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Markov state models (MSMs) are a widely used method for approximating the eigenspectrum of the molecular dynamics propagator, yielding insight into the long-timescale statistical kinetics and slow dynamical modes of biomolecular systems.…

Biomolecules · Quantitative Biology 2015-03-30 Robert T. McGibbon , Vijay S. Pande

We investigate the dynamical process of optically trapped X$^{1}$$\Sigma$$^{+}$ (v" = 0) state $^{85}$Rb$^{133}$Cs molecules distributing in J" = 1 and J" = 3 rotational states. The considered molecules, formed from short-range…

Atomic Physics · Physics 2018-03-14 Zhonghao Li , Ting Gong , Zhonghua Ji , Yanting Zhao , Liantuan Xiao , Suotang Jia

Phenotype-based screening has attracted much attention for identifying cell-active compounds. Transcriptional and proteomic profiles of cell population or single cells are informative phenotypic measures of cellular responses to…

Quantitative Methods · Quantitative Biology 2023-11-20 Wei Huang , Aichun Zhu , Hui Liu

We study dynamic self-organisation and order-disorder transitions in a two-dimensional system of self-propelled particles. Our model is a variation of the Vicsek model, where particles align the motion to their neighbours but repel each…

Statistical Mechanics · Physics 2013-05-02 Maksym Romenskyy , Vladimir Lobaskin

Discrete dynamics arise naturally in systems with broken temporal translation symmetry and are typically described by first-order recurrence relations representing classical or quantum Markov chains. When memory effects induced by hidden…

Statistical Mechanics · Physics 2025-10-31 Hugues Meyer , Kay Brandner

The packing geometry of macromolecules in complex mesophases is of key importance to self-organization in synthetic and biological soft materials. While approximate or heuristic models rely on often-untested assumptions about how flexible…

Soft Condensed Matter · Physics 2023-10-05 Benjamin R. Greenvall , Michael S. Dimitriyev , Gregory M. Grason

Visualization tools can help synthetic biologists and molecular programmers understand the complex reactive pathways of nucleic acid reactions, which can be designed for many potential applications and can be modelled using a…

Quantitative Methods · Quantitative Biology 2023-11-08 Chenwei Zhang , Jordan Lovrod , Boyan Beronov , Khanh Dao Duc , Anne Condon

A discrete Boltzmann model (DBM) is proposed to probe the Rayleigh-Taylor instability (RTI) in two-component compressible flows. Each species has a flexible specific heat ratio and is described by one discrete Boltzmann equation (DBE).…

Soft Condensed Matter · Physics 2017-11-22 Chuandong Lin , Aiguo Xu , Guangcai Zhang , Kaihong Luo , Yingjun Li

The scrutiny surrounding vote-by-mail (VBM) in the United States has increased in recent years, highlighting the need for a rigorous quantitative framework to evaluate the resilience of the absentee voting infrastructure. This paper…

Cryptography and Security · Computer Science 2026-04-06 Carmen A. Haseltine , Laura A. Albert

Real-time cone-beam computed tomography (CBCT) provides instantaneous visualization of patient anatomy for image guidance, motion tracking, and online treatment adaptation in radiotherapy. While many real-time imaging and motion tracking…

Medical Physics · Physics 2024-09-27 Hua-Chieh Shao , Tielige Mengke , Tinsu Pan , You Zhang

Thermodynamic nonequilibrium effects play a central role in momentum and energy transport in compressible flows. In conventional BGK kinetic models, the relaxation time $\tau$ is taken as a constant, which neglects the dependence of the…

Fluid Dynamics · Physics 2026-05-19 Demei Li , Zhongyi He , Huilin Lai , Yanbiao Gan , Hailong Liu , Pengfei Lin

This study integrates causal inference, graph analysis, temporal complexity measures, and machine learning to examine whether individual symptom trajectories can reveal meaningful diagnostic patterns. Testing on a longitudinal dataset of…

Applications · Statistics 2025-07-22 Eleonora Vitanza , Pietro DeLellis , Chiara Mocenni , Manuel Ruiz Marin

Structure-Based Drug Design (SBDD) is crucial for identifying bioactive molecules. Recent deep generative models are faced with challenges in geometric structure modeling. A major bottleneck lies in the twisted probability path of…

Biomolecules · Quantitative Biology 2025-06-06 Keyue Qiu , Yuxuan Song , Zhehuan Fan , Peidong Liu , Zhe Zhang , Mingyue Zheng , Hao Zhou , Wei-Ying Ma

This paper aims at a comprehensive understanding on the novel elastic property of double-stranded DNA (dsDNA) discovered very recently through single-molecule manipulation techniques. A general elastic model for double-stranded biopolymers…

Soft Condensed Matter · Physics 2009-10-31 Haijun Zhou , Yang Zhang , Zhong-can Ou-Yang

1. Hidden Markov models (HMMs) are powerful tools for modelling time-series data with underlying state structure. However, selecting appropriate parametric forms for the state-dependent distributions is often challenging and can lead to…

Human brain functional connectivity (FC) is often measured as the similarity of functional MRI responses across brain regions when a brain is either resting or performing a task. This paper aims to statistically analyze the dynamic nature…

Computer Vision and Pattern Recognition · Computer Science 2024-10-30 Mengyu Dai , Zhengwu Zhang , Anuj Srivastava

Cardiac motion over a cardiac cycle is crucial for quantifying regional function and is strongly affected by cardiovascular diseases. Since temporally dense mesh sequences are difficult to obtain in practice, we focus on leveraging the more…

Computer Vision and Pattern Recognition · Computer Science 2026-05-21 Xuan Yang , Xiaohan Yuan , Hao Li , Lingyu Chen , Yanan Liu , Lei Li

Fluctuation in fluorescence emission of immobilized single molecule is typically ascribed to the chromophore's intrinsic structural conformations and the influence of local environmental factors. Despite extensive research over several…

Chemical Physics · Physics 2024-08-07 Aranyak Sarkar , Vinu Namboodiri , Manoj Kumbhakar

Molecular Dynamics (MD) is a powerful computational microscope for probing protein functions. However, the need for fine-grained integration and the long timescales of biomolecular events make MD computationally expensive. To address this,…

Machine Learning · Computer Science 2026-03-30 Kacper Kapuśniak , Cristian Gabellini , Michael Bronstein , Prudencio Tossou , Francesco Di Giovanni

A dynamical system is considered, which comprises an $n$-dimensional lattice $N_1 \times N_2 \times \dots \times N_n$ with periodic boundary conditions. Particles traverse this lattice following a variant of the Biham--Middleton--Levine…

Optimization and Control · Mathematics 2023-10-05 Valery V. Kozlov , Alexander G. Tatashev , Marina V. Yashina
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