Beyond behaviour: is social anxiety low in Williams syndrome

Individuals with Williams syndrome (WS) exhibit striking social behaviour that may be indicative of abnormally low social anxiety. The present research aimed to determine whether social anxiety is unusually low in WS and to replicate previous findings of increased generalised anxiety in WS using both parent and self report. Fifteen individuals with WS aged 12-28 years completed the Spence Children’s Anxiety Scale (SCAS) and the Children’s Automatic Thoughts Scale (CATS). Their responses were compared to clinically anxious and community comparison groups matched on mental age. The findings suggest that WS is not associated with unusually low social anxiety but that generalised anxiety symptoms and physical threat thoughts are increased in WS, relative to typically developing children.

Descriptive/Inferential Cognitive Processes and Evaluative Cognitive Processes: Relationships Among Each Other and with Emotional Distress

We aimed to delineate key constructs from two forms of cognitive-behavioral therapy: cognitive therapy and rational-emotive behavior therapy. Furthermore, we aimed to investigate the interrelations among each other and with emotional distress. The key constructs of the underlying theories of these therapies (i.e., descriptive/inferential beliefs, evaluative beliefs) are often treated together as distorted cognitions and included as such in various scales. We used a cross-sectional design. Seventy-four undergraduate students (mean age = 24.68) completed measures of automatic thoughts and emotional distress. Three therapists trained in cognitive-behavioral therapy divided automatic thoughts into descriptive/inferential beliefs and evaluative beliefs by consensus. Correlation and mediation analyses were performed. These constructs showed medium to high associations to each other and to distress. The relationship between descriptive/inferential beliefs and distress was mediated by evaluative beliefs. Descriptive and inferential cognitions may not produce emotions without first being appraised in terms of personal relevance.

Cognitive change processes in a group cognitive behavior therapy of depression

The present study attempted to examine the causal relationships among changes in automatic thoughts, dysfunctional attitudes, and depressive symptoms in a 12-week group cognitive behavior therapy (GCBT) program for depression. In all, 35 depressed patients attending the GCBT program were monitored with the Automatic Thoughts Questionnaire, Dysfunctional Attitudes Scale, and Beck Depression Inventory at the pre-treatment, 4th and 8th sessions, and post-treatment. The results were as follows: (1) GCBT reduces negative cognitions; (2) changes in automatic thoughts and dysfunctional attitudes lead to change in depressive symptoms; and (3) automatic thoughts play a mediating role between dysfunctional attitudes and depression. The findings taken as a whole support the Causal Cognition Model of depression. (C) 2003 Elsevier Science Ltd. All rights reserved.

Study of the integrated cognitive model of depression among Latin-Americans

Objective: The objective of the present study is to test the validity of the integrated cognitive model (ICM) of depression proposed by Kwon and Oei with a Latin-American sample. The ICM of depression postulates that the interaction between negative life events with dysfunctional attitudes increases the frequency of negative automatic thoughts, which in turns affects the depressive symptomatology of a person. This model was developed for Western Europeans such as Americans and Australians and the validity of this model has not been tested on Latin-Americans. Method: Participants were 101 Latin-American migrants living permanently in Brisbane, including people from Chile, El Salvador, Nicaragua, Argentina and Guatemala. Participants completed the Beck Depression Inventory, the Dysfunctional Attitudes Scale, the Automatic Thoughts Questionnaire and the Life Events Inventory. Alternative or competing models of depression were examined, including the alternative aetiologies model, the linear mediational model and the symptom model. Results: Six models were tested and the results of the structural equation modelling analysis indicated that the symptom model only fits the Latin-American data. Conclusions: Results show that in the Latin-American sample depression symptoms can have an impact on negative cognitions. This finding adds to growing evidence in the literature that the relationship between cognitions and depression is bidirectional, rather than unidirectional from cognitions to symptoms.

Cognitive change process during group cognitive behaviour therapy for depression

Background: This study extended that of Kwon and Oei [Kwon, S.M., Oei, T.P.S., 2003. Cognitive change processes in a group cognitive behavior therapy of depression. J. Behav. Ther. Exp. Psychiatry, 3, 73-85], which outlined a number of testable models based on Beck's cognitive theory of depression. Specifically, the current study tested the following four competing models: the causal, consequential, fully and partially interactive cognitive models in patients with major depressive disorder. Methods: A total of 168 clinically depressed outpatients were recruited into a 12-week group cognitive behaviour therapy program. Data was collected at three time points: baseline, mid- and at termination of therapy using the ATQ DAS and BD1. The data were analysed with Amos 4.01 (Arbuckle, J.L., 1999. Amos 4.1. Smallwaters, Chicago.) structural equation modelling. Results: Results indicated that dysfunctional attitudes, negative automatic thoughts and symptoms of depression reduced significantly during treatment. Both the causal and consequential models equally provided an adequate fit to the data. The fully interactive model provided the best fit. However, after removing non-significant pathways, it was found that reduced depressive symptom contributed to reduced depressogenic automatic thoughts and dysfunctional attitudes, not the reverse. Conclusion: These findings did not fully support Beck's cognitive theory of depression that cognitions are primary in the reduction of depressed mood. (c) 2006 Elsevier B.V. All rights reserved.

The role of psychological inflexibility in Beck's cognitive model of depression in a sample of undergraduates

Beck's cognitive model of depression proposes that depressogenic schemas have an effect on depressive symptoms by increasing the frequency of negative automatic thoughts in response to negative life events. We aimed to test a moderated, serial mediation model where psychological inflexibility, a core concept of the Acceptance and Commitment Therapy (ACT) model of psychopathology, both mediates and moderates the relationship between depressogenic schemas and the frequency of negative automatic thoughts. A cross-sectional design was used in which 210 undergraduates responded to questionnaires assessing the constructs of interest. Results supported the proposed moderated mediation model. Both psychological inflexibility and negative automatic thoughts were significant mediators of the relationship between depressogenic schemas and depressive symptoms, and psychological inflexibility also moderated the effect of depressogenic schemas on negative automatic thoughts. We conclude that the role of psychological inflexibility in the cognitive model of depression deserves more attention.

Relação entre mindfulness, pensamentos automáticos e autocompaixão em população adulta

Dissertação de Mestrado apresentada no ISPA – Instituto Universitário para obtenção do grau de Mestre em Psicologia especialidade em Psicologia da Saúde.

Evidence for divided automatic attention

A long-standing debate in the literature is whether attention can form two or more independent spatial foci in addition to the well-known unique spatial focus. There is evidence that voluntary visual attention divides in space. The possibility that this also occurs for automatic visual attention was investigated here. Thirty-six female volunteers were tested. In each trial, a prime stimulus was presented in the left or right visual hemifield. This stimulus was characterized by the blinking of a superior, middle or inferior ring, the blinking of all these rings, or the blinking of the superior and inferior rings. A target stimulus to which the volunteer should respond with the same side hand or a target stimulus to which she should not respond was presented 100 ms later in a primed location, a location between two primed locations or a location in the contralateral hemifield. Reaction time to the positive target stimulus in a primed location was consistently shorter than reaction time in the horizontally corresponding contralateral location. This attentional effect was significantly smaller or absent when the positive target stimulus appeared in the middle location after the double prime stimulus. These results suggest that automatic visual attention can focus on two separate locations simultaneously, to some extent sparing the region in between.

Characterizing chaotic melodies in automatic music composition

In this paper, we initially present an algorithm for automatic composition of melodies using chaotic dynamical systems. Afterward, we characterize chaotic music in a comprehensive way as comprising three perspectives: musical discrimination, dynamical influence on musical features, and musical perception. With respect to the first perspective, the coherence between generated chaotic melodies (continuous as well as discrete chaotic melodies) and a set of classical reference melodies is characterized by statistical descriptors and melodic measures. The significant differences among the three types of melodies are determined by discriminant analysis. Regarding the second perspective, the influence of dynamical features of chaotic attractors, e.g., Lyapunov exponent, Hurst coefficient, and correlation dimension, on melodic features is determined by canonical correlation analysis. The last perspective is related to perception of originality, complexity, and degree of melodiousness (Euler's gradus suavitatis) of chaotic and classical melodies by nonparametric statistical tests. (c) 2010 American Institute of Physics. [doi: 10.1063/1.3487516]

Automatic Network Fingerprinting through Single-Node Motifs

Complex networks have been characterised by their specific connectivity patterns (network motifs), but their building blocks can also be identified and described by node-motifs-a combination of local network features. One technique to identify single node-motifs has been presented by Costa et al. (L. D. F. Costa, F. A. Rodrigues, C. C. Hilgetag, and M. Kaiser, Europhys. Lett., 87, 1, 2009). Here, we first suggest improvements to the method including how its parameters can be determined automatically. Such automatic routines make high-throughput studies of many networks feasible. Second, the new routines are validated in different network-series. Third, we provide an example of how the method can be used to analyse network time-series. In conclusion, we provide a robust method for systematically discovering and classifying characteristic nodes of a network. In contrast to classical motif analysis, our approach can identify individual components (here: nodes) that are specific to a network. Such special nodes, as hubs before, might be found to play critical roles in real-world networks.

SAB(IO): A BIOLOGICALLY PLAUSIBLE CONNECTIONIST APPROACH TO AUTOMATIC TEXT SUMMARIZATION

An implementation of a computational tool to generate new summaries from new source texts is presented, by means of the connectionist approach (artificial neural networks). Among other contributions that this work intends to bring to natural language processing research, the use of a more biologically plausible connectionist architecture and training for automatic summarization is emphasized. The choice relies on the expectation that it may bring an increase in computational efficiency when compared to the sa-called biologically implausible algorithms.

An algorithm for computerized automatic tuning of power system stabilizers

The main objective of this paper is to relieve the power system engineers from the burden of the complex and time-consuming process of power system stabilizer (PSS) tuning. To achieve this goal, the paper proposes an automatic process for computerized tuning of PSSs, which is based on an iterative process that uses a linear matrix inequality (LMI) solver to find the PSS parameters. It is shown in the paper that PSS tuning can be written as a search problem over a non-convex feasible set. The proposed algorithm solves this feasibility problem using an iterative LMI approach and a suitable initial condition, corresponding to a PSS designed for nominal operating conditions only (which is a quite simple task, since the required phase compensation is uniquely defined). Some knowledge about the PSS tuning is also incorporated in the algorithm through the specification of bounds defining the allowable PSS parameters. The application of the proposed algorithm to a benchmark test system and the nonlinear simulation of the resulting closed-loop models demonstrate the efficiency of this algorithm. (C) 2009 Elsevier Ltd. All rights reserved.

Automatic tuning method for the design of supplementary damping controllers for flexible alternating current transmission system devices

The design of supplementary damping controllers to mitigate the effects of electromechanical oscillations in power systems is a highly complex and time-consuming process, which requires a significant amount of knowledge from the part of the designer. In this study, the authors propose an automatic technique that takes the burden of tuning the controller parameters away from the power engineer and places it on the computer. Unlike other approaches that do the same based on robust control theories or evolutionary computing techniques, our proposed procedure uses an optimisation algorithm that works over a formulation of the classical tuning problem in terms of bilinear matrix inequalities. Using this formulation, it is possible to apply linear matrix inequality solvers to find a solution to the tuning problem via an iterative process, with the advantage that these solvers are widely available and have well-known convergence properties. The proposed algorithm is applied to tune the parameters of supplementary controllers for thyristor controlled series capacitors placed in the New England/New York benchmark test system, aiming at the improvement of the damping factor of inter-area modes, under several different operating conditions. The results of the linear analysis are validated by non-linear simulation and demonstrate the effectiveness of the proposed procedure.

An approach of optimal sensitivity applied in the tertiary loop of the automatic generation control

This paper proposes an approach of optimal sensitivity applied in the tertiary loop of the automatic generation control. The approach is based on the theorem of non-linear perturbation. From an optimal operation point obtained by an optimal power flow a new optimal operation point is directly determined after a perturbation, i.e., without the necessity of an iterative process. This new optimal operation point satisfies the constraints of the problem for small perturbation in the loads. The participation factors and the voltage set point of the automatic voltage regulators (AVR) of the generators are determined by the technique of optimal sensitivity, considering the effects of the active power losses minimization and the network constraints. The participation factors and voltage set point of the generators are supplied directly to a computational program of dynamic simulation of the automatic generation control, named by power sensitivity mode. Test results are presented to show the good performance of this approach. (C) 2008 Elsevier B.V. All rights reserved.

AUTOMATIC CORONARY WALL SEGMENTATION IN INTRAVASCULAR ULTRASOUND IMAGES USING BINARY MORPHOLOGICAL RECONSTRUCTION

Intravascular ultrasound (IVUS) image segmentation can provide more detailed vessel and plaque information, resulting in better diagnostics, evaluation and therapy planning. A novel automatic segmentation proposal is described herein; the method relies on a binary morphological object reconstruction to segment the coronary wall in IVUS images. First, a preprocessing followed by a feature extraction block are performed, allowing for the desired information to be extracted. Afterward, binary versions of the desired objects are reconstructed, and their contours are extracted to segment the image. The effectiveness is demonstrated by segmenting 1300 images, in which the outcomes had a strong correlation to their corresponding gold standard. Moreover, the results were also corroborated statistically by having as high as 92.72% and 91.9% of true positive area fraction for the lumen and media adventitia border, respectively. In addition, this approach can be adapted easily and applied to other related modalities, such as intravascular optical coherence tomography and intravascular magnetic resonance imaging. (E-mail: matheuscardosomg@hotmail.com) (C) 2011 World Federation for Ultrasound in Medicine & Biology.