Results 81 to 90 of about 4,577,308 (305)
A Multi‐Scale Machine Learning Framework for the Inverse Design of High Entropy Alloys
High‐entropy alloys offer vast potential for various applications, including electrocatalysis; however, their compositional complexity challenges conventional screening. We introduce an inverse‐design framework combining two neural networks to determine optimal compositions and reconstruct nanoparticle geometry from targeted properties and conventional
Mikael Takoutsin +14 more
wiley +1 more source
Improving Parametric Mortgage Prepayment Models with Non-parametric Kernel Regression [PDF]
Developing a good prepayment model is a central task in the valuation of mortgages and mortgage-backed securities but conventional parametric models often have bad out-of-sample predictive ability.
Michael Marschoun +2 more
core
Econometric Analysis of Ratings — with an Application to Health and Wellbeing
Summary We propose a new non-linear regression model for rating dependent variables. The rating scale model accounts for the upper and lower bounds of ratings. Parametric and semi-parametric estimation is discussed.
Raphael Studer, Rainer Winkelmann
doaj +1 more source
A dynamically actuated reconfigurable topographical surface (DARTS) integrates contact‐mediated bactericidal nanotopography with programmable mechanical actuation to actively disrupt bacterial biofilms. Dynamic surface reconfiguration enhances bacterial killing and suppresses implant‐associated infections in vivo, providing a new strategy for active ...
Mohammad Asadi Tokmedash +4 more
wiley +1 more source
Copula-Based Regression with Mixed Covariates
In this paper, we focused on developing copula-based modeling procedures that effectively capture the dependence between response and explanatory variables. Building upon the work of Noh et al. (J. Am. Stat. Assoc.
Saeed Aldahmani +2 more
doaj +1 more source
Semi-nonparametric count data estimation with an endogenous binary variable [PDF]
This paper proposes a semi-nonparametric Poisson model with an endogenous binary variable, which generalizes bivariate correlated unobserved heterogeneity using Hermite polynomials, and compares this model with a parametric one.
Hiroaki Masuhara
core
Cell therapies typically rely on cold‐chain logistics and cryopreservation, limiting access and compromising cell quality. Here, a dual‐chamber device separates an oxygen‐supplying chamber from a hyaluronic acid cargo chamber, sustaining oxygen delivery for over 70 h and enabling ambient‐temperature shipment.
Daniel A. Domingo‐Lopez +9 more
wiley +1 more source
On Statistical Analysis of Compound Point Process
The contribution deals with a stochastic process cumulating random increments at random moments (the compound point process). First, its martingale - compensator decomposition is recalled.
Petr Volf
doaj +1 more source
Hafnium zirconium oxide thin films are grown using plasma‐enhanced atomic layer deposition with the addition of an atomic layer annealing (ALA) step. ALA leads to a change in the short‐range structure of the deposit and encourages formation of the ferroelectric Pca21 phase. The result is wake‐up‐free performance with films exposed to ALA.
Nicolas K. Lam +18 more
wiley +1 more source
logbin: An R Package for Relative Risk Regression Using the Log-Binomial Model
Relative risk regression using a log-link binomial generalized linear model (GLM) is an important tool for the analysis of binary outcomes. However, Fisher scoring, which is the standard method for fitting GLMs in statistical software, may have ...
Mark W. Donoghoe, Ian C. Marschner
doaj +1 more source

