Effect of Diffusion on the Appearance of a Percolation Cluster in Magnets with Direct Exchange

2021 ◽  
Vol 122 (12) ◽  
pp. 1169-1172
Author(s):  
V. I. Belokon’ ◽  
O. I. D’yachenko ◽  
R. V. Lapenkov
2020 ◽  
Vol 59 (04/05) ◽  
pp. 162-178
Author(s):  
Pouyan Esmaeilzadeh

Abstract Background Patients may seek health care services from various providers during treatment. These providers could serve in a network (affiliated) or practice separately (unaffiliated). Thus, using secure and reliable health information exchange (HIE) mechanisms would be critical to transfer sensitive personal health information (PHI) across distances. Studying patients' perceptions and opinions about exchange mechanisms could help health care providers build more complete HIEs' databases and develop robust privacy policies, consent processes, and patient education programs. Objectives Due to the exploratory nature of this study, we aim to shed more light on public perspectives (benefits, concerns, and risks) associated with the four data exchange practices in the health care sector. Methods In this study, we compared public perceptions and expectations regarding four common types of exchange mechanisms used in the United States (i.e., traditional, direct, query-based, patient-mediated exchange mechanisms). Traditional is an exchange through fax, paper mailing, or phone calls, direct is a provider-to-provider exchange, query-based is sharing patient data with a central repository, and patient-mediated is an exchange mechanism in which patients can access data and monitor sharing. Data were collected from 1,624 subjects using an online survey to examine the benefits, risks, and concerns associated with the four exchange mechanisms from patients' perspectives. Results Findings indicate that several concerns and risks such as privacy concerns, security risks, trust issues, and psychological risks are raised. Besides, multiple benefits such as access to complete information, communication improvement, timely and convenient information sharing, cost-saving, and medical error reduction are highlighted by respondents. Through consideration of all risks and benefits associated with the four exchange mechanisms, the direct HIE mechanism was selected by respondents as the most preferred mechanism of information exchange among providers. More than half of the respondents (56.18%) stated that overall they favored direct exchange over the other mechanisms. 42.70% of respondents expected to be more likely to share their PHI with health care providers who implemented and utilized a direct exchange mechanism. 43.26% of respondents believed that they would support health care providers to leverage a direct HIE mechanism for sharing their PHI with other providers. The results exhibit that individuals expect greater benefits and fewer adverse effects from direct HIE among health care providers. Overall, the general public sentiment is more in favor of direct data transfer. Our results highlight that greater public trust in exchange mechanisms is required, and information privacy and security risks must be addressed before the widespread implementation of such mechanisms. Conclusion This exploratory study's findings could be interesting for health care providers and HIE policymakers to analyze how consumers perceive the current exchange mechanisms, what concerns should be addressed, and how the exchange mechanisms could be modified to meet consumers' needs.


1999 ◽  
Vol 121 (5) ◽  
pp. 480-486 ◽  
Author(s):  
O. I. Craciunescu ◽  
S. K. Das ◽  
S. T. Clegg

Dynamic contrast-enhanced magnetic resonance imaging (DE-MRI) of the tumor blood pool is used to study tumor tissue perfusion. The results are then analyzed using percolation models. Percolation cluster geometry is depicted using the wash-in component of MRI contrast signal intensity. Fractal characteristics are determined for each two-dimensional cluster. The invasion percolation model is used to describe the evolution of the tumor perfusion front. Although tumor perfusion can be depicted rigorously only in three dimensions, two-dimensional cases are used to validate the methodology. It is concluded that the blood perfusion in a two-dimensional tumor vessel network has a fractal structure and that the evolution of the perfusion front can be characterized using invasion percolation. For all the cases studied, the front starts to grow from the periphery of the tumor (where the feeding vessel was assumed to lie) and continues to grow toward the center of the tumor, accounting for the well-documented perfused periphery and necrotic core of the tumor tissue.


1991 ◽  
Vol 24 (3) ◽  
pp. 735-740
Author(s):  
Jae Woo Lee ◽  
Ho Chui Kim ◽  
Jong-Jean Kim

1992 ◽  
Vol 03 (01) ◽  
pp. 213-219 ◽  
Author(s):  
ULLI WOLFF

Percolation cluster Monte Carlo algorithms for nonlinear σ-models on the lattice are reviewed with special emphasis on their possible generalizations. While they have been found to practically eliminate critical slowing down for the standard O(n) invariant vector models, their extension to other physically similar models — like RPn−1 and SU(n)×SU(n) chiral models — is less straight forward than one might have thought. I outline the present situation in this area of research. In the second part of my talk I described a numerical calculation of a physical running coupling constant in the O(3) model. This represents an application of the cluster technique in a preparatory study for a later lattice gauge theory calculation. This material can be found in Ref. 11.


1989 ◽  
Vol 03 (10) ◽  
pp. 765-770
Author(s):  
C.S. KIM ◽  
MIN-HO LEE

We studied two subjects related to anisotropy: random walk on percolation cluster having anisotropy (RWAC) and direction dependent (anisotropic) random walk on percolation cluster (AWIC). We find that the anisotropy of the cluster has only time-delaying effect on asymptotic convergence of the spectral dimensionality ds and fractal dimensionality of walk dw, however, the anisotropy of the walk results in lower spectral dimensionality and higher fractal dimensionality, as anisotropy grows larger.


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