Results 111 to 120 of about 45,190 (303)
Boundary oscillations and nonlinear boundary conditions
We study how oscillations in the boundary of a domain affect the behavior of solutions of elliptic equations with nonlinear boundary conditions of the type ∂u∂n+g(x,u)=0. We show that there exists a function γ defined on the boundary, that depends on the oscillations at the boundary, such that, if γ is a bounded function, then, for all nonlinearities g,
Arrieta, Jose M., Bruschi, Simone M.
openaire +3 more sources
Mechanistic Learning for Predicting Survival Outcomes in Head and Neck Squamous Cell Carcinoma
ABSTRACT We employed a mechanistic learning approach, integrating on‐treatment tumor kinetics (TK) modeling with various machine learning (ML) models to address the challenge of predicting post‐progression survival (PPS)—the duration from the time of documented disease progression to death—and overall survival (OS) in Head and Neck Squamous Cell ...
Kevin Atsou +4 more
wiley +1 more source
Finding Evidence for Massive Neutrinos using 3D Weak Lensing
In this paper we investigate the potential of 3D cosmic shear to constrain massive neutrino parameters. We find that if the total mass is substantial (near the upper limits from LSS, but setting aside the Ly alpha limit for now), then 3D cosmic shear ...
A. Cooray +12 more
core +1 more source
Fuzzy postprocessing of seasonal climate forecasts for semiarid river basins
Meteorological forecasts from AI‐based fuzzy rule‐based system (FRB) are compared to linear scaling (LS) and quantile mapping (QM). Seasonal forecasts from the Copernicus Climate Change Service (C3S) are considered. Results show that the highest skill is achieved for the FRB approach.
Dariana Isamel Avila‐Velasquez +2 more
wiley +1 more source
Ensemble Kalman filter in latent space using a variational autoencoder pair
The use of the ensemble Kalman filter (EnKF) in strongly nonlinear or constrained atmospheric, oceanographic, or sea‐ice models can be challenging. Applying the EnKF in the latent space of a variational autoencoder (VAE) ensures that the ensemble members satisfy the balances and constraints present in the model.
Ivo Pasmans +4 more
wiley +1 more source
The precise temporal coordination of neural activity is crucial for brain function. In the hippocampus, this precision is reflected in the oscillatory rhythms observed in CA1. While it is known that a balance between excitatory and inhibitory activity is
Chinnakkaruppan Adaikkan +9 more
doaj +1 more source
Emerging evidence challenges the direct causal relationship between amyloid-β (Aβ) deposition and cognitive decline in Alzheimer's disease (AD), as exemplified in presenilin-1 and presenilin-2 conditional double knockout (cDKO) mice which exhibit no ...
Jinnan Chen +6 more
doaj +1 more source
Entanglement production by quantum error correction in the presence of correlated environment
We analyze the effect of a quantum error correcting code on the entanglement of encoded logical qubits in the presence of a dephasing interaction with a correlated environment. Such correlated reservoir introduces entanglement between physical qubits. We
Averin D. V. +7 more
core +1 more source
Forecast verification using information and noise
Verification of weather forecasts is usually expressed in terms of total error metrics. This is useful for end users of the forecasts but does not allow evaluation of the intrinsic information content of the forecasts. To overcome this limitation, we propose a new total error decomposition into information and noise error measures, connect it to ...
Massimo Bonavita, Alan J. Geer
wiley +1 more source
We quantified the causal effect (CE) of linkages between four monthly climate indices ENSO, SMHP, RWC, and MHC for 1940–2022 with a time lag of one month. The results show CE values from (1) ENSO to SMHP of −0.33$$ -0.33 $$ to −0.44$$ -0.44 $$ (i.e., a one standard deviation (SD) increase in ENSO causes a decrease in SMHP of −0.33$$ -0.33 $$ to −0.44$$
Grzegorz Muszynski +5 more
wiley +1 more source

