Results 101 to 110 of about 7,331,913 (294)
Functional Limit Theorems for Occupation Time Fluctuations of Branching Systems in the Case of Long-Range Dependence [PDF]
Functional central limit theorem; Occupation time uctuation; Branching particle system; Distribution-valued Gaussian process; Fractional Brownian motion; Sub-fractional Brownian motion; Long-range ...
Luis G. Gorostiza +2 more
core
Agribusiness, EarlyView.ABSTRACT The US hemp market is a new and nascent industry that has been devoid of research for about half a century. This study examined the effects of exogenous shock on price at each phase of the value chain—Farm (hemp biomass), and its impact on prices at other phases of the value chain—Intermediary Processor (crude cannabidiol hemp) and Final ...
Solomon Odiase +2 more
wiley +1 more source
The Geography of Success: A Spatial Analysis of Export Intensity in the Italian Wine Industry
Agribusiness, EarlyView.ABSTRACT This paper investigates the paradox of how Italy's fragmented, SME‐dominated wine industry achieves global export success. Moving beyond purely firm‐centric explanations, we test whether export intensity is spatially dependent, clustering geographically in regional ecosystems.
Nicolas Depetris Chauvin, Jonas Di Vita
wiley +1 more source
A bivariate local limit theorem
Journal of Multivariate Analysis, 1991 A random 2-vector in \(X\subset\mathbb{R}^{(2)}\) is said to have a stable distribution if there exist a sequence of i.i.d. vectors \(Y_ n=(Y_ n^{(1)},Y_ n^{(2)})\) and associated 2-vector sequences \(\{b_ n\}\), and \(\{a_ n\}\) with \(b_ n=\{b_ n^{(1)},b_ n^{(2)}\}\), \(a_ n=\{a_ n^{(1)},a_ n^{(2)}\}\), \(a_ n^{(i)}>0\), \(i=1,2\), with \(\{S_ n^{(1)}
openaire +2 more sources
A Donsker Theorem for Lévy Measures [PDF]
Given n equidistant realisations of a Lévy process (Lt; t >= 0), a natural estimator for the distribution function N of the Lévy measure is constructed. Under a polynomial decay restriction on the characteristic function, a Donsker-type theorem is proved,
Richard Nickl, Markus Reiß
core
Advanced Intelligent Discovery, EarlyView.This perspective highlights how knowledge‐guided artificial intelligence can address key challenges in manufacturing inverse design, including high‐dimensional search spaces, limited data, and process constraints. It focused on three complementary pillars—expert‐guided problem definition, physics‐informed machine learning, and large language model ...
Hugon Lee +3 more
wiley +1 more source
Stability and Andronov-Hopf Bifurcation of a System with Three Time Delays
Journal of Mathematics, 2013 A general system of three autonomous ordinary differential equations with three discrete time delays is considered. With respect to the delays, we investigate the local stability of equilibria by analyzing the corresponding characteristic equation. Using
Svetoslav Nikolov
doaj +1 more source
Advanced Intelligent Discovery, EarlyView.In this work, the Doubao large language model (LLM) is involved in the formula derivation processes for Hubbard U determination regarding the second‐order perturbations of the chemical potential. The core ML tool is optimized for physical domain knowledge, which is not limited to parameter prediction but rather serves as an interactive physical theory ...
Mingzi Sun +8 more
wiley +1 more source
A Unifying Approach to Self‐Organizing Systems Interacting via Conservation Laws
Advanced Intelligent Discovery, EarlyView.The article develops a unified way to model and analyze self‐organizing systems whose interactions are constrained by conservation laws. It represents physical/biological/engineered networks as graphs and builds projection operators (from incidence/cycle structure) that enforce those constraints and decompose network variables into constrained versus ...
F. Barrows +7 more
wiley +1 more source
Explaining the Origin of Negative Poisson's Ratio in Amorphous Networks With Machine Learning
Advanced Intelligent Discovery, EarlyView.This review summarizes how machine learning (ML) breaks the “vicious cycle” in designing auxetic amorphous networks. By transitioning from traditional “black‐box” optimization to an interpretable “AI‐Physics” closed‐loop paradigm, ML is shown to not only discover highly optimized structures—such as all‐convex polygon networks—but also unveil hidden ...
Shengyu Lu, Xiangying Shen
wiley +1 more source