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As electric vehicle (EV) adoption increases, transportation services will shift dependence from liquid fuel infrastructure to electric power infrastructure. Since transportation plays a major role in disaster response and recovery, this shift in dependence has important implications for coupling electrical grids and transport resilience. The implications for the electrical grid for southwestern British Columbia, Canada are examined, motivated by this region's high EV adoption rate and the potential for a catastrophic magnitude 9.5 earthquake. A comparison of the resilience of the electrical infrastructure compared to the fuel infrastructure is provided and approaches for increasing resilience in the region for EV power supply are discussed. This paper compiles lessons learned from past large earthquakes in Chile, Japan, and New Zealand with consideration given to successes and failures. While this paper was written with a focus on southwestern British Columbia, many of the suggestions for increasing power system resilience could be applied in other seismically active locations during the transition to EVs. This paper also considers integrated disaster resilience planning for the changing transport landscape from fuel vehicles to EVs. [ABSTRACT FROM AUTHOR]

This paper serves as an introduction to focus on the meaning of resilience as a notion that hypothetically enables cities and their citizens to remain unaffected by shocks and stresses of diverse nature, but in practice, is a parsimonious representation of a highly complex human endogenous condition that is often not adequately understood and addressed due to weak or weathered disaster risk governance. Through an empirical analysis, the relevance of the occurrence of disasters such as the one produced by the Mexico City earthquake of September 19, 2017, and its relationship to the meaning of urban resilience is addressed. Since the 100 Resilient Cities program launch in 2013, several cities, including Mexico City, have adopted diverse strategies to build and become more resilient to physical, social, and economic shocks and stresses. Nonetheless, the degree of success of such strategies expressed in everyday life within the cities, regardless of what the official documents report, reveals highly heterogeneous results. In the case of Mexico City, it is evident that the appropriate strategy for attaining the desired outcome of becoming a Resilient City has not been successful. Despite setting the goal of advancing disaster risk reduction through urban and regional planning, the impact of the earthquake of September 19, 2017, proved otherwise. [ABSTRACT FROM AUTHOR]

Despite the great development and advancement of technology over time, the problem of disaster and crisis management and dealing with it remains a major and great challenge. Early detection of natural disasters, strict laws against man-made disasters, and even the enforcement of the safety requirements for industrial disasters could not stop the occurrence of disasters and crises that leave devastation, general disability, suffering, and deprivation, in addition to injuries, wounded, victims, and even missing and dead human beings. Therefore, technologies, algorithms, and modern methods such as mechanical, electronic, robots, image, and signal processing, artificial intelligence, wireless communication, and so on must be harnessed to deal with disasters after their occurrence as well as limit their effects. Because preserving the lives of people and helping them is greatly important, this research has been prepared to review the work and techniques of researchers. The reviewed research dealt with the early detection of disasters and managing them in the fastest time and with high efficiency, including detecting and locating victims and also relieving survivors to reduce the psychological, physical, and economic impact of these disasters. Also, the paper presented the development of using some technology as a robot in this field. This paper can be a base for other researchers and rescue workers to improve and enhance their operations or mission of managing disasters or crises. [ABSTRACT FROM AUTHOR]

The strong spatial nonuniformity of dam soil is a key factor for studying the safety and stability of landslide dams. In this paper, a 500 × 500 × 500 mm cubic model box was made, and the dam soil was deposited in it by layered deposition and different sliding angles to investigate the nonuniformity of the deposition. The depositional characteristics and particle size distribution (PSD) variations in different zones of different depositions were analyzed. Furthermore, based on the basic principle of grading entropy, the particle distributions of different depositions using the entropy parameter A−B coordinates were discussed. Finally, an index of nonuniformity Nd was proposed to quantitatively assess the nonuniformity degree of the deposition. We yielded that as the sliding angle increased, the deposition showed prominent sorting characteristics in the sliding direction. The coarser and finer particles were mainly concentrated in the front and back parts of the deposition, respectively. Compared with the traditional characteristic parameters, the grading entropy is more meticulous for characterizing the PSD curve. In the entropy parameter A−B coordinates, the points for the expected uniform deposition are more concentrated, which indicates that the nonuniformity of this deposition is smaller. The points of different zones for the sliding deposition are arch-shaped, and their distribution is more dispersed and directional in these coordinates, which indicates a greater nonuniformity of this deposition. For the sliding deposition, the index of nonuniformity Nd of different depositions tends to increase and then decrease with increasing sliding angle. The Nd of the deposition made by the sliding angle of 60° is the largest at 0.173. However, that of the expected uniform deposition is only 0.057. This study improves the understanding of spatial nonuniformity and aids the disaster prevention and mitigation of landslide dams. [ABSTRACT FROM AUTHOR]

This study investigates the intricate relationship between natural disasters and regional entrepreneurship in Türkiye, a developing nation highly vulnerable to earthquakes, floods, and other hazards. The study extends Hierarchical Multiple Regression (HMR) analysis (1990–2020, 81 NUTS-III regions), beyond existing literature focused on physical damage. Our findings reveal a counterintuitive effect: while the number of disasters and total property damage correlate positively with regional entrepreneurship, human life loss has a negative impact. This suggests a complex interplay between destruction and entrepreneurial spirit. Further analyses using Discriminant Function Analysis (DFA) and MANOVA-ANOVA for robustness check explores regional characteristics that contribute to entrepreneurial resilience against natural disasters. By comparing regions categorized by entrepreneurial performance and disaster exposure, the study identifies key differentiators. Regions with supportive business environments demonstrate greater resilience, highlighting the crucial role of fostering a strong entrepreneurial ecosystem in mitigating disaster effects. This research fills a critical gap by examining the understudied relationship between natural disasters and regional entrepreneurship, going beyond individual firm-level studies. By analysing interregional disparities and resilience factors, this paper provides valuable insights for both regional development and entrepreneurship & resilience literature. It emphasizes the importance of human capital alongside disaster preparedness and institutional quality in building regional resilience. [ABSTRACT FROM AUTHOR]

Landslides, widespread and highly dangerous geological disasters, pose significant risks to humankind and the ecological environment. Consequently, predicting landslides is vital for disaster prevention and mitigation strategies. At present, the predominant methods for predicting landslide susceptibility are evolving from conventional machine learning techniques to deep learning approaches. At present, the predominant methods for predicting landslide susceptibility are evolving from conventional machine learning techniques to deep learning approaches. Prior studies have shown that in the context of landslide susceptibility, these models frequently underperform relative to tree-based machine learning algorithms. This shortcoming has restricted the application of deep learning in this domain. To overcome this challenge, this study presents the TabNet algorithm, which combines the interpretability and selective feature extraction of tree models with the representation learning and comprehensive training capabilities of neural network models. This paper explores the potential of employing the TabNet algorithm for landslide susceptibility analysis in China's WanZhou region and evaluates its performance against traditional machine learning techniques. The experimental data indicate that the TabNet algorithm achieves a recall score of 0.898 and an AUC of 0.915, demonstrating a generalization capability that is comparable to that of classical machine learning algorithms. [ABSTRACT FROM AUTHOR]

Selecting appropriate mapping units is vital for landslide susceptibility mapping as well as pattern investigation, given that various units-based analyses extensively control the prediction performances. This paper investigated the landslide development through the interpretation and field surveys along the Yunling–Yanjing segment of the Lancang River in southeastern Tibet, and fulfil LSM with the consideration of 15 conditioning factors. Two grid unit methods (single-point and multi-point patterns) and two slope unit methods were comparatively analyzed for model training and mapping of landslide susceptibility via machine learning algorithms. The results suggest that the landslides are preferentially distributed in an elevation range of 2000–4000 m, in a slope range of 20–40°, a local relief range of 1000–2500 m, and southwest-oriented slopes. The data extracted by the multi-point method denotes a higher representation of landslide development features. All models possessed positive prediction ability for landslide susceptibility, and the multi-point method based on grid unit performed the best with the AUC exceeding 0.9. The best-performing models indicated that zones of high and very high susceptibility mainly distributed adjacent to the mainstem and some tributaries of the Lancang River. Furthermore, the distribution of "safety islands" (the slopes less prone to landslides) along National Highway G214 was reasonably illustrated as well, which provides a hazard predictability for such an important transportation corridor along the deeply-incised valley in the Lancang River. This study demonstrates a theoretical basis for the regional disaster prevention and mitigation for human activity, and provides methodological references for landslide susceptibility evaluation in similar mountainous areas over the world. [ABSTRACT FROM AUTHOR]

In disaster scholarship, there is limited understanding about how vulnerability is socially constructed by a convergence of varying social structural and historical processes that predispose certain vulnerable groups to disasters even before a hazard event occurs. This article aims to fill this void by using Critical Disaster Studies perspectives to explore the root causes of why crop farmers in the coastal region of the Vietnamese Mekong Delta have been locked in a permanent position of vulnerability. In order to develop more sustainable food supply chains, this exploration aims to shed light on the socio-cultural interpretations, experiences, and needs of disaster-affected farmers—the most important but vulnerable actors in the crop production hierarchy in Vietnam. Following a historic disaster between late 2015 and early 2016, local governments deliberately organised farmers into an agricultural cooperative in an attempt to support farmers in enhancing economic resilience and disaster preparedness. However, this intervention has failed since farmers refused to participate in the organisation's activities. While this reaction may seem irrational, it reflects farmers' distrust in the government, which was largely a result of their collective trauma from the state's agricultural collectivisation policy implemented between 1976 and 1985. Farmers chose to cling to their individual working routines out of concern about government supervision, forcing them to take bigger risks and pay for the food supply chains' catastrophic damage. Our findings show that a strained relationship between farmers and the government can jeopardise disaster recovery and resilience building. Our paper adds to the Critical Disaster Studies literature by revisiting the concepts of vulnerability and resilience, emphasising the importance of addressing socio-cultural vulnerability before improving disaster resilience. [ABSTRACT FROM AUTHOR]

After thirty-two years of the devastating earthquake in Mexico City in 1985, the city was again shaken by the consequences of the 7.1 Mw earthquake that struck central Mexico on September 19, 2017. The impact of the disaster nationwide was 369 deaths, 6000 injured, 256,000 total affected people, and damages in the order of US$ 6 billion. Although the earthquake's impact figures are not consistent yet, some sources indicate that in Mexico City alone, the earthquake caused 228 deaths, 44 collapsed buildings, and 73,000 damaged properties, including 5765 homes and 973 schools. The effect on the economy was estimated at between 0.1 and 0.3% of GDP for 2018, and the funds needed for reconstruction were calculated at more than US$3.4 billion. Local government responses to the earthquake were dosed and limited to immediate actions based on a traditional and militarized perspective. Once again, after the quake hit, city authorities and urban planners introduced several actions and initiatives to rethink how disasters can be managed in the city. Regular assessment of impacts on the security of the facilities at risk, liability, damages and losses initiatives, changes to the law, and purges in the local civil protection offices were carried on. As we argue in this article, all these actions are increasingly seen as a cause of serious concerns about the accountability of the authorities responsible for civil protection and risk management at the different levels of government. This article briefly introduces the renewed interest that has emerged in recent years around the globe, including Mexico City, regarding the increasing demands for accountability related to disasters. In the second section, the methodology of the article is described. It will then examine the results and discussion of the analysis of the disaster triggered by the earthquake of September 19, 2017. This included three major topics: (1) background from a hazard perspective and a general characterization of earthquake exposure, (2) damages and losses, and (3) insights into disaster management. The final section concerning closing remarks aims to reflect on future challenges for disaster accountability and community involvement in disaster risk management. [ABSTRACT FROM AUTHOR]