Results 61 to 70 of about 8,902 (235)
CauFinder: Steering Cell‐State and Phenotype Transitions by Causal Disentanglement Learning
CauFinder combines causal disentanglement modeling and network control to prioritize causal drivers of cell‐state transitions from observational transcriptomic data. The framework separates transition‐relevant signals from spurious associations, nominates intervention targets across biological and disease contexts, and identifies DAAM1 as an actionable
Chengming Zhang +11 more
wiley +1 more source
A New Type-2 Soft Set: Type-2 Soft Graphs and Their Applications
The correspondence between a vertex and its neighbors has an essential role in the structure of a graph. Type-2 soft sets are also based on the correspondence of primary parameters and underlying parameters.
Khizar Hayat +3 more
doaj +1 more source
Physics‐Informed Neural Network‐Enabled Forward Prediction and Inverse Design of Ring Origami
This work presents a KRT‐PINN framework that integrates Kirchhoff rod theory with physics‐informed neural networks for the forward prediction and inverse design of ring origami consisting of closed‐loop rods. The framework predicts stable states of segmented rings with prescribed natural‐curvature profiles and determines the natural‐curvature profiles ...
Luyuan Ning +3 more
wiley +1 more source
-labeling of supersubdivided connected graph plus an edge
Rosa, in his classical paper (Rosa, 1967) introduced a hierarchical series of labelings called and labeling as a tool to settle Ringel’s Conjecture which states that if is any tree with edges then the complete graph can be decomposed into copies of ...
G. Sethuraman, M. Sujasree
doaj +1 more source
CHCHD10 loss in Alzheimer's disease is associated with mitochondrial dysfunction, epigenomic disruption, and tau pathology. Restoration of CHCHD10 shifts DNA methylation toward a non‐disease state and reduces tau and amyloid pathology, with KATNAL2 acting as a downstream effector.
Teresa M. Thomas +13 more
wiley +1 more source
Edge Irregular Reflexive Labeling for the Disjoint Union of Gear Graphs and Prism Graphs
In graph theory, a graph is given names—generally a whole number—to edges, vertices, or both in a chart. Formally, given a graph G = ( V , E ) , a vertex naming is a capacity from V to an arrangement of marks.
Xiujun Zhang +3 more
doaj +1 more source
Non‐Noble Metal Nanocatalysts for Hydrogen Evolution
Recent overviews and latest developments of diverse classes of non‐noble catalysts for application toward high‐performance photocatalysis, thermocatalytic steam reforming, and electrocatalysis. Toward sustainability objectives, several advanced characterization tools in combination with the latest breakthroughs in machine learning for material ...
Lina Jaya Diguna +7 more
wiley +1 more source
The locating chromatic number of (k,n)-split cycle graph and its barbell operation
The locating chromatic number remains an active topic in graph theory. It combines the concepts of partition dimension and proper vertex coloring. A necessary condition for determining the locating chromatic number is that each vertex must have a unique ...
Asmiati Asmiati +3 more
doaj +1 more source
“Follow the Leader”: A Centrality Guided Clustering and Its Application to Social Network Analysis
Within graph theory and network analysis, centrality of a vertex measures the relative importance of a vertex within a graph. The centrality plays key role in network analysis and has been widely studied using different methods.
Qin Wu +3 more
doaj +1 more source
Molecular and Cellular Hallmarks of Age‐Related Vestibular Hair Cell Degeneration
This study utilizes single‐cell RNA‐seq transcriptomes, advanced imaging, and electrophysiology to examine universal and cell‐type‐specific aging signatures of vestibular hair cells. The study shows that impaired hair bundle function is a key driver of age‐related vestibular dysfunction.
Samadhi Kulasooriya +10 more
wiley +1 more source

