Affective disorder in the parents of a clinic sample of children with anxiety disorders

Background: Family history studies in adults reveal strong familiality for the anxiety disorders with some specificity. The aim of the current study was to establish whether there was an elevated rate of anxiety disorders in the parents of children with anxiety disorders, and whether there was intergenerational specificity in the form of disorder. Methods: The mental state of a clinic sample of 85 children with anxiety disorder and their parents was systematically assessed, together with a comparison sample of 45 children with no current disorder and their parents. Results: Compared to the rate of anxiety disorder amongst parents of comparison children, the rate of current anxiety disorder in mothers of anxious children was significantly raised, as was the lifetime rate of anxiety disorder for both mothers and fathers. The mothers of children with generalised anxiety disorder, social phobia, specific phobia and separation anxiety disorder all had raised lifetime rates of the corresponding disorder, but also raised rates of others disorders. Limitations: Only 60% of the fathers of the anxious children were assessed. Conclusions: Strong familiality of anxiety disorders was confirmed, especially between child and maternal anxiety disorder. All child anxiety disorders were associated with several forms of anxiety disorder in the mother. Some specificity in the form of anxiety disorder in the child and the mother was apparent for social phobia and separation anxiety disorder. The findings have implications for the management of child anxiety. (c) 2006 Elsevier B.V. All rights reserved.

Research into anxiety of childhood: playing catch-up (to Olympic standard)

This special issue is the culmination of an ESRC seminar series grant awarded to the authors of this editorial. We named the seminar series CATTS (Child Anxiety, Theory and Treatment Seminars) and it took the form of six highly stimulating, one-day seminars on the subject of child anxiety, with participants from clinical and academic backgrounds and from Great Britain, Europe, the USA and Australia. Most of the authors in this publication, and a sister special issue in Cognitions and Emotion (2008), participated in the CATTS series.

Identification of nonlinear systems using generalized kernel models

Nonlinear system identification is considered using a generalized kernel regression model. Unlike the standard kernel model, which employs a fixed common variance for all the kernel regressors, each kernel regressor in the generalized kernel model has an individually tuned diagonal covariance matrix that is determined by maximizing the correlation between the training data and the regressor using a repeated guided random search based on boosting optimization. An efficient construction algorithm based on orthogonal forward regression with leave-one-out (LOO) test statistic and local regularization (LR) is then used to select a parsimonious generalized kernel regression model from the resulting full regression matrix. The proposed modeling algorithm is fully automatic and the user is not required to specify any criterion to terminate the construction procedure. Experimental results involving two real data sets demonstrate the effectiveness of the proposed nonlinear system identification approach.

Generalized matching networks and their properties

In this paper, we introduce two kinds of graphs: the generalized matching networks (GMNs) and the recursive generalized matching networks (RGMNs). The former generalize the hypercube-like networks (HLNs), while the latter include the generalized cubes and the star graphs. We prove that a GMN on a family of k-connected building graphs is -connected. We then prove that a GMN on a family of Hamiltonian-connected building graphs having at least three vertices each is Hamiltonian-connected. Our conclusions generalize some previously known results.

Minimum neighborhood in a generalized cube

Generalized cubes are a subclass of hypercube-like networks, which include some hypercube variants as special cases. Let theta(G)(k) denote the minimum number of nodes adjacent to a set of k vertices of a graph G. In this paper, we prove theta(G)(k) >= -1/2k(2) + (2n - 3/2)k - (n(2) - 2) for each n-dimensional generalized cube and each integer k satisfying n + 2 <= k <= 2n. Our result is an extension of a result presented by Fan and Lin [J. Fan, X. Lin, The t/k-diagnosability of the BC graphs, IEEE Trans. Comput. 54 (2) (2005) 176-184]. (c) 2005 Elsevier B.V. All rights reserved.

Generalized honeycomb torus is Hamiltonian

Generalized honeycomb torus is a candidate for interconnection network architectures, which includes honeycomb torus, honeycomb rectangular torus, and honeycomb parallelogramic torus as special cases. Existence of Hamiltonian cycle is a basic requirement for interconnection networks since it helps map a "token ring" parallel algorithm onto the associated network in an efficient way. Cho and Hsu [Inform. Process. Lett. 86 (4) (2003) 185-190] speculated that every generalized honeycomb torus is Hamiltonian. In this paper, we have proved this conjecture. (C) 2004 Elsevier B.V. All rights reserved.

A lower bound on the size of k-neighborhood in generalized cubes

The determination of the minimum size of a k-neighborhood (i.e., a neighborhood of a set of k nodes) in a given graph is essential in the analysis of diagnosability and fault tolerance of multicomputer systems. The generalized cubes include the hypercube and most hypercube variants as special cases. In this paper, we present a lower bound on the size of a k-neighborhood in n-dimensional generalized cubes, where 2n + 1 <= k <= 3n - 2. This lower bound is tight in that it is met by the n-dimensional hypercube. Our result is an extension of two previously known results. (c) 2005 Elsevier Inc. All rights reserved.

A novel radix-3/9 algorithm for type-III generalized discrete Hartley transform

A novel radix-3/9 algorithm for type-III generalized discrete Hartley transform (GDHT) is proposed, which applies to length-3(P) sequences. This algorithm is especially efficient in the case that multiplication is much more time-consuming than addition. A comparison analysis shows that the proposed algorithm outperforms a known algorithm when one multiplication is more time-consuming than five additions. When combined with any known radix-2 type-III GDHT algorithm, the new algorithm also applies to length-2(q)3(P) sequences.

What does a transdiagnostic approach have to offer the treatment of anxiety disorders?

Purpose: The purpose of this paper is to review the rationale for 'transdiagnostic' approaches to the understanding and treatment of anxiety disorders. Methods: Databases searches and examination of the reference lists of relevant studies were used to identify papers of relevance. Results: There is increasing recognition that diagnosis-specific interventions for single anxiety-disorders are of less value than might appear since a large proportion of patients have more than one co-existing anxiety disorder and the treatment of one anxiety disorder does not necessarily lead to the resolution of others. As transdiagnostic approaches have the potential to address multiple co-existing anxiety disorders they are potentially more clinically relevant than single anxiety disorder interventions. They may also have advantages in ease of dissemination and in treating anxiety disorder not otherwise specified. Conclusions: The merits of the various transdiagnostic cognitive-behavioral approaches that have been proposed are reviewed. Such approaches have potential benefits, particularly in striking the balance between completely idiosyncratic formulations and diagnosis-driven treatments of anxiety disorders. However, caution is needed to ensure that transdiagnostic theories and treatments benefit from progress made by research on diagnosis-specific treatments, and further empirical work is needed to identify the shared maintaining processes that need to be targeted in the treatment of anxiety disorders.

Thermodynamics of climate change: generalized sensitivities

Using a recent theoretical approach, we study how global warming impacts the thermodynamics of the climate system by performing experiments with a simplified yet Earth-like climate model. The intensity of the Lorenz energy cycle, the Carnot efficiency, the material entropy production, and the degree of irreversibility of the system change monotonically with the CO2 concentration. Moreover, these quantities feature an approximately linear behaviour with respect to the logarithm of the CO2 concentration in a relatively wide range. These generalized sensitivities suggest that the climate becomes less efficient, more irreversible, and features higher entropy production as it becomes warmer, with changes in the latent heat fluxes playing a predominant role. These results may be of help for explaining recent findings obtained with state of the art climate models regarding how increases in CO2 concentration impact the vertical stratification of the tropical and extratropical atmosphere and the position of the storm tracks.

A geometric approach to generalized Stokes conjectures

We consider the Stokes conjecture concerning the shape of extreme two-dimensional water waves. By new geometric methods including a nonlinear frequency formula, we prove the Stokes conjecture in the original variables. Our results do not rely on structural assumptions needed in previous results such as isolated singularities, symmetry and monotonicity. Part of our results extends to the mathematical problem in higher dimensions.

Interpretation of ambiguity in children: a prospective study of associations with anxiety and parental interpretations

Interpretation of ambiguity is consistently associated with anxiety in children, however, the temporal relationship between interpretation and anxiety remains unclear as do the developmental origins of interpretative biases. This study set out to test a model of the development of interpretative biases in a prospective study of 110 children aged 5–9 years of age. Children and their parents were assessed three times, annually, on measures of anxiety and interpretation of ambiguous scenarios (including, for parents, both their own interpretations and their expectations regarding their child). Three models were constructed to assess associations between parent and child anxiety and threat and distress cognitions and expectancies. The three models were all a reasonable fit of the data, and supported conclusions that: (i) children’s threat and distress cognitions were stable over time and were significantly associated with anxiety, (ii) parents’ threat and distress cognitions and expectancies significantly predicted child threat cognitions at some time points, and (iii) parental anxiety significantly predicted parents cognitions, which predicted parental expectancies at some time points. Parental expectancies were also significantly predicted by child cognitions. The findings varied depending on assessment time point and whether threat or distress cognitions were being considered. The findings support the notion that child and parent cognitive processes, in particular parental expectations, may be a useful target in the treatment or prevention of anxiety disorders in children.