Results 161 to 170 of about 2,240,617 (314)

Glymphatic dysfunction couples with cortical excitation–inhibition imbalance in epilepsy: Evidence from Rasmussen encephalitis

open access: yesEpilepsia, EarlyView.
Cong Fu et al. demonstrate that glymphatic system dysfunction is linked to enhanced inhibitory cortical activity using diffusion MRI and EEG. These findings highlight a mechanistic link between perivascular fluid dynamics and neuronal activity, suggesting a role for glymphatic function in maintaining cortical stability in epilepsy.
Cong Fu   +11 more
wiley   +1 more source

A Multivariate Mixed‐Effects Regression Framework for Ground Motion Modeling: Integrating Parametric and Machine Learning Approaches

open access: yesEarthquake Engineering &Structural Dynamics, EarlyView.
ABSTRACT Multivariate ground motion models (GMMs) that capture the correlation between different intensity measures (IMs) are essential for seismic risk assessment. Conventional GMMs are often developed using a two‐stage approach, where separate univariate models with predefined functional forms are fitted first, and correlation is addressed in a ...
Sayed Mohammad Sajad Hussaini   +2 more
wiley   +1 more source

Most totally real fields do not have universal forms or the Northcott property. [PDF]

open access: yesProc Natl Acad Sci U S A
Daans N   +4 more
europepmc   +1 more source

An Efficient Quasi‐Static Condensation‐Based Framework for Seismic Analysis of Multi‐Supported Secondary Structures

open access: yesEarthquake Engineering &Structural Dynamics, EarlyView.
ABSTRACT Multi‐supported non‐structural components (NSCs) are prone to seismic damage, yet their response prediction remains challenging when support motions are spatially incoherent. This study proposes an enhanced quasi‐static condensation (EQSC) method for linear, lightweight, dynamically detuned multi‐supported NSCs under the neglect of primary ...
Duozhi Wang   +5 more
wiley   +1 more source

Coherent Forecasting of Realized Volatility

open access: yesJournal of Forecasting, EarlyView.
ABSTRACT The QLIKE loss function is the stylized favorite of the literature on volatility forecasting when it comes to out‐of‐sample evaluation and the state of the art model for realized volatility (RV) forecasting is the HAR model, which minimizes the squared error loss for in‐sample estimation of the parameters.
Marius Puke, Karsten Schweikert
wiley   +1 more source

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