E. Whitney Pollio^1,*, David E. Pollio², Carol S. North^3,4

International Journal of Mental Health Promotion, Vol.27, No.10, pp. 1483-1495, 2025, DOI:10.32604/ijmhp.2025.067755 - 31 October 2025

Abstract Objectives: At the time of the bombing of the federal building in Oklahoma City, Oklahoma (OKC), it was the deadliest terrorist attack in the United States of America. Available research on this incident, and in general, has been quantitative, using deductive methods. The purpose of the current study was to systematically examine professional disaster response workers’ emotions elicited spontaneously and in detail as they were experienced over time after a major disaster. This qualitative study will add to existing knowledge of psychopathology and the psychosocial effects of disasters on professional responders, which have not been… More >

Cesar E. Montelongo Hernandez^1,*, Carol S. North¹, E. Whitney Pollio², David E. Pollio³

International Journal of Mental Health Promotion, Vol.27, No.6, pp. 737-752, 2025, DOI:10.32604/ijmhp.2025.065317 - 30 June 2025

Abstract Background: Disaster mental health outcomes of individuals may be affected by the families they inhabit, with effects rippling through the entire family system. Existing research on the experience of children in disasters has typically been limited to examining single individuals or, at most, family dyads. Research is needed to explore interactions within families as a whole, including interactions among multiple family members, as well as with community entities in a broad systems approach with dynamic analysis of family systems over time. The purpose of this study was to combine quantitative and qualitative data using structured… More >

Zhengzheng Cao¹, Shuaiyang Zhang¹, Cunhan Huang^2,*, Feng Du^3,4, Zhenhua Li^3,4, Shuren Wang¹, Wenqiang Wang^3,4, Minglei Zhai^3,4

FDMP-Fluid Dynamics & Materials Processing, Vol.21, No.5, pp. 1007-1028, 2025, DOI:10.32604/fdmp.2025.062738 - 30 May 2025

Abstract Karst collapse columns typically appear unpredictably and without a uniform spatial arrangement, posing challenges for mining operations and water inrush risk assessment. As major structural pathways for mine water inrush, they are responsible for some of the most frequent and severe water-related disasters in coal mining. Understanding the mechanisms of water inrush in these collapse columns is therefore essential for effective disaster prevention and control, making it a key research priority. Additionally, investigating the developmental characteristics of collapse columns is crucial for analyzing seepage instability mechanisms. In such a context, this paper provides a comprehensive… More > Graphic Abstract

Stephen Afrifa^1,2,*, Vijayakumar Varadarajan^3,4,5,*, Peter Appiahene², Tao Zhang¹, Richmond Afrifa⁶

Computer Systems Science and Engineering, Vol.48, No.6, pp. 1625-1639, 2024, DOI:10.32604/csse.2024.055084 - 22 November 2024

Abstract Users of social networks can readily express their thoughts on websites like Twitter (now X), Facebook, and Instagram. The volume of textual data flowing from users has greatly increased with the advent of social media in comparison to traditional media. For instance, using natural language processing (NLP) methods, social media can be leveraged to obtain crucial information on the present situation during disasters. In this work, tweets on the Uttarakhand flash flood are analyzed using a hybrid NLP model. This investigation employed sentiment analysis (SA) to determine the people’s expressed negative attitudes regarding the disaster. More >

Yue He¹, Yaxiong You¹, Zhian He¹, Haiying Lu¹, Lei Chen^2,*, Yuqi Jiang², Hongkun Chen²

Energy Engineering, Vol.121, No.10, pp. 2825-2849, 2024, DOI:10.32604/ee.2024.052371 - 11 September 2024

Abstract In recent times, the impact of typhoon disasters on integrated energy active distribution networks (IEADNs) has received increasing attention, particularly, in terms of effective cascading fault path prediction and enhanced fault recovery performance. In this study, we propose a modified ORNL-PSerc-Alaska (OPA) model based on optimal power flow (OPF) calculation to forecast IEADN cascading fault paths. We first established the topology and operational model of the IEADNs, and the typical fault scenario was chosen according to the component fault probability and information entropy. The modified OPA model consisted of two layers: An upper-layer model to More >

Maan Habib^1,*, Ahed Habib², Mohammad Abboud³

Revue Internationale de Géomatique, Vol.33, pp. 247-271, 2024, DOI:10.32604/rig.2024.053857 - 07 August 2024

Abstract Digital elevation models (DEMs) are essential tools in environmental science, particularly for hazard assessments and landscape analyses. However, their application across multiple environmental hazards simultaneously remains in need for a multi-aspect critical assessment to promote their effectiveness in comprehensive risk management. This paper aims to review and critically assess the application of DEMs in mapping and managing specific environmental hazards, namely floods, landslides, and coastal erosion. In this regard, it seeks to promote their utility of hazard maps as key tools in disaster risk reduction and environmental planning by employing high-resolution DEMs integrated with advanced More >

Yun-Jung Choi^1,#,*, Jae-Won Kwak^2,#, Hae-In Namgung³

International Journal of Mental Health Promotion, Vol.26, No.6, pp. 439-447, 2024, DOI:10.32604/ijmhp.2024.050458 - 28 June 2024

Abstract This study evaluated the state of anxiety, depression, post-traumatic stress disorder, general mental health, and mental well-being among citizens after a crowd-crush disaster in Korea. Individuals who experienced the crowd crush had significantly higher anxiety, depression, and post-traumatic stress disorder (PTSD) scores than those who did not (p < 0.001). Additionally, people who avoided the disaster area had significantly higher depression and PTSD scores than those who did not avoid the area (p < 0.001). Those who directly witnessed the Seoul Halloween crowd crush had a significant difference in PTSD levels in either group than those More >

Rana Muhammad Zulqarnain¹, Hafiz Khalil ur Rehman², Imran Siddique³, Hijaz Ahmad^4,5, Sameh Askar⁶, Shahid Hussain Gurmani^1,*

CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.2, pp. 1863-1892, 2024, DOI:10.32604/cmes.2023.031480 - 29 January 2024

Abstract This research is devoted to diagnosing water-borne infectious diseases caused by floods employing a novel diagnosis approach, the Einstein hybrid structure of q-rung orthopair fuzzy soft set. This approach integrates parts of fuzzy logic and soft set theory to develop a robust alternative for disease detection in stressful situations, especially in areas affected by floods. Compared to the traditional intuitionistic fuzzy soft set and Pythagorean fuzzy soft set, the q-rung orthopair fuzzy soft set (q-ROFSS) adequately incorporates unclear and indeterminate facts. The major objective of this investigation is to formulate the q-rung orthopair fuzzy soft… More >

Yongxin Liu¹, Puyu Zhao², Jianxin Xu², Xiaokai Meng¹, Hong Yang¹, Bo He^2,*

Structural Durability & Health Monitoring, Vol.17, No.6, pp. 521-539, 2023, DOI:10.32604/sdhm.2023.029850 - 17 November 2023

Abstract Numerical simulation of the spatial wind field plays a very important role in the study of wind-induced response law of transmission tower structures. A reasonable construction of a numerical simulation method of the wind field is conducive to the study of wind-induced response law under the action of an actual wind field. Currently, many research studies rely on simulating spatial wind fields as Gaussian wind, often overlooking the basic non-Gaussian characteristics. This paper aims to provide a comprehensive overview of the historical development and current state of spatial wind field simulations, along with a detailed… More > Graphic Abstract

Jayaraj Thankappan¹, Delphin Raj Kesari Mary², Dong Jin Yoon³, Soo-Hyun Park^4,*

CMC-Computers, Materials & Continua, Vol.77, No.1, pp. 1053-1079, 2023, DOI:10.32604/cmc.2023.038437 - 31 October 2023

Abstract Flooding is a hazardous natural calamity that causes significant damage to lives and infrastructure in the real world. Therefore, timely and accurate decision-making is essential for mitigating flood-related damages. The traditional flood prediction techniques often encounter challenges in accuracy, timeliness, complexity in handling dynamic flood patterns and leading to substandard flood management strategies. To address these challenges, there is a need for advanced machine learning models that can effectively analyze Internet of Things (IoT)-generated flood data and provide timely and accurate flood predictions. This paper proposes a novel approach-the Adaptive Momentum and Backpropagation (AM-BP) algorithm-for… More >