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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]

The landscape and the factors affecting the development of advanced tools (e.g., artificial intelligence, predictive analytics of outbreaks, knowledge management, vigilance, and reporting systems) with specific concern on supply chain disruptions are described, so as the main topics on health emergencies, preparedness, and mitigation are introduced. This work deals with Multi-Criteria Decision Making (MCDM) tools to address the Suppliers Selection Problem (SSP) and prepare emergency responses by applying Robust Optimization (RO) models, dealing with uncertainty and risk, and coping with computational issues. Definitions and goals are updated, and approaches and models for emergency preparation and responses are adjusted to enlighten the costing and performance indexes. Relevant topics are also integrated: the provisions (and procurement) disruptions and the mitigation of related impacts. After that, an actual situation for deciding on the supplier bid for Information Systems oriented to emergency events is addressed. The decision matrix is built using the referred criteria. Four different MCDM methods/models with the associated software are applied: (i) the simple additive model, (ii) the Technique for Order of Preference by Similarity to the Ideal Solution (TOPSIS) model, (iii) the "e" Fuzzy model, and (iv) - the Elimination and Choice Expressing Reality (ELECTRE) model. The hierarchy of alternatives is built, and the decision process ends by assigning one of the bidder supplier companies. As the differences between the obtained hierarchies are minor, a comparative analysis that addresses the deviation amplitude, the best and the least alternatives, is performed. [ABSTRACT FROM AUTHOR]

Medical emergencies, though rare, may occur unpredictably in a dental office during or after dental procedures. It may occur accidentally or subsequent to systemic problems of patients. These series of clinical events entail instantaneous management to evade any potential consequences. Basic life support measures require sufficient knowledge, expertise, skills, and equipment. Several medications and equipment are necessary to be available for immediate reach in any dental office. Health authorities of different countries usually propose these lists to dental practitioners. However, the best emergency kit is the one, which is arranged and maintained by the dentists based on their needs and easily accessible for immediate use. Considering the importance of this subject and the results yielded from the regular visits of the Dental Supervision Department (Vice Chancellor for treatment of Shiraz University of Medical Sciences) to the dental centers of Shiraz in the spring and summer of 2023, we decided to recall the importance of emergency medicines and equipment through a brief communication. [ABSTRACT FROM AUTHOR]

Utilizing 336 documents of administrative punishment decisions on fabricating COVID-19 rumors in Zhejiang province between December 2019 and December 2022, this article explores the effects of three sets of factors on the severity of administrative punishment. Empirical results suggest that administrative punishment for COVID-19 rumors is an ad hoc administrative measure only utilized in a state of emergency when the Chinese government implemented the "dynamic zero-case" policy. While it did not directly contravene existing Chinese laws, such a type of punishment practice represented the expansive trend of administrative punishment power. It caused tension with the current legal system. The expansion of administrative power manifested through the broadened scope of punishable false speech, lowered criteria of public order disruption, and lowered punishable criteria of offenders' intent. Given that the Chinese society (as any other societies) periodically enters a state of emergency, it is necessary to consider how to maintain a dynamic balance between the abnormal exercise of administrative power and the protection of individual's basic rights when the emergency reappears. This article advances the understanding of the dynamics surrounding administrative punishment for rumors and furnishes policy and legal recommendations for employing administrative measures in rumor control during national emergencies. [ABSTRACT FROM AUTHOR]

Fire accidents in oil tank farms can trigger domino effects, leading to multiple tank fires with catastrophic consequences. Preventing losses in large‐scale tank farms requires a dynamic assessment of fire‐induced domino accidents. Existing research often focuses on calculating the time to failure (TTF) of storage tanks but overlooks the influence of failure modes. This study develops numerical models to explore failure modes of oil storage tanks with uniform and stepwise walls exposed to thermal radiation. Factors such as the flame heights of combustion tank, adjacent spacings, wall thickness, and tank volumes are considered. The numerical model employs a solid double‐layer flame model to determine thermal radiation intensity and temperature, followed by a dynamic stress–strain and buckling analysis to obtain time to buckling (TTB) and time to yielding (TTY). If TTB < TTY, the failure model is buckling; otherwise, the failure model is yielding. Results indicate that failure modes in nonuniform thermal fields include buckling and yielding, with stepwise walls favoring buckling and uniform walls favoring yielding. When the wall thickness is below the critical value, failure is yielding; otherwise, it is buckling. These findings support risk management and emergency response for fire‐induced domino effects in oil tank farms. [ABSTRACT FROM AUTHOR]

With the increase in service time of oil pipelines, the probability of pipeline damage increases and the risk of leakage increases. However, as an important equipment for transporting oil, long‐distance pipelines have to be built across rivers. According to statistics, the leakage accidents of oil pipelines crossing rivers account for nearly 50% of all pipeline leakage accidents. Crude oil diffused into rivers easily cause serious pollution and damage to rivers and nearby organisms. Therefore, it is of great significance to study a reasonable, rapid, and efficient oil spill emergency treatment scheme for pollution and property loss. In this paper, an optimization model of emergency disposal scheme based on Apriori‐Topsis is proposed. Firstly, according to the characteristics of the oil spill pipeline, the general scheme library of emergency disposal is automatically generated by association rules, including the type, quantity, layout, and selected disposal technology of oil recovery equipment. Then, combined with the calculation of emergency disposal materials, the multi‐decision technology Topsis model is adopted to optimize the scheme from two angles of oil recovery effect and economic cost, and finally the cost‐effective emergency disposal scheme is obtained. Finally, taking the oil pollution accident on the second line of the Qing river as an example, the optimization model of emergency disposal scheme based on Apriori‐Topsis proposed in this paper is carried out. The application results verify the availability and effectiveness of the model, which provides a new method for the selection of emergency materials for rivers and pipeline process safety. [ABSTRACT FROM AUTHOR]

In its iron ore operations, Vale, the largest mining company in Brazil and the fourth largest mining company in the world by market value, has 77 dams considered with high potential damage in case of a failure in the stability controls. This classification follows the criteria of the sector regulatory agency in Brazil and determines that, for this class, a mass alert system is necessary for the resident population and workers immediately downstream of the dam within a region preset by legislation, considering a simulated flood area. For Vale, the mass alert system for dam emergencies is part of a critical mitigating control for a business risk analysis considering the hypothetical dam break as an unwanted material event. Therefore, both the probability of failure on demand, spurious failure, and availability of the assets of this protection barrier are important elements for this purpose, as well as the emergency response plan and the evacuation simulation of flood areas, which are part of a risk management system that require continuous verification and continuous improvement. Currently, Vale has 375 sirens, and it is planned to reach 420 sirens by the end of 2024. The purpose of this article is to present how the safety concepts applied to these systems were developed, the good practices applied from this study, and the lessons learned from the dam emergency management arising from the break of the Brumadinho dam in 2019. The reliability analyses of the systems involved and the main contributors to the Safety Critical Unavailability are presented, as well as the results of the reduction in the maintenance time and increase in system availability. [ABSTRACT FROM AUTHOR]

As climate change exacerbates disasters around the world every year, millions more animals are negatively affected. There is increasing awareness of the importance of the human–animal bond to people's emotional well-being, along with studies on the traumatic effects on those who lose their animals, both companion animals and livestock, because of disasters. Despite this, however, changes in disaster management to include animal disaster response plans are not being reflected in many communities, and barriers to establishing these protocols remain. This paper addresses the ongoing trauma that can result from losing animals during disasters, outlines barriers that prevent widespread adoption of animal disaster response plans, and offers some suggestions and solutions. [ABSTRACT FROM AUTHOR]

This paper describes how the Government of Manitoba employed a task force to support the recovery of diagnostic and surgical services from the impact of COVID-19 from December 2021 to December 2023. The paper describes how the system evolved during this period to optimise the efficiency and effectiveness of recovery efforts. The paper supports a more comprehensive implementation of the incident command system (ICS) to manage recovery effectively, with specific reference to the recovery of diagnostic and surgical services. The implementation of ICS and robust structure and processes led to the elimination of 83 per cent of the pandemic backlog and achievement of wait time targets for 26 per cent of services lines in 'expanded scope', with 83 per cent of service lines trending positively towards the target. ICS structured task forces may be an important tool in addressing specific challenges within a healthcare system. [ABSTRACT FROM AUTHOR]

In an era marked by the increasing frequency of major natural and manmade disasters, the imperative for effective disaster recovery planning and response has never been more pronounced. As communities grapple with the aftermath of hurricanes, earthquakes, wildfires, pandemics and other crises and emergencies, the integration of innovation technologies has emerged as a beacon of hope for more resilient and efficient recovery efforts. Standing at the forefront of this technological revolution is artificial intelligence (AI) — a transformative force with the potential to revolutionise every facet of disaster recovery. While the benefits are substantial, challenges in AI implementation are evident. These challenges underscore the need for continuous research and development efforts to unlock the full spectrum of AI's potential benefits. The journey toward harnessing AI in disaster recovery is dynamic, requiring ongoing innovation to overcome existing limitations. Navigating the evolving systems of AI in disaster recovery planning, the amalgamation of benefits, challenges and ongoing evolution underscores the pivotal role that AI plays in shaping the future of resilient disaster response. This paper identifies where AI can play the most significant positive role for disaster recovery. [ABSTRACT FROM AUTHOR]

This paper examines how Stanford Hospital, a Level I trauma centre serving the metropolitan region of California's Bay Area, manages an acute surge of patients from a mass casualty incident, specifically within the context of the crowded and overburdened US emergency medicine system. The authors offer practical considerations for the rapid creation of space and bandwidth during an acute surge of injured patients as well as best practices for reorganising daily systems to care for those patients efficiently. The study also discusses how past mass casualty incidents were examined for lessons learned in order to build and refine the response plan at Stanford Hospital, with input from a multidisciplinary committee. [ABSTRACT FROM AUTHOR]

The Province of Nova Scotia has a broad range of responsibilities during provincial emergencies. Hurricane Fiona had significant impacts on citizens and government services for a considerable time due to widespread telecommunication and power outages. The spring wildfires caused widespread destruction, presented coordination and logistical problems, and resulted in mental health impacts for affected communities and responders. This paper describes the challenges faced by provincial emergency management and business continuity response teams: 1) mental health matters — the next evolution in business continuity requires building confidence in people executing the plan under stressful and uncertain conditions for extended periods; 2) senior leadership support is vital to balance business continuity priorities with ongoing operational business demands; and 3) the best plans are as effective as the relationships that make them work. The importance and value of individual and team relationships during planning, preparedness and response, therefore, cannot be underestimated. [ABSTRACT FROM AUTHOR]

There is growing evidence that climate change adversely affects human health. Multiple diseases are sensitive to climate change, including cardiovascular diseases (CVDs), which are also the leading cause of death globally. Countries such as India face a compounded challenge, with a growing burden of CVDs and a high vulnerability to climate change, requiring a co-ordinated, multi-sectoral response. In this framework synthesis, we analysed whether and how CVDs are addressed with respect to climate change in the Indian policy space. We identified 10 relevant national-level policies, which were analysed using the framework method. Our analytical framework consisted of four themes: (1) political commitment; (2) health information systems; (3) capacity building; and (4) cross-sectoral actions. Additionally, we analysed a subset of these policies and 29 state-level climate change and health action plans using content analysis to identify health priorities. Our analyses revealed a political commitment in addressing the health impacts of climate change; however, CVDs were poorly contextualized with most of the efforts focusing on vector-borne and other communicable diseases, despite their recognized burden. Heat-related illnesses and cardiopulmonary diseases were also focused on but failed to encompass the most climate-sensitive aspects. CVDs are insufficiently addressed in the existing surveillance systems, despite being mentioned in several policies and interventions, including emergency preparedness in hospitals and cross-sectoral actions. CVDs are mentioned as a separate section in only a small number of state-level plans, several of which need an impetus to complete and include CVD-specific sections. We also found several climate-health policies for specific diseases, albeit not for CVDs. This study identified important gaps in India's disease-specific climate change response and might aid policymakers in strengthening future versions of these policies and boost research and context-specific interventions on climate change and CVDs. [ABSTRACT FROM AUTHOR]

Emergency evacuations involve a complex interaction between different stress-related factors (encompassing both human behavior and physical infrastructure) and associated responses. Utilizing the unity real-time development platform, this research examines these dynamics by exploring diverse aspects of evacuation, such as psychological traits and their interaction with physical infrastructure elements such as building layout, exit options, and crowd density. A single-story workspace at Marshall University was used as a case study. The findings reveal that individual human traits, behaviors, and interactions significantly impact evacuation success, often more than the physical infrastructure features themselves. Moreover, there is potential for the coupling effect where multiple stress inducing and/or reducing factors may act together and increase and/or decrease evacuation efficiency. In essence, this study underscores the complexity of human behavior under stress, emphasizing the importance of considering related factors in evacuation models to simulate realistic scenarios accurately. These insights, validated by subject matter experts for general applicability across various workplace setups, can help organizations enhance their emergency management strategies, resulting in more effective systems, better-prepared personnel, and more adaptive responses to different stressors. [ABSTRACT FROM AUTHOR]

In this study, full-scale fire experiments and numerical simulations of the underground powerhouse of a hydropower station during the construction stage were performed to investigate the temperature distribution and smoke propagation. The characteristic of inverse ambient temperature in the vertical direction was discovered, resulting in the vertical movement of smoke differing from that in a uniform temperature environment. The maximum temperature increase appeared at non-highest points. Smoke characteristic parameters such as smoke settlement height and temperature increase were discussed at different heat release rates (HRRs) of fire sources to determine the fire risk distribution of the powerhouse. Two ventilation modes were proposed, and their smoke control effects were compared. The optimal ventilation mode and volume in different fire scenarios were proposed. The findings offer scenario and data support for fire smoke control and emergency plan design in powerhouses of hydropower stations. [ABSTRACT FROM AUTHOR]

When faced with a financial emergency, households have a number of ways to respond. In the most recent version of the U.S. Survey of Consumer Finances, a variable was added that asked whether households would consider increased work as a response. This paper examines how economic and demographic factors affect the response to that question. [ABSTRACT FROM AUTHOR]

In this article we analyzed the international legal experience of implementing measures to ensure criminal proceedings in the conditions of special periods, and we formulated proposals for improving this area of legal regulation in the criminal process of Ukraine. We highlighted the experiences of Lithuania, Estonia, Armenia and Turkey regarding detention and detention during special periods. We investigated how courts provided during special periods in Estonia, Latvia, Georgia, Turkey, France and Ukraine. We have described the regulatory and legal regulation of Latvia, Lithuania and Estonia regarding some aspects of the criminal process in the conditions of special periods of legislation. We have studied the legislation of Latvia, which specifies the choice of the simplest type of criminal process during martial law. We think that corresponds to the specific circumstances of the martial law and it is also the most adaptable to the circumstances of a special period and non-bureaucratized. We analyzed the specifics of the application of preventive measures against military personnel on the example of Kazakhstan, Tajikistan, Turkmenistan, Moldova, Armenia, Georgia, and Israel. We have concluded that, based on the results of the analysis of the experience of foreign countries in the implementation of measures to ensure criminal proceedings in special periods, it is possible to formulate such proposals for the improvement of the relevant sphere of legal regulation in the criminal process of Ukraine. We propose to review the duration of detention of persons in conditions of special periods - following the example of Lithuania, Estonia, Armenia and Turkey. We also plan to introduce the possibility of choosing the simplest type of criminal process that corresponds to specific circumstances - following the example of Latvia. We propose to introduce special types of preventive measures against military personnel who are able to ensure the performance of the tasks of criminal proceedings. Nevertheless, such measures should not be associated with deprivation of liberty, minimally limit rights and freedoms, and not have a negative impact on the state’s defense capability – following the example of Kazakhstan, Tajikistan, Turkmenistan, Moldova, Armenia, Georgia and Israel. [ABSTRACT FROM AUTHOR]

In order to establish principles for implementing requirements contained in legal acts regarding methods of preventing serious industrial accidents, a study of the procedures in place at NITROERG SA, a company manufacturing explosives, was conducted. The analysis also included regulations concerning actions to be taken in the event of an accident, aimed at minimizing negative impacts on people and the environment. Legislative solutions imply the necessity for business entities to submit reports to emergency services, while also carrying out a range of activities to counteract threats associated with serious accidents. This article presents how these recommendations are implemented by the company and the methods of obtaining data to improve the undertaken projects. However, incidents in recent years indicate the need for further verification of processes to eliminate risks. [ABSTRACT FROM AUTHOR]

Although demand for emotional labor (EL) is at its highest in times of disasters, there is a lack of studies on EL by disaster response and recovery workers in intercultural contexts. Using in-depth interviews and secondary data collected in Haiti, this article focuses on the link between culture and EL. We find that an understanding of the cultural context and the cultural competencies used to effectively navigate that context are central to each step of effective emotional labor performance. These findings help disaster response organizations better understand the value of cultural competence and how it effects the performance of EL. [ABSTRACT FROM AUTHOR]

This paper investigates the impact of climate change on international portfolio allocations of global funds. We select the heat wave disasters in Europe in 2018 as a quasi‐natural experiment and employ the DID framework. Our findings indicate that global funds would reduce their holdings in the affected country after heat wave disasters. The congestion of inland waterways and electricity shortages during the heatwave have resulted in production delays, thereby transmit risks to the financial sector. Countries with higher foreign exposure experience a larger scale of capital outflow after heat waves; while countries with great institutional quality and resilience demonstrate greater capacity to withstand heat wave disasters. The funds with lower risk tolerance are more sensitive to climate change. Additionally, domestic funds will remain in their home countries post‐heatwave when foreign capitals flow away. These findings have important policy implications, and countries with high climate risks should carefully monitor the capital flows. In order to reduce the impact of climate risks, it is crucial to improve the quality of institution and efficiency of government as well as to implement effective disaster prevention and mitigation measures. [ABSTRACT FROM AUTHOR]

Throughout the response phase of the disaster, the speedy restoration of transportation by reconnecting the nodes where the connection is broken is absolutely critical for evacuating civilians, providing clear access to hospitals, and distributing aid. Following a disaster, some roads in a disaster area might be closed to transportation. In reality, some roads can be blocked due to debris, and some of roads can be blocked by collapsing. In this model, different types of road unblocking methods are included, and each road can only be opened to access by a vehicle suitable for that method. So, different types of vehicles may be needed to repair the roads depending on the type of damage. In addition, fast-built bridges built both on land and over water are also used if necessary following a disaster. In problems of this nature, it is essential to restore the roads to enable the complete connectivity of the network such that all nodes can be reached by one another. In addition, it is also critical for the speedy reach of critical nodes, such as hospitals, and emergency disaster centers. This study aims to reduce the maximum time for connection and minimize the total time in which to reach critical nodes. For this purpose, we developed a bi-objective mathematical model that considers the multiple vehicle types that can repair different types of damages. Since the problem is NP-hard, two heuristic methods were developed, and the numerical results were presented. It has been observed that the local search algorithm gives better results than the hybrid algorithm. Additionally, different scenario data was produced. Numbers of unconnected components from 3 to 10 are solved with heuristic algorithms for test data containing 80 and 250 nodes, and real-life data containing 223 nodes and 391 edges are solved with heuristic algorithms for the number of unconnected components 6, 9, 12, and 15. [ABSTRACT FROM AUTHOR]

The evolution of hazardous chemical accidents (HCAs) is characterized by uncertainty and complexity. It is challenging for decision‐makers to expeditiously adapt emergency response plans in response to dynamically changing scenario states. This study proposes a data‐driven methodology for constructing accident scenarios and develops a novel hybrid deep learning model for scenario deduction analysis. This model aids in accurately predicting the evolution of HCAs, enabling emergency responders to prepare and implement targeted interventions proactively. First, a framework for constructing an accident scenario database is presented, based on the time‐sequential characteristics of accident progression. This framework employs a data‐driven approach to describe the evolution process of accident scenarios. Second, a deep learning model (CNN‐LSTM‐Attention) that integrates convolutional neural network (CNN), long short‐term memory (LSTM), and attention mechanism (AM) is developed for accident scenario deduction analysis. Finally, to illustrate practical application, a scenario database for HCAs is established. A major HCA case study is conducted to demonstrate the ability of this model to analyze various scenarios, thereby improving emergency decision‐making efficiency. Compared with algorithms such as CNN, LSTM, and CNN‐LSTM, the prediction accuracy of this method ranges from 86% to 93%, signifying an improvement of over 7%. This work provides a reliable framework for supporting decision‐making in emergency management. [ABSTRACT FROM AUTHOR]

Real-time multi-criteria decision-making applications in fields like high-speed algorithmic trading, emergency response, and disaster management have driven the development of new types of preference queries. This is an example of a skyline search. Multi-criteria decision-making utilizes the skyline operator to extract highly significant tuples or useful data points from extensive sets of multi-dimensional databases. The user's settings determine the results, which include all tuples whose attribute vector remains undefeated by another tuple. The extracted tuples are commonly known as the skyline set. Lately, there has been a growing trend in research studies to perform skyline queries on data stream applications. These queries consist of extracting desired records from sliding windows and removing outdated records from incoming data sets that do not meet user requirements. The datasets in these applications are extremely large and exhibit a wide range of dimensions that vary over time. Consequently, the skyline query is considered a computationally demanding task, with the challenge of achieving a real-time response within an acceptable duration. We must transport and process enormous quantities of data. Traditional skyline algorithms have faced new challenges due to limitations in data transmission bandwidth and latency. The transfer of vast quantities of data would affect performance, power efficiency, and reliability. Consequently, it is imperative to make alterations to the computer paradigm. Parallel skyline queries have attracted the attention of both scholars and the business sector. The study of skyline queries has focused on sequential algorithms and parallel implementations for multicore processors, primarily due to their widespread use. While previous research has focused on sequential algorithms, there is a limitation to comprehensive studies that specifically address modern parallel processors. While numerous articles have been published regarding the parallelization of regular skyline queries, there is a limited amount of research dedicated specifically to the parallel processing of continuous skyline queries. This study introduces PRSS, a continuous skyline technique for multicore processors specifically designed for sliding window-based data streams. The efficacy of the proposed parallel implementation is demonstrated through tests conducted on both real-world and synthetic datasets, encompassing various point distributions, arrival rates, and window widths. The experimental results for a dataset characterized by a large number of dimensions and cardinality demonstrate significant acceleration. [ABSTRACT FROM AUTHOR]

Effective coordination, networking, and voluntary civil engagement are crucial for ensuring effective disaster responses. It should be noted, however, that these recommendations are primarily derived from the experiences of Western pluralistic countries. Thus, there has been insufficient consideration given to the applicability of these recommendations to non-pluralistic countries and the ways in which non-Western authoritarian countries navigate the difficulties of coordinating and establishing networks with civil sector organizations. This study broadens the scope of research by examining non-Western authoritarian countries through an analysis of how China responded to the floods of 2020. The results of the study indicate that the Chinese flood response system was primarily government-driven, centralized, and hierarchical. According to the pluralistic model, this arrangement encounters difficulties in integrating resources and information from partners in different sectors and jurisdictions. Consequently, this poses additional challenges to the Chinese disaster response systems. Nevertheless, the study findings reveal that the Chinese system proficiently resolved problems. This was accomplished by flattening the hierarchical structure via innovative interventions and remedying the lack of voluntary civic sector engagement through mass mobilization. Consequently, it would be fallacious to hold that the pluralist model can be effortlessly transplanted to non-Western authoritarian nations without regard for their distinct political, cultural, economic, and social contexts. Points for practitioners: To improve disaster response, practitioners should consider adapting hierarchical networks and embracing flexibility. This can be achieved by reducing bureaucratic layers, which enhances effectiveness and encourages innovative interventions for streamlined decision making. It is important to emphasize provincial–local support and mass mobilization, as seen in China, which underscores the need for engaging civil sectors in non-pluralistic contexts. Context-specific approaches are crucial and should consider political, cultural, and social factors. Transforming hierarchical structures into modular networks may improve response. [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]

The article offers an examination of augmented reality (AR)-assisted disaster preparedness guidelines designed to improve public awareness and engagement. Topics include the use of AR to enhance disaster preparedness by incorporating object recognition for environmental hazard identification, a comparison of AR-based guidelines with traditional paper-based ones in terms of usability and task performance, and the findings from testing these interfaces across different age groups.

This study attempted to determine the impact of school disaster risk reduction and management program in public schools in Angono, Rizal for school year 2023 -2024 which served as basis to develop an enhanced contingency plan. The method of research used was the descriptive type of research with the questionnaire as the data gathering instrument. The respondents who rated the nine (9) schools principals, SDRRM coordinators non-teaching personnel, thirty (30) teachers and PTA officers of the nine public school in Angono, Rizal with a total of 442. The findings revealed that the teaching personnel and the SH/DRRMC/NTP respondents rated the impact of Prevention and Mitigation, Preparedness, disaster response and recovery and rehabilitation the grand weighted mean of 3.50and 3.64 respectively with verbal interpretation of strongly agree while the PTA officers -respondents rated the four aspects of grand weighted mean of 3.42 verbally interpreted as agree. Meanwhile, the perceptions of the teaching personnel and the SH/DRRMC/NTP on the challenges encountered on SDRR Program got the grand weighted mean of 3.54 and 3. 65 which interpreted as strongly agree. Meanwhile, PTA officer- respondents rated the four aspects as Agree with grand weighted mean of 3.49. Furthermore, there is a relationship between the impact of disaster risk reduction and management programs as regards preparedness, disaster response and recovery and rehabilitation and the challenges encountered by school. [ABSTRACT FROM AUTHOR]

With an estimated 357.7 million internal displacements caused since 2008, weather-related disasters are a major driver of human mobility worldwide. As climate change is projected to increase the frequency and intensity of extreme weather events in many parts of the world, it is important to better understand how trends in weather patterns related to global warming have affected the intensity of disasters that have caused displacements. Here we combined observational and counterfactual climate data with global internal displacement records to estimate how climate change has affected precipitation and wind speeds at the time and location of floods and storms that led to internal displacements. We estimate that, on average, climate change increased precipitation and decreased wind speeds during such events by +3.7% and − 1.4%, respectively. However, the variability across events is considerable (±28.6 and ± 6.6%, respectively), highlighting the large signal of natural variability of the weather system as compared to the global warming signal. Our results caution against overstating the role of climate change in displacement-inducing disasters in the past, especially compared to socio-economic and development factors of vulnerability and adaptive capacity that determine whether weather-related hazards turn into disasters.' [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]

Vanuatu is located within the Pacific Ring of Fire, known for its intense tectonic activity. The country is highly vulnerable to natural disasters, affecting about 12% of the population and causing an average loss of 42.8% of GDP. Internal displacement of population is one of the elements of the strategy to adapt to the consequences of climate change and natural disasters. This article, based on government documents and legislative acts, examines the national policy of the Republic of Vanuatu on climate change and natural disasters, analyzing it to highlight relevant aspects for Ukraine that, after critical reflection and thorough study, should be considered when developing appropriate legislation in Ukraine. It was found that the basis of this policy consists of the following documents: «National Sustainable Development Plan for 2016-2030», «Vanuatu Climate Change and Disaster Risk Reduction Policy for 2016-2030», «National Adaptation Program of Action», «Disaster Risk Management Act No. 23 of 2019», «Meteorology, Geological Hazards and Climate Change Act No. 25 of 2016», «Vanuatu's Revised and Enhanced 1ST Nationally Determined Contribution», «National Policy on Climate Change and Disaster-Induced Displacement». From the perspective of legal support for the rights of displaced persons and the regulation of this process, the most important act is the «National Policy on Climate Change and Disaster-Induced Displacement», which ensures the functioning of institutions involved in planning potential emergencies and combating their consequences, in cooperation with the government of Vanuatu to meet the needs of all affected displaced communities and host communities, including different types of displaced persons: controlled displaced, internal migrants, residents of informal settlements, as well as those threatened with displacement. It is noted that displacement occurs in accordance with international law, with mandatory adherence to fundamental human rights. Considering the limited possibilities for population displacement due to the geomorphological structure of the islands of the Republic of Vanuatu, the efforts of the government of the country are concentrated on disaster prevention and climate change control measures. This is the focus of other important foundational documents of national environmental policy, the analysis of which indicates the construction of a successful system of state management of processes, synergy between the public sector and non-governmental organizations involved, and innovative methods of economic reform. The reviewed documents address a wide range of problems caused by climate change, containing solutions that are undoubtedly useful for legislators, politicians, and executive authorities of many countries, including Ukraine. [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]

Climate change has intensified flooding and increased localized torrential rainfalls, leading to disasters such as landslides, infrastructure collapse, and urban floods. The extent and accuracy of flood damage information significantly impact recovery processes. While previous studies primarily utilized satellite and aerial imagery for broad flood assessments, they often lacked the precision needed for accurate damage analysis. This study addresses the gap between rapid assessment needs and precise damage quantification in flood inundation analysis. This research introduces a novel image-based investigation approach to enhance the speed and accuracy of flood inundation assessment. By leveraging unmanned aerial vehicles (UAVs) and image-based spatial data technology, aerial images of flooded areas are rapidly captured to construct three-dimensional disaster site terrain information. The proposed methodology employs advanced techniques in aerial photography, image processing, and geographic analysis to quantitatively analyze flood inundation scale using only aerial images and geographic information systems (GIS). The research yielded a calculated flood inundation area of 3,847.36 m2 and a flood volume of 13,895.13 m3. This methodology complements existing flood inundation assessment techniques and has the potential to significantly improve disaster management efforts by providing rapid, accurate, and actionable data for decision-makers. [ABSTRACT FROM AUTHOR]

Disasters occur during unanticipated events, in which immediate responses are needed under the process of rescue and relief operations. Rescuers play an important role during disasters and catastrophes, they ensure that public safety is prioritized. Rescuers deal with various rescue operations, and it was evident that they have faced challenging experiences going through emergencies and disaster responses. Although these duties are essential to the community, they are taxing on rescuers and increase their risk of trauma over time which may lead to poor performance at work, job dissatisfaction, and sleep deprivation. emergencies are unpredictable and cause destructive effects on our society, it has become an important research project in the field of crisis management for the development of scientific coping mechanisms and to improve rescuers' resilience. Psychological distress was experienced during disasters which affected the rescuers emotionally. Given that emergencies are unpredictable and cause destructive effects on our society, it has become an important research project in the field of crisis management for the development of scientific coping mechanisms and to improve rescuers' resilience. [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]

Precipitation nowcasting, which is critical for flood emergency and river management, has remained challenging for decades, although recent developments in deep generative modeling (DGM) suggest the possibility of improvements. River management centers, such as the Tennessee Valley Authority, have been using Numerical Weather Prediction (NWP) models for nowcasting, but they have been struggling with missed detections even from best-in-class NWP models. While decades of prior research achieved limited improvements beyond advection and localized evolution, recent attempts have shown progress from so-called physics-free machine learning (ML) methods, and even greater improvements from physics-embedded ML approaches. Developers of DGM for nowcasting have compared their approaches with optical flow (a variant of advection) and meteorologists' judgment, but not with NWP models. Further, they have not conducted independent co-evaluations with water resources and river managers. Here we show that the state-of-the-art physics-embedded deep generative model, specifically NowcastNet, outperforms the High Resolution Rapid Refresh (HRRR) model, which is the latest generation of NWP, along with advection and persistence, especially for heavy precipitation events. Thus, for grid-cell extremes over 16 mm/h, NowcastNet demonstrated a median critical success index (CSI) of 0.30, compared with median CSI of 0.04 for HRRR. However, despite hydrologically-relevant improvements in point-by-point forecasts from NowcastNet, caveats include overestimation of spatially aggregate precipitation over longer lead times. Our co-evaluation with ML developers, hydrologists and river managers suggest the possibility of improved flood emergency response and hydropower management. [ABSTRACT FROM AUTHOR]