Search

The emergency lighting system (ELS) is mandatory to be installed at the commercial, residential, and public buildings and must be activated automatically in the case of disasters such as fire, earthquake, flood, hurricane, and electricity power outage situations. Conventional ELS must use an extra phase line to charge its battery as well as to detect the presence of an emergency condition. It is costly to use an additional phase line in the electrical system and requires a new system configuration in the existing systems. In this study, an ELS design is proposed that eliminates the need for additional phase line installation by using power line communication (PLC) circuitry. Additionally, LED lamp is preferred instead of fluorescent lamp due to their advantages. The proposed ELS detects the presence of emergency and power outage conditions and then charges the battery of the system through the PLC. [ABSTRACT FROM AUTHOR]

In recent years, there is a significant increase in research combining social media data for disaster warning and damage assessment. When natural disasters occur, social media data can also contain rumors, which not only reduce the accuracy of assessment but also have a very negative social impact. In this paper, a multi-feature fusion neural network with attention mechanism is proposed for rumor detection, which makes the attempt to integrate user, textual and propagation features in one united framework. Specifically, a Bidirectional Long Short-Term Memory Network (Bi-LSTM) is applied to extract user and textual features and a Graph Convolutional Neural Network (GCN) is employed to extract the high-order propagation features. In addition, both the complementary and alignment relationships between different features are considered to achieve better fusion. It shows that our method can detect rumors effectively and perform better than previous methods on the Weibo dataset. To validate the effectiveness of our model, rumor detection is conducted in the social media data collected from Typhoon Lekima on Aug 10th–14th 2019 in China, the earthquake of magnitude 6.8 on Sep 5th–9th, 2022 in Sichuan, China, the wildfire on Aug 15th–26th, 2022 in Chongqing, China. Results show that: (1) the proposed method performs well in rumor detection in disaster; (2) rumors often appear along with hot topics; (3) rumors express much negative sentiment; (4) rumor propagation networks have tighter structure and deeper propagation depth. (5) rumors account for a relatively small percentage of social media data in disaster, which means that most social media data is credible. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Planning Education & Research is the property of Sage Publications Inc. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Nowadays the recent development of new information generation processes in the Internet of Things (IoT) is applied in various factors such as the development of modern sensors, wireless networks, big data applications, automatic monitoring systems, etc. Landslide disaster monitoring is an important and practical direction of Internet of Things technology in a disaster monitoring system, which has the advantages of low cost and mature technology. With the continuous development of IoT technology, standardized data sharing and interoperability have been put forward on the agenda. Based on the Open Geospatial Consortium (OGC) Sensor Thing Application Programming Interface (API) standard, this article analyzes landslide monitoring data sharing and interoperability from the data model, shared service content, and system construction and provides a reference for the standardization of geological disaster data sharing and interoperability regarding IoT applications. Due to the characteristics of a simple layout, strong anti-damage and self-healing ability, self-organization, etc., based on the ZigBee multi-sensor and wireless Mesh network, it is widely used in the data collection and transmission of geological disaster monitoring systems. The experimental analysis is carried out based on various parameters namely computational cost, power utilization, fitness function, danger rate, evacuation time, total travel time as well as root mean square error. Finally, the results conclude that the proposed approach attained better performances in terms of cost, power utilization, and error rate. [ABSTRACT FROM AUTHOR]

In the twenty-first century, providing humanitarian assistance to other nations forms an essential part of the U.S. military's mission. Designed to "relieve or reduce endemic conditions such as human suffering, disease, hunger, [and] privation," the military's humanitarian tasks include such activities as assisting refugees, delivering food and medical equipment to partner nations, and removing unexploded landmines. But among the most recognized—and best publicized—of the U.S. Armed Forces' humanitarian activities are its foreign disaster relief operations. In response to such recent catastrophes as the 2010 earthquake in Haiti, the 2011 tsunami in Japan, 2019's Cyclone Idai in Mozambique, and the 2023 earthquakes in Turkey, the Department of Defense launched extensive humanitarian operations. Taking advantage of the U.S. military's vast global footprint, military leaders dispatched ships and aircraft, service personnel, relief supplies, equipment, and other material and logistical aid to the scene of these crises and to many others like them globally. Carried out for the humanitarian goals of saving lives and reducing suffering, each of these foreign disaster aid operations also shared a critical diplomatic objective: "generating goodwill" for the United States and creating a "favorable impression" of its armed forces. Never purely altruistic, the U.S. military's responses to global disasters also function as a valuable instrument of contemporary U.S. foreign policy. [ABSTRACT FROM AUTHOR]

This study focuses on the identification of collapsed buildings in satellite images after earthquakes through deep learning-based image segmentation models. The performance of four different architectures, namely U-Net, LinkNet, FPN, and PSPNet, was evaluated using various performance metrics, such as accuracy, precision, recall, F1 score, specificity, AUC, and IoU. The study used satellite images taken from the area located in the south and southeast of Türkiye covering the eleven provinces which are most affected by the Mw 7.7 Pazarcık (Kahramanmaraş) and Mw 7.6 Elbistan (Kahramanmaraş) earthquakes. The results indicated that FPN and U-Net were the best-performing models depending on the performance metric of interest. FPN achieved the highest accuracy and specificity scores, as well as the best precision score, while U-Net achieved the best recall and F1 score values, as well as the best AUC and IoU scores. The training and validation accuracy and loss curves were analyzed, and the results indicated that all four models achieved an accuracy value of over 96%. The FPN model outperformed the others in terms of accurately segmenting images while maintaining a low loss value. This study provides insights into the potential of deep learning-based image segmentation models in disaster management and can be useful for future research in this field. [ABSTRACT FROM AUTHOR]

The frequent occurrence of urban flood disasters is a major and persistent problem threatening the safety of cities in China and elsewhere in the world. As this issue is so pervasive, exploring new methods for more effective risk prevention and urban flood disaster control is now being prioritized. Taking the case of the city of Zhengzhou as an example, this paper proposes using geological, hydrogeological, ecological, and environmental conditions together with appropriate engineering designs to address the problem of urban flooding. The strategy includes integrating urban sponge–hydrogeological conditions, ecological engineering, and the construction of deep underground water storage facilities. Field investigations, data collection and analysis, in situ observations, testing, and laboratory experiments, are analyzed to explain the formation mechanism and means to mitigate flood disasters in Zhengzhou. Our results suggest that the appropriate use of geological, ecological, and hydrogeological aspects, combined with effective engineering practices, can significantly improve the city's flood control capacity. These measures can solve the problem of the "once-in-a-millennium" occurrence of torrential rain disasters such as the "720" torrential rainstorm that has affected the city of Zhengzhou. [ABSTRACT FROM AUTHOR]

After a natural disaster, it is very important for the government to conduct a damaged assessment as soon as possible. Fast and accurate disaster assessment helps the government disaster relief departments allocate resources and respond quickly and effectively to minimize the losses caused by the disaster. Usually, the method of measuring disaster losses is to rely on manual field exploration and measurement, and then calculate and label the damaged buildings or land, or rely on unmanned collections to remotely collect pictures of the disaster-stricken area, and compare the original pictures to carry out the disaster annotation and calculation. These methods are timeconsuming, labor-intensive, and inefficient. This paper proposes a posthurricane building damage detection method based on transfer learning, which uses deep learning image classification algorithms to achieve post-disaster satellite image damage detection and classification, thereby improving disaster assessment efficiency and preparing for disaster relief and postdisaster reconstruction. The proposed method adopts the theory of transfer learning, establishes a disaster image detection model based on the convolutional neural network model, and uses the 2017 Hurricane Harvey data as the experimental data set. Experiments have proved that our proposed model accuracy of disaster detection reaches 97%, which is 1% higher than other models. [ABSTRACT FROM AUTHOR]

Disaster Recovery (DR) providers define the main services as backup and restore, both with critical data and applications. Most clients of data and application backup, fully rely on DR's services to restore them in the disaster events. Furthermore, in the normal conditions, DR provider backs up data, sometimes with application in routine or regular basis. Thus, providers should deliver the services in sophisticated way through several Key Performance Indicators (KPIs). In this paper, development of KPIs is focused on performance and assurance, which a laboratory testing simulates backup and restore services. On the other hand, experimental data such as network and system parameters are analysed to build performance and assurance framework. Meanwhile, interdependence among each performance and assurance of DRCs was used to build a relationship model. It is acted as a part of service level agreement, that a DR providers can present services dynamically. They also should adapt the computing resources to deliver services to meet SLA (Service Level Agreement) in flexible strategy. In turn, they can negotiate SLA with the customers based on this new approach. [ABSTRACT FROM AUTHOR]

When governments are structurally unable to provide social services, or when disaster strikes, relief organisations tend to step in. This is also the case in South and East Asia. Such organisations may be faith-based, leading to the emergence of what Asians colloquially call “rice Christians”: persons who (allegedly) convert to a religion in order to access services, or out of loyalty to the aid-supplying organisation. Such converts may continue to practice their traditional religions and beliefs. This raises the question whether rights to religion or belief are still available to “rice Christians” when governments, e.g., seek to redevelop a sacred site that formed part of their original belief system. The present article addresses that question, drawing upon the concept of multiple religious belonging (‘mrb’) and a 2017 decision of the African Court on Human and Peoples’ Rights in which the court accepted that individuals may adhere to multiple religions, especially where conversion happened within a missionary context and the now-claimed belief is Indigenous or traditional. It argues in favour of recognition of mrb within the context of freedom of religion, which would mean that also “rice Christians” can continue to rely on original belief systems to protect their practices and places. [ABSTRACT FROM AUTHOR]

Natural disasters lead to massive human and financial losses yearly; thus, disaster planning is of critical importance. One of the most crucial measures for disaster planning is developing an efficient disaster relief supply chain (DRSC) network. Thus, many researchers have focused on this field while overlooking some crucial actual conditions as a result of the complexity of the problem. Consequently, this study develops a DRSC network considering the perishability of relief commodities (RCs), the gradual injection of the limited pre-disaster budgets, pre-disaster lateral transportation, and the time value of money. In this respect, a novel multi-period multi-commodity mixed-integer non-linear programming model is presented, which optimizes pre-disaster warehouse location and inventory management and the post-disaster re-procurement and distribution of RCs in each period. Utilizing a new service utility index, the proposed model strives to minimize deprivation cost while maximizing demand coverage and fair service. To provide the required RCs in the pre-disaster phase, a bidirectional quantity flexibility contract (BQFC) is proposed, which is integrated with multi-sourcing and allows for two-part buybacks, installment and delayed payments, and quantity-based discounts on its terms. The applicability and performance of the model are validated via a real case study in Mashhad, Iran. Various sensitivity analyses are provided to highlight the desirable performance of the model and achieve helpful managerial insights. [ABSTRACT FROM AUTHOR]

The article is devoted to exploring the possibilities of using online communication channels and modelling the relationship between offline and online channels in social work with traumatized people particularly those affected by the Chernobyl disaster. The distribution of age and number of Internet users for different categories of victims of the Chernobyl disaster has been calculated. It is shown that the percentage of Internet users, including the elderly ones, in foreign countries is higher than in Ukraine, which creates prerequisites for increasing their involvement in online communication. It is established that in the majority of scientific and educational information sources there is no grouping of the victims of the Chernobyl disaster into a separate category of the object of social work, which leads to the necessity of enriching the curricula of social workers’ professional training. [ABSTRACT FROM AUTHOR]

Earthquakes in the past have caused significant damage, injuries, and deaths. The remaining resources do not equal the amount needed. For this reason, effective and efficient disaster management methods are needed. Learning from recent research that describes how they optimize the coordination function of hospital systems to overcome the imbalance between need and care capacity, we add the bed occupancy ratio (BOR) of healthcare facilities to the modeling. This paper aims to provide information about the distribution mechanism for injured victims by minimizing the total time to arrive at the healthcare facility. This victim evacuation modeling uses the integer linear programming method with two scenarios. Simulations were carried out on 164 injured victims, estimated by residents who live in areas that cross the Great Sumatran fault. The results show that the second scenario, which involves distributing it to the nearest healthcare facility, is 3.6 hours shorter compared to taking it to the general hospital in the first scenario. [ABSTRACT FROM AUTHOR]

Purpose: This article argues that transnational multilingual entrepreneurs, particularly immigrant Asian/American small business owners, negotiate their access to disaster recovery-related resources by tactically sharing their own user cases through translocal business networks and developing local ethnocultural collaborative entrepreneurships. Method: This study was based on a 9-month user experience study across 14 entrepreneurial sites in two cities located in U.S.-Mexico border regions. Results: User narratives from this study demonstrate that transnational multilingual small business workers tactically adopted nuanced collaboration tactics in navigating resource-constrained environments in post-pandemic workplace settings. Conclusion: The study findings suggest that the binary notion of use and non-use of multilingual resources and the arrangement of multilingual content in federal disaster relief programs should be reconsidered to better situate human-centered design for transnational multilingual users in workplaces in under-resourced disaster-specific bureaucratic writing contexts. [ABSTRACT FROM AUTHOR]

In recent years, UAV techniques are developing very fast, and UAVs are becoming more and more popular in both civilian and military fields. An important application of UAVs is rescue and disaster relief. In post-earthquake evaluation scenes where it is difficult or dangerous for human to reach, UAVs and sensors can form a wireless sensor network and collect environmental information. In such application scenarios, task allocation algorithms are important for UAVs to collect data efficiently. This paper firstly proposes an improved immune multi-agent algorithm for the offline task allocation stage. The proposed algorithm provides higher accuracy and convergence performance by improving the optimization operation. Then, this paper proposes an improved adaptive discrete cuckoo algorithm for the online task reallocation stage. By introducing adaptive step size transformation and appropriate local optimization operator, the speed of convergence is accelerated, making it suitable for real-time online task reallocation. Simulation results have proved the effectiveness of the proposed task allocation algorithms. [ABSTRACT FROM AUTHOR]

Rapid response to emergency needs through an efficient emergency shelter relief system is crucial to mitigate the impact of disasters in affected areas. This paper discusses the location of different types of emergency shelter, the allocation of evacuees, and the assignment of materials on demand in layers. Based on the proposed conceptual framework for emergency relief at three levels, the method provides for three recursive mechanisms: (1) the number of evacuees and materials demand forecasting, (2) shelter location and evacuee allocation, and (3) materials assignment. The paper formulates a hybrid algorithm by proposing fuzzy clustering, multi-objective and dynamic models. The objectives of the proposition are to minimize the number of shelters selected and the evacuation distance and maximize the satisfaction rate of materials demand. The robustness and performance of the proposed model are illustrated by a numerical study of an actual large-scale earthquake in China. The framework can ensure that emergency rescue operations are carried out orderly and efficiently. [ABSTRACT FROM AUTHOR]

Purpose: The purpose of this article is to propose a Global Performance Index for humanitarian NGOs that operate on a global basis The proposed index also includes a list of indicators for measuring the performance’s effectiveness in the economic, operational, and social areas. Design/methodology/approach: The analysis of existing theoretical concepts of performance measurement contributed to the development of a model of NGO organizational performance and three key elements emerged: 1. operational effectiveness, 2. economic effectiveness, and 3. social effectiveness. Based on the credit scoring method the list of indicators developed a proposal for a Global Performance Index for humanitarian NGOs operating globally. Conclusions: The Global Performance Index, together with a proposal of indicators, allows the measurement of NGO performance. It also takes into account specific aspects of international humanitarian NGOs in areas such as their non-profit purpose, their field of activity (emergency relief and development), and their necessary effectiveness and efficiency to gain legitimacy from public and private donors. Research limitations/conclusions: The limitations of the concept adopted relate to the choice and weighting of measurement criteria. Even if we take into account the actual historical data of the organization, as well as documents specific to the donors or the organizations themselves, there remains a bias of subjectivity that needs to be reduced by specific applications. This would allow testing both the validity of the selected criteria and their relative importance in measuring performance. Such application would benefit from being complemented by analyses of failure situations and stakeholder consultation. Practical implications: This index of NGO performance indicators may become a tool for potential investors or donors who would like to assess the health of such organizations. Originality/value: The methodological approach adopted in the article for assessing the performance of NGOs, the model developed and the list of indicators is novel and may, in further research, form the basis for creating comprehensive performance measurement indices for NGOs. [ABSTRACT FROM AUTHOR]

Because of its large capacity, high efficiency and energy savings, the subway has gradually become the primary mode of transportation for citizens. A high density of passengers exists within a large-passenger-flow subway station, and the number of casualties and injuries during a fire emergency is substantial. In this paper, Pathfinder software and on-site measured data of Pingzhou station in Shenzhen (China) were utilized to simulate a fire emergency evacuation in a large-passenger-flow subway station. The Required Safe Egress Time (RSET), number of passengers and flow rates of stairs and escalators were analysed for three fire evacuation scenarios: train fire, platform fire and hall fire. The evacuation time of the train fire, which was 1173 s, was the longest, and 3621 occupants needed to evacuate when the train was fully loaded. Occupants could not complete the evacuation within 6 mins in all three fire evacuation scenarios, which does not meet the current standard requirements and codes. By changing the number of passengers and the number of stairs for evacuation, the flow rate capacity and evacuation time were explored, which have reference values for safety management and emergency evacuation plan optimization during peak hours of subway operation. [ABSTRACT FROM AUTHOR]

Copyright of Chinese Medical Equipment Journal is the property of Chinese Medical Equipment Journal Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This study achieved the construction of earthquake disaster scenarios based on physics-based methods—from fault dynamic rupture to seismic wave propagation—and then population and economic loss estimations. The physics-based dynamic rupture and strong ground motion simulations can fully consider the three-dimensional complexity of physical parameters such as fault geometry, stress field, rock properties, and terrain. Quantitative analysis of multiple seismic disaster scenarios along the Qujiang Fault in western Yunnan Province in southwestern China based on different nucleation locations was achieved. The results indicate that the northwestern segment of the Qujiang Fault is expected to experience significantly higher levels of damage compared to the southeastern segment. Additionally, there are significant variations in human losses, even though the economic losses are similar across different scenarios. Dali Bai Autonomous Prefecture, Chuxiong Yi Autonomous Prefecture, Yuxi City, Honghe Hani and Yi Autonomous Prefecture, and Wenshan Zhuang and Miao Autonomous Prefecture were identified as at medium to high seismic risks, with Yuxi and Honghe being particularly vulnerable. Implementing targeted earthquake prevention measures in Yuxi and Honghe will significantly mitigate the potential risks posed by the Qujiang Fault. Notably, although the fault is within Yuxi, Honghe is likely to suffer the most severe damage. These findings emphasize the importance of considering rupture directivity and its influence on ground motion distribution when assessing seismic risk. [ABSTRACT FROM AUTHOR]

Disaster information content is an objective mapping of disaster situations, social response, and public opinions. Social response to emergency is an important mechanism for implementing and guaranteeing emergency management of major natural hazard-related disasters. Understanding how disaster information content affects social response to emergencies is helpful for managing risk communication and efficient disaster response. Based on the 2008 freezing-rain and snowstorm disasters in southern China, this study used Python to extract 7,857 case-related media reports and applied natural language processing for text analysis. It used three typical cases to identify and analyze disaster media report content and the relationship between these reports and the social response to the emergency. Eight categories of disaster response—such as prewarning and forecasting, announcements by the authorities, and social mobilization—appeared in the disaster information in the media, along with disaster impact information, that is, real-time disaster status. Disaster response information and an appropriate amount of disaster impact information played important roles in prewarning, disaster relief, public opinion guidance, and social stability maintenance and can serve important functions in communicating with all stakeholders of emergency management, assisting or influencing emergency departments or individuals in decision making, and eliminating "information islands." Empathy caused the general public to become "disaster responders" through receiving information. Rumors and an excess of negative information may have a perverse amplification effect on public opinion and increase the unpredictability of the disaster situation and the risk of social crisis. [ABSTRACT FROM AUTHOR]

Adhoc network expansion to FANET has attracted researchers and different companies to think of it as a trade and let users use it as per their needs. Mobility, in contrast to the mobile revolution, has led to its implementation on different networks. FANET is a case where mobility is inculcated with flying nodes where UAVs are deployed in real-time scenarios linked together-operating cooperatively in the best possible coordination for successful data transmission to a base station. The operational efficiency of such networks is in different rapidly changing missions, from line-of-sight to beyond-line-of-sight. Mission applicability ranging from rescue, disaster relief, army, surveillance, delivery of goods, agriculture, 3D mapping, and many others necessitates the development of a competent routing protocol that takes into account the nature of the application and amenities for positioning UAVs. Routing in UAVs has serious questions owing to its fast mobility, sometimes static and, at the same time, static with dynamic. According to recent studies, directed transmission and reception can achieve significant throughput improvements over omnidirectional transmission and reception. Numerous routing protocols are proposed, but each has its pros and cons for such dynamic flying networks. This paper presents the simulation-based performance of the OLSR routing protocol in various propagation models for FANET with directional antenna in different scenarios and considerations (parameters). [ABSTRACT FROM AUTHOR]

Identification of infrastructure and human damage assessment tweets is beneficial to disaster management organizations as well as victims during a disaster. Most of the prior works focused on the detection of informative/situational tweets, and infrastructure damage, only one focused on human damage. This study presents a novel approach for detecting damage assessment tweets involving infrastructure and human damages. We investigated the potential of the Bidirectional Encoder Representations from Transformer (BERT) model to learn universal contextualized representations targeting to demonstrate its effectiveness for binary and multi-class classification of disaster damage assessment tweets. The objective is to exploit a pre-trained BERT as a transfer learning mechanism after fine-tuning important hyper-parameters on the CrisisMMD dataset containing seven disasters. The effectiveness of fine-tuned BERT is compared with five benchmarks and nine comparable models by conducting exhaustive experiments. The findings show that the fine-tuned BERT outperformed all benchmarks and comparable models and achieved state-of-the-art performance by demonstrating up to 95.12% macro-f1-score, and 88% macro-f1-score for binary and multi-class classification. Specifically, the improvement in the classification of human damage is promising. [ABSTRACT FROM AUTHOR]

The internal structural details of unknown structures are very helpful to our personnel in carrying out activities during anti-terrorism operations and emergency disaster relief operations in urban environments. According to multipath identification and propagation mechanism separation technology, a building structure perspective imaging algorithm based on the ray-tracing model is proposed in this paper by making full use of the rich multipath delay power spectrum information and gradually filtering the multipath. Based on the imaging results taking overall consideration of all the propagation factors involved, the presented study is used to obtain the intricate geometric structure of indoor buildings. The original approach is then verified by using measured data, and the proposed algorithm is further optimized by extracting the internal wall structure of the building scene based on the Hough transform algorithm. In comparison with the real wall of the building, the average error of the inverse building wall position using simulated data is 0.071 m, and the average error of the inverse building wall position using the measured data is 0.355 m. [ABSTRACT FROM AUTHOR]

The scientific evidence based on experiences with past disasters points to the possibility of the occurrence of future mental health issues among those who were affected by the recent Turkey–Syria earthquake. However, post-disaster care information on factors that could give rise to mental health issues among those affected have yet to be provided. In March 2011, Tohoku University compiled and published a booklet with post-disaster healthcare information based on the experiences with the Great East Japan Earthquake. This study aimed to promote the introduction and use of this booklet for post-disaster care in Turkey and Syria by presenting the results of a satisfaction survey conducted with relevant Japanese organizations about the booklet. A total of 505 Japanese organizations participated in the satisfaction survey of, and evaluated, the booklet. The results indicated the need to consider the ease of understanding for the general public when providing information on post-disaster care through booklets. We hope that this study leads to the appropriate provision of easy-to-understand, post-disaster healthcare information to the victims of the Turkey–Syria earthquake and future disasters. [ABSTRACT FROM AUTHOR]

Chinese civilian rescue teams (CRTs) emergency response to major disasters in China has effectively complemented national and regional government emergency management systems. However, there has been little research into the CRT's functions or their joint disaster relief procedures. This study employed in-depth interviews and social network analysis to investigate the CRTs' functions and joint disaster relief response procedures during the 2021 Henan flood disaster emergency. It was found that the CRTs had a five-stage emergency response procedure and varied emergency response roles, with the main emergency support functions being search and rescue people and rescue supply transfers and distribution. During joint relief operations, government departments, the coordination center, public institutions, and foundations interact with CRTs in terms of information, personnel and resources; the coordination center was the main information bridge between the CRTs, the local government, and the other relief actors. As the CRTs were bottom-up participants, when they arrived at the disaster site, they were incorporated into the government-led, top-down command-based disaster relief system. Two CRT joint rescue operations were identified: joint rescue alliances in the same region and same brand joint rescue alliances. The results provide information for possible future policies on CRT regulation and development and the integration of CRTs into multi-organizational disaster and emergency response plans. [ABSTRACT FROM AUTHOR]

Natural disasters, including floods, earthquakes, and hurricanes, result in devastating consequences at the individual and community levels. To date, much of the research reflecting the consequences of natural disasters focuses heavily on victims, with little attention paid to the personnel responding to such disasters. We conducted a systematic review of the challenges faced by military, medical and public safety personnel supporting natural disaster relief operations. Specifically, we report on the current evidence reflecting challenges faced, as well as positive outcomes experienced by military, medical and public safety personnel following deployment to natural disasters. The review included 382 studies. A large proportion of the studies documented experiences of medical workers, followed by volunteers from humanitarian organizations and military personnel. The most frequently reported challenges across the studies were structural (i.e., interactions with the infrastructure or structural institutions), followed by resource limitations, psychological, physical, and social challenges. Over 60% of the articles reviewed documented positive or transformative outcomes following engagement in relief work (e.g., the provision of additional resources, support, and training), as well as self-growth and fulfillment. The current results emphasize the importance of pre-deployment training to better prepare relief workers to manage expected challenges, as well as post-deployment supportive services to mitigate adverse outcomes and support relief workers' well-being. [ABSTRACT FROM AUTHOR]

With scientists warning that climate change will increase the intensity of hurricanes, the Robert T. Stafford Disaster Relief and Emergency Assistance Act (Stafford Act) will be used by the federal government with greater frequency. But the Stafford Act is not without its flaws. After Hurricane Katrina, a Federal Emergency Management Agency (FEMA) officer declared that the Stafford Act is like “bringing a donkey to the Kentucky Derby.”1 In § 5150 of the Stafford Act, Congress directs that “to the extent feasible and practicable,” federal funds should be given to contractors and businesses local to the area affected.2 However, it is unclear what qualifies as “feasible and practicable.” To best prepare for the likely increase in the Stafford Act’s use, Congress should clarify the ambiguity of the term “feasible and practicable” found in the Stafford Act’s § 5150’s preference for local contractors. As of now, the preference for use of local contractors is easily ignored by those responsible for contracting after a disaster. Ignoring local contractors, and instead using larger, out of state companies, contributed to the federal mismanagement after both Hurricanes Katrina and Maria. Failure to clarify this preference will result in more failed federal responses to disasters. This Note will discuss the benefits of the preference for local contractors and recommend two possible definitions of “feasible and practicable” that will ensure that more locals are being used as a part of the federal government’s response to emergencies and major disasters. Finally, the Note will recommend two amendments to the Stafford Act’s reporting requirements of FEMA that will ensure greater accountability and incentivize the use of local contractors. [ABSTRACT FROM AUTHOR]

Natural Disaster is a harsh truth from which nobody can escape and Pakistan has been generally powerless against natural disasters by its novel geo-climatic conditions. Floods, cyclones, tsunamis, droughts, earthquakes, and landslides have been an intermittent peculiarity. Among these floods, earthquakes, and droughts risk are very high. These disasters undermine a huge number of lives and cause enormous scale financial, framework, horticulture, and productivity losses that genuinely block Pakistan's overall development. To limit the harm brought about by disasters, different endeavors have been taken by the government, society, NGOs, and worldwide networks. Disaster management possesses a significant spot in this country's policy framework. The research paper covered the Disaster profile of Pakistan and the Disaster management system in Pakistan in subtleties and concluded with Suggestions. [ABSTRACT FROM AUTHOR]

Researchers across disciplines have long sought to collect 'perishable data' in the context of disasters. Yet, this data type is neither consistently defined nor discussed in specific detail in the literature. To address this gap, this paper defines perishable data and provides guidance on ways to improve both how it is collected and shared. Here, perishable data is conceptualised as highly transient data that may degrade in quality, be irrevocably altered, or be permanently lost if not gathered soon after it is generated. Perishable data may include ephemeral information that must be collected to characterise pre‐existing hazardous conditions, near‐miss events, actual disasters, and longer‐term recovery processes. This data may need to be gathered at multiple points in time across varying geographic scales to accurately characterise exposure, susceptibility to harm, or coping capacity. The paper considers ethical and logistical challenges and discusses opportunities to advance equitable perishable data collection and dissemination. [ABSTRACT FROM AUTHOR]

In disaster rescue, multiple resource allocation strategies before and after disasters are a key research issue. Response planning for sudden-onset disasters must take into account the inherent uncertainties associated with the catastrophe and potential ensuing disasters. This article investigates the problem of resource allocation optimization in the context of natural disasters accompanied by the occurrence of multiple secondary hazards. A two-stage stochastic optimization model is proposed to simulate the scenario of random occurrence and severity of multiple natural hazards to optimize the resource allocation of rescue teams, warehousing items and medical resources when multiple natural hazards occur in combination. A particle swarm optimization (PSO) algorithm is designed and compared with a commercial solver (CPLEX) and lower bound at various scales. The results show that PSO performs optimally for large-scale cases. A case study, undertaken in Beijing, demonstrates that this method can improve the estimated casualty rescue success rate to 90.6%. [ABSTRACT FROM AUTHOR]

Estimating disaster relief supplies is crucial for governments coordinating and executing disaster relief operations. Rapid and accurate estimation of disaster relief supplies can assist the government to optimize the allocation of resources and better organize relief efforts. Traditional approaches for estimating disaster supplies are based on census data and regional risk assessments. However, these methods are often static and lack timely updates, which can result in significant disparities between the availability and demand of relief supplies. Social media, network maps, and other sources of big data contain a large amount of real-time disaster-related information that can promptly reflect the occurrence of a disaster and the relief requirements of the affected residents in a given region. Based on this information, this study presents a model to estimate the demand for disaster relief supplies using social media data. This study employs a deep learning approach to extract real-time disaster information from social media big data and integrates it with a spatial information diffusion model to estimate the population in need of relief in the affected regions. Additionally, this study estimates the demand for emergency materials based on the population in need of relief. These findings indicate that social media data can capture information on the demand for relief materials in disaster-affected regions. Moreover, integrating social media big data with traditional static data can effectively improve the accuracy and timeliness of estimating the demand for disaster relief supplies. [ABSTRACT FROM AUTHOR]

Objective: To map and classify the socio-environmental vulnerability of regions in the municipality of Blumenau (SC) to socio-environmental disasters (floods and landslides) through the construction of a socio-environmental vulnerability index (SEVI) for the period 2000-2020. Method: The SEVI map was developed from a multicriteria analysis with the aid of a geographic information system (GIS). For the SEVI to operate, it was necessary to prepare the indices of environmental susceptibility (ES) and social vulnerability (SV), which were then crossreferenced in an impact matrix. Relevance: To develop a methodology for assessing the socio-environmental vulnerability to disasters, which considers issues related both to the local natural environment and to the ability of social groups to resist/respond to disasters. Results: The results have indicated an increase in informal settlements in permanent preservation areas, environmental degradation, social inequality and consequently a population exposed to risk. In short, Blumenau presents a pattern of high susceptibility and an exacerbated increase in social vulnerability, which thereby configures a highly vulnerable scenario for socioenvironmental disasters. Contributions: Advances made in evaluation research and in formulating integrated management proposals for risk and resilience in the municipalities of Vale do Itajaí/SC/Brazil. In this context, it is essential to understand the scenarios with the greatest impact of socioenvironmental disasters, as a tool for urban planning and disaster risk management in the municipality of Blumenau (SC). [ABSTRACT FROM AUTHOR]

After the natural disasters in the Shaanxi-Gansu-Ningxia border region, the Communist Party of China actively responded and took various relief measures to resettle the victims. Mainly through food and fund supply, prioritizing victims in recruitment, transferring victims to safe place, and providing additional compensation, the production and livelihood of disaster victims were secured. By reviewing the disaster relief of the Communist Party of China, some meaningful experiences and inspirations can be concluded. On the basis of material supplies, psychological and spiritual care should not be neglected; Food and fund supply should be distributed fairly and made fully use of; A joint disaster relief mechanism with other departments should be established and all social forces need be mobilized to participate in the resettlement of disaster victims; Marxist perspectives and methods are to be adopted to guide the resettlement work of disaster victims. [ABSTRACT FROM AUTHOR]

In response to the COVID-19 pandemic, Congress in conjunction with the Small Business Administration (SBA) created the Paycheck Protection Program (PPP) to help small business owners retain employees. We improve on previous literature exploring the relationship between bank density and PPP loan dispersion by implementing precisely geocoded data to map loans to commuting zones. Revisiting results in Deming and Weiler (2023), we confirm the statistically significant relationship between bank density and PPP loans per small business. We consider three distinct periods of lending to analyze how changes in the PPP loan program rules might have impacted dispersion. The coefficient in the regression of loans per small business on bank density is largest in the final wave of lending, and in commuting zones with high loan densities. This suggests that having additional bank branches in the commuting zone may have helped facilitate rapid dispersion of relief funds to high demand areas during the program. [ABSTRACT FROM AUTHOR]

Dr. Rebecca Pender Baum interviews Dr. Cathy Malchiodi, a leading international expert, writer, and educator in the fields of art therapy, expressive arts therapy, as well as, trauma and arts in healthcare. Dr. Malchiodi has over 30 years of experience and education in trauma intervention and disaster relief. This interview will highlight her expressive arts background and the use of this modality in working with families. [ABSTRACT FROM AUTHOR]

This simulation provides public administration, public policy, and management students and practitioners with an immersive disaster scenario. The table-top exercise provides an example of how municipal leaders can prepare for disaster scenarios and the importance of embedding social equity into disaster response. Additionally, it provides an example of how to embed social equity in the planning and development of disaster response planning and preparation. This classroom-based group simulation takes approximately 90 minutes (20 minutes for preparation, 50 minutes for the simulation case study, and 20 minutes for discussion) and also includes barriers to disaster relief experienced by minority populations. The case is organized into three sections and concludes with teaching notes and discussion questions. [ABSTRACT FROM AUTHOR]

This study investigates disaster resilience during major hurricane events by analyzing Twitter data. The study focuses on resilience-relevant tweets during major hurricanes from 2013 to 2020 in the USA that caused over 1 billion dollars in losses. The study explores variations in resilience perceptions across different racial, gender, and political groups, as well as the sentiment expressed in tweets during different phases of the disaster. Additionally, the study examines the alignment of Twitter discussions with the actual phases of the disasters from a spatiotemporal perspective. The findings highlight disparities in resilience perception among racial and gender groups, emphasizing the need for targeted approaches to promote inclusivity and equity in disaster resilience efforts. The importance of early awareness and preparedness is underscored, suggesting the significance of investing in forecasting and early alert systems to reduce the impact of disasters. [ABSTRACT FROM AUTHOR]

Copyright of Critical Planning is the property of Critical Planning and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This article explores the shifting dynamics of US-Thai relations, emphasizing missed opportunities and potential areas of collaboration. Recent Thai elections could have rekindled US enthusiasm as a victory for democracy, but the conservative establishment's actions led to a less democratic outcome. Yet, with a new Thai government and foreign minister, opportunities arise for increased cooperation. Potential areas of focus include safeguarding the Mekong River ecosystem, addressing climate change, and strengthening economic ties in mainland Southeast Asia. Additionally, this shift presents a chance for more constructive dialogue on Myanmar, especially in terms of cross-border humanitarian assistance. In the realm of defense and security, discussions on transforming U-Tapao Air Base into a regional disaster relief hub and addressing potential security concerns, such as Chinese access to Ream Naval Base in Cambodia, are on the horizon. While a return to the alliance's heyday may seem improbable, this article argues that patience, persistence, and an acknowledgment of new geopolitical realities can pave the way for a more productive relationship between these long-standing allies. [ABSTRACT FROM AUTHOR]

Firms responded to the COVID‐19 pandemic by participating in an unprecedented level of corporate social responsibility (CSR). The authors build on the existing CSR and crisis response and disaster relief literatures by examining nine CSR types employed during the pandemic (donating in‐kind, donating money, creating content, free products, free services, communication of operational changes, employee support, financial support, and shifting production). Then, they test the impact of starting versus stopping each CSR type on consumer perceptions of authenticity, attitude, and purchase intentions in two experiments, replicated in 2020, 2021, and 2022. Consumers distinguish between CSR types and rate employee and financial support most favorably and creating content and communication of operational changes least favorably. Starting (vs. stopping or no) CSR increases authenticity and subsequent attitude and purchase intentions. Interestingly, stopping CSR is worse than no CSR in 2020, but no CSR is worse than stopping CSR in 2022. This indicates that consumers discredit firms for stopping CSR during the acute phase of the pandemic but discredit firms for not engaging in any CSR after the acute phase ends. Finally, consumers rate small (vs. large) firms more favorably for engaging in some CSR types. Taken together, these results help inform how firms should engage in CSR activities in response to crises and disasters. [ABSTRACT FROM AUTHOR]

Landslide disasters in Nepal are widely reported to have increased in the last decade, but there has been limited on trends in landslide occurrence in Nepal from 2011 to 2020. This study presents the spatio-temporal distribution and trends of landslide disasters in the Nepal Himalayas and identifies landslide-prone areas. Landslide disaster data was collected to assess annual variations, investigate the relation between rainfall and landslides, describe the landslide distribution pattern, conduct statistical analysis, and predict landslide causes and triggering factors. The dataset suggests that the overall trend in landslide disasters in Nepal from 2011 to 2020 is increasing, with a high level of variability in the number of landslide disasters from year to year, depending on several factors. Results show that landslide events were clustered in space and time, with 93.26% of total landslides occurring in the rainy season. The average density of landslide disasters in 2011 was 0.85 events per 1000 km2 and increased to 3.34 in 2020. The effect of earthquake preconditioning was observed as the landslide disaster rate has been elevated since the 2015 Gorkha earthquake with systematic shifting of locations over time. Power-law relationships fit well for the cumulative frequency distribution of daily landslide disasters and the probability density of time interval between landslides. The gap between landslide events was observed as 1–170 days. Moreover, trend analysis has shown an increasing trend of landslide disasters both seasonally and annually. [ABSTRACT FROM AUTHOR]

Copyright of Voluntaris: Journal of Volunteer Services & Civic Engagement / Zeitschrift für Freiwilligendienste und Zivilgesellschaftliches Engagement is the property of Nomos Verlagsgesellschaft mbH & Co. KG and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Purpose: While researchers recognize the significance of philanthropic donations in disaster relief and recovery, the benefits that firms derive from such donations remain unclear, particularly when firms are adversely impacted by the disaster. To address this gap, this study seeks to elucidate the impact of various donation strategies on firm resilience in the context of the COVID-19 pandemic. Design/methodology/approach: Based on the hand-collected data on donations, the authors employ ordinary least squares regressions to investigate the effectiveness of various donation strategies – including type, timing and location – in enhancing firm resilience in terms of the severity of stock price losses during the pandemic. To address potential endogeneity concerns, the authors use a two-stage least squares regression with instrumental variables. Findings: This study finds robust evidence that certain donation strategies are more effective at mitigating stock price losses during the pandemic. Specifically, the authors find that in-kind donations (compared to monetary ones), earlier donations (compared to later ones) and donations targeting severely impacted areas (Hubei province vs. other places) are more effective methods to reduce the severity of stock price losses. Originality/value: This study points out an alternative mechanism through which donations influence firm resilience during a crisis context and provides important managerial implications for firms to better engage in disaster donations. [ABSTRACT FROM AUTHOR]

Purpose: This paper examines what facilitates the swift reconfiguration of freight movements across transport modes in the wake of a major disaster. Design/methodology/approach: A qualitative research approach focussing on the New Zealand (NZ) domestic freight transport operations in the wake of the 2016 Kaikōura earthquake is used with data collected through 19 interviews with 27 informants. The interviews are thematically analysed by using the framework method. Findings: The paper provides rich and detailed descriptions of the ability of a freight transport system to recover from a disaster through rapid modal shifts. This paper identifies nine factors enabling modular transport operations and highlights the critical role of physical, digital, operational and inter-organisational interconnectivity in the aftermath of a disaster. Originality/value: Although the management of freight disruptions has become a prevalent topic not only in industry and policy-making circles, but also in the academic literature, qualitative research focussing on the ability of commercial freight systems to adapt and recover from a disaster through rapid modal shifts is limited. This qualitative study sheds light on the mechanisms underlying the continuity of freight operations in the wake of a disaster and provides a comprehensive understanding of modular transport operations and the ability of freight systems to keep goods moving. [ABSTRACT FROM AUTHOR]

Earthquakes are one of the major natural disaster threats worldwide and directly cause substantial economic losses and many casualties every year. Research on the resource and environmental carrying capacity in earthquake-prone areas is urgently required for regional earthquake relief efforts and post-disaster reconstruction. This study considered Ganzi Tibetan Autonomous Prefecture (Ganzi Prefecture) in Sichuan Province, China, focusing on the impact of the Luding 6.8 Magnitude Earthquake in Ganzi Prefecture in 2022. An evaluation system for the resource and environmental carrying capacity of earthquake-prone areas was established. A total of 23 indicators were selected that cover ecological, social economical, and geological aspects, and the weight of each index was determined by the Analytic Hierarchy Process. The relative ranking of the resource and environmental carrying capacities of each county and city were calculated using the weighted Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). Consequently, the post-disaster reconstruction strategy of Ganzi Prefecture was evaluated and analyzed. The results show that the resource and environmental carrying capacities of each administrative area differ regionally. Evidence shows that the resource and environmental carrying capacity in southeastern Ganzi Prefecture is generally higher than in the northwest, owing to the joint influence of the social economy and ecological and geological environment. This study provides carrying capacity assessment data and support methods for earthquake-prone areas. [ABSTRACT FROM AUTHOR]

If a firm afflicted by a disaster chooses to donate to disaster relief, how will this decision affect the firm's market value? From a self-protection perspective, diverting resources to support the public may jeopardize a firm's continuity and thereby reduce its value. Yet from a reputation-building perspective, supporting the public in need may enhance corporate reputation and thus increase firm value. In this study, we contrasted the two perspectives to develop a conceptual framework consisting of various competing hypotheses. We tested these hypotheses using data on Chinese firms' donations to disaster relief during the first coronavirus disease 2019 outbreak. Our analysis shows that firms' donations generally led to an increase in firm value. This was especially true for firms that were smaller or less profitable, firms that donated goods in addition to cash, and firms that donated before an increasing number of industry peers had done so. These results support the reputation-building perspective, suggesting that even when firms are afflicted by disaster exposure, their donations are still recognized as a value-adding investment. In contrast, donating a larger amount of cash and donating on an earlier day after the onset of the outbreak resulted in a lower firm value. These results align with the self-protection perspective, pointing to the need to consider resource preservation. [ABSTRACT FROM AUTHOR]

This paper considers a population model (system) which is prone to catastrophe that kills individuals in batches. Individuals enter the system in accordance with the renewal process and catastrophe occurs as per the Poisson process. The catastrophe attacks the population in a successive order in batches of random size, each batch of individuals dies with probability ξ. This successive process ends when the whole population is wiped out or a batch of individuals survives with probability 1 − ξ. This type of killing pattern is known as geometric catastrophe. The supplementary variable technique is used to develop the steady-state governing equations. Further using the difference operator, the distributions of population size are evaluated at arbitrary, pre-arrival, and post-catastrophe epochs. In addition to that, a few different measurements of the system's performance are derived. In order to demonstrate the applicability of the model, a number of numerical and graphical outcomes are presented in the form of tables and graphs. [ABSTRACT FROM AUTHOR]

The frequency and severity of natural or human-induced disaster events, such as floods, earthquakes, hurricanes, fires, pandemics, hazardous material spills, groundwater contamination, structural failures, explosions, etc., as well as their impacts, have greatly increased in recent decades due to population growth and extensive urbanization, among other factors. The World Bank estimates that the total cost of cities' and communities' vulnerability to these types of disasters could reach more than USD 300 billion per year by 2030. However, it has been argued that investment to improve the quality and resilience of engineered physical assets that are the backbone of modern societies, such as critical infrastructure, industrial facilities, and buildings, could significantly contribute to more sustainable and prosperous societies. Engineered assets are key to the delivery of essential services, such as transport, food, water, electricity supply, health and safety, etc. Some of these physical assets are integrated into asset systems and national or regional networks, with life cycles of several decades or even centuries. It is, therefore, of great importance that strategies and life cycle decisions, such as those related to short- and long-term capital investment planning, maintenance strategies, operational plans, and asset disposal, lead to the maximization of the value derived from these assets. Moreover, it is essential that the achievement of these goals is sustainable over time. Organizations dealing with engineering assets, both public and private, must, therefore, integrate sustainability and resilience concerns into everyday operations, using budgets that are often restricted, while also meeting demanding performance requirements in risky and uncertain environments. This Special Issue collates a selection of papers reporting the latest research and case studies regarding the trends and emerging strategies used to address these challenges, with contributions discussing how asset management principles and techniques can help to push the boundaries of sophistication and innovation to improve the life cycle management of engineered assets to ensure more sustainable and resilient cities and societies. [ABSTRACT FROM AUTHOR]

Wireless Multimedia Sensor Networks (WMSNs) have been an essential part of our lives, with various applications from disaster assistance to medical services. As a result, the lifetime and energy consumption of WMSNs have become challenging research issues. In the previous decades, a large number of protocols have been established to improve the energy efficiency of WMSNs. One of the proposed solutions is clustering. The cluster head selection criteria, network architecture, and heterogeneity are mostly addressed in these protocols. In this paper, we proposed an Energy-Efficient Multipath Clustering with Load Balancing Routing Protocol for Wireless Multimedia Sensor Networks (EEMCL). In the proposed protocol, the main cluster heads (MCHs) are preselected in each cluster in the network field with more energy than normal sensor nodes. The selection of two secondary cluster heads (SCHs) by the main cluster heads algorithm is used in which nodes have higher energy will be chosen as SCHs. Moreover, inter-cluster multi-hop routing with the help of MCHs can enhance the network lifetime when the sink is located at the corner of the network area. The MATLAB simulation tool is used to investigate the performance of the proposed protocol EEMCL. The results have been shown that the best position of the base station (BS) is at the center of the network area which can prolong the lifetime of sensor nodes, and random distribution of the sensor nodes gives better performance relating to the residual energy and the nodes still alive than static distribution. [ABSTRACT FROM AUTHOR]