Search results for "Stewart"

The Norwegian Motion-Laboratory

2018

This paper contains an overview of the equipment currently available in the Norwegian Motion Laboratory, a description of the IT networking infrastructure in the laboratory, a GitHub link to open source code developed, description of the PyQt-based graphical user interface, presentation of robot forward and inverse kinematics, presentation of equations of motion for the suspended load motion and a description of the full system kinematics. The paper ends with a list of research experiments and publications from the laboratory to date.

Taiteen kritiikki ja kritiikin taide : Stewart Home porvarillisen kulttuurin raunioilla

1999

Charles Stewart Parnell - Irlannin kruunaamaton kuningas : sankari, petturi vai karismaattinen parlamentaarikko?

2006

Chloride/sodium ratio and sodium.chloride difference inpatients with renal failure and metabolic acidosis in hemodialysis treatment

2018

Weight loss in Alzheimer’s disease, vascular dementia and dementia with Lewy bodies: Impact on mortality and hospitalization by dementia subtype

2021

Objectives Loss of weight is associated with cognitive decline as well as several adverse outcomes in dementia. The aim of this study was to assess whether weight loss is associated with mortality and hospitalization in dementia subtypes. Methods A cohort of 11,607 patients with dementia in Alzheimer's disease (AD), vascular dementia (VD), or dementia with Lewy bodies (DLB) was assembled from a large dementia care health records database in Southeast London. A natural language processing algorithm was developed to established whether loss of weight was recorded around the time of dementia diagnosis. Cox proportional hazard models were applied to examine the associations of reported weight l…

High precision numerical approach for Davey–Stewartson II type equations for Schwartz class initial data

2020

We present an efficient high-precision numerical approach for Davey–Stewartson (DS) II type equa- tions, treating initial data from the Schwartz class of smooth, rapidly decreasing functions. As with previous approaches, the presented code uses discrete Fourier transforms for the spatial dependence and Driscoll’s composite Runge–Kutta method for the time dependence. Since DS equations are non-local, nonlinear Schrödinger equations with a singular symbol for the non-locality, standard Fourier methods in practice only reach accuracy of the order of 10−6or less for typical examples. This was previously demonstrated for the defocusing integrable case by comparison with a numerical approach for …