Universal zero-bias conductance for the single-electron transistor

The thermal dependence of the zero-bias conductance for the single electron transistor is the target of two independent renormalization-group approaches, both based on the spin-degenerate Anderson impurity model. The first approach, an analytical derivation, maps the Kondo-regime conductance onto the universal conductance function for the particle-hole symmetric model. Linear, the mapping is parametrized by the Kondo temperature and the charge in the Kondo cloud. The second approach, a numerical renormalization-group computation of the conductance as a function the temperature and applied gate voltages offers a comprehensive view of zero-bias charge transport through the device. The first approach is exact in the Kondo regime; the second, essentially exact throughout the parametric space of the model. For illustrative purposes, conductance curves resulting from the two approaches are compared.

Short Cognitive Performance Test: Diagnostic Accuracy and Education Bias in Older Brazilian Adults

The ""Short Cognitive Performance Test"" (Syndrom Kurztest, SKT) is a cognitive screening battery designed to detect memory and attention deficits. The aim of this study was to evaluate the diagnostic accuracy of the SKT as a screening tool for mild cognitive impairment (MCI) and dementia. A total of 46 patients with Alzheimer`s disease (AD), 82 with MCI, and 56 healthy controls were included in the study. Patients and controls were allocated into two groups according to educational level (< 8 years or > 8 years). ROC analyses suggested that the SKT adequately discriminates AD from non-demented subjects (MCI and controls), irrespective of the education group. The test had good sensitivity to discriminate MCI from unimpaired controls in the sub-sample of individuals with more than 8 years of schooling. Our findings suggest that the SKT is a good screening test for cognitive impairment and dementia. However, test results must be interpreted with caution when administered to less-educated individuals.

Residual stresses in titanium nitride thin films obtained with step variation of substrate bias voltage during deposition

In this work, a series of depositions of titanium nitride (TiN) films on M2 and D2 steel substrates were conducted in a Triode Magnetron Sputtering chamber. The temperature; gas flow and pressure were kept constant during each run. The substrate bias was either decreased or increased in a sequence of steps. Residual stress measurements were later conducted through the grazing X-ray diffraction method. Different incident angles were used in order to change the penetration depth and to obtain values of residual stress at different film depths. A model described by Dolle was adapted as an attempt to calculate the values of residual stress at each incident angle as a function of the value from each individual layer. Stress results indicated that the decrease in bias voltage during the deposition has produced compressive residual stress gradients through the film thickness. On the other hand, much less pronounced gradients were found in one of the films deposited with increasing bias voltage. (C) 2010 Elsevier B.V. All rights reserved.

TiAlN coatings deposited by triode magnetron sputtering varying the bias voltage

TiAlN films were deposited on AISI O1 tool steel using a triode magnetron sputtering system. The bias voltage effect on the composition, thickness, crystallography, microstructure, hardness and adhesion strength was investigated. The coatings thickness and elemental composition analyses were carried out using scanning electron microscopy (SEM) together with energy dispersive X-ray (EDS). The re-sputtering effect due to the high-energy ions bombardment on the film surface influenced the coatings thickness. The films crystallography was investigated using X-ray diffraction characterization. The X-ray diffraction (XRD) data show that TiAlN coatings were crystallized in the cubic NaCl B1 structure, with orientations in the {111}, {200} {220} and {311} crystallographic planes. The surface morphology (roughness and grain size) of TiAlN coatings was investigated by atomic force microscopy (AFM). By increasing the substrate bias voltage from -40 to -150 V, hardness decreased from 32 GPa to 19 GPa. Scratch tester was used for measuring the critical loads and for measuring the adhesion. (C) 2011 Elsevier B. V. All rights reserved.

Extensions of discrete triangular distributions and boundary bias in kernel estimation for discrete functions

Asymmetric discrete triangular distributions are introduced in order to extend the symmetric ones serving for discrete associated kernels in the nonparametric estimation for discrete functions. The extension from one to two orders around the mode provides a large family of discrete distributions having a finite support. Establishing a bridge between Dirac and discrete uniform distributions, some different shapes are also obtained and their properties are investigated. In particular, the mean and variance are pointed out. Applications to discrete kernel estimators are given with a solution to a boundary bias problem. (C) 2010 Elsevier B.V. All rights reserved.

Bias-corrected Pearson estimating functions for Taylor`s power law applied to benthic macrofauna data

Estimation of Taylor`s power law for species abundance data may be performed by linear regression of the log empirical variances on the log means, but this method suffers from a problem of bias for sparse data. We show that the bias may be reduced by using a bias-corrected Pearson estimating function. Furthermore, we investigate a more general regression model allowing for site-specific covariates. This method may be efficiently implemented using a Newton scoring algorithm, with standard errors calculated from the inverse Godambe information matrix. The method is applied to a set of biomass data for benthic macrofauna from two Danish estuaries. (C) 2011 Elsevier B.V. All rights reserved.

Survey of Listeria spp. in matched clinical, food and refrigerator samples at home level in Brazil

Listeria monocytogenes is a bacterial pathogen that represents a serious threat during pregnancy and several cases of listeriosis have been linked to the consumption of contaminated foods worldwide. In Brazil, there is no report of foodborne listeriosis, despite some sporadic cases of infection by this bacterium occur. In general in our country, there is no awareness of medical personnel to instruct moms-to-be to avoid high risk foods. In the present study, a total of 141 samples were surveyed for the presence of Listeria spp., including cervicovaginal samples of patients, foods and home refrigerators. No clinical sample was positive for Listeria spp., but it was isolated from two refrigerators. L. monocytogenes was detected in two food samples out of five positive ones for Listeria spp. In conclusion, it was shown the presence of contaminated food items at home level and the lack of information on the risks of listeriosis, indicating the need of implementation of food safety education programs. (C) 2007 Elsevier Ltd. All rights reserved.

Go home fascist

Girls with placard during visit of former South Vietnamese vice president Nguyen Cao Ky to Brisbane, Australia in January 1967. Placard reads Go home fascist

Go home fascist 2

Girl with placard Go home fascist during visit of former South Vietnamese vice president Nguyen Cao Ky to Brisbane, Australia in January 1967.

Bringing Us Home: Cohousing and the Environmental Possibilities of Reuniting People with Neighbourhoods

Cohousing is a form of intentional community which has made a significant contribution to urban environmentalism by recreating the neighbourhood as the setting for engagement with the world beyond the front door.

Selection bias in gene extraction on the basis of microarray gene-expression data

In the context of cancer diagnosis and treatment, we consider the problem of constructing an accurate prediction rule on the basis of a relatively small number of tumor tissue samples of known type containing the expression data on very many (possibly thousands) genes. Recently, results have been presented in the literature suggesting that it is possible to construct a prediction rule from only a few genes such that it has a negligible prediction error rate. However, in these results the test error or the leave-one-out cross-validated error is calculated without allowance for the selection bias. There is no allowance because the rule is either tested on tissue samples that were used in the first instance to select the genes being used in the rule or because the cross-validation of the rule is not external to the selection process; that is, gene selection is not performed in training the rule at each stage of the cross-validation process. We describe how in practice the selection bias can be assessed and corrected for by either performing a cross-validation or applying the bootstrap external to the selection process. We recommend using 10-fold rather than leave-one-out cross-validation, and concerning the bootstrap, we suggest using the so-called. 632+ bootstrap error estimate designed to handle overfitted prediction rules. Using two published data sets, we demonstrate that when correction is made for the selection bias, the cross-validated error is no longer zero for a subset of only a few genes.