Results 131 to 140 of about 5,219 (266)

The Future of Foundation Machine Learning Potentials and DFT in Homogeneous Catalysis: Competition or Synergy?

Chemistry – A European Journal, EarlyView.
Machine‐learning potentials are increasingly taking on the exploratory tasks of homogeneous catalysis, enabling rapid conformer sampling and reaction‐space mapping. However, when selectivity depends on subtle electronic effects, electronic‐structure methods remain essential.
Maxime Ferrer, Julen Munarriz, Thijs Stuyver, Ruben Laplaza   +3 more
wiley   +1 more source

Asymptotic expansion of regular and connected regular graphs

We derive the asymptotic expansion (asymptotics with an arbitrary number of error terms) of k-regular graphs by applying the Laplace method on a recent exact formula from Caizergues and de Panafieu (2023). We also deduce the asymptotic expansion of connected k-regular graphs using standard techniques for divergent series developed by Wright (1970) and ...
openaire   +2 more sources

Economic and environmental implications of the development of UASB reactors in Mexico for sustainable industrial wastewater treatment

The Canadian Journal of Chemical Engineering, EarlyView.
Abstract The objective of this work is to demonstrate that the inclusion of an up‐flow anaerobic sludge bed (UASB reactor) within an industrial wastewater treatment plant reduces the plant's investment and operating costs compared to a system based solely on conventional complete‐mix activated sludge (CMAS), operating under the same design principles ...
Juan Manuel Morgan‐Sagastume, Adalberto Noyola   +1 more
wiley   +1 more source

Asymptotic properties of cross‐classified sampling designs

Canadian Journal of Statistics, EarlyView.
Abstract We investigate the family of cross‐classified sampling designs across an arbitrary number of dimensions. We introduce a variance decomposition that enables the derivation of general asymptotic properties for these designs and the development of straightforward and asymptotically unbiased variance estimators.
Jean Rubin, Guillaume Chauvet
wiley   +1 more source

Bayesian inverse ensemble forecasting for COVID‐19

Canadian Journal of Statistics, EarlyView.
Abstract Variations in strains of COVID‐19 have a significant impact on the rate of surges and on the accuracy of forecasts of the epidemic dynamics. The primary goal for this article is to quantify the effects of varying strains of COVID‐19 on ensemble forecasts of individual “surges.” By modelling the disease dynamics with an SIR model, we solve the ...
Kimberly Kroetch, Don Estep
wiley   +1 more source

Jackknife bias‐corrected variance estimation for the generalized regression estimator

Canadian Journal of Statistics, EarlyView.
Abstract Commonly used variance estimators for the generalized regression estimator (GREG) are based on Taylor linearization and jackknife. Traditionally, a jackknife GREG variance estimator is obtained by jackknifing GREG, which consists of computing GREG from each of several subsamples of the parent sample, and estimating the variance of the parent ...
Marius Stefan, J.N.K Rao
wiley   +1 more source

On the Krasnoselskii-type fixed point theorems for the sum of continuous and asymptotically nonexpansive mappings in Banach spaces

Journal of Inequalities and Applications, 2011
In this article, we prove some results concerning the Krasnoselskii theorem on fixed points for the sum A + B of a weakly-strongly continuous mapping and an asymptotically nonexpansive mapping in Banach spaces.
Arunchai Areerat, Plubtieng Somyot
doaj  

A partial envelope approach for modelling multivariate spatial‐temporal data

Canadian Journal of Statistics, EarlyView.
Abstract In the new era of big data, modelling multivariate spatial‐temporal data is a challenging task due to both the high dimensionality of the features and complex associations among the responses across different locations and time points.
Reisa Widjaja, Wenbo Wu, Victor De Oliveira, Keying Ye   +3 more
wiley   +1 more source

Null Geodesic Congruences, Asymptotically-Flat Spacetimes and Their Physical Interpretation

Living Reviews in Relativity, 2012
A priori, there is nothing very special about shear-free or asymptotically shear-free null geodesic congruences. Surprisingly, however, they turn out to possess a large number of fascinating geometric properties and to be closely related, in the context ...
Timothy M. Adamo, Ezra T. Newman, Carlos Kozameh   +2 more
doaj  

Nonlinear permuted Granger causality

Canadian Journal of Statistics, EarlyView.
Abstract Granger causality is an established, contentious method that seeks causal temporal connections via association and precedence. While not true causal inference, it assists in mapping networks of information flow that may warrant further study.
Noah D. Gade, Jordan Rodu
wiley   +1 more source