Results 31 to 40 of about 177 (131)
ABSTRACT This study develops a novel multivariate stochastic framework for assessing systemic risks, such as climate and nature‐related shocks, within production or financial networks. By embedding a linear stochastic fluid network, interpretable as a generalized vector Ornstein–Uhlenbeck process, into the production network of interdependent ...
Giovanni Amici +3 more
wiley +1 more source
Abstract We propose the novel p‐branch‐and‐bound method for solving two‐stage stochastic programming problems whose deterministic equivalents are represented by non‐convex mixed‐integer quadratically constrained quadratic programming (MIQCQP) models. The precision of the solution generated by the p‐branch‐and‐bound method can be arbitrarily adjusted by
Nikita Belyak, Fabricio Oliveira
wiley +1 more source
Invariant Measure and Universality of the 2D Yang–Mills Langevin Dynamic
ABSTRACT We prove that the Yang–Mills (YM) measure for the trivial principal bundle over the two‐dimensional torus, with any connected, compact structure group, is invariant for the associated renormalised Langevin dynamic. Our argument relies on a combination of regularity structures, lattice gauge‐fixing and Bourgain's method for invariant measures ...
Ilya Chevyrev, Hao Shen
wiley +1 more source
Nonstationary Spatial Correlation of Earthquake Ground Motions in California
Assessing seismic risk to spatially distributed infrastructure systems requires realistic representations of spatially correlated ground motions. Existing models for the spatial correlations of ground motions rely on strong second‐order stationarity assumptions, under which the correlation structure is assumed to be invariant across space, potentially ...
Pengfei Wang +4 more
wiley +1 more source
Optimal model‐based design of experiments for parameter precision: Supercritical extraction case
Abstract This study investigates the process of chamomile oil extraction from flowers. A parameter‐distributed model consisting of a set of partial differential equations is used to describe the governing mass transfer phenomena in a cylindrical packed bed with solid chamomile particles under supercritical conditions using carbon dioxide as a solvent ...
Oliwer Sliczniuk, Pekka Oinas
wiley +1 more source
Time Distributed Classification of Alzheimer's Disease on MRI Scans
Longitudinal MRI‐derived cortical thickness slopes improved AD/CN discrimination. A time‐distributed 3D ResNet‐101 + LSTM further captured spatiotemporal progression, reaching 96.7% accuracy and also improving MCI‐related classification. ABSTRACT The diagnosis of Alzheimer's disease (AD) has progressively depended on sophisticated neuroimaging methods ...
Mehmet Sait Dundar, Bulent Yilmaz
wiley +1 more source
Econometrics at the Extreme: From Quantile Regression to QFAVAR1
ABSTRACT This paper surveys quantile modelling from its theoretical origins to current advances. We organize the literature and present core econometric formulations and estimation methods for: (i) cross‐sectional quantile regression; (ii) quantile time series models and their time series properties; (iii) quantile vector autoregressions for ...
Stéphane Goutte +4 more
wiley +1 more source
A real‐time, data‐driven framework detects and classifies photovoltaic array faults using edge sensing and server‐side machine learning. Ensemble tree models achieve near‐perfect accuracy with low latency, enabling practical, low‐cost deployment for reliable PV monitoring and intelligent maintenance.
Premkumar Manoharan +4 more
wiley +1 more source
Modeling the Intermediate Flow Regime in Flow‐Compensated Intravoxel Incoherent Motion MRI
ABSTRACT Purpose The intravoxel incoherent motion (IVIM) model is commonly used to separate the effects of motion related to diffusion and blood microcirculation (perfusion) on the MR signal. Depending on the encoding time (T), it is possible to probe the different temporal regimes of blood motion, which resemble a ballistic flow at short T and a ...
Louise Rosenqvist +5 more
wiley +1 more source
ABSTRACT Purpose Diffusion MRI probes tissue microstructure, but low SNR and limited resolution hinder detection of features and parameter estimates. We introduce slice excitation with random overlap (SERO), which enables variable repetition times (TRs) and diffusion weighting within a single shot.
Felix Mortensen +7 more
wiley +1 more source

