Variational treatment of π°-condensed neutron matter in a realistic potential model

2006 ◽  
pp. 68-75
Author(s):  
Omar Benhar
Keyword(s):  
Potential Model ◽  
Neutron Matter ◽  
Realistic Potential ◽  
Variational Treatment

Alpha-cluster states ofPo212in a realistic potential model

1994 ◽  
Vol 50 (5) ◽  
pp. 2631-2634 ◽  
Author(s):  
F. Hoyler ◽  
P. Mohr ◽  
G. Staudt
Keyword(s):  
Potential Model ◽  
Cluster States ◽  
Realistic Potential ◽  
Alpha Cluster

BALB-Abcb4 mice lacking the hepatobiliary phospholipid transporter represent a potential model of hepatic osteodystrophy

2009 ◽  
Vol 47 (09) ◽  
Author(s):  
K Hochrath ◽  
B Rathkolb ◽  
K Butuzova ◽  
W Hans ◽  
H Fuchs ◽  
...  
Keyword(s):  
Potential Model ◽  
Hepatic Osteodystrophy

RELATIVE CONTRIBUTIONS OF FIBROSIS AND CONNEXIN CHANGES TOTHE ATRIAL FIBRILLATION SUBSTRATE DURING THE DEVELOPMENT AND REVERSAL OF CONGESTIVEHEART FAILURE

2008 ◽  
Vol 31 (4) ◽  
pp. 5
Author(s):  
Brett Burstein ◽  
Kunihiro Nishida ◽  
Philippe Comtois ◽  
Louis Villenuve ◽  
Yung-Hsin Yeh ◽  
...  
Keyword(s):  
Atrial Fibrillation ◽  
Potential Model ◽  
Diastolic Pressure ◽  
Recovery Period ◽  
Left Ventricular ◽  
Muscle Bundle ◽  
Protein Ratio ◽  
Conduction Disturbances ◽  
Conduction Abnormalities ◽  
Mrna And Protein Expression

Background: Connexin alterations occur in various atrial fibrillation (AF) paradigms, but their functional significance remains unclear. No data are available regarding the effects of CHF on atrial connexin expression and phosphorylation. We therefore analyzed connexin changes and their contribution to the AF substrate during the development and reversal ofCHF. Methods and Results: Dogs were allocated to three groups: CHF induced by 2-week ventricular tachypacing (CHF, n=15); CHF dogs allowed to recover for 4 weeks after 2-week tachypacing (REC, n=15) and non-paced shams (CTL, n=11). Left ventricular end-diastolic pressure increased with CHF (14.5±1.0*** vs.3.7±0.7, ***P < 0.001 vs. CTL) and normalized upon CHF recovery (5.1±1.0^†††, ^††† P < 0.001 vs. CHF). Real-time PCR and Western-blot analyses revealed connexin43 (Cx43) and connexin40 (Cx40) mRNA and protein expression to be unchanged by CHF and REC. However, CHF caused Cx43 dephosphorylation(by ~73%***) and increased Cx40/Cx43 protein ratio (by ~35%***), with both alterations completely reversing in REC. Immunofluorescent confocal microscopy confirmed connexin protein trends, with a reduction in phosphorylated Cx43 (by ~68%*** in CHF) that returned to control in REC. CHF caused conduction abnormalities (phasedelay-range and heterogeneity index, both P < 0.01) and burst pacing-induced AF prolongation (CTL 22±7s, CHF 1100±171s***, REC 884±220s***) which persisted in the recovery period, along with residual fibrosis (CTL 3.6±0.7%, CHF 14.7±1.5%***, REC13.3±2.3%***). Fibrosis physically interrupted muscle bundle continuity and anionically-based action potential model of canine atrium showed that fibrosiswas able to account for the observed conduction abnormalities. Conclusions: CHF causes connexin-dephosphorylation and Cx40/Cx43ratio increases. With CHF reversal, atrial connexin alterations recover completely, but tissue fibrosis, conduction abnormalities and a substrate forAF remain with fibrosis accounting for conduction abnormalities. Thus, althougha trial connexin changes occur with CHF, they are not essential for conduction disturbances and AF promotion, which appear rather to be related primarily tofibrotic interruption of muscle-bundle continuity.

The Affine Rational Potential Model

2015 ◽  
Author(s):  
The Anh Nguyen ◽  
Frank Thomas Seifried
Keyword(s):  
Potential Model ◽  
Rational Potential

Statistical mechanics

2017 ◽  
Author(s):  
Michael P. Allen ◽  
Dominic J. Tildesley
Keyword(s):  
Statistical Mechanics ◽  
Potential Model ◽  
Quantum Corrections ◽  
Inhomogeneous Systems ◽  
Hard Constraints ◽  
Complex Liquids ◽  
Fluid Membranes ◽  
Dynamical Properties ◽  
Canonical Ensembles ◽  
Grand Canonical

This chapter contains the essential statistical mechanics required to understand the inner workings of, and interpretation of results from, computer simulations. The microcanonical, canonical, isothermal–isobaric, semigrand and grand canonical ensembles are defined. Thermodynamic, structural, and dynamical properties of simple and complex liquids are related to appropriate functions of molecular positions and velocities. A number of important thermodynamic properties are defined in terms of fluctuations in these ensembles. The effect of the inclusion of hard constraints in the underlying potential model on the calculated properties is considered, and the addition of long-range and quantum corrections to classical simulations is presented. The extension of statistical mechanics to describe inhomogeneous systems such as the planar gas–liquid interface, fluid membranes, and liquid crystals, and its application in the simulation of these systems, are discussed.

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