Search Results (6,569)

This study presents a high-fidelity digital twin (DT) framework designed to evaluate and improve vertiport operations for Advanced Air Mobility (AAM). By integrating Unreal Engine, AirSim, and Cesium, the framework enables real-time simulation of Unmanned Aerial Vehicles (UAVs), including unmanned electric vertical take-off and landing (eVTOL) operations under nominal and disrupted conditions, such as adverse weather and engine failures. The DT supports interactive visualisation and risk-free analysis of decision-making protocols, vertiport layouts, and UAV handling strategies across multi-scenarios. To validate system realism, mixed-reality experiments involving physical UAVs, acting as surrogates for eVTOL platforms, demonstrate consistency between simulations and real-world flight behaviours. These UAV-based tests confirm the applicability of the DT environment to AAM. Intelligent algorithms detect Final Approach and Take-Off (FATO) areas and adjust flight paths for seamless take-off and landing. Live environmental data are incorporated for dynamic risk assessment and operational adjustment. A structured capacity evaluation method is proposed, modelling constraints including turnaround time, infrastructure limits, charging requirements, and emergency delays. Mitigation strategies, such as ultra-fast charging and reconfiguring the layout, are introduced to restore throughput. This DT provides a scalable, drone-integrated, and data-driven foundation for vertiport optimisation and regulatory planning, supporting safe and resilient integration into the AAM ecosystem. Full article

Rural tourism is one of the important measures used to realize the rural revitalization strategy in China. At the same time, the “action of prospering the border and enriching the people” is a crucial link in driving the economic development of border areas. With the continuous improvement of the G331 section of the Jilin Line, the development of rural tourism along the border has been accelerated. Therefore, reducing the livelihood vulnerability of farmers is conducive to promoting the rural revitalization strategy in China and consolidating the achievements of poverty alleviation and difficulties in tackling them. This paper takes Tumen City, Yanbian Korean Autonomous Prefecture, Jilin Province, as the sample area; takes Mapai Village, Bailong Village, Hexi Village, Liangshui Village, and Tingyan Village as the research objects; obtains survey data for 224 households through on-the-spot investigation; constructs an evaluation index system for farmers’ livelihood vulnerability in border rural tourist destinations based on the sustainable livelihood theory and the analysis framework of “exposure–sensitivity–adaptability”; calculates farmers’ livelihood vulnerability in this research area by the entropy method and the comprehensive index method; and classifies different villages’ and farmers’ livelihood vulnerability by the natural breakpoint method. By using the multiple linear regression method, this paper analyzes the factors influencing farmers’ livelihood vulnerability in border rural tourist destinations. The results show the following: (1) The overall livelihood vulnerability of farmers is negative, indicating that farmers have a certain ability to resist external risks, but the livelihood vulnerability of some investigated villages is positive, indicating that farmers’ ability to resist external risks is weak, which is closely related to village geographical environment, tourism market environment, family characteristics, and other factors. (2) The livelihood vulnerability of villages with relatively perfect tourism formats is low, which shows that tourism can effectively reduce the livelihood vulnerability of farmers to a certain extent. (3) The household head’s education level, the total price of agricultural machinery, annual income, the ability to borrow money, family size, the number of disabled people, and other factors have a significant influence on the livelihood vulnerability of farmers. Full article

Unsafe behavior among air traffic controllers is a significant causal factor in civil aviation safety incidents. To explore the risks and pathways associated with controller-induced aviation accidents, this study develops an analytical model of controller unsafe behavior based on association rules and fault tree Bayesian networks. First, the Human Factors Analysis and Classification System (HFACS) was applied to identify and categorize aviation incident reports attributed to controller errors. Next, association rule algorithms were employed to uncover potential associations between controller unsafe behaviors and related risk factors, and a fault tree Bayesian network (FT-BN) model of controller unsafe behaviors was constructed based on these associations. The results revealed that the most likely unsafe behaviors were: improper allocation of aircraft spacing (30.5%), failure to take necessary intervention measures (28.4%), and improper transfer of control (27.8%). Backward analysis of the FT-BN indicated that improper allocation of aircraft spacing was most likely triggered by failure to provide adequate controller training, failure to take necessary intervention measures was most often caused by forgotten information, and improper transfer of control was most frequently associated with controller fatigue and failure to put risk management efforts in place. This study provides an important framework for the analysis and evaluation of controller behavior management and offers key insights for improving air traffic safety. Full article

This research evaluates the vulnerability of public infrastructure in San Luis parish, Riobamba canton, Ecuador, to the flood risk posed by the Chibunga River under return period scenarios of 10, 50, 100, and 500 years. The main objective was to identify the most exposed systems—such as drinking water, sewerage, power grid, and utility poles—in order to prioritize mitigation measures. The methodology combined hydrometeorological analysis, hydraulic modeling using HEC-HMS and Iber, and the estimation of economic losses through the DaLA methodology. The results reveal that the low vulnerability of the drinking water system, as less than 0.08% of the network’s length, is at risk in the high-to-very-high range, even in a scenario with a 500-year return period. On the other hand, there is evidence of high exposure of the sewerage network in extreme scenarios, considering that 49.15% is at high-to-very-high risk in the worst-case scenario. Furthermore, as the return period increases, there is a growing impact on the electrical network, where the proportion of assets at high-to-very-high risk increases from 0.60% to 6.88% for high voltage, 0.00% to 18.03% for low voltage, and 0.00% to 1.18% for streetlights for a return period of 10 to 500 years. It should be noted that the estimated direct economic losses amount to USD 84,162.86 when taking into account the worst-case scenario. In this regard, the novelty of this study lies in the integration of technical, hydraulic, and economic analyses for a scarcely studied rural Andean area, providing crucial data for preventive risk management. It concludes that investment in prevention is more cost-effective than post-disaster reconstruction, recommending the strengthening of the sewerage system’s hydraulic capacity and the optimization of electrical infrastructure protection. Full article

To accurately grasp the land and ecological dynamics in the Henan section of the Yellow River Basin (YRB) and provide detailed local data for the ecological protection of the YRB, this article takes the Henan segment within the YRB as the research area, explores the spatio-temporal evolution of land use (LU) and landscape ecological risks (LERS), and predicts LU and LERS under various scenarios in the future based on the PLUS model. We found that: (1) From 2000 to 2020, object types in research area were given priority with cultivated land, forest land, and construction land, with construction land and cultivated land experiencing the largest changes of 5.71% and −6.34%, respectively. Changes in other land types varied within a ±3% range. The expansion of construction land principally encroached upon cultivated land, indicating significant urban sprawl. (2) The high-ecological-risk areas were clustered in the area centered in Zhengzhou, and the low-ecological-risk areas were distributed in the edge of the study area. As risk levels increased, the risk center gradually shifted towards the central regions, particularly around Luoyang and at the junction of Luoyang, Zhengzhou, and Jiaozuo. (3) The LU status in 2030 was projected using the PLUS model under three varied scenarios. The Kappa coefficient of the model was 0.81, and the overall accuracy was about 88.13%. Cultivated land, forest land, and construction land still accounted for the main part, and the area of cultivated land and construction land changed significantly. Based on this analysis of LERS prediction, the distribution of risk levels in different scenarios was different, but in general, high-ecological-risk areas and higher-ecological-risk areas accounted for the main part, while the study area’s edges were where low-ecological-risk zones were situated. Research can offer scientific and technological support for the sensible utilization and administration of resources, along with the protection of the ecological environment and regional sustainable development. Full article

The increased complexity of buildings has led to rigorous performance demands from materials and building envelopes. As markets for low-carbon, renewable construction materials grow, cross-laminated timber and wood fiber insulation have emerged as promising alternatives to meet these rigorous demands. However, an investigation into the performance and interaction of materials within high-performance systems is necessary to determine the durability risks associated with increased complexity and the introduction of new materials. This is important in order to ensure that these materials can meet the required functions of the building while taking advantage of their environmental benefits. To do so, this case study investigated a building constructed of cross-laminated timber and wood fiber insulation in a cold climate (Zone 6A) (Belfast, ME, USA). During construction, the building was instrumented with temperature, relative humidity, and moisture content monitoring instrumentation through the envelope, i.e., wall and roof assemblies. The conditions within the envelope were monitored for a two-year period and used to calibrate a hygrothermal model, along with measured material properties. The calibrated model was used to conduct a 5-year simulation and mold risk assessment. Findings demonstrated that there was no moisture or mold risk throughout the monitoring period or simulation. This supports the integration of cross-laminated timber and wood fiber insulation in sustainable building practices, particularly in cold climates where moisture management is critical. Full article

Background and Objectives: Despite the potential benefits for the patient, aerospace interventions pose significant risks. Pre-hospital triage and patient transport are two essential elements for achieving an organized system of trauma. The advantages and disadvantages of using land transport from the scene of the accident to the trauma centers have been extensively studied, but there are gaps for air transport, and their exact level of efficiency is not known. Materials and Methods: The present study includes a total number of 77 patients, present at SMURD Galați air service for polytraumas caused by various mechanisms, with pluri-regional involvement. The identification of patients, as well as the selection of the most important anamnestic data, was performed after signing a confidentiality agreement; subsequently, all this information was introduced in centralized tables made in the statistical program IBM SPSS Statistics V24. Results: Out of the total of 77 polytraumatized patients who needed air transfer, an average age of 17.3 years will be noted, with a predominance of males in a 2:1 ratio. Most polytraumas are due to road accidents (74%) and patients with minimal tri-regional damage (51.4%). Conclusions: Taking into account the existing statistics in this research, it is important to implement prevention elements, designed based on the profile of the polytraumatized patient. Thus, accessing the most important characteristics of these patients can be an extremely important starting point in reducing the incidence of polytrauma or even patient deaths. Full article

Background/Objectives: Preterm infants without neurological damage are at greater risk of developing specific difficulties due to the unpredictable effects of the interaction between biological immaturity and characteristics of physical and social environment. This paper discusses the potential advantages and limitations of placing premature infants in daycare in the first three years. Methods: In light of the scientific literature, the article discuss-es the topic through a critical comparison of studies on the developmental outcomes of preterm infants, on the characteristics of nurseries and on the role of educators. Results: Nursery placement must be evaluated in an integrated and multifactorial perspective, taking into account the specific vulnerabilities of each individual preterm child and the characteristics of the nursery. The role of educators is to structure a quality educational environment that meets the specific needs of each individual preterm child, in close collaboration with parents and specialists. Conclusion: This article provides suggestions to parents, educators, and specialists for the assessment and intervention with preterm children without neurological impairment in the educational setting, with a multidisciplinary view to prevention and early intervention. Full article

Lung cancer is the leading cause of cancer mortality globally, despite the advancements in screening and management. Survival rates for lung cancer remain suboptimal, largely due to late-stage diagnoses and tumor heterogeneity. Recent advancements in artificial intelligence and radiomics provide a promising outlook for lung cancer screening, diagnosis, personalized treatment, and prognosis. These advances use large-scale clinical and imaging datasets that help identify patterns and predictive features that may be missed by human interpretation. Artificial intelligence tools hold the potential to take clinical decision-making to another level, thus improving patient outcomes. This review summarizes current evidence on the applications, challenges, and future directions of artificial intelligence (AI) in lung cancer care, with an emphasis on early diagnosis and personalized treatment. We examine recent developments in AI-driven approaches, including machine learning and deep neural networks, applied to imaging (radiomics), histopathology, biomarker analysis, and multi-omic data integration. AI-based models demonstrate promising performance in early detection, risk stratification, molecular profiling (e.g., programmed death-ligand 1 (PD-L1) and epidermal growth factor receptor (EGFR) status), and outcome prediction. These tools may enhance diagnostic accuracy, optimize therapeutic decisions, and ultimately improve patient outcomes. However, significant challenges remain, including model heterogeneity, limited external validation, generalizability issues, and ethical concerns related to transparency and clinical accountability. AI holds transformative potential for lung cancer care but requires further validation, standardization, and integration into clinical workflows. Multicenter collaborations, regulatory frameworks, and explainable AI models will be essential for successful clinical adoption. Full article

In this study, a novel pattern recognition method named boosting–partial least squares–discriminant analysis (Boosting-PLS-DA) was developed for the non-destructive and accurate origin identification of food and medicine homologous substances (FMHSs). Taking Gastrodia elata, Aurantii Fructus Immaturus, and Angelica dahurica as examples, spectra of FMHSs from different origins were obtained by portable near-infrared (NIR) spectroscopy without destroying the samples. The identification models were developed with Boosting-PLS-DA, compared with principal component analysis (PCA) and partial least squares–discriminant analysis (PLS-DA) models. The model performances were evaluated using the validation set and an external validation set obtained one month later. The results showed that the Boosting-PLS-DA method can obtain the best results. For the analysis of Aurantii Fructus Immaturus and Angelica dahurica, 100% accuracies of the validation sets and external validation sets were obtained using Boosting-PLS-DA models. For the analysis of Gastrodia elata, Boosting-PLS-DA models showed significant improvements in external validation set accuracies compared to PLS-DA, reducing the risk of overfitting. Boosting-PLS-DA method combines the high robustness of ensemble learning with the strong discriminative capability of discriminant analysis. The generalizability will be further validated with a sufficiently large external validation set and more types of FMHSs. Full article

Background/Objectives: This review aimed to evaluate whether patients undergoing dental extractions while taking antidepressants experience increased intra-operative or post-operative bleeding compared to patients not taking these medications. Methods: A comprehensive literature search was conducted across PubMed, EMBASE, Web of Science, Scopus, and ClinicalTrials.gov for randomized controlled trials (RCTs) published before 17 August 2025. Studies were included if they compared bleeding outcomes between antidepressant users and non-users undergoing dental extraction procedures. The review followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines and was registered with the International Prospective Register of Systematic Reviews (PROSPERO, CRD42025645035). Results: Of 689 studies screened, no RCTs met the eligibility criteria. Only one retrospective study, which did not match the inclusion criteria, identified a 1% incidence of bleeding complications in users of selective serotonin reuptake inhibitors (SSRIs) undergoing invasive dental procedures. However, it lacked a control group and standardized methodology, so this study was included in the discussion section. Conclusions: The lack of high-quality evidence, especially studies examining dynamic coagulation parameters like bleeding time and prothrombin time before and after antidepressant use, highlights a significant gap in the research. These findings emphasize the urgent need for well-designed clinical trials to determine the potential effect of antidepressants on bleeding risk. Full article

Surface subsidence induced by underground mining in mining areas significantly alters surface topography and hydrogeological conditions, forming depressions and fissures, thereby affecting regional runoff-ponding processes and groundwater infiltration patterns. Accurate assessment of infiltration volumes in subsidence zones under heavy rainfall is crucial for designing underground drainage systems and evaluating water-inrush risks in open-pit to underground transition mines. Taking the surface subsidence area of the Dahongshan Iron Mine as a case study, this paper proposes a rainfall infiltration calculation method based on the precise delineation of surface ponding-infiltration zones. By numerically simulating the subsidence range, the study divides the area into two distinct infiltration characteristic zones under different mining states: the caved zone and the water-conducting fracture zone. The rainfall infiltration volume under storm conditions was calculated separately for each zone. The results indicate that high-intensity mining-induced subsidence leads to a nonlinear surge in stormwater infiltration, primarily due to the significant expansion of the highly permeable caved zone. The core mechanism lies in the area expansion of the caved zone as a rapid infiltration channel, which dominates the overall infiltration capacity multiplication. These findings provide a scientific basis for the design of mine drainage systems and the prevention of water-inrush disasters. Full article

The article presents an analysis of current (during the period 1985–2022) and projected (during the period 2025–2099) changes in the hydrological regime of the Buktyrma, Yesil, and Zhaiyk river basins in Kazakhstan under the conditions of global climate change. This study is based on the integration of data from General Circulation Models (GCMs) of the sixth phase of the CMIP6 project, socio-economic development scenarios SSP2-4.5 and SSP5-8.5, as well as the results of hydrological modelling using the SWIM model. The studies were carried out with an integrated approach to hydrological change assessment, taking into account scenario modelling, uncertainty analysis and the use of bias correction methods for climate data. A calculation method was used to analyse the intra-annual distribution of runoff, taking into account climate change. Detailed forecasts of changes in runoff and intra-annual water distribution up to the end of the 21st century for key water bodies in Kazakhstan were obtained. While the projections of river flow and hydrological parameters under CMIP6 scenarios are actively pursued worldwide, few studies have explicitly focused on forecasting intra-annual flow distribution in Central Asia, calculated using a methodology appropriate for this region and using CMIP6 ensemble scenarios. There have been studies on changes in the intra-annual distribution of runoff for individual river basins or local areas, but for the historical period, there have also been studies on modelling runoff forecasts using CMIP6 climate models, but have been very few systematic publications on the distribution of predicted intra-annual runoff in Central Asia, and this issue has not been fully studied. The projections suggest an intensification of flow seasonality (1), earlier flood peaks (2), reduced summer discharges (3) and an increased likelihood of extreme hydrological events under future climatic conditions. Changes in the seasonal structure of river flow in Central Asia are caused by both climatic factors—temperature, precipitation and glacier degradation—and significant anthropogenic influences, including irrigation and water management structures. These changes directly affect the risks of flooding and water shortages, as well as the adaptive capacity of water management systems. Given the high level of water management challenges and interregional conflicts over water use, the intra-annual distribution of runoff is important for long-term planning, the development of adaptation measures, and the formulation of public policy on sustainable water management in the face of growing climate challenges. This is critically important for water, agricultural, energy, and environmental planning in a region that already faces annual water management challenges and conflicts due to the uneven seasonal distribution of resources. Full article

The number of students studying outside their home countries has increased in recent years, and the United Kingdom has long been positioned as a leading destination, consistently being ranked among the top five English-speaking countries for international education. However, in 2024, the UK experienced a significant decline in international student enrolments, with Australia surpassing the UK to take second place globally. This decline coincided with an increasingly restrictive political climate, particularly reflected in changes to student visa policies and new limitations on dependents. The reduction in international student numbers poses serious financial risks to UK universities, many of which rely heavily on tuition from overseas students, and brings broader organizational challenges, including staffing cuts, programme restructuring, and reduced support services. Societally, it impacts local economies, reduces cultural diversity, and weakens the UK’s soft power and global educational influence. This entry explores the current state of the UK’s international student supply chain, examines emerging post-2024 challenges, and outlines key implications to inform institutional and policy-level responses. Full article

Background/Objectives: The combination of denosumab treatment with biological disease-modifying antirheumatic drugs (bDMARDs) or targeted synthetic disease-modifying antirheumatic drugs (tsDMARDs) in patients with inflammatory rheumatic diseases (IRD) may raise safety concerns for clinicians, particularly regarding infections. In this study, we investigated whether the risk of infection increases in patients who receive bDMARDs or tsDMARDs for IRD and are simultaneously treated with denosumab for osteoporosis (OP). Methods: As a control group, we evaluated patients receiving bDMARDs or tsDMARDs concomitantly with zoledronic acid (ZA), which is not clearly associated with infections. A total of 88 patients—including 30 patients receiving bDMARDs or tsDMARDs with ZA and 58 patients receiving bDMARDs or tsDMARDs with denosumab—met the criteria and were included in this study. The groups were compared in terms of the ratio/risk of serious infections requiring hospitalisation and infections requiring outpatient treatment after applying the inverse probability of treatment weighting (IPTW) to the control for confounding factors. The Cox proportional hazards regression model was used to compare the risks of infection, taking confounding factors into account. Results: The mean age of patients in the ZA group was 59.07 years (±SD: 13.65), while that of patients in the denosumab group was 69.93 years (±SD: 11.72). Comorbidities occurred more frequently in the denosumab group (n = 44, 75.86%) than in the ZA group (n = 14, 46.66%). The median duration of medication use in the denosumab group was 24 months (minimum: 6 months; maximum: 72 months). The median duration of medication use in the ZA group was 24 months (minimum: 12 months; maximum: 60 months). When comparing the groups regarding the risk of infection, denosumab was not associated with an increased risk of either a serious infection requiring hospitalisation (Hazard Ratio (HR): 0.37; 95% Confidence Interval (CI): 0.14–0.94) or an infection requiring outpatient treatment (HR: 0.29; 95% CI: 0.12–0.71). Conclusions: In conclusion, the combination of denosumab treatment with bDMARD or tsDMARD treatments is safe for short-term use. Full article