Gauge invariant perturbation theory and non-critical string models of Yang-Mills theories

We carry out a gauge invariant analysis of certain perturbations of $D-2$-branes solutions of low energy string theories. We get generically a system of second order coupled differential equations, and show that only in very particular cases it is possible to reduce it to just one differential equation. Later, we apply it to a multi-parameter, generically singular family of constant dilaton solutions of non-critical string theories in $D$ dimensions, a generalization of that recently found in arXiv:0709.0471[hep-th]. According to arguments coming from the holographic gauge theory-gravity correspondence, and at least in some region of the parameters space, we obtain glue-ball spectra of Yang-Mills theories in diverse dimensions, putting special emphasis in the scalar metric perturbations not considered previously in the literature in the non critical setup. We compare our numerical results to those studied previously and to lattice results, finding qualitative and in some cases, tuning properly the parameters, quantitative agreement. These results seem to show some kind of universality of the models, as well as an irrelevance of the singular character of the solutions. We also develop the analysis for the T-dual, non trivial dilaton family of solutions, showing perfect agreement between them.Comment: A new reference added

On the Existence of Meta-stable Vacua in Klebanov-Strassler

We solve for the complete space of linearized deformations of the Klebanov-Strassler background consistent with the symmetries preserved by a stack of anti-D3 branes smeared on the $S^3$ of the deformed conifold. We find that the only solution whose UV physics is consistent with that of a perturbation produced by anti-D3 branes must have a singularity in the infrared, coming from NS and RR three-form field strengths whose energy density diverges. If this singularity is admissible, our solution describes the backreaction of the anti-D3 branes, and is thus likely to be dual to the conjectured metastable vacuum in the Klebanov-Strassler field theory. If this singularity is not admissible, then our analysis strongly suggests that anti-D3 branes do not give rise to metastable Klebanov-Strassler vacua, which would have dramatic consequences for some string theory constructions of de Sitter space. Key to this result is a simple, universal form for the force on a probe D3-brane in our ansatz.Comment: 35 pages, LaTeX. v2: further details provided regarding the IR singularity and the discussion modified accordingly. typos corrected, refs adde

Stringy effects in black hole decay

We compute the low energy decay rates of near-extremal three(four) charge black holes in five(four) dimensional N=4 string theory to sub-leading order in the large charge approximation. This involves studying stringy corrections to scattering amplitudes of a scalar field off a black hole. We adapt and use recently developed techniques to compute such amplitudes as near-horizon quantities. We then compare this with the corresponding calculation in the microscopic configuration carrying the same charges as the black hole. We find perfect agreement between the microscopic and macroscopic calculations; in the cases we study, the zero energy limit of the scattering cross section is equal to four times the Wald entropy of the black hole.Comment: 32 page

Linear, Deterministic, and Order-Invariant Initialization Methods for the K-Means Clustering Algorithm

Over the past five decades, k-means has become the clustering algorithm of choice in many application domains primarily due to its simplicity, time/space efficiency, and invariance to the ordering of the data points. Unfortunately, the algorithm's sensitivity to the initial selection of the cluster centers remains to be its most serious drawback. Numerous initialization methods have been proposed to address this drawback. Many of these methods, however, have time complexity superlinear in the number of data points, which makes them impractical for large data sets. On the other hand, linear methods are often random and/or sensitive to the ordering of the data points. These methods are generally unreliable in that the quality of their results is unpredictable. Therefore, it is common practice to perform multiple runs of such methods and take the output of the run that produces the best results. Such a practice, however, greatly increases the computational requirements of the otherwise highly efficient k-means algorithm. In this chapter, we investigate the empirical performance of six linear, deterministic (non-random), and order-invariant k-means initialization methods on a large and diverse collection of data sets from the UCI Machine Learning Repository. The results demonstrate that two relatively unknown hierarchical initialization methods due to Su and Dy outperform the remaining four methods with respect to two objective effectiveness criteria. In addition, a recent method due to Erisoglu et al. performs surprisingly poorly.Comment: 21 pages, 2 figures, 5 tables, Partitional Clustering Algorithms (Springer, 2014). arXiv admin note: substantial text overlap with arXiv:1304.7465, arXiv:1209.196

Analysis of gene expression data from non-small celllung carcinoma cell lines reveals distinct sub-classesfrom those identified at the phenotype level

Microarray data from cell lines of Non-Small Cell Lung Carcinoma (NSCLC) can be used to look for differences in gene expression between the cell lines derived from different tumour samples, and to investigate if these differences can be used to cluster the cell lines into distinct groups. Dividing the cell lines into classes can help to improve diagnosis and the development of screens for new drug candidates. The micro-array data is first subjected to quality control analysis and then subsequently normalised using three alternate methods to reduce the chances of differences being artefacts resulting from the normalisation process. The final clustering into sub-classes was carried out in a conservative manner such that subclasses were consistent across all three normalisation methods. If there is structure in the cell line population it was expected that this would agree with histological classifications, but this was not found to be the case. To check the biological consistency of the sub-classes the set of most strongly differentially expressed genes was be identified for each pair of clusters to check if the genes that most strongly define sub-classes have biological functions consistent with NSCLC

Chemical, functional, and structural properties of spent coffee grounds and coffee silverskin

Spent coffee grounds (SCG) and coffee silverskin (CS) represent a great pollution hazard if discharged into the environment. Taking this fact into account, the purpose of this study was to evaluate the chemical composition, functional properties, and structural characteristics of these agro-industrial residues in order to identify the characteristics that allow their reutilization in industrial processes. According to the results, SCG and CS are both of lignocellulosic nature. Sugars polymerized to their cellulose and hemicellulose fractions correspond to 51.5 and 40.45 % w/w, respectively; however, the hemicellulose sugars and their composition significantly differ from one residue to another. SCG and CS particles differ in terms of morphology and crystallinity, but both materials have very low porosity and similar melting point. In terms of functional properties, SCG and CS present good water and oil holding capacities, emulsion activity and stability, and antioxidant potential, being therefore great candidates for use on food and pharmaceutical fields.The authors acknowledge the financial support of the Science and Technology Foundation of Portugal (FCT) through the grant SFRH/BD/80948/2011 and the Strategic Project PEst-OE/EQB/LA0023/2013. The authors also thank the Project "BioInd - Biotechnology and Bioengineering for improved Industrial and Agro-Food processes", REF. NORTE-07-0124-FEDER-000028 co-funded by the Programa Operacional Regional do Norte (ON.2-O Novo Norte), QREN, FEDER. Thanks are also given to Prof. Jose J.M. Orfao, from the Department of Chemical Engineering, Universidade do Porto (Portugal), for his assistance with the porosity analyses

Prevalence of Cataract Surgery and Visual Outcomes in Indian Immigrants in Singapore: The Singapore Indian Eye Study

10.1371/journal.pone.0075584PLoS ONE810-POLN

Selection of the solvent and extraction conditions for maximum recovery of antioxidant phenolic compounds from coffee silverskin

The extraction of antioxidant phenolic compounds from coffee silverskin (CS) was studied. Firstly, the effect of different solvents (methanol, ethanol, acetone, and distilled water) on the production of antioxidant extracts was evaluated. All the extracts showed antioxidant activity (FRAP and DPPH assays), but those obtained with methanol and ethanol had significantly higher (p < 0.05) DPPH inhibition than the remaining ones. Due to the lower toxicity, ethanol was selected as extraction solvent, and further experiments were performed in order to define the solvent concentration, solvent/solid ratio, and time to maximize the extraction results. The best condition to produce an extract with high content of phenolic compounds (13 mg gallic acid equivalents/g CS) and antioxidant activity [DPPH = 18.24 μmol Trolox equivalents/g CS and FRAP = 0.83 mmol Fe(II)/g CS] was achieved when using 60 % ethanol in a ratio of 35 ml/g CS, during 30 min at 60–65 °C.This work was supported by the Portuguese Foundation for Science and Technology (FCT). The authors gratefully acknowledge Teresa Conde, student of Biological Engineering, for the help and interest in this work

A Multi-Stage Model for Fundamental Functional Properties in Primary Visual Cortex

Many neurons in mammalian primary visual cortex have properties such as sharp tuning for contour orientation, strong selectivity for motion direction, and insensitivity to stimulus polarity, that are not shared with their sub-cortical counterparts. Successful models have been developed for a number of these properties but in one case, direction selectivity, there is no consensus about underlying mechanisms. We here define a model that accounts for many of the empirical observations concerning direction selectivity. The model describes a single column of cat primary visual cortex and comprises a series of processing stages. Each neuron in the first cortical stage receives input from a small number of on-centre and off-centre relay cells in the lateral geniculate nucleus. Consistent with recent physiological evidence, the off-centre inputs to cortex precede the on-centre inputs by a small (∼4 ms) interval, and it is this difference that confers direction selectivity on model neurons. We show that the resulting model successfully matches the following empirical data: the proportion of cells that are direction selective; tilted spatiotemporal receptive fields; phase advance in the response to a stationary contrast-reversing grating stepped across the receptive field. The model also accounts for several other fundamental properties. Receptive fields have elongated subregions, orientation selectivity is strong, and the distribution of orientation tuning bandwidth across neurons is similar to that seen in the laboratory. Finally, neurons in the first stage have properties corresponding to simple cells, and more complex-like cells emerge in later stages. The results therefore show that a simple feed-forward model can account for a number of the fundamental properties of primary visual cortex