Zenithal bistability in a nematic liquid crystal device with a monostable surface condition

The ground-state director configurations in a grating-aligned, zenithally bistable nematic device are calculated in two dimensions using a Q tensor approach. The director profiles generated are well described by a one-dimensional variation of the director across the width of the device, with the distorted region near the grating replaced by an effective surface anchoring energy. This work shows that device bistability can in fact be achieved by using a monostable surface term in the one-dimensional model. This implies that is should be possible to construct a device showing zenithal bistability without the need for a micropatterned surface

Resampling methods for parameter-free and robust feature selection with mutual information

Combining the mutual information criterion with a forward feature selection strategy offers a good trade-off between optimality of the selected feature subset and computation time. However, it requires to set the parameter(s) of the mutual information estimator and to determine when to halt the forward procedure. These two choices are difficult to make because, as the dimensionality of the subset increases, the estimation of the mutual information becomes less and less reliable. This paper proposes to use resampling methods, a K-fold cross-validation and the permutation test, to address both issues. The resampling methods bring information about the variance of the estimator, information which can then be used to automatically set the parameter and to calculate a threshold to stop the forward procedure. The procedure is illustrated on a synthetic dataset as well as on real-world examples

Is This a Joke? Detecting Humor in Spanish Tweets

While humor has been historically studied from a psychological, cognitive and linguistic standpoint, its study from a computational perspective is an area yet to be explored in Computational Linguistics. There exist some previous works, but a characterization of humor that allows its automatic recognition and generation is far from being specified. In this work we build a crowdsourced corpus of labeled tweets, annotated according to its humor value, letting the annotators subjectively decide which are humorous. A humor classifier for Spanish tweets is assembled based on supervised learning, reaching a precision of 84% and a recall of 69%.Comment: Preprint version, without referra

Current Induced Fingering Instability in Magnetic Domain Walls

The shape instability of magnetic domain walls under current is investigated in a ferromagnetic (Ga,Mn)(As,P) film with perpendicular anisotropy. Domain wall motion is driven by the spin transfer torque mechanism. A current density gradient is found either to stabilize domains with walls perpendicular to current lines or to produce finger-like patterns, depending on the domain wall motion direction. The instability mechanism is shown to result from the non-adiabatic contribution of the spin transfer torque mechanism.Comment: 5 pages, 3 figures + supplementary material

Overcoming Calibration Problems in Pattern Labeling with Pairwise Ratings: Application to Personality Traits

We address the problem of calibration of workers whose task is to label patterns with continuous variables, which arises for instance in labeling images of videos of humans with continuous traits. Worker bias is particularly difficult to evaluate and correct when many workers contribute just a few labels, a situation arising typically when labeling is crowd-sourced. In the scenario of labeling short videos of people facing a camera with personality traits, we evaluate the feasibility of the pairwise ranking method to alleviate bias problems. Workers are exposed to pairs of videos at a time and must order by preference. The variable levels are reconstructed by fitting a Bradley-Terry-Luce model with maximum likelihood. This method may at first sight, seem prohibitively expensive because for N videos, p=N(N−1)/2 pairs must be potentially processed by workers rather that N videos. However, by performing extensive simulations, we determine an empirical law for the scaling of the number of pairs needed as a function of the number of videos in order to achieve a given accuracy of score reconstruction and show that the pairwise method is affordable. We apply the method to the labeling of a large scale dataset of 10,000 videos used in the ChaLearn Apparent Personality Trait challenge

Magnetic pair-breaking in superconducting (Ba,K)BiO_3 investigated by magnetotunneling

The de Gennes and Maki theory of gapless superconductivity for dirty superconductors is used to interpret the tunneling measurements on the strongly type-II high-Tc oxide-superconductor Ba1-xKxBiO3 in high magnetic fields up to 30 Tesla. We show that this theory is applicable at all temperatures and in a wide range of magnetic fields starting from 50 percent of the upper critical field Bc2. In this magnetic field range the measured superconducting density of states (DOS) has the simple energy dependence as predicted by de Gennes from which the temperature dependence of the pair-breaking parameter alpha(T), or Bc2(T), has been obtained. The deduced temperature dependence of Bc2(T) follows the Werthamer-Helfand-Hohenberg prediction for classical type-II superconductors in agreement with our previous direct determination. The amplitudes of the deviations in the DOS depend on the magnetic field via the spatially averaged superconducting order parameter which has a square-root dependence on the magnetic field. Finally, the second Ginzburg-Landau parameter kappa2(T) has been determined from the experimental data.Comment: 11 pages, 5 figure

A Comparison of U. S. and European University-Industry Relations in the Life Sciences

We draw on diverse data sets to compare the institutional organization of upstream life science research across the United States and Europe. Understanding cross-national differences in the organization of innovative labor in the life sciences requires attention to the structure and evolution of biomedical networks involving public research organizations (universities, government laboratories, nonprofit research institutes, and research hospitals), science-based biotechnology firms, and multinational pharmaceutical corporations. We use network visualization methods and correspondence analyses to demonstrate that innovative research in biomedicine has its origins in regional clusters in the United States and in European nations. But the scientific and organizational composition of these regions varies in consequential ways. In the United States, public research organizations and small firms conduct R&D across multiple therapeutic areas and stages of the development process. Ties within and across these regions link small firms and diverse public institutions, contributing to the development of a robust national network. In contrast, the European story is one of regional specialization with a less diverse group of public research organizations working in a smaller number of therapeutic areas. European institutes develop local connections to small firms working on similar scientific problems, while cross-national linkages of European regional clusters typically involve large pharmaceutical corporations. We show that the roles of large and small firms differ in the United States and Europe, arguing that the greater heterogeneity of the U. S. system is based on much closer integration of basic science and clinical development

Large-scale Nonlinear Variable Selection via Kernel Random Features

We propose a new method for input variable selection in nonlinear regression. The method is embedded into a kernel regression machine that can model general nonlinear functions, not being a priori limited to additive models. This is the first kernel-based variable selection method applicable to large datasets. It sidesteps the typical poor scaling properties of kernel methods by mapping the inputs into a relatively low-dimensional space of random features. The algorithm discovers the variables relevant for the regression task together with learning the prediction model through learning the appropriate nonlinear random feature maps. We demonstrate the outstanding performance of our method on a set of large-scale synthetic and real datasets.Comment: Final version for proceedings of ECML/PKDD 201

Orientational instabilities in nematics with weak anchoring under combined action of steady flow and external fields

We study the homogeneous and the spatially periodic instabilities in a nematic liquid crystal layer subjected to steady plane {\em Couette} or {\em Poiseuille} flow. The initial director orientation is perpendicular to the flow plane. Weak anchoring at the confining plates and the influence of the external {\em electric} and/or {\em magnetic} field are taken into account. Approximate expressions for the critical shear rate are presented and compared with semi-analytical solutions in case of Couette flow and numerical solutions of the full set of nematodynamic equations for Poiseuille flow. In particular the dependence of the type of instability and the threshold on the azimuthal and the polar anchoring strength and external fields is analysed.Comment: 12 pages, 6 figure

Application of Volcano Plots in Analyses of mRNA Differential Expressions with Microarrays

Volcano plot displays unstandardized signal (e.g. log-fold-change) against noise-adjusted/standardized signal (e.g. t-statistic or -log10(p-value) from the t test). We review the basic and an interactive use of the volcano plot, and its crucial role in understanding the regularized t-statistic. The joint filtering gene selection criterion based on regularized statistics has a curved discriminant line in the volcano plot, as compared to the two perpendicular lines for the "double filtering" criterion. This review attempts to provide an unifying framework for discussions on alternative measures of differential expression, improved methods for estimating variance, and visual display of a microarray analysis result. We also discuss the possibility to apply volcano plots to other fields beyond microarray.Comment: 8 figure