14,275 research outputs found
A pairwise maximum entropy model describes energy landscape for spiral wave dynamics of cardiac fibrillation
Heart is an electrically-connected network. Spiral wave dynamics of cardiac
fibrillation shows chaotic and disintegrated patterns while sinus rhythm shows
synchronized excitation patterns. To determine functional interactions between
cardiomyocytes during complex fibrillation states, we applied a pairwise
maximum entropy model (MEM) to the sequential electrical activity maps acquired
from the 2D computational simulation of human atrial fibrillation. Then, we
constructed energy landscape and estimated hierarchical structure among the
different local minima (attractors) to explain the dynamic properties of
cardiac fibrillation. Four types of the wave dynamics were considered: sinus
rhythm; single stable rotor; single rotor with wavebreak; and multiple wavelet.
The MEM could describe all types of wave dynamics (both accuracy and
reliability>0.9) except the multiple random wavelet. Both of the sinus rhythm
and the single stable rotor showed relatively high pairwise interaction
coefficients among the cardiomyocytes. Also, the local energy minima had
relatively large basins and high energy barrier, showing stable attractor
properties. However, in the single rotor with wavebreak, there were relatively
low pairwise interaction coefficients and a similar number of the local minima
separated by a relatively low energy barrier compared with the single stable
rotor case. The energy landscape of the multiple wavelet consisted of a large
number of the local minima separated by a relatively low energy barrier,
showing unstable dynamics. These results indicate that the MEM provides
information about local and global coherence among the cardiomyocytes beyond
the simple structural connectivity. Energy landscape analysis can explain
stability and transitional properties of complex dynamics of cardiac
fibrillation, which might be determined by the presence of 'driver' such as
sinus node or rotor.Comment: Presented at the 62nd Biophysical Society Annual Meeting, San
Francisco, California, 201
Of McKay Correspondence, Non-linear Sigma-model and Conformal Field Theory
The ubiquitous ADE classification has induced many proposals of often
mysterious correspondences both in mathematics and physics. The mathematics
side includes quiver theory and the McKay Correspondence which relates finite
group representation theory to Lie algebras as well as crepant resolutions of
Gorenstein singularities. On the physics side, we have the graph-theoretic
classification of the modular invariants of WZW models, as well as the relation
between the string theory nonlinear -models and Landau-Ginzburg
orbifolds. We here propose a unification scheme which naturally incorporates
all these correspondences of the ADE type in two complex dimensions. An
intricate web of inter-relations is constructed, providing a possible guideline
to establish new directions of research or alternate pathways to the standing
problems in higher dimensions.Comment: 35 pages, 4 figures; minor corrections, comments on toric geometry
and references adde
Empirical Modeling of Ducting Effects on a Mobile Microwave Link Over a Sea Surface
In this paper, signal enhancement due to the ducts over a sea surface is experimentally investigated and modeled. The investigation is carried out through the study of air-to-ground mobile microwave links over a tropical ocean with low airborne altitudes (0.37 - 1.83 km) at C band (5.7 GHz). The distance-dependence of the ducting induced enhancement (with reference to the free-space propagation) is linearly modeled, and the physical variations of the ducts are found to be Gaussian distributed. Empirical ducting coefficients and parameters for the Gaussian function are estimated and provided for the prediction of the distance-dependent signal enhancement due to the ducts in similar scenarios
Using Microservices to Customize Multi-Tenant SaaS: From Intrusive to Non-Intrusive
Customization is a widely adopted practice on enterprise software applications such as Enterprise resource planning (ERP) or Customer relation management (CRM). Software vendors deploy their enterprise software product on the premises of a customer, which is then often customized for different specific needs of the customer. When enterprise applications are moving to the cloud as mutli-tenant Software-as-a-Service (SaaS), the traditional way of on-premises customization faces new challenges because a customer no longer has an exclusive control to the application. To empower businesses with specific requirements on top of the shared standard SaaS, vendors need a novel approach to support the customization on the multi-tenant SaaS. In this paper, we summarize our two approaches for customizing multi-tenant SaaS using microservices: intrusive and non-intrusive. The paper clarifies the key concepts related to the problem of multi-tenant customization, and describes a design with a reference architecture and high-level principles. We also discuss the key technical challenges and the feasible solutions to implement this architecture. Our microservice-based customization solution is promising to meet the general customization requirements, and achieves a balance between isolation, assimilation and economy of scale
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