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We propose a novel Bayesian framework for changepoint detection in large-scale spherical spatiotemporal data, with broad applicability in environmental and climate sciences. Our approach models changepoints as spatially dependent…

Methodology · Statistics 2026-02-16 Samantha Shi-Jun , Bo Li

Change point analysis is a statistical tool to identify homogeneity within time series data. We propose a pruning approach for approximate nonparametric estimation of multiple change points. This general purpose change point detection…

Methodology · Statistics 2017-09-20 Wenyu Zhang , Nicholas James , David Matteson

Cells control fluid flows with a spatial and temporal precision that far exceeds the capabilities of current microfluidic technologies. Cells achieve this superior spatio-temporal control by harnessing dynamic networks of cytoskeleton and…

Soft Condensed Matter · Physics 2025-05-26 Fan Yang , Shichen Liu , Heun Jin Lee , Rob Phillips , Matt Thomson

Phase contrast microscopy (PCM) has been widely used in biomedicine research, which allows users to observe objectives without staining or killing them. One important related research is to employ PCM to monitor live cells. How to segment…

Computer Vision and Pattern Recognition · Computer Science 2019-11-26 Lin Zhang

We consider the problem of change-point estimation of the instantaneous phase of an observed time series. Such change points, or phase shifts, can be markers of information transfer in complex systems; their analysis occurring in geology,…

Applications · Statistics 2014-01-17 William Marshall , Paul Marriott

In an era where climate change aggravates environmental uncertainties, the identification and detection of event precursors are becoming crucial to mitigate the impacts of disastrous natural hazards. While classical sensors such as…

Computer Vision and Pattern Recognition · Computer Science 2026-05-28 Arthur Dérédel , Carlos Crispim-Junior , Pierre Lemaire , Johan Berthet , Laure Tougne Rodet

Involved in mitotic condensation, interaction of transcriptional regulatory elements or isolation of structural domains, understanding loop formation is becoming a paradigm in the deciphering of chromatin architecture and its functional…

Quantitative Methods · Quantitative Biology 2024-09-17 Michaël Liefsoens , Timothy Földes , Maria Barbi

Single-particle tracking allows to infer the motion of single molecules in living cells. When we observe a long trajectory (more than 100 points), it is possible that the particle switches mode of motion over time. Then, fitting a single…

Methodology · Statistics 2018-04-16 Vincent Briane , Charles Kervrann , Myriam Vimond

In this article we present a new diagnostic approach utilizing flow-cytometry to study compounds of nanoparticle samples in solution by analysis of their scattering patterns retrieved from the cytometric measurements. As a specific…

Many systems of interacting elements can be conceptualized as networks, where network nodes represent the elements and network ties represent interactions between the elements. In systems where the underlying network evolves in time, it is…

Methodology · Statistics 2015-05-05 Ian Barnett , Jukka-Pekka Onnela

We present a new technique for monitoring microlensing activity even in highly crowded fields, and use this technique to place limits on low-mass MACHOs in the haloes of M31 and the Galaxy. Unlike present Galactic microlensing surveys, we…

Astrophysics · Physics 2009-09-28 Austin B. Tomaney , Arlin P. S. Crotts

We propose a model for cell migration where epithelial cells are able to detect trajectories of other cells and try to follow them. As cells move along in 2D cell culture, they mark their paths by loosing tiny parts of cytoplasm. Any cell…

Condensed Matter · Physics 2009-11-07 Stefan Thurner , Nikolaus Wick , Rudolf Hanel , Roland Sedivy , Lukas Huber

Cytoplasmic streaming, the coherent flow of cytoplasm, plays a critical role in transport and mixing over large scales in eukaryotic cells. In many large cells, this process is driven by active forces at the cell boundary, such as cortical…

Biological Physics · Physics 2025-02-18 Pyae Hein Htet , Eric Lauga

Several meters below the coastal ocean surface there are areas of high ecological activity that contain thin layers of concentrated motile phytoplankton. Gyrotactic trapping has been proposed as a potential mechanism for layer formation of…

Fluid Dynamics · Physics 2019-05-22 Smitha Maretvadakethope , Eric E. Keaveny , Yongyun Hwang

This paper develops a unified and computationally efficient method for change-point estimation along the time dimension in a non-stationary spatio-temporal process. By modeling a non-stationary spatio-temporal process as a piecewise…

Methodology · Statistics 2023-10-09 Zifeng Zhao , Ting Fung Ma , Wai Leong Ng , Chun Yip Yau

The Dynamic Template model of biological cell membranes and the cytoplasm as spatially organised fluid layers is extended to plant cells, and is shown to offer a feasible shear driven mechanism for the co-alignment of internal and external…

General Physics · Physics 2008-07-15 J. T. Lofthouse

Planktonic organisms, despite their passive drift in the ocean, exhibit complex responses to fluid flow, including escape behaviors and larval settlement detection. But what flow signals can they perceive? This paper addresses this question…

Fluid Dynamics · Physics 2024-11-27 Christophe Eloy

Biomolecular condensates form on timescales of seconds in cells upon environmental or compositional changes. Condensate formation is thus argued to act as a mechanism for sensing such changes and quickly initiating downstream processes,…

Subcellular Processes · Quantitative Biology 2025-12-09 Henry Alston , Mason Rouches , Arvind Murugan , Aleksandra M. Walczak , Thierry Mora

A number-conserving cellular automaton is a simplified model for a system of interacting particles. This paper contains two related constructions by which one can find all one-dimensional number-conserving cellular automata with one kind of…

Cellular Automata and Lattice Gases · Physics 2023-06-22 Markus Redeker

This manuscript studies the unsupervised change point detection problem in time series of graphs using a decoder-only latent space model. The proposed framework consists of learnable prior distributions for low-dimensional graph…

Methodology · Statistics 2025-04-18 Yik Lun Kei , Jialiang Li , Hangjian Li , Yanzhen Chen , Oscar Hernan Madrid Padilla
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