Results 91 to 100 of about 155,289 (268)
ABSTRACT Advancing artificial intelligence (AI) has transformed learning and work, yet higher education and professional development programs have not systematically equipped learners for AI‐prevalent environments. This lack of preparation creates uncertainty regarding control, responsibility, trust, and accountability.
Moon‐Heum Cho, Jerusalem Merkebu
wiley +1 more source
Interpretable Physics-Informed Machine Learning for Pyrolysis
Accurate prediction of biomass pyrolysis products remains challenging due to the inherent complexity of thermochemical kinetics and the lack of mechanistic interpretability in modern Machine Learning (ML) models.
Diego Racero Galaraga +1 more
doaj +1 more source
ABSTRACT Background Cognitive impairment is a common non‐motor symptom in Multiple Sclerosis (MS), negatively affecting autonomy and Quality of Life (QoL). Innovative rehabilitation strategies, such as semi‐immersive virtual reality (VR) and computerized cognitive training (CCT), may offer advantages over traditional cognitive rehabilitation (TCR ...
Maria Grazia Maggio +8 more
wiley +1 more source
A Hybrid Physics-Augmented Neural Network for Dynamic System Modeling with Partially Known Dynamics
This paper introduces Hybrid Physics-Augmented Neural Network (HyPA-Net), a hybrid modeling framework that integrates physics-based linear time-invariant models with artificial neural networks (ANNs) to address dynamic system modeling when only partial ...
Laurin Ludmann +4 more
doaj +1 more source
Bi‐ and Mono‐Allelic RFC1 Expansion in a North American Cohort With Idiopathic Axonal Neuropathy
ABSTRACT Objective RFC1 biallelic repeat expansion is increasingly recognized as a cause of chronic idiopathic axonal polyneuropathy (CIAP), but it remains challenging to know who to test. This study aims to determine the prevalence of biallelic and monoallelic RFC1 expansions and their corresponding neuropathy phenotypes in CIAP patients and identify ...
Amro M. Stino +25 more
wiley +1 more source
The use of post-consumer scrap (PCS) in aluminium structural components is a challenging but important strategy for reducing carbon footprint in the automotive industry.
Christian Dalheim Øien
doaj +1 more source
Deep Learning Pose Estimation for Phenotyping of Co‐Occurring Hyperkinetic Movement Disorders
ABSTRACT Objective To explore whether routine outpatient video combined with deep learning‐based pose estimation and clinically interpretable kinematic features can support multi‐label phenotyping of co‐occurring hyperkinetic movement disorders (HMDs).
Laura Cif +17 more
wiley +1 more source
Reliable estimation of battery state of charge (SOC) and state of energy (SOE) under real world dynamic driving conditions is essential for battery management systems.
Sushil Krishnan, Yokesh Babu Sundaresan
doaj +1 more source
Complementary Modeling of Hybrid Systems
A complementarity framework is described for the modeling of certain classes of mixed continuous/discrete dynamical systems. The use of such a framework is well-known for mechanical systems with inequality constraints, but we give a more general formulation which applies for instance also to systems with relays in a feedback loop.
van der Schaft, Abraham Jan +1 more
openaire +3 more sources
ABSTRACT Objective Neuromyelitis optica spectrum disorder (NMOSD) is a devastating neurological disease that lacks serological biomarkers that can accurately reflect disease activity. We established a live cell‐based assay (LCBA) using serum with endogenous complement to quantify the overall cytotoxicity, offering a novel functional tool for monitoring
Xiaona Xu +10 more
wiley +1 more source

