Subgroup relations: A comparison of mutual intergroup differentiation and common ingroup identity models of prejudice reduction

Two studies examined relations between groups (humanities and math-science students) that implicitly or explicitly share a common superordinate category (university student). In Experiment 1, 178 participants performed a noninteractive decision-making task during which category salience was manipulated in a 2 (superordinate category salience) x 2 (subordinate category salience) between-groups design. Consistent with the mutual intergroup differentiation model, participants for whom both categories were salient exhibited the lowest levels of bias, whereas bias was strongest when the superordinate category alone was made salient. This pattern of results was replicated in Experiment 2 (N = 135). In addition, Experiment 2 demonstrated that members of subgroups that are nested within a superordinate category are more sensitive to how the superordinate category is represented than are members of subgroups that extend beyond the boundaries of the superordinate category.

Incorporating phase retardation effects into radiofrequency resonator models: application to magnetic resonance microscopy

A method is presented for including path propagation effects into models of radiofrequency resonators for use in magnetic resonance imaging. The method is based on the use of Helmholtz retarded potentials and extends our previous work on current density models of resonators based on novel inverse finite Hilbert transform solutions to the requisite integral equations. Radiofrequency phase retardation effects are most pronounced at high field strengths (frequencies) as are static field perturbations due to the magnetic materials in the resonators themselves. Both of these effects are investigated and a novel resonator structure presented for use in magnetic resonance microscopy.

Empirical catchment-wide rainfall erosivity models for two rivers in the humid tropics of Australia

The concept of rainfall erosivity is extended to the estimation of catchment sediment yield and its variation over time. Five different formulations of rainfall erosivity indices, using annual, monthly and daily rainfall data, are proposed and tested on two catchments in the humid tropics of Australia. Rainfall erosivity indices, using simple power functions of annual and daily rainfall amounts, were found to be adequate in describing the interannual and seasonal variation of catchment sediment yield. The parameter values of these rainfall erosivity indices for catchment sediment yield are broadly similar to those for rainfall erosivity models in relation to the R-factor in the Universal Soil Loss Equation.

Integrable Kondo impurities in one-dimensional extended Hubbard models

Three kinds of integrable Kondo problems in one-dimensional extended Hubbard models are studied by means of the boundary graded quantum inverse scattering method. The boundary K matrices depending on the local moments of the impurities are presented as a nontrivial realization of the graded reflection equation algebras acting in a (2s alpha + 1)-dimensional impurity Hilbert space. Furthermore, these models are solved using the algebraic Bethe ansatz method, and the Bethe ansatz equations are obtained.

Swapping space for time and unfair tests of ecological models

Testing ecological models for management is an increasingly important part of the maturation of ecology as an applied science. Consequently, we need to work at applying fair tests of models with adequate data. We demonstrate that a recent test of a discrete time, stochastic model was biased towards falsifying the predictions. If the model was a perfect description of reality, the test falsified the predictions 84% of the time. We introduce an alternative testing procedure for stochastic models, and show that it falsifies the predictions only 5% of the time when the model is a perfect description of reality. The example is used as a point of departure to discuss some of the philosophical aspects of model testing.

An update on genetic, structural and functional studies of arylamine N-acetyltransferases in eucaryotes and procaryotes

Arylamine N-acetyltransferase (NAT) was first identified as the inactivator of the anti-tubercular drug isoniazid, The enzyme was shown to catalyse the transfer of an acetyl group from acetyl-CoA to the terminal nitrogen of the hydrazine drug. The rate of inactivation of isoniazid was polymorphically distributed in the population and was one of the first examples of pharmacogenetic variation, NAT was identified recently in Mycobacterium tuberculosis and is a candidate for; modulating the response to isoniazid, Genome sequences have revealed many homologous members of this unique family of enzymes. The first three-dimensional structure of a member of the NAT family identifies a catalytic triad consisting of aspartate, histidine and cysteine proposed to form the activation mechanism. So far, all procaryotic NATs resemble the human enzyme which acetylates isoniazid (NAT2), Human NAT2 is characteristic of drug-metabolizing enzymes: it is found in liver and intestine, In humans and other mammals, there are up to three different isoenzymes. If only one isoenzyme is present, it is like human NAT1. Human NAT1 and its murine equivalent specifically acetylate the folate catabolite p-amino-benzoylglutamate. NAT1 and its murine homologue each have a ubiquitous tissue distribution and are expressed early in development at the blastocyst stage, During murine embryonic development, NAT is expressed in the developing neural tube. The proposed endogenous role of NAT in folate metabolism, and its multi-allelic nature, indicate that its role in development should be assessed further.

A novel genetic locus for low renin hypertension: familial hyperaldosteronism type II maps to chromosome 7 (7p22)

Familial hyperaldosteronism type II (FH-II) is caused by adrenocortical hyperplasia or aldosteronoma or both and is frequently transmitted in an autosomal dominant fashion. Unlike FH type I (FI-I-I), which results from fusion of the CYP11B1 and CYP11B2 genes, hyperaldosteronism in FH-II is not glucocorticoid remediable. A large family with FH-II was used for a genome wide search and its members were evaluated by measuring the aldosterone:renin ratio. In those with an increased ratio, FH-II was confirmed by fludrocortisone suppression testing. After excluding most of the genome, genetic linkage was identified with a maximum two point lod score of 3.26 at theta =0, between FH-II in this family and the polymorphic markers D7S511, D7S517, and GATA24F03 on chromosome 7,a region that corresponds to cytogenetic band 7p22. This is the first identified locus for FH-II; its molecular elucidation may provide further insight into the aetiology of primary aldosteronism.

Evolution of stress deficit and changing rates of seismicity in cellular automaton models of earthquake faults

We investigate the internal dynamics of two cellular automaton models with heterogeneous strength fields and differing nearest neighbour laws. One model is a crack-like automaton, transferring ail stress from a rupture zone to the surroundings. The other automaton is a partial stress drop automaton, transferring only a fraction of the stress within a rupture zone to the surroundings. To study evolution of stress, the mean spectral density. f(k(r)) of a stress deficit held is: examined prior to, and immediately following ruptures in both models. Both models display a power-law relationship between f(k(r)) and spatial wavenumber (k(r)) of the form f(k(r)) similar tok(r)(-beta). In the crack model, the evolution of stress deficit is consistent with cyclic approach to, and retreat from a critical state in which large events occur. The approach to criticality is driven by tectonic loading. Short-range stress transfer in the model does not affect the approach to criticality of broad regions in the model. The evolution of stress deficit in the partial stress drop model is consistent with small fluctuations about a mean state of high stress, behaviour indicative of a self-organised critical system. Despite statistics similar to natural earthquakes these simplified models lack a physical basis. physically motivated models of earthquakes also display dynamical complexity similar to that of a critical point system. Studies of dynamical complexity in physical models of earthquakes may lead to advancement towards a physical theory for earthquakes.

Accelerating seismic energy release and evolution of event time and size statistics: Results from two heterogeneous cellular automaton models

The evolution of event time and size statistics in two heterogeneous cellular automaton models of earthquake behavior are studied and compared to the evolution of these quantities during observed periods of accelerating seismic energy release Drier to large earthquakes. The two automata have different nearest neighbor laws, one of which produces self-organized critical (SOC) behavior (PSD model) and the other which produces quasi-periodic large events (crack model). In the PSD model periods of accelerating energy release before large events are rare. In the crack model, many large events are preceded by periods of accelerating energy release. When compared to randomized event catalogs, accelerating energy release before large events occurs more often than random in the crack model but less often than random in the PSD model; it is easier to tell the crack and PSD model results apart from each other than to tell either model apart from a random catalog. The evolution of event sizes during the accelerating energy release sequences in all models is compared to that of observed sequences. The accelerating energy release sequences in the crack model consist of an increase in the rate of events of all sizes, consistent with observations from a small number of natural cases, however inconsistent with a larger number of cases in which there is an increase in the rate of only moderate-sized events. On average, no increase in the rate of events of any size is seen before large events in the PSD model.

Minimum-order stable recursive filter design via the genetic algorithm approach

In this paper, the minimum-order stable recursive filter design problem is proposed and investigated. This problem is playing an important role in pipeline implementation sin signal processing. Here, the existence of a high-order stable recursive filter is proved theoretically, in which the upper bound for the highest order of stable filters is given. Then the minimum-order stable linear predictor is obtained via solving an optimization problem. In this paper, the popular genetic algorithm approach is adopted since it is a heuristic probabilistic optimization technique and has been widely used in engineering designs. Finally, an illustrative example is sued to show the effectiveness of the proposed algorithm.