Results 241 to 250 of about 323,200 (377)

Predictors of Loneliness in Parkinson's Disease and Craniocervical Dystonia

open access: yesMovement Disorders Clinical Practice, EarlyView.
Abstract Background Loneliness is a state in which an individual feels socially isolated due to deficiencies in the quantity or quality of social relationships and interaction. To date very little is known about loneliness in Parkinson's disease (PD) and focal/segmental craniocervical dystonia (FSCD).
Suzette Shahmoon   +5 more
wiley   +1 more source

Subjective Well‐Being and Its Predictors in Parkinson's Disease and Dystonia: A Comparative Study

open access: yesMovement Disorders Clinical Practice, EarlyView.
Abstract Background Quality of life (QoL) is a commonly used outcome measure in people with chronic neurological diseases (CND). As valuable as QoL is, it does not take into account aspects of subjective well‐being (SWB) such as subjective happiness, meaning in life, life satisfaction and hope; all constructs that are considered central to well‐being ...
Suzette Shahmoon   +5 more
wiley   +1 more source

A Multi-User Game-Theoretical Multipath Routing Protocol to Send Video-Warning Messages over Mobile Ad Hoc Networks. [PDF]

open access: yesSensors (Basel), 2015
Mezher AM   +7 more
europepmc   +1 more source

Cholinergic System Changes in Dopa‐Unresponsive Freezing of Gait in Parkinson's Disease

open access: yesMovement Disorders, EarlyView.
Abstract Background Freezing of gait (FoG) is a debilitating mobility disturbance that becomes increasingly resistant to dopaminergic pharmacotherapies with advancing Parkinson's disease (PD). The pathophysiology underlying the response of FoG to dopaminergic treatment is poorly understood.
Kelvin L. Chou   +6 more
wiley   +1 more source

A framework for reliable routing in mobile ad hoc networks

open access: yesIEEE INFOCOM 2003. Twenty-second Annual Joint Conference of the IEEE Computer and Communications Societies (IEEE Cat. No.03CH37428), 2003
Zhenqiang Ye   +2 more
semanticscholar   +1 more source

Multiobjective optimization of dielectric, thermal, and mechanical properties of inorganic glasses utilizing explainable machine learning and genetic algorithm

open access: yesMaterials Genome Engineering Advances, EarlyView.
A data‐driven framework that incorporates machine learning models, model‐agnostic interpretation methods, and genetic algorithms was proposed to explore the composition–property relationship and accelerate the design of novel glass materials with good dielectric, thermal, and mechanical properties.
Jincheng Qin   +4 more
wiley   +1 more source

Home - About - Disclaimer - Privacy