Paper List
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An AI Implementation Science Study to Improve Trustworthy Data in a Large Healthcare System
This paper addresses the critical gap between theoretical AI research and real-world clinical implementation by providing a practical framework for as...
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The BEAT-CF Causal Model: A model for guiding the design of trials and observational analyses of cystic fibrosis exacerbations
This paper addresses the critical gap in cystic fibrosis exacerbation management by providing a formal causal framework that integrates expert knowled...
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Hierarchical Molecular Language Models (HMLMs)
This paper addresses the core challenge of accurately modeling context-dependent signaling, pathway cross-talk, and temporal dynamics across multiple ...
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Stability analysis of action potential generation using Markov models of voltage‑gated sodium channel isoforms
This work addresses the challenge of systematically characterizing how the high-dimensional parameter space of Markov models for different sodium chan...
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Approximate Bayesian Inference on Mechanisms of Network Growth and Evolution
This paper addresses the core challenge of inferring the relative contributions of multiple, simultaneous generative mechanisms in network formation w...
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EnzyCLIP: A Cross-Attention Dual Encoder Framework with Contrastive Learning for Predicting Enzyme Kinetic Constants
This paper addresses the core challenge of jointly predicting enzyme kinetic parameters (Kcat and Km) by modeling dynamic enzyme-substrate interaction...
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Tissue stress measurements with Bayesian Inversion Stress Microscopy
This paper addresses the core challenge of measuring absolute, tissue-scale mechanical stress without making assumptions about tissue rheology, which ...
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DeepFRI Demystified: Interpretability vs. Accuracy in AI Protein Function Prediction
This study addresses the critical gap between high predictive accuracy and biological interpretability in DeepFRI, revealing that the model often prio...
Macroscopic Dominance from Microscopic Extremes: Symmetry Breaking in Spatial Competition
Department of Mathematics, Florida State University | Department of Mathematics and Statistics, Cleveland State University | Institute of Molecular Biophysics, Florida State University
30秒速读
IN SHORT: This paper addresses the fundamental question of how microscopic stochastic advantages in spatial exploration translate into macroscopic resource dominance, revealing that initial discovery and final monopolization are governed by distinct physical mechanisms.
核心创新
- Methodology Introduces a dimensionless scaling parameter χ = (N₂/N₁)8^(d₁-d₂) that completely determines competitive symmetry, showing that a linear spatial disadvantage requires an exponential population advantage to overcome.
- Theory Demonstrates that extreme first-passage statistics govern initial discovery, while non-reciprocal interaction bias (β) controls the sharpness of the competitive phase transition and stability of the absorbing state.
- Biology Reveals a strict hierarchy of symmetry-breaking factors: proximity to resource > population size > interaction bias, with β being necessary but not sufficient for dominance.
主要结论
- Proximity imparts the strongest competitive advantage: a colony with distance d₁ < d₂ requires N₂/N₁ ~ 8^(d₂-d₁) ants to compensate (Equation 3).
- The interaction bias β acts as a phase transition tuner: for β → 0, outcomes remain probabilistic; for large β, the symmetry-breaking boundary sharpens into a step function (Figure 3).
- Discovery and monopolization are decoupled: extreme first-passage statistics govern initial finding (⟨T_i⟩ = d_i + (1-p_i)^(N_i)), while β strictly controls stability of the absorbing state.
摘要: How do competing populations convert a spatial advantage into macroscopic dominance? We introduce a stochastic model for resource competition that decouples the transient discovery phase from monopolization. Initial symmetry breaking is governed by extreme value statistics of first-passage times: a linear spatial disadvantage requires an exponentially larger population to overcome. However, transient superiority cannot stabilize dominance. A non-reciprocal interaction bias is strictly necessary to arrest local fluctuations and drive the system into a robust absorbing state.