Results 111 to 120 of about 531,551 (278)
CSF Monoamine Metabolites and Cognitive Trajectory in Early Parkinson's Disease
ABSTRACT Background Imaging and postmortem studies indicate that abnormalities in monoaminergic neurotransmission contribute to cognitive impairment in Parkinson's disease (PD). However, it remains uncertain if cerebrospinal fluid (CSF) monoamine metabolites can serve as biomarkers of cognitive decline in early PD.
Jing‐Yu Shao +7 more
wiley +1 more source
MatchIt: Nonparametric Preprocessing for Parametric Causal Inference [PDF]
MatchIt implements the suggestions of Ho, Imai, King, and Stuart (2007) for improving parametric statistical models by preprocessing data with nonparametric matching methods.
Daniel Ho +3 more
core +1 more source
ABSTRACT Objective Considerable efforts have been dedicated to developing effective treatments for post‐stroke executive impairment (PSEI), among which repetitive transcranial magnetic stimulation (rTMS) has shown great potential. This study aimed to investigate the therapeutic effects of high‐frequency rTMS on working memory (WM) and response ...
Mengting Lao +6 more
wiley +1 more source
A Workflow to Accelerate Microstructure‐Sensitive Fatigue Life Predictions
This study introduces a workflow to accelerate predictions of microstructure‐sensitive fatigue life. Results from frameworks with varying levels of simplification are benchmarked against published reference results. The analysis reveals a trade‐off between accuracy and model complexity, offering researchers a practical guide for selecting the optimal ...
Luca Loiodice +2 more
wiley +1 more source
User microprogrammable processors for high data rate telemetry preprocessing [PDF]
The use of microprogrammable processors for the preprocessing of high data rate satellite telemetry is investigated. The following topics are discussed along with supporting studies: (1) evaluation of commercial microprogrammable minicomputers for ...
Ogrady, E. P., Pugsley, J. H.
core +1 more source
Numerical Exploration of Thermal Shock Resistance in MgO–C Refractories
A mesostructure‐resolved numerical framework is developed to evaluate the thermal shock resistance of MgO–C refractories. By modeling interface debonding under rapid temperature changes and introducing a modified thermal shock parameter that accounts for mesocracks, the study shows how graphite content and aggregate size influence thermal shock ...
Jishnu Vinayak Gopi +3 more
wiley +1 more source
Unleashing the Power of Machine Learning in Nanomedicine Formulation Development
A random forest machine learning model is able to make predictions on nanoparticle attributes of different nanomedicines (i.e. lipid nanoparticles, liposomes, or PLGA nanoparticles) based on microfluidic formulation parameters. Machine learning models are based on a database of nanoparticle formulations, and models are able to generate unique solutions
Thomas L. Moore +7 more
wiley +1 more source
Monitoring moving bio-objects is currently of great interest for both fundamental and practical research. The advent of deep-learning algorithms has made it possible to automate the qualitative and quantitative analysis of the behavior of bio-objects ...
Marina Barulina +5 more
doaj +1 more source
OPTIMIZING DATA PREPROCESSING: THE DATA PREPROCESSING INTERFACE
openaire +1 more source
Trap‐Assisted Transport and Neuromorphic Plasticity in Lead‐Free 2D Perovskites PEA2SnI4
An artificial retina built from lead‐free layered perovskite (PEA)2SnI4 converts light input into a persistent photocurrent and sums successive flashes over time. Micro/nanocrystals integrated on electrodes act as synapse‐like pixels that perform temporal integration directly in hardware. This in‐sensor preprocessing merges detection and computation on
Ofelia Durante +17 more
wiley +1 more source

