Emergence of (bi)multi-partiteness in networks having inhibitory and excitatory couplings

(Bi)multi-partite interaction patterns are commonly observed in real world systems which have inhibitory and excitatory couplings. We hypothesize these structural interaction pattern to be stable and naturally arising in the course of evolution. We demonstrate that a random structure evolves to the (bi)multi-partite structure by imposing stability criterion through minimization of the largest eigenvalue in the genetic algorithm devised on the interacting units having inhibitory and excitatory couplings. The evolved interaction patterns are robust against changes in the initial network architecture as well as fluctuations in the interaction weights.Comment: 6 pages, 7 figure

Optimization of synchronizability in multiplex networks

We investigate the optimization of synchronizability in multiplex networks and demonstrate that the interlayer coupling strength is the deciding factor for the efficiency of optimization. The optimized networks have homogeneity in the degree as well as in the betweenness centrality. Additionally, the interlayer coupling strength crucially affects various properties of individual layers in the optimized multiplex networks. We provide an understanding to how the emerged network properties are shaped or affected when the evolution renders them better synchronizable.Comment: 6 pages and 6 figure

Optimization of synchronizability in multiplex networks by rewiring one layer

Peer reviewedPublisher PD

Velocity Response of the Observed Explosive Events in the Lower Solar Atmosphere: I. Formation of the Flowing Cool Loop System

We observe plasma flows in cool loops using the Slit-Jaw Imager (SJI) onboard the Interface Region Imaging Spectrometer (IRIS). Huang et al. (2015) observed unusually broadened Si IV 1403 angstrom line profiles at the footpoints of such loops that were attributed to signatures of explosive events (EEs). We have chosen one such uni-directional flowing cool loop system observed by IRIS where one of the footpoints is associated with significantly broadened Si IV line profiles. The line profile broadening indirectly indicates the occurrence of numerous EEs below the transition region (TR), while it directly infers a large velocity enhancement /perturbation further causing the plasma flows in the observed loop system. The observed features are implemented in a model atmosphere in which a low-lying bi-polar magnetic field system is perturbed in the chromosphere by a velocity pulse with a maximum amplitude of 200 km/s. The data-driven 2-D numerical simulation shows that the plasma motions evolve in a similar manner as observed by IRIS in the form of flowing plasma filling the skeleton of a cool loop system. We compare the spatio-temporal evolution of the cool loop system in the framework of our model with the observations, and conclude that their formation is mostly associated with the velocity response of the transient energy release above their footpoints in the chromosphere/TR. Our observations and modeling results suggest that the velocity responses most likely associated to the EEs could be one of the main candidates for the dynamics and energetics of the flowing cool loop systems in the lower solar atmosphere.Comment: In Press; The Astrophysical Journal; 14 Pages; 9 Figure

Classification of HIV-1 Sequences Using Profile Hidden Markov Models

Accurate classification of HIV-1 subtypes is essential for studying the dynamic spatial distribution pattern of HIV-1 subtypes and also for developing effective methods of treatment that can be targeted to attack specific subtypes. We propose a classification method based on profile Hidden Markov Model that can accurately identify an unknown strain. We show that a standard method that relies on the construction of a positive training set only, to capture unique features associated with a particular subtype, can accurately classify sequences belonging to all subtypes except B and D. We point out the drawbacks of the standard method; namely, an arbitrary choice of threshold to distinguish between true positives and true negatives, and the inability to discriminate between closely related subtypes. We then propose an improved classification method based on construction of a positive as well as a negative training set to improve discriminating ability between closely related subtypes like B and D. Finally, we show how the improved method can be used to accurately determine the subtype composition of Common Recombinant Forms of the virus that are made up of two or more subtypes. Our method provides a simple and highly accurate alternative to other classification methods and will be useful in accurately annotating newly sequenced HIV-1 strains

Optimization of synchronizability in multiplex networks

We investigate the optimization of synchronizability in multiplex networks and demonstrate that the interlayer coupling strength is the deciding factor for the efficiency of optimization. The optimized networks have homogeneity in the degree as well as in the betweenness centrality. Additionally, the interlayer coupling strength crucially affects various properties of individual layers in the optimized multiplex networks. We provide an understanding as to how the emerged network properties are shaped or affected when the evolution renders them better synchronizable

Subtype D classification using the standard method.

<p>Distribution of Z-scores for all HIV-1 group M sequences in the database when the training set is constructed using sequences belonging to the subtype D.</p

Accuracy of subtype detection in the <i>gag-pol</i> region of CRFs.

<p>Accuracy of subtype detection in the <i>gag-pol</i> region of CRFs.</p