Results 31 to 40 of about 39,522 (208)
Pairwise MRF Calibration by Perturbation of the Bethe Reference Point [PDF]
We investigate different ways of generating approximate solutions to the pairwise Markov random field (MRF) selection problem. We focus mainly on the inverse Ising problem, but discuss also the somewhat related inverse Gaussian problem because both types
Furtlehner, Cyril +3 more
core +3 more sources
Central limit theorem for exponentially quasi-local statistics of spin models on Cayley graphs
Central limit theorems for linear statistics of lattice random fields (including spin models) are usually proven under suitable mixing conditions or quasi-associativity.
Reddy, Tulasi Ram +2 more
core +1 more source
Objective Somatic items used in depression assessments can potentially overlap with symptoms related to physical illness, including systemic sclerosis (SSc). No studies have looked at whether somatic depression items may be influenced by diffuse versus limited SSc disease subtypes, which are associated with varying degrees of symptom presentation.
Sophie Hu +109 more
wiley +1 more source
This study investigates laser shock peening for enhancing fatigue performance of riveted aerospace aluminum joints. A comparative approach with cold expansion combines fatigue testing and synchrotron X‐ray methods. Integrating mechanical testing with residual stress and strain characterization provides insights into how different treatments affect the ...
Ogün Baris Tapar +6 more
wiley +1 more source
We analyze a new random algorithm for numerical integration of $d$-variate functions over $[0,1]^d$ from a weighted Sobolev space with dominating mixed smoothness $\alpha\ge 0$ and product weights $1\ge\gamma_1\ge\gamma_2\ge\cdots>0$, where the functions
Kritzer, Peter +3 more
core +2 more sources
Curvature‐tuned auxetic lattices are designed, fabricated, and mechanically characterized to reveal how geometric curvature governs stretchability, stress redistribution, and Poisson's ratio evolution. Photoelastic experiments visualize stress pathways, while hyperelastic simulations quantify deformation mechanics.
Shuvodeep De +3 more
wiley +1 more source
Unleashing the Power of Machine Learning in Nanomedicine Formulation Development
A random forest machine learning model is able to make predictions on nanoparticle attributes of different nanomedicines (i.e. lipid nanoparticles, liposomes, or PLGA nanoparticles) based on microfluidic formulation parameters. Machine learning models are based on a database of nanoparticle formulations, and models are able to generate unique solutions
Thomas L. Moore +7 more
wiley +1 more source
Two-Sample U-Statistic Processes for Long-Range Dependent Data [PDF]
Motivated by some common-change point tests, we investigate the asymptotic distribution of the U-statistic process $U_n(t)=\sum_{i=1}^{[nt]}\sum_{j=[nt]+1}^n h(X_i,X_j)$, $0\leq t\leq 1$, when the underlying data are long-range dependent.
Dehling, Herold +2 more
core
Loop Vertex Expansion for Phi^2k Theory in Zero Dimension
In this paper we extend the method of loop vertex expansion to interactions with degree higher than 4. As an example we provide through this expansion an explicit proof that the free energy of Phi^2k scalar theory in zero dimension is Borel-Le Roy ...
Rivasseau, Vincent, Wang, Zhituo
core +2 more sources
Peptide Sequencing With Single Acid Resolution Using a Sub‐Nanometer Diameter Pore
To sequence a single molecule of Aβ1−42–sodium dodecyl sulfate (SDS), the aggregate is forced through a sub‐nanopore 0.4 nm in diameter spanning a 4.0 nm thick membrane. The figure is a visual molecular dynamics (VMD) snapshot depicting the translocation of Aβ1−42–SDS through the pore; only the peptide, the SDS, the Na+ (yellow/green) and Cl− (cyan ...
Apurba Paul +8 more
wiley +1 more source

