Results 121 to 130 of about 5,298,464 (247)
microRNA‐7‐5p and α‐Synuclein SAA Predict Parkinson's Disease Phenoconversion
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objective Corroborate blood neuron‐derived extracellular vesicle (NDEV) alpha‐synuclein (αSyn), the CSF αSyn seed amplification assay (αSyn‐SAA), and blood microRNA‐7‐5p (miR‐7‐5p) as markers for Parkinson's disease (PD) phenoconversion and determine if combining these markers would help select subjects who would be more likely to phenoconvert.
Shayan Zadegan +4 more
wiley +1 more source
A Q‐Learning Algorithm to Solve the Two‐Player Zero‐Sum Game Problem for Nonlinear Systems
International Journal of Adaptive Control and Signal Processing, Volume 39, Issue 3, Page 566-581, March 2025.A Q‐learning algorithm to solve the two‐player zero‐sum game problem for nonlinear systems. ABSTRACT This paper deals with the two‐player zero‐sum game problem, which is a bounded L2$$ {L}_2 $$‐gain robust control problem. Finding an analytical solution to the complex Hamilton‐Jacobi‐Issacs (HJI) equation is a challenging task.
Afreen Islam +2 more
wiley +1 more source
, 1968 A design review presentation given by Time Zero on ALSEP / SIDE / CCGE prepared for Rice University Houston, TexasPrime Contract NAS 9-5911 Contract No.
Time-Zero Corporation
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Circulating Current Suppression Control Method for Distributed Grid-Connected Converter
Kongzhi Yu Xinxi JishuDistributed three-level converters operate in a grid-connected state through an input-parallel output-parallel (IPOP) mode. These converters offer advantages such as high efficiency, high flexibility, and low cost, making them widely applicable in new ...
HU Liang +5 more
doaj
dynoGP: Deep Gaussian Processes for Dynamic System Identification
International Journal of Adaptive Control and Signal Processing, EarlyView.This work introduces a novel class of deep models for system identification, dynamical deep Gaussian processes, which combine the strengths of data‐driven methods, such as those based on neural network architectures, with the ability to output a probability distribution for uncertainty representation.
Alessio Benavoli +3 more
wiley +1 more source
Case study: turning dough into savings
, 2014 Case study produced by Zero Waste Scotland, featuring Strathmore Foods Ltd. The company produces a wide range of pies and ready meals and this case study discusses the culture of waste management at the company and the benefits and cost savings that this
Zero Waste Scotland
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What Do Large Language Models Know About Materials?
Advanced Engineering Materials, EarlyView.If large language models (LLMs) are to be used inside the material discovery and engineering process, they must be benchmarked for the accurateness of intrinsic material knowledge. The current work introduces 1) a reasoning process through the processing–structure–property–performance chain and 2) a tool for benchmarking knowledge of LLMs concerning ...
Adrian Ehrenhofer +2 more
wiley +1 more source
Advanced Engineering Materials, EarlyView.A numerical–experimental framework is developed for characterizing multi‐matrix fiber‐reinforced polymers (MM‐FRPs) combining epoxy and polyurethane matrices. Harmonic bending tests are integrated with finite element model updating (FEMU) to simultaneously identify elastic and viscoelastic material parameters.
Rodrigo M. Dartora +4 more
wiley +1 more source
This paper develops and analyzes an online methodology to detect demagnetization faults in surface-mounted permanent magnet synchronous motors. The proposed methodology, which takes into account the effect of the inverter that feeds the machine, is based
Romeral Martínez, José Luis +3 more
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Advanced Engineering Materials, EarlyView.Building machine‐readable vocabularies for materials science is slow, expert‐driven work. This study benchmarks 13 large language models on two of its first steps: finding candidate terms in engineering articles and deciding where they belong in a class hierarchy.
Thomas Bjarsch +3 more
wiley +1 more source