For a broad class of planar Markov processes, viz. Lévy processes satisfying certain conditions (valid, e.g., in the case of Brownian motion and Lévy flights), we establish an exact, universal formula describing the shape of the convex hull of sample paths. We show indeed that the average number of edges joining paths' points separated by a time lapse Δτ ∈ [Δτ(1),Δτ(2)] is equal to 2 ln(Δτ(2)/Δτ(1)), regardless of the specific distribution of the process's increments and regardless of its total duration T. The formula also exhibits invariance when the time scale is multiplied by any constant. Apart from its theoretical importance, our result provides insights regarding the shape of two-dimensional objects (e.g., polymer chains) modeled by the sample paths of stochastic processes generally more complex than Brownian motion. In particular, for a total time (or parameter) duration T, the average number of edges on the convex hull ("cut off" to discard edges joining points separated by a time lapse shorter than some Δτ < T) will be given by 2 ln(T/Δτ). Thus it will only grow logarithmically, rather than at some higher pace.
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http://dx.doi.org/10.1103/PhysRevE.89.052112 | DOI Listing |
JMIR Form Res
January 2025
Northwestern Medicine, Chicago, IL, United States.
Background: Patient recruitment and data management are laborious, resource-intensive aspects of clinical research that often dictate whether the successful completion of studies is possible. Technological advances present opportunities for streamlining these processes, thus improving completion rates for clinical research studies.
Objective: This paper aims to demonstrate how technological adjuncts can enhance clinical research processes via automation and digital integration.
JMIR Med Inform
January 2025
Department of Systems Design Engineering, Faculty of Engineering, University of Waterloo, Waterloo, ON, Canada.
Background: While expert optometrists tend to rely on a deep understanding of the disease and intuitive pattern recognition, those with less experience may depend more on extensive data, comparisons, and external guidance. Understanding these variations is important for developing artificial intelligence (AI) systems that can effectively support optometrists with varying degrees of experience and minimize decision inconsistencies.
Objective: The main objective of this study is to identify and analyze the variations in diagnostic decision-making approaches between novice and expert optometrists.
ACS Appl Bio Mater
January 2025
Physics Department, Federal University of Viçosa, Viçosa, Minas Gerais 36570-900, Brazil.
This study investigates the functionalization of gold-coated magnetoelastic sensors with thionine molecules, focusing on resonance frequency shifts. The functionalization process was characterized by using Raman spectroscopy and analyzed via scanning electron microscopy and atomic force microscopy, revealing the progressive formation of molecular clusters over time. Our results demonstrate that longer functionalization time leads to saturation of surface coverage and cluster formation, impacting the sensor's resonance frequency shifts.
View Article and Find Full Text PDFPhys Rev Lett
December 2024
Massachusetts Institute of Technology, Cambridge, Massachusetts, USA.
We introduce an approach for analyzing the responses of dynamical systems to external perturbations that combines score-based generative modeling with the generalized fluctuation-dissipation theorem. The methodology enables accurate estimation of system responses, including those with non-Gaussian statistics. We numerically validate our approach using time-series data from three different stochastic partial differential equations of increasing complexity: an Ornstein-Uhlenbeck process with spatially correlated noise, a modified stochastic Allen-Cahn equation, and the 2D Navier-Stokes equations.
View Article and Find Full Text PDFPhys Rev Lett
December 2024
Key Laboratory for Laser Plasmas and School of Physics and Astronomy, and Collaborative Innovation Center of IFSA, Shanghai Jiao Tong University, Shanghai 200240, China.
Time-dependent density functional theory (TDDFT) is widely used for understanding and predicting properties and behaviors of matter. As one of the fundamental theorems in TDDFT, Van Leeuwen theorem [Phys. Rev.
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