Search Results (261)

Animal models provide a controlled and reproducible environment for investigating the pathogenesis of human lung diseases. In many cases, the morphological changes associated with a particular model may resemble those seen in their human counterparts, but the corresponding biochemical events may differ, and their timeframe may be significantly reduced. Nevertheless, gaining insight into human disease mechanisms may be possible by employing experimental approaches that minimize the problems associated with extrapolating data from animal studies. Such strategies include using more than one model of a particular disease, employing different routes of administration of the injurious agent, using a variety of animal strains or species, or focusing on biochemical mechanisms common to both the animal model and its human counterpart. For example, rodent models that replicate elastic fiber injury in human pulmonary emphysema have been used to test aerosolized hyaluronan’s ability to slow the disease’s progression. The same models facilitated the identification of a new biomarker for pulmonary emphysema that may be a real-time indicator of therapeutic efficacy in clinical trials. Therefore, the appropriate use of these models can provide a necessary road map for designing appropriate dosages, delivery routes, timeframes, and endpoints in clinical trials of novel agents for the treatment of lung disease. Full article

This study presents a system model developed for collecting and analyzing spatial data on the project environment of transport infrastructure development in the post-war context, with a focus on supporting sustainable management and recovery planning. The model utilizes the OpenStreetMap Overpass Application Programming Interface (Overpass API) to extract structured geospatial information from OpenStreetMap (OSM), enabling efficient and accurate assessments of settlements affected by armed conflict. Python 3.11-based software modules were created to process OSM data, evaluate 17 relevant attributes of transport infrastructure objects, and visualize key characteristics for decision-makers. A case study was conducted on 23 Ukrainian settlements with partially damaged infrastructure, demonstrating how the proposed model facilitates timely and informed decisions for infrastructure redevelopment. By improving the accessibility and quality of spatial data, the model enhances the capacity for sustainable management of post-war transport infrastructure projects. To ensure the quality of spatial data obtained from OSM, a verification procedure was carried out by cross-checking with satellite images and official national geospatial data. The results showed an average deviation of ±4.4% in the length of road sections, confirming the reliability and accuracy of spatial objects obtained from OSM for use in transport infrastructure planning. The findings offer valuable insights for regional planners, public administrators, and policymakers involved in sustainable reconstruction and digital governance. Future research will focus on developing a comprehensive information system for identifying and prioritizing infrastructure development projects within defined administrative units such as municipalities and local communities. Full article

Skid resistance, or friction, on a road surface is a critical parameter in functional highway assessments, given its direct relationships with safety and accident frequency. Therefore, road administrations must collect friction data across their road networks to ensure safe roads for users. In addition, having a predictive model of skid resistance for each road section is essential for an efficient pavement management system (PMS). Traditionally, road authorities disregard rural roads, since they are more focused on freeways and traffic-intense roads. This study develops a model for predicting minimum-available skid resistance, which occurs in summer, measured using the Sideway-force Coefficient Routine Investigation Machine (SCRIM), on bituminous pavements in the single-carriageway road network of the Province of Gipuzkoa, Spain. To this end, traffic volume data available in the PMS of the Provincial Council of Gipuzkoa, such as the annual average daily traffic (AADT) and the AADT of heavy vehicles (AADT.HV), were uniquely used to forecast skid-resistance values collected in summer. Additionally, a methodology for eliminating outliers is proposed. Despite the simplicity of the model, which does not include information about the materials at the surface layer, a coefficient of determination (R²) of 0.439 was achieved. This model can help road authorities identify the roads for which lower skid-resistance values are most likely to occur, allowing them to focus their attention and efforts on these roads, which are key infrastructure in rural areas. Full article

Roman cities represent the Empire’s broader approach to urban planning, characterized by geometric precision and a strategic layout. Their spatial organization reflects the underlying military and administrative objectives, which can be better understood through new analytical tools. This research investigates the Roman military strategy behind the establishment of Timgad, a Roman archeology in Algeria, using Space Syntax Analysis (SSA) to examine its spatial and urban structure. This study highpoints how its spatial configuration was intricately linked to military tactics aimed at asserting control and dominance by analyzing the city’s grid-like layout and applying SSA indicators, such as Connectivity, Integration, Entropy, Control, Controllability and Through Vision (via Axial Map and Visibility Graph Analysis). The results show high value in these indicators, especially in areas where military structures were strategically located along main roads and key urban nodes, demonstrating a careful exertion to maintain surveillance and authority over space. This spatial configuration reveals a deep synergy connecting military logic and urban design, sustaining the idea that Roman town planning supported both functional and symbolic roles in establishing imperial authority. This study concludes that Roman military strategy was not only central to their territorial expansion but also instrumental in shaping long-lasting urban models, influencing the structure of colonial cities far beyond their time. Timgad thus serves as an influential case of how military requirements shaped the built environment in the Roman Empire. Full article

With the rapid adoption of automated driving systems, ensuring safe and efficient driver takeover has become a crucial challenge for road safety. This study introduces a novel psychological framework for understanding and predicting takeover behavior in conditionally automated vehicles, leveraging an extended Theory of Planned Behavior (TPB) model enriched by real-world driver experience. Drawing on survey data from 385 automated driving system users recruited in Shaoguan City, China, through face-to-face questionnaire administration covering various ADS types (ACC, lane-keeping, automatic parking), we demonstrate that driver attitudes, perceived behavioral control, and subjective norms are significant determinants of takeover intention, collectively explaining nearly half of its variance (R² = 48.7%). Importantly, our analysis uncovers that both intention and perceived behavioral control have robust, direct effects on actual takeover behavior. Crucially, this work is among the first to reveal that individual user characteristics—such as driving experience and ADS (automated driving system) usage frequency—substantially moderate these psychological pathways: experienced or frequent users rely more on perceived control and attitude, while less experienced drivers are more susceptible to social influences. By advancing a multi-dimensional psychological model that integrates personal, social, and experiential moderators, our findings deliver actionable insights for the design of adaptive human–machine interfaces, tailored driver training, and targeted safety interventions in the context of automated driving. Using structural equation modeling with maximum likelihood estimation (χ²/df = 2.25, CFI = 0.941, RMSEA = 0.057), this psychological approach complements traditional engineering models by revealing that takeover behavior variance is explained at 58.3%. Full article

Rural roads are critical for connecting isolated communities to essential services such as education and health and administrative services, as well as production and market opportunities in low-income countries. More than 70% of movements of people and goods in Sub-Saharan Africa are heavily reliant on rural transport systems, using both motorised but mainly alternative means of transport. However, rural roads often suffer from poor construction due to the use of low-strength, in situ soils and limited financial resources, leading to premature failures and subsequent traffic disruptions with significant economic losses. This study investigates the use of rice husk ash (RHA), a waste byproduct from rice production, as a sustainable supplement to Ordinary Portland Cement (OPC) for soil stabilisation in order to increase durability and sustainability of rural roads, hence limit recurrent maintenance needs and associated transport costs and challenges. To conduct this study, soil samples collected from Mulungushi, Zambia, were treated with combinations of 6–10% OPC and 10–15% RHA by weight. Laboratory tests measured maximum dry density (MDD), optimum moisture content (OMC), and California Bearing Ratio (CBR) values; the main parameters assessed to ensure the quality of road construction soils. Results showed that while the MDD did not change significantly and varied between 1505 kg/m³ and 1519 kg/m³, the OMC increased hugely from 19.6% to as high as 26.2% after treatment with RHA. The CBR value improved significantly, with the 8% OPC + 10% RHA mixture achieving the highest resistance to deformation. These results suggest that RHA can enhance the durability and sustainability of rural roads and hence improve transport systems and subsequently improve socioeconomic factors in rural areas. Full article

Urban health planning requires a multi-scalar understanding of the territory, capable of capturing socio-economic inequalities and health needs at the local level. In the case of Rome, current administrative subdivisions—Urban Zones (Zone Urbanistiche)—are too large and internally heterogeneous to serve as effective units for equitable health planning. This study presents a methodology for the territorial redefinition of Rome’s Municipality III, aimed at supporting healthcare planning through an integrated analysis of census sections. These were grouped using a combination of census-based socio-demographic indicators (educational attainment, employment status, single-person households) and real estate values (OMI data), alongside administrative and road network data. The resulting territorial units—21 newly defined Mesoareas—are smaller than Urban Zones but larger than individual census sections and correspond to socio-territorially homogeneous neighborhoods; this structure enables a more nuanced spatial understanding of health-related inequalities. The proposed model is replicable, adaptable to other urban contexts, and offers a solid analytical basis for more equitable and targeted health planning, as well as for broader urban policy interventions aimed at promoting spatial justice. Full article

Highway rest areas are relevant components of road infrastructure, providing drivers with essential opportunities to rest and mitigate fatigue-related crash risks. Despite their acknowledged importance, little is known about the factors that influence their actual utilization. This study addresses this gap by applying supervised machine learning algorithms to predict hourly occupancy levels of truck parking lots at highway rest areas using a dataset collected from digital monitoring systems in Poland. The dataset includes 10,740 observations and 33 features describing infrastructural, administrative, and locational characteristics of selected rest areas in Poland. Eight classification models—Gradient Boosting, XGBoost, Random Forest, k-NN, Decision Tree, Logistic Regression, SVM, and Naive Bayes—were implemented and compared using standard performance metrics. Gradient Boosting emerged as the best-performing model, achieving the highest prediction accuracy and identifying key features such as the presence of fuel stations, rest area category, and facility amenities as significant predictors of occupancy. The findings highlight the potential of interpretable machine learning methods for supporting infrastructure planning, particularly in identifying underutilized or overburdened facilities. This research demonstrates a data-driven approach for analyzing rest area usage and provides practical insights for optimizing facility distribution, enhancing road safety, and informing future investments in transport infrastructure. Full article

This study presents an integrated surveying methodology for efficient and accurate cadastral documentation, combining UAV photogrammetry, SLAM-based terrestrial and aerial scanning, and conventional geodetic measurements. Designed to be scalable across various cadastral and planning contexts, the workflow was tested in Charlottenburg, Romania’s only circular heritage village. The approach addresses challenges in built environments where traditional total station or GNSS techniques face limitations due to obstructed visibility and complex architectural geometries. The SLAM system was initially deployed in mobile scanning mode using a backpack configuration for ground-level data acquisition, and was later mounted on a UAV to capture building sides and areas inaccessible from the main road. The results demonstrate that the integration of aerial and terrestrial data acquisition enables precise building footprint extraction, with a reported RMSE of 0.109 m between the extracted contours and ground-truth total station measurements. The final cadastral outputs are fully compatible with GIS and CAD systems, supporting efficient land registration, urban planning, and historical site documentation. The findings highlight the method’s applicability for modernizing cadastral workflows, particularly in dense or irregularly structured areas, offering a practical, accurate, and time-saving solution adaptable to both national and international land administration needs. Beyond the combination of known technologies, the innovation lies in the practical integration of terrestrial and aerial SLAM (dual SLAM) with RTK UAV workflows under real-world constraints, offering a field-validated solution for complex cadastral scenarios where traditional methods are limited. Full article

As transportation infrastructure systems continue to expand, the demand for unmanned aerial vehicle (UAV) technologies in the assessment of urban infrastructure is expected to grow substantially, due to their strong potential for efficient data collection and post-processing. UAVs offer numerous advantages in infrastructure assessment, including enhanced time and cost efficiency, improved safety, and the ability to capture high-quality data. Furthermore, integrating various data-collecting sensors enhances the versatility of UAVs, enabling the acquisition of diverse data types to support comprehensive infrastructure evaluations. Numerous post-processing software applications utilizing various structure-from-motion (SfM) techniques have been developed, significantly facilitating the assessment process. However, researchers’ efforts to find the potentialities of this technology will be in vain if its applications are not utilized effectively in the practical field. Therefore, this study aims to determine the adaptation condition of UAV technologies in different Department of Transportation (DOT) and Federal Highway Administration (FHWA) agencies to assess transportation infrastructure systems. This study also explores the quantitative analysis of benefits and challenges/barriers, expectations for every UAV and post-processing software, and the cutting-edge features that should be integrated with UAVs to effectively evaluate transportation infrastructure systems. A comprehensive survey form was distributed to all 50 DOTs and the FHWA, and 35 complete responses were recorded from 27 DOTs and the FHWA. The survey results show that 25 agencies currently use UAVs for roads or highways, and 23 DOTs for bridges, confirming these as the most commonly assessed infrastructure systems. The top benefits found in this study include safety, cost effectiveness, and time efficiency (mean ratings: 3.95–4.28), while weather, FAA regulations, and airspace restrictions are the main challenges. Respondents emphasize the need for longer flight times, better automation, and advanced data tools, underscoring growing adoption and highlighting the need to overcome technical, regulatory, and data privacy challenges for optimal UAV integration within transportation infrastructure systems management. Full article

This scientific research presents the most significant aspects of the structural analysis and verification of the main steel railway bridges in Peru in accordance with the American standard. To this end, linear and finite element analyses (FEMs) were performed using calculation notes in MATHCAD and structural validation software (SAP2000, CSI Bridge, IDEA STATICA and GE05), among others, based on on-site inspections, which allowed results to be obtained to analyze, evaluate and determine the structural performance factors (RF) of the main railway bridges in Peru. For this, data obtained from several railway corridors in Peru were taken into consideration, such as the lines of the Southern Railway Train, Central Andean Railway, Huancayo–Huancavelica Railway Train and the Tacna–Arica Train; in addition to the feasibility studies on the Interoceanic Train project: Iquitos–Yurimaguas; projects administered through Public–Private Partnership PPP as well as by the Regionals Government and MTC-Peru. These data were used in order to be able to warn of certain technical aspects that would influence the recommendations for a locomotive replacement project in which new units had different load distributions between the axles, which would make it necessary to review the tracks and bridges of the same in order to determine if they would be able to withstand the new forces safely, as well as to reinforce structural elements according to the material and the structural condition, and finally, to assess the variation in the increase in train speed in some road corridors to achieve a better FRA (Federal Railway Administration) classification of Class 3, where the presence of structures dating back to the last century has been verified as well (1851–1856–1908). Likewise, the seismic criteria and geotechnical conditions of the most representative areas of the country (acceleration 0.30 g) were included in order to also be able to make technical recommendations that would allow us to ensure the useful life of the structure in service, operation and maintenance conditions. Full article

Background/Objectives: Epidemics have historically shaped societies, influencing demographic structures, social organization, and economic stability. The 1742–1743 epidemic had a profound impact on populations along the Royal Road (Camino Real), the main colonial corridor between Buenos Aires and Lima. However, its specific demographic and socio-economic effects remain underexplored. This study aims to examine these impacts of the 1742–1743 epidemic through a comparative analysis of urban centers and Indigenous communities. Methods: A historical–comparative approach was employed, analyzing secondary sources including parish records and colonial administrative documents. This study assessed excess mortality and socio-economic consequences across different population groups and settlement types. Results: Mortality rates increased dramatically—up to twelve times the pre-epidemic average in Cordova (Córdoba) and by 45% in Santa Fe—disproportionately affecting Indigenous and enslaved populations. Urban centers experienced severe economic disruption and slow recovery, whereas Indigenous communities and Jesuit missions demonstrated greater resilience. Their communal strategies and early isolation measures contributed to a faster demographic stabilization. Additionally, the epidemic weakened colonial governance in some areas, altering local power structures. Conclusions: The epidemic of 1742–1743 revealed divergent patterns of vulnerability and resilience. Comparative analysis underscores recurring themes in the epidemic response and recovery, drawing relevant parallels with contemporary crises such as COVID-19. Recognizing these historical patterns of adaptation can inform present and future public health strategies. The terminology “plague” is used based on contemporary sources and not confirmed clinically. Full article

The trematodes Fasciola hepatica and F. gigantica are transmitted by lymnaeid snails and cause fascioliasis in livestock and humans. Human infection is emerging in southern and southeastern Asia. In India, the number of case reports has increased since 1993. This multidisciplinary study analyzes the epidemiological scenario of human infection. The study reviews the total of 55 fascioliasis patients, their characteristics, and geographical distribution. Causes underlying this emergence are assessed by analyzing (i) the climate change suffered by India based on 40-year-data from meteorological stations, and (ii) the geographical fascioliasis hotspots according to archeological–historical records about thousands of years of pack animal movements. The review suggests frequent misdiagnosis of the wide lowland-distributed F. gigantica with F. hepatica and emphasizes the need to obtain anamnesic information about the locality of residence and the infection source. Prevalence appears to be higher in females and in the 30–40-year age group. The time elapsed between symptom onset and diagnosis varied from 10 days to 5 years (mean 9.2 months). Infection was diagnosed by egg finding (in 12 cases), adult finding (28), serology (3), and clinics and image techniques (12). Climate diagrams and the Wb-bs forecast index show higher temperatures favoring the warm condition-preferring main snail vector Radix luteola and a precipitation increase due to fewer rainy days but more days of extreme rainfall, leading to increasing surface water availability and favoring fascioliasis transmission. Climate trends indicate a risk of future increasing fascioliasis emergence, including a seasonal infection risk from June–July to October–November. Geographical zones of high human infection risk defined by archeological–historical analyses concern: (i) the Indo-Gangetic Plains and corridors used by the old Grand Trunk Road and Daksinapatha Road, (ii) northern mountainous areas by connections with the Silk Road and Tea-Horse Road, and (iii) the hinterlands of western and eastern seaport cities involved in the past Maritime Silk Road. Routes and nodes are illustrated, all transhumant–nomadic–pastoralist groups are detailed, and livestock prevalences per state are given. A baseline defining areas and seasons of high infection risk is established for the first time in India. This is henceforth expected to be helpful for physicians, prevention measures, control initiatives, and recommendations for health administration officers. Full article

Forests, as tourism resources with ecological and aesthetic value, play a significant role in rural development. Forest villages, which rely on forest resources, are an essential component of rural construction. Studying the spatial distribution characteristics and influencing factors of national forest villages within provincial administrative areas provides valuable insights into the sustainable development of rural tourism and the achievement of rural revitalization goals. This study examines 125 national forest villages in Liaoning Province. Based on the data on the geographical locations of the villages and their related influencing factors collected during the period from May to December 2024, spatial indices such as the nearest neighbor index, Gini index, and kernel density have been analyzed using mathematical statistics and ArcGIS spatial analysis methods. Additionally, this research investigates various factors influencing the distribution of forests and rural areas, as well as the interaction mechanisms among these factors. The results indicate the following. (1) The spatial distribution of national forest villages in Liaoning Province is clustered and uneven, with a pattern of “dense in the east and west, sparse in the middle”. (2) The number of forest villages in Liaoning Province is generally positively correlated with forest coverage, temperature, rainfall, road network density, and river network density. Conversely, it is negatively correlated with economic development level, population density, total population, and altitude. (3) Geographical exploration results suggest that economic development level and forest coverage rate are the most significant factors affecting the spatial differentiation of forest and rural areas in Liaoning Province. Interaction analysis reveals that river network density and forest coverage rate have the strongest combined effect, followed by total economic output and forest coverage rate. Full article

The new EU Cohesion Policy for 2021–2027 aims for inclusive and sustainable growth to address regional disparities by improving transport connectivity, digitalisation, and social inclusion, thereby reducing peripheral isolation. It is intended to provide development tools and enable investments in green and digital transitions to integrate peripheral areas more effectively with their development centres. This study assumes that, considering the EU cohesion policy objectives, regional centres (in Poland, centres of administrative territorial units named Voivodeships) should exert significant economic and social influence over their administrative regions. This aligns with both classic spatial concepts of socio-economic development and contemporary approaches to sustainable development. The research aimed to assess the extent to which regional centres are connected to their regions and their impact on the entire regional hinterland, particularly on municipalities outside the agglomeration system. The study identified municipalities that lack the influence of regional centres, creating zones with challenging socio-economic development conditions (based on the road network and the population potential of the Huff model). The analysis reveals that the highest probabilities are observed near Warsaw (Mazowieckie voivodeship; 0.7548) while the lowest are around Olsztyn (Warmińsko-Mazurskie voivodeship; 0.6763). The deepest depression in terms of usage of the regional capital is observed in the Zachodniopomorskie voivodeship. In this voivodeship, municipalities in the internal peripheries have an average probability coefficient of 0.3015. Full article