Results 121 to 130 of about 6,058 (264)
The historical scaling of deep learning models and decentralized multi-agent routing networks has relied almost exclusively on linear operations mapped within flat, Euclidean geometric spaces. However, as the dimensionality of representations and the topological complexity of agentic networks scale, these Cartesian coordinate systems suffer from severe
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Consensus Formation and Change are Enhanced by Neutrality
Neutral agents are shown to enhance both the formation and overturning of consensus in collective decision‐making. A general mathematical model and experiments with locusts and humans reveal that neutrality enables robust consensus via simple interactions and accelerates consensus change by reducing effective population size.
Andrei Sontag +3 more
wiley +1 more source
Two-dimensional billiards are Turing complete. [PDF]
Miranda E, Ramos I.
europepmc +1 more source
Physical Origin of Temperature Induced Activation Energy Switching in Electrically Conductive Cement
The temperature‐induced Arrhenius activation energy switching phenomenon of electrical conduction in electrically conductive cement originates from structural degradation within the biphasic ionic‐electronic conduction architecture and shows percolation‐governed characteristics: pore network opening dominates the low‐percolation regime with downward ...
Jiacheng Zhang +7 more
wiley +1 more source
BoolForge: controlled generation and analysis of Boolean functions and networks. [PDF]
Kadelka C, Coberly B.
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Single‐cell longitudinal profiling reveals that androgen‐deprivation therapy induces a DPT+ fibroblast‐complement axis that suppresses macrophage inflammation and drives CD8+ T cell exhaustion in prostate cancer. Concurrently, resistant epithelial subpopulations persist and engage TSPAN1‐ and NRXN1‐mediated programs promoting CRPC and neuroendocrine ...
Yang Chen +19 more
wiley +1 more source
Coarse-Graining Reshapes Knot Dynamics in Polymers and Proteins. [PDF]
Sarkar S, DelloStritto M, Klein ML.
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ML Workflows for Screening Degradation‐Relevant Properties of Forever Chemicals
The environmental persistence of per‐ and polyfluoroalkyl substances (PFAS) necessitates efficient remediation strategies. This study presents physics‐informed machine learning workflows that accurately predict critical degradation properties, including bond dissociation energies and polarizability.
Pranoy Ray +3 more
wiley +1 more source
From Chaos to Care: Personalized AI for Early Cardiac Arrhythmia Warning. [PDF]
Halder S, Kim CM, Periwal V.
europepmc +1 more source
This repository archives the preprint and supporting numerical resources for RENASCENT-Q, an advanced extension of the TET–CVTL theoretical framework. RENASCENT-Q investigates time-symmetric quantum dynamics in open systems, with a focus on retrocausal mechanisms capable of inducing local negentropic effects (damping parameter β ≈ φ⁻² ≈ 0.382) that ...
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