Results 191 to 200 of about 114,074 (272)
Estimation of white matter fiber parameters from compressed multiresolution diffusion MRI using sparse Bayesian learning. [PDF]
Neuroimage, 2018 Pisharady PK +4 more
europepmc +1 more source
Oikos, EarlyView.Misinterpretation of p‐values, coupled with insufficient consideration of the prior plausibility of ecological hypotheses, leads to overconfident and often unreliable inference in ecological research. To address this issue, we present a methodological framework for p‐value calibration that reinterprets conventional p‐values through minimum Bayes ...
Rafael Dettogni Guariento +2 more
wiley +1 more source
A Sparse Bayesian Learning Algorithm for White Matter Parameter Estimation from Compressed Multi-shell Diffusion MRI. [PDF]
Med Image Comput Comput Assist Interv, 2017 Pisharady PK +3 more
europepmc +1 more source
CPT: Pharmacometrics &Systems Pharmacology, Volume 14, Issue 3, Page 435-447, March 2025.Abstract Intranasal diamorphine (IND), approved for managing breakthrough pain in the UK, has been identified as an acceptable alternative offering effective, expedient, and less traumatic analgesia for children. However, the current dose regimen in pediatric populations relies on clinical expertise while the pharmacokinetics properties are poorly ...
Lianjin Cai +6 more
wiley +1 more source
A Fast and Robust Non-Sparse Signal Recovery Algorithm for Wearable ECG Telemonitoring Using ADMM-Based Block Sparse Bayesian Learning. [PDF]
Sensors (Basel), 2018 Cheng Y +5 more
europepmc +1 more source
COBASE: A new copula‐based shuffling method for ensemble weather forecast postprocessing
Quarterly Journal of the Royal Meteorological Society, EarlyView.We propose COBASE, a novel copula‐based postprocessing methododology that combines the strengths of multivariate parametric correction with non‐parametric rank‐based approaches. We consider two case studies for multi‐site temperature in Austria and multi‐site temperature and dew‐point temperature in the Netherlands.
Maurits Flos +4 more
wiley +1 more source
Physics‐Informed Neural Networks for Battery Degradation Prediction Under Random Walk Operations
Quality and Reliability Engineering International, EarlyView.ABSTRACT This study addresses the challenge of predicting the state of health (SoH) and capacity degradation in Battery Energy Storage Systems (BESS) under highly variable conditions induced by frequent control adjustments. In environments where random walk behavior prevails due to stochastic control commands, conventional estimation methods often ...
Alaa Selim +3 more
wiley +1 more source
Phase I Multivariate Coefficient of Variation Control Charts for High‐Dimensional Processes
Quality and Reliability Engineering International, EarlyView.ABSTRACT Multivariate control charts have traditionally focused on monitoring the process mean vector and/or covariance matrix. Recent studies have extended this framework to Phase II monitoring of the multivariate coefficient of variation (MCV); yet very limited work has examined MCV‐based monitoring in Phase I.
O. A. Oyegoke +2 more
wiley +1 more source
Responsive Materials, EarlyView.Machine learning provides a unifying framework to connect structure, fluorescence properties, and applications of carbon‐based quantum dots. This review highlights how data‐driven strategies enable fluorescence regulation, reveal underlying mechanisms, and accelerate the rational design of functional carbon dots.
Liangfeng Chen +8 more
wiley +1 more source
Modelling forest dynamics using integral projection models and repeat lidar
Remote Sensing in Ecology and Conservation, EarlyView.Forests are facing increasing pressure from climate change and disturbance, yet linking individual tree trajectories to whole‐forest outcomes remains a major challenge. Our study integrates repeat airborne lidar with an Integral Projection Model to analyse demographic processes at the landscape scale.
Alice Rosen +9 more
wiley +1 more source