Attachment, Self-Esteem, Worldviews, and Terror Management: Evidence for a Tripartite Security System.

On the basis of prior work integrating attachment theory and terror management theory, the authors propose a model of a tripartite security system consisting of dynamically interrelated attachment, self-esteem, and worldview processes. Four studies are presented that, combined with existing evidence, support the prediction derived from the model that threats to one component of the security system result in compensatory defensive activation of other components. Further, the authors predicted and found that individual differences in attachment style moderate the defenses. In Studies 1 and 2, attachment threats motivated worldview defense among anxiously attached participants and motivated self-enhancement (especially among avoidant participants), effects similar to those caused by mortality salience. In Studies 3 and 4, a worldview threat and a self-esteem threat caused attachment-related proximity seeking among fearful participants and avoidance of proximity among dismissing participants. The authors' model provides an overarching framework within which to study attachment, self-esteem, and worldviews. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

The Validity of the Five-Factor Model Prototypes for Personality Disorders in Two Clinical Samples.

The authors examined the validity of D. R. Lynam and T. A. Widiger's (2001) prototypes for personality disorders (PDs) derived from the facets of the 5-factor model (FFM) of personality in 2 clinical samples. In the 1st sample (N = 94), there was good agreement between the prototypes generated by experts and the profiles reported by patients. These FFM PD similarity scores also demonstrated good convergent and discriminant validity with results from a semistructured interview and a self-report measure of Axis II pathology. In the 2nd sample (N = 132), the FFM PD similarity scores demonstrated excellent longitudinal stability and good predictive validity with regard to consensus ratings of PD features. The implications of these findings are discussed. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Overconfidence in Interval Estimates.

Judges were asked to make numerical estimates (e.g., "In what year was the first flight of a hot air balloon?"). Judges provided high and low estimates such that they were X% sure that the correct answer lay between them. They exhibited substantial overconfidence: The correct answer fell inside their intervals much less than X% of the time. This contrasts with choices between 2 possible answers to a question, which showed much less overconfidence. The authors show that overconfidence in interval estimates can result from variability in setting interval widths. However, the main cause is that subjective intervals are systematically too narrow given the accuracy of one's information-sometimes only 40% as large as necessary to be well calibrated. The degree of overconfidence varies greatly depending on how intervals are elicited. There are also substantial differences among domains and between male and female judges. The authors discuss the possible psychological mechanisms underlying this pattern of findings. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Simple Penning ion source for laboratory research and development applications

A simple Penning ion generator (PIG) that can be easily fabricated with simple machining skills and standard laboratory accessories is described. The PIG source uses an iron cathode body, samarium cobalt permanent magnet, stainless steel anode, and iron cathode faceplate to generate a plasma discharge that yields a continuous 1 mA beam of positively charged hydrogen ions at 1 mTorr of pressure. This operating condition requires 5.4 kV and 32.4 W of power. Operation with helium is similar to hydrogen. The ion source is being designed and investigated for use in a sealed-tube neutron generator; however, this ion source is thoroughly described so that it can be easily implemented by other researchers for other laboratory research and development applications.     

Human, rhesus macaque, and feline sequences highly similar to mouse mammary tumor virus sequences

Sequences highly similar (>95%) to the mouse mammary tumor virus (MMTV) env gene have been amplified from human DNA samples, including DNA samples from patients with breast cancer (BC) and persons who did not have BC. The sequences from human DNA were distinct from the MMTV sequences used as controls in these PCR reactions, indicating that these results are not simply due to contamination. In addition to both, mouse and human-related sequences were also amplified from some monkey and cat genomic DNA samples. These products were shown to be distinct from, but highly related to, the MMTV env gene, whereas, testing of other sources (lambda phage, snake, cockroach, sea urchin, chicken, or dog) demonstrated no specific amplification. A sequence 90% similar to the MMTV group antigen gene (gag) was amplified from cat DNA. These results indicate that DNA from vertebrate species other than rodents, including some but not all humans, monkeys, and cats, can contain sequences closely related to MMTV.     

Oxygen Reduction Reaction Performance of [MTBD][beti]‐Encapsulated Nanoporous NiPt Alloy Nanoparticles

Recent advances in oxygen reduction reaction catalysis for proton exchange membrane fuel cells (PEMFCs) include i) the use of electrochemical dealloying to produce high surface area and sometimes nanoporous catalysts with a Pt‐enriched outer surface, and ii) the observation that oxygen reduction in nanoporous materials can be potentially enhanced by confinement effects, particularly if the chemical environment within the pores can bias the reaction toward completion. Here, these advances are combined by incorporating a hydrophobic, protic ionic liquid, [MTBD][beti], into the pores of high surface‐area NiPt alloy nanoporous nanoparticles (np‐NiPt/C + [MTBD][beti]). The high O₂ solubility of the [MTBD][beti], in conjunction with the confined environment within the pores, biases reactant O₂ toward the catalytic surface, consistent with an increased residence time and enhanced attempt frequencies, resulting in improved reaction kinetics. Half‐cell measurements show the np‐NiPt/C+[MTBD][beti] encapsulated catalyst to be nearly an order of magnitude more active than commercial Pt/C, a result that is directly translated into operational PEMFCs.     

Pheromone responsiveness is regulated by components of the Gpr1p‐mediated glucose sensing pathway in Saccharomyces cerevisiae

Many fungi have evolved mechanisms to assess environmental nutrient availability prior to the energy‐intensive process of mating. In this study, we examined one such system in Saccharomyces cerevisiae, involving a glucose‐sensing pathway mediated by Gpr1p and the pheromone‐induced mating pathway. Initially we observed that the mating pathway in MATa cells is sensitive to environmental glucose depletion. This phenomenon can be partially reversed with a high glucose spike, but not with the addition of low levels of glucose. Deletion of the low‐affinity glucose receptor, Gpr1p, eliminated this glucose‐induced recovery of pheromone responsiveness. We then determined the impact of GPR1 deletion on the mating pathway and observed that, in all end points studied, the mating pathway response to pheromone is reduced in the absence of Gpr1p. Similarly, elimination of the Gα for Gpr1p, Gpa2p, resulted in reduction in pheromone sensitivity in all assays studied. The negative effect of removing Gpr1p on mating pathway activation could be recovered by overexpressing the mating receptor, Ste2p. Furthermore, Ste2p levels are reduced in the absence of glucose and GPR1. These data suggest that activity of the GPCR‐mediated mating pathway in S. cerevisiae is modulated by extracellular glucose concentrations through the only other GPCR in MATa cells, Gpr1p. Copyright © 2014 John Wiley & Sons, Ltd.     

Complex and dynamic population structures: synthesis, open questions, and future directions

The population structure of an evolutionary algorithm influences the dissemination and mixing of advantageous alleles, and therefore affects search performance. Much recent attention has focused on the analysis of complex population structures, characterized by heterogeneous connectivity distributions, non-trivial clustering properties, and degree–degree correlations. Here, we synthesize the results of these recent studies, discuss their limitations, and highlight several open questions regarding (1) unsolved theoretical issues and (2) the practical utility of complex population structures for evolutionary search. In addition, we will discuss an alternative complex population structure that is known to significantly influence dynamical processes, but has yet to be explored for evolutionary optimization. We then shift our attention toward dynamic population structures, which have received markedly less attention than their static counterparts. We will discuss the strengths and limitations of extant techniques and present open theoretical and experimental questions and directions for future research. In particular, we will focus on the prospects of “active linking,” wherein edges are dynamically rewired according to the genotypic or phenotypic properties of individuals, or according to the success of prior inter-individual interactions.     

Propagation of Data Error and Parametric Sensitivity in Computable General Equilibrium Models

While computable general equilibrium (CGE) models are a well-established tool in economic analyses, it is often difficult to disentangle the effects of policies of interest from that of the assumptions made regarding the underlying calibration data and model parameters. To characterize the behavior of a CGE model of carbon output with respect to two of these assumptions, we perform a large-scale Monte Carlo experiment to examine its sensitivity to base year calibration data and elasticity of substitution parameters in the absence of a policy change. By examining a variety of output variables at different levels of economic and geographic aggregation, we assess how these forms of uncertainty impact the conclusions that can be drawn from the model simulations. We find greater sensitivity to uncertainty in the elasticity of substitution parameters than to uncertainty in the base-year data as the projection period increases. While many model simulations were conducted to generate large output samples, we find that few are required to capture the mean model response of the variables tested. However, characterizing standard errors and empirical probability distribution functions is not possible without a large number of simulations.