Results 41 to 50 of about 20,013,753 (226)
Anorectal Dysfunction in Systemic Sclerosis: Clinical Phenotypes and Functional Patterns
Objective The aim of this study was to characterize specific physiologic defects in anorectal dysfunction in systemic sclerosis (SSc) using anorectal manometry (ARM), evaluate associations with gastrointestinal (GI) and extraintestinal clinical phenotypes, and explore potential serologic markers for risk stratification.
Timothy Kaniecki +6 more
wiley +1 more source
Tensorized Consensus Graph Learning for Incomplete Multi-View Clustering with Confidence Integration
Graph-based multi-view clustering has gained significant attention in recent years due to its superior ability to reveal clustering structures. However, existing methods often incur high computational costs when capturing local information and overlook ...
Guangqi Jiang +3 more
doaj +1 more source
Incomplete Contrastive Multi-View Clustering with High-Confidence Guiding
Incomplete multi-view clustering becomes an important research problem, since multi-view data with missing values are ubiquitous in real-world applications.
Chu, Dianhui, Chao, Guoqing, Jiang, Yi
core +1 more source
Incomplete Contrastive Multi-View Clustering with High-Confidence Guiding
Incomplete multi-view clustering becomes an important research problem, since multi-view data with missing values are ubiquitous in real-world applications.
Chu, Dianhui, Chao, Guoqing, Jiang, Yi
core
A Lightweight Procedural Layer for Hybrid Experimental–Computational Workflows in Materials Science
We unveil a prototype hybrid‐workflow framework that fuses automatedcomputation with hands‐on experiments. Built atop pyiron, a lightweight, parameterized layer translates procedure descriptions into executable manual steps, syncing instrument settings, human interventions, and data capture in real‐time today.
Steffen Brinckmann +8 more
wiley +1 more source
A Review of Clustering Algorithms Based on Anchor Point Acceleration Mechanism
With the advent of the big data era, clustering algorithms have become pivotal in data mining and machine learning. However, the exponential growth in data size and dimensionality has resulted in escalating time and space complexities for traditional ...
WU Qinting, FENG Yuzhe, PAN Jinyan, ZHANG Haifeng, CAO Chao, GAO Yunlong
doaj +1 more source
Entropy‐Driven Design of Low‐Melting‐Point Alloys via Compositionally Complex Strategy
Conventional low‐melting‐point alloys (LMPAs) are limited by a narrow compositional space and inherent property trade‐offs. This review presents an entropy‐driven design strategy that overcomes these limitations, ushering in a new class of low‐melting‐point compositionally complex alloys (LMCCAs).
Yinghui Shang +6 more
wiley +1 more source
Subspace clustering methods are increasingly favored in engineering applications because of their unsupervised nature. However, their performance in processing multi-view nonlinear data in unsupervised systems is often affected by the following three ...
Li Guo, Zhigui Liu, Jiao Bao, Qian Wang
doaj +1 more source
A Method for Consensus Anchor Graph Learning for Incomplete Multi-View Clustering
Multi-view clustering (MVC) is a prevalent method for integrating heterogeneous domain-specific information from diverse views. However, most MVC methods assume that all views have complete observed data, which is often unfeasible in practical ...
Seungmin Lee +4 more
doaj +1 more source
Laser‐Induced Graphene from Waste Almond Shells
Almond shells, an abundant agricultural by‐product, are repurposed to create a fully bioderived almond shell/chitosan composite (ASC) degradable in soil. ASC is converted into laser‐induced graphene (LIG) by laser scribing and proposed as a substrate for transient electronics.
Yulia Steksova +9 more
wiley +1 more source

