Results 81 to 90 of about 685,298 (326)

Amygdala Neurodegeneration: A Key Driver of Visual Dysfunction in Parkinson's Disease

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Visual disability in Parkinson's disease (PD) is not fully explained by retinal neurodegeneration. We aimed to delineate the brain substrate of visual dysfunction in PD and its association with retinal thickness. Methods Forty‐two PD patients and 29 controls underwent 3‐Tesla MRI, retinal spectral‐domain optical coherence tomography,
Asier Erramuzpe, Ane Murueta‐Goyena, Antonio Jimenez‐Marin, Marian Acera, Sara Teijeira‐Portas, Rocío Del Pino, Tamara Fernández‐Valle, Ibai Diez, Unai Sainz‐Lugarezaresti, Naroa Ibarretxe‐Bilbao, Unai Ayala, Maitane Barrenechea, Alberto Cabrera‐Zubizarreta, Jesús Cortés, Juan Carlos Gómez‐Esteban, Iñigo Gabilondo   +15 more
wiley   +1 more source

Paraphrase Generation with Deep Reinforcement Learning

, 2018
Automatic generation of paraphrases from a given sentence is an important yet challenging task in natural language processing (NLP), and plays a key role in a number of applications such as question answering, search, and dialogue.
Jiang, Xin, Li, Hang, Li, Zichao, Shang, Lifeng   +3 more
core   +1 more source

Home‐Based Tele‐tDCS in Amyotrophic Lateral Sclerosis: Feasibility, Safety, and Preliminary Efficacy

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Amyotrophic lateral sclerosis (ALS) is a progressive neurodegenerative disease with limited treatment options. Transcranial direct current stimulation (tDCS) shows promise as a neuromodulatory intervention in various neurological disorders, but its application in ALS, particularly in a remote, home‐based format, remains underexplored.
Sangeetha Madhavan, Shravni Deshmukh, Mark Cummings, Aditi Doshi, Kourosh Rezania, Sally Freels, Gina Sawa   +6 more
wiley   +1 more source

Barriers and Facilitators for Implementing Resilience Coaching for Youth With Chronic Musculoskeletal Pain: Pediatric Rheumatologists’ Perspectives

Arthritis Care &Research, EarlyView.
Objective Promoting Resilience in Stress Management (PRISM) is a resilience coaching program designed for adolescents with chronic illness. We aimed to examine the perceived feasibility, acceptability, and appropriateness of PRISM among pediatric rheumatologists treating adolescents with chronic musculoskeletal pain and obtain recommendations for ...
Sabrina Gmuca, Anyun Chatterjee, Mackenzie McGill, Nellie Butler, Katherine S. Kellom, Jami F. Young, Tonya M. Palermo, Pamela F. Weiss, Abby R. Rosenberg, Peter F. Cronholm   +9 more
wiley   +1 more source

Augmented Q Imitation Learning (AQIL) [PDF]

arXiv, 2020
The study of unsupervised learning can be generally divided into two categories: imitation learning and reinforcement learning. In imitation learning the machine learns by mimicking the behavior of an expert system whereas in reinforcement learning the machine learns via direct environment feedback.
arxiv  

Bridging Nature and Technology: A Perspective on Role of Machine Learning in Bioinspired Ceramics

Advanced Engineering Materials, EarlyView.
Machine learning (ML) is revolutionizing the development of bioinspired ceramics. This article investigates how ML can be used to design new ceramic materials with exceptional performance, inspired by the structures found in nature. The research highlights how ML can predict material properties, optimize designs, and create advanced models to unlock a ...
Hamidreza Yazdani Sarvestani, Aditi Singh, Behnam Ashrafi   +2 more
wiley   +1 more source

A real-time HIL control system on rotary inverted pendulum hardware platform based on double deep Q-network

Measurement + Control, 2021
For real applications, rotary inverted pendulum systems have been known as the basic model in nonlinear control systems. If researchers have no deep understanding of control, it is difficult to control a rotary inverted pendulum platform using classic ...
Yanyan Dai, KiDong Lee, SukGyu Lee
doaj   +1 more source

Day-Ahead Optimal Dispatch Strategy for Active Distribution Network Based on Improved Deep Reinforcement Learning

IEEE Access, 2022
To effectively deal with the challenge of optimal dispatch caused by uncertainties such as renewable energy in active distribution network, a day-ahead optimal dispatch strategy for active distribution network based on improved deep reinforcement ...
Xiaoyu Li, Xueshan Han, Ming Yang
doaj   +1 more source

Modelling resource allocation in uncertain system environment through deep reinforcement learning [PDF]

arXiv, 2021
Reinforcement Learning has applications in field of mechatronics, robotics, and other resource-constrained control system. Problem of resource allocation is primarily solved using traditional predefined techniques and modern deep learning methods. The drawback of predefined and most deep learning methods for resource allocation is failing to meet the ...
arxiv  

Musicking Deep Reinforcement Learning

, 2022
In this paper, I relate an auto-reflexive analysis of my practice of designing and musicking deep reinforcement learning. Based on technical description of the Co-Explorer, a deep reinforcement learning agent designed to support sonic exploration through positive or negative human feedback, I discuss how deep reinforcement learning can be seen as a ...
openaire   +2 more sources