Using OCT-based microangiography for in vivo longitudinal study of arteriogenesis (Conference Presentation)

Author(s):  
Yuandong Li ◽  
Woo June Choi ◽  
Ruikang K. Wang
Keyword(s):  
2020 ◽  
Author(s):  
Oliver James Scholten ◽  
David Zendle ◽  
James Alfred Walker

Decentralised gambling applications are a new way for individuals to engage in online gambling. Decentralised gambling applications are distinguished from traditional online casinos in that individuals use cryptocurrency as a stake. Furthermore, rather than being stored on a traditional server, decentralised gambling applications are stored on a cryptocurrency’s blockchain.Previous work in the player behaviour tracking literature has examined the spending profiles of gamblers on traditional online casinos. However, parallel work has not taken place in the decentralised gambling domain. The profile of gamblers on decentralised gambling applications are therefore not known.This paper explores 2,232,741 transactions from 24,234 unique addresses to three such applications operating atop the Ethereum cryptocurrency network over 583 days. We present spending profiles across these applications, providing the first detailed summary of spending behaviours in this technologically advanced domain. We find that the typical user spends approximately \$110 equivalent across a median of 6 bets in a single day, although heavily involved bettors spend approximately \$100,000 equivalent over a median of 644 bets across 35 days. Our findings suggest that the use of decentralised gambling applications typically involves lower and less frequent expenditures than other online casinos, but that the most heavily involved players in this new domain spend substantially more. Our findings also demonstrate the use of these applications as a research platform, specifically for large scale longitudinal in-vivo data analysis.


2017 ◽  
Vol 7 ◽  
pp. S55-S56
Author(s):  
Emmanuelle Flatt ◽  
Cristina Cudalbu ◽  
Olivier Braissant ◽  
Stefan Mitrea ◽  
Dario Sessa ◽  
...  

Author(s):  
A. Dupay ◽  
P. Snyder ◽  
W. Lee ◽  
S. Baek

For an abdominal aortic aneurysm (AAA) in vivo there are multiple tissues contacting its boundary, none of which have been fully considered for their effect throughout disease progression. Trends such as arterial asymmetry, surface curvature flattening, and arterial tortuosity could be significantly influenced by both surrounding tissue and hemodynamic factors. In order to quantify either the combined or separate influence of such factors during disease progression a precise characterization of aneurysm geometry evolution is needed. Multiple methods for geometrical parameterization of abdominal aortic aneurysms (AAAs) have been previously developed using isolated patient CT scan data but the focus has been mainly on the association of such geometrical parameters with the rupture risk and the efficacy of the parameterization is not fully investigated for a longitudinal study yet (multiple CT scans per patient at progressive intervals) [1]. For this study we have produced a series of 3D models for AAAs in longitudinal studies, developed an arterial centerline generation algorithm, and automated a geometric parameterization procedure for the arterial surfaces. It should be noted that the caliber of our collection of data is relatively rare as it is high resolution, features many patients, and on average has 4–5 images per patient.


2008 ◽  
Vol 4 ◽  
pp. T65-T65
Author(s):  
Victor L. Villemagne ◽  
Kerryn E. Pike ◽  
Uwe Ackermann ◽  
David Ames ◽  
Kathryn Ellis ◽  
...  

2016 ◽  
Vol 6 (1) ◽  
Author(s):  
Antonietta Mele ◽  
Adriano Fonzino ◽  
Francesco Rana ◽  
Giulia Maria Camerino ◽  
Michela De Bellis ◽  
...  

1998 ◽  
Vol 26 (1) ◽  
pp. S76-S76 ◽  
Author(s):  
CAROLINE A. WARNOCK ◽  
M. BARBARA E. LIVINGSTONE ◽  
EDWARD S. GILLESPIE ◽  
CHRISTOPHER R. BARNETT ◽  
YVONNE A. BARNETT

2016 ◽  
Vol 12 (1) ◽  
Author(s):  
Christian P. Bertholle ◽  
Ellen Meijer ◽  
Willem Back ◽  
Arjan Stegeman ◽  
P. René van Weeren ◽  
...  

Sign in / Sign up

Export Citation Format

Share Document