Zhishui Sheng¹, Hong Jiang¹, Gang Liu², Fulai Zhang³, Wei Zhang^3,*

Structural Durability & Health Monitoring, Vol.19, No.3, pp. 531-548, 2025, DOI:10.32604/sdhm.2024.059662 - 03 April 2025

Abstract Concrete materials are employed extensively in a variety of large-scale structures due to their economic viability and superior mechanical properties. During the service life of concrete structures, they are inevitably subjected to damage from impact loading from natural disasters, such as earthquakes and storms. In recent years, the phase-field model has demonstrated exceptional capability in predicting the stochastic initiation, propagation, and bifurcation of cracks in materials. This study employs a phase-field model to focus on the rate dependency and failure response of concrete under impact deformation. A viscosity coefficient is introduced within the phase-field model… More >

Wenhai Zhao¹, Wanrun Li^1,2,*, Ximei Li^1,2, Shoutu Li³, Yongfeng Du^1,2

Structural Durability & Health Monitoring, Vol.19, No.3, pp. 593-611, 2025, DOI:10.32604/sdhm.2024.057759 - 03 April 2025

Abstract Addressing the current challenges in transforming pixel displacement into physical displacement in visual monitoring technologies, as well as the inability to achieve precise full-field monitoring, this paper proposes a method for identifying the structural dynamic characteristics of wind turbines based on visual monitoring data fusion. Firstly, the Lucas-Kanade Tomasi (LKT) optical flow method and a multi-region of interest (ROI) monitoring structure are employed to track pixel displacements, which are subsequently subjected to band pass filtering and resampling operations. Secondly, the actual displacement time history is derived through double integration of the acquired acceleration data and… More >

Hira Akhtar¹, Akhtar Hameed^1,*, Rana Binyamin¹, Kashif Riaz², Hafiz Muhammad Usman Aslam^1,3, Faizan Ali⁴, Subhan Ali¹, Zuniara Akash⁵, Muhammad Saqlain Zaheer^6,*, Kamran Ikram⁶, Yasir Niaz⁶, Hafiz Haider Ali^7,8

Phyton-International Journal of Experimental Botany, Vol.94, No.3, pp. 561-581, 2025, DOI:10.32604/phyton.2025.061262 - 31 March 2025

Abstract Strawberry (Fragaria ananassa) is well known among consumers because of its attractive color, delicious taste, and nutritional benefits. It is widely grown worldwide, but its production has become a significant challenge due to changing climatic conditions that lead to abiotic stresses in plants, which results in poor root development, nutrient deficiency, and poor plant health. In this context, the major abiotic stresses are temperature fluctuations, water shortages, and high levels of soil salinity. The accumulation of salts in excessive amounts disrupts the osmotic balance and impairs physiological processes. However, drought reduces fruit size, yield, and quality.… More >

Veronika Dyakova^1,2,*, Olga Vlasova¹, Victor Kozlov¹

FDMP-Fluid Dynamics & Materials Processing, Vol.21, No.3, pp. 493-508, 2025, DOI:10.32604/fdmp.2025.060577 - 01 April 2025

Abstract An experimental investigation of the dynamics of the interface between two low-viscosity fluids with high density contrast oscillating in a fixed vertical slotted channel has been conducted. It has been found that as the amplitude of the liquid column oscillations increases, parametric oscillations of the interface are excited in the form of a standing wave located in the channel plane. In particular, depending on the interfacial tension, the standing waves have a frequency equal to that of liquid piston oscillations (harmonic response), or half of the frequency of oscillations of the liquid column in the… More >

Shuaijie Jiang¹, Zechen Zhou¹, Xiuli Wang¹, Wei Xu², Wenzhuo Guo¹, Qingjiang Xiang^1,*

FDMP-Fluid Dynamics & Materials Processing, Vol.21, No.3, pp. 471-491, 2025, DOI:10.32604/fdmp.2025.059878 - 01 April 2025

Abstract In nature, cavitation bubbles typically appear in clusters, engaging in interactions that create a variety of dynamic motion patterns. To better understand the behavior of multiple bubble collapses and the mechanisms of inter-bubble interaction, this study employs molecular dynamics simulation combined with a coarse-grained force field. By focusing on collapse morphology, local density, and pressure, it elucidates how the number and arrangement of bubbles influence the collapse process. The mechanisms behind inter-bubble interactions are also considered. The findings indicate that the collapse speed of unbounded bubbles located in lateral regions is greater than that of More >

Hongjuan Guo¹, Dan Liu^1,2, Ruyu Yan^1,2, Tianjing Zhang³, Kecheng Zhou^1,2,*, Minxia Liu^1,*

BIOCELL, Vol.49, No.3, pp. 483-502, 2025, DOI:10.32604/biocell.2025.062143 - 31 March 2025

Abstract Objectives: Non-small cell lung cancer (NSCLC) represents a formidable malignancy characterized by its marked metastatic potential and intrinsic resistance to therapeutic interventions. The identification of potential biomarkers delineating the progression and metastatic cascade of NSCLC assumes paramount importance in fostering advancements toward enhanced patient outcomes and prognostic stratification. Methods: The expression level of the actin-related protein 2/3 complex; subunit 1A (ARPC1A) in NSCLC was evaluated using The Cancer Genome Atlas (TCGA) and Gene Expression Profiling Interactive Analysis (GEPIA) databases; along with the LinkedOmics database for co-expression genes. Further verification of ARPC1A expression in normal lung cells… More >

Yi-Feng Luo¹, Guan-Jhu Chen^2,*, Chun-Liang Liu³, Yen-Tse Chung⁴

CMC-Computers, Materials & Continua, Vol.83, No.1, pp. 823-844, 2025, DOI:10.32604/cmc.2025.061498 - 26 March 2025

Abstract As lithium-ion batteries become increasingly prevalent in electric scooters, vehicles, mobile devices, and energy storage systems, accurate estimation of remaining battery capacity is crucial for optimizing system performance and reliability. Unlike traditional methods that rely on static alternating internal resistance (SAIR) measurements in an open-circuit state, this study presents a real-time state of charge (SOC) estimation method combining dynamic alternating internal resistance (DAIR) with artificial neural networks (ANN). The system simultaneously measures electrochemical impedance |Z| at various frequencies, discharge C-rate, and battery surface temperature during the discharge process, using these parameters for ANN training. The… More >

Keyuan Chen¹, Xingkao Zhang¹, Li Ma¹, Jueyi Ye¹, Qi Qiu¹, Haoxiang Zhang¹, Ju Rong^1,*, Yudong Sui^1,*, Xiaohua Yu^1,2, Jing Feng¹

CMC-Computers, Materials & Continua, Vol.83, No.1, pp. 685-700, 2025, DOI:10.32604/cmc.2025.060713 - 26 March 2025

Abstract The deep potential (DP) is an innovative approach based on deep learning that uses ab initio calculation data derived from density functional theory (DFT), to create high-accuracy potential functions for various materials. Platinum (Pt) is a rare metal with significant potential in energy and catalytic applications, However, there are challenges in accurately capturing its physical properties due to high experimental costs and the limitations of traditional empirical methods. This study employs deep learning methods to construct high-precision potential models for single-element systems of Pt and validates their predictive performance in complex environments. The newly developed DP… More >

Jianfeng Lu¹, Tao Huang¹, Yuanai Xie^2,*, Shuqin Cao¹, Bing Li³

CMC-Computers, Materials & Continua, Vol.83, No.1, pp. 619-634, 2025, DOI:10.32604/cmc.2025.060094 - 26 March 2025

Abstract The proliferation of deep learning (DL) has amplified the demand for processing large and complex datasets for tasks such as modeling, classification, and identification. However, traditional DL methods compromise client privacy by collecting sensitive data, underscoring the necessity for privacy-preserving solutions like Federated Learning (FL). FL effectively addresses escalating privacy concerns by facilitating collaborative model training without necessitating the sharing of raw data. Given that FL clients autonomously manage training data, encouraging client engagement is pivotal for successful model training. To overcome challenges like unreliable communication and budget constraints, we present ENTIRE, a contract-based dynamic… More >

Qinglei Zhang, Bai Hu^*, Jiyun Qin, Jianguo Duan, Ying Zhou

CMC-Computers, Materials & Continua, Vol.83, No.1, pp. 1257-1273, 2025, DOI:10.32604/cmc.2025.059955 - 26 March 2025

Abstract Grasping is one of the most fundamental operations in modern robotics applications. While deep reinforcement learning (DRL) has demonstrated strong potential in robotics, there is too much emphasis on maximizing the cumulative reward in executing tasks, and the potential safety risks are often ignored. In this paper, an optimization method based on safe reinforcement learning (Safe RL) is proposed to address the robotic grasping problem under safety constraints. Specifically, considering the obstacle avoidance constraints of the system, the grasping problem of the manipulator is modeled as a Constrained Markov Decision Process (CMDP). The Lagrange multiplier… More >