Search Results (217)

Industrial systems operating under severe mission environment are frequently confronted with intricate failure behaviors arising from system internal degradation and extrinsic stresses, posing an elevating challenge to system survivability and mission reliability. Mission termination strategies are attracting increasing attention as an intuitive and effective means to mitigating catastrophic mission-induced risk. However, how to manage coupled risk arising from competing fault processes, particularly when these modes are interdependent, has been rarely reported in existing works. To bridge this gap, this study delves into a dynamic risk control policy for continuously degrading systems operating under a random shock environment, which yields competing and dependent fault processes. An optimal mission termination policy is developed to minimize risk-centered losses throughout the mission execution, whose optimization problem constitutes a finite-time Markov decision process. Some critical structural properties associated with the optimal policy are derived, and by leveraging these structures, the alerting threshold for implementing mission termination procedure is formally established. Alternative risk control policies are introduced for comparison, and experimental evaluations substantiate the superior model capacity in risk mitigation. Full article

The Pinus yunnanensis forest of southwestern China represents a unique and ecologically critical vegetation type, historically shaped by fire disturbances. To mitigate catastrophic wildfire risks, prescribed burning has been widely implemented as a management tool in these ecosystems. However, its effects on plant community structure and biodiversity remain insufficiently quantified. To investigate the specific changes in plant community characteristics caused by prescribed burning, this study was conducted in the Pinus yunnanensis forest in Zhaobi Hill, Xinping county. Our results revealed that prescribed burning induced differential effects on understory communities while exerting negligible effects on canopy tree composition. In the shrub layer, the number of shrub species decreased from 26 to 20, accompanied by a complete extirpation of arboreal saplings. Dominance hierarchies shifted markedly, transitioning from Lithocarpus mairei and Pinus yunnanensis regeneration cohorts in unburned plots to fire-adapted species Duhaldea cappa and Craibiodendron stellatum. Concomitantly, the average height of shrubs had a significant reduction in burning plots. Contrastingly, the number of herb species increased from 30 to 37 in burning plots, with non-significant alterations in abundance, height, and importance values. Prescribed burning significantly decreases the α species diversity of shrubs, but only has minimal effects on the α species diversity indices of herbs. Overall, prescribed burning appears to be the primary factor affecting the species diversity index of shrubs, while altitude, forest structure, and soil nutrient content exert greater influences on the species diversity index of the herbaceous layer. Prescribed burning was the dominant factor shaping the community structure and species diversity of the shrub layer, and the missing saplings of trees in the shrub layer might influence future forest succession in the long term. Full article

As a globally renowned alpine gorge region and seismically active zone, the eastern margin of the Qinghai–Tibet Plateau (QTP) is highly prone to landslide dam formation. Considering unstable landslide dams often pose catastrophic risks to downstream areas, current research on landslide dams along QTP primarily focuses on the breach mechanisms of unstable dams, while studies on the formation mechanisms of stable landslide dams—which can provide multiple benefits to downstream regions—remain limited. This paper selected the Conaxue Co landslide dam on the eastern margin of the QTP as one case example. Field investigation, sampling, numerical simulation, and comprehensive analysis were carried out to disclose its formation mechanisms. Field investigation shows that the Conaxue Co landslide dam was formed by a high-speed long-runout landslide blocking the river, with its structure exhibiting a typical inverse grading pattern characterized by coarse-grained rock overlying fine-grained layers. The inverse grading structure plays a critical role in the stability of the Conaxue Co landslide dam. On one hand, the coarse, hard rock boulders in the upper dam mitigate fluvial erosion of the lower fine-grained sediments. On the other hand, the fine-grained layer in the lower dam acts as a relatively impermeable aquitard, preventing seepage of dammed lake water. Additionally, the step-pool system formed in the spillway of the Conaxue Co landslide dam contributes to the protection of the dam structure by dissipating 68% of the river’s energy (energy dissipation rate η = 0.68). Understanding the formation mechanisms of the Conaxue Co landslide dam can provide critical insights into managing future landslide dams that may form in the QTP, both in emergency response and long-term strategies. Full article

Background: Medical clearance for competitive sports is vital to safeguarding athletes’ health, particularly in high-intensity disciplines like football. In Italy, fitness assessments follow stringent protocols set by the Commissione di Vigilanza per il controllo dell’Idoneità Sportiva (COCIS), with a strong focus on cardiovascular screening. The primary goal is to prevent sudden cardiac death (SCD), a rare but catastrophic event in athletes. Methods: This paper provides an in-depth narrative review of the 2023 COCIS guidelines, examining the cardiological screening process, required diagnostic tests, management of identified cardiovascular conditions, and the protocols’ role in reducing SCD risk. Results: Comparisons with international standards underscore the effectiveness of the Italian approach. Conclusions: The COCIS 2023 guidelines provide clear, evidence-based protocols for cardiovascular risk assessment, significantly enhancing athlete safety and reducing the incidence of SCD in high-intensity sports. Full article

This study presents the scientific and methodological foundation of Spain’s first national framework for the ethical management of community cat populations: the Action Plan for the Management of Community Cat Colonies (PACF), launched in 2025 under the mandate of Law 7/2023. This pioneering legislation introduces a standardized, nationwide obligation for trap–neuter–return (TNR)-based management of free-roaming cats, defined as animals living freely, territorially attached, and with limited socialization toward humans. The PACF aims to support municipalities in implementing this mandate through evidence-based strategies that integrate animal welfare, biodiversity protection, and public health objectives. Using standardized data submitted by 1128 municipalities (13.9% of Spain’s total), we estimated a baseline population of 1.81 million community cats distributed across 125,000 colonies. These data were stratified by municipal population size and applied to national census figures to generate a model-ready demographic structure. We then implemented a stochastic simulation using Vortex software to project long-term population dynamics over a 25-year horizon. The model integrated eight demographic–environmental scenarios defined by a combination of urban–rural classification and ecological reproductive potential based on photoperiod and winter temperature. Parameters included reproductive output, mortality, sterilization coverage, abandonment and adoption rates, stochastic catastrophic events, and territorial carrying capacity. Under current sterilization rates (~20%), our projections indicate that Spain’s community cat population could surpass 5 million individuals by 2050, saturating ecological and social thresholds within a decade. In contrast, a differentiated sterilization strategy aligned with territorial reproductive intensity (50% in most areas, 60–70% in high-pressure zones) achieves population stabilization by 2030 at approximately 1.5 million cats, followed by a gradual long-term decline. This scenario prioritizes feasibility while substantially reducing reproductive output, particularly in rural and high-intensity contexts. The PACF combines stratified demographic modeling with spatial sensitivity, offering a flexible framework adaptable to local conditions. It incorporates One Health principles and introduces tools for adaptive management, including digital monitoring platforms and standardized welfare protocols. While ecological impacts were not directly assessed, the proposed demographic stabilization is designed to mitigate population-driven risks to biodiversity and public health without relying on lethal control. By integrating legal mandates, stratified modeling, and realistic intervention goals, this study outlines a replicable and scalable framework for coordinated action across administrative levels. It exemplifies how national policy can be operationalized through data-driven, territorially sensitive planning tools. The findings support the strategic deployment of TNR-based programs across diverse municipal contexts, providing a model for other countries seeking to align animal welfare policy with ecological planning under a multi-level governance perspective. Full article

Minimally invasive cosmetic procedures, such as dermal fillers, botulinum toxin injections, autologous fat grafting, intense pulsed light (IPL) treatments, and platelet-rich plasma (PRP) treatments, are increasingly popular worldwide due to their convenience and aesthetic benefits. While generally considered safe, these procedures can result in rare but serious ophthalmological complications. The most catastrophic adverse events include central retinal artery occlusion and ischemic optic neuropathy, which may lead to irreversible vision loss. Other complications include diplopia, ptosis, dry eye, and orbital cellulitis, with varying degrees of severity and reversibility. Awareness of potential ocular risks, appropriate patient selection, and adherence to safe injection techniques are crucial for preventing complications. This narrative review summarizes the incidence, mechanisms, clinical features, risk factors, diagnostic approaches, and management strategies of ocular complications associated with aesthetic medical procedures. A narrative literature review was conducted, emphasizing data from clinical studies, case series, and expert consensus published between 2015 and 2025. Special attention is given to anatomical danger zones, the pathophysiological pathways of filler embolization, and the roles of hyaluronidase and hyperbaric oxygen therapy in acute management. Although many complications are self-limited or reversible, prompt recognition and intervention are critical to prevent permanent sequelae. The increasing prevalence of these procedures demands enhanced education, informed consent, and interdisciplinary collaboration between aesthetic providers and ophthalmologists. Full article

This study evaluates the current Spanish insurance framework for catastrophic flood risk, administered by the Consorcio de Compensación de Seguros (CCS), based on nationwide loss data reported by the CCS for the period 1996–2020. The analysis of historical claims data enables a clear differentiation between frequent, low-cost events and infrequent, high-impact catastrophes. While the CCS has fulfilled a critical role in post-disaster compensation, the findings highlight the parallel need for ex ante risk mitigation strategies. The study proposes a more efficient, two-tier risk coverage model. Events whose impacts can be managed through standard insurance mechanisms should be underwritten by private insurers using actuarially fair premiums. In contrast, events with catastrophic implications—due to their scale or financial impact—should be addressed through general solidarity mechanisms, centrally managed by the CCS. Such a risk segmentation would improve the financial sustainability of the system and create fiscal space for prevention-oriented incentives. The current design of the CCS scheme may generate moral hazard, as flood exposure is not explicitly priced into the premium structure. Empirical findings support a shift towards a more transparent, incentive-aligned model that combines collective risk sharing with individual risk responsibility—an essential balance for effective climate adaptation and long-term resilience. Full article

The October 2024 cut-off low event triggered one of the most catastrophic floods recorded in the Valencia Metropolitan Area, exposing significant vulnerabilities in urban planning, infrastructure resilience, and emergency preparedness. This study presents a novel comprehensive assessment of the event, using a multi-sensor satellite approach combined with socio-economic and infrastructure data at the metropolitan scale. It provides a comprehensive spatial assessment of the flood’s impacts by integrating of radar Sentinel-1 and optical Sentinel-2 and Landsat 8 imagery with datasets including population density, land use, and critical infrastructure layers. Approximately 199 km² were inundated, directly affecting over 90,000 residents and compromising vital infrastructure such as hospitals, schools, transportation corridors, and agricultural lands. Results highlight the exposure of peri-urban zones and agricultural areas, reflecting the socio-economic risks associated with the rapid urban expansion into flood-prone plains. The applied methodology demonstrates the essential role of multi-sensor remote sensing in accurately delineating flood extents and assessing socio-economic impacts. This approach constitutes a transferable framework for enhancing disaster risk management strategies in other Mediterranean urban regions. As extreme hydrometeorological events become more frequent under changing climatic conditions, the findings underscore the urgent need for integrating remote sensing technologies, early warning systems, and nature-based solutions into regional governance to strengthen resilience, reduce vulnerabilities, and mitigate future flood risks. Full article

This study investigates the influence of exposure to climate change on the readability of narrative disclosures in annual reports. Analyzing a sample of 38,229 firm-year observations from 2002 to 2022, the study provides evidence supporting the information obfuscation hypothesis. Specifically, it finds that exposure to climate change is linked to less readable annual reports. This effect is both statistically and economically significant; a one standard deviation increase in climate change exposure leads to an 8.5% reduction in readability. Moreover, this effect is particularly evident among firms operating in environmentally sensitive industries, as well as those characterized by weak corporate culture. Additional tests indicate that the different aspects of climate change exposure (opportunity, physical, and regulatory) are individually associated with a decrease in readability of annual reports, with the physical dimension exerting the most significant impact. The findings underscore the necessity of implementing measures to mitigate climate change exposure and enhance sustainable business environments, such as transitioning to renewable energy sources (such as solar, wind, and hydro), minimizing dependence on fossil fuels, minimizing emissions from industries and transportation, sourcing low-carbon materials, adopting circular economy models, directing capital toward climate-friendly projects, and managing climate risks through catastrophe bonds and climate insurance. The significance of these actions is underscored by the impact of climate change on firms’ information environments, as documented in the current study. Full article

Risk analysis is critical for preventing catastrophic failures in complex systems, as exemplified by the Deepwater Horizon disaster, a stark reminder of systemic vulnerabilities in offshore drilling operations, where inadequate appraisal of overlapping failures led to severe environmental and human losses. This study addresses the absence of a predictive framework capable of capturing cumulative risk interactions across both time stages and defensive layers. To fill this gap, and by drawing on prior frameworks such as the Swiss Cheese Model (SCM) and the Risk Matrix (RM), as well as critiques of their limitations, we introduce the Synergy and Accumulation Model for Analysis (SAMA). This model defines project life-cycle stages and risk recipients, characterizes each risk by four parameters (the focus of impact, suddenness, frequency, and effectiveness), and calculates horizontal (RF_h) and vertical (RF_v) risk factors. We applied SAMA to fifteen identified failure modes of the Macondo well, categorizing them across two time stages (operational and construction) and four defensive layers. Horizontal analysis revealed that the regulatory-laws layer accumulated the highest risk factors, RFh_1laws = 129.25 during the operational stage and RFh_2laws = 95.98 during the construction stage. Vertical analysis showed that the safety objective experienced the greatest systemic vulnerability, with RF_vsafety = 135.8 across ten overlapping risks, followed by the quality objective at RF_vquality = 128.39. These findings demonstrate SAMA’s enhanced capability to identify critical collapse paths often overlooked by conventional models. For researchers, SAMA offers a transparent, parameter-driven methodology applicable across engineering and construction domains. For industry stakeholders, regulators, project managers, and safety engineers, this model provides actionable insights to prioritize resource allocation and strengthen specific defensive layers, thereby enhancing both preventive planning and resilience against future disasters. Full article

Background: Chronic pain affects millions worldwide, influenced by biological, psychological, and social factors. Catastrophizing predicts chronic pain outcomes, increased pain intensity, and worsening recovery. Virtual reality (VR) interventions offer innovative pain management strategies, but their effects on catastrophizing remain unclear. Methods: This systematic review and meta-analysis followed the PRISMA guidelines. Studies involving adults with chronic musculoskeletal pain, VR-based interventions, and randomized controlled trials were included. The primary outcome was pain catastrophizing. Searches were conducted in PubMed, CINAHL, Scopus, WoS, and PEDro until May 2025. The risk of bias was assessed using Cochrane RoB-2. Meta-analysis calculated effect sizes using mean differences (MD) and standardized mean differences (SMD) with fixed and randomized-effects models. Results: Of 306 records, 244 were screened, 19 underwent full-text review, and two additional studies were identified via Google Scholar. Nine studies were included, eight of which were meta-analyzed. The interventions included eight immersive and one non-immersive VR studies, lasting 3 to 12 weeks. A small but statistically significant effect was found when comparing VR-based interventions with controls (SMD = −0.26 [−0.48; −0.04]). Psycho-cognitive VR-based interventions had a significant effect (SMD = −0.32 [−0.56; −0.09]), while exercise-based VR did not (MD = −0.11 [−4.36; 4.14]). Immersive VR showed a small but significant effect when compared to non-intervention or sham controls (SMD = −0.37 [−0.75; −0.00]). However, when compared to all types of comparators, the effect was not statistically significant (SMD = −0.25 [−0.51 to −0.00]). Heterogeneity was moderate and not significant (p > 0.05). Conclusions: VR-based interventions, particularly immersive with psycho-cognitive approaches, show potential in reducing pain catastrophizing. Future randomized trials are needed to elucidate VR’s efficacy in managing pain catastrophizing. Full article

Diffuse alveolar hemorrhage (DAH), a catastrophic complication of connective tissue disorders (CTDs), manifests as rapid-onset hypoxemia, alveolar infiltrates, and progressive bleeding into the airways. While immune-mediated alveolar–endothelial injury primarily drives its pathophysiology, diagnosis is based on bronchoscopy and chest imaging. The clinical urgency lies in securing the compromised airway and stabilizing respiratory failure, a challenge increased by CTD-specific anatomical alterations such as cervical spine instability, cricoarytenoid arthritis, and subglottic stenosis. High-dose corticosteroids and immunosuppression are essential, while severe cases require extracorporeal membrane oxygenation or plasmapheresis. This comprehensive review introduces two novel approaches to address fundamental gaps in the management of CTD-induced DAH: a structured algorithm for a CTD-specific airway risk stratification tool, integrating anatomical screening and the application of lung ultrasounds (LUSs) for post-intubation CTD-induced DAH ventilation management. The need for a multidisciplinary team approach is also discussed. Despite aggressive care, mortality remains high (25–50%), underscoring the necessity for improved early recognition and intervention strategies for these high-risk patients. Full article

The increasing demand for energy storage solutions, particularly in electric vehicles and renewable energy systems, has intensified research on lithium-ion (Li-ion) battery safety and performance. A critical challenge is thermal runaway (TR), a highly exothermic sequence of reactions triggered by mechanical, electrical, or thermal abuse, which can lead to catastrophic failures. While most TR models focus on fresh cells, aging significantly impacts battery behavior and safety. This study develops an electrochemical–thermal coupled model that incorporates aging effects to better predict thermal behavior and TR initiation in cylindrical Li-ion batteries. The model is validated against experimental data for fresh NMC and aged NCA cells, and statistical analysis is conducted to identify key factors influencing TR (p < 0.05). A full factorial design evaluates the effects of internal resistance (10, 20, 30, and 40 mΩ), capacity (1, 2, 3, and 5 Ah), and current rate (1C, 3C, 6C, and 8C) on temperature evolution. Additionally, a machine learning algorithm (logistic regression) is employed to identify an internal resistance threshold, beyond which thermal runaway (TR) becomes highly probable, and to predict TR probability based on key battery parameters. The model achieved a high prediction accuracy of 95% on the test dataset. Results indicate that aging affects thermal stability in complex ways. The increased internal resistance exacerbates heating rates, while capacity fade reduces stored energy, mitigating TR risk. These findings provide a validated framework for enhancing battery thermal management and predictive safety mechanisms, which contributed to the development of safer, more reliable Li-ion energy storage systems. Full article

Forest fires have become one of the most destructive natural disasters worldwide, causing catastrophic losses, sometimes with the loss of lives. Therefore, some countries have created legislation to enforce mandatory fuel management within buffer zones in the vicinity of buildings and roads. The purpose of this study is to investigate whether inexpensive off-the-shelf drones equipped with standard RGB cameras could be used to detect the excess of trees and vegetation within those buffer zones. The methodology used in this study was the development and evaluation of a complete system, which uses AI to detect the contours of buildings and the services provided by the CHAMELEON bundles to detect trees and vegetation within buffer zones. The developed AI model is effective at detecting the building contours, with a mAP50 of 0.888. The article analyses the results obtained from two use cases: a road surrounded by dense forest and an isolated building with dense vegetation nearby. The main conclusion of this study is that off-the-shelf drones equipped with standard RGB cameras can be effective at detecting non-compliant vegetation and trees within buffer zones. This can be used to manage biomass within buffer zones, thus helping to reduce the risk of wildfire propagation in wildland–urban interfaces. Full article

Gas distribution stations (GDSs), pivotal nodes in long-distance natural gas transportation networks, are susceptible to catastrophic fire and explosion accidents stemming from system failures, thereby emphasizing the urgency for robust safety measures. While previous studies have mainly focused on gas transmission pipelines, GDSs have received less attention, and existing risk assessment methodologies for GDSs may have limitations in providing accurate and reliable accident probability predictions and fault diagnoses, especially under data uncertainty. This paper introduces a novel dynamic accident probability assessment framework tailored for GDS under data uncertainty. By integrating Bayesian network (BN) modeling with fuzzy expert judgments, frequentist estimation, and Bayesian updating, the framework offers a comprehensive approach. It encompasses accident modeling, root event (RE) probability estimation, undesired event (UE) predictive analysis, probability adaptation, and accident diagnosis analysis. A case study demonstrates the framework’s reliability and effectiveness, revealing that the occurrence probability of major hazards like vapor cloud explosions and long-duration jet fires diminishes significantly with effective safety barriers. Crucially, the framework acknowledges the dynamic nature of risk by incorporating observed failure incidents or near-misses into the assessment, promptly adjusting risk indicators like UE probabilities and RE criticality. This underscores the importance for decision-makers to maintain a heightened awareness of these dynamics, enabling swift adjustments to maintenance strategies and resource allocation prioritization. By mitigating assessment uncertainty and enhancing precision in maintenance strategies, the framework represents a significant advancement in GDS safety management, ultimately striving to elevate safety and reliability standards, mitigate natural gas distribution risks, and safeguard public safety and the environment. Full article