Long term ordering kinetics of the two dimensional q-state Potts model

We studied the non-equilibrium dynamics of the q-state Potts model in the square lattice, after a quench to sub-critical temperatures. By means of a continuous time Monte Carlo algorithm (non-conserved order parameter dynamics) we analyzed the long term behavior of the energy and relaxation time for a wide range of quench temperatures and system sizes. For q>4 we found the existence of different dynamical regimes, according to quench temperature range. At low (but finite) temperatures and very long times the Lifshitz-Allen-Cahn domain growth behavior is interrupted with finite probability when the system stuck in highly symmetric non-equilibrium metastable states, which induce activation in the domain growth, in agreement with early predictions of Lifshitz [JETP 42, 1354 (1962)]. Moreover, if the temperature is very low, the system always gets stuck at short times in a highly disordered metastable states with finite life time, which have been recently identified as glassy states. The finite size scaling properties of the different relaxation times involved, as well as their temperature dependency are analyzed in detail.Comment: 10 pages, 17 figure

EMD: an ensemble algorithm for discovering regulatory motifs in DNA sequences

BACKGROUND: Understanding gene regulatory networks has become one of the central research problems in bioinformatics. More than thirty algorithms have been proposed to identify DNA regulatory sites during the past thirty years. However, the prediction accuracy of these algorithms is still quite low. Ensemble algorithms have emerged as an effective strategy in bioinformatics for improving the prediction accuracy by exploiting the synergetic prediction capability of multiple algorithms. RESULTS: We proposed a novel clustering-based ensemble algorithm named EMD for de novo motif discovery by combining multiple predictions from multiple runs of one or more base component algorithms. The ensemble approach is applied to the motif discovery problem for the first time. The algorithm is tested on a benchmark dataset generated from E. coli RegulonDB. The EMD algorithm has achieved 22.4% improvement in terms of the nucleotide level prediction accuracy over the best stand-alone component algorithm. The advantage of the EMD algorithm is more significant for shorter input sequences, but most importantly, it always outperforms or at least stays at the same performance level of the stand-alone component algorithms even for longer sequences. CONCLUSION: We proposed an ensemble approach for the motif discovery problem by taking advantage of the availability of a large number of motif discovery programs. We have shown that the ensemble approach is an effective strategy for improving both sensitivity and specificity, thus the accuracy of the prediction. The advantage of the EMD algorithm is its flexibility in the sense that a new powerful algorithm can be easily added to the system

Protein-protein docking using region-based 3D Zernike descriptors

<p>Abstract</p> <p>Background</p> <p>Protein-protein interactions are a pivotal component of many biological processes and mediate a variety of functions. Knowing the tertiary structure of a protein complex is therefore essential for understanding the interaction mechanism. However, experimental techniques to solve the structure of the complex are often found to be difficult. To this end, computational protein-protein docking approaches can provide a useful alternative to address this issue. Prediction of docking conformations relies on methods that effectively capture shape features of the participating proteins while giving due consideration to conformational changes that may occur.</p> <p>Results</p> <p>We present a novel protein docking algorithm based on the use of 3D Zernike descriptors as regional features of molecular shape. The key motivation of using these descriptors is their invariance to transformation, in addition to a compact representation of local surface shape characteristics. Docking decoys are generated using geometric hashing, which are then ranked by a scoring function that incorporates a buried surface area and a novel geometric complementarity term based on normals associated with the 3D Zernike shape description. Our docking algorithm was tested on both bound and unbound cases in the ZDOCK benchmark 2.0 dataset. In 74% of the bound docking predictions, our method was able to find a near-native solution (interface C-<it>α</it>RMSD ≤ 2.5 Å) within the top 1000 ranks. For unbound docking, among the 60 complexes for which our algorithm returned at least one hit, 60% of the cases were ranked within the top 2000. Comparison with existing shape-based docking algorithms shows that our method has a better performance than the others in unbound docking while remaining competitive for bound docking cases.</p> <p>Conclusion</p> <p>We show for the first time that the 3D Zernike descriptors are adept in capturing shape complementarity at the protein-protein interface and useful for protein docking prediction. Rigorous benchmark studies show that our docking approach has a superior performance compared to existing methods.</p

Internal Energy of the Potts model on the Triangular Lattice with Two- and Three-body Interactions

We calculate the internal energy of the Potts model on the triangular lattice with two- and three-body interactions at the transition point satisfying certain conditions for coupling constants. The method is a duality transformation. Therefore we have to make assumptions on uniqueness of the transition point and that the transition is of second order. These assumptions have been verified to hold by numerical simulations for q=2, 3 and 4, and our results for the internal energy are expected to be exact in these cases.Comment: 9 pages, 4 figure

Premature ovarian failure in twins: case report

Premature ovarian failure (POF)is a serious life-changing condition that affects young women, remains an enigma and the researchers’ challenge. POF, premature ovarian insufficiency (POI), premature menopause, premature dysfunction (POD), or hypergonadotropic hypogonadism is one of the most perplexing disorders with aheterogeneous origin. Infertility, social and psychological stress are common consequences of this entity. This paper presents a rare condition where both twins had presented with POF

An incidental case of uterus didelphys and fibroids: Right sided myomectomy and left hemi-hysterectomy

Congenital anomalies of the uterus occur due to agenesis or lack of fusion of the Mullerian ducts. The incidence of these anomalies is largely&nbsp; unknown since they are unlikely to be diagnosed in asymptomatic women. Uterine didelphys or double uterus occurs when the two Mullerian ducts&nbsp; fail to fuse resulting in duplication of the uterus and cervix. This report discusses a case of a 38-yearold woman who had presented with a longstanding history of abnormal uterine bleeding and cyclical pain. She had had two successful vaginal deliveries prior to presentation to our unit. Sonographic findings revealed large uterine myomas and was consented for open myomectomy. Intraoperatively she was found to have two uteri, both of which had intramural fibroids and two cervices. Keywords: didelphys uterus, fibroid

Hard-wall Potential Function for Transport Properties of Alkali Metals Vapor

This study demonstrates that the transport properties of alkali metals are determined principally by the repulsive wall of the pair interaction potential function. The (hard-wall) Lennard-Jones(15-6) effective pair potential function is used to calculate transport collision integrals. Accordingly, reduced collision integrals of K, Rb, and Cs metal vapors are obtained from Chapman-Enskog solution of the Boltzman equation. The law of corresponding states based on the experimental-transport reduced collision integral is used to verify the validity of a LJ(15-6) hybrid potential in describing the transport properties. LJ(8.5-4) potential function and a simple thermodynamic argument with the input PVT data of liquid metals provide the required molecular potential parameters. Values of the predicted viscosity of monatomic alkali metals vapor are in agreement with typical experimental data with the average absolute deviation 2.97% for K in the range 700-1500 K, 1.69% for Rb, and 1.75% for Cs in the range 700-2000 K. In the same way, the values of predicted thermal conductivity are in agreement with experiment within 2.78%, 3.25%, and 3.63% for K, Rb, and Cs, respectively. The LJ(15-6) hybrid potential with a hard-wall repulsion character conclusively predicts best transport properties of the three alkali metals vapor.Comment: 21 pages, 5 figures, 41 reference

Helium, Oxygen, Proton, and Electron (HOPE) Mass Spectrometer for the Radiation Belt Storm Probes Mission

The HOPE mass spectrometer of the Radiation Belt Storm Probes (RBSP) mission (renamed the Van Allen Probes) is designed to measure the in situ plasma ion and electron fluxes over 4π sr at each RBSP spacecraft within the terrestrial radiation belts. The scientific goal is to understand the underlying physical processes that govern the radiation belt structure and dynamics. Spectral measurements for both ions and electrons are acquired over 1 eV to 50 keV in 36 log-spaced steps at an energy resolution ΔE FWHM/E≈15 %. The dominant ion species (H+, He+, and O+) of the magnetosphere are identified using foil-based time-of-flight (TOF) mass spectrometry with channel electron multiplier (CEM) detectors. Angular measurements are derived using five polar pixels coplanar with the spacecraft spin axis, and up to 16 azimuthal bins are acquired for each polar pixel over time as the spacecraft spins. Ion and electron measurements are acquired on alternate spacecraft spins. HOPE incorporates several new methods to minimize and monitor the background induced by penetrating particles in the harsh environment of the radiation belts. The absolute efficiencies of detection are continuously monitored, enabling precise, quantitative measurements of electron and ion fluxes and ion species abundances throughout the mission. We describe the engineering approaches for plasma measurements in the radiation belts and present summaries of HOPE measurement strategy and performance

Transmission of Information in Active Networks

Shannon's Capacity Theorem is the main concept behind the Theory of Communication. It says that if the amount of information contained in a signal is smaller than the channel capacity of a physical media of communication, it can be transmitted with arbitrarily small probability of error. This theorem is usually applicable to ideal channels of communication in which the information to be transmitted does not alter the passive characteristics of the channel that basically tries to reproduce the source of information. For an {\it active channel}, a network formed by elements that are dynamical systems (such as neurons, chaotic or periodic oscillators), it is unclear if such theorem is applicable, once an active channel can adapt to the input of a signal, altering its capacity. To shed light into this matter, we show, among other results, how to calculate the information capacity of an active channel of communication. Then, we show that the {\it channel capacity} depends on whether the active channel is self-excitable or not and that, contrary to a current belief, desynchronization can provide an environment in which large amounts of information can be transmitted in a channel that is self-excitable. An interesting case of a self-excitable active channel is a network of electrically connected Hindmarsh-Rose chaotic neurons.Comment: 15 pages, 5 figures. submitted for publication. to appear in Phys. Rev.