Search Results (236)

Rapid and comprehensive assessment of building damage caused by earthquakes is essential for effective emergency response and rescue efforts in the immediate aftermath. Advanced technologies, including real-time simulations, remote sensing, and multi-sensor systems, can effectively enhance situational awareness and structural damage evaluations. However, most existing methods rely on isolated time snapshots, and few studies have systematically explored the continuous, time-scaled integration and update of building damage estimates from multiple data sources. This study proposes a stepwise framework that continuously updates time-scaled, single-damage estimation outputs using the best available multi-sensor data for estimating earthquake-induced building damage. We demonstrated the framework using the 2024 Noto Peninsula Earthquake as a case study and incorporated official damage reports from the Ishikawa Prefectural Government, real-time earthquake building damage estimation (REBDE) data, and satellite-based damage estimation data (ALOS-2-building damage estimation (BDE)). By integrating the REBDE and ALOS-2-BDE datasets, we created a composite damage estimation product (integrated-BDE). These datasets were statistically validated against official damage records. Our framework showed significant improvements in accuracy, as demonstrated by the mean absolute percentage error, when the datasets were integrated and updated over time: 177.2% for REBDE, 58.1% for ALOS-2-BDE, and 25.0% for integrated-BDE. Finally, for stepwise damage estimation, we proposed a methodological framework that incorporates social media content to further confirm the accuracy of damage assessments. Potential supplementary datasets, including data from Internet of Things-enabled home appliances, real-time traffic data, very-high-resolution optical imagery, and structural health monitoring systems, can also be integrated to improve accuracy. The proposed framework is expected to improve the timeliness and accuracy of building damage assessments, foster shared understanding of disaster impacts across stakeholders, and support more effective emergency response planning, resource allocation, and decision-making in the early stages of disaster management in the future, particularly when comprehensive official damage reports are unavailable. Full article

With increasing urban economic development, some industrial parks and residential areas are being situated adjacent to each other, creating a potential risk of soil and groundwater contamination from the wastewater and solid waste produced by enterprises. This contamination poses a threat to the health of nearby residents. Currently, groundwater pollution prevention and control zoning in China primarily targets groundwater environmental pollution risks and does not consider the health risks associated with groundwater exposure in industry–city integration areas. Therefore, a scientific assessment of environmental risks in industry–city integration areas is essential for effectively managing groundwater pollution. This study focuses on the high frequency and rapid pace of human activities in industry–city integration areas. It combines health risk assessment and groundwater pollution simulation results with traditional groundwater pollution control classification outcomes to develop a groundwater pollution risk zoning framework specifically suited to these integrated areas. Using this framework, we systematically assessed groundwater pollution risks in a representative industry–city integration area in the middle reaches of the Yangtze River in China and delineated groundwater pollution risk zones to provide a scientific basis for local groundwater environmental management. The assessment results indicate that the total area of groundwater pollution risk control zones is 30.37 km², accounting for 19.06% of the total study area. The first-level control zone covers 5.38 km² (3.38% of the total area), while the secondary control zone spans 24.99 km² (15.68% of the total area). The first-level control zone is concentrated within industrial clusters, whereas the secondary control zone is widely distributed throughout the region. In comparison to traditional assessment methods, the zoning results derived from this study are more suitable for industry–city integration areas. This study also provides groundwater management recommendations for such areas, offering valuable insights for groundwater control in integrated industrial–residential zones. Full article

International efforts are underway to implement carbon neutrality policies in rapidly changing climate conditions. This situation has strongly demanded the discovery of novel carbon sinks. The Salix genus has attracted attention as a promising carbon sink owing to its rapid growth and efficient use as a biofuel in short-rotation cultivation. The present study aims to derive an allometric equation and conduct stem analysis as fundamental tools for estimating net primary productivity (NPP) in Salix pierotii Miq. stand, which is increasingly acknowledged as an important emerging carbon sink. The allometric equations derived showed a high explanatory rate and fitness (R² ranged from 0.74 to 0.99). The allometric equations between DBH and stem volume and biomass derived in the process of stem analysis also showed a high explanatory rate and fitness (R² ranged from 0.87 to 0.94). The NPPs calculated based on the allometric equation derived and stem analysis were 11.87 tonC∙ha⁻¹∙yr⁻¹ and 15.70 tonC∙ha⁻¹∙yr⁻¹, respectively. These results show that the S. pierotii community, recognized as the representative riparian vegetation, could play an important role as a carbon sink. In this context, an assessment of the carbon absorption capacity of riparian vegetation such as willow communities could contribute significantly to achieving carbon neutrality goals. Full article

External Human–Machine Interfaces (eHMIs) enhance pedestrian safety in interactions with autonomous vehicles (AVs) by signaling crossing risk based on time-to-arrival (TTA), categorized as low, medium, or high. This study compared five eHMI configurations (single-level low, medium, high; two-level low-medium, medium-high) against a three-level (low-medium-high) configuration to assess their impact on pedestrians’ crossing decisions, mental workload (MW), and situation awareness (SA) in vehicle platoon scenarios under full and partial eHMI penetration. In a video-based experiment with 24 participants, crossing decisions were evaluated via temporal gap selection, MW via P300 event-related potentials in an auditory oddball task, and SA via the Situation Awareness Rating Technique. The three-level configuration outperformed single-level medium, single-level high, two-level low-medium, and two-level medium-high in gap acceptance, promoting safer decisions by rejecting smaller gaps and accepting larger ones, and exhibited lower MW than the two-level medium-high configuration under partial penetration. No SA differences were observed. Although the three-level configuration was generally appreciated, future research should optimize presentation to mitigate issues from rapid signal changes. Notably, the single-level low configuration showed comparable performance, suggesting a simpler alternative for real-world eHMI deployment. Full article

Rapid visual screening has been used worldwide as the first approach to evaluate the seismic vulnerability of civil structures in a specific area, in order to prioritize buildings based on the need for upgrading or retrofitting. In this work, a novel mobile application tool for the rapid visual screening of reinforced concrete buildings is presented and discussed. The herein suggested “SeismicV” tool performs a pre-seismic visual screening based on the Japanese guidelines for the seismic evaluation of existing RC buildings. A preliminary seismic vulnerability assessment of a complex modern building situated in the capital of Brazil, Brasilia, was carried out using this mobile app. The data were collected from in situ and based on some data from plants and documents. The SeismicV tool consists of an effective, user-friendly, and straightforward mobile application. Since the methodology is based on a performance score that is compared to the seismic demand, this application design allows for the knowledge of intermediate indices at each step of the evaluation, including dominant variables such as structural irregularity, building age, ground index, and usage index. Although the application was conceived and applied to heritage buildings in the early stages, it can be employed for other complex structures. The findings highlight that utilizing SeismicV to assess the seismic vulnerability of complex buildings through the rapid visual screening method offers significant benefits, including faster evaluations, increased accuracy, and improved accessibility for field assessments. Full article

This study investigates the complex dynamics of new-type urbanization in resource-based county-level cities, using Wuan City in Hebei Province, China, as a representative case. As China pursues a high-quality development agenda, cities historically dependent on resource extraction face profound challenges in achieving sustainable and inclusive urban growth. This research employs a multi-method approach—including Theil index analysis, industrial shift-share analysis, a Cobb–Douglas production function model, and a composite urbanization index—to quantitatively diagnose the constraints on Wuan’s development and assess its transformation efforts. Our empirical results reveal a multifaceted situation: while the urban–rural income gap has narrowed, rural income streams remain fragile. The shift-share analysis indicates that although Wuan’s traditional industries have regained competitiveness, the city’s economic structure is still burdened by a persistent negative structural component, hindering diversification. Furthermore, the economy exhibits characteristics of a labor-intensive growth model with inefficient capital deployment. These underlying issues are reflected in a comprehensive urbanization index that, after a period of rapid growth, has recently stagnated, signaling the exhaustion of the city’s traditional development mode. In response, Wuan attempts an “industrial transformation-driven new-type urbanization” path. This study details the three core strategies being implemented: (1) incremental population urbanization through development at the urban fringe and in industrial zones; (2) in situ urbanization of the existing rural population; and (3) the cultivation of specialized “characteristic small towns” to create new, diversified economic nodes. The findings from Wuan offer critical, actionable lessons for other resource-dependent regions. The case demonstrates that successful urban transformation requires not only industrial upgrading but also integrated, spatially aware planning and robust institutional support. We conclude that while Wuan’s model provides a valuable reference, its strategies must be adapted to local contexts, emphasizing the universal importance of institutional innovation, human capital investment, and a people-centered approach to achieving resilient and high-quality urbanization. Full article

The rapid spread of artificial intelligence (AI) in education means that students need to master both AI literacy and personal agency. This study situates a sample of 425 Slovenian secondary technical students within a three-tier framework that maps psychological empowerment onto AI literacy outcomes within a cultural–historical activity system. The agency competence assessments yielded four profiles of student agency, ranging from fully empowered to largely disempowered. The cluster membership explained significant additional variance in AI literacy scores, supporting the additive empowerment model in an AI-rich vocational education and training context. The predictive modeling revealed that while self-efficacy, mastery-oriented motivations, and metacognitive self-regulation contributed uniquely—though small—to improving AI literacy, an unexpectedly negative relationship was identified for internal locus of control and for behavioral self-regulation focused narrowly on routines, with no significant impact observed for grit-like perseverance. These findings underscore the importance of fostering reflective, mastery-based, and self-evaluative learning dispositions over inflexible or solely routine-driven strategies in the development of AI literacy. Addressing these nuanced determinants may also be vital in narrowing AI literacy gaps observed between diverse disciplinary cohorts, as supported by recent multi-dimensional literacy frameworks and disciplinary pathway analyses. Embedding autonomy-supportive, mastery-oriented, student-centered projects and explicit metacognitive training into AI curricula could shift control inward and benefit students with low skills, helping to forge an agency-driven pathway to higher levels of AI literacy among high school students. The most striking and unexpected finding of this study is that students with a strong sense of competence—manifested as high self-efficacy—can achieve foundational AI literacy levels equivalent to those possessing broader, more holistic agentic profiles, suggesting that competence alone may be sufficient for acquiring essential AI knowledge. This challenges prevailing models that emphasize a multidimensional approach to agency and has significant implications for designing targeted interventions and curricula to rapidly build AI literacy in diverse learner populations. Full article

Effective post-disaster damage assessment is crucial for guiding emergency response and resource allocation. This study introduces DamageScope, an integrated deep learning framework designed to detect and classify building damage levels from post-disaster satellite imagery. The proposed system leverages a convolutional neural network trained exclusively on post-event data to segment building footprints and assign them to one of four standardized damage categories: no damage, minor damage, major damage, and destroyed. The model achieves an average F1 score of 0.598 across all damage classes on the test dataset. To support geospatial analysis, the framework extracts the coordinates of damaged structures using embedded metadata, enabling rapid and precise mapping. These results are subsequently visualized through an interactive, web-based platform that facilitates spatial exploration of damage severity. By integrating classification, geolocation, and visualization, DamageScope provides a scalable and operationally relevant tool for disaster management agencies seeking to enhance situational awareness and expedite post-disaster decision making. Full article

Introduction: Psychomotor agitation represents a complex medical emergency, particularly challenging in prehospital settings. Since March 2020, the incidence of psychomotor agitation has significantly increased. Rationale: Emergency Medical Services (EMS) frequently serve as the first point of contact, bearing the critical responsibility of effectively managing these situations. Objective: This was to assess the feasibility and suitability of the intranasal route for administering pharmacological therapy in the prehospital management of patients experiencing psychomotor agitation. Materials and Methods: An integrative review of the literature was conducted to evaluate the use of the intranasal route for drug administration in patients with psychomotor agitation in prehospital settings. The review was carried out between September 2022 and July 2024. A total of 454 articles were identified, 15 of which met the inclusion criteria. These were supplemented by an additional 10 records, resulting in the analysis of 25 studies. Results: Seventeen studies outlined protocols for managing agitated patients, five described the correct technique for intranasal drug administration, and eleven identified drugs suitable for this route. Conclusions: The intranasal route is a safe, rapid, and accessible method for the pharmacological containment of agitated patients in prehospital settings, particularly for individuals who are uncooperative. Full article

Ubiquitous and accelerating mass loss from the Greenland Ice Sheet (GrIS) has been widely reported in recent scientific studies, implying rapid changes in the Arctic cryosphere. However, while numerous studies provide accounts of glacial mass loss and consequent sea level change, a qualitative assessment of the implications is conspicuously absent. This scoping review addresses that gap by synthesizing the recent scientific literature related to cryospheric change in Greenland and its implications for key species and ecological processes; and highlights the necessity of understanding the bigger picture of how multiple ecological processes, abiotic-biotic assemblages, and cryosphere-human interactions with the environment are rapidly changing and pushing the Arctic into a possible no-analog scenario in recent geological times. It is also argued that this situation presents a novel challenge for planetary sustainability and warrants the identification of new research priorities that can generate a holistic understanding of the complexity of the Arctic cryosphere, interactions between biotic and abiotic components, and local lifeworlds—all of which are related to the well-being of the Earth itself. Full article

Background and Objectives: The introduction of portable ultrasound devices has transformed clinical practice in emergency medicine. Diagnostic accuracy and patient safety have been enhanced by point-of-care ultrasonography (POCUS), which has become a fundamental diagnostic and procedural tool. In addition to the standard clinical evaluation, POCUS provides quick patient assessments, allowing for the exclusion of life-threatening conditions and prognostication in different critical situations. Tissue Doppler imaging (TDI), as an advanced echocardiographic technique, offers additional quantitative data by measuring myocardial velocities, thereby improving the evaluation of systolic and diastolic ventricular function. The purpose of this review is to highlight the potential use of TDI in multiple acute and critical conditions. Materials and Methods: We conducted a narrative review of the main application topics for TDI. Results: TDI is an essential diagnostic and prognostic tool for acute coronary syndromes, assessing systolic or diastolic dysfunction, and etiological diagnosis of acute heart failure. It helps differentiate cardiogenic pulmonary edema from acute respiratory distress syndrome and identifies right ventricular systolic dysfunction in acute pulmonary embolism. TDI also facilitates distinctions between hypertension emergencies and urgencies and contributes to the stratification of atrial fibrillation reoccurrence risk. Furthermore, it aids in the differentiation of constrictive pericarditis from other restrictive cardiomyopathy patterns. In intensive care settings, TDI is particularly valuable during mechanical ventilation weaning, where elevated E/E’ values serve as a predictor of weaning failure. Due to its accessibility, rapid execution, and high reproducibility, it is suitable for longitudinal monitoring. Conclusions: TDI enhances the diagnostic precision, guides therapeutic strategies, and provides critical prognostic insights across a wide range of time-sensitive clinical scenarios, solidifying its role as an indispensable tool in modern emergency and critical care practice. Full article

Background/Objectives: Highly pathogenic coronaviruses (CoVs), including SARS-CoV, MERS-CoV, and SARS-CoV-2, continue to pose a significant threat to global public health. Therefore, this situation highlights the urgent need for effective broad-spectrum antiviral agents. Curcumin, a naturally occurring polyphenol known for its antiviral and anti-inflammatory properties, faces limitations such as poor bioavailability and rapid metabolic degradation, restricting its practical therapeutic application. Methods: To address these limitations, this study introduces a novel design strategy aimed at 42 new curcumin derivatives with improved pharmacokinetic profiles, specifically targeting the conserved coronavirus enzyme papain-like protease (PLpro). A comprehensive in silico evaluation was performed, including ADMET (Absorption, Distribution, Metabolism, Elimination, and Toxicity) analysis, molecular docking, molecular dynamics (MD) simulations, and Molecular Mechanics/Poisson-Boltzmann Surface Area (MM/PBSA) calculations. Results: Extensive pharmacokinetic and toxicological assessments (ADMET analyses) identified 19 derivatives exhibiting optimal drug-like characteristics according to Lipinski’s Rule of Five (Ro5). Molecular docking analyses demonstrated that these novel derivatives possess significantly enhanced binding affinities to PLpro enzymes from SARS-CoV, MERS-CoV, and SARS-CoV-2 compared to standard antiviral agents and natural curcumin. Further validation through MD simulations and MM/PBSA calculations confirmed the structural stability and robust interactions of the most promising derivatives within the SARS-CoV PLpro active site. Conclusions: The results of this study provide essential structural and functional insights, reinforcing the potential of these newly developed curcumin derivatives as potent, broad-spectrum antiviral agents effective against current and future coronavirus threats. Full article

The rapid advancement of computing power, combined with the ability to collect vast amounts of data, has unlocked new possibilities for industrial applications. While traditional time–domain industrial signals generally do not allow for direct stability assessment or the detection of abnormal situations, alternative representations can reveal hidden patterns. This paper introduces time-shifted maps (TSMs) as a novel method for analyzing industrial data—an approach that is not yet widely adopted in the field. Unlike contemporary machine learning techniques, TSM relies on a simple and interpretable algorithm designed to process data from standard industrial automation systems. By creating clear, visual representations, TSM facilitates the monitoring and control of production process. Specifically, TSMs are constructed from time series data collected by an acceleration sensor mounted on a robot base. To evaluate the effectiveness of TSM, its results are compared with those obtained using classical signal processing methods, such as the fast Fourier transform (FFT) and wavelet transform. Additionally, TSMs are classified using computed correlation dimensions and entropy measures. To further validate the method, we numerically simulate three distinct anomalous scenarios and present their corresponding TSM-based graphical representations. Full article

Water, often described as the elixir of life, is a critical resource that sustains life on Earth. The acute water scarcity in the major basins of the Arabian Peninsula has been further aggravated by rapid population growth, urbanization, and the impacts of climate change. This situation underscores the urgent need for a comprehensive analysis of the region’s morphometric characteristics. Such an analysis is essential for informed decision-making in water resource management, infrastructure development, and conservation efforts. This study provides a foundational basis for implementing sustainable water management strategies and preserving ecological systems by deepening the understanding of the unique hydrological processes within the Arabian Peninsula. Additionally, this research offers valuable insights to policymakers for developing effective flood mitigation strategies by identifying vulnerable areas. The study focuses on an extensive investigation and assessment of morphometric parameters in the primary basins of the Arabian Peninsula, emphasizing their critical role in addressing water scarcity and promoting sustainable water management practices. The findings reveal that the Arabian Peninsula comprises 12 major basins, collectively forming a seventh-order drainage system and covering a total land area of 3.24 million km². Statistical analysis demonstrates a strong correlation between stream order and cumulative stream length, as well as a negative correlation between stream order and stream number (R² = 99%). Further analysis indicates that many of these basins exhibit a high bifurcation ratio, suggesting the presence of impermeable rocks and steep slopes. The hypsometric integral (HI) of the Peninsula is calculated to be 60%, with an erosion integral (EI) of 40%, indicating that the basin is in a mature stage of geomorphological development. Importantly, the region is characterized by a predominantly coarse drainage texture, limited infiltration, significant surface runoff, and steep slopes, all of which have critical implications for water resource management. Full article

In megacities, the rapid development of construction entails threats to the environment, in particular, to the health of urban residents. One of the main sources of danger is microscopic dust particles PM_2.5 and PM₁₀, resulting from construction projects that can seriously impair people’s health. To minimize these risks, it is necessary to actively implement control over the level of dust in the air and carry out scientific work to study the impact of construction on the environment. These measures should become mandatory aspects in the planning of modern cities, given that the degree of air pollution in large cities has already reached critical levels. In modern megacities, where development is intensive and, in some places, very dense, there is a key importance of environmental audit of territories intended for construction, for creating effective and safe development projects. The lack of adequate risk control during the construction stages can lead not only to emergencies, but also have a harmful impact on the natural environment. It is worth noting that environmental hazards can vary significantly depending on the unique characteristics of each specific construction site. As a result of an in-depth analysis of the ecological state of the region, which included an assessment of various levels of pollution and their impact on the health of residents, it was found that intensive construction in some areas of the city significantly worsens the ecological situation. In particular, it was found that the level of dust pollution in areas with active construction exceeds the regulatory indicators by two times, which indicates a serious environmental problem. These data highlight the need for targeted actions to improve air quality and reduce harmful air emissions. Thus, the study raises the alarm about the point-pattern housing development as a source of high environmental danger and underlines the development of strategies for air purification in the city. The PM₁₀ contamination level was 671.6 micrograms per cubic meter, while PM_2.5 was at 368.2 micrograms per cubic meter. These data indicate that the main cause of pollution is local dust exposure. Full article