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Flood detection from synthetic aperture radar (SAR) imagery plays an important role in crisis and disaster management. Based on pre- and post-flood SAR images, flooded areas can be extracted by detecting changes of water bodies. Existing state-of-the-art change detection methods primarily target optical image pairs. The nature of SAR images, such as scarce visual information, similar backscatter signals, and ubiquitous speckle noise, pose great challenges to identifying water bodies and mining change features, thus resulting in unsatisfactory performance. Besides, the lack of large-scale annotated datasets hinders the development of accurate flood detection methods. In this paper, we focus on the difference between SAR image pairs and present a differential attention metric-based network (DAM-Net), to achieve flood detection. By introducing feature interaction during temporal-wise feature representation, we guide the model to focus on changes of interest rather than fully understanding the scene of the image. On the other hand, we devise a class token to capture high-level semantic information about water body changes, increasing the ability to distinguish water body changes and pseudo changes caused by similar signals or speckle noise. To better train and evaluate DAM-Net, we create a large-scale flood detection dataset using Sentinel-1 SAR imagery, namely S1GFloods. This dataset consists of 5,360 image pairs, covering 46 flood events during 2015–2022, and spanning 6 continents of the world. The experimental results on this dataset demonstrate that our method outperforms several advanced change detection methods. DAM-Net achieves 97.8% overall accuracy, 96.5% F1, and 93.2% IoU on the test set. Our dataset and code are available at https://github.com/Tamer-Saleh/S1GFlood-Detection. [ABSTRACT FROM AUTHOR]

Visual geo-localization enables the UAV to know its position in GNSS-denied application scenarios, such as disaster emergency response, forest inventory management and indoor facility monitoring. However, there are still some challenges in using oblique-view imagery, especially for UAV images with large oblique viewing angles, to perform visual geo-localization. On the one hand, using geotags of references as image-level geo-localization results is insufficient for oblique-view imagery, because the UAV is often situated at a distance and not directly over the observation area. On the other hand, the obvious differences in viewpoint, viewing angle, and scale between UAV oblique-view images and geo-tagged orthographic reference images severely limit the accuracy of all three steps in pixel-level geo-localization, including image-based retrieval, matching and space resection. In this study, we proposed a coarse-to-fine visual geo-localization method to address these challenges for UAV position determination using oblique-view imagery, assisted by orthographic references. Firstly, we proposed a novel image-level geo-localization method by employing Segments Direction Statistics (SDS) feature patterns and bilateral retrieval strategy. Secondly, we matched UAV oblique-view images with geo-tagged orthographic reference images using feature points and descriptors extracted by the improved SuperPoint network, incorporating the Discrete Gaussian Pyramid Module (DGPM) and the Two-stage Matching Results Refinement Module (TMRRM). Thirdly, based on the matched points with 2D pixel coordinates and 3D ground coordinates, we adopted the triangular pyramid constrained resection method with angle similarity constraints to accurately determine the pixel-level position of UAV. We conducted experiments using a publicly available multi-view images dataset (University-1652), as well as two self-collected datasets of oblique-view images captured by UAVs. Experiments indicate that the localization error of the proposed method is less than 0.1 m for applications with the flight height about 200 m. Meanwhile, the error is about 10 m for UAVs with extremely high flight height (more than 4 km) and large oblique viewing angle (more than 60°). And the average time cost of the proposed method is about 400 ms. Therefore, experimental results demonstrated the effectiveness and efficiency of the proposed method in automatically obtaining reliable UAV positions using oblique-view imagery, as well as its robustness for various UAV oblique-view image-based applications. [ABSTRACT FROM AUTHOR]

Previous studies show that the COVID-19 pandemic affected the number of surgeries performed. However, data on the association between the COVID-19 pandemic and otolaryngologic surgeries according to subspecialties are lacking. This study was performed to evaluate the impact of the COVID-19 pandemic on various types of otolaryngologic surgeries. Methods. We retrospectively identified patients who underwent otolaryngologic surgeries from April 2018 to February 2021 using a Japanese national inpatient database. We performed interrupted time-series analyses before and after April 2020 to evaluate the number of otolaryngologic surgeries performed. The Japanese government declared its first state of emergency during the COVID-19 pandemic in April 2020. We obtained data on 348,351 otolaryngologic surgeries. Interrupted time-series analysis showed a significant decrease in the number of overall otolaryngologic surgeries in April 2020 (-3619 surgeries per month; 95% confidence interval, -5555 to -1683; p < 0.001). Removal of foreign bodies and head and neck cancer surgery were not affected by the COVID-19 pandemic. In the post-COVID-19 period, the number of otolaryngologic surgeries, except for ear and upper airway surgeries, increased significantly. The number of tracheostomies and peritonsillar abscess incisions did not significantly decrease during the COVID-19 pandemic. The COVID-19 pandemic was associated with a decrease in the overall number of otolaryngologic surgeries, but the trend differed among subspecialties. [ABSTRACT FROM AUTHOR]

Burn mass casualty incident (BMCI) preparedness is lacking across Canada. A focused exploration of the current policies, protocols and practices in Alberta that address the response to a BMCI was conducted. In this case study, data were gathered from documents outlining the health system response to a mass casualty incident and health care professionals directly involved. Interviews were conducted online, recorded and transcribed. Qualitative description was used to code common themes across documents and transcripts. Fifteen documents and nine participant interviews were included in this study. Overall, the current policies, protocols and practices in place were limited to all-hazards mass casualty incident planning and did not address the specialized needs of burn patients. Deficiencies included no burn-specific plan at each of the two burn centres, a lack of provincial-level recognition of the unique challenges associated with a BMCI and no established Canadian burn disaster communication plan. Suggestions of strategies for a burn plan included forward triage, patient movement, use of telemedicine, partnering skilled and non-skilled staff, and procuring additional supplies. For best patient outcomes the provincial health authority needs to provide dedicated time for burn care experts to develop BMCI response plans to better address this unique hazard. • All hazards mass casualty (MC) plans do not work for multiple burn injured patients. • Participant communication and decision-making practices deviated from the MC plan. • Participants expressed concerns about the overall ability to respond to a burn MC. • Creating burn capacity includes strategies for space, staffing, and supplies needed. [ABSTRACT FROM AUTHOR]

Extracting building footprints from extensive very-high spatial resolution (VHSR) remote sensing data is crucial for diverse applications, including surveying, urban studies, population estimation, identification of informal settlements, and disaster management. Although convolutional neural networks (CNNs) are commonly utilized for this purpose, their effectiveness is constrained by limitations in capturing long-range relationships and contextual details due to the localized nature of convolution operations. This study introduces the masked-attention mask transformer (Mask2Former), based on the Swin Transformer, for building footprint extraction from large-scale satellite imagery. To enhance the capture of large-scale semantic information and extract multiscale features, a hierarchical vision transformer with shifted windows (Swin Transformer) serves as the backbone network. An extensive analysis compares the efficiency and generalizability of Mask2Former with four CNN models (PSPNet, DeepLabV3+, UpperNet-ConvNext, and SegNeXt) and two transformer-based models (UpperNet-Swin and SegFormer) featuring different complexities. Results reveal superior performance of transformer-based models over CNN-based counterparts, showcasing exceptional generalization across diverse testing areas with varying building structures, heights, and sizes. Specifically, Mask2Former with the Swin transformer backbone achieves a mean intersection over union between 88% and 93%, along with a mean F-score (mF-score) ranging from 91% to 96.35% across various urban landscapes. [ABSTRACT FROM AUTHOR]

Practitioners can face significant challenges when managing the airways of infants and neonates because of their unique anatomical and physiological features. The requirement for emergency airway management in this age group is rare. Details of emergency airway techniques in paediatric practice guidelines are missing or lack consensus, and it is known that outcomes for affected children can be poor. Ideally, these children should be managed by experienced paediatric airway practitioners working in a team. However, situations can arise where practitioners, unfamiliar and inexperienced with infants, find themselves in charge. So, what happens when such a practitioner encounters this life-or-death scenario and feels ill-equipped to act? The ethical and legal issues surrounding the management of this emergency are clearly defined, but they can be unknown or misunderstood by doctors. Compounding the extreme stress of the scenario is the moral and ethical dilemma of whether to act or not. The following discussion explores these issues and examines the philosophical and psychological perspectives. [ABSTRACT FROM AUTHOR]

As large-scale disasters continue to become increasingly common worldwide, nursing homes, whose residents are more vulnerable to disaster-related health and psychosocial shocks, and their staff, are carrying progressively more responsibility for health care readiness practices. Implementation science is a research discipline that seeks to improve uptake of evidence-based practices, such as health care readiness planning, and thus has potential to improve nursing home care delivery during and after disasters. We describe the limited field of existing evidence-based strategies in the peer-reviewed literature that seek to advance health care readiness in the nursing home setting and illustrate how implementation science can better support health care readiness planning for nursing homes. We rest on 3 main themes: (1) implementation science frameworks can strengthen nursing home staff engagement around health care readiness; (2) implementation science can support tailoring of emergency preparedness plans to individual nursing homes' unique needs; and (3) implementation science can advance the integration of nursing homes into local, state, and federal health care readiness planning initiatives. Finally, research is urgently needed to both generate and disseminate implementation strategies that increase uptake of evidence-based health care readiness practices in the nursing home setting. [ABSTRACT FROM AUTHOR]

[Display omitted] • Fusion of varied data sources are used to develop more informed flood extent maps. • SVM outscored the MLE, RF, Iso cluster, and Otsu's algorithms in all strategies. • PCA-based technique outperforms the other three approaches. • First and Second approaches performed better in VV than VH polarisation. Accurate and timely mapping of flood extent is crucial for effective disaster response and management. However, existing methods often face challenges in integrating diverse data sources and leveraging advanced techniques for precise inundation mapping. This research aimed to address this gap by proposing and evaluating four different methods for improving flood extent mapping in Sindh, Pakistan, by integrating various data sources, including precipitation, Synthetic Aperture Radar (SAR), buildings, population, and optical data. The first strategy involves categorizing post-flood SAR data immediately using non-parametric (Support Vector Machine (SVM) and Random Forest (RF)), parametric (Maximum Likelihood Estimation (MLE)), and cluster (ISO) algorithms for Vertical transmit and Vertical received (VV) and Vertical transmit and Horizontal received (VH) polarisations. The second method relies on Otsu's method for automatic thresholding on post-flood event VH and VV data. The third approach utilizes both pre- and post-flood event data by creating a stack of Pre-event VH, Pre-event VV, Post-event VH, and Post-event VV data, which is then classified using the SVM, RF, MLE, and ISO algorithms. Lastly, the fourth method employs the stack of Principal Component Analysis (PCA) bands, consisting of PCA components 1, 2, and 3, to categorize data for flooding using the SVM, RF, MLE, and ISO algorithms. The rationale behind evaluating these diverse methods was to identify the most effective approach for accurately mapping flood extent by exploiting the strengths of different algorithms and data processing techniques. The accuracy and precision of these approaches were rigorously evaluated using Landsat-9 Normalized Difference Water Index (NDWI) as a reference dataset, along with error matrix and compound value (C v) metrics. The findings show that a PCA-based technique with SVM is marginally superior (based on the overall accuracy and Kappa coefficient with a value of 92.20 % and kappa coefficient 0.821) than the other approaches tested in the study. By reducing the dimensionality of the dataset while preserving relevant information, PCA offers a computationally efficient approach to flood extent mapping. Among all the approaches, the collective performance of the algorithms was computed using the C v metric. The SVM algorithm with a C v of 1.25 demonstrated the best performance, followed by the RF algorithm with C v of 1.5, and the MLE algorithm with C v of 2.5. The worst performing algorithm among all is found to be ISO with C v of 4. It comes into view that first and second approach underperformed in VH polarisation compared to the VV polarisation and provide a more accurate representation of flooded area in VV polarisation. The flood extent with highest accuracy, together with the world's gridded population, latest Microsoft's Global ML Building Footprints, and OpenStreetMap building data are used in conjunction to estimate the number of people and buildings at risk within the study area. [ABSTRACT FROM AUTHOR]

It is the position of the Society for Nutrition Education and Behavior that for effective recovery from and resilience to disasters, it is essential that impacted individuals and communities have access to safe, nutritious, and culturally and contextually appropriate foods and beverages, and receive emergency-related food and nutrition education before, during, and after a disaster. Despite the increasing number, duration, and intensity of disasters worldwide, there is relatively limited guidance for research, policy, and practice about addressing the emergency-related food and nutrition needs of affected populations. Although nutrition emergencies tend to be understudied, emerging efforts are working to advance food and nutrition security during disaster response and recovery. To help elevate the importance of emergency-related food and nutrition education before, during, and after a disaster, Society for Nutrition Education and Behavior, which represents the unique professional interests of nutrition educators worldwide, summarizes the relevant literature and puts forth recommendations for all those who are engaged in this work in the following 4 key areas: (1) improving communication and outreach, (2) fostering community engagement and locally-driven preparedness, (3) building the evidence base and translating the evidence into action, and (4) training current professionals and the next generation of public health leaders. Altogether, before, during, and after a disaster, those who engage in this work, among other allies, can help elevate the importance of nutrition education and other strategies to promote healthy eating behaviors through research, policy, and practice. [ABSTRACT FROM AUTHOR]

Emerging evidence suggests that nonadherence to treatment guidelines for seizures may affect patient outcomes. We examined the feasibility of conducting a larger investigation to test this hypothesis in the pediatric population. We retrospectively reviewed charts of patients aged ≤18 years who presented with seizure to the emergency departments of two Ontario hospitals in 2019 to 2021. Patients were grouped by seizure duration (<5 minutes [n = 37], ≥5 minutes [n = 41]). We examined nonadherence to guideline-recommended treatment, adverse outcomes (hospitalization, length of stay, respiratory complications), and missing values for key variables. Of 78 patients, 34 (44%) did not receive guideline-recommended treatment. Nonadherence was similar in the two groups (<5 minutes: 46%; ≥5 minutes: 41%). Common deviations included administering an antiseizure medication (ASM) for seizures of less than five minutes (46%), a delay (>10 minutes) between the first and second ASM doses (50%), and use of a benzodiazepine for the third dose (45%). Hospitalizations were common in both seizure duration groups (∼90%), whereas respiratory complications were relatively rare. Time of seizure onset was missing in 51% of charts, and none contained the time of first contact with emergency services when patients were transported by ambulance. We found evidence of substantial nonadherence to guideline-recommended treatment of pediatric seizures. Medical records do not contain sufficient information to comprehensively investigate this issue. A multicenter prospective study is the most feasible option to examine the association between nonadherence to guideline-recommended treatment and patient outcomes. [ABSTRACT FROM AUTHOR]

In an industry known for its workplace hazards, such as the management and manipulation of animals that could bite, kick or cause considerable damage simply because of their size, combined with long working hours, lifting of heavy loads and the general mental stress, it is perhaps surprising that the veterinary industry is not also known for its safety culture and structures. One would expect that where such hazards and risks have been identified, there would be many and varied levels of education on risk and hazard management, a comprehensive set of tools with which to mitigate these risks as well as discussion and debriefing of significant adverse events to ensure they do not occur again. One would also assume that there would be a strong sense of safety culture in the workplace and that personnel would expect each other to ensure that the health and safety of themselves and their colleagues was a number one priority. Yet, is this the case in the veterinary industry? A request was made by the Association of Veterinary Anaesthetists (AVA) to provide 'safety guidelines' for use in general practice, particularly pertaining to pregnancy. The AVA set up a task force to address these concerns and to determine if guidelines could be created. This article is offered as a starting point for considering safety in the veterinary industry in a broad sense, with the hope that in the future there may be development of such guidelines. It is hoped that this article also provides the stimulus for further research in this area. [ABSTRACT FROM AUTHOR]

Hydrogen refueling stations (HRSs) play a vital role in the hydrogen energy industry and are being built worldwide. However, the potential risk of hydrogen leakage poses a significant challenge. Accurately predicting the consequences of such accidents is crucial for effective mitigation. Traditional methods, like numerical simulation, provide accurate results but lack timely predictions. To address this, we propose a hybrid surrogate model that combines Generative Adversarial Network (GAN) and Long Short-Term Memory Network (LSTM), incorporating Deep Neural Network (DNN) for predicting hydrogen leakage consequences in HRSs based on source parameters. The surrogate model was trained using training samples generated through numerical simulation. Reduced-scale experiments were conducted to verify the results of numerical simulations and assess the surrogate model's generalization ability. Results demonstrate the model's ability to predict hydrogen distribution after an accident, indicating its potential for real-time decision making in emergency response plans. • Hybrid GAN and LSTM surrogate model for accident consequence prediction in HRS. • Fused DNN enables consequence prediction based on leakage source parameters. • Training surrogate models using results from numerical simulation. • Generalizability of surrogate model was verified using reduced-scale experiments. [ABSTRACT FROM AUTHOR]

Postpartum depression (PPD) is an illness that is difficult for the affected women themselves to recognize. Moreover, many mothers believe that mothers should not complain about the mental difficulties of taking care of their children. Therefore, in addition to self-evaluation for PPD, evaluation from others is also necessary. We aimed to develop a novel measure to screen for PPD based on a parent-rating scale that is administered to the parents of postpartum mothers. The 15-item maternity-monitoring scale by parents (MMSP) was designed and applied to the feasibility cohort (n = 61) and the emergency cohort (n = 55). The Edinburgh Postnatal Depression Scale (EPDS) (threshold score of 8/9) was used to evaluate a high risk of PPD. An egogram-based index, the over-adaptation index for depression (OAID), was performed along with the EPDS and MMSP. In the feasibility cohort, MMSP was moderately correlated with EPDS. In the emergency cohort, under the circumstance of the state of emergency declaration over the coronavirus disease 2019 in Japan, application of the MMSP was delayed, resulting in the proportion of parents who overlooked PPD symptoms in their daughters increasing from 33 % to 50 %. Our findings suggest that a novel approach of parent-rated PDD screening of postpartum women is potentially possible, and the MMSP is a potential candidate for screening. Moreover, the OAID is also helpful in identifying women with hidden PPD, along with the EPDS. The performance of the MMSP should be confirmed in the parents of patients with PPD diagnosed by psychiatrists. • The Edinburgh Postnatal Depression Scale (EPDS) has been the most used measurement of PPD, but required greater precision. The novel approach, parent-rating depression screening MMSP and over-adaptation index for depression OAID, are helpful to distinguish PPD. The MMSP, followed by a composite measure constructed using the EPDS and OAID, will broadly contribute to the screening of PPD. [ABSTRACT FROM AUTHOR]

VIIRS flood products have been widely used by the National Weather Service (NWS) for river flood monitoring, and by the Federal Emergency Management Agency (FEMA) and the International Charter Program for rescue and relief efforts. However, some water bodies, like irrigated or flooded paddy rice fields, and water in seasonal wetlands, are detected as floodwater instead of permanent, seasonal, controlled, or normal water in the VIIRS flood products. Because these kinds of floodwater don't cause any severe disasters, they should be delineated as non-hazard floods to differentiate from real hazardous floods, the latter of which generally pose a significant risk and damage to human life, property, and the environment. Hazardous floods are usually caused by intensive rainfall, rapid snowmelt, or ice jams, they appear accidentally and tend to be short-term events. Non-hazard floodwaters generally result from tides, wetlands, agricultural irrigation, and other human activities, and thus they appear regularly and often stand for a longer time. Therefore, non-hazard floodwaters are some kind of standing water and usually have much larger long-time flood frequency or probability than hazardous floods. Based on this feature, it's possible to combine long-time flood frequency calculated as the ratio of total flooding days over total clear days, including both flooding and no-flooding days, from VIIRS flood products with some additional information, such as agriculture statistics and land cover and land use map, to identify non-hazard floodwater in paddy rice fields and wetland. In this study, non-hazard floodwater bodies are classified into four types: paddy rice fields, wetlands, riparian and coastal tidal flooding, and other non-hazard floods, including possible fishing ponds. In this study, we selected several examples, such as the 2023 California flood event and some large paddy rice fields in China, to demonstrate how to identify water in paddy rice fields. The Florida flood event due to Hurricane Ian in 2022 is used to demonstrate how to separate wetlands from real hazardous floods. In addition to non-hazard floodwaters in wetlands, some coastal tidal flooding in Florida is also detected. The non-hazard floodwaters extracted from the proposed methods are compared with change detection analysis and good agreement is found. The paddy rice fields obtained from this study are compared and evaluated with the rice distribution data from the USDA. The quantitative evaluation results from the confusion matrix calculation demonstrate that the accuracy is 99.96%, recall is 83.69%, precision is 61.57%, and the F1-score is 70.95%. The high accuracy indicates that the method developed in this study for paddy rice field extraction from the VIIRS flood products is feasible. [ABSTRACT FROM AUTHOR]

In the event of a fire or explosion at a hybrid hydrogen-gasoline fueling station, the consequences can be significantly more severe compared to a traditional refueling station or hydrogen refueling station. It is imperative to establish an effective assessment model specific to the hybrid station to prevent and mitigate such accidents. This paper introduces a temporal dynamic assessment model designed to evaluate the emergency response and rescue capabilities of hybrid hydrogen-gasoline fueling stations. The model is grounded in dynamic scenario construction and utilizes information-driven theory. This innovative approach allows for evaluations of the risk evolution process at different stages of an accident. The proposed assessment model combines the Temporal Weighted Average (TOWA) and Temporal Weighted Geometric Average (TOWGA) operators to integrate assessment values across different stages including the initial disaster assessment, emergency action plans, effectiveness feedback, and emergency response adjustment. This integration yields a comprehensive dynamic assessment value for the emergency response and rescue capabilities of the hybrid hydrogen-gasoline fueling station. Based on the dynamic assessment of a previously occurring accident, the specialized emergency management department performed most effectively during the incident response stage, achieving a commendable assessment value of 3.184. Following closely was the government emergency response department, with assessment values of 2.865 and 2.277. This study offers a novel analytical perspective for emergency management in hybrid hydrogen-gasoline fueling stations by incorporating the findings of both dynamic and static assessments. • The information-driven theory is introduced to form dynamic emergency response scenario construction analysis modle. • For the first time, the emergency response and rescue capacity assessment were carried out bothly at each stage of the accident. • The TOWA-TOWGA hybrid operator modle is used to evaluate the emergency response and rescue capabilities. • The assessment results can reflect various level of emergency response and rescue capability under different accident periods. [ABSTRACT FROM AUTHOR]

The exponential growth of COVID-19 cases in early 2020 presented a massive challenge for healthcare systems and called for the adaptation of emergency care routines and intensive care capacities. We, therefore, analyzed a possible impact of the COVID-19 pandemic on the general structure and emergency preparedness of burn centers in German-speaking countries through a cross-sectional descriptive survey questionnaire. The survey was conducted for the first time in January 2019 by Al-Shamsi et al. before the beginning of the COVID-19 pandemic. It was performed for a second time in November 2020 during the second wave of COVID-19 infections in German-speaking countries. We noticed a pronounced increase in the preparation for a great number of patients in need of intensive care including the enlargement of overall capacity when necessary. We also showed a notable decrease in the specific preparation for burn disasters and also reduced communication with first responders and other burn centers. To what extent these alterations were caused by the impact the pandemic had on healthcare systems could not be determined in this study and should be the subject of future research. • Increase in the preparation for a great number of patients in need of intensive care during the Covid-19 pandemic. • Increase in the ability of the burn centers to enlarge overall capacity when necessary during Covid-19 pandemic. • Decrease in the specific preparation for a burn disaster during the COVID 19 pandemic. • Reduced communication with first responders and other burn centers during the Covid 19 pandemic. [ABSTRACT FROM AUTHOR]

Hydrogen release and dispersion from hydrogen refuelling stations have the potential to cause explosion disaster and bring significant causalities and economic losses to the surroundings. Real-time spatial hydrogen plume concentration prediction is essential for the quick emergency response planning to dissipate such flammable vapor cloud and prevent explosion disaster. Deep learning approaches have recently been applied to real-time gas release and dispersion modeling, however, are 'over-confident' for spatial plume concentration and boundary estimation, which could not support the robust decision-makings. This study proposes a hybrid deep probability learning-based spatial hydrogen plume concentration prediction model, namely DPL_H 2 Plume by integrating deep learning and Variational Bayesian Inference. Numerical model of hydrogen release and dispersion from hydrogen refuelling station is built to construct the benchmark dataset. By using such dataset, two pre-defined parameters, namely Monte Carlo sampling number m = 300 and dropout probability p = 0.1 are determined to ensure the model's tradeoff between inference accuracy and efficiency. Comparison between our proposed model and the state-of-the-art model is also conducted. The results demonstrate that our model exhibits a competitive accuracy of R 2 = 0.97 as well as an inference time 3.32 s. In addition, our model gives the comprehensive estimations including not only spatial hydrogen plume concentration but also its uncertainty. Also, our model provides the more accurate estimation at plume boundary compared to the state-of-the-art model. Overall, our proposed model could provide reliable alternative for constructing a digital twin for emergency management of hydrogen refuelling station. • Deep probabilistic learning-based hydrogen plume prediction model is proposed. • Optimal hyperparameters of variational Bayesian inference are determined. • Model accurately predicts real-time spatial hydrogen plume concentration given scenario-related parameters. • Model predicts additional uncertainty information for comprehensive emergency decision-makings. [ABSTRACT FROM AUTHOR]

In March 2021, the 3rd wave of COVID-19 pandemic had ended and the second emergency declaration in January in Tokyo and 3 other prefectures had been lifted. The restrictions on the social activities imposed on the Japanese people and it had become established as "the new lifestyle norm" for each age group. Following our first survey, we conducted a questionnaire survey again to determine the physical changes in all age groups and compared the findings. The 1st survey was conducted after the initial emergency declaration lifted in July 2020, and the 2nd survey was 10 months after the first survey March 2021. And the analysis was conducted by simple and cross tabulation. The number of valid responses were obtained over 12,000 samples for the both surveys. One year later, "Corona locomo" decreased from the previous year in all age groups, especially school students, while it increased in "80s∼". "Corona stress" decreased sharply among children, especially elementary school students, while it increased slightly in 20s, 30s, and "80s∼". The physical condition was closely related to the proportion of exercising population and duration in each age group. "The new lifestyle norm" as a countermeasure against COVID-19 crisis had a significant influence on physical condition in each age group as "the secondary health damage". Forcusing on "With Corona era", it is considered necessary for preventing "locomo-frail", to improve the exercise lifestyles by selecting tailor-made training methods. [ABSTRACT FROM AUTHOR]

After the fire at Notre-Dame de Paris in April 2019, conservation scientists and art historians joined forces with the chief architect and the monument curators to facilitate the management of emergency operations on the stained-glass windows. Information and methodologies were provided for the swift removal of twenty-five 19th and 20th-century windows following the disaster. Restoration and lead decontamination protocols were studied in laboratories and inside the building in order to determine the duration and cost of the upcoming restorations. Thanks to the careful handling of the fire by the firefighters, the stained-glass windows of Notre-Dame were mostly preserved and very little thermal stress breakage was observed on the panels. However, the necessity to use all the teams available inside the building to deal with the generalized lead contamination caused by the roof fire considerably slowed down all the restoration operations. Given the limited time remaining before the building would be reopened, the teams decided to follow two different protocols: a decontamination protocol of the stained glass that remained in the building, and the complete off-site decontamination then restoration of the panels that had been removed. The presence of scaffolding inside the cathedral also provided the opportunity to draw up new restoration charts for the medieval stained glass in the rose windows. This new document would update the previous chart published in 1959, which was based on binocular observations from the ground. The disaster in Notre-Dame de Paris has reminded everyone that a building can quickly be destroyed by a fire, even today. One of the immediate consequences has been the revision of many cathedral security procedures in case of fire, and we can now reflect on improving the management of stained-glass windows after such a catastrophe. [ABSTRACT FROM AUTHOR]

Sexual harassment in academia is endemic driven by gender-based inequalities and sustained through organizational tolerance, and its impact extends beyond the primary victim(s). Applying principles of emergency management provides a framework for institutions to balance their obligations to the primary victim(s) while also acknowledging the need to restore the well-being and culture of secondary victims. [ABSTRACT FROM AUTHOR]

This paper proposes a methodology for computing, visualizing, and analyzing critical decision boundaries for the selection of shortest paths in a given environment. Decision boundaries are defined as the points in a map from which two or more different shortest paths exist towards a destination. This paper introduces the problem of visualizing their evolution, taking into account moving obstacles, moving goals, and as well multiple goals. The proposed visualizations enable analyzing which paths should be taken and at which departure times, such that a destination can be reached by the shortest possible path when taking into account a moving target or time-varying areas to be avoided. The proposed techniques are also applied to the analysis and improvement of exit placement in a given environment, in order to improve the evacuation flow in emergency situations. [Display omitted] • This research presents a unique method for detecting decision boundaries in a given environment, based on the analysis of the generator points of the Shortest Path Map (SPM) rather than employing traditional scalar field topological methods relying on cell neighborhood information which can be affected by the representation resolution. • The proposed approach introduces tools and techniques to visualize the evolution of decision boundaries when considering dynamically-changing obstacles and targets, and to design exit placement to equalize the escape flow distribution. • This novel approach supports decision-making applications related to navigation and environment modeling in emergency evacuation planning. • By analyzing and visualizing SPM decision boundaries, the lengths of globally-optimal Euclidean shortest paths are taken into account, instead of grid-based accumulated distances used in other approaches. [ABSTRACT FROM AUTHOR]

Adequate and effective emergency preparedness for hospital surge capacity is a prerequisite to ensuring standard healthcare services for disaster victims. This study aimed to identify, review, and synthesize the preparedness activities for and the barriers to hospital surge capacity in disasters and emergencies. We systematically searched seven databases (PubMed, MEDLINE, CINAHL, Scopus, Embase, Ovid, and PsycINFO). We included all English peer-reviewed studies published in January 2016 and July 2022 on surge capacity preparedness in hospital settings. Two independent researchers screened titles and abstracts, reviewed the full texts, and conducted data extractions using CADIMA software. We assessed the rigor of the included studies using the NIH quality assessment tools for quantitative studies, the Noyes et al. guidelines for qualitative studies, and the MMAT tool for mixed methods studies and summarized findings using the narrative synthesis method. We also used PRISMA reporting guidelines. From the 2560 studies identified, we finally include 13 peer-reviewed studies: 10 quantitative, one qualitative, and two mixed methods. Five studies were done in the USA, three in Iran (n = 3), and the remaining in Australia, Pakistan, Sweden, Taiwan, and Tanzania. The study identified various ways to increase hospital surge capacity preparedness in all four domains (staff , stuff , space , and system); among them, the use of the Hospital Medical Surge Preparedness Index and the Surge Simulation Tool for surge planning was noteworthy. Moreover, nine studies (69%) recognized several barriers to hospital surge capacity preparedness. The review provides synthesized evidence of contemporary literature on strategies for and barriers to hospital surge capacity preparedness. Despite the risk of selection bias due to the omission of gray literature, the study findings could help hospital authorities, public health workers, and policymakers to develop effective plans and programs for improving hospital surge capacity preparedness with actions, such as enhancing coordination, new or adapted flows of patients, disaster planning implementation, or the development of specific tools for surge capacity. PROSPERO CRD42022360332. [ABSTRACT FROM AUTHOR]

Conducting a vulnerability assessment of hydrogen stations is beneficial for a more comprehensive understanding of safety risks, timely identification of weak links in hydrogen stations to reduce accident risks. This paper proposes a vulnerability assessment method for hydrogen stations in industrial parks based on the improved combination ordered weighted averaging (COWA) operator and ordinal relationship method (G1) and cloud gravity center theory. The vulnerability assessment index system for hydrogen stations considers the vulnerability of personnel, facilities, materials, environment, and emergency response capabilities. The Pythagorean fuzzy decision-making trial and evaluation laboratory (PFDEMATEL) method is used to determine the centrality of the evaluation index, and the comprehensive weight is determined by combining the COWA operator and the G1 method. The cloud gravity center is utilized to determine the vulnerability assessment level by calculating the weighted similarity. A hydrogen station is used as an example to verify the applicability and objectivity of the method. The simulation results indicate that the proposed method has high efficiency and is suitable for vulnerability evaluations. The research findings can provide a theoretical reference and decision-making basis for improving safety management and emergency response of hydrogen stations. [Display omitted] • A vulnerability evaluation index system for hydrogen stations was built. • Pythagorean fuzzy numbers address the haziness and ambiguity of assessment. • Apply PFDEMATEL-COWA and G1 method combination assignment to obtain more objective results. • The cloud center of gravity theory is used for the first time to better evaluate the vulnerability of hydrogen stations. [ABSTRACT FROM AUTHOR]

There emerges increasing doubt regarding whether the policy composite indicators are applicable to the COVID-19 pandemic. A few early studies demonstrate that the association between some composite indicators of policy preparedness and the risk of COVID-19 is statistically insignificant, and the relation between any composite indicators and recovery process (e.g., vaccination coverage) remains unexplored. To examine the relation between composite indicators and pandemic risk (as well as the vaccination coverage) with robustness, this study applies different policy preparedness indicators by using data from multi-sources. A cross-sectional analysis was performed. Regression analysis is adopted to examine the relation between four policy preparedness indicators (i.e., [1] International Health Regulations core capacity index, [2] Global Health Security Index, [3] epidemic preparedness index, and [4] World Governance Index) and COVID-19-confirmed cases/death/vaccination coverage at different time points. The linear regression is performed, and the spatial distribution of indicators are illustrated. Countries with higher ranking in policy preparedness indexes can experience less severity of pandemic risk (e.g., confirmed cases and mortality) and faster recovery process (e.g., higher vaccination coverage). However, slight disparity in effectiveness exists across different indicators. Results show that the policy preparedness indicators have predictive value of the confirmed cases, mortality, and vaccination coverage of COVID-19 pandemic, given sufficiently long-time span is observed. [ABSTRACT FROM AUTHOR]

Stadiums are an important part of the entertainment and sporting cultures of communities around the world, but the combination of outdated infrastructure with poor safety planning, large numbers of people gathering within a confined space, and the high frequency of such events have led to a number of significant disasters in the past. This is a descriptive analysis of stadium disasters occurring between 1901 and 2021 which may provide useful insight for event safety personnel and disaster medicine specialists to better prevent and mitigate the effects of potential future stadium disasters. Data were collected using a retrospective database search of the Emergency Events Database (EM-DATS) for all stadium-related accidental disasters occurring between January 1, 1901 - and July 30th, 2022. A disaster is defined by Centre for Research on the Epidemiology of Disasters (CRED) in its glossary as 'technological accidents of an industrial nature, or involving industrial buildings'. All categories and definitions are predetermined by the EM-DATS as per their glossary. The 24th May 1964 Estadio Nacional disaster in Lima, Peru, was the worst (in terms of deaths) to date with 350 deaths. This is followed by the 1982 Luzhniki Stadium disaster in Moscow, Russia (340 deaths), the 2001 Accra Sport Stadium disaster in Ghana (123 deaths), and the 1985 Hillsborough Stadium disaster in Sheffield, England (96 deaths). Fourteen of the 40 stadium disasters occurred in Africa, 11 in Europe, 10 in the Americas, and five in Asia. A total of 40 stadium disasters were included, leading to 2025 deaths and 6640 injuries. This equated to an average of 50.6 deaths and 166.0 injuries per disaster. Given the potential risk of mass casualty events, stadiums should incorporate disaster medicine education, training, and expertise in their emergency medical plans. [ABSTRACT FROM AUTHOR]

In early 2020, at COVID-19's onset in the United States, the American Dental Association recommended postponing elective dental procedures to minimize viral spread. Subsequently, concerns arose that this could result in increased dental infections and resultant emergency department visits. This study quantifies the number and severity of dental infections at the onset of the early COVID-19 outbreak in early 2020 in the Northeast United States resulting in emergency room visits and radiographic imaging compared to 2017–2019 with an analysis of geographic population characteristics. Cross-sectional head and neck imaging performed at an East Coast hospital system was retrospectively reviewed for dental infections from March 2020 through December 2020, and compared to prior years 2017–2019. Inclusion criteria included radiology reporting of a dental infection, ranging in severity. Electronic medical records (EMR) and imaging reports were queried for patient characteristics and dental findings. There were 735 confirmed imaging reports of odontogenic infections. There was a significant increase in imaging reporting of odontogenic infections in the post-shutdown period. These were more frequently early-type infections, involved a higher proportion of male and non-white patients, and the patients were more often from disadvantaged zip codes when compared with prior years. These findings highlight the varying impact of outpatient dental office closures on different socioeconomic groups in the setting of a pandemic. Potential implications include increased morbidity and mortality for patients, as well as increased cost and resource allocations for the healthcare system. • The pandemic closures of dental clinics were associated with a significant increase in odontogenic infections by imaging. • There was a higher proportion of male and non-white patients with odontogenic infections compared with prior years. • There was also a higher proportion of patients from financially disadvantaged zip codes. [ABSTRACT FROM AUTHOR]

Limited research on food systems and food insecurity (FI) following disasters finds contextual differences in post-disaster food systems that shape dimensions of FI. Measurement limitations make it difficult to address FI and develop effective practices for disaster-affected communities. To develop, validate, and test a Disaster Food Security Framework (DFSF). Mixed-methods approach was used, including in-depth interviews to understand lived experiences during disasters; expert panel input to validate DFSF designed using responses from in-depth interviews; and quantitative testing of robustness of DFSF using the coronavirus disease 2019 pandemic as a disaster example. The in-depth interviews included participants from Vermont (n = 5), North Carolina (n = 3), and Oklahoma (n = 2) who had been living in those states during Hurricane Irene (2011), Hurricane Florence (2018), the Moore tornadoes (2013), and coronavirus disease 2019 pandemic (2020). The expert panel consisted of researchers and practitioners from different US geographical regions and food-related disciplines (n = 18). For the quantitative testing survey, data from 4 US states (New York, New Mexico, Vermont, and Maryland; n = 3,228) from the National Food Access and COVID Research Team was used. The outcomes from the in-depth interviews were dimensions of disaster FI, those from the expert panel was a content validity ratio, and those from the quantitative testing was the number of items and components to be included. Inductive and deductive reasoning were using when reporting on the in-depth interviews and expert panel results, including frequencies. The quantitative testing was conducted using multiple correspondence analysis. The in-depth interviews revealed four dimensions of FI: availability (supply and donation), accessibility (economic, physical, and social), acceptability (preference and health), and agency (infrastructure and self-efficacy). The panel of experts reported high content validity for the DFSF and its dimensions (content validity ratio >0.42), thus giving higher credibility to the DFSF. Multiple correspondence analysis performed on 25 food-related variables identified one component with 13 indicators representing three of the four dimensions: availability, acceptability, and accessibility, but not agency. [ABSTRACT FROM AUTHOR]

We compared external ventricular drains (EVDs) with percutaneous continuous cerebrospinal fluid (CSF) drainage via ventricular access devices (VADs) for the acute management of hydrocephalus in adults. This was a retrospective review of all ventricular drains inserted for a new diagnosis of hydrocephalus into noninfected CSF over four years. We compared infection rates, return to theatre, and patient outcome between EVDs and VADs. We explored the effect of duration of drainage, frequency of sampling, hydrocephalus aetiology, and catheter location on these outcomes using multivariable logistic regression modelling. We included 179 drains (76 EVDs and 103 VADs). EVDs were associated with a higher rate of unplanned return to theatre for replacement or revision (27/76, 36%, vs. 4/103, 4%, OR: 13.4 95%CI: 4.3–55.8). However, infection rates were higher in VADs (13/103, 13% vs. 5/76, 7%, OR: 2.0, 95%CI: 0.65–7.7). EVDs were 91% antibiotic impregnated whereas VADs were 98% nonimpregnated. In multivariable analysis, infection was associated with duration of drainage (median: 11 days prior to infection for infected drains vs. 7 days total for noninfected drains), but not drain type (VADs vs. EVDs OR: 1.6, 95%CI: 0.5–6). EVDs had a higher rate of unplanned revisions but a lower infection rate compared to VADs. However, in multivariable analysis choice of drain type was not associated with infection. We suggest a prospective comparison of antibiotic impregnated VADs and EVDs using similar sampling protocols to assess whether VADs or EVDs for acute hydrocephalus have a lower overall complication rate. [ABSTRACT FROM AUTHOR]

• COVID-19 vaccine hesitancy was heterogeneous both in terms of time and magnitude. • Following COVID-19 news, trust levels, risk preferences, and vaccine confidence predicted intention reversals. • Lowering the cost of following the news for the population may raise vaccine uptake. This paper investigates the prevalence and determinants of three main states of people's willingness to be vaccinated (WTBV) against COVID-19 – willing, unwilling and hesitant – and the occurrence and predictors of shifts between these states over time. Understanding the dynamics of vaccine intentions is crucial for developing targeted campaigns to increase uptake and emergency response preparedness. A panel survey consisting of 9 quarterly waves of data collected between April 2020 and January 2022. Baseline data included 24 952 adults from Germany, UK, Denmark, the Netherlands, France, Portugal, and Italy recruited from online panels to construct census-matched nationally representative samples. Self-reported COVID-19 vaccine intention was the main outcome. Multinomial logit random effects models were used to analyze the relationships of interest. All results reported as relative risk ratios (RRR). Hesitancy to get vaccinated was the most unstable vaccine intention, with on average 42% of ever hesitant respondents remaining in this state through future waves, followed by the 'unwilling' (53%) and 'willing (82%). Following COVID-19 news, trust in information from the government, GPs and the WHO, risk preferences, risk perceptions, and confidence in vaccines (or lack thereof) predicted vaccination intention reversals. Risk preferences acted both as an impediment and as a facilitator for the vaccine uptake depending on the initial vaccine intention. This study revealed the dynamic nature of COVID-19 vaccine intentions and its predictors in 7 European countries. The findings provide insights to policymakers for designing more effective communication strategies, particularly targeted at hesitant and unwilling to vaccinate population groups, to increase vaccine uptake for future public health emergencies. [ABSTRACT FROM AUTHOR]

To optimize the early care of burned patients, protocols were developed that guide pre-hospital care and the need to transfer to a specialized burn treatment unit. Burn disasters are an important public health concern in developed and developing nations. Among the early steps in disaster preparedness is the understanding of geographic locations and capacity of burn care facilities. We aimed to map and classify medical facilities that provide burn care in Brazil and to undertake a location-allocation analysis to identify which could be targeted to increase capacity. A review of burn hospitalizations was conducted using Brazilian Ministry of Health data. Capacity was defined by number of burn patients admitted each year and bed type. Spatial population data per one-square kilometer were obtained from World Pop as a raster dataset. A road network dataset using Open Street Map data was created to conduct the drive time analysis. Location/allocation analysis was conducted to identify the proportion of Brazil's population living within 2- and 6-hours' drive time of a burn care capable hospital, stratified by the level of hospital capacity. Hospitals were ranked according to number of additional people served. We found 26.471 burn admissions. Of these, 3.508(13,2 %) were ICU admissions. A total of 735(2,7 %) hospital deaths occurred under the selected burn codes. In all, 1.273 facilities admitted burn patients, and 263(20,7 %) reported ICU admissions of burn patients. Seventeen hospitals were classified as maximum capacity facilities. Additional 23 hospitals were identified as potential targets for capacity building. Most maximum capacity hospitals are clustered in the Southeast of Brazil. Currently, 40.8 % of the Brazilian population live within 2 h of a maximum capacity facility. A large part of the population lives farther than 6 h away from a maximum capacity hospital. Most of the potential targets for capacity building are located near the coast of Brazil. We mapped and classified facilities that provide public burn care in Brazil. We identified public facilities that could be targeted to increase capacity to improve access for patients in the event of a burn disaster. Mapping, planning, and coordinating response is key for optimal outcomes in Mass Casualties Incidents. Cataloging and understanding local resources is a crucial first step in disaster management. Inequality in profiles can determine specific regional needs. Specialized burn centers are rare in regions other than the southeast. Health equity should be considered when planning disaster preparedness initiatives. Location-allocation modelling may assist in universal and equitable burn care service offerings. This study proposes an initial step in the classification and mapping of available burn treatment centers and population coverage in Brazil. • Burn disasters are an important public health concern in developed and developing nations. • Mapping, planning, and coordinating response is key for optimal outcomes in Mass Casualties Incidents. • Location-allocation modelling may assist in universal and equitable burn care service offerings. • Cataloging and understanding local resources is a crucial first step in disaster management. [ABSTRACT FROM AUTHOR]

Squall lines observed over the sahelo-sudanese regions are responsible for most of the annual rainfall recorded in these regions. They originate from the development of convective processes embedded in the Mesoscale Convective Systems (MCS). The impact assessment of the West African Monsoon (WAM) on the development of squall lines in the sahelo-sudanese regions, particularly the far north region of Cameroon is studied. In this study, the Tropical Rainfall Measuring Mission data (TRMM 3A12 and 3B43) and ERA5 reanalysis data from 1998 to 2008 have been used. The technique used is based on the use of the Climate Data Operator (CDO) software and the NCAR command language (NCL). Analysis of these data shows that the seasonal distribution of winds from the saharan heat-low and the Saint Helena high is the dominant atmospheric dynamics associated with the disturbances behind the development of squall lines. This distribution makes it possible to specifically draw up the evolution of the InterTropical Discontinuity (ITD) on the African continent, and thus, highlight the contribution of the WAM on precipitation in the far north region of Cameroon. This study is performed to contribute to the prediction of hydro-meteorological phenomena to improve disaster risks management associated with floods and landslides in this region, the most vulnerable in Cameroon. [ABSTRACT FROM AUTHOR]

The novel coronavirus (COVID-19) that emerged in 2019 and spread globally in 2020 has resulted in the imposition of lockdowns or a state of emergency in many cities worldwide. In Japan, a "new lifestyle" is being advocated. We hypothesize that the new lifestyle has changed people's use of their upper limbs during the COVID-19 pandemic. Therefore, through this questionnaire study, we aimed to determine the factors associated with exacerbation of symptoms during the pandemic and to investigate the current status of patients who require hand surgery. This study was a prospective multi-center questionnaire survey. This study was conducted in Japan from December 2020 to July 2021 at university and general hospitals in nine prefectures. A questionnaire was administered to patients who visited a hospital with symptoms of nerve entrapment syndrome, osteoarthritis, or tenosynovitis. A total of 502 patients with a mean age of 63.8 years responded. The 240 patients who experienced exacerbation (exacerbated and markedly exacerbated) were compared with other patients (unchanged, improved, and markedly improved). An increase in the time spent on personal computers and smartphones was associated with exacerbation of hand symptoms. Patients who wanted to undergo surgery but were postponed due to COVID-19 accounted for 23.5% of the outpatients. The mean scores for pain, jitteriness, and anxious depression in these patients were significantly higher than those of patients who did not want surgery. Our results suggest that an increase in the time spent on personal computers and smartphones is associated with exacerbation of hand symptoms during the COVID-19 pandemic. Patients who wanted to undergo surgery but were postponed by COVID-19 experienced greater pain, jitteriness, and anxious depression. [ABSTRACT FROM AUTHOR]

Long short-term memory (LSTM) has been widely applied to real-time automated natural gas leak detection and localization. However, LSTM approach could not provide the interpretation that this leak position is localized instead of other positions. This study proposes a leakage detection and localization approach by integrating the attention mechanism (AM) with the LSTM network. In this hybrid network, a fully-connected neural network behaving as AM is first applied to assign initial weights to time-series data. LSTM is then used to discover the complex correlation between the weighted data and leakage positions. A labor-scale pipeline leakage experiment of an urban natural gas distribution network is conducted to construct the benchmark dataset. A comparison between the proposed approach and the state-of-the-arts is also performed. The results demonstrate our proposed approach exhibits higher accuracy with AUC = 0.99. Our proposed approach assigns a higher attention weight to the sensor close to the leakage position, indicating the variation of data from the sensor has a significant influence on leakage localization. It corresponds that the closer to the leakage position, the larger variation of monitoring pressure after leakage, which enhances the detection results' trustiness. This study provides a transparent and robust alternative for real-time automatic pipeline leak detection and localization, which contributes to constructing a digital twin of emergency management of urban pipeline leakage. [ABSTRACT FROM AUTHOR]

This national survey aimed to explore how existing pandemic preparedness plans (PPP) accounted for the demands placed on infection prevention and control (IPC) services in acute and community settings in England during the first wave of the COVID-19 pandemic. This was a cross-sectional survey of IPC leaders working within National Health Service Trusts or clinical commissioning groups/integrated care systems in England. The survey questions related to organisational COVID-19 preparedness pre-pandemic and the response provided during the first wave of the pandemic (January to July 2020). The survey ran from September to November 2021, and participation was voluntary. In total, 50 organisations responded. Seventy-one percent (n = 34/48) reported having a current PPP in December 2019, with 81% (n = 21/26) indicating their plan was updated within the previous 3 years. Around half of IPC teams were involved in previous testing of these plans via internal and multi-agency tabletop exercises. Successful aspects of pandemic planning were identified as command structures, clear channels of communication, COVID-19 testing, and patient pathways. Key deficiencies were lack of personal protective equipment, difficulties with fit testing, keeping up to date with guidance, and insufficient staffing. Pandemic plans need to consider the capability and capacity of IPC services to ensure they can contribute their critical knowledge and expertise to the pandemic response. This survey provides a detailed evaluation of how IPC services were impacted during the first wave of the pandemic and identifies key areas, which need to be included in future PPP to better manage the impact on IPC services. [ABSTRACT FROM AUTHOR]

Applications including change detection, disaster management, and urban planning require precise building information, and therefore automatic building extraction has become a significant research topic. With the improvements in sensor and satellite technologies, more data has become available, and with the increased computational power, deep learning methods have emerged as successful tools. In this study, U-Net and FPN architectures using four different backbones (ResNet-50, ResNeXt-50, SE-ResNext-50, and DenseNet-121), and an Attention Residual U-Net approach were used for building extraction from high-resolution aerial images. Two publicly available datasets, Inria Aerial Image Labeling Dataset and Massachusetts Buildings Dataset were used to train and test the models. According to the results, Attention Residual U-Net model has the highest F1 score with 0.8154, IoU score with 0.7102, and test accuracy with 94.51% on the Inria dataset. On the Massachusetts dataset, FPN Dense-Net-121 model has the highest F1 score with 0.7565 and IoU score with 0.6188, and Attention Residual U-Net model has the highest test accuracy with 92.43%. It has been observed that, FPN with DenseNet backbone can be a better choice when working with small size datasets. On the other hand, Attention Residual U-Net approach achieved higher success when a sufficiently large dataset is provided. [ABSTRACT FROM AUTHOR]

1. Analyze the role of hospices and research needs relative to emergency preparedness and response. 2. Evaluate at least five (5) key hospice considerations in emergency planning and response. Hospices play an important role in emergency planning and response, but there are several challenges including lack of role definition and inconsistencies in guidance. The formulation of best practices and the pursuit of a research agenda could provide further opportunities to strengthen hospices' role in planning for and managing disasters. The underlying characteristics of hospice translate into unique considerations for emergency preparedness planning. These characteristics also convey both organizational vulnerabilities and strengths when responding to disasters. The Centers for Medicare and Medicaid Services have recently expanded their Emergency Preparedness Conditions of Participation for hospice, and the COVID-19 pandemic has highlighted the importance of end-of-life care in disaster planning and response. 1,2 However, the lack of a clearly defined role at federal, state, and local authorities remain as barriers for hospices as they pursue emergency preparedness. 3 Additionally, collaboration with other preparedness partners has been identified as a challenge. Despite this, many hospice providers have experience in disasters and an examination of the academic and professional literature reveals some important roles that hospices may play in their communities during times of disaster. 4 Collaboration with other emergency management partners can provide bi-directional benefit for hospices, healthcare systems, and the communities in which they serve. Continued research in this specialized area is needed to improve hospices' emergency preparedness efforts. Further research is needed in the clarifying the roles of hospices in disasters, best practices in preparedness and response, understanding experiences of hospice providers in disasters, methods of protecting the hospice workforce, and how hospice emergency preparedness planning can help foster resilience in vulnerable communities. Advocacy / Policy / Regulations Scientific Research [ABSTRACT FROM AUTHOR]

In 2020, an estimated 424,300 youth were arrested and nearly 128,000 youth were detained in the United States, with disproportionately higher rates for minoritized youth when compared to White youth.1 Although the number of youth in detention facilities has decreased since the late 1990s, a staggering number of children and adolescents enter the justice system each year. This remains a critical issue for child and adolescent psychiatrists. By the time youth enter juvenile detention, individual mental health needs are already exceptionally high. [ABSTRACT FROM AUTHOR]

The safety of energy infrastructure is currently attracting more and more attention. Once accidents happened or improper incident handling, uncontrolled release of huge energy will lead catastrophic consequences. The manuscript takes the hydrogen refueling station as a typical representative of the energy infrastructure. Once the hydrogen in hydrogen refueling stations (HRSs) leaks, it easily forms a combustible cloud and can explode by encountering a heat source. At such a time, effective emergency management can prevent and reduce the impact of accidents. In this paper, the "scene-task-ability" scenario construction method is first applied to HRS leakage and explosive accidents and used to illustrate the risk evolution process during the different stages of an accident. This method separates the emergency tasks of various emergency responders and evaluates their emergency response ability. The values of prevention, preparation, response and recovery are coupled using the time-ordered weighted averaging and time-ordered weighted geometric averaging hybrid operator, in order to derive a systematic and comprehensive evaluation of the safe emergency management of HRSs. Finally, based on the results of the emergency response ability evaluation, targeted and effective suggested measures are proposed to improve the emergency management level of emergency responders. • The "scene-task-ability" method is first applied to HRS accident. • This scenario construction method separates the tasks of emergency responders. • This paper uses the TOWA-TOWGA hybrid operator model for dynamic evaluation. • Measures to improve the emergency level are proposed based on evaluation results. [ABSTRACT FROM AUTHOR]

Subsea gas release incidents may result in catastrophic consequences, e.g., overturning of offshore floating structures, fire, and explosion. This paper developed a model to investigate the dispersion behavior of underwater gas released from the seafloor soil under combined action of current and wave. Eulerian-Eulerian model is used to track underwater gas dispersion trajectory. Porous model is utilized to describe the seafloor soil and simulate the penetration of gas released from seafloor soil. The numerical model is validated by comparing with small-scale experiments. The effect of release rate, current velocity and soil porosity is investigated. The parameters, e.g., rising time, horizontal dispersion distance and surfacing area are estimated. The uniqueness of this study is that underwater gas plumes are simulated considering the seafloor soil and the combined action of current and wave. The results indicate that the presence of seafloor soil has a significant effect on the migration shape and trajectory of underwater gas plume. The combined action of current and wave increases the dispersion distance of gas plume. This study can support risk assessment and emergency planning of subsea gas release accidents. [ABSTRACT FROM AUTHOR]

A European response plan to burn mass casualty incidents has been jointly developed by the European Commission and the European Burn Association. Upon request for assistance by an affected country, the plan outlines a mechanism for coordinated international assistance, aiming to alleviate the burden of care in the affected country and to offer adequate specialized care to all patients who can benefit from it. To that aim, Burn Assessment Teams are deployed to assess and triage patients. Their transportation priority recommendations are used to distribute outnumbering burn casualties to foreign burn centers. Following an appropriate medical evacuation, these casualties receive specialized care in those facilities. The European Burns Association's disaster committee developed medical-organizational guidelines to support this European plan. The experts identified fields of interest, defined questions to be addressed, performed relevant literature searches, and added their expertise in burn disaster preparedness and response. Due to the lack of high-level evidence in the available literature, recommendations and specially designed implementation tools were provided from expert opinion. The European Burns Association officially endorsed the draft recommendations in 2019, and the final full text was approved by the EBA executive committee in 2022. The resulting 46 recommendations address four fields. Field 1 underlines the need for national preparedness plans and the necessary core items within such plans, including coordination and integration with an international response. Field 2 describes Burn Assessment Teams' roles, composition, training requirements, and reporting goals. Field 3 addresses the goals of specialized in-hospital triage, appropriate severity criteria, and their effects on priorities and triage. Finally, field 4 covers medical evacuations, including their timing and organization, the composition of evacuation teams and their assets, preparation, and the principles of en route care. • These guidelines support the European burn disaster response plan in four fields. • National preparedness is a prerequisite and should link with international response. • Casualties should be assessed by deployed Burn Assessment Teams in a shared standard. • Specialized in-hospital triage should guide casualty transport and burn center referral. • Medical evacuations need careful planning, preparation, coordination and implementation. [ABSTRACT FROM AUTHOR]

Patients arriving at the emergency department with a potential cervical spine injury and immobilized in a rigid cervical collar often require emergency airway management and rapid sequence induction intubation (RSII). There have been several advances in airway management with the advent of channeled (AirtraqⓇ; Prodol Meditec) and nonchanneled (McGrathⓇ; Meditronics) video laryngoscopes, which enable intubation without the removal of the cervical collar, but their efficacy and superiority over conventional laryngoscopy (Macintosh) in the presence of a rigid cervical collar and cricoid pressure have not been evaluated. Our aim was to compare the channeled (Airtraq [group A]) and nonchanneled (McGrath [Group M]) video laryngoscopes with a conventional laryngoscope (Macintosh [Group C]) in a simulated trauma airway. A prospective randomized controlled study was conducted in a tertiary care center. Participants were 300 patients requiring general anesthesia (American Society of Anesthesiologists class I or II), of both sexes, and aged 18–60 years. Airway management was simulated without removal of a rigid cervical collar and using cricoid pressure during intubation. After RSI, patients were intubated with one of the study techniques according to randomization. Intubation time and intubation difficulty scale (IDS) score were noted. Mean intubation time was 42.2 s in group C, 35.7 s in group M, and 21.8 s in group A (p = 0.001). Intubation was easy in group M and group A (median IDS score of 0; interquartile range [IQR] 0–1 for group M and median IDS score of 1; IQR 0–2 for group A and group C; p < 0.001). A higher proportion (95.1%) of patients had an IDS score of < 1 in group A. The performance of RSII with cricoid pressure in the presence of a cervical collar was easier and more rapid with channeled video laryngoscope than with other techniques. [ABSTRACT FROM AUTHOR]

El Niño/Southern Oscillation (ENSO) mainly occurs in the tropical Pacific Ocean every a few years. But it affects the climate around the world and has a dramatic impact on the development of ecology and agriculture. The analysis and prediction of ENSO become particularly important for meteorology and disaster management. However, due to insufficient data, spring predictability barrier (SPB), and model uncertainty, traditional analysis models face challenges. To address these issues, researchers begin to apply deep learning (DL) technologies to ENSO research, exploring the impact of ENSO on the world's extreme climate changes. In recent years, deep learning-based methods have obtained impressive progress with more accurate and effective predictions of ENSO. In this paper, we summarize the attempts of DL technologies in predicting ENSO. We first introduce the properties of ENSO, followed by the architecture introduction of DL technologies and their application to ENSO. We then investigate the potential of DL technologies for ENSO prediction from various aspects, including model evaluation metrics, prediction algorithms, overcoming SPB and prediction uncertainty. Finally, we provide discussions on the future trends and challenges of using DL technologies for ENSO prediction. [ABSTRACT FROM AUTHOR]

Problems with COVD-19 are not limited to the infection itself, but also include the secondary health damage arising from the prolonged self-restraint, which has affected all age groups in the Japanese population. Numerous studies have reported clear evidence of the secondary health damage. Published reports cover a wide range of damages, from locomotive dysfunction caused by decreased physical activity to decreased cognitive function and changes in eating and oral functions, and further to decreased opportunities for social participation. Such damage can also lead to worsening of so-called frailty. Under this circumstance, orthopedic surgeons conducted a questionnaire survey to determine the physical changes observed after the start of the COVD-19 self-restraint period. In this article, we report findings of the survey, along with some literature considerations. The survey was started two months after the state of emergency in Japan was lifted, July 20 to August 12, 2020 (16 days total). And the analysis was conducted by simple and cross tabulation. Valid responses to the questionnaire were obtained from 12,254 participants. Approximately 40% of the subjects felt a lack of physical strength (Corona stress), with the percentage peaking in high school, in the elderly it remained rather below average. On the other hand, locomotive dysfunction (Corona locomo) increased with age, independent of physical activity, and was not correlated with Corona stress. Japanese citizens need to change their behaviors for the purpose of improving their exercise and lifestyle habits towards shifting to a new lifestyle norm. Looking ahead to the ''With Corona" era, it is considered necessary by selecting a tailor-made training method suitable for each age group. [ABSTRACT FROM AUTHOR]

The accurate extraction of building damage after destructive natural disasters is critical for disaster rescue and assessment. To achieve a rapid disaster response, training a model from scratch using enough ground-truth data collected in situ is not feasible. Often, in disaster situations, it is ineffective to directly apply an existing model due to the vast diversity among buildings worldwide, the limited number of label samples for training, and the different sources of remote sensing images between the pre- and post-disaster. To solve this problem, we present an incremental learning framework for the rapid identification of collapsed buildings triggered by sudden natural disasters. Specifically, end-to-end gradient boosting networks are improved into an incremental learning framework for an emergency response, where the historical natural disaster data are transferred into the same style of images that were captured shortly after a disaster event by using cycle-consistent generative adversarial networks. The proposed method is tested on two cases, i.e., the Haiti earthquake in January 2010 and the Nepal earthquake in April 2015, achieving Kappa accuracies of 0.70 and 0.68, respectively. The optimization of building damage extraction can be completed within 8 h after the disaster using the transferred data. The experimental results show that the proposed method is an effective way to evaluate the building damage triggered by natural disasters with different source remote sensing images. The code of this work and the data of the test cases are available at https://github.com/gjy-Ari/Incre-Trans. [ABSTRACT FROM AUTHOR]

Abrupt air pollution accidents can endanger people's health and destroy the local ecological environment. The appropriate emergency response can minimize the harmful effects of accidents and protect people's lives and property. This paper provides an overview of the key emergency response technologies for abrupt air pollution accidents around the globe with emphasis on the major achievements that China has obtained in recent years. With decades of effort, China has made significant progress in emergency monitoring technologies and equipment, source estimation technologies, pollutant dispersion simulation technologies and others. Many effective domestic emergency monitoring instruments (e.g., portable DOAS/FT-IR systems, portable FID/PID systems, portable GC-MS systems, scanning imaging remote sensing systems, and emergency monitoring vehicles) had been developed which can meet the demands for routine emergency response activities. A monitoring layout technique combining air dispersion simulation, fuzzy comprehensive evaluation, and a post-optimality analysis was proposed to identify the optimal monitoring layout scheme under the constraints of limited monitoring resources. Multiple source estimation technologies, including the forward method and the inversion method, have been established and evaluated under various scenarios. Multi-scale dynamic pollution dispersion simulation systems with high temporal and spatial resolution were further developed. A comprehensive emergency response platform integrating database support, source estimation, monitoring schemes, fast monitoring of pollutants, pollution predictions and risk assessment was developed based on the technical idea of "source identification - model simulation - environmental monitoring" dynamic interactive feedback. It is expected that the emergency response capability for abrupt air pollution accidents will gradually improve in China. [Display omitted] [ABSTRACT FROM AUTHOR]

Water distribution systems are susceptible to contamination events, which can occur due to naturally occurring events, accidents or even malicious attacks. When a contamination event occurs, dangerous substances infiltrating the network may be consumed thereby deteriorating the consumers' health and possibly affecting the economy. Advances in sensor and actuator technologies are enabling water networks to become smarter and more resilient to these types of events. This paper provides a broad review of the theoretical, modeling, and computational developments in the area of contamination event diagnosis for water distribution systems. Research is segmented into three main tasks, summarized as "Preparedness", "Event Detection and Isolation" and "Emergency Event Management". The key research topics from each task are described within a unified systems-theoretic mathematical framework, and their open challenges are discussed. [ABSTRACT FROM AUTHOR]

During the COVID-19 pandemic, the incidence of many droplet-transmitted infections decreased due to increased mask-wearing and social distancing. Contrastingly, there has been concern that COVID-19 countermeasures, such as lockdowns, may increase legionellosis incidence via water stagnation. During the pandemic in Japan, four state of emergency declarations were imposed between 2020 and 2021, which makes it particularly suitable to test this hypothesis. We use country-level surveillance data from the National Institute of Infectious Diseases to track the relative incidence of legionellosis compared to invasive pneumococcal disease (IPD) during the COVID-19 pandemic in Japan, with a focus on the periods just after state of emergency declarations were lifted. The absolute number of legionellosis and IPD cases decreased in 2020 and 2021 compared to previous years. The average relative incidence of legionellosis as well as the variance of the relative incidence significantly increased during the pandemic compared to previous years. There were no increases in the relative incidence of legionellosis during the periods immediately following emergency declaration liftings, but the relative incidence did increase considerably during the first two states of emergency. COVID-19 countermeasures appear more effective at decreasing the incidence of human-to-human transmitted infections, such as IPD, compared to environmentally-transmitted infections, such as legionellosis. Though no evidence was found to suggest that legionellosis cases increased after state of emergency declarations, public health efforts should continue to emphasize the importance of routine sanitation and water system maintenance to prevent water stagnation and Legionella spp. contamination. [ABSTRACT FROM AUTHOR]