Perceived discrimination among ethnic minority young people : the role of psychological variables

Because of difficulties in objectively determining discrimination, attention has turned to individual differences in perceptions of discrimination. This study aimed to build on such work by investigating the role of psychological variables in predicting perceived discrimination (PD) in a UK sample of ethnic minority young people (n = 154). A series of multiple regression analyses yielded 3 pathways leading to PD. There was a direct effect of gender on PD. Depression and low self-esteem and need for approval predicted anxiety, which in turn was related to higher PD. Finally, private collective self-esteem correlated with public collective self-esteem, which in turn predicted lower PD. The results point to the importance of psychological variables, both personal and collective, in the perception of ethnic discrimination. Furthermore, the findings enhance our understanding of the complex associations between self-esteem, affect, and PD

Theory of Planned Behaviour and Parasuicide: An Exploratory Study

Recent evidence suggests that parasuicide (deliberate self-harm) should be considered in terms of ‘normal’ rather than ‘abnormal’ behaviour. This study aimed to address this assertion by applying a social cognition model, for the first time, to parasuicidal behaviour. An extended theory of planned behaviour (TPB) model was tested on 55 individuals drawn from hospital and non-hospital populations. Thirty-eight percent of the sample (n=21) reported a history of deliberate self-harm. Findings supported the utility of the TPB: attitudes, subjective norm, self-efficacy, moral norm and anticipated affect discriminated significantly between those with and without a history of parasuicide. The extended TPB explained more than 50% of the variance associated with intentions to deliberately self-harm. These findings have considerable theoretical and practical implications for intervention. Future research should investigate the utility of the TPB employed within a prospective framework

Authors' reply

No abstract available

Fuzzy Scalar Field Theory as a Multitrace Matrix Model

We develop an analytical approach to scalar field theory on the fuzzy sphere based on considering a perturbative expansion of the kinetic term. This expansion allows us to integrate out the angular degrees of freedom in the hermitian matrices encoding the scalar field. The remaining model depends only on the eigenvalues of the matrices and corresponds to a multitrace hermitian matrix model. Such a model can be solved by standard techniques as e.g. the saddle-point approximation. We evaluate the perturbative expansion up to second order and present the one-cut solution of the saddle-point approximation in the large N limit. We apply our approach to a model which has been proposed as an appropriate regularization of scalar field theory on the plane within the framework of fuzzy geometry.Comment: 1+25 pages, replaced with published version, minor improvement

Matrix Models, Gauge Theory and Emergent Geometry

We present, theoretical predictions and Monte Carlo simulations, for a simple three matrix model that exhibits an exotic phase transition. The nature of the transition is very different if approached from the high or low temperature side. The high temperature phase is described by three self interacting random matrices with no background spacetime geometry. As the system cools there is a phase transition in which a classical two-sphere condenses to form the background geometry. The transition has an entropy jump or latent heat, yet the specific heat diverges as the transition is approached from low temperatures. We find no divergence or evidence of critical fluctuations when the transition is approached from the high temperature phase. At sufficiently low temperatures the system is described by small fluctuations, on a background classical two-sphere, of a U(1) gauge field coupled to a massive scalar field. The critical temperature is pushed upwards as the scalar field mass is increased. Once the geometrical phase is well established the specific heat takes the value 1 with the gauge and scalar fields each contributing 1/2.Comment: 41 pages,23 figures,two references added,typos corrected, extra comments include

Nonperturbative studies of fuzzy spheres in a matrix model with the Chern-Simons term

Fuzzy spheres appear as classical solutions in a matrix model obtained via dimensional reduction of 3-dimensional Yang-Mills theory with the Chern-Simons term. Well-defined perturbative expansion around these solutions can be formulated even for finite matrix size, and in the case of $k$ coincident fuzzy spheres it gives rise to a regularized U($k$) gauge theory on a noncommutative geometry. Here we study the matrix model nonperturbatively by Monte Carlo simulation. The system undergoes a first order phase transition as we change the coefficient ($\alpha$) of the Chern-Simons term. In the small $\alpha$ phase, the large $N$ properties of the system are qualitatively the same as in the pure Yang-Mills model ($\alpha =0$), whereas in the large $\alpha$ phase a single fuzzy sphere emerges dynamically. Various `multi fuzzy spheres' are observed as meta-stable states, and we argue in particular that the $k$ coincident fuzzy spheres cannot be realized as the true vacuum in this model even in the large $N$ limit. We also perform one-loop calculations of various observables for arbitrary $k$ including $k=1$. Comparison with our Monte Carlo data suggests that higher order corrections are suppressed in the large $N$ limit.Comment: Latex 37 pages, 13 figures, discussion on instabilities refined, references added, typo corrected, the final version to appear in JHE

Exploring the psychology of suicidal ideation: A theory driven network analysis

Two leading theories within the field of suicide prevention are the interpersonal psychological theory of suicidal behaviour (IPT) and the integrated motivational-volitional (IMV) model. The IPT posits that suicidal thoughts emerge from high levels of perceived burdensomeness and thwarted belongingness. The IMV model is a multivariate framework that conceptualizes defeat and entrapment as key drivers of suicide ideation. We applied network analysis to cross-sectional data collected as part of the Scottish Wellbeing Study, in which a nationally representative sample of 3508 young adults (18–34 years) completed a battery of psychological measures. Network analysis can help us to understand how the different theoretical components interact and how they relate to suicide ideation. Within a network that included only the core factors from both models, internal entrapment and perceived burdensomeness were most strongly related to suicide ideation. The core constructs defeat, external entrapment and thwarted belonginess were mainly related to other factors than suicide ideation. Within the network of all available psychological factors, 12 of the 20 factors were uniquely related to suicide ideation, with perceived burdensomeness, internal entrapment, depressive symptoms and history of suicide ideation explaining the most variance. None of the factors was isolated, and we identified four larger clusters: mental wellbeing, interpersonal needs, personality, and suicide-related factors. Overall, the results suggest that relationships between suicide ideation and psychological risk factors are complex, with some factors contributing direct risk, and others having indirect impact

Spallation reactions. A successful interplay between modeling and applications

The spallation reactions are a type of nuclear reaction which occur in space by interaction of the cosmic rays with interstellar bodies. The first spallation reactions induced with an accelerator took place in 1947 at the Berkeley cyclotron (University of California) with 200 MeV deuterons and 400 MeV alpha beams. They highlighted the multiple emission of neutrons and charged particles and the production of a large number of residual nuclei far different from the target nuclei. The same year R. Serber describes the reaction in two steps: a first and fast one with high-energy particle emission leading to an excited remnant nucleus, and a second one, much slower, the de-excitation of the remnant. In 2010 IAEA organized a worskhop to present the results of the most widely used spallation codes within a benchmark of spallation models. If one of the goals was to understand the deficiencies, if any, in each code, one remarkable outcome points out the overall high-quality level of some models and so the great improvements achieved since Serber. Particle transport codes can then rely on such spallation models to treat the reactions between a light particle and an atomic nucleus with energies spanning from few tens of MeV up to some GeV. An overview of the spallation reactions modeling is presented in order to point out the incomparable contribution of models based on basic physics to numerous applications where such reactions occur. Validations or benchmarks, which are necessary steps in the improvement process, are also addressed, as well as the potential future domains of development. Spallation reactions modeling is a representative case of continuous studies aiming at understanding a reaction mechanism and which end up in a powerful tool.Comment: 59 pages, 54 figures, Revie

Mechanisms underlying a thalamocortical transformation during active tactile sensation

During active somatosensation, neural signals expected from movement of the sensors are suppressed in the cortex, whereas information related to touch is enhanced. This tactile suppression underlies low-noise encoding of relevant tactile features and the brain’s ability to make fine tactile discriminations. Layer (L) 4 excitatory neurons in the barrel cortex, the major target of the somatosensory thalamus (VPM), respond to touch, but have low spike rates and low sensitivity to the movement of whiskers. Most neurons in VPM respond to touch and also show an increase in spike rate with whisker movement. Therefore, signals related to self-movement are suppressed in L4. Fast-spiking (FS) interneurons in L4 show similar dynamics to VPM neurons. Stimulation of halorhodopsin in FS interneurons causes a reduction in FS neuron activity and an increase in L4 excitatory neuron activity. This decrease of activity of L4 FS neurons contradicts the "paradoxical effect" predicted in networks stabilized by inhibition and in strongly-coupled networks. To explain these observations, we constructed a model of the L4 circuit, with connectivity constrained by in vitro measurements. The model explores the various synaptic conductance strengths for which L4 FS neurons actively suppress baseline and movement-related activity in layer 4 excitatory neurons. Feedforward inhibition, in concert with recurrent intracortical circuitry, produces tactile suppression. Synaptic delays in feedforward inhibition allow transmission of temporally brief volleys of activity associated with touch. Our model provides a mechanistic explanation of a behavior-related computation implemented by the thalamocortical circuit

Enhancing studies of the connectome in autism using the autism brain imaging data exchange II

The second iteration of the Autism Brain Imaging Data Exchange (ABIDE II) aims to enhance the scope of brain connectomics research in Autism Spectrum Disorder (ASD). Consistent with the initial ABIDE effort (ABIDE I), that released 1112 datasets in 2012, this new multisite open-data resource is an aggregate of resting state functional magnetic resonance imaging (MRI) and corresponding structural MRI and phenotypic datasets. ABIDE II includes datasets from an additional 487 individuals with ASD and 557 controls previously collected across 16 international institutions. The combination of ABIDE I and ABIDE II provides investigators with 2156 unique cross-sectional datasets allowing selection of samples for discovery and/or replication. This sample size can also facilitate the identification of neurobiological subgroups, as well as preliminary examinations of sex differences in ASD. Additionally, ABIDE II includes a range of psychiatric variables to inform our understanding of the neural correlates of co-occurring psychopathology; 284 diffusion imaging datasets are also included. It is anticipated that these enhancements will contribute to unraveling key sources of ASD heterogeneity