Results 121 to 130 of about 10,380,352 (315)
Clustering Algorithm Reveals Dopamine‐Motor Mismatch in Cognitively Preserved Parkinson's Disease
ABSTRACT Objective To explore the relationship between dopaminergic denervation and motor impairment in two de novo Parkinson's disease (PD) cohorts. Methods n = 249 PD patients from Parkinson's Progression Markers Initiative (PPMI) and n = 84 from an external clinical cohort.
Rachele Malito +14 more
wiley +1 more source
Mutual Alignment Transfer Learning
Training robots for operation in the real world is a complex, time consuming and potentially expensive task. Despite significant success of reinforcement learning in games and simulations, research in real robot applications has not been able to match similar progress.
Wulfmeier, M, Posner, H, Abbeel, P
openaire +3 more sources
Value of MRI Outcomes for Preventive and Early‐Stage Trials in Spinocerebellar Ataxias 1 and 3
ABSTRACT Objective To examine the value of MRI outcomes as endpoints for preventive and early‐stage trials of two polyglutamine spinocerebellar ataxias (SCAs). Methods A cohort of 100 participants (23 SCA1, 63 SCA3, median Scale for the Assessment and Rating of Ataxia (SARA) score = 5, 42% preataxic, and 14 gene‐negative controls) was scanned at 3T up ...
Thiago J. R. Rezende +26 more
wiley +1 more source
Functional and Structural Evidence of Neurofluid Circuit Aberrations in Huntington Disease
ABSTRACT Objective Disrupted neurofluid regulation may contribute to neurodegeneration in Huntington disease (HD). Because neurofluid pathways influence waste clearance, inflammation, and the distribution of central nervous system (CNS)–delivered therapeutics, understanding their dysfunction is increasingly important as targeted treatments emerge.
Kilian Hett +8 more
wiley +1 more source
Objective Australian evidence on lived and care experiences of chronic musculoskeletal shoulder pain (CMSP), irrespective of disorder classification or disease, is limited. However, such evidence is important for person‐centered care and informing local service pathways and care guidelines or standards.
Sonia Ranelli +8 more
wiley +1 more source
Domain Transfer Multiple Kernel Learning
Cross-domain learning methods have shown promising results by leveraging labeled patterns from the auxiliary domain to learn a robust classifier for the target domain which has only a limited number of labeled samples. To cope with the considerable change between feature distributions of different domains, we propose a new cross-domain kernel learning ...
Duan, Lixin +2 more
openaire +3 more sources
This paper proposes two projector‐based Hopfield neural network (HNN) estimators for online, constrained parameter estimation under time‐varying data, additive disturbances, and slowly drifting physical parameters. The first is a constraint‐aware HNN that enforces linear equalities and inequalities (via slack neurons) and continuously tracks the ...
Miguel Pedro Silva
wiley +1 more source
This work introduces an adaptive human pilot model that captures pilot time‐delay effects in adaptive control systems. The model enables the prediction of pilot–controller interactions, facilitating safer integration and improved design of adaptive controllers for piloted applications.
Abdullah Habboush, Yildiray Yildiz
wiley +1 more source
Predicting extreme defects in additive manufacturing remains a key challenge limiting its structural reliability. This study proposes a statistical framework that integrates Extreme Value Theory with advanced process indicators to explore defect–process relationships and improve the estimation of critical defect sizes. The approach provides a basis for
Muhammad Muteeb Butt +8 more
wiley +1 more source
Corporations are increasingly looking beyond inter-company collaborations to multidimensional collaborative activities between departments and organizational members within the company to strengthen innovative market competitiveness.
Sunghee Lee, Boyoung Kim
doaj +1 more source

