Search Results (688)

The IPCC has emphasised the increasing impacts of climate change across multiple sectors, including cultural heritage. In response, UNESCO launched the Policy Document on Climate Action for World Heritage in 2023, offering guidance on mitigation strategies for historic sites. Cultural heritage faces risks not only from sudden catastrophic events—such as floods, droughts, and wildfires—but also from the gradual deterioration of buildings and artefacts due to shifting environmental conditions. Climate change further affects the indoor microclimate of heritage sites, including museums, archives, and libraries, which are critical to the long-term preservation of cultural assets. Heritage, including heritage buildings and both tangible and intangible heritages, are subject to changes; therefore, their conservation should be assessed to identify sustainable approaches. This study investigates how climate change and microclimate alterations impact the conservation of historic buildings without modern climate control, using the Malatestiana Library—a UNESCO Memory of the World site—as a case study. The library has preserved a remarkably stable indoor environment for centuries, without the introduction of heating, cooling, or major restorations. A monitoring campaign during the summer of 2024 assessed the effects of extreme heat events on the library’s microclimate, comparing two internal spaces to examine the attic’s role in mitigating thermal stress. Data from the 2024 heatwave are also compared with similar data collected in 2013. Results show a marked shift toward a more tropical indoor climate over the past decade, signalling new threats to the preservation of historic materials. These findings highlight the urgent need for adaptive conservation strategies to address the evolving challenges posed by climate change. Full article

Background: In malignant pleural mesothelioma, epithelioid histology is traditionally considered a favorable prognostic marker. However, it remains clinically undetermined whether the intensity of an oncogenic insult can disrupt this link. Radiation-induced cases serve as an unconfounded biological model to dissect such trajectories masked by asbestos confounding. Methods: We performed an Individual Patient Data (IPD) synthesis of 20 strictly asbestos-unexposed human cases, applying clinically established dose stratification (intermediate: 20–45 Gy vs. high: >45 Gy). To confirm the observed pattern, we examined data from 829 dogs in the Colorado State University (CSU) Beagle Study. Results: In the intermediate-dose group (n = 13), a significant positive correlation persisted between age at radiotherapy and the latent period (ρ = 0.567, p = 0.043). Conversely, high-dose exposure (>45 Gy) showed a disruption of this age-dependent pattern, with a trend toward inverse correlation (ρ = −0.754, p = 0.084). Interaction analysis confirmed a statistically significant divergence between these dose-dependent trends (p = 0.005). The CSU Beagle Study (n = 829) demonstrated the physical basis of this phenomenon: in the canine model, high-dose exposure (≥0.74 Gy) triggered a “Step-Jump” in cumulative incidence (30.4% at 0.5 years), indicating instantaneous carcinogenic onset distinct from cumulative biological aging. Conclusions: This kinetic divergence points to a “Diagnostic Trap.” We propose a ‘Single- to Double-Brake’ framework where intermediate doses preserve age-dependent progression, whereas high doses likely trigger catastrophic genomic failure (chromothripsis) that bypasses the time required for morphological dedifferentiation. Consequently, morphologically indolent epithelioid tumors in high-dose survivors may harbor aggressive molecular profiles not predicted by histology alone, necessitating risk-stratified precision surveillance. Full article

Floods are among the most catastrophic natural disasters, causing severe impact on human lives and ecosystems. The proposed methodology integrates Geographic Information Systems, 2D hydraulic modeling, and deep learning techniques to develop a computational simulation approach for flood extent prediction and was implemented in the Enipeas River basin, located within the Thessalia River Basin District, Greece. Hydrological analysis was performed using the HEC-HMS software (version 4.12), while hydraulic simulations were conducted with HEC-RAS 2D. The hydraulic modeling produced synthetic flood scenarios for a 1000-year return period, generating spatially distributed outputs of flood extents. The deep learning algorithm was based on a U-Net (CNN) architecture. The model was trained using multi-channel raster tiles, including open access geospatial data such as Digital Elevation Model, slope, flow direction, stream centerline, land use, and simulated flood extents. Model validation was carried out in two independent domains (TS1 and TS2) located within the same river basin. Model outputs are adequately compared with both 2D hydraulic simulations and official Flood Risk Management Plan maps, and the comparison indicates close spatial and quantitative agreement, with flood extent area differences below 8%. Based on the results, the proposed methodology presents a potential and efficient tool for rapid flood risk mapping. Full article

Catastrophic mass flows originating from the high mountain cryosphere often cause cascading hazards. With increasing human activities in the alpine region and the sensitivity of the cryosphere to climate warming, cryospheric hazards are becoming more frequent in the mountain regions. Monitoring the evolution and impact of the glaciers and ice-rock avalanches and hazard consequences in the mountain regions is crucial to understand nature and drivers of mass flow process in order to prevent and mitigate potential hazard risks. In this study, the glacier and ice-rock avalanches that occurred in the Tibetan Plateau (TP) were investigated based on the Sentinel-2 satellite data and in situ observations, and the main driving forces and impacts on the regional environment, landscape, and geomorphological conditions were also analyzed. The results showed that the avalanche deposit of Arutso glacier No. 53 completely melted away in 2 years, while the deposit of Arutso glacier No. 50 melted in 7 years. Four large-scale ice-rock avalanches in the Sedongpu basin not only had significant impacts on the river flow, landscape, and geomorphologic shape in the basin, but also caused serious disasters in the region and beyond. These glacier and ice-rock avalanches were caused by temperature anomaly, heavy precipitation, climate warming, and seismic activity, etc., which act on the specific glacier properties in the high mountain regions. The study highlights scientific advances should support and benefit the remote and vulnerable mountain communities to make mountain regions safer. Full article

Background and Clinical Significance: Paroxysmal extreme pain disorder (PEPD) is an extremely rare autosomal dominant sodium channelopathy caused by SCN9A gain-of-function variants. It is characterized by infantile-onset excruciating paroxysmal pain, typically in rectal, ocular, or mandibular regions, triggered by innocuous stimuli and accompanied by autonomic flares. Carbamazepine is dramatically effective in most reported cases. To date, only two genetically confirmed cases have been documented in Chinese patients, and fewer than 20 disease-causing variants are reported worldwide. We report the third Chinese case harboring a novel likely pathogenic SCN9A variant (p.Leu1623Gln), notable for its unusually severe, progressive, and carbamazepine-refractory phenotype, as well as life-threatening psychiatric sequelae, highlighting phenotypic heterogeneity and the devastating impact when standard therapy fails. Case Presentation: A Chinese male proband with positive family history presented with lifelong trigger-induced catastrophic burning and tearing pain in the perineum and lower limbs, associated with erythema, swelling, and occasional non-epileptic seizures. Attacks worsened with age despite escalating polypharmacy, including high-dose opioids, benzodiazepines, topical lidocaine and carbamazepine. Both the proband and his father developed profound psychosocial sequelae including severe depression and suicidal attempts. Next-generation sequencing in the proband revealed a novel heterozygous likely pathogenic variant NM_001365536.1 (SCN9A): c.4868T>A p.(Leu1623Gln). Conclusions: This third reported ethnic Chinese PEPD case expands the genotypic and phenotypic spectrum of SCN9A-related channelopathies, demonstrating that some variants can produce carbamazepine-refractory, progressive, and profoundly disabling disease with high suicidality risk. Early genetic diagnosis is critical in family planning and cascade testing, and has the potential in guiding targeted therapy that is under active research. Full article

Gears, as critical components of rotating machinery, are prone to wear and fracture due to their complex structural dynamics and harsh operating conditions, leading to catastrophic failures, economic losses, and safety risks. AE technology enables real-time fault diagnosis by capturing stress wave emissions from material defects with high sensitivity. However, mechanical background noise significantly corrupts AE signals, while optimal selection of gear health indicators remains challenging, critically impacting fault feature extraction accuracy. This study develops an adaptive feature extraction method for fault diagnosis using AE. Through gear fault simulation experiments, VMD analyzes mode number and penalty factor effects on signal decomposition. Correlation coefficient-based reconstruction optimization is implemented. For feature selection challenges, SVM-RFE enables adaptive parameter ranking. Finally, SVM with optimized kernel parameters achieves effective fault classification. Optimized VMD enhances signal decomposition, while SVM-RFE reduces feature dimensionality, addressing manual selection uncertainty and computational redundancy. Experimental results demonstrate superior accuracy in gear fault classification. This study proposes an AE-based adaptive feature extraction method with three innovations: (1) establishing VMD parameter–decomposition quality relationships; (2) developing an SVM-RFE feature selection framework; (3) achieving high-accuracy gear fault classification. The method provides a novel technical approach for rotating machinery diagnostics with significant engineering value. Full article

This paper proposes a novel methodology, based on machine learning and statistical models, for predicting hurricane-related losses to specific assets. Our approach uses three critical storm parameters typically tracked by meteorological agencies: maximum wind speed, minimum sea level pressure, and radius of maximum wind. The system categorizes potential damage events into three insurance-relevant classes: non-payable, partially payable, and fully payable. Three triggers for final payouts were designed: hybrid framework, standalone regression, and standalone non-linear regression. The hybrid framework combines two classification models and a non-linear regression model in an ensemble specifically designed to minimize the absolute differences between predicted and actual payouts (Total Absolute Error or TAE), addressing highly imbalanced and partially compensable events. Although this complex approach may not be suitable for all current contracts due to limited interpretability, it provides an approximate lower bound for the minimization of the absolute error. The standalone non-linear regression model is structurally simpler, yet it likewise offers limited transparency. This hybrid framework is not intended for direct deployment in parametric insurance contracts, but rather serves as a benchmarking and research tool to quantify the achievable reduction in basis risk under highly imbalanced conditions. The standalone linear regression provides an interpretable linear regression model optimized for feature selection and interaction terms, enabling direct deployment in parametric insurance contracts while maintaining transparency. These three approaches allow analysis of the trade-off between model complexity, predictive performance, and interpretability. The three approaches are compared using comprehensive hurricane simulation data from an industry-standard catastrophe model. The methodology is particularly valuable for parametric insurance applications, where rapid assessment and claims settlement are essential. Full article

Transmission tower guy wires are critical flexible tension members ensuring the stability and safe operation of overhead power transmission networks. However, these components are vulnerable to external impacts from falling rocks, ice masses, and other natural hazards, which can cause excessive deformation, anchorage loosening, and catastrophic failure. Current design standards primarily consider static loads, lacking comprehensive models for predicting dynamic impact responses. This study presents a theoretical model for predicting the peak impact response of guy wires by modeling the impact process as a point mass impacting a nonlinear spring system. Using an energy-based elastic potential method combined with cable theory, analytical solutions for axial force, displacement, and peak impact force are derived. Newton–Cotes numerical integration solves the implicit function to obtain closed-form solutions for efficient prediction. Validated through finite element simulations, deviations of peak displacement, peak impact force, and peak axial force between theoretical and numerical results are within ±4%, ±18%, and ±4%, respectively. Using the validated model, parametric studies show that increasing the inclination angle from 15° to 55° slightly reduces peak displacement by 2–4%, impact force by 1–13%, and axial force by 1–10%. Higher prestress (100–300 MPa) decreases displacement and impact force but increases axial force. Longer lengths (15–55 m) cause linear displacement growth and nonlinear force reduction. Impacts near anchorage points help control displacement risks, and impact velocity generally has a more significant influence on response characteristics than impactor mass. This model provides a scientific basis for impact-resistant design of power grid infrastructure and guidance for optimizing de-icing strategies, enhancing transmission system safety and reliability. Full article

This study investigates five catastrophic historical floods of the Tripero stream, a small tributary of the Guadiana River that flows through Villafranca de los Barros (Extremadura, Spain), occurring between 1865 and 1952. Despite their devastating impacts on the local population and infrastructure, these events have received little scientific attention. By combining historical documentary evidence with meteorological reanalysis data from the Twentieth Century Reanalysis (20CRv3), this research reconstructs the circumstances and atmospheric mechanisms associated with each event. The results reveal a notable diversity of synoptic configurations, reflecting both seasonal variability and the distinct meteorological origins of the floods. The 1865 and 1876 events were associated with large-scale Atlantic disturbances—the former linked to a cut-off low and moisture transport resembling an atmospheric river, and the latter to a strongly negative North Atlantic Oscillation (NAO) phase and other atmospheric river, producing widespread flooding across southwestern Iberia. In contrast, the floods of 1903, 1949, and 1952 were triggered by intense convective activity, typical of late spring and summer thunderstorms, fueled by local moisture and instability. The combination of historical sources and modern reanalysis provides valuable insights into the climatological context of extreme hydrometeorological events in small Mediterranean basins, contributing to improved understanding of local flood risks in historically understudied regions. Full article

On 19 December 2015 and 21 February 2017, Longyearbyen was hit by major avalanches from the steep hillside of the mountain Sukkertoppen. In this article, we specifically consider the 2015 avalanche that destroyed eleven houses and buried nine people; seven were located and rescued, while two died. We describe the meteorological conditions leading up to the avalanche, the rescue operation, the media coverage, and the immediate aftermath of the catastrophe. Both events came as a result of warming, strong easterly winds, and drifting snow, with the December 2015 event being the most extreme. The 2017 avalanche damaged two houses, but no people were hurt. We analyse the catastrophes in relation to the knowledge of the risks and impacts of avalanches in Longyearbyen, as provided through field-based student courses at the University Centre of Svalbard (UNIS). To protect against further avalanche accidents, parts of Longyearbyen have been restructured, and physical barriers against avalanches have been installed on the hillside of Sukkertoppen. Now there are snow drift fences to reduce snow accumulation in the release areas, avalanche protection fences mounted in the hillside, and a large wall at the foot of the mountain to catch avalanche debris in the future. In hindsight, the accidents have contributed to an increased national awareness of the danger of severe weather events. Full article

Despite significant advances in the medical sciences, out-of-pocket (OOP) healthcare costs have remained a concern, especially for lower-middle-class and poor people. The current study aims to investigate the critical factors that notably contribute to catastrophic healthcare expenses (CHCEs). To this end, the ongoing research is conducted through two phases. The first phase aims to identify the key determinants of CHCEs through expert and household evaluations. A multi-criteria decision analysis (MCDA) framework using the FullEX method is developed to analyze expert and household opinions. In the second phase, the experts investigate the hierarchical relationships among key determinants. Interpretive structural modeling (ISM) and MICMAC analysis are carried out to examine the structural relationships among the determinants. The findings of the FullEX analysis reveal that experts and households are in consensus. It is found that low-income level, number of dependable members, frequent birth rate, high child mortality, and lack of job security and risk pooling mechanisms notably contribute to the higher CHCEs. The ISM analysis indicates the strong driving power of income, education, and job security, leading to disparities in rural economic conditions, reflecting the need for holistic development. The MICMAC analysis confirms the hierarchical relationships among the key determinants of CHCEs. The findings necessitate formulating an inclusive strategy to reduce financial distress and improve the healthcare outlook for rural households, leading to sustainable development. Full article

Against the backdrop of intensifying global climate change and human activities, the increasing frequency and evolution of major wildfire events pose severe challenges to global disaster prevention and mitigation systems. Systematically understanding their disaster characteristics, spatiotemporal patterns, and societal response efficacy is an urgent scientific requirement for formulating effective coping strategies. This study constructed a comprehensive database covering 137 major global wildfire events from 2018 to 2024, with data sourced from GFED, EM-DAT, and official national reports. Utilizing a synthesis of methods including descriptive statistics, spatiotemporal clustering analysis, K-means pattern recognition, and non-parametric tests, a multi-dimensional quantitative analysis was conducted on disaster characteristics, evolutionary trends, casualty patterns, and policy effectiveness. Despite potential reporting biases and heterogeneous data standards across countries, the analysis reveals the following: (1) All key wildfire metrics (e.g., burned area, casualties, evacuation scale) exhibited extreme right-skewed distributions, indicating that a minority of catastrophic events dominate the overall risk profile; (2) Global wildfire hotspots demonstrated dynamic expansion, spreading from traditional regions in North America and Australia to emerging areas such as Mediterranean Europe, Chile, and the Russian Far East, forming three significant spatiotemporal clusters; (3) Four distinct casualty patterns were identified: “High-Lethality”, “Large-Scale Evacuation”, “Routine-Control”, and “Ecological-Destruction”, revealing the differentiated formation mechanisms under various disaster scenarios; (4) A substantial gap of nearly 65 times in emergency evacuation efficiency—defined as the ratio of evacuated individuals to total casualties—was observed between developed and developing countries, highlighting a significant “development gap” in emergency management capabilities. This study finds evidence of increasing extremization, expansion, and polarization in global wildfire risk within the 2018–2024 event sample. The conclusions emphasize that future risk management must shift from addressing “normal” events to prioritizing preparedness for “catastrophic” scenarios and adopt refined strategies based on casualty patterns. Simultaneously, the international community needs to focus on bridging the emergency response capability gap between nations to collectively build a more resilient global wildfire governance system. Full article

In mass-casualty incidents, emergency responders require access to accurate and timely information to support informed decision-making and ensure the efficient allocation of resources. This article presents a dataset derived from a case study conducted in Mexico City (CDMX) based on the earthquake of 19 September 2017. The dataset presents hypothetical scenarios involving multiple demand points and large numbers of victims, making it suitable for analysis using optimization techniques. It integrates voluntary collaborative geographic information, open government data sources, and historical records, and details the data collection, cleaning, and preprocessing stages. The accompanying Python 3 source code enables users to update the original data for consistent analysis and processing. Researchers can adapt this dataset to other cities with similar risk characteristics, such as Santiago (Chile), Los Angeles (USA), or Tokyo (Japan), and extend it to other types of catastrophic events, including floods, landslides, or epidemics, to support emergency response and resource allocation planning. Full article

Climate change is advancing, sea levels are rising, and peak river discharges are increasing. Accelerated sea level rise (SLR) may pose a significant threat to the long-term habitability of the Netherlands. In the short term, further reinforcement of flood defenses is required. However, the key long-term question is which adaptation strategy will most effectively manage flood risk in the Netherlands. As part of the SLR Knowledge Programme, research was conducted on various long-term strategies, focusing on the feasibility of three approaches: Protect, Advance, and Accommodate. The Protect and Advance strategies aim to reduce flood risk primarily through the prevention of flooding. The Accommodate strategy, particularly in its more extreme form, emphasizes Managed Retreat, following the precautionary principle, or seeks to mitigate flood consequences rather than invest in Prevention. This study examined the economic implications of two opposing cornerstone strategies, Protect and Managed Retreat, as well as hybrid strategies that integrate elements of both, across different sea level rise scenarios. Additionally, the study includes a forward-looking assessment of the potential impacts on the financial sector, with particular attention to catastrophe insurance and capital requirements aimed at mitigating default risk. The findings indicate that a Managed Retreat strategy represents a last-resort option and cannot be implemented effectively without concurrent protective measures. Furthermore, the annual flood risk is only marginally reduced under the Accommodate strategy, even when combined with protective interventions, while its associated costs significantly exceed those of the Protect strategy. A combined approach integrating protection with localized Accommodate measures that support multi-functional land use, such as nature-based solutions and water storage, appears to offer a more promising strategy, if these values cover the costs. The results can be used to evaluate the effectiveness of possible adaptation strategies to sea level rise. Full article

Background: Despite the apparent importance of global catastrophe risks (GCRs), human society has invested relatively little to reduce them. One possible reason is that we do not understand the significance of reducing GCRs, especially when measured in the monetary terms that we typically use to make decisions. Consequently, we cannot compare them to other issues that influence our decision making and well-being. Purpose: In this study, we quantified the benefits of reducing all non-natural GCRs to highlight their importance. Method: We used a probabilistic model for simulation. Due to limited information, we introduced concepts and assumptions to aid the calculations, such as steady-state economics and sensitivity analyses. In addition, we converted expert opinions to help us focus on a narrower range of risk levels. Results: Within a considerably plausible range of the GCR, we found the following: 1. The benefits of halving the overall non-natural GCR over the next 100 years are substantial. 2. The expected human survival years are sensitive to the mitigation effort but robust to the horizon length. 3. The higher the population growth rate, the larger the expected life years saved. 4. The expected monetary benefits are positively related to the GWP per capita growth rate, mitigation period, and magnitude of natural GCRs but are negatively related to the discounting rate. Significance: The human species is actually facing multiple GCRs simultaneously. In the literature, there is still a gap in quantifying the benefits of reducing all non-natural GCRs/ERs in the coming century while accounting for the very long run on a million-year scale. This article fills such a gap, and the results may serve as a reference for global policymaking to handle this global public issue. Full article