Results 101 to 110 of about 11,230,345 (378)
AbstractBusiness networks are fluid, yet decoding network dynamics provides a number of methodological challenges. This research illustrates how, by using a technology-bundled business net, the temporal fluidity of the network boundary and the associated processes and events that affect this can be understood.
Chou, Hsin Hui, Zolkiewski, Judy
openaire +2 more sources
Disruption of SETD3‐mediated histidine‐73 methylation by the BWCFF‐associated β‐actin G74S mutation
The β‐actin G74S mutation causes altered interaction of actin with SETD3, reducing histidine‐73 methylation efficiency and forming two distinct actin variants. The variable ratio of these variants across cell types and developmental stages contributes to tissue‐specific phenotypical changes. This imbalance may impair actin dynamics and mechanosensitive
Anja Marquardt+8 more
wiley +1 more source
Circulating histones as clinical biomarkers in critically ill conditions
Circulating histones are emerging as promising biomarkers in critical illness due to their diagnostic, prognostic, and therapeutic potential. Detection methods such as ELISA and mass spectrometry provide reliable approaches for quantifying histone levels in plasma samples.
José Luis García‐Gimenez+17 more
wiley +1 more source
Unmanned Aerial Vehicles (UAVs) are integral to the development of smart city infrastructures, enabling essential services such as real-time surveillance, urban traffic regulation, and cooperative environmental monitoring.
Mfonobong Uko+4 more
doaj +1 more source
Comment on "Regularizing capacity of metabolic networks"
In a recent paper, Marr, Muller-Linow and Hutt [Phys. Rev. E 75, 041917 (2007)] investigate an artificial dynamic system on metabolic networks. They find a less complex time evolution of this dynamic system in real networks, compared to networks of ...
A. Wagner+4 more
core +1 more source
Single‐cell insights into the role of T cells in B‐cell malignancies
Single‐cell technologies have transformed our understanding of T cell–tumor cell interactions in B‐cell malignancies, revealing new T‐cell subsets, functional states, and immune evasion mechanisms. This Review synthesizes these findings, highlighting the roles of T cells in pathogenesis, progression, and therapy response, and underscoring their ...
Laura Llaó‐Cid
wiley +1 more source
Restricted Boltzmann Machine-Based Approaches for Link Prediction in Dynamic Networks
Link prediction in dynamic networks aims to predict edges according to historical linkage status. It is inherently difficult because of the linear/non-linear transformation of underlying structures.
Taisong Li+4 more
semanticscholar +1 more source
Stochastic Block Transition Models for Dynamic Networks [PDF]
There has been great interest in recent years on statistical models for dynamic networks. In this paper, I propose a stochastic block transition model (SBTM) for dynamic networks that is inspired by the well-known stochastic block model (SBM) for static ...
Xu, Kevin S.
core
Distributed Queuing in Dynamic Networks
We consider the problem of forming a distributed queue in the adversarial dynamic network model of Kuhn, Lynch, and Oshman (STOC 2010) in which the network topology changes from round to round but the network stays connected.
Busch, Costas, Sharma, Gokarna
core +2 more sources
Urine is a rich source of biomarkers for cancer detection. Tumor‐derived material is released into the bloodstream and transported to the urine. Urine can easily be collected from individuals, allowing non‐invasive cancer detection. This review discusses the rationale behind urine‐based cancer detection and its potential for cancer diagnostics ...
Birgit M. M. Wever+1 more
wiley +1 more source