Buddhini Chaturika Jayasinghe¹, Neel Chaminda Withanage¹, Prabuddh Kumar Mishra^2,*

Revue Internationale de Géomatique, Vol.34, pp. 707-729, 2025, DOI:10.32604/rig.2025.067395 - 12 September 2025

Abstract Road Traffic Accidents (RTAs) pose significant threats to public safety and urban infrastructure. While numerous studies have addressed this issue in other countries, there remains a notable gap in localized RTA research in Sri Lanka. In this context, the present study investigates the spatial and temporal patterns of RTAs in the Matara urban area in 2023, with the goal of supporting evidence-based policy interventions. A suite of GIS-based spatial analysis techniques including hotspot analysis, kernel density estimation, GiZscore mapping, and spatial autocorrelation (Moran’s I = 0.36, p < 0.01) was applied to examine the distribution and… More >

Xi Qin^1,#, Yulan Liu^1,#, Lin Zhu², Yunyan Mo¹, Jing Zhang³, Zhuchun Jiang⁴, Dongning Huang⁵, Xinrong Hu⁶, Jingzhang Li⁷, Quanfang Chen⁸, Feng Xue^1,*

Oncology Research, Vol.33, No.9, pp. 2451-2462, 2025, DOI:10.32604/or.2025.064119 - 28 August 2025

Abstract Background: The use of third-generation different tyrosine kinase inhibitors (TKIs) is considered the most effective option for treating advanced non-small cell lung cancer (aNSCLC) with epidermal growth factor receptor (EGFR) mutations. However, there is limited information on the efficacy and safety of aumolertinib in patients remains these cases. Methods: The clinical records of patients receiving aumolertinib as first-line therapy across four hospitals in the Guangxi Zhuang Autonomous Region from April 2020 to December 2021 were retrospectively analyzed, using progression-free survival (PFS) as the primary endpoint and overall survival (OS) representing the secondary endpoint. Adverse events… More >

Yubin Qu^1,2, Song Huang^2,*, Long Li³, Peng Nie², Yongming Yao²

CMC-Computers, Materials & Continua, Vol.85, No.1, pp. 249-300, 2025, DOI:10.32604/cmc.2025.067750 - 29 August 2025

Abstract Large language models (LLMs) represent significant advancements in artificial intelligence. However, their increasing capabilities come with a serious challenge: misalignment, which refers to the deviation of model behavior from the designers’ intentions and human values. This review aims to synthesize the current understanding of the LLM misalignment issue and provide researchers and practitioners with a comprehensive overview. We define the concept of misalignment and elaborate on its various manifestations, including generating harmful content, factual errors (hallucinations), propagating biases, failing to follow instructions, emerging deceptive behaviors, and emergent misalignment. We explore the multifaceted causes of misalignment,… More >

Ruigang Zhang^1,*, Qihui Yan², Jialiang Wang¹, Hao Wang¹, Jie Sun², Junjiao Shi²

Energy Engineering, Vol.122, No.9, pp. 3609-3624, 2025, DOI:10.32604/ee.2025.066880 - 26 August 2025

Abstract As the core facility of offshore wind power systems, the structural safety of offshore booster stations directly impacts the stable operation of entire wind farms. With the global energy transition toward green and low-carbon goals, offshore wind power has emerged as a key renewable energy source, yet its booster stations face harsh marine environments, including persistent wave impacts, salt spray corrosion, and equipment-induced vibrations. Traditional monitoring methods relying on manual inspections and single-dimensional sensors suffer from critical limitations: low efficiency, poor real-time performance, and inability to capture millinewton-level stress fluctuations that signal early structural fatigue.… More >

Ciro Caliendo, Isidoro Russo^*, Gianluca Genovese

CMES-Computer Modeling in Engineering & Sciences, Vol.144, No.1, pp. 693-715, 2025, DOI:10.32604/cmes.2025.068123 - 31 July 2025

Abstract Road pavements in tunnels are usually made of asphalt mixtures, which, unfortunately, are flammable materials. Hence, this type of pavement could release heat, and more specifically smoke, in the event of a tunnel fire, thereby worsening the environmental conditions for human health. Extensive research has been conducted in recent years to enhance the fire reaction of traditional asphalt mixtures for the road pavements used in tunnels. The addition of the Flame Retardants (FRs) in conventional asphalt mixtures appears to be promising. Nevertheless, the potential effects of the FRs in terms of the reduction in consequences… More > Graphic Abstract

Ling Ji^1,2,*, Nan Jiang³, Yingbo Ren³, Tao Yin¹, Haibo Wang¹, Bing Cheng⁴

CMES-Computer Modeling in Engineering & Sciences, Vol.144, No.1, pp. 267-288, 2025, DOI:10.32604/cmes.2025.066596 - 31 July 2025

Abstract During the construction of bank slopes involving pile driving, ensuring slope stability is crucial. This requires the design of appropriate support systems and a thorough evaluation of the failure mechanisms of pile structures under dynamic loading conditions. Based on the Huarong Coal Wharf project, various support schemes are analyzed using numerical simulation methods to calculate and compare slope stability coefficients. The optimal scheme is then identified. Under the selected support scheme, a numerical model of double-row suspended steel sheet piles is developed to investigate the dynamic response of the pile structures under pile driving loads.… More >

Junling Zhong¹, Furong Geng², Zhixiao Chen¹, Wenbin Hou^1,*

CMES-Computer Modeling in Engineering & Sciences, Vol.144, No.1, pp. 1-27, 2025, DOI:10.32604/cmes.2025.065664 - 31 July 2025

Abstract This study presents an interpretable surrogate framework for predicting pedestrian-leg injury severity that integrates high-fidelity finite-element (FE) simulations with a TabNet-based deep-learning model. We generated a parametric dataset of 3000 impact scenarios—covering ten vehicle types and various legform impactors—using automated FE runs configured via Latin hypercube sampling. After preprocessing and one-hot encoding of categorical features, we trained TabNet alongside Support-Vector Regression, Random Forest, and Decision-Tree ensembles. All models underwent hyperparameter tuning via Optuna’s Bayesian optimization coupled with repeated four-fold cross-validation (20 trials per model). TabNet achieved the best balance of explanatory power and predictive accuracy, More > Graphic Abstract

Longmei Wang¹, Jiawen Liu¹, Lei Lu^2,*

Journal of Psychology in Africa, Vol.35, No.3, pp. 309-317, 2025, DOI:10.32604/jpa.2025.068580 - 31 July 2025

Abstract This study examined the relationship between inclusive leadership and subordinates’ upward voice, focusing on the mediating role of psychological safety and the moderating role of collectivism. Data were collected from 284 subordinates and supervisors across 11 organizations in China in three cross-lagged waves. Structural equation modeling results indicated that inclusive leadership was associated with subordinates’ upward voice via psychological safety. Moreover, collectivism strengthens the association between inclusive leadership and upward voice via psychological safety, leading to a higher upward voice. These findings highlight the importance of inclusive leadership in fostering an environment that promotes open More >

Chongyang Wang¹, Qiongyan Li¹, Shu Liu², Pengle Cheng^1,*, Ying Huang³

CMC-Computers, Materials & Continua, Vol.84, No.3, pp. 5157-5176, 2025, DOI:10.32604/cmc.2025.067367 - 30 July 2025

Abstract With rapid urbanization, fires pose significant challenges in urban governance. Traditional fire detection methods often struggle to detect smoke in complex urban scenes due to environmental interferences and variations in viewing angles. This study proposes a novel multimodal smoke detection method that fuses infrared and visible imagery using a transformer-based deep learning model. By capturing both thermal and visual cues, our approach significantly enhances the accuracy and robustness of smoke detection in business parks scenes. We first established a dual-view dataset comprising infrared and visible light videos, implemented an innovative image feature fusion strategy, and More >

Habib Hadj-Mabrouk^*

CMC-Computers, Materials & Continua, Vol.84, No.3, pp. 4399-4430, 2025, DOI:10.32604/cmc.2025.067143 - 30 July 2025

Abstract A literature review on AI applications in the field of railway safety shows that the implemented approaches mainly concern the operational, maintenance, and feedback phases following railway incidents or accidents. These approaches exploit railway safety data once the transport system has received authorization for commissioning. However, railway standards and regulations require the development of a safety management system (SMS) from the specification and design phases of the railway system. This article proposes a new AI approach for analyzing and assessing safety from the specification and design phases of the railway system with a view to… More >