The structure of a fabric is a highly complex assembly of fibres, which have order and regularity as well as disorder and randomness. The complexity of the structure poses challenges in defining its mechanical behaviour, particularly at low stress, which is typical to end uses. The coexistence of multiple deformations and the high degree of nonlinearity of the fabric due to fibre friction make its stress-strain relationship complicated. This article reviews the literature on friction related to the low-stress mechanics of fabrics, and it establishes its range and regularity to help with finding a unified reference model, in which although the physical meanings of fabric tensile, shear, and bending vary, they follow consistent mathematical regularities. So, invariably, their disorder and randomness needed in defining them can be obtained from fabric measurement data. It defines the scope and patterns of friction to facilitate the development of a unified reference model. It argues that although the physical interpretations of fabric tensile, shear, and bending characteristics may differ, they adhere to consistent mathematical regularities within this model, and hence extracting disorder and randomness from fabric measurement data may be achievable. This paper concludes with a number of recommendations, postulating that hysteresis caused by friction between fibres in a fabric is an important component of mechanical information, and it coexists with its purely elastic component, but it cannot be obtained directly by measurement. Seeking means to effectively decompose the friction hysteresis and pure elastic components contained in fabric mechanics measurement data will provide an accurate characterization of fabric mechanical properties and hence an accurate modelling and simulation of its behaviour, and will impact many traditional and industrial textile end uses.
Download full-text PDF |
Source |
---|---|
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11313532 | PMC |
http://dx.doi.org/10.3390/ma17153828 | DOI Listing |
Sci Rep
December 2024
School of Engineering and Technology, Sunway University, No. 5, Jalan Universiti, Bandar Sunway, Petaling Jaya, 47500, Selangor Darul Ehsan, Malaysia.
Cervical cancer is a deadly disease in women globally. There is a greater chance of getting rid of cervical cancer in case of earliest diagnosis. But for some patients, there is a chance of recurrence.
View Article and Find Full Text PDFNPJ Vaccines
December 2024
Department for Evidence-based Medicine and Evaluation, University for Continuing Education Krems (Danube University Krems), Krems, Austria.
Pneumococcal infections are a serious health issue associated with increased morbidity and mortality. This systematic review evaluated the efficacy, effectiveness, immunogenicity, and safety of the pneumococcal conjugate vaccine (PCV)15 compared to other pneumococcal vaccines or no vaccination in children and adults. We identified 20 randomized controlled trials (RCTs).
View Article and Find Full Text PDFSci Rep
December 2024
School of Pharmacy, Jiangxi Medical College, Nanchang University, Nanchang, 330006, People's Republic of China.
Cuproptosis, a newly identified form of cell death, has drawn increasing attention for its association with various cancers, though its specific role in colorectal cancer (CRC) remains unclear. In this study, transcriptomic and clinical data from CRC patients available in the TCGA database were analyzed to investigate the impact of cuproptosis. Differentially expressed genes linked to cuproptosis were identified using Weighted Gene Co-Expression Network Analysis (WGCNA).
View Article and Find Full Text PDFSci Rep
December 2024
Department of Applied Mathematics, Faculty of Mathematical Science, Ferdowsi University of Mashhad, Mashhad, Iran.
This study presents a web application for predicting cardiovascular disease (CVD) and hypertension (HTN) among mine workers using machine learning (ML) techniques. The dataset, collected from 699 participants at the Gol-Gohar mine in Iran between 2016 and 2020, includes demographic, occupational, lifestyle, and medical information. After preprocessing and feature engineering, the Random Forest algorithm was identified as the best-performing model, achieving 99% accuracy for HTN prediction and 97% for CVD, outperforming other algorithms such as Logistic Regression and Support Vector Machines.
View Article and Find Full Text PDFNat Commun
December 2024
School of Data Science, The Chinese University of Hong Kong-Shenzhen, Shenzhen, China.
Recently, RNA velocity has driven a paradigmatic change in single-cell RNA sequencing (scRNA-seq) studies, allowing the reconstruction and prediction of directed trajectories in cell differentiation and state transitions. Most existing methods of dynamic modeling use ordinary differential equations (ODE) for individual genes without applying multivariate approaches. However, this modeling strategy inadequately captures the intrinsically stochastic nature of transcriptional dynamics governed by a cell-specific latent time across multiple genes, potentially leading to erroneous results.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!