Linking superiority bias in the interpersonal and intergroup domains

The author conducted 2 studies to explore the link between superiority bias in the interpersonal and intergroup domains. Australian university students evaluated the extent to which various personality traits were more or less applicable to themselves than to other Australian university students in general. They then evaluated the extent to which the same traits were more or less applicable to Australians than to people from other countries in general. As expected, the more participants evaluated themselves as superior to other university students, the more they evaluated Australians as a whole as superior to people from other countries. This link between interpersonal and intergroup superiority biases explained 22.1% of variance in Study 1 and 33.6% of variance in Study 2. The author interprets the results of the 2 studies as support for fundamental principles of social identity theory: (a) that self-concept consists of not only one's personal self but also the social groups to which one belongs and (b) that people are motivated to view both levels of self in a relatively positive fashion.

Loyalty without Conformity: Tailoring Self-perception as a Means of Balancing Belonging and Differentiation

We argue that members of individualist cultures balance their desire to belong with their desire to be different by maintaining a self-image as being loyal but relatively immune to group influence. Consistent with this, in Study 1 there was a strong tendency for people to rate themselves as being more independent (i.e., less conformist) than other people in their college. College students also rated themselves as being highly loyal to the group, however no self - other discrepancies were found on this dimension. This is despite the fact that traits of loyalty were rated more positively than were traits of independence. Study 2 provided evidence that culture influences the pattern of self - other discrepancies. Whereas people from individualist countries self-enhance on independence dimensions, people from collectivist countries self-enhance on loyalty dimensions. Again, these effects could not be explained as being a function of how positive these traits were seen to be, suggesting a cultural explanation rather than a straight forward superiority bias explanation for the observed discrepancies in self - other ratings. Results are discussed in relation to the SCENT model.

How narcissistic self-construction sabotages their relationships: Accuracy and bias in partner perception

Trapped by their superordinate goal to maintain a grandiose self, narcissists navigate their relationships wishing to re-assure themselves of their specialness and superiority, using strategies bound to fail. Dyadic analyses of diary data (14 days, 83 couples) showed that narcissists focus on their partners’ shortcomings, becoming experts at detecting negative forms of support, while simultaneously minimizing their partner’s positive intentions. Partners of narcissists, in contrast, appear to have a positive bias in ongoing relationships and seem to compensate for some of the narcissists’ shortcomings. Narcissists’ focus on their own selfconstruction purposes also extends to their parenting roles. In a retrospective study, narcissistic mothers were found to demand superior performance, desiring to show-off their child, yet concurrently attributing their child’s success to themselves. They also exercise psychological control and role-reversal, requiring the child to cater to their needs, and to admire them, while simultaneously oblivious to their child’s needs and desires.

Hubble parameter reconstruction from a principal component analysis: minimizing the bias

Aims. A model-independent reconstruction of the cosmic expansion rate is essential to a robust analysis of cosmological observations. Our goal is to demonstrate that current data are able to provide reasonable constraints on the behavior of the Hubble parameter with redshift, independently of any cosmological model or underlying gravity theory. Methods. Using type Ia supernova data, we show that it is possible to analytically calculate the Fisher matrix components in a Hubble parameter analysis without assumptions about the energy content of the Universe. We used a principal component analysis to reconstruct the Hubble parameter as a linear combination of the Fisher matrix eigenvectors (principal components). To suppress the bias introduced by the high redshift behavior of the components, we considered the value of the Hubble parameter at high redshift as a free parameter. We first tested our procedure using a mock sample of type Ia supernova observations, we then applied it to the real data compiled by the Sloan Digital Sky Survey (SDSS) group. Results. In the mock sample analysis, we demonstrate that it is possible to drastically suppress the bias introduced by the high redshift behavior of the principal components. Applying our procedure to the real data, we show that it allows us to determine the behavior of the Hubble parameter with reasonable uncertainty, without introducing any ad-hoc parameterizations. Beyond that, our reconstruction agrees with completely independent measurements of the Hubble parameter obtained from red-envelope galaxies.

Experimental studies of di-jet survival and surface emission bias in Au plus Au collisions via angular correlations with respect to back-to-back leading hadrons

We report first results from an analysis based on a new multi-hadron correlation technique, exploring jet-medium interactions and di-jet surface emission bias at the BNL Relativistic Heavy Ion Collider (RHIC). Pairs of back-to-back high-transverse-momentum hadrons are used for triggers to study associated hadron distributions. In contrast with two-and three-particle correlations with a single trigger with similar kinematic selections, the associated hadron distribution of both trigger sides reveals no modification in either relative pseudorapidity Delta eta or relative azimuthal angle Delta phi from d + Au to central Au + Au collisions. We determine associated hadron yields and spectra as well as production rates for such correlated back-to-back triggers to gain additional insights on medium properties.

Low-bias negative differential resistance in graphene nanoribbon superlattices

We theoretically investigate negative differential resistance (NDR) for ballistic transport in semiconducting armchair graphene nanoribbon (aGNR) superlattices (5 to 20 barriers) at low bias voltages V(SD) < 500 mV. We combine the graphene Dirac Hamiltonian with the Landauer-Buttiker formalism to calculate the current I(SD) through the system. We find three distinct transport regimes in which NDR occurs: (i) a ""classical"" regime for wide layers, through which the transport across band gaps is strongly suppressed, leading to alternating regions of nearly unity and zero transmission probabilities as a function of V(SD) due to crossing of band gaps from different layers; (ii) a quantum regime dominated by superlattice miniband conduction, with current suppression arising from the misalignment of miniband states with increasing V(SD); and (iii) a Wannier-Stark ladder regime with current peaks occurring at the crossings of Wannier-Stark rungs from distinct ladders. We observe NDR at voltage biases as low as 10 mV with a high current density, making the aGNR superlattices attractive for device applications.

Universal zero-bias conductance through a quantum wire side-coupled to a quantum dot

A numerical renormalization-group study of the conductance through a quantum wire containing noninteracting electrons side-coupled to a quantum dot is reported. The temperature and the dot-energy dependence of the conductance are examined in the light of a recently derived linear mapping between the temperature-dependent conductance and the universal function describing the conductance for the symmetric Anderson model of a quantum wire with an embedded quantum dot. Two conduction paths, one traversing the wire, the other a bypass through the quantum dot, are identified. A gate potential applied to the quantum wire is shown to control the current through the bypass. When the potential favors transport through the wire, the conductance in the Kondo regime rises from nearly zero at low temperatures to nearly ballistic at high temperatures. When it favors the dot, the pattern is reversed: the conductance decays from nearly ballistic to nearly zero. When comparable currents flow through the two channels, the conductance is nearly temperature independent in the Kondo regime, and Fano antiresonances in the fixed-temperature plots of the conductance as a function of the dot-energy signal interference between them. Throughout the Kondo regime and, at low temperatures, even in the mixed-valence regime, the numerical data are in excellent agreement with the universal mapping.

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.

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.