Results 61 to 70 of about 2,175,773 (278)

Corporate Dynamic Eco‐Innovation Capability and Carbon Emission Reduction: Evidence From African Listed Firms With the Role of Institutional Pressures

open access: yesBusiness Strategy and the Environment, EarlyView.
ABSTRACT Despite the global emphasis on simultaneous achievement of higher growth and lower pollution (green growth), the dynamic link between eco‐innovation and CO2 emissions remains inadequately understood globally and specifically in Africa, with a complex and diverse institutional and regulatory landscape.
Idorenyin J. Okon   +2 more
wiley   +1 more source

Almost everywhere continuity of conditional expectations

open access: yesModern Stochastics: Theory and Applications
A necessary and sufficient condition on a sequence ${\{{\mathcal{A}_{n}}\}_{n\in \mathbb{N}}}$ of σ-subalgebras which assures convergence almost everywhere of conditional expectations for functions in ${L^{\infty }}$ is given. It is proven that for $f\in
Alberto Alonso, Fernando Brambila-Paz
doaj   +1 more source

Rewiring the Circular Economy Through AI‐Informed Pathways: Structural and Distributional Drivers of Environmental Outcomes in the European Union

open access: yesBusiness Strategy and the Environment, EarlyView.
ABSTRACT This study investigates the structural and distributional factors that influence environmental performance in 27 European Union (EU) countries from 2010 to 2021, focusing especially on circular economy (CE) measures and the increasing use of artificial intelligence (AI)‐based analytical tools.
Cosimo Magazzino   +3 more
wiley   +1 more source

Nonsmooth spectral gradient methods for unconstrained optimization

open access: yesEURO Journal on Computational Optimization, 2017
To solve nonsmooth unconstrained minimization problems, we combine the spectral choice of step length with two well-established subdifferential-type schemes: the gradient sampling method and the simplex gradient method.
Milagros Loreto   +3 more
doaj   +1 more source

Almost everywhere convergence of series

open access: yesMathematische Annalen, 1988
Let (X,\(\beta\),m) be a probability space and let \(T: L_ 2(X)\to L_ 2(X)\) be a contraction. The series \(\sum ^{\infty}_{n=1}c_ nT^ n\) converges in norm if \(\sum ^{\infty}_{n=1}c_ n\exp (2\pi inx)\) converges uniformly. But also there are many examples of \((c_ n)\) for which \(\sum ^{\infty}_{n=1}| c_ n| =\infty\) and yet the series \(\sum ...
openaire   +2 more sources

An almost sure conditional convergence result and an application to a generalized Polya urn [PDF]

open access: yes, 2009
We prove an almost sure conditional convergence result toward a Gaussian kernel and we apply it to a two-colors randomly reinforced ...
Crimaldi, I, Crimaldi, Irene
core   +1 more source

Comparison of modelling approaches for liquid fluidized beds

open access: yesThe Canadian Journal of Chemical Engineering, EarlyView.
Abstract This study presents a comparison of three promising numerical models for the detailed simulation of liquid–solid fluidized bed. These models differ in their treatment of the solid phase, ranging from treating each particle individually to treating the collection of particles as a continuum.
Andreu Bernad‐Serra   +3 more
wiley   +1 more source

Bayesian inverse ensemble forecasting for COVID‐19

open access: yesCanadian 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

Front Propagation Through a Perforated Wall

open access: yesCommunications on Pure and Applied Mathematics, EarlyView.
ABSTRACT We consider a bistable reaction– diffusion equation ut=Δu+f(u)$u_t=\Delta u +f(u)$ on RN${\mathbb {R}}^N$ in the presence of an obstacle K$K$, which is a wall of infinite span with many holes. More precisely, K$K$ is a closed subset of RN${\mathbb {R}}^N$ with smooth boundary such that its projection onto the x1$x_1$‐axis is bounded and that ...
Henri Berestycki   +2 more
wiley   +1 more source

Constraint Unlearnability in Overparameterized Neural Networks

open access: yesMathematics
We study whether overparameterized neural networks can learn to satisfy pointwise constraints without inductive bias. One might expect that a sufficiently expressive network would learn to respect such constraints. We prove that this is not the case. For
Hongyu Qi, Zhen Tan
doaj   +1 more source

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