Mengxue Li^1,2, Xinyi Chen^1,*, Yuxi Xie²

Structural Durability & Health Monitoring, Vol.20, No.5, 2026, DOI:10.32604/sdhm.2026.079754 - 24 August 2026

Abstract Concrete stress is a critical indicator for evaluating the performance of concrete structures. To achieve non-contact testing of concrete stress, this study analyzed the propagation of laser-generated Rayleigh waves (R-wave) in concrete. A correlation model was established between the concrete stress and the R-wave velocity. To validate the theoretical analysis, ultrasonic experiments were conducted. The experimental results demonstrated that the stress history of concrete determines whether a stable linear relationship exists between the stress and the R-wave velocity. Additionally, the acoustoelastic coefficient of concrete was found to vary with its age. Based on these findings, More >

Hongyan Liu, Fang Wang, Jie Zhao, Feng Wu^*

Structural Durability & Health Monitoring, Vol.20, No.5, 2026, DOI:10.32604/sdhm.2026.079457 - 24 August 2026

Abstract This study investigates the thermo-mechanical behavior and residual strength of full-scale reinforced concrete (RC) beams subjected to ISO-834 fire exposure, emphasizing temperature-dependent material degradation and bond-slip effects. A sequentially coupled numerical framework was developed in ABAQUS, integrating a temperature-indexed Concrete Damage Plasticity (CDP) model for concrete, elastoplastic steel constitutive laws, and a temperature-dependent bond-slip model implemented via nonlinear SPRING2 elements. The model explicitly accounts for post-peak concrete softening, steel yield degradation, and interface deterioration, and was calibrated against full-scale experiments. Experimental measurements included internal and surface temperatures, load–midspan deflection, and residual strength after natural cooling. More >

Mohammed Alghannam¹, Marwan Abdulqader¹, Amin Al-Fakih^1,2,*

Structural Durability & Health Monitoring, Vol.20, No.5, 2026, DOI:10.32604/sdhm.2026.079454 - 24 August 2026

Abstract This review presents a comprehensive evaluation of jacketing techniques used in reinforced concrete (RC) columns repair and rehabilitation. It critically examines reinforced concrete jacketing, steel jacketing, fiber-reinforced polymer (FRP) jacketing, fiber-reinforced cementitious matrix (FRCM) jacketing, and ferrocement jacketing based on recent experimental, analytical, and numerical studies. The paper discusses material characteristics, application methods, and performance under different loading and environmental conditions. Special focus is placed on advancements such as hybrid FRP systems and high-performance composites, which aim to overcome limitations of traditional jacketing techniques. The review also explores non-destructive testing methods for assessing retrofitted structures. More >

Kai Luo^1,2,*, Yuzhi Chen³

Structural Durability & Health Monitoring, Vol.20, No.5, 2026, DOI:10.32604/sdhm.2026.079382 - 24 August 2026

Abstract Material property variability in carbon fiber-reinforced polymer composites is a major source of uncertainty in quantitative Lamb wave-based delamination imaging. Even minor deviations in elastic properties can alter dispersion characteristics and wave propagation behavior, thereby reducing the reliability of imaging-based assessments. To systematically investigate this effect, the present study examines the influence of subtle material variations on Lamb wave responses through combined numerical modeling and finite element simulations. Time-of-flight features at the excitation frequency are extracted using a continuous wavelet transform with Morlet wavelets, enabling robust identification of mode-dependent arrival information. Within a finite element… More >

Bingbing Han^1,2, Ruidong Li¹, Yu Zhang^2,3,*, Hui Zhang⁴

Structural Durability & Health Monitoring, Vol.20, No.5, 2026, DOI:10.32604/sdhm.2026.075275 - 24 August 2026

Abstract To explore the impact of seismic action on the stability of saline soil subgrade slopes considering the influence of surface runoff on the strength of saline soil subgrade fillers, this paper first conducted shear tests on saline soil under different moisture contents to determine the influence of moisture content on the shear strength of saline soil. Then, the initial moisture field of the saline soil subgrade was simulated using COMSOL software, and a subgrade moisture content-strength parameter model was established based on the calculated moisture fields under different rainfall intensities. Subsequently, based on the subgrade… More >

Carla Simone Moreira Freitas^1,2,*, Fabiana Rocha-Silva², Thaís Almeida Marques-Silva², Ana Carolina Ribeiro de Oliveira¹, Sérgio Gomes da Silva^1,3,4, Fabrizio dos Santos Cardoso^1,5, Aleida Nazareth Soares²

Canadian Journal of Urology, Vol.33, No.4, pp. 827-839, 2026, DOI:10.32604/cju.2026.069559 - 21 August 2026

Abstract Background: Androgen deprivation therapy (ADT) is widely employed in the management of advanced prostate cancer, with luteinizing hormone-releasing hormone (LHRH) agonists such as leuprolide and goserelin being common options. However, pharmacological and metabolic differences between these agents may affect the efficacy of hormonal suppression and adverse event profiles. This study compared the effects of leuprolide (22.5 and 45 mg) and goserelin (10.8 mg) on prostate-specific antigen (PSA) and testosterone reduction, as well as their metabolic and cardiovascular impacts and the influence of genetic variants on therapeutic response. Methods: A prospective, randomized, controlled study was conducted… More >

Yuqing Cao, Xiliang Chen^*, Legui Zhang^*, Jun Lai, Haoyang Dong, Xuefei Sun, Xiaoyan Wang

CMC-Computers, Materials & Continua, Vol.89, No.1, 2026, DOI:10.32604/cmc.2026.086261 - 13 August 2026

Abstract The design of reward functions is crucial to the success of reinforcement learning, yet the process often relies on expert experience and is difficult to debug. Although large language models (LLMs) offer new opportunities for automated reward design, existing methods still face challenges such as poor interpretability, inability to reuse knowledge, and optimization blindness. To address these issues, this paper proposes a method for structural decoupling and knowledge reuse evolution, referred to as SD-KRE. Its core lies in treating the reward function as a composition of multiple structured units with clear semantics and functionally decoupled… More >

Hyunbum Kim^*

CMC-Computers, Materials & Continua, Vol.89, No.1, 2026, DOI:10.32604/cmc.2026.085773 - 13 August 2026

Abstract Recently, unmanned aerial vehicles (UAVs), or drones, have attracted considerable research interest across diverse fields, encompassing public and private domains, industrial and academic fields, transportation areas, disaster and harsh environments, reliable delivery services, digital twin-enabled space, and smart cities. In particular, UAVs play a critical role in surveillance and security applications. In this paper, we investigate recent advances in surveillance and intelligent security applications using UAVs. This study covers a wide range of practical tasks and missions including intelligent traffic monitoring, disaster environments, forests and national parks, large-scale events and patrols in public circumstances. Also, More >

Yufei Wang¹, Jiayi Shang¹, Fang Liu^1,*, Jun Liu²

CMC-Computers, Materials & Continua, Vol.89, No.1, 2026, DOI:10.32604/cmc.2026.085708 - 13 August 2026

Abstract Ship detection is an effective way of sea area supervision, which has important research value in both military and civil fields. For small ship targets in the sea scene, the deep feature map is difficult to effectively capture their subtle features, resulting in the decline of small target detection accuracy and the increase of the missing detection rate. To solve this problem, this paper proposes a detection algorithm called YOLO-MARALight, which adds a small target detection layer in the head network, uses a larger scale feature map to retain the details, and improves the discrimination… More > Graphic Abstract

Weijun Gao, Ziyang Zhang^*, Maotang Su

CMC-Computers, Materials & Continua, Vol.89, No.1, 2026, DOI:10.32604/cmc.2026.085382 - 13 August 2026

Abstract Multimodal sentiment analysis (MSA) has made significant progress in integrating heterogeneous information from text, speech, and vision. However, real-world multimodal data often suffer from modality noise, semantic inconsistency, and incomplete modality information, which can weaken cross-modal fusion and reduce the reliability of sentiment prediction. To address these challenges, this paper proposes RUAL, a robust uncertainty-aware learning framework for multimodal sentiment analysis. Specifically, RUAL first employs a Gathered Multi-Head Attention Pooling (GMHA) module to aggregate intra-modal features and estimate modality uncertainty based on attention entropy. Then, an Uncertainty-Aware Cross-Modal Coupled Layer (UACCL) is introduced to dynamically More >