Results 41 to 50 of about 3,426,931 (297)

Canonical decompositions of certain generalized Brownian bridges [PDF]

open access: yes, 2002
We define a generalized Brownian bridge and we provide some information about its filtration. Two decompositions of this process as a semi-martingale are given.
Alili, Larbi
core   +1 more source

Artificial molecular machines and motors—Design and control of nanoscale motion

open access: yesFEBS Letters, EarlyView.
Molecules are constantly moving because of thermal fluctuations, but random motion alone cannot be exploited to perform directional tasks. Artificial molecular machines use chemical, electrical, or light energy to bias this motion. Molecular shuttles, rotary motors, and supramolecular pumps illustrate how nanoscale movement can be controlled and ...
Leonardo Andreoni, Alberto Credi
wiley   +1 more source

Nonlinear Brownian motion - mean square displacement

open access: yesCondensed Matter Physics, 2004
The stochastic dynamics of self-propelled Brownian particles is studied by means of the Langevin and the Fokker-Planck approach. We model the driving by a nonlinear friction function which has a negative part at small velocities, leading to active ...
W.Ebeling
doaj   +1 more source

Malliavin Weight Sampling: A Practical Guide

open access: yesEntropy, 2013
Malliavin weight sampling (MWS) is a stochastic calculus technique for computing the derivatives of averaged system properties with respect to parameters in stochastic simulations, without perturbing the system’s dynamics. It applies to systems in or out
Patrick B. Warren, Rosalind J. Allen
doaj   +1 more source

Learning the non-equilibrium dynamics of Brownian movies

open access: yesNature Communications, 2020
A tracking-free approach by Gnesotto et al. is developed to distinguish active and thermal fluctuations in microscopy data of non-equilibrium systems such as cell membranes. The method relies on a dimensional reduction scheme revealing a hierarchy of the
Federico S. Gnesotto   +3 more
doaj   +1 more source

Optimization of seminal extracellular vesicle isolation protocols for cancer biomarker analysis using proteomic profiling

open access: yesMolecular Oncology, EarlyView.
This paper shows that size‐exclusion chromatography and sequential centrifugation applied to seminal plasma enrich for different populations of extracellular vesicles. This may significantly affect the detection and analysis of extracellular vesicle‐associated cancer biomarkers.
Elen Telumyan   +8 more
wiley   +1 more source

Two levels of topology in skyrmion lattice dynamics

open access: yesPhysical Review Research
Skyrmions are localized, topological spin structures that can be described as quasiparticles. Skyrmions in thin films are an ideal model system to study Brownian motion and lattice formation in two dimensions.
Daniel Schick   +5 more
doaj   +1 more source

Dyson's Brownian motions, intertwining and interlacing [PDF]

open access: yes, 2007
A reflected Brownian motion in the Gelfand-Tsetlin cone is used to construct Dyson's process of non-colliding Brownian motions. The key step of the construction is to consider two interlaced families of Brownian paths with paths belonging to the second ...
Warren, Jon
core  

Using fluorescence fluctuation spectroscopy to quantify molecular dynamics within cells

open access: yesFEBS Open Bio, EarlyView.
Microscopy techniques like fluorescence correlation spectroscopy (FCS) and number and brightness analysis (N&B) allow to quantify concentrations, diffusion rates, and oligomerization of fluorescently labeled molecules in the living cell. In this protocol the principles of how to set up these types of experiments are described including calibration ...
Mark A. Hink
wiley   +1 more source

dynoGP: Deep Gaussian Processes for Dynamic System Identification

open access: yesInternational Journal of Adaptive Control and Signal Processing, EarlyView.
This work introduces a novel class of deep models for system identification, dynamical deep Gaussian processes, which combine the strengths of data‐driven methods, such as those based on neural network architectures, with the ability to output a probability distribution for uncertainty representation.
Alessio Benavoli   +3 more
wiley   +1 more source

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