Results 201 to 210 of about 197,057 (337)

Medullary radius as a major contributor to variance in the proximal femur: Insights from statistical shape modeling

open access: yesJournal of Anatomy, EarlyView.
Workflow from CT to PCA‐based shape modeling of the proximal femoral canal (n = 763). Feature maps (size, roundness, torsion, flare, curvature) reveal sex‐ and age‐dependent patterns; three PCs capture ≈68% of variance and summarize dominant anatomical changes. Insights inform implant sizing and design envelopes in cementless THA.
Stefan Bracher   +3 more
wiley   +1 more source

Industry Exposure to Artificial Intelligence, Board Network Heterogeneity, and Firm Idiosyncratic Risk

open access: yesJournal of Management Studies, EarlyView.
Abstract Despite the growing impact of artificial intelligence (AI) in business, there is little research examining its effects on firm idiosyncratic risk (IR). This is an important issue for boards: as key conduits of firm–environment information flows via board interlock networks, traditional risk oversight functions are being increasingly augmented ...
Kerry Hudson, Robert E. Morgan
wiley   +1 more source

On the Disentanglement of an Economic Union

open access: yesJournal of Regional Science, EarlyView.
ABSTRACT We study how the unilateral withdrawal of a region from an economic union affects the spatial distribution of economic activity and social welfare. We explore a three‐region economic geography model under the assumption that this withdrawal can be expressed as a higher transportation cost between the leaving party and the remaining union ...
Jorge Saraiva   +2 more
wiley   +1 more source

Markov Determinantal Point Process for Dynamic Random Sets

open access: yesJournal of Time Series Analysis, EarlyView.
ABSTRACT The Law of Determinantal Point Process (LDPP) is a flexible parametric family of distributions over random sets defined on a finite state space, or equivalently over multivariate binary variables. The aim of this paper is to introduce Markov processes of random sets within the LDPP framework. We show that, when the pairwise distribution of two
Christian Gouriéroux, Yang Lu
wiley   +1 more source

Moving Sum Procedure for Multiple Change Point Detection in Large Factor Models

open access: yesJournal of Time Series Analysis, EarlyView.
ABSTRACT This paper proposes a moving sum methodology for detecting multiple change points in high‐dimensional time series under a factor model, where changes are attributed to those in loadings as well as emergence or disappearance of factors. We establish the asymptotic null distribution of the proposed test for family‐wise error control and show the
Matteo Barigozzi   +2 more
wiley   +1 more source

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