98%
921
2 minutes
20
The modeling of the concrete matrix serves as a foundation for mesoscale analysis of concrete, which provides a crucial avenue for investigating the crack propagation and strength characteristics of concrete. However, the primary prerequisite for conducting such analyses is the generation of aggregate models. By combining the advantages of Voronoi diagrams and the random walk algorithm (RWA), a Voronoi-random walk algorithm is proposed in this paper. The algorithm overcomes the limitations of traditional methods, including constraints on aggregate volume fraction, low computational efficiency, and insufficient randomness in aggregate distribution. The meso-structure of a concrete block was modeled by the proposed method, and then its failure behavior under uniaxial compression was simulated using the finite element method. The numerical results agreed well with the experimental observations, indicating the effectiveness and accuracy of the proposed approach.
Download full-text PDF |
Source |
---|---|
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11433165 | PMC |
http://dx.doi.org/10.3390/ma17184440 | DOI Listing |
Ann Hematol
September 2025
Faculty of Medicine, Division of Hematology, Department of Internal Medicine, Istanbul University-Cerrahpaşa, Istanbul, Turkey.
The development of pulmonary hypertension (PH) after splenectomy is one of the recently controversial issues. This study aims to investigate whether splenectomy itself is an independent risk factor for the development of PH or if the primary contributor to PH development is the underlying condition that necessitated splenectomy. This study was conducted prospectively.
View Article and Find Full Text PDFComput Methods Biomech Biomed Engin
September 2025
Robotics Institute, Ningbo University of Technology, Ningbo, China.
Surface electromyography (sEMG) holds great potential in walking function evaluation. Compressed sensing (CS) leverages the sparsity of signals to decrease the number of samples required. In this study, a sEMG CS algorithm for spinal cord injury (SCI) patients based on regularized orthogonal matching pursuit (ROMP) was introduced.
View Article and Find Full Text PDFBiol Methods Protoc
September 2025
School of Information and Communications Technology, Hanoi University of Science and Technology, Hanoi 100000, Vietnam.
MicroRNAs (miRNAs) play a critical role in disease mechanisms, making the identification of disease-associated miRNAs essential for precision medicine. We propose a novel computational method, multiplex-heterogeneous network for MiRNA-disease associations (MHMDA), which integrates multiple miRNA functional similarity networks and a disease similarity network into a multiplex-heterogeneous network. This approach employs a tailored random walk with restart algorithm to predict disease-miRNA associations, leveraging the complementary information from experimentally validated and predicted miRNA-target interactions, as well as disease phenotypic similarities.
View Article and Find Full Text PDFPLoS One
September 2025
School of Chemical Engineering, University of New South Wales, Sydney, New South Wales, Australia.
Coal blending in thermal power plants is a complex multi-objective challenge involving economic, operational and environmental considerations. This study presents a Q-learning-enhanced NSGA-II (QLNSGA-II) algorithm that integrates the adaptive policy optimization of Q-learning with the elitist selection of NSGA-II to dynamically adjust crossover and mutation rates based on real-time performance metrics. A physics-based objective function takes into account the thermodynamics of ash fusion and the kinetics of pollutant emission, ensuring compliance with combustion efficiency and NOx limits.
View Article and Find Full Text PDFJ Pharmacol Toxicol Methods
September 2025
Department of Pharmacology, Faculty of Pharmacy, Kabul University, 1006 Kabul, Afghanistan.
Polypharmacy during tuberculosis (TB) treatment, particularly in patients with comorbidities such as diabetes mellitus (DM), significantly increases the risk of adverse drug reactions (ADRs) due to complex drug-drug interactions (DDIs). Existing computational methods primarily focus on pairwise drug interactions, often failing to capture the multifactorial nature of ADRs in polypharmacy contexts. To address this gap, we developed PolyCheck, a hybrid predictive model that integrates network-based and rule-based methods to identify potential ADRs arising from multi-drug regimens.
View Article and Find Full Text PDF