Zeinel Momynkulov^1,2, Azhar Tursynova^1,2,*, Olzhas Olzhayev^1,2, Akhanseri Ikramov^1,2, Sayat Ibrayev¹, Batyrkhan Omarov^1,2,3,*

CMES-Computer Modeling in Engineering & Sciences, Vol.145, No.1, pp. 891-918, 2025, DOI:10.32604/cmes.2025.068615 - 30 October 2025

Abstract Robotic manipulators increasingly operate in complex three-dimensional workspaces where accuracy and strict limits on position, velocity, and acceleration must be satisfied. Conventional geometric planners emphasize path smoothness but often ignore dynamic feasibility, motivating control-aware trajectory generation. This study presents a novel model predictive control (MPC) framework for three-dimensional trajectory planning of robotic manipulators that integrates second-order dynamic modeling and multi-objective parameter optimization. Unlike conventional interpolation techniques such as cubic splines, B-splines, and linear interpolation, which neglect physical constraints and system dynamics, the proposed method generates dynamically feasible trajectories by directly optimizing over acceleration inputs while… More >

Jinghua Yang¹, Bin Gong^1,2,*

The International Conference on Computational & Experimental Engineering and Sciences, Vol.33, No.3, pp. 1-2, 2025, DOI: 10.32604/icces.2025.011889

Abstract Geological stratification interpretation divides geological strata based on acquired well-logging data, providing comparative analysis results for strata and structures. This process serves as a fundamental framework for subsequent drilling and development design plans, making it a crucial step in oil exploration and development process. Traditional geological stratification interpretation methods are based primarily on geological, logging, and experimental data, with manual determination of strata boundaries to obtain interpretation results. However, manual interpretation is characterized by strong subjectivity and reliance on experience, which may compromise the quality and consistency of the results. To eliminate the dependency on… More >

Chenghuan Liu, Xiangbo Hu, Xiaogang Wang^*

The International Conference on Computational & Experimental Engineering and Sciences, Vol.33, No.3, pp. 1-1, 2025, DOI:10.32604/icces.2025.010910

Abstract Digital image correlation (DIC) is an emerging non-contact optical measurement method that tracks speckle patterns on the specimen surface to obtain the deformation, providing an advanced methodology for the quantitative evaluation of full-field strain. The present work focuses on the quantitative assessment of deformation from micro to macro scales based on the DIC method and examines damage evolution in metal materials under static and cyclic loading conditions. First, an SEM-based DIC method allowing high-resolution strain measurement at subgrain scales is developed for investigating strain partitioning in dual-phase steel. The results reveal that the strain distribution… More >

Duong Tien Dung^1,2,3, Ha Hai Nam⁴, Nguyen Long Giang³, Luong Thi Hong Lan^5,*

CMC-Computers, Materials & Continua, Vol.85, No.3, pp. 5625-5642, 2025, DOI:10.32604/cmc.2025.069636 - 23 October 2025

Abstract Semi-supervised clustering techniques attempt to improve clustering accuracy by utilizing a limited number of labeled data for guidance. This method effectively integrates prior knowledge using pre-labeled data. While semi-supervised fuzzy clustering (SSFC) methods leverage limited labeled data to enhance accuracy, they remain highly susceptible to inappropriate or mislabeled prior knowledge, especially in noisy or overlapping datasets where cluster boundaries are ambiguous. To enhance the effectiveness of clustering algorithms, it is essential to leverage labeled data while ensuring the safety of the previous knowledge. Existing solutions, such as the Trusted Safe Semi-Supervised Fuzzy Clustering Method (TS3FCM),… More >

Tian Tian^1,2, Boyue Wang^1,2, Xiaxia He^1,2,*, Wentong Wang³, Meng Wang¹

CMC-Computers, Materials & Continua, Vol.85, No.3, pp. 4885-4898, 2025, DOI:10.32604/cmc.2025.067795 - 23 October 2025

Abstract Attribute-graph clustering aims to divide the graph nodes into distinct clusters in an unsupervised manner, which usually encodes the node attribute feature and the corresponding graph structure into a latent feature space. However, traditional attribute-graph clustering methods often neglect the effect of neighbor information on clustering, leading to suboptimal clustering results as they fail to fully leverage the rich contextual information provided by neighboring nodes, which is crucial for capturing the intrinsic relationships between nodes and improving clustering performance. In this paper, we propose a novel Neighbor Dual-Consistency Constrained Attribute-Graph Clustering that leverages information from… More >

Liwen Guan¹, Xiaoteng Wang^2,*, Tang Biao²

The International Conference on Computational & Experimental Engineering and Sciences, Vol.33, No.2, pp. 1-4, 2025, DOI:10.32604/icces.2025.012534

Abstract By using the continuous cyclic loading-unloading tensile test method, the nonlinear variation behavior of the chord modulus of mild steel under different temperature conditions was systematically investigated, and the corresponding relationship between plastic strain and chord modulus during the cyclic loading-unloading process was clarified. Through the analysis of test data, the variation trends and quantitative corresponding models of plastic strain and chord modulus at different temperatures were established. The research results show that under constant temperature conditions, as the plastic strain increases to 10%, the chord modulus attenuation process presents a significant two-stage characteristic -… More >

Anastasia Vylegzhanina^1,2, Irina Shalaginova^2,*, Dana Korolevich¹, Dmitry Katserov¹, Alexandra Semenova¹, Maria Sidorova¹, Sergey Eresko³, Marat Airapetov³, Marina Pavlova², Anna Levina², Natalia Dyuzhikova²

BIOCELL, Vol.49, No.10, pp. 2007-2031, 2025, DOI:10.32604/biocell.2025.071198 - 22 October 2025

Abstract Objectives: Chronic stress can trigger neuroinflammation and gut microbiota alterations, contributing to post-stress disorders. Individual differences in stress responses, shaped by genetic and physiological factors, require better characterization. We aimed to investigate the long-term effects of chronic stress in rats selectively bred for high and low nervous system excitability. Methods: Adult male rats from two strains selectively bred for high (HT) and low (LT) excitability thresholds of the nervous system underwent a 15-day chronic emotional-pain stress protocol. Behavioral assessments (elevated plus maze), cytokine levels (TNF, IL-1β, IL-6, IL-10) in the hippocampus and amygdala measured by… More >

Oncology Research Editorial Office

Oncology Research, Vol.33, No.10, pp. 3157-3157, 2025, DOI:10.32604/or.2025.073033 - 26 September 2025

Abstract This article has no abstract. More >

Jianchang Hou¹, Zhanpeng Jiang¹, Fenghe Wu¹, Hui Lian¹, Zhaohua Wang², Zijian Liu³, Weicheng Li^1,*

CMES-Computer Modeling in Engineering & Sciences, Vol.144, No.2, pp. 1545-1572, 2025, DOI:10.32604/cmes.2025.068482 - 31 August 2025

Abstract In this paper, a topology optimization method for coordinated stiffness and strength design is proposed under mass constraints, utilizing the Solid Isotropic Material with Penalization approach. Element densities are regulated through sensitivity filtering to mitigate numerical instabilities associated with stress concentrations. A p-norm aggregation function is employed to globalize local stress constraints, and a normalization technique linearly weights strain energy and stress, transforming the multi-objective problem into a single-objective formulation. The sensitivity of the objective function with respect to design variables is rigorously derived. Three numerical examples are presented, comparing the optimized structures in terms More >

Shubham Desai, Sai Sidhardh^*

CMES-Computer Modeling in Engineering & Sciences, Vol.144, No.2, pp. 1271-1334, 2025, DOI:10.32604/cmes.2025.068141 - 31 August 2025

Abstract The increasing integration of small-scale structures in engineering, particularly in Micro-Electro-Mechanical Systems (MEMS), necessitates advanced modeling approaches to accurately capture their complex mechanical behavior. Classical continuum theories are inadequate at micro- and nanoscales, particularly concerning size effects, singularities, and phenomena like strain softening or phase transitions. This limitation follows from their lack of intrinsic length scale parameters, crucial for representing microstructural features. Theoretical and experimental findings emphasize the critical role of these parameters on small scales. This review thoroughly examines various strain gradient elasticity (SGE) theories commonly employed in literature to capture these size-dependent effects… More >