Visualization of the Significant Explicative Categories using Catanova Method and Non-Symmetrical Correspondence Analysis for Evaluation of Passenger Satisfaction

ANalysis Of VAriance (ANOVA) is a method to decompose the total variation of the observations into sum of variations due to different factors and the residual component. When the data are nominal, the usual approach of considering the total variation in response variable as measure of dispersion about the mean is not well defined. Light and Margolin (1971) proposed CATegorical ANalysis Of VAriance (CATANOVA), to analyze the categorical data. Onukogu (1985) extended the CATANOVA method to two-way classified nominal data. The components (sums of squares) are, however, not orthogonal. Singh (1996) developed a CATANOVA procedure that gives orthogonal sums of squares and defined test statistics and their asymptotic null distributions. In order to study which exploratory categories are influential factors for the response variable we propose to apply Non-Symmetrical Correspondence Analysis (D'Ambra and Lauro, 1989) on significant components. Finally, we illustrate the analysis numerically, with a practical example

Spectrally accurate space-time solution of Hamiltonian PDEs

Recently, the numerical solution of multi-frequency, highly-oscillatory Hamiltonian problems has been attacked by using Hamiltonian Boundary Value Methods (HBVMs) as spectral methods in time. When the problem derives from the space semi- discretization of (possibly Hamiltonian) partial differential equations (PDEs), the resulting problem may be stiffly-oscillatory, rather than highly-oscillatory. In such a case, a different implementation of the methods is needed, in order to gain the maximum efficiency.Comment: 17 pages, 3 figure

Novel sulfur and selenium containing bis-α-amino acids from 4-hydroxyproline

The synthesis of new substituted prolines carrying at C-4 a second α-amino acid residue is reported. The amino acid, l-cysteine or l-selenocysteine, is linked to the proline ring through the sulfur or the selenium atom, respectively. The products were prepared with different stereochemistry at C-4, in few and clean high-yielding steps, with suitable protections for solid phase applications. The introduction of both sulfur and selenium atoms at C-4 of the proline ring seems to enhance significantly the cis geometry at the prolyl amide bond

Usefulness of image guidance in the surgical treatment of petrous apex cholesterol granuloma

The petrous apex is a pyramid-shaped structure, located medial to the inner ear and the intrapetrous segment of the internal carotid artery. Lesions of the petrous apex can be surgically treated through different surgical routes. Because of the important neurovascular structures located inside the temporal bone, anatomical 3D knowledge is paramount. For this reason, image-guided surgery could represent a useful tool. We report the case of a young woman who came to our observation for a trigeminal neuralgia due to a petrous apex cholesterol granuloma. The lesion was treated through the placement of a drainage tube via an infracochlear approach, with the aid of neuronavigation and intraoperative MRI. Preoperative CT scan images and intraoperative MRI images were fused for surgical planning. The accuracy of the neuronavigation system has proved to be good, and the safety of the procedure was enhanced. Therefore, neuronavigation and intraoperative MRI, though not available in all neurootological centres, should be considered useful tools in these challenging procedures

Evocative gene-environment correlation between genetic risk for schizophrenia and bullying victimization

Bullying exposure concerns over 10% of adolescents in Europe. Moreover, bullying victimization is heritable and victims are liable to psychotic symptoms, partly because of shared heritability with psychosis. The genetic component of bullying victimization has been proposed to involve the social reactions elicited by victims – a mechanism called “evocative gene-environment correlation”. We hypothesized that genetic risk for schizophrenia, a heritable disease also associated with social stress during childhood and adolescence, is related with social experiences during adolescence and is involved in the risk of developing psychotic symptoms. We studied 908 individuals of the TRAILS sample and found that 13-14-year-old adolescents with greater genetic risk for schizophrenia are more exposed to bullying assessed via peer nomination scores than their peers with lower genetic risk. Importantly, bullying victimization mediated the path from genetic risk to the frequency of psychotic symptoms about three years later. These findings provide evidence of a previously unreported form of gene-environment interplay that may be a mechanism of risk for psychosis and schizophrenia. To the extent that genetic risk translation into clinical symptoms is mediated by environmental risk factors, this evidence supports mental health prevention aimed at antagonizing bullying victimization in vulnerable individuals

Neural network determination of parton distributions: the nonsinglet case

We provide a determination of the isotriplet quark distribution from available deep--inelastic data using neural networks. We give a general introduction to the neural network approach to parton distributions, which provides a solution to the problem of constructing a faithful and unbiased probability distribution of parton densities based on available experimental information. We discuss in detail the techniques which are necessary in order to construct a Monte Carlo representation of the data, to construct and evolve neural parton distributions, and to train them in such a way that the correct statistical features of the data are reproduced. We present the results of the application of this method to the determination of the nonsinglet quark distribution up to next--to--next--to--leading order, and compare them with those obtained using other approaches.Comment: 46 pages, 18 figures, LaTeX with JHEP3 clas

Generalized log odds ratio analysis for the association in two-way contingency table.

The odds ratio is a measure of association used both for the analysis of a contingency table and an contingency table, where I and J are bigger than 2. Nevertheless, the total number of odds ratios to check grows with I and J and several methods have been developed to summarize them. In the present paper we present a general framework for the analysis of the complete set of log odds ratio. Particularly we propose and connect two different methodologies performed on two different data sets. Moreover starting from these methodologies, we focus our attention on the factorial representation of the log odds ratios

No surviving evolved companions to the progenitor of supernova SN 1006

Type Ia supernovae are thought to occur as a white dwarf made of carbon and oxygen accretes sufficient mass to trigger a thermonuclear explosion$^{1}$. The accretion could occur slowly from an unevolved (main-sequence) or evolved (subgiant or giant) star$^{2,3}$, that being dubbed the single-degenerate channel, or rapidly as it breaks up a smaller orbiting white dwarf (the double- degenerate channel)$^{3,4}$. Obviously, a companion will survive the explosion only in the single-degenerate channel$^{5}$. Both channels might contribute to the production of type Ia supernovae$^{6,7}$ but their relative proportions still remain a fundamental puzzle in astronomy. Previous searches for remnant companions have revealed one possible case for SN 1572$^{8,9}$, though that has been criticized$^{10}$. More recently, observations have restricted surviving companions to be small, main-sequence stars$^{11,12,13}$, ruling out giant companions, though still allowing the single-degenerate channel. Here we report the result of a search for surviving companions to the progenitor of SN 1006$^{14}$. None of the stars within 4' of the apparent site of the explosion is associated with the supernova remnant, so we can firmly exclude all giant and subgiant companions to the progenitor. Combined with the previous results, less than 20 per cent of type Iae occur through the single degenerate channel.Comment: Published as a letter in Nature (2012 September 27

Neural network approach to parton distributions fitting

We will show an application of neural networks to extract information on the structure of hadrons. A Monte Carlo over experimental data is performed to correctly reproduce data errors and correlations. A neural network is then trained on each Monte Carlo replica via a genetic algorithm. Results on the proton and deuteron structure functions, and on the nonsinglet parton distribution will be shown.Comment: 4 pages, 5 eps figures. Talk given by Andrea Piccione at the "X International Workshop on Advanced Computing and Analysis Techniques in Physics Research", ACAT 2005, DESY-Zeuthen, Germany, 22-27 May 2005. Corrected fig.