The Association between Fear of COVID-19,Obsession with COVID-19,and Post Traumatic Stress Disorder in Korean Emergency Rescue Firefighters:A Cross-Sectional Study

During the rapid spread of COVID-19,first responders are at risk of being exposed to COVID-19 due to their role in providing first aid and responding to an unspecified number of people.This uncertainty can have adverse mental health effects,such as increased anxiety and fear.This study aimed to investigate the degree of association between fear of COVID-19,obsession with COVID-19,and post-traumatic stress disorder(PTSD)in emergency rescue firefighters.The participants were 150 emergency rescue firefighters working in Region S,Korea.They filled out self-report questionnaires:The data obtained through the Fear of COVID-19 Scale,Obsession with COVID-19 Scale,and Impact of Event Scale-Revised Korean version were subjected to nonparametric statistical analysis using SPSS WIN 25.0.The study found a significant correlation between emergency rescue firefighters’fear of COVID-19,obsession with COVID-19,and PTSD.Fear and obsession with COVID-19 were higher among first responder firefighters who were directly involved in COVID-19-related tasks.Furthermore,a one-point increase in obsession was associated with a 2.837-point increase in PTSD.Based on the results,we found that there is a need for effective control of obsessions and fears among first responder firefighters during COVID-19,and we suggest that there is a need for mental health care for first responder firefighters during the pandemic through the development and support of programs to prevent and mitigate obsessions.

Robust hydrogel adhesives for emergency rescue and gastric perforation repair

Development of biocompatible hydrogel adhesives with robust tissue adhesion to realize instant hemorrhage control and injury sealing,especially for emergency rescue and tissue repair,is still challenging.Herein,we report a potent hydrogel adhesive by free radical polymerization of N-acryloyl aspartic acid(AASP)in a facile and straightforward way.Through delicate adjustment of steric hindrance,the synergistic effect between interface interactions and cohesion energy can be achieved in PAASP hydrogel verified by X-ray photoelectron spectroscopy(XPS)analysis and simulation calculation compared to poly(N-acryloyl glutamic acid)(PAGLU)and poly(N-acryloyl amidomalonic acid)(PAAMI)hydrogels.The adhesion strength of the PAASP hydrogel could reach 120 kPa to firmly seal the broken organs to withstand the external force with persistent stability under physiological conditions,and rapid hemostasis in different hemorrhage models on mice is achieved using PAASP hydrogel as physical barrier.Furthermore,the paper-based Fe^(3+)transfer printing method is applied to construct PAASP-based Janus hydrogel patch with both adhesive and non-adhesive surfaces,by which simultaneous wound healing and postoperative anti-adhesion can be realized in gastric perforation model on mice.This advanced hydrogel may show vast potential as bio-adhesives for emergency rescue and tissue/organ repair.

A dynamic task assignment model for aviation emergency rescue based on multi-agent reinforcement learning

China's natural disaster situation presents a complex and severe scenario, resulting in substantial human and material losses as a result of large-scale emergencies. Recognizing the significance of aviation emergency rescue, the state provides strong support for its development. However, China's current aviation emergency rescue system is still under construction and encounters various challenges;one such challenge is to match the dynamically changing multi-point rescue demands with the limited availability of aircraft dispatch. We propose a dynamic task assignment model and a trainable model framework for aviation emergency rescue based on multi-agent reinforcement learning. Combined with a targeted design, the scheduling matching problem is transformed into a stochastic game process from the rescue location perspective. Subsequently, an optimized strategy model with high robustness can be obtained by solving the training framework. Comparative experiments demonstrate that the proposed model is able to achieve higher assignment benefits by considering the dynamic nature of rescue demands and the limited availability of rescue helicopter crews. Additionally, the model is able to achieve higher task assignment rates and average time satisfaction by assigning tasks in a more efficient and timely manner. The results suggest that the proposed dynamic task assignment model is a promising approach for improving the efficiency of aviation emergency rescue.

Team effectiveness evaluation and virtual reality scenario mapping model for helicopter emergency rescue

The application of helicopter emergency rescue is becoming increasingly widespread,but the flight crew training in this area is still difficult due to high cost and risk.Nevertheless,with the development of Virtual Reality(VR)technology,virtual simulation has become a significant role in crew training of helicopter rescue.During the implementation of VR-based training,how to transform complex real tasks into VR scenarios and how to evaluate the performance of crew are of great importance.To address these issues,a novel VR-based R-E-A-D(Report,Evaluate,Agree,Do)evaluation model for training is proposed,which is suitable for complex missions with multiple tasks,multiple scenarios,and multiple people.Then,a mapping method of VR scenarios is put forward,which can transform the real tasks into virtual scenarios to serve the virtual simulation training.Finally,an experiment is carried out to verify the feasibility of the evaluation method and virtual scenario mapping method.

Application of BeiDou navigation satellite system in emergency rescue of natural hazards: a case study for field geological survey of Qinghai−Tibet plateau

In recent years,geological and mineral resources exploration in China has expanded to deep hinterland of the Qinghai−Tibet Plateau and other regions with complex geological conditions.The special natural conditions of Qinghai−Tibet Plateau determine the characteristics of“life-forbidden zone”that is characterized by alpine hypoxia,changeable weather,complex road conditions,and beast attack.In particular,the work in wild depopulated zones with severe environment and poor communications imposes serious threats to the life safety of geological personnel.Therefore,how to guarantee the safety of geological personnel working on the Qinghai−Tibet Plateau and how to reduce or even avoid casualty of geological personnel have currently become the urgent challenge.In this study,an emergency rescue information system for field geological survey is constructed based on BeiDou Navigation Satellite System.A case study of emergency rescue has been conducted in the depopulated zone of the Qinghai−Tibet Plateau and good effects have been achieved,providing security assurance for personnel engaged in field geological survey on the Qinghai−Tibet Plateau and technical support for the emergency rescue in case of natural hazards on the Qinghai−Tibet Plateau.The BeiDou Navigation Satellite System(BDS)can be effectively used to locate and communicate in the emergency rescue for rigorous Geological survey task where there is no network signal for the mobile phone,and the emergency rescue guarantee system is independent,reliable,and relatively cheap.The application value of BDS is demonstrated in the geological field.

Router and gateway node placement in wireless mesh networks for emergency rescue scenarios

The focus of this paper is on base functionalities required for UAV-based rapid deployment of an ad hoc communication infrastructure in the initial phases of rescue operations.The main idea is to use heterogeneous teams of UAVs to deploy communication kits that include routers,and are used in the generation of ad hoc Wireless Mesh Networks(WMN).Several fundamental problems are considered and algorithms are proposed to solve these problems.The Router Node Placement problem(RNP)and a generalization of it that takes into account additional constraints arising in actual field usage is considered first.The RNP problem tries to determine how to optimally place routers in a WMN.A new algorithm,the RRT-WMN algorithm,is proposed to solve this problem.It is based in part on a novel use of the Rapidly Exploring Random Trees(RRT)algorithm used in motion planning.A comparative empirical evaluation between the RRT-WMN algorithm and existing techniques such as the Covariance Matrix Adaptation Evolution Strategy(CMA-ES)and Particle Swarm Optimization(PSO),shows that the RRT-WMN algorithm has far better performance both in amount of time taken and regional coverage as the generalized RNP problem scales to realistic scenarios.The Gateway Node Placement Problem(GNP)tries to determine how to locate a minimal number of gateway nodes in a WMN backbone network while satisfying a number of Quality of Service(QoS)constraints.Two alternatives are proposed for solving the combined RNP-GNP problem.The first approach combines the RRT-WMN algorithm with a preexisting graph clustering algorithm.The second approach,WMNbyAreaDecomposition,proposes a novel divide-and-conquer algorithm that recursively partitions a target deployment area into a set of disjoint regions,thus creating a number of simpler RNP problems that are then solved concurrently.Both algorithms are evaluated on real-world GIS models of different size and complexity.WMNbyAreaDecomposition is shown to outperform existing algorithms using 73%to 92%fewer router nodes while at the same time satisfying all QoS requirements.

Post-disaster medical rescue strategy in tropical regions

BACKGROUND:Earthquakes,floods,droughts,storms,mudslides,landslides,and forest wild fires are serious threats to human lives and properties.The present study aimed to study the environmental characteristics and pathogenic traits,recapitulate experiences,and augment applications of medical reliefs in tropical regions.METHODS:Analysis was made on work and projects of emergency medical rescue,based on information and data collected from 3 emergency medical rescue missions of China International Search and Rescue Team to overseas earthquakes and tsunamis aftermaths in tropical disaster regions — Indonesia-Aceh,Indonesia-Yogyakarta,and Haiti-Port au Prince.RESULTS:Shock,infection and heat stroke were frequently encountered in addition to outbreaks of infectious diseases,skin diseases,and diarrhea during post-disaster emergency medical rescue in tropical regions.CONCLUSIONS:High temperature,high humidity,and proliferation of microorganisms and parasites are the characteristics of tropical climate that impose strict requirements on the preparation of rescue work including selective team members suitable for a particular rescue mission and the provisioning of medical equipment and life support materials.The overseas rescue mission itself needs a scientific,efficient,simple workflow for providing efficient emergency medical assistance.Since shock and infection are major tasks in post-disaster treatment of severely injured victims in tropical regions,the prevention and diagnosis of hyperthermia,insect-borne infectious diseases,tropic skin diseases,infectious diarrhea,and pest harms of disaster victims and rescue team staff should be emphasized during the rescue operations.

Stochastic Petri Net Based Modeling of Emergency Medical Rescue Processes During Earthquakes

The post-disaster emergency medical rescue(EMR) is critical for people’s lives. This paper presents a stochastic Petri net(SPN) model based on the process of the rescue structure and a Markov chain model(MC), which is applied to the optimization of the EMR process, with the aim of identifying the key activities of EMR. An isomorphic MC model is developed for measuring and evaluating the time performance of the EMR process during earthquakes with the data of the 2008 Wenchuan earthquake.This paper provides a mathematical approach to simulate the process and to evaluate the efficiency of EMR. Simultaneously, the expressions of the steady state probabilities of this system under various states are obtained based on the MC, and the variations of the probabilities are analyzed by changing the firing rates for every transition. Based on the concrete data of the event, the authors find the most time consuming and critical activities for EMR decisions. The model results show that the key activities can improve the efficiency of medical rescue, providing decision-makers with rescue strategies during the large scale earthquake.

A Deep Learning Application for Building Damage Assessment Using Ultra-High-Resolution Remote Sensing Imagery in Turkey Earthquake

Rapid building damage assessment following an earthquake is important for humanitarian relief and disaster emergency responses.In February 2023,two magnitude-7.8 earthquakes struck Turkey in quick succession,impacting over 30 major cities across nearly 300 km.A quick and comprehensive understanding of the distribution of building damage is essential for e fficiently deploying rescue forces during critical rescue periods.This article presents the training of a two-stage convolutional neural network called BDANet that integrated image features captured before and after the disaster to evaluate the extent of building damage in Islahiye.Based on high-resolution remote sensing data from WorldView2,BDANet used predisaster imagery to extract building outlines;the image features before and after the disaster were then combined to conduct building damage assessment.We optimized these results to improve the accuracy of building edges and analyzed the damage to each building,and used population distribution information to estimate the population count and urgency of rescue at different disaster levels.The results indicate that the building area in the Islahiye region was 156.92 ha,with an affected area of 26.60 ha.Severely damaged buildings accounted for 15.67%of the total building area in the affected areas.WorldPop population distribution data indicated approximately 253,297,and 1,246 people in the collapsed,severely damaged,and lightly damaged areas,respectively.Accuracy verification showed that the BDANet model exhibited good performance in handling high-resolution images and can be used to directly assess building damage and provide rapid information for rescue operations in future disasters using model weights.

Improving social media use for disaster resilience: challenges and strategies

This paper develops a social media-disaster resilience analysis framework by categorizing types of social media use and their challenges to better understand and assess its role in disaster resilience research and management.The framework is derived primarily from several case studies of Twitter use in three hurricane events in the United States-Hurricanes Isaac,Sandy,and Harvey.The paper first outlines four major contributions of social media data for disaster resilience research and management,which include serving as an effective communication platform,providing ground truth information for emergency response and rescue operations,providing information on people's sentiments,and allowing predictive modeling.However,there are four_key challenges to its uses,which include,easy spreading of false information,social and geographical disparities of Twitter use,technical issues on processing and analyzing big and noisy data,especially on improving the locational accuracy of the tweets,and algorithm bias in Al and other types of modeling.Then,the paper proposes twenty strategies that the four sectors of the social media community-organizations,individuals,social media companies,and researchers-could take to improve social media use to increase disaster resilience.