Playing Tic-Tac-Toe Using Genetic Neural Network with Double Transfer functions

Computational intelligence is a powerful tool for game development. In this paper, an algorithm of playing the game Tic-Tac-Toe with computational intelligence is developed. This algorithm is learned by a Neural Network with Double Transfer functions (NNDTF), which is trained by genetic algorithm (GA). In the NNDTF, the neuron has two transfer functions and exhibits a node-to-node relationship in the hidden layer that enhances the learning ability of the network. A Tic-Tac-Toe game is used to show that the NNDTF provide a better performance than the traditional neural network does

Predicting protein-ligand binding site using support vector machine with protein properties

Identification of protein-ligand binding site is an important task in structure-based drug design and docking algorithms. In the past two decades, different approaches have been developed to predict the binding site, such as the geometric, energetic, and sequence-based methods. When scores are calculated from these methods, the algorithm for doing classification becomes very important and can affect the prediction results greatly. In this paper, the support vector machine (SVM) is used to cluster the pockets that are most likely to bind ligands with the attributes of geometric characteristics, interaction potential, offset from protein, conservation score, and properties surrounding the pockets. Our approach is compared to LIGSITE, LIGSITEcsc, SURFNET, Fpocket, PocketFinder, Q-SiteFinder, ConCavity, and MetaPocket on the data set LigASite and 198 drug-target protein complexes. The results show that our approach improves the success rate from 60 to 80 percent at AUC measure and from 61 to 66 percent at top 1 prediction. Our method also provides more comprehensive results than the others

Online support vector machine application for model based fault detection and isolation of HVAC system

Abstract—Preventive maintenance plays an important role in Heating, Ventilation and Air Conditioning (HVAC) system. One cost effective strategy is the development of analytic fault detection and isolation (FDI) module by online monitoring the key variables of HAVC systems. This paper investigates realtime FDI for HAVC system by using online Support Vector Machine (SVM), by which we are able to train a FDI system with manageable complexity under real time working conditions. It is also proposed a new approach which allows us to detect unknown faults and updating the classifier by using these previously unknown faults. Based on the proposed approach, a semi unsupervised fault detection methodology has been developed for HVAC system

Photoluminescence and lasing characteristics of single nonpolar GaN microwires

published_or_final_versio

Hoxb3 negatively regulates Hoxb1 expression in mouse hindbrain patterning

The spatial regulation of combinatorial expression of Hox genes is critical for determining hindbrain rhombomere (r) identities. To address the cross-regulatory relationship between Hox genes in hindbrain neuronal specification, we have generated a gain-of-function transgenic mouse mutant Hoxb3 Tg using the Hoxb2 r4-specific enhancer element. Interestingly, in r4 of the Hoxb3 Tg mutant where Hoxb3 was ectopically expressed, the expression of Hoxb1 was specifically abolished. The hindbrain neuronal defects of the Hoxb3 Tg mutant mice were similar to those of Hoxb1 -/- mutants. Therefore, we hypothesized that Hoxb3 could directly suppress Hoxb1 expression. We first identified a novel Hoxb3 binding site S3 on the Hoxb1 locus and confirmed protein binding to this site by EMSA, and by in vivo ChIP analysis using P19 cells and hindbrain tissues from the Hoxb3 Tg mutant. We further showed that Hoxb3 could suppress Hoxb1 transcriptional activity by chick in ovo luciferase reporter assay. Moreover, in E10.5 wildtype caudal hindbrain, where Hoxb1 is not expressed, we showed by in vivo ChIP that Hoxb3 was consistently bound to the S3 site on the Hoxb1 gene. This study reveals a novel negative regulatory mechanism by which Hoxb3 as a posterior gene serves to restrict Hoxb1 expression in r4 by direct transcriptional repression to maintain the rhombomere identity. © 2011 Elsevier Inc.postprin

Challenges of Profile Likelihood Evaluation in Multi-Dimensional SUSY Scans

Statistical inference of the fundamental parameters of supersymmetric theories is a challenging and active endeavor. Several sophisticated algorithms have been employed to this end. While Markov-Chain Monte Carlo (MCMC) and nested sampling techniques are geared towards Bayesian inference, they have also been used to estimate frequentist confidence intervals based on the profile likelihood ratio. We investigate the performance and appropriate configuration of MultiNest, a nested sampling based algorithm, when used for profile likelihood-based analyses both on toy models and on the parameter space of the Constrained MSSM. We find that while the standard configuration is appropriate for an accurate reconstruction of the Bayesian posterior, the profile likelihood is poorly approximated. We identify a more appropriate MultiNest configuration for profile likelihood analyses, which gives an excellent exploration of the profile likelihood (albeit at a larger computational cost), including the identification of the global maximum likelihood value. We conclude that with the appropriate configuration MultiNest is a suitable tool for profile likelihood studies, indicating previous claims to the contrary are not well founded.Comment: 21 pages, 9 figures, 1 table; minor changes following referee report. Matches version accepted by JHE

The midbrain to pons ratio: a simple and specific MRI sign of progressive supranuclear palsy.

MRI-based measurements used to diagnose progressive supranuclear palsy (PSP) typically lack pathologic verification and are not easy to use routinely. We aimed to develop in histologically proven disease a simple measure of the midbrain and pons on sagittal MRI to identify PSP

First Results from Lattice Simulation of the PWMM

We present results of lattice simulations of the Plane Wave Matrix Model (PWMM). The PWMM is a theory of supersymmetric quantum mechanics that has a well-defined canonical ensemble. We simulate this theory by applying rational hybrid Monte Carlo techniques to a naive lattice action. We examine the strong coupling behaviour of the model focussing on the deconfinement transition.Comment: v3 20 pages, 8 figures, comment adde

Boundary entropy of supersymmetric Janus solutions

In this paper we compute the holographic boundary entropy for half-BPS Janus deformations of the $AdS_3\times S^3\times T^4$ vacuum of type IIB supergravity. Previous work \cite{Chiodaroli:2009yw} has shown that there are two independent deformations of this sort. In one case, the six-dimensional dilaton jumps across the interface, while the other case displays a jump of axion and four-form potential. In case of a jump of the six-dimensional dilaton, it is possible to compare the holographic result with the weak-coupling result for a two-dimensional interface CFT where the radii of the compactified bosons jump across the interface. We find exact agreement between holographic and CFT results. This is to be contrasted with the holographic calculation for the non-supersymmetric Janus solution, which agrees with the CFT result only at the leading order in the jump parameter. We also examine the implications of the holographic calculation in case of a solution with a jump in the axion, which can be associated with a deformation of the CFT by the $Z_2$-orbifold twist operator.Comment: 35 pages, pdf-LaTeX, 5 figures, v2: minor changes, typos corrected, reference adde