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Hurricane Ian in 2022 was a destructive category 4 Atlantic hurricane striking the state of Florida, which caused hundreds of deaths and injuries, catastrophic property damage, and an economic loss of more than $112 billion. Before the landfall of Ian in Florida, the state government issued evacuation orders in high-risk zones to reduce casualties and injuries. However, there is limited data available to monitor the actual evacuation patterns and compliance with the evacuation orders at a large geographic scale. This study utilizes human mobility data (i.e. SafeGraph Weekly Pattern) to analyse the spatial patterns of evacuation during Hurricane Ian in 2022. The objectives of the study include three key aspects: 1) proposing an analytical workflow that utilizes human mobility data to detect mobility patterns in disasters and other emergency events; 2) identifying significant evacuation patterns, and 3) revealing the spatial variations in the compliance with evacuation orders in the affected areas. Using data science and spatial analysis techniques, this study detected notable changes in population movements, both within Florida and nationwide, which are potentially linked to the hurricane-induced population evacuation. The distance decay pattern of population flows from Florida demonstrates a propensity for individuals to relocate to nearby areas during the hurricane. Furthermore, the increase in population outflows from the impacted areas suggests the effectiveness of mandatory evacuation orders. A more pronounced increase in outflows from designated mandatory evacuation areas points to the public awareness of the evacuation zone designation. This study provides large-scale, fine-resolution analysis of evacuation behaviours in natural disasters which cannot be easily detected in traditional data sources. The analytical workflows provide actionable tools for government agencies and policymakers to evaluate the effectiveness of evacuation orders and improve evacuation plans in future disasters. [ABSTRACT FROM AUTHOR]

The Taihang Mountains in China span numerous cities, where landslide disasters occur frequently in the mountainous areas, jeopardizing the lives and properties of residents. Consequently, it is of great significance to focus on prevention and control of landslide disasters in the region. Currently, a single model is commonly employed to analyze landslide susceptibility mapping (LSM), but the accuracy of the results fails to meet the demands of early warning, prevention, and control. This paper focuses on the Taihang Mountain area as the research area, organizes the collection of landslide disaster potential points and related influence factor data, and employs the information quantity method to derive a composite machine learning model by coupling with Random Forest (RF) and Extreme Gradient Boosting (XGB), subsequently utilizing the Genetic Optimization Algorithm (GA) to optimize the model. The performance of the composite model is enhanced using the Genetic Algorithm (GA), employing accuracy, regression rate, precision, F1 score, AUC value, and Taylor diagram to evaluate the comprehensive accuracy of the model results, with a susceptibility map generated for comparative analysis. The results demonstrate that the IV-GA-RF model performs optimally (accuracy = 0.956, precision = 0.96, recall = 0.953, F1 score = 0.957, AUC = 0.946 for the testing set, AUC = 0.929 for the training set), with all-around improvement in performance metrics compared to the unoptimized composite model, with metric values improving by 0.044, 0.051, 0.046, 0.044, 0.021 and 0.020, respectively. The IV-GA-RF model exhibits a significant advantage over the IV-GA-XGB algorithm, also optimized using the GA algorithm. The accuracy of the susceptibility map produced by the IV-GA-RF model is superior, as assessed by the Seed Cell Area Index (SCAI) method. The four factors of slope, rainfall, seismicity, and stratigraphic lithology are crucial in determining the occurrence of landslides in the study area. In summary, the IV-GA-RF model can be utilized as an effective model for analyzing landslide disasters, providing a reference for research in this field and contributing scientific insights to disaster prevention and control efforts in the study area; simultaneously, the concept of the composite optimization model introduces new perspectives into this field. [ABSTRACT FROM AUTHOR]

Many landslides occurred every year, causing extensive property losses and casualties in China. Landslide susceptibility mapping is crucial for disaster prevention by the government or related organizations to protect people's lives and property. This study compared the performance of random forest (RF), classification and regression trees (CART), Bayesian network (BN), and logistic model trees (LMT) methods in generating landslide susceptibility maps in Yanchuan County using optimization strategy. A field survey was conducted to map 311 landslides. The dataset was divided into a training dataset and a validation dataset with a ratio of 7:3. Sixteen factors influencing landslides were identified based on a geological survey of the study area, including elevation, plan curvature, profile curvature, slope aspect, slope angle, slope length, topographic position index (TPI), terrain ruggedness index (TRI), convergence index, normalized difference vegetation index (NDVI), distance to roads, distance to rivers, rainfall, soil type, lithology, and land use. The training dataset was used to train the models in Weka software, and landslide susceptibility maps were generated in GIS software. The performance of the four models was evaluated by receiver operating characteristic (ROC) curves, confusion matrix, chi-square test, and other statistical analysis methods. The comparison results show that all four machine learning models are suitable for evaluating landslide susceptibility in the study area. The performances of the RF and LMT methods are more stable than those of the other two models; thus, they are suitable for landslide susceptibility mapping. [ABSTRACT FROM AUTHOR]

Background: The COVID‐19 pandemic has taken a significant toll on the US population, with birthing people having special clinical needs. The Pregnancy Risk Assessment Monitoring System (PRAMS) is a population‐based surveillance system for monitoring birthing people's experiences. Comment data from the PRAMS survey can provide further insight into birthing people's experiences. This study aims to use PRAMS data to describe pandemic‐related experiences in a representative sample of birthing people in Wisconsin to help inform future emergency preparedness planning. Methods: This study analyzed 2020 Wisconsin PRAMS data for births in March or later. Content analysis of pandemic‐related comment data was conducted, and quantitative data on demographic characteristics and pandemic‐related experiences were examined. Results: Findings from 1406 respondents indicated that many birthing people were affected by the pandemic, including changes in healthcare visits and employment. One hundred respondents commented on pandemic‐related experiences; four interrelated themes emerged from content analysis: changed nature and quality of healthcare, limited social support, increased anxiety, stress, or fear, and employment or financial burden. Most comments discussed negative impacts; some expressed positive aspects. Discussion: Findings suggest opportunities for improving support for birthing people during public health emergencies, for example, through developing healthcare policies and public health guidelines that prioritize the protective mechanisms of social support for birthing people, identifying additional and immediately accessible policy protections to support birthing and postpartum people (e.g., insurance and paid leave) during public health emergencies, and implementing additional screening and support to help address increased mental health needs during public health emergencies. [ABSTRACT FROM AUTHOR]

Introduction: Epistaxis is commonly referred to as nosebleeds. The age range in which it most frequently manifests itself is three to eight years old. One of the primary settings for pediatric epistaxis is schools since kids can get accidental injuries while playing. The security and welfare of the pupils in school are the teacher's concerns. So, the teachers must be aware of the correct basic first-aid protocols. This study aims to assess the awareness of handling of epistaxis first aid in schools. Methodology: The study participant's responses were gathered using a pre-tested semi-structured questionnaire. Statistical analysis was done and the significance of the results was assessed Results & Conclusion: The majority of participants felt confident when it came to managing epistaxis, despite the fact that they had not received any formal training and simply possessed only an average understanding of the subject, lacking detailed insights and intricacies related to its first aid treatment. This underscores the fact that they were overestimating their knowledge and expertise in this domain. Therefore, educators, who are typically the initial responders to pediatric epistaxis in schools, have a limited or inadequate understanding and familiarity with the appropriate first aid protocols. Further studies scaling larger populations and propagating awareness in institutes related to children especially through means of live demonstrations and workshops can advance first aid management during emergencies. [ABSTRACT FROM AUTHOR]

In recent years, the landscape of disasters, conflicts and terror events has become more frequent and complex. Climate change, armed conflicts, terrorism, disinformation, cyber‐attacks, inequality and pandemics now present significant challenges to humanity. Emergency physicians today are likely to encounter ideologically motivated violent extremism or terrorist actions by radicalised lone actors. Terror medicine, distinct from disaster medicine, addresses the unique and severe injuries caused by terrorist incidents, including explosions, gunshots and chemical agents. The chaotic aftermath of such attacks demands rapid triage, prioritisation and strict adherence to scene safety protocols. Moreover, terrorist events have profound psychological impacts on victims and responders alike. Understanding the broader public health implications of these attacks is crucial for emergency physicians to enhance community safety and resilience. Terror medicine also brings unique ethical and legal challenges, such as patient confidentiality, mandatory reporting and mass casualty management. Effective responses to terror incidents necessitate close collaboration between healthcare providers and law enforcement. Familiarity with terror medicine principles fosters better communication and coordination, ultimately improving response efficiency and patient outcomes. This review offers a comprehensive approach to understanding terror medicine, defining the concept of 'terror', its significance for emergency physicians, and the known health impacts on patients, healthcare workers and responders. By delving into these aspects, the review aims to equip medical professionals with the knowledge and skills needed to navigate the complexities of terror‐related emergencies effectively. [ABSTRACT FROM AUTHOR]

Landslides are among the most dangerous hazards in Asia, posing a significant threat to human lives, infrastructure, and sustainable development. Landslide susceptibility maps provide useful insights into hazard potential but lack quantitative exposure assessments to develop targeted mitigation strategies and resource allocation. This study aims to propose an integrated approach for landslide hazards and exposure evaluation using machine learning models on the Google Earth Engine environment and geospatial analysis techniques. A geospatial database was established to predict hazards and evaluate exposure, including data on topography, geology, hydrology, climate features, land use, and building data. The landslide susceptibility map was created with advanced machine-learning algorithms, including Classification And Regression Tree (CART), Random Forest (RF), Gradient Boosting (GB), and Support Vector Machine (SVM). The ROC curve and the Wilcoxon signed-rank test were employed to evaluate the performance differences among the CART, GB, RF, and SVM models. The results indicated that the RF model demonstrated the highest performance, leading to its selection for creating a landslide susceptibility map. Landslide exposure was evaluated by overlaying the landslide susceptibility map with building data to quantify the number of affected houses by landslides across districts and communes. The analysis results identified the Cho Don district as the most exposed, with 46,237 households located in high and very high landslide susceptibility zones, followed by Ba Be district (39,631 households), Bac Kan city (37,266 households), Bach Thong district (28,495 households), Cho Moi district (28,436 households), Na Ri district (17,723 households), Ngan Son district (14,142 households), and Pac Nam district (13,034 households). These findings enable the identification of the potential consequences of landslides on infrastructure, human settlements, and livelihoods, contributing to the promotion of disaster reduction and prevention strategies. [ABSTRACT FROM AUTHOR]

• The future-oriented approach considers climate change impacts and LULC change. • Integrated AHP & bivariate analysis for precise flood susceptibility mapping. • Crucial insights for policymakers to enhance disaster preparedness. Flood susceptibility maps provide invaluable information for assessing and managing flood-prone areas, aiding in proactive planning, risk reduction strategies, and safeguarding vulnerable communities. The current research concentrates on advancing sustainable development practices by undertaking a comprehensive assessment of flood susceptibility in the Upper Vellar basin, with a projection for 2050. Employing an integrative methodology, this study utilizes an Analytical Hierarchy Process (AHP) and Bivariate Analysis. Nine critical parameters were used: elevation, distance from the river, distance from the road, drainage density, predicted LULC, projected precipitation, slope, soil type, and Topographic Wetness Index (TWI). The Modules of Land Use Change Evaluation (MOLUSE) plugin, which uses Cellular Automata-Artificial Neural Network (CA-ANN), was employed to predict the LULC map for the year 2050. Furthermore, bias-corrected Coupled Model Intercomparison Project 6 (CMIP 6) EC EARTH 3 Model (GCM) RCP 4.5 and 8.5 projected precipitation data were employed. The resulting flood susceptibility zones are classified into three categories: low, moderate, and high, with proportions of 32.64%, 55.52%, and 11.84% for RCP 4.5, and 34.63%, 53.46%, and 11.91% for RCP 8.5, respectively, concerning the total area. In both scenarios, nearly 38% of the settlement area is at high flood risk. This study provides essential insights for policymakers and stakeholders, facilitating the formulation of sustainable strategies to address projected changes in land use, precipitation patterns, and flood susceptibility in the Upper Vellar region up to 2050. [ABSTRACT FROM AUTHOR]

More and more severe weather events necessitate better evacuation strategies, particularly for vulnerable populations without access to private vehicles. This study investigates opportunities for shared autonomous vehicles (SAVs) in faster evacuation of the Houston, Texas coastline, with a focus on the crucial first-mile connection to bus stations. Microsimulations of various scenarios reveal performance of SAV systems with different seating capacities, fleet sizes, shared-ride acceptance levels, and coordination with bus departures to shelters. The Houston evacuations appear most effective with smaller, 5-seater SAVs, operated at a ratio of 1 SAV per 14 evacuees. The results underscore the importance of SAV-to-bus coordination, demonstrating that strategic ride-sharing and scheduling can significantly reduce evacuee wait times and fleet operating costs while maintaining timely arrivals at distant shelters. This work illuminates the practical implications of integrating SAV technology with existing transit systems to improve emergency management for carless populations. [ABSTRACT FROM AUTHOR]

Wildfires pose significant threats to communities, requiring robust pre-event planning for efficient evacuations. Transportation systems are crucial for these efforts, yet global research gaps persist, especially those related to transportation assets and transportation modes beyond privately owned automobiles. This study conducts a systematic review of four under-researched areas – infrastructure, modality, networks, and planning – to build a more comprehensive understanding of wildfire evacuations. Initial research is emerging in these domains, related to post-fire debris flows, air and transit evacuations, network analysis, and shelter planning. However, systematic analyses, evidence, and recommendations remain lacking. This includes wildfire's direct impact on transportation infrastructure, multi-modal evacuations, routing strategies, and community-driven evacuation plans. We underscore the need for empirical evacuation strategies to foster resilience for wildfire-threatened communities, offering valuable context-specific insights, identifying key actions, and highlighting ongoing research gaps. [ABSTRACT FROM AUTHOR]

Background and Purpose: Patients presenting at the emergency room (ER) with headache often encounter a hostile atmosphere and experience delays in diagnosis and treatment. The aim of this study was to design a protocol for the ER with the goal of optimizing the care of patients with urgent headache to facilitate diagnosis and expedite treatment. Methods: A narrative literature review was conducted via a MEDLINE search in October 2021. The "Code Headache" protocol was then developed considering the available characteristics and resources of the ER at a tertiary care center within the Spanish National Public Health system. Results: The Code Headache protocol comprises three assessments: two scales and one checklist. The assessments identify known red flags and stratify patients based on suspected primary/secondary headaches and the need for pain treatment. Initial assessments, performed by the triage nurse, aim to first exclude potentially high morbidity and mortality etiologies (HEAD1 scale) and then expedite appropriate pain management (HEAD2 scale) based on scoring criteria. HEAD1 evaluates vital signs and symptoms of secondary serious headache disorders that can most benefit from earlier identification and treatment, while HEAD2 assesses symptoms indicative of status migrainosus, pain intensity, and vital signs. Subsequently, ER physicians employ a third assessment that reviews red flags for secondary headaches (grouped under the acronym 'PEACE') to guide the selection of complementary tests and aid diagnosis. Conclusions: The Code Headache protocol is a much needed tool to facilitate quick clinical assessment and improve patient care in the ER. Further validation through comparison with standard clinical practice is warranted. [ABSTRACT FROM AUTHOR]

Landslides, as a common natural disaster, pose a significant threat to human society and the natural environment, including loss of life, economic damage, and environmental destruction. Effective landslide early warning is key to reducing these negative impacts. However, current warning methods face two major challenges: one is the reliance on static threshold judgments, which not only easily leads to false and missed alarms but also cannot adapt to complex and changing natural conditions. The second is the lack of ground data support in areas with complex terrain, which greatly limits the application range and accuracy of traditional warning methods. To overcome these challenges, this study designed an efficient processing system for Interferometric Synthetic Aperture Radar (InSAR) based on the (Artificial Intelligence) AI Earth Cloud platform, integrated with the Comprehensive Standardized Deformation Index (CSDI) approach, to provide an early warning analysis for the Zhenxiong landslide in Yunnan Province, China on January 22, 2024. Utilizing the cloud platform for rapid generation of deformation rates and selection of characteristic deformation points to reflect landslide trends, and applying the CSDI method for time-displacement curve analysis, enabled a fast and accurate landslide early warning. The research results show that the method proposed in this study can effectively warn of landslide events, significantly improving the accuracy and practicality of the warning. By combining InSAR technology with the CSDI model, this study not only addresses the challenges faced by traditional methods but also provides new insights and solutions in the field of landslide early warning, demonstrating the great potential of technological innovation in natural disaster management. [ABSTRACT FROM AUTHOR]

Landslide disasters are one of the frequently occurring geological hazards, posing a significant threat to human life and property safety. Swift and accurate identification of landslide areas is crucial for disaster prevention and mitigation. Current object detection algorithms have limitations in the localization and recognition of landslide areas. To address this issue, this paper proposes a cross-spatial network based on efficient multi-scale attention (EMA-Net) landslide recognition model. The proposed EMA-Net model incorporates the efficient multi-scale attention (EMA) for cross space learning, enhancing the model's focus on landslide areas. Additionally, by employing convolution with absolute positioning (CoordConv), the positional information of features is retained to enhance the capability of multiscale feature extraction. The utilization of the SCYLLA-IoU (SIoU)loss function enhances regression learning ability for model prediction borders, thereby improving the efficiency and accuracy of the model. To assess its performance, EMA-Net is evaluated against other models, including Yolov5 - 5.0, Yolov5 - 6.1, Yolov7, and Faster-R-CNN. The evaluation demonstrates that the proposed EMA-Net achieves a precision of 0.980, recall of 0.982, and mAP of 0.717, exhibiting clear improvement over the compared networks. Furthermore, through visualized analysis, the proposed network is capable of effectively identifying landslides within a smaller range. Comparative analysis of the aforementioned experiments validates the superiority of the proposed network. [ABSTRACT FROM AUTHOR]

Summary: Background: Skilled facilitators are essential to drive effective simulation training in healthcare. Competency‐based frameworks support the development of facilitation skills but, to our knowledge, there are no frameworks that specifically address context‐sensitive priorities developed with practitioners working in low‐resource settings. Methods: We aimed to develop a core competency framework for healthcare simulation facilitation in low‐resource settings using a modified Delphi process. We drew on the domain expertise of members of the Vital Anaesthesia Simulation Training Community of Practice, with the study guided by a four‐member steering group experienced in the conduct of simulation in low‐resource settings. In survey round 1, participants (n = 54) were presented with an initial competency set derived from a previous qualitative study and co‐created a set of 57 competencies for effective simulation facilitation in low‐resource settings. In survey round 2, participants (n = 52) ranked competencies by relevance into three performance categories: techniques; artistry; and values. In survey round 3, participants (n = 50) ranked competencies on their importance. The steering group collated results and presented a draft core competency framework. In survey round 4, participants (n = 50) voted with 98% agreement that this framework represented the most relevant and important competencies for effective facilitation of simulation sessions in low‐resource settings. Results: The final 32‐item framework encompasses core competencies found in existing standards and includes important new concepts such as demonstration of cultural sensitivity; humility; ability to recognise and respond to potential language barriers; facilitation team collaboration; awareness of logistics; and contingency planning. Discussion: This competency‐based framework highlights specific practices required for effective simulation facilitation in low‐resource settings. Further work is required to refine and validate this tool to train simulation facilitators to deliver effective training to improve patient safety. [ABSTRACT FROM AUTHOR]

Astroviruses are an emerging hazard in hatchery management, and they are responsible for great economic losses in poultry farms worldwide. Chicken astrovirus (CAstV) and avian nephritis virus (ANV) are involved in decreased hatching rate, mainly due to embryo deaths, and pale and runted chicks too weak to hatch. Hatchery diseases occur through direct egg infection or vertical transmission. However, the specific role of astroviruses in these diseases is still largely unknown. To elucidate this a high-quality Piedmont hatchery (Italy) was selected based on farm clinical signs and the astrovirus serological positivity in the breeder farm. The viral dynamics were followed from the hatchery to the farm. The presence of both CAstV and ANV was monitored by evaluating the viral load in environmental and bird samples. Interestingly, both viruses were detected in chick yolk sacs at 18 days of incubation, and in the gut contents of 1-day chicks, whereas in the hatchery environmental samples, the eggs' external surfaces and the embryos' intestinal contents were negative. The CAstV copy number was higher in bird tissues from the hatchery, while a greater ANV load was detected in bird tissues from the farm. Moreover, our data suggest vertical transmission of both viruses. Frequent co-infection was also observed in samples from both the hatchery and the farm. Lastly, the first Italian full-length genome and molecular characterization of ANV was obtained. RESEARCH HIGHLIGHTS: Identified the role of the hatchery in astrovirus transmission. Sequenced the avian nephritis virus complete genome. Investigated tissue distribution of astrovirus from egg to chicks. Demonstrated co-infection of ANV/CAstV. [ABSTRACT FROM AUTHOR]

The legal regulation of the state of emergency is a very wide and controversial due to the fact that the tension between the branches of government, which is not so obvious in everyday life, is often more transparent in cases of state emergency. This tension appeared in many countries as well as in Kosovo during the application of the measures to deal with the COVID-19 pandemic, and which revolves around whether the parliament should decide on the measures taken and their financing, or if this responsibility falls within the purview of the executive branch. This paper analyses the legality of the actions taken by the government during the pandemic. Further, it examines the legal ramifications of declaring a state of emergency, the resulting tension between the branches of government and measures taken to ensure respect for human rights. [ABSTRACT FROM AUTHOR]

During the occurrence of the Covid-19 pandemic, the laws made by the House of Representatives of the Republic of Indonesia (DPR) as a legislative body, ideally, should not cease to reflect society's needs pursuant to the realisation of the representation principle. In analysing the fulfilment of such an ideal conception with the reality of its implementation, this paper aims to discuss the trends and discourses regarding the laws made by DPR, as a balancing power to the presidential body, during the pandemic as a new state of emergency. The authors would like to scrutinise the trend of laws passed by the DPR in various sectors, both quantitatively by evaluating the number of outcomes and qualitatively by observing the issues raised during the law-making process. Finally, this paper finds that the DPR still falls short of expectations on ensuring the actualisation of a democratic law-making process amidst the pandemic. [ABSTRACT FROM AUTHOR]

On 25–26 March 2023, the U.S. National Council on Radiation Protection and Measurements (NCRP) held its 2024 annual meeting in Bethesda, Maryland, USA. The NCRP dates from 1929, and this meeting celebrated the 60th anniversary of receiving a U.S. Congressional Charter. For this annual meeting the NCRP felt it was essential to provide a briefing about advanced and small modular nuclear reactors (SMRs). The Journal of Radiological Protection is delighted to publish the following synopsis of material presented at the U.S. NCRP meeting. This synopsis is divided into five sections. The first section provides an overview of the whole meeting together with summaries of two context setting overview papers. The following four sessions of this synopsis are specific to advanced and small modular nuclear power reactors. The meeting also included keynote presentations by three of NCRP annual award recipients. The meeting topical areas were Technology Overview and Critical Issues. The individual papers laid the groundwork to understanding reactor technologies, terminology, and the fundamental concepts and processes for electrical generation. The perspectives of the U.S. Environmental Protection Agency and states, through the Conference of Radiation Control Program Directors were provided. The papers included a discussion of diverse topics including potential emergency preparedness considerations, radiological survey requirements, an evaluation of the future of nuclear power, the economics of reactors (both large and small), and the critical issues identified by the recent National Academies of Sciences' study on advanced reactors. The summary papers were developed to briefly document the major points and concepts presented during the oral papers presented at the 2024 NCRP Annual Meeting. The meeting heralded the dawn of a new era for commercial nuclear power. [ABSTRACT FROM AUTHOR]

Allocating emergency resources effectively is an essential aspect of disaster preparation and response. The Emergency Siting Problem (ESP) involves identifying the best places to locate emergency services in order that it can serve the most people in the least amount of time. Maintaining time limitations is of greatest significance in situations where each second matters, such as during disasters or public health emergencies. In this study, we concentrate on the difficulty of solving the ESP under extreme time limits. In this research, Genetic-adaptive reptile search optimization (GRSO) is proposed to provide a different way to solve the ESP problem within the constraints of limited time. The proposed GRSO method takes into account travel times, prospective facility places, and the geographic location of demand sites while keeping to the established time restrictions. In this study, the proposed method demonstrating superior performance accuracy in locating transportation facilities under extreme time limits for Emergency Service Planning (ESP), outperforming established optimization strategies and heuristics commonly applied to ESP problems. A fitness function is created to assess the standard of responses based on elements including response speed, coverage, and meeting deadlines. The GRSO algorithm has been modified and altered to handle the distinctive features of the ESP, such as precise facility placements and time constraints. Simulated and real-world datasets describing emergency circumstances are used in computational research to confirm the efficiency of the proposed method. The results are evaluated with established optimization strategies and heuristics generally applied to ESP problems. Results show that the GRSOapproach provides solutions that are more in pace with time limit constraints without sacrificing sufficient degrees of coverage or response time. [ABSTRACT FROM AUTHOR]

In the context of global warming, the frequency, intensity, and duration of heatwave events have markedly increased, bearing profound implications for both natural ecosystems and human societies. To effectively cope with this challenge, it is imperative to accurately identify and comprehensively assess the risks posed by heatwaves. This study undertakes a systematic approach and robust methodology to assess heatwave risks by leveraging a diverse array of data sources—encompassing remote sensing, statistical analyses. The methodology integrates the risk triangle theory alongside established risk assessment frameworks laid out by the Intergovernmental Panel on Climate Change (IPCC). Employing a three‐dimensional evaluation framework encompassing hazard, exposure, and vulnerability, we unravel spatial–temporal patterns, high‐risk zones, and dominant dimensions of heatwave risks contributing to potential disasters. Results indicated that during 1999–2008, roughly 27% of the study areas were affected by high and above risk levels of heatwaves, and the areas with high and very high hazard, exposure, and vulnerability accounted for approximately 19.5%, 10%, and 32.5%, respectively. During 2009–2018, the proportion of areas with high and very high risk, hazard, and exposure increased to about 31%, 26%, and 14%, respectively, while the percentage of areas with high and very high vulnerability decreased to about 24.43%. Notably, Xinjiang and the western part of Northwestern China are characterized by hazard‐dominant conditions, while Southern China's risk profile has shifted from 1999–2008 to 2009–2018 from high hazard and vulnerability conditions to a more complex interaction involving hazard, exposure, and vulnerability. Moreover, Northern China and the northern segment of Southwestern China exhibit simultaneous high‐risk rankings across hazard, exposure, and vulnerability dimensions, forming a comprehensive high‐risk zone. These findings characterize heatwave risk patterns and offer critical insights for risk management decisions, guiding effective disaster prevention and relief measures to ensure socio‐economic stability and public health. [ABSTRACT FROM AUTHOR]

This study develops a Stochastic Mixed Integer Linear Programming (SMILP) model to optimize the reverse logistics network for debris generated from proactive demolition of end-of-life buildings. Unlike most existing research, this study addresses proactive strategies for the Mitigation stage of disaster management. Our model identifies the optimal number of landfilling areas and sorting facilities, factoring in uncertainties in debris quantity and material quality. It incorporates environmental constraints, such as mandatory sorting processes and recycling thresholds. Multiple scenarios are considered, each with unique parameter values and occurrence probabilities, with the overall objective of minimizing net costs across all scenarios. A realistic case study is used to illustrate the model, demonstrating its capacity to reduce post-disaster recovery costs, improve operational efficiency, and balance financial and environmental considerations. This study offers insights for decision-makers, advocating proactive end-of-life buildings’ management as a disaster preparedness and sustainable practices. [ABSTRACT FROM AUTHOR]

The objective of this research is to develop an AI-based model that provides a map of potential emergency shelters for seismic-prone regions. While the predominant approach for locating emergency shelters involves expert-answered questionnaires, their accuracy has often been criticized globally. To address this, machine learning can enhance the speed and accuracy of shelter site selection; the results can also be generalized to other regions. Support vector machine (SVM), K-nearest neighbor (KNN), logistic regression (LR), gaussian processes classifier (GPC), and artificial neural network (ANN) methods are used to develop the model here. These algorithms are trained using maps of emergency shelters in San Francisco, enabling the resulting model to automatically provide potential emergency shelter maps not only for the studied case but also for cities with similar criteria. Except for LR, the other algorithms achieved F1 scores between 0.7 and 1.0 in selecting emergency shelter sites. The model developed in this research can serve as a reliable tool for disaster management planners in managing emergency shelters for people affected by earthquakes. [ABSTRACT FROM AUTHOR]

ABSTRACT Management of traumatic dental injuries (TDI) is very complex, even under ideal circumstances. Children in the primary dentition have unique needs, and it is important that the diagnosis and treatment choices are offered to parents. The prevalence of TDI in the primary dentition is far greater than for any other age group. Education of parents and caregivers in prevention and emergency management of oral injuries is essential. When injuries occur, the dental professionals must also respond appropriately to establish correct diagnosis of the injuries and assist parents in making decisions for management while communicating realistic expectations for the future. Progress has been made in the diagnosis and management of dental injuries in the primary dentition based on the biological healing response of oral tissues following injury over time. Several factors influence critical decisions that must be made based on basic principles and guidelines to improve successful outcomes for the child. Managing co‐operation must be balanced with the benefit of anticipated treatment need. The current evidence challenges previous dental interventions. The IADT guidelines updated the approach to management of TDI in children in the primary dentition. Encouraging a positive attitude to the dental setting early in the life course prepares the child to be a motivated dental attendee throughout their lifetime. This manuscript aimed to outline the critical issues and clinical choices for injuries to the primary dentition and to summarise recent guidance from the International Association of Dental Traumatology (IADT). [ABSTRACT FROM AUTHOR]

Exploring the relationship between governmental infectious disease management and emergency systems, I examine the turn to emergency in European measles management during the resurgence of the disease between 2017 and 2020. While measles management was shaped by hope for disease eradication and as a progressive pursuit of elimination, amid growing concerns with vaccination coverage, hope was redirected toward reversing regression in the struggle against infectious disease. I argue that perception of and action on public health issues as emergencies is intricately tied to change in the fundamental construct of governmental infectious disease management, regardless of change in the disease or its categorization. [ABSTRACT FROM AUTHOR]

ABSTRACT Objectives Methods Results Conclusions Systematic Review Registration Evidence‐based protocols for managing bleeding emergencies in patients with immune thrombocytopenia (ITP) are lacking. We conducted a systematic review of treatments for critical bleeding in patients with ITP.We included all study designs and extracted data in aggregate or individually for patients who received one or more interventions and for whom any of the following outcomes were reported: platelet count response, bleeding, disability, or death.We identified 49 eligible studies reporting 112 critical bleed patients with ITP, including 66 children (median age, 10 years), 36 adults (median age, 41.5 years), and 10 patients with unreported age. Patients received corticosteroids (n = 67), IVIG (n = 49), platelet transfusions (n = 41), TPO‐RAs (n = 17), and splenectomy (n = 28) either alone or in combination. Studies reported 29 different treatment combinations, the 5 most common were corticosteroids, platelet transfusion and splenectomy (n = 13), corticosteroids and IVIG (n = 13), or splenectomy alone (n = 13); IVIG alone (n = 11); and corticosteroids, IVIG and TPO‐RA (n = 8). Mortality among patients with critical bleeds in ITP was 30.6% for adults and 19.7% for children.The effects of individual treatments on patient outcomes were uncertain due to very low‐quality evidence. There is a need for a standardized approach to the treatment of ITP critical bleeds.CRD42020161206. [ABSTRACT FROM AUTHOR]

ABSTRACT In the context of unexpected disasters, comprehending individual decision‐making strategy is essential for governmental policy formulation and evacuation planning. The main challenges stem from the absence of large‐scale mobility data and the complex influences of multiple factors on personal strategies. To address this, this study focuses on the 2011 Tohoku earthquake in Japan as a case, which struck at 14:46 on March 11, a typical working day. Decision‐making strategies regarding how people return home from their workplaces have emerged as a primary concern. Therefore, we construct a large human mobility database for the Greater Tokyo area, and develop an empirical prediction for decision‐making strategies following earthquakes with the consideration of multiple factors. Except for users' location‐based information, we extract the grid‐based stay areas from historical stay records (normal days before disasters) and discover the functions of these areas combined with points of interest located within them. Experimental results indicate the effectiveness of our proposed framework in strategy prediction. Besides, we conduct an explainable feature importance analysis of key factors, which also provides insights for understanding human decisions during disasters. [ABSTRACT FROM AUTHOR]

ABSTRACT Aim Materials and Methods Results Conclusion The aim of this study is to examine the disaster management experiences and psychosocial problems of individuals who survived the earthquake in Turkey during the earthquake of the century.A qualitative research design, phenomenological research, was applied in this study. This qualitative study included 33 volunteer earthquake survivors. The interviews were conducted using WhatsApp. Colaizzi's phenomenological analysis method was used to analyze the data.In the analysis of the data, five themes (perception of the earthquake concept, things to do during an earthquake, actions taken to survive under the rubble, meeting everyday chores and dealing with post‐earthquake challenges, perceptions of disaster management), and fifteensubthemes (features of the earthquake, emotions, thoughts, correct actions, incorrect actions, actions for the body, situation‐oriented actions, housing, nutrition, hygiene, sleep, security, preparation, coping, and intervention) were identified.The study showed that the earthquake negatively affected individuals psychosocially, but the effective spiritual coping mechanisms utilized to cope with the catastrophic event under the rubble supported the survival process. In addition, it was determined that the participants believed that religion and spirituality were important in coping with the earthquake. [ABSTRACT FROM AUTHOR]

The worldwide prevalence of disasters exposes students, staff, and faculty at colleges and universities to multiple disasters, potentially impacting their mental health. This study investigates the influence of cumulative disaster-related stressors on depression among 1,497 higher education participants. Results from modified Poisson regression analyses reveal that individuals exposed to cumulative stressors (COVID-19 and Hurricane Sandy) have a higher prevalence of depression (PR 4.20; 95% CI: 1.45–6.12) compared to those without such exposure. The relationship was confounded when disaster preparedness knowledge factors (specifically, medication and grocery delivery knowledge) were added to the model (PR 3.75; 95% CI: 1.36–5.47). These results underscore the importance of integrating disaster preparedness knowledge into mental health interventions for the higher education community. Adapting interventions based on individual preparedness knowledge levels, especially for students and staff, can be a critical strategy in mitigating the impact of disasters on mental health in higher education settings. [ABSTRACT FROM AUTHOR]

Future changes to the year-to-year swings between active and inactive North Atlantic tropical cyclone (TC) seasons have received little attention, yet may have great societal implications in areas prone to hurricane landfalls. This work investigates past and future changes in North Atlantic TC activity, focusing on interannual variability and evaluating the contributions from anthropogenic forcing. We show that interannual variability of Atlantic TC activity has already increased, evidenced by an increase in the occurrence of both extremely active and inactive TC seasons. TC-resolving general circulation models project a 36% increase in the variance of North Atlantic TC activity, measured by accumulated cyclone energy, by the middle of the 21st century. These changes are the result of increased variability in vertical wind shear and atmospheric stability, in response to enhanced Pacific-to-Atlantic interbasin sea surface temperature variations. Robust anthropogenic-forced intensification in the variability of Atlantic TC activity will continue in the future, with important implications for emergency planning and societal preparedness. [ABSTRACT FROM AUTHOR]

The article "�i�ekian Critique of Violence in Alfonso Cuar�n�s Children of Men (2006)" by Shreyansh Jain and Smita Jha delves into the representation of systemic violence in the film "Children of Men." The authors analyze the film's portrayal of subjective and objective violence, critiquing �i�ek's notion of revolutionary violence as the only solution to systemic violence. They argue that nonviolent strategies should be employed first, drawing parallels to historical events and emphasizing the importance of ethical considerations in counter-violence. The article provides a comprehensive exploration of violence in the film, highlighting the complexities of systemic violence and its implications for society. [Extracted from the article]

Background Aim Methods Findings Conclusions Implications for nursing and health policy Nurses' critical input and firsthand disaster management experience are vital to healthcare quality.This study aims to comprehend nurses' experiences during and after the earthquakes, their coping mechanisms for posttraumatic stress disorder (PTSD), and the consequent effects on their profession, given the nurses' crucial role in disaster response.A descriptive qualitative study using semistructured interviews was conducted between April and May 2024. Fifteen nurses were selected using criterion and snowball sampling methods from those working as earthquake survivor nurses in the affected areas. The COREQ guidelines for reporting qualitative research were followed.Five main themes were: emotional reactions/physical difficulties, career and motivation, PTSD and well‐being, suggestions, and work performance. The results highlighted the significant psychological and professional challenges that nurses encounter, including the effects of severe PTSD symptoms, coping strategies, and the influence on their capacity to deliver care.Nurses dealing with earthquakes face unique challenges that test their resilience on all levels. Learning from their experiences and coping mechanisms can help healthcare systems support these frontline workers better. Investing in disaster preparedness and mental health resources for nurses is crucial for their well‐being and the overall strength of the healthcare system during crises.Effectively managing workloads and rest periods can reduce physical fatigue and prevent burnout. Shift rotations and adequate staffing levels are necessary. Access to psychological mental health support is vital for nurses to recover from the psychological effects of disasters. Regular disaster preparedness training is imperative for physical safety and psychological resilience. Robust support systems, including safe accommodation and peer support groups, are crucial for nurses in disaster response. [ABSTRACT FROM AUTHOR]

Objective Methods Results Conclusions The present study analyses Oceania's protest and conflict events (2021–2022) to aid healthcare systems better understand the scope of the issue.Data from the Armed Conflict Location & Event Data database were examined for event types and fatalities.A total of 2743 events were recorded, mainly protests (83.3%). Fatalities stemmed from battles, violence against civilians and riots. Australia had the most events (56.1%); Papua New Guinea the highest fatality rate (1.03/event).Australia faced pandemic‐related protests; Papua New Guinea grappled with tribal violence, posing healthcare challenges. A comprehensive approach emphasising disaster preparedness, regional cooperation and addressing root causes is crucial to bolster healthcare systems. [ABSTRACT FROM AUTHOR]

ABSTRACT Aim Design Methods Results Conclusions Implications for the Profession Impact Reporting Method Patient or Public Contributions To elucidate strategies for improving organisational adaptation during public health emergencies from the perspectives of nurse managers.This study utilised a qualitative approach, incorporating complex adaptive system theory within a phenomenological tradition.Semi‐structured interviews were conducted from May 2022 to June 2022. Participants included core members of the Shanghai Public Health Emergency Teams‐Nursing from 12 tertiary hospitals in Shanghai, all of whom had substantial experience as nurse leaders impacting health systems. Data obtained were coded and analysed using interpretative phenomenological analysis.Seventeen frontline nurse managers participated, leading to the emergence of three key themes related to complex organisational adaptation: seeking institutional support for environmental adaptation, building intrateam support for structural adaptation and activating individual support for behavioural adaptation. A conceptual framework of organisational adaptation was proposed, displaying the interconnections among these themes.The study provides valuable insights into managing nursing teams involved in public health emergency preparedness and response as an adaptive system. Identified managerial strategies offer guidance to ensure effective organisational assembly and optimal utilisation of the nursing workforce within the healthcare system.Recognising the crucial role of nurses in managerial positions, who leverage leadership, adaptability and decision‐making skills to coordinate frontline teams, is vital for effective public health emergency response. Their involvement in administrative roles underscores the importance of nursing perspectives in strategic planning, organisational adaptation and enhancing health system resilience during crises.The organisational adaptation strategies effectively adopted by nurse managers provide a reference for international scholars seeking to enhance the function and performance of nursing staff in healthcare system during public health emergencies.Consolidated Criteria for Reporting Qualitative Research (COREQ) checklist.No Patient or Public Contributions. [ABSTRACT FROM AUTHOR]

Background: Research of interventional treatment success in arterial bleeding cases is almost exclusively focused on technical and procedural factors. This study investigates the effect of an improved preprocedural activation algorithm for acute arterial bleedings treated by interventional radiology. Methods: During the three-year study period (2018–2021), the authors implemented an always-reachable, simple-to-remember emergency phone number routed to the responsible interventional radiologist on call and compared this pathway to the previous activation process. Data were acquired for all emergency cases with active arterial bleeding detected in CT scans and the diagnosis to treatment intervals before and after implementation were retrospectively analysed. Time signatures in CT and angiography were used to determine the interval. Results: 1322 calls or contacts occurred during the study period. In general, 625 emergency procedures were conducted; 120 bleeding interventions met the study requirements. In the study 44 patients were treated via the conventional pathway and 76 via the emergency phone activation. The activation algorithm utilizing the emergency phone led to a slight decrease in radiation doses and fluoroscopy time and a significant reduction (15min) in diagnosis to treatment intervals (p = 0.019). After implementing the emergency phone, the technical success rate increased significantly from 68% to 94% (p<0.001). Conclusions: This study shows that effective communication structures, such as implementing a standardized activation pathway via an emergency phone, can significantly reduce diagnosis to treatment intervals and increase technical success rates. Effective communication is crucial for interventional radiology to deal with acute and life-threatening conditions requiring immediate treatment. This study presents a possible improvement and provides valuable insight for interventional radiology clinics seeking to optimize their communication and management strategies for emergency cases. [ABSTRACT FROM AUTHOR]

Background: Employment and household responsibility are critical health determinants. The COVID-19 pandemic altered the work and social landscapes in Nevada, USA through closures of workplaces and schools/childcare centers, changing patterns of employment, and household responsibilities. This study aimed to measure changes in employment status and perceived housework responsibilities among Nevada adults in December 2020, before widespread availability of COVID-19 vaccines in a pandemic-affected economy. Methods: Using a cross-sectional telephone survey of 1,000 Nevada adults, this study compared respondent experiences and perceptions of employment and time spent on housework in December 2020 to pre-pandemic using multinominal logistic, proportional odds, and logistic models. Results: 70.52% of participants experienced no employment change; roughly 24% reported being fired/laid-off, working reduced hours, or quitting. Chi-square analyses found participants of color more likely than Whites to report being fired/laid-off or working reduced hours (p-value = 0.0005), though these findings were not significant in our models. Participants in the lowest income bracket had higher odds of being fired/laid off (p-value = 0.0030), and participants aged 65+ were less likely to experience employment change (p-value<0.0001). 32.43% of participants reported more time spent on housework. Multivariate analyses showed age is significantly associated with changes in both employment status (p-value<0.0001) and housework time (p-value<0.0001); income is a significant factor for employment status change (p-value = 0.0024). Of those reporting their households spent more time on housework, females were 2.90 times (95% CI = 1.66, 5.05, p-value = 0.0002) more likely to report taking on the additional work. Conclusions: Results demonstrate a disproportionate burden in employment change and/or more perceived household responsibilities on lower income and younger respondents, and females reporting they are more likely to take on additional housework. Understanding systemic vulnerabilities related to employment status and household responsibilities is necessary to aid impacted communities and to plan for future emergencies. [ABSTRACT FROM AUTHOR]

COVID-19 offers many valuable lessons, many of which could be found in unique societies like Hong Kong. The metropolis is special for its drastically varying—good and bad—COVID-19 performances. Hong Kong was widely considered a pandemic control and containment success for maintaining a remarkably low number of COVID-19 infections and deaths, until it was not. In March 2022, for instance, Hong Kong had the world's highest COVID-19 infection rates. As Hong Kong shares many similarities with other metropolises around the world, it is important to learn the hard-earned lessons from its failure to control infections. Drawing insights from the literature and our own research, this analysis aims to identify key lessons societies could gain from Hong Kong's COVID-19 responses to ensure better preparation for future pandemics. [ABSTRACT FROM AUTHOR]

Summary: Location‐based underwater communication applications such as strategic surveillance, disaster prevention, marine research, and mine detection have given the field of underwater wireless sensor networks (UWSN) a head start. Node localization is a prerequisite for accurate data collection, target monitoring, and network management in UWSNs. However, the unique characteristics of the underwater environment, such as signal attenuation, multipath propagation, and variable acoustic properties, pose a major challenge to effective node localization. Accurate sensor node location data is essential for successful underwater data collection, but difficult to achieve as the GPS system cannot be used in an underwater environment. In this paper, existing node localization techniques such as ALS, SLUM, MASL, SLMP, UDB, USP, etc., and recent advances such as the fusion of range‐based and range‐free techniques, the fusion of RSSI and AoA to improve localization accuracy by using directional information in addition to signal strength, and the use of optimization techniques such as PSO, COA, and WOA algorithms to improve the accuracy of the applied node localization algorithm, e.g., TP‐TSFLA, and challenges related to UWSN are discussed. Also, different localization algorithms that affect the accuracy of UWSN localization techniques have been evaluated and compared with NS2 in terms of localization error, localization coverage, energy consumption, and average communication cost metrics. In addition, this paper also provides an up‐to‐date investigation of localization techniques. Finally, the tools available for simulation are presented, followed by open research questions that need to be addressed in the localization of nodes. [ABSTRACT FROM AUTHOR]

AbstractWith the rapid development of artificial intelligence technology, generative AI has shown broad application prospects and potential in various fields. Frequent emergencies have put forward higher requirements for traditional Emergency Response Decision Support Systems (ERDSS). This paper proposes a theoretical framework of ERDSS based on generative AI (ERDSS-GAI), which deeply integrates generative AI with three stages of emergency response decision-making. The framework aims to leverage the advantages of generative AI in massive data processing, knowledge mining, strategy optimization, and other aspects, thereby enhancing the intelligence level and emergency response capability of ERDSS. The key components and implementation path of ERDSS-GAI are systematically explained from a theoretical perspective, and its application value is analyzed through the case of rainstorm and flood disaster in Shenzhen. This research demonstrates that generative AI can improve the scientific and refined level of emergency response decision-making, providing a theoretical framework and practical insights for its widespread adoption in emergency management. [ABSTRACT FROM AUTHOR]

The rapid development of UAV communication technology makes it have application potential in wireless systems. However, for the optimization problem of UAV base station providing communication for ground personnel in the disaster area under special natural disasters, traditional deep reinforcement learning is used. Algorithms cannot solve such problems well. This article proposes the AD3QN algorithm combined with the attention mechanism, which can communicate with disaster victims on the ground better and more quickly, providing better information collection for rescue missions and completing the task of communication optimization. In the mission simulation environment, in order to make the environment more realistic, we innovatively designed the ground user distribution model, air-to-ground communication model, and electromagnetic interference model. Finally, the effect of the proposed algorithm is evaluated by comparing different deep reinforcement learning algorithms. The results show that the algorithm we proposed can provide communication services faster and has higher practicability in terms of algorithm. [ABSTRACT FROM AUTHOR]

Aim Background Method Results Implications for nursing/midwifery and health policy To determine the experiences of nurses and midwives providing perinatal care in an earthquake area.On February 6, 2023, two earthquakes measuring 7.8 and 7.6 magnitudes struck Turkey, affecting a large area. It is crucial for perinatal care to be rapidly organized, provided under the most suitable conditions, and delivered by qualified health professionals. Understanding the post‐disaster experiences of nurses and midwives is crucial to addressing this issue.This is a qualitative study using phenomenological methodology with 8 nurses and 12 midwives in the earthquake‐affected area. Personal information and semistructured interview forms were used for data collection. Content analysis was used for data analysis.Participants had a mean age of 33.75 years. The experiences of nurses and midwives were grouped into five themes: emotions experienced, challenges encountered, problems in perinatal services, coping mechanisms, and recommendations. The emotions experienced theme encompasses both positive and negative emotions. The challenges encountered theme includes challenging environmental conditions, organizational issues, problems with medical supplies and drugs, and being a victim of the earthquake. The problems in perinatal services theme includes pregnancy, childbirth, and postpartum services. The coping mechanism's theme encompasses problem‐focused and emotion‐focused coping strategies. The recommendations theme includes education and awareness, preparedness for disasters, and sustainable services.Nurses and midwives working in the earthquake‐affected area experienced numerous physical and psychological challenges and encountered difficulties in delivering health services. A disaster education course including simulated disaster drills and practice can be integrated into the education system. Strengthening healthcare facilities against disasters and raising awareness among the community are crucial. [ABSTRACT FROM AUTHOR]

To assess the impact of China's regional emergency logistics response capabilities on economic growth sustainability, this study develops a set of comprehensive indicators. It applies the entropy weight method combined with the TOPSIS method to evaluate these capabilities across regions. Based on panel data from 30 provinces in China from 2012 to 2021, this study employs panel models, panel quantile regression, and panel threshold models to analyze the impact of emergency logistics response capability on sustainable economic growth. By measuring the regional emergency logistics response capability and examining its effects on the sustainability of economic growth, this research provides foreign investors with a clearer understanding of the ability of different regions in China to handle unexpected public incidents. This, in turn, helps reduce investment uncertainty, mitigate certain risks, and offers valuable insights for enhancing the efficiency of international investments in China. Key findings are: (1) Since 2018, the establishment of the Ministry of Emergency Management has significantly improved China's regional emergency logistics capabilities, with the eastern region outperforming the central and western regions. (2) Enhancing China's emergency logistics response capability helps improve the sustainability level of economic growth. This reflects how China's emergency management departments can mitigate the adverse impacts of public emergencies on economic growth by transforming social logistics into emergency logistics. (3) As emergency response capabilities have strengthened, their impact on economic sustainability initially decreased but later increased. [ABSTRACT FROM AUTHOR]

The World Health Organization declared a state of emergency in 2022 because of monkeypox. This disease has raised international concern as it has spread beyond Africa, where it is endemic. The global community has shown attention and solidarity in combating this disease as its daily increase becomes evident. Various skin symptoms appear in people infected with this disease, which can spread easily, especially in a polluted environment. It is difficult to diagnose monkeypox in its early stages because of its similarity with the symptoms of other diseases such as chicken pox and measles. Recently, computer-aided classification methods such as deep learning and machine learning within artificial intelligence have been employed to detect various diseases, including COVID-19, tumor cells, and Monkeypox, in a short period and with high accuracy. In this study, we propose the CanDark model, an end-to-end deep-learning model that incorporates cancelable biometrics for diagnosing Monkeypox. CanDark stands for cancelable DarkNet-53, which means that DarkNet-53 CNN is utilized for extracting deep features from Monkeypox skin images. Then a cancelable method is applied to these features to protect patient information. Various cancelable techniques have been evaluated, such as bio-hashing, multilayer perceptron (MLP) hashing, index-of-maximum Gaussian random projection-based hashing (IoM-GRP), and index-of-maximum uniformly random permutation-based hashing (IoM-URP). The proposed approach's performance is evaluated using various assessment issues such as accuracy, specificity, precision, recall, and fscore. Using the IoM-URP, the CanDark model is superior to other state-of-the-art Monkeypox diagnostic techniques. The proposed framework achieved an accuracy of 98.81%, a specificity of 98.73%, a precision of 98.9%, a recall of 97.02%, and fscore of 97.95%. [ABSTRACT FROM AUTHOR]

Aim Background Introduction Methods Results Conclusion Implications for nursing policy The study aimed to determine the experiences of Turkish nurses who volunteered in the disaster zone following the 2023 Türkiye–Syria earthquake.The earthquake devastated 11 cities in Türkiye, which required a comprehensive humanitarian response. Despite the crucial role of nurses in crisis management, limited research exists on their experiences in earthquake zones.Nurses experience difficulties in disaster areas, such as physical conditions, lack of disaster plans, and inadequate disaster training before being deployed to earthquake areas.This study used a qualitative research model and case study design. Data were collected through in‐depth qualitative interviews. Nine participants who had worked in earthquake zones for at least 5 days were included in the study. The discussions were recorded, transcribed verbatim, and analyzed thematically. The purposive sampling method was used, and the Consolidated Criteria for Reporting Qualitative Research guidelines were followed.As a result, 4 themes, namely physical conditions, psychosocial conditions, professional conditions, and organization, and their 14 subthemes were determined. This study revealed that nurses encountered difficulties related to physical conditions in earthquake zones. Moreover, the emotional burden expressed by the nurses highlighted the profound psychological impact of disaster response.This study determines that disaster preparedness and support for nurses should be enhanced to improve the arrangement of health services in future calamities.The results of this study can be used by nurse managers and healthcare policymakers to create nursing training programs that focus on disaster‐related competencies. [ABSTRACT FROM AUTHOR]

Food insecurity and malnutrition are rising worldwide due to disruptions in food systems related to interconnected health-, climate- and conflict-related crises. Although governments globally are committed to addressing nutritional challenges, policy responses have increasingly focused on food security and, particularly, on food affordability. However, these short-term measures often overlook the necessity of integrating nutritious foods into the food system to ensure improved long-term nutrition. By drawing on the United Nations Committee on World Food Security's Voluntary guidelines on food systems and nutrition, this article outlines opportunities for policy-makers to integrate nutrition into key elements of the crisis response. Key policy areas where nutrition could be further integrated include social protection, agricultural investment, trade policy and urban planning. Strengthening the focus of nutrition in these measures will be essential to establish long-term incentives that support food systems transformation for improved nutrition. Drawing on theories of the policy process, I propose that stronger governance and cross-sectoral dialogue will be critical to achieve sustained nutritional outcomes. Health policy-makers can play a leadership role in supporting cross-sectoral policy change by carefully framing the policy issues, advocating for institutional structures that promote collaboration across sectors to prioritize nutrition, and strengthening the management of conflicts of interest in food system policy-making. [ABSTRACT FROM AUTHOR]

Evidence about the impact of mass gatherings during the coronavirus disease 2019 (COVID-19) pandemic on the number of disease cases and on the health-care systems of host countries is limited. Additionally, there have been few publications on the lessons identified from the adaptation of mass gatherings held during the pandemic, including the implementation of comprehensive public health and social measures aimed at reducing viral transmission. This article describes preparations made for the 2020 Union of European Football Associations (UEFA) European Football Championship (UEFA Euro 2020) by the World Health Organization's (WHO) Regional Office for Europe, UEFA and other stakeholders after the championship had been rescheduled because of the COVID-19 pandemic. Technical guidance on preparations for the football tournament and risk assessment tools were provided by WHO. A task force established by the WHO Regional Office for Europe conducted traditional and event-based disease surveillance before and during UEFA Euro 2020, monitored public health and social measures in the 11 host countries, and developed a risk communication and community engagement strategy that involved multimedia campaigns targeting news and social media, fans, athletes, event organizers and other stakeholders. The lessons and good practices identified during UEFA Euro 2020 are described to help guide preparations for future mass gatherings in health emergencies. Sharing data and recommendations on best practice from previous mass gatherings with the organizers and countries involved in planning for a major event is particularly important. [ABSTRACT FROM AUTHOR]

To investigate the erosive damage effect of the acidic solution on sandstone, experiments were conducted to examine the macro‐ and micro‐characteristics of sandstone samples under different acid etching times. Microscopic morphology changes, pore structure characteristics, mineral composition changes, and mechanical response characteristics were obtained before and after acid etching. Finally, a comprehensive evaluation index for acid etching damage was proposed. The results show that: (1) Acidic solution will erode the sandstone skeleton and cause the sandstone to collapse. The etched surface appears "flocculent" and yellow sediment is produced. (2) The pores in sandstone samples are mainly micro‐ and mesopores, and the total porosity increases exponentially with the duration of acid etching. The volume fraction of micropores can reach up to 81.5%. (3) The acid etching process of sandstone samples includes physical diffusion and chemical dissolution, which can be divided into four stages and three regions from the outside to the inside. After acid etching, the uniaxial compression failure mode of the sample changes from shear to mixed shear‐tensile failure. (4) The comprehensive evaluation index based on three failure modes generated during the loading process shows good consistency with the overall changes of characteristics parameters such as elastic modulus, peak stress, and peak strain. The research findings of this paper can provide theoretical support for the assessment of rock mass stability and disaster prevention in acidic environments. [ABSTRACT FROM AUTHOR]

Despite the important roles that academic managers play and the growing body of literature on online learning, research on the organisational level, such as management, remains underexplored, particularly within the context of interim online teaching. Therefore, our study aimed to fill this gap by examining academic managers' key roles and the challenges they experienced in migrating to interim online teaching. This case study involved eight academic managers from private and public higher education institutions in the Philippines, who were selected through purposive sampling. Using semi-structured interviews, the findings indicated that their roles and challenges across the six leadership functions intensified and expanded during the transition to interim online teaching. It is further revealed that these challenges and roles were shaped not only by individual and institutional factors, such as university culture and structure, technological resources, and institutional policies, but also by larger contextual factors, such as national policies, economic conditions, and the country's technological readiness. Implications for management development, policy-making, and future research are discussed. [ABSTRACT FROM AUTHOR]

The article "Cochrane in CORR®: Red Flags to Screen for Vertebral Fracture in Patients Presenting With Low-back Pain" discusses the importance of identifying vertebral fractures in patients with low back pain to guide appropriate medical or surgical management. The study found that red flags such as significant trauma, older age, corticosteroid use, and presence of contusion or abrasion were most diagnostically useful for screening vertebral fractures. While these red flags can help guide the decision to order imaging, clinicians should exercise clinical judgment due to the risk of false positives and false negatives. [Extracted from the article]

Accessibility between fire hydrants and buildings is paramount in emergency response, significantly influencing the efficiency and effectiveness of firefighting operations in the event of an incident. However, assessing this relationship within a geographic information system (GIS) framework presents challenges on two fronts. Obtaining the path avoiding building and parcel obstructions to hydrants is not trivial. Further, determining the furthest extent around a building exterior from hydrants is complicated, yet it is critically important given the spatial limitations of equipment reach. To assess furthest extent, an analytical framework is introduced based on the Euclidean shortest path problem. The proposed approach offers a comprehensive, automated GIS‐based methodology tailored to evaluate the dynamic relationship between hydrants and buildings. The developed methods are able to accurately and precisely identify the furthest point around a building structure from hydrant, facilitating risk assessment as well as fire code compliance. This enables a comprehensive evaluation of potential loss and structure vulnerability at property, street, neighborhood, and regional levels. [ABSTRACT FROM AUTHOR]

The accurate measurement of coal seam gas content is essential for several aspects of deep coal mining, including disaster management, resource allocation and sustainability. However, obtaining in-situ coal samples while preserving gas content under challenging conditions, such as high stress, temperature fluctuations, and drilling fluid environments, remains a significant challenge. To overcome this difficulty, we present an innovative insitu pressure- and gas-preserved coring tool specifically designed for deep coal mining applications. This device enables the collection of coal seam samples under in-situ conditions while ensuring that both pressure and gas content are preserved, thereby preventing gas escape during sample transfer and providing more accurate parameters for evaluating coal and natural gas reserves. In the demanding environment of deep coal seams, the performance of the pressure-preserved chamber of the corer relies on the reliability of its remote triggering mechanism. The presence of drilling fluid introduces medium resistance, which can impair the triggering process--an issue largely overlooked in previous research. Herein, we propose a robust method to calculate remote triggering forces within liquid media and optimize its key parameters to improve operational stability. Laboratory tests and field validations in coal mining environments are conducted, which confirm the effectiveness of the optimized design and demonstrate the tool's practical applicability. This study offers valuable insights into addressing key challenges in deep coal reservoir exploration and gas resource preservation. [ABSTRACT FROM AUTHOR]