Results 11 to 20 of about 55,281 (143)

Evolutionary dynamics on a regular networked structured and unstructured multi‐population

International Journal of Robust and Nonlinear Control, EarlyView., 2023
Abstract In this paper, we study collective decision‐making in a multi‐population framework, where groups of individuals represent whole populations that interact by means of a regular network. Each group consists of a number of players and every player can choose between two options.
Wouter Baar, Leonardo Stella, Dario Bauso   +2 more
wiley   +1 more source

Mechanoadaptation via Myosin Cytoplasmic Redistribution Protects Circulating Tumor Cells From Shear‐induced Death During Hematogenous Dissemination

Advanced Science, EarlyView.
This study investigates how CTCs survive varying shear stress during hematogenous metastasis. We uncover a self‐protection mechanism, by which non‐adherent CTCs adapt to high shearing milieu through accumulated cytoplasmic myosin‐mediated disruption of myosin‐actin binding, attenuating force transmission into chromatin to protect CTCs from shear ...
Cunyu Zhang, Qianchun Wang, Keming Li, Guanshuo Hu, Ying Xin, Kai Tang, Bing Hu, Pengyu Du, Renwei Mao, Baohua Ji, Youhua Tan   +10 more
wiley   +1 more source

SPICE‐Compatible Compact Modeling of Cuprate‐Based Memristors Across a Wide Temperature Range

Advanced Electronic Materials, EarlyView.
A physics‐guided compact model for YBCO memristors is introduced, incorporating carrier trapping, field‐induced detrapping, and a differential balance equation to describe their switching dynamics. The model is compared with experiments and implemented in LTspice, allowing realistic circuit‐level simulations.
Thomas Günkel, Aleix Barrera, Lluís Balcells, Narcís Mestres, Enrique Miranda, Anna Palau, Jordi Suñé   +6 more
wiley   +1 more source

Interpretability and Representability of Commutative Algebra, Algebraic Topology, and Topological Spectral Theory for Real‐World Data

Advanced Intelligent Discovery, EarlyView.
This article investigates how persistent homology, persistent Laplacians, and persistent commutative algebra reveal complementary geometric, topological, and algebraic invariants or signatures of real‐world data. By analyzing shapes, synthetic complexes, fullerenes, and biomolecules, the article shows how these mathematical frameworks enhance ...
Yiming Ren, Guo‐Wei Wei
wiley   +1 more source

Revealing Protein–Protein Interactions Using a Graph Theory‐Augmented Deep Learning Approach

Advanced Intelligent Discovery, EarlyView.
This study presents a fast, cost‐efficient approach for classifying protein–protein interactions by integrating graph‐theory parametrization with deep learning (DL). Multiscale features extracted from graph‐encoded polarized‐light microscopy (PLM) images enable accurate prediction of binding strengths.
Bahar Dadfar, Gözde Kabay, Matthias Franzreb, Kody Whisnant, Nicholas A. Kotov, Joerg Lahann   +5 more
wiley   +1 more source

Deep Learning Approaches for Classifying Crack States With Overload and Predicting Fatigue Parameters in a Titanium Alloy

Advanced Intelligent Systems, EarlyView.
This study proposes a deep learning approach to evaluate the fatigue crack behavior in metals under overload conditions. Using digital image correlation to capture the strain near crack tips, convolutional neural networks classify crack states as normal, overload, or recovery, and accurately predict fatigue parameters.
Seon Du Choi, Suman Timilsina, Youn Woo Shin, Yong Nam Kwon, Kee‐Sun Sohn, Ji Sik Kim   +5 more
wiley   +1 more source

An Introduction to Predictive Processing Models of Perception and Decision‐Making

Topics in Cognitive Science, EarlyView., 2023
Abstract The predictive processing framework includes a broad set of ideas, which might be articulated and developed in a variety of ways, concerning how the brain may leverage predictive models when implementing perception, cognition, decision‐making, and motor control.
Mark Sprevak, Ryan Smith
wiley   +1 more source

Risk‐aware safe reinforcement learning for control of stochastic linear systems

Asian Journal of Control, EarlyView.
Abstract This paper presents a risk‐aware safe reinforcement learning (RL) control design for stochastic discrete‐time linear systems. Rather than using a safety certifier to myopically intervene with the RL controller, a risk‐informed safe controller is also learned besides the RL controller, and the RL and safe controllers are combined together ...
Babak Esmaeili, Nariman Niknejad, Hamidreza Modares   +2 more
wiley   +1 more source

A hidden Markov model and reinforcement learning‐based strategy for fault‐tolerant control

The Canadian Journal of Chemical Engineering, EarlyView.
Abstract This study introduces a data‐driven control strategy integrating hidden Markov models (HMM) and reinforcement learning (RL) to achieve resilient, fault‐tolerant operation against persistent disturbances in nonlinear chemical processes. Called hidden Markov model and reinforcement learning (HMMRL), this strategy is evaluated in two case studies
Tamera Leitao, Debaprasad Dutta, Simant R. Upreti   +2 more
wiley   +1 more source

Computational linear algebra over finite fields [PDF]

, 2012
We present here algorithms for efficient computation of linear algebra problems over finite ...
Dumas, Jean-Guillaume, Pernet, Clément
core   +3 more sources