astronauts before and after the ISS mission, and calculated percent gray matter volume changes in the whole hippocampus and its (anterior, body, and posterior) subregions in both hemispheres. (3) Following the six-month mission in the ISS, we found a significantly decreased volume in the whole left hippocampus; in addition, when looking at subregions separately, we detected a significantly decreased volume in the anterior subregion of the left hippocampus and the body subregion of the right hippocampus. We also found a significantly decreased volume in the whole right hippocampus of male astronauts as compared to female astronauts. (4) Conclusions: This study, providing the very first evidence of hippocampal volumetric changes in astronauts following a six-month mission to the ISS, could have significant implications for cognitive performance during future long-duration spaceflights. Full article

Participation in horse-related activities frequently involves relocating horses from the home stable to an activity venue, which might require local, regional, or international travel. In these circumstances, horses are exposed to unfamiliar surroundings and experience changes to their daily routines, which could have negative welfare impacts. An online survey was conducted in 2021 to ask experienced horse sector participants about the horse management practices that they perceived worked well and provided for positive horse welfare when undertaken at venues. Qualitative analysis identified four themes: ‘managing venues’, ‘monitoring fitness to participate’, ‘maintaining a healthy equine digestive system’, and ‘using horse behaviors to inform decision-making’. The findings indicate that activity-related individuals selected practices that assisted horses to adapt to venue surroundings, remain calm, and stay healthy. The co-authors propose that experienced participants recognize that practices include both provisions (inputs) and outcomes (the horse’s subjective experiences), resonating with the Five Freedoms and Five Domains models. For horse activity organizations proposing to implement the Five Domains model, the findings indicate that reviewing practices and implementing updates is timely and achievable. The authors propose that continuously updating practices will contribute to safeguarding horses and maintaining the sector’s social license to operate. Full article

Analyses of student mobility are typically conducted in an urban environment and are informed by socio-demographic or trip attributes. The prevailing focus is on individual modes of transport, different groups of commuters travelling to campus, students’ behavioural perceptions, and the totality of student trips. This paper starts with the identification of the determinants of student mobility that have received insufficient research attention. Utilising surveys, the study captures the mobility patterns of a sample of 1014 students and calculates their carbon footprint (CF; in kg/academic year) to assess whether the factors neglected in previous studies influence differences in the actual environmental load of student commuting. A regression analysis is employed to ascertain the significance of these factors as predictors of sustainable student mobility. This study exclusively focuses on the group of student commuters to campus and analyses the trips associated with compulsory activities at a suburban campus that is distant from the university centre and student facilities, which changes the mobility context in terms of commuting options. The under-researched factors identified in this research have not yet been quantified as CF. The findings confirm that only some of the factors neglected in previous research are statistically significant predictors of the local environmental load of student mobility. Specifically, variables such as student employment, frequency of class attendance, and propensity for ride-sharing could be utilised to forecast and regulate students’ mobility towards more sustainable patterns. However, all of the under-researched factors (including household size, region of origin (i.e., past experiences), residing at term-time accommodation while studying, and the availability of a family car) have an influence on the differences in CF magnitude in the studied campus. Full article