Nur Syaiful Afrizal¹, Khairul Adib Yusof^1,2,*, Lokman Hakim Muhamad¹, Nurul Shazana Abdul Hamid^2,3, Mardina Abdullah^2,4, Mohd Amiruddin Abd Rahman¹, Syamsiah Mashohor⁵, Masashi Hayakawa^6,7

CMC-Computers, Materials & Continua, Vol.86, No.2, pp. 1-16, 2026, DOI:10.32604/cmc.2025.066421 - 09 December 2025

Abstract Detecting geomagnetic anomalies preceding earthquakes is a challenging yet promising area of research that has gained increasing attention in recent years. This study introduces a novel reconstruction-based modeling approach enhanced by negative learning, employing a Bidirectional Long Short-Term Memory (BiLSTM) network explicitly trained to accurately reconstruct non-seismic geomagnetic signals while intentionally amplifying reconstruction errors for seismic signals. By penalizing the model for accurately reconstructing seismic anomalies, the negative learning approach effectively magnifies the differences between normal and anomalous data. This strategic differentiation enhances the sensitivity of the BiLSTM network, enabling improved detection of subtle geomagnetic More >

Burak Canpolat^1,*, Göktuğ Norman², Cemal Gündoğdu², Şakir Tüfekçi², Yalın Aygün², Taylan Akbuğa³

International Journal of Mental Health Promotion, Vol.27, No.11, pp. 1781-1795, 2025, DOI:10.32604/ijmhp.2025.069852 - 28 November 2025

Abstract Objectives: This study examines the effectiveness of an eight-week game-based physical activity program designed to reduce post-traumatic stress levels in children affected by the Kahramanmaraş-centered earthquakes that occurred in Turkey on 06 February 2023. Following the earthquake, millions of children experienced significant changes in their education and living conditions, adversely affecting their psychological health. Methods: The therapeutic effects of physical activity on post-traumatic stress disorder (PTSD) are frequently emphasized in the literature, and this study specifically focuses on the impact of game-based exercises. The research employed an experimental design, involving 80 earthquake-affected children aged 10 to… More >

Xinrui Ma, Shizhi Chen^*

Structural Durability & Health Monitoring, Vol.19, No.6, pp. 1745-1767, 2025, DOI:10.32604/sdhm.2025.071148 - 17 November 2025

Abstract The rapid and accurate assessment of structural damage following an earthquake is crucial for effective emergency response and post-disaster recovery. Traditional manual inspection methods are often slow, labor-intensive, and prone to human error. To address these challenges, this study proposes STPEIC (Swin Transformer-based Framework for Interpretable Post-Earthquake Structural Classification), an automated deep learning framework designed for analyzing post-earthquake images. STPEIC performs two key tasks: structural components classification and damage level classification. By leveraging the hierarchical attention mechanisms of the Swin Transformer (Shifted Window Transformer), the model achieves 85.4% accuracy in structural component classification and 85.1% More >

Harsh Kumar¹, Shilpa Suman², Abhishek Rawat^2,*, Rajat Subhra Chatterjee³, Dheeraj Kumar⁴, B. S. Chaudhary⁵

Revue Internationale de Géomatique, Vol.34, pp. 351-362, 2025, DOI:10.32604/rig.2025.064031 - 30 June 2025

Abstract The unconsolidated soils of the Indo-Gangetic Plains (IGP) contribute significantly to the amplification of seismic damage during earthquakes. Site-specific effects play a critical role in intensifying ground motion and shaping the spatial distribution of seismic hazards. This study aims to investigate the spatial variability of seismic hazards using geophysical and geological parameters such as lithology, shear wave velocity, soil texture, basement depth, and proximity to fault lines. Training data were derived from common hazard points identified in earthquake catalogues. Several machine learning (ML) models, including Logistic Regression (LR), K-Nearest Neighbors, Random Forest, and Decision Tree, More >

Jiuqing Zhou^1,2,3, Daming Lin⁴, Leifa Li^1,2,3, Guanghui Zhang^1,2,3, Shumao Qiu^4,*

Structural Durability & Health Monitoring, Vol.19, No.3, pp. 705-729, 2025, DOI:10.32604/sdhm.2025.060298 - 03 April 2025

Abstract The objective of this research is to assess the seismic behavior of the continuous T-beam bridge located at Kulungou in Xinjiang. In addition to traditional static and modal analyses, this study introduces a novel approach by comprehensively examining the performance of the bridge during construction stages, under ultimate load capacities and seismic load. Compliance with regulatory standards is verified by the static analysis, which also yields a thorough comprehension of stress distribution across various stages of construction. By unveiling the initial 100 vibration modes, the modal analysis has significantly enhanced our comprehension and established… More >

Ahed Habib^1,*, Zaid A. Al-Sadoon², Murat Saatcioglu³, Ausamah Al Houri⁴, Mohamed Maalej², Salah Al-Toubat², Mazen Shrif²

Structural Durability & Health Monitoring, Vol.19, No.3, pp. 417-439, 2025, DOI:10.32604/sdhm.2025.059524 - 03 April 2025

Abstract Squat reinforced concrete (RC) shear walls are essential structural elements in low-rise buildings, valued for their high strength and stiffness. However, research on their seismic behavior remains limited, as most studies focus on tall, slender walls, which exhibit distinct failure mechanisms and deformation characteristics. This study addresses this gap by conducting an extensive review of existing research on the seismic performance of squat RC shear walls. Experimental studies, analytical models, and numerical simulations are examined to provide insights into key factors affecting wall behavior during seismic events, including material properties, wall geometry, reinforcement detailing, and More >

Sourabh Mhaski^*, G. V. Ramana

CMES-Computer Modeling in Engineering & Sciences, Vol.142, No.1, pp. 251-277, 2025, DOI:10.32604/cmes.2024.055963 - 17 December 2024

Abstract Earthquake-induced soil liquefaction poses significant risks to the stability of geotechnical structures worldwide. An understanding of the liquefaction triggering, and the post-failure large deformation behaviour is essential for designing resilient infrastructure. The present study develops a Smoothed Particle Hydrodynamics (SPH) framework for earthquake-induced liquefaction hazard assessment of geotechnical structures. The coupled flow-deformation behaviour of soils subjected to cyclic loading is described using the PM4Sand model implemented in a three-phase, single-layer SPH framework. A staggered discretisation scheme based on the stress particle SPH approach is adopted to minimise numerical inaccuracies caused by zero-energy modes and tensile… More >

Hacer Kabakoglu^1,2,*, Fatma Nuray Kuşçu Sahin²

International Journal of Mental Health Promotion, Vol.26, No.10, pp. 855-863, 2024, DOI:10.32604/ijmhp.2024.055653 - 31 October 2024

Abstract Background: Disasters have effects that leave great negative marks on our lives, even after many years have passed. Individuals who experience an earthquake experience physical and psychological difficulties. The purpose of this study is to determine how psychological resilience levels affect the feeling of hopelessness and post-traumatic growth in adults who experienced the 06 February, 2023 Turkey-Syria earthquake. Methods: Data were collected using the “Personal Information Form (PIF)”, “Turkish forms of Adult Resilience Measure (ARM)”, “Dispositional Hope Scale (DHS)” and “Post-Traumatic Growth Inventory (PTGI)”. In order to determine whether there is a significant difference in… More >

Liangwei Jiang^1,2, Wei Zhang², Hongyin Yang^1,2,3,*, Xiucheng Zhang¹, Jinghan Wu², Zhangjun Liu²

Structural Durability & Health Monitoring, Vol.18, No.6, pp. 835-851, 2024, DOI:10.32604/sdhm.2024.051125 - 20 September 2024

Abstract Aiming at the problem that it is difficult to obtain the explicit expression of the structural matrix in the traditional train-bridge coupling vibration analysis, a combined simulation system of train-bridge coupling system (TBCS) under earthquake (MAETB) is developed based on the cooperative work of MATLAB and ANSYS. The simulation system is used to analyze the dynamic parameters of the TBCS of a prestressed concrete continuous rigid frame bridge benchmark model of a heavy-haul railway. The influence of different driving speeds, seismic wave intensities, and traveling wave effects on the dynamic response of the TBCS under More >

Shalu¹, Twinkle Acharya¹, Dhwanilnath Gharekhan^1,*, Dipak Samal²

Revue Internationale de Géomatique, Vol.33, pp. 111-134, 2024, DOI:10.32604/rig.2024.051788 - 15 May 2024

Abstract Seismic vulnerability modeling plays a crucial role in seismic risk assessment, aiding decision-makers in pinpointing areas and structures most prone to earthquake damage. While machine learning (ML) algorithms and Geographic Information Systems (GIS) have emerged as promising tools for seismic vulnerability modeling, there remains a notable gap in comprehensive geospatial studies focused on India. Previous studies in seismic vulnerability modeling have primarily focused on specific regions or countries, often overlooking the unique challenges and characteristics of India. In this study, we introduce a novel approach to seismic vulnerability modeling, leveraging ML and GIS to address… More >