Covariate dimension reduction for survival data via the Gaussian process latent variable model

The analysis of high dimensional survival data is challenging, primarily due to the problem of overfitting which occurs when spurious relationships are inferred from data that subsequently fail to exist in test data. Here we propose a novel method of extracting a low dimensional representation of covariates in survival data by combining the popular Gaussian Process Latent Variable Model (GPLVM) with a Weibull Proportional Hazards Model (WPHM). The combined model offers a flexible non-linear probabilistic method of detecting and extracting any intrinsic low dimensional structure from high dimensional data. By reducing the covariate dimension we aim to diminish the risk of overfitting and increase the robustness and accuracy with which we infer relationships between covariates and survival outcomes. In addition, we can simultaneously combine information from multiple data sources by expressing multiple datasets in terms of the same low dimensional space. We present results from several simulation studies that illustrate a reduction in overfitting and an increase in predictive performance, as well as successful detection of intrinsic dimensionality. We provide evidence that it is advantageous to combine dimensionality reduction with survival outcomes rather than performing unsupervised dimensionality reduction on its own. Finally, we use our model to analyse experimental gene expression data and detect and extract a low dimensional representation that allows us to distinguish high and low risk groups with superior accuracy compared to doing regression on the original high dimensional data

D-brane orbiting NS5-branes

We study real time dynamics of a Dp-brane orbiting a stack of NS5-branes. It is generally known that a BPS D-brane moving in the vicinity of NS5-branes becomes unstable due to the presence of tachyonic degree of freedom induced on the D-brane. Indeed, the D-brane necessarily falls into the fivebranes due to gravitational attraction and eventually collapses into a pressureless fluid. Such a decay of the D-brane is known to be closely related to the rolling tachyon problem. In this paper we show that in special cases the decay of D-brane caused by gravitational attraction can be avoided. Namely for certain values of energy and angular momentum the D-brane orbits around the fivebranes, maintaining certain distance from the fivebranes all the time, and the process of tachyon condensation is suppressed. We show that the tachyonic degree of freedom induced on such a D-brane really disappears and the brane returns to a stable D-brane.Comment: 12 pages, latex, added referenc

Study of Optical-Feedback Using an Integrated Laser-Modulator/Amplifier Device

We study optical-feedback effects using an integrated laser-modulator/amplifier. Our experiment and theory are agree well and provide interesting results of feedback effects on optical spectrum, spatial-hole burning, the photon density profile, and the microwave modulation

Dynamic biclustering of microarray data by multi-objective immune optimization

Abstract Background Newly microarray technologies yield large-scale datasets. The microarray datasets are usually presented in 2D matrices, where rows represent genes and columns represent experimental conditions. Systematic analysis of those datasets provides the increasing amount of information, which is urgently needed in the post-genomic era. Biclustering, which is a technique developed to allow simultaneous clustering of rows and columns of a dataset, might be useful to extract more accurate information from those datasets. Biclustering requires the optimization of two conflicting objectives (residue and volume), and a multi-objective artificial immune system capable of performing a multi-population search. As a heuristic search technique, artificial immune systems (AISs) can be considered a new computational paradigm inspired by the immunological system of vertebrates and designed to solve a wide range of optimization problems. During biclustering several objectives in conflict with each other have to be optimized simultaneously, so multi-objective optimization model is suitable for solving biclustering problem. Results Based on dynamic population, this paper proposes a novel dynamic multi-objective immune optimization biclustering (DMOIOB) algorithm to mine coherent patterns from microarray data. Experimental results on two common and public datasets of gene expression profiles show that our approach can effectively find significant localized structures related to sets of genes that show consistent expression patterns across subsets of experimental conditions. The mined patterns present a significant biological relevance in terms of related biological processes, components and molecular functions in a species-independent manner. Conclusions The proposed DMOIOB algorithm is an efficient tool to analyze large microarray datasets. It achieves a good diversity and rapid convergence

Two-dimensional polyaniline (C3N) from carbonized organic single crystals in solid state

The formation of 2D polyaniline (PANI) has attracted considerable interest due to its expected electronic and optoelectronic properties. Although PANI was discovered over 150 y ago, obtaining an atomically well-defined 2D PANI framework has been a longstanding challenge. Here, we describe the synthesis of 2D PANI via the direct pyrolysis of hexaaminobenzene trihydrochloride single crystals in solid state. The 2D PANI consists of three phenyl rings sharing six nitrogen atoms, and its structural unit has the empirical formula of C3N. The topological and electronic structures of the 2D PANI were revealed by scanning tunneling microscopy and scanning tunneling spectroscopy combined with a first-principle density functional theory calculation. The electronic properties of pristine 2D PANI films (undoped) showed ambipolar behaviors with a Dirac point of -37 V and an average conductivity of 0.72 S/cm. After doping with hydrochloric acid, the conductivity jumped to 1.41 x 10(3) S/cm, which is the highest value for doped PANI reported to date. Although the structure of 2D PANI is analogous to graphene, it contains uniformly distributed nitrogen atoms for multifunctionality; hence, we anticipate that 2D PANI has strong potential, from wet chemistry to device applications, beyond linear PANI and other 2D materials.116431Ysciescopu

On the jet formation through a leaky glottis

The present experimental study aims at analyzing the jet formation of the glottal jet flow using a model of a leaky glottis. Experiments were performed in a flow channel with dynamic models of the vocal folds in order to measure the glottal waveform and the velocity distribution in the supraglottal region using High Speed Particle Image Velocimetry (HSPIV). Proper Orthogonal Decomposition (POD) of the vortex Q-criterion was performed in order to detect the energetically most significant large-scale vortex structures and their appearance in the jet flow. The spectral analysis of the glottal waveforms results in an increased spectral decay with more prominent peaks at higher frequencies in the case of a leaky glottis compared to a completely closing reference case. Vortex induced fluctuation frequencies have similar spectral content in both cases as they appear as trains of vortex packets in a regular manner over the glottal cycle. However, when removing the false vocal folds in the leaky glottis model, coherence of vortex generation is lost over the motion cycle. Thus, the presence of the false vocal folds retains most of the vortex induced characteristics in the source spectrum even when the vocal folds do not close fully

Signal transducer and activator of transcription 3-mediated CD133 up-regulation contributes to promotion of hepatocellular carcinoma

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