Shyness and face scanning in children

Contrary to popular beliefs, a recent empirical study using eye tracking has shown that a non-clinical sample of socially anxious adults did not avoid the eyes during face scanning. Using eye-tracking measures, we sought to extend these findings by examining the relation between stable shyness and face scanning patterns in a non-clinical sample of 11-year-old children. We found that shyness was associated with longer dwell time to the eye region than the mouth, suggesting that some shy children were not avoiding the eyes. Shyness was also correlated with fewer first fixations to the nose, which is thought to reflect the typical global strategy of face processing. Present results replicate and extend recent work on social anxiety and face scanning in adults to shyness in children. These preliminary findings also provide support for the notion that some shy children may be hypersensitive to detecting social cues and intentions in others conveyed by the eyes. Theoretical and practical implications for understanding the social cognitive correlates and treatment of shyness are discussed. (C) 2009 Elsevier Ltd. All rights reserved.

Entanglement distribution with global control in a star-shaped multi-splitter

Distributed quantum information processing (QIP) is a promising way to bypass problems due to unwanted interactions between elements. However, this strategy presupposes the engineering of protocols for remote processors. In many of them, pairwise entanglement is a key resource. We study a model which distributes entanglement among elements of a delocalized network without local control. The model is efficient both in finite- and infinite-dimensional Hilbert spaces. We suggest a setup of electromechanical systems to implement our proposal.

Targeting poverty: Lessons from monitoring Ireland's national anti-poverty strategy

In 1997 the Irish government adopted the National Anti-Poverty Strategy (NAPS), a global target for the reduction of poverty which illuminates a range of issues relating to official poverty targets. The Irish target is framed in terms of a relative poverty measure incorporating both relative income and direct measures of deprivation based on data on the extent of poverty from 1994. Since 1994 Ireland has experienced an unprecedented period of economic growth that makes it particularly important to assess whether the target has been achieved, but in doing so we cannot avoid asking some underlying questions about how poverty should be measured and monitored over time. After briefly outlining the nature of the NAPS measure, this article examines trends in poverty in Ireland between 1987 and 1997, Results show that the relative income and deprivation components of the NAPS measure reveal differential trends with increasing relative income poverty, but decreasing deprivation. However, this differential could be due to the fact that the direct measures of deprivation upon which NAPS is based have not been updated to take account of changes in real living standards and increasing expectations. To test whether this is so, we examine the extent to which expectations about living standards and the structure of deprivation have changed over time using confirmatory factor analysis and tests of criterion validity using different definitions of deprivation. Results show that the combined income and deprivation measure, as originally constituted, continues to identify a set of households experiencing generalised deprivation resulting from a lack of resources.

Optimization strategy for minimizing damage in postbuckling stiffened panels

Composite materials are finding increasing use on primary aerostructures to meet demanding performance targets while reducing environmental impact. This paper presents a finite-element-based preliminary optimization methodology for postbuckling stiffened panels, which takes into account damage mechanisms that lead to delamination and subsequent failure by stiffener debonding. A global-local modeling approach is adopted in which the boundary conditions on the local model are extracted directly from the global model. The optimization procedure is based on a genetic algorithm that maximizes damage resistance within the postbuckling regime. This routine is linked to a finite element package and the iterative procedure automated. For a given loading condition, the procedure optimized the stacking sequence of several areas of the panel, leading to an evolved panel that displayed superior damage resistance in comparison with nonoptimized designs.

The European Union funded NEOShield project: A global approach to near-Earth object impact threat mitigation

Although discussions are underway within the Action Team 14 of the United Nations COPUOS, there is currently no concerted international plan addressing the impact threat from near-Earth objects (NEOs) and how to organize, prepare and implement mitigation measures. We report on a new international project to address impact hazard mitigation issues, being the subject of a proposal submitted to the European Commission in response to the 2011 FP7 Call "Prevention of impacts from near-Earth objects on our planet". Our consortium consists of 13 research institutes, universities, and industrial partners from 6 countries and includes leading US and Russian space organizations. The primary aim of the project, NEOShield, is to investigate in detail the three most promising mitigation techniques: the kinetic impactor, blast deflection,and the gravity tractor, and devise feasible demonstration missions. Furthermore, we will investigate options for an international strategy for implementation when an actual impact threat arises. The NEOShield project was formally accepted by the European Commission on 17 November 2011 and funded with a total of 5.8 million Euros for a period of 3.5 years. The kick-off meeting took place at the DLR Institute of Planetary Research, Berlin, in January 2012. In this paper we present a brief overview of the planned scope of the project.

Constrained Multi-Objective Aerofoil Design Using a Multi-Level Optimisation Strategy

A novel approach for the multi-objective design optimisation of aerofoil profiles is presented. The proposed method aims to exploit the relative strengths of global and local optimisation algorithms, whilst using surrogate models to limit the number of computationally expensive CFD simulations required. The local search stage utilises a re-parameterisation scheme that increases the flexibility of the geometry description by iteratively increasing the number of design variables, enabling superior designs to be generated with minimal user intervention. Capability of the algorithm is demonstrated via the conceptual design of aerofoil sections for use on a lightweight laminar flow business jet. The design case is formulated to account for take-off performance while reducing sensitivity to leading edge contamination. The algorithm successfully manipulates boundary layer transition location to provide a potential set of aerofoils that represent the trade-offs between drag at cruise and climb conditions in the presence of a challenging constraint set. Variations in the underlying flow physics between Pareto-optimal aerofoils are examined to aid understanding of the mechanisms that drive the trade-offs in objective functions.

An improved TLBO with elite strategy for parameters identification of PEM fuel cell and solar cell models

Clean and renewable energy generation and supply has drawn much attention worldwide in recent years, the proton exchange membrane (PEM) fuel cells and solar cells are among the most popular technologies. Accurately modeling the PEM fuel cells as well as solar cells is critical in their applications, and this involves the identification and optimization of model parameters. This is however challenging due to the highly nonlinear and complex nature of the models. In particular for PEM fuel cells, the model has to be optimized under different operation conditions, thus making the solution space extremely complex. In this paper, an improved and simplified teaching-learning based optimization algorithm (STLBO) is proposed to identify and optimize parameters for these two types of cell models. This is achieved by introducing an elite strategy to improve the quality of population and a local search is employed to further enhance the performance of the global best solution. To improve the diversity of the local search a chaotic map is also introduced. Compared with the basic TLBO, the structure of the proposed algorithm is much simplified and the searching ability is significantly enhanced. The performance of the proposed STLBO is firstly tested and verified on two low dimension decomposable problems and twelve large scale benchmark functions, then on the parameter identification of PEM fuel cell as well as solar cell models. Intensive experimental simulations show that the proposed STLBO exhibits excellent performance in terms of the accuracy and speed, in comparison with those reported in the literature.

An Adaptive Predictive Control Strategy for RMPPT under Partially Shaded Conditions

As one of key technologies in photovoltaic converter control, Maximum Power Point Tracking (MPPT) methods can keep the power conversion efficiency as high as nearly 99% under the uniform solar irradiance condition. However, these methods may fail when shading conditions occur and the power loss can over as much as 70% due to the multiple maxima in curve in shading conditions v.s. single maximum point in uniformly solar irradiance. In this paper, a Real Maximum Power Point Tracking (RMPPT) strategy under Partially Shaded Conditions (PSCs) is introduced to deal with this kind of problems. An optimization problem, based on a predictive model which will change adaptively with environment, is developed to tracking the global maxima and corresponding adaptive control strategy is presented. No additional circuits are required to obtain the environment uncertainties. Finally, simulations show the effectiveness of proposed method.

A comprehensive strategy to detect the fraudulent adulteration of herbs: The oregano approach

Fraud in the global food supply chain is becoming increasingly common due to the huge profits associated with this type of criminal activity. Food commodities and ingredients that are expensive and are part of complex supply chains are particularly vulnerable. Both herbs and spices fit these criteria perfectly and yet strategies to detect fraudulent adulteration are still far from robust. An FT-IR screening method coupled to data analysis using chemometrics and a second method using LC-HRMS were developed, with the latter detecting commonly used adulterants by biomarker identification. The two tier testing strategy was applied to 78 samples obtained from a variety of retail and on-line sources. There was 100% agreement between the two tests that over 24% of all samples tested had some form of adulterants present. The innovative strategy devised could potentially be used for testing the global supply chains for fraud in many different forms of herbs.

New Organizational Leadership: Nonstate Actors in Global Economic Governance

States and international organizations have found irresistible cause in a globalizing world to coopt nonstate actors (NGOs, private standard setters and so forth) to manage the manifold problems arising under their stretched mandates and resources. The pooling of capacities in the pursuit of common goals seems perfectly sensible. Yet although the strategy of cooptation has become a policy of choice, policy makers often lack full knowledge of its implications. As Philip Selznick first showed, cooptation can have unintended consequences, shifting leadership from one organization to another. We place this fertile insight in a better specified analytical framework. That is, one capable of explaining when and how leadership shifts occur and where the status quo leaders will remain at the helm. Using original interview data and structured focused comparisons to test the framework, we reveal dramatic variation in leadership changes following the cooptation of outside actors in global financial and environmental governance.