Attentional Biases for Negative Interpersonal Stimuli in Clinical Depression.

An information-processing paradigm was used to examine attentional biases in clinically depressed participants, participants with generalized anxiety disorder (GAD), and nonpsychiatric control participants for faces expressing sadness, anger, and happiness. Faces were presented for 1,000 ms, at which point depressed participants had directed their attention selectively to depression-relevant (i.e., sad) faces. This attentional bias was specific to the emotion of sadness; the depressed participants did not exhibit attentional biases to the angry or happy faces. This bias was also specific to depression; at 1,000 ms, participants with GAD were not attending selectively to sad, happy, or anxiety-relevant (i.e., angry) faces. Implications of these findings for both the cognitive and the interpersonal functioning of depressed individuals are discussed and directions for future research are advanced. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Energy function analysis of dynamic programming neural networks

All analytical examination of the energy function associated with a dynamic programming neural network is presented. The analysis is carried out in two steps. First, the locations and numbers of the minimum states for different components of the energy function are investigated in the extreme cases. A clearer insight into the energy function can be gained through the minimum states of different components. Secondly, the locations of the minimum states of the energy function using different parameter values are derived. It is shown that the minimum states can reside in regions which are regarded as valid solutions with certain conditions. Examples and simulation results are given to justify the validity of the theories developed.     

A new simplified threshold-voltage model for n-MOSFETs with nonuniformly doped substrate and its application to MOSFET's miniaturization

The formulation, verification, and application of a new simplified 2-D threshold voltage model for n-MOSFETs with nonuniformly doped substrate profile are provided, in which the averaged normal field at the Si/SiO/sub 2/ interface in the active channel is quoted from a simplified solution of two-dimensional Poisson equation using the Green function technique. Starting with the expression of this average normal field, a simple threshold-voltage model for short-channel n-MOSFETs with nonuniformly doped substrate profile is explicitly expressed in terms of device structures and terminal voltages by considering parabolic source-drain boundary potentials. Moreover, the effects of the junction depth on the threshold voltage are examined in detail. It is shown that the DIBL effect cannot be completely eliminated by simply increasing the substrate doping concentration. Comparisons among developed model, 2-D numerical analysis, and experimental data have been made and the accuracy of the developed analytical model has been verified. In addition, a direct extension of our model to the case of uniformly doped substrates leads to a new constraint equation for device miniaturization.<>     

Assumptions and Consequences of Treating Providers in Therapy Studies as Fixed Versus Random Effects: Reply to Crits-Christoph, Tu, and Gallop (2003) and Serlin, Wampold, and Levin (2003).

In their comments on the authors' article (see record 2003-10163-009), R. C. Serlin, B. E. Wampold, and J. R. Levin (see record 2003-10163-011) and P. Crits-Christoph, X. Tu, and R. Gallop (see record 2003-10163-010) took issue with the authors' suggestion to evaluate therapy studies with nested providers with a fixed model approach. In this rejoinder, the authors' comment on Serlin et al's critique by showing that their arguments do not apply, are based on misconceptions about the purpose and nature of statistical inference, or are based on flawed reasoning. The authors also comment on Crits-Christoph et al's critique by showing that the proposed approach is very similar to, but less inclusive than, their own suggestion. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Ausgleich der Volatilität der Erneuerbaren Energien mittels Wärmespeichern auf Salzbasis

To compensate for the volatility of renewable energies, solutions beyond fossil reserve power plants are needed. One approach is salt-based heat storage with phase change materials (PCM). In order to achieve economic efficiency, ambitious targets are required. A sensible and latent heat storage system for the temperature range around 400 °C based on salts and thermal oils with high development potential is presented.     

On the composition of ISO 25964 hierarchical relations (BTG,BTP, BTI)

Knowledge organization systems (KOS) can use different types of hierarchical relations: broader generic (BTG), broader partitive (BTP), and broader instantial (BTI). The latest ISO standard on thesauri (ISO 25964) has formalized these relations in a corresponding OWL ontology (De Smedt et al., ISO 25964 part 1: thesauri for information retrieval: RDF/OWL vocabulary, extension of SKOS and SKOS-XL. http://purl.org/iso25964/skos-thes, 2013) and expressed them as properties: broaderGeneric, broaderPartitive, and broaderInstantial, respectively. These relations are used in actual thesaurus data. The compositionality of these types of hierarchical relations has not been investigated systematically yet. They all contribute to the general broader (BT) thesaurus relation and its transitive generalization broader transitive defined in the SKOS model for representing KOS. But specialized relationship types cannot be arbitrarily combined to produce new statements that have the same semantic precision, leading to cases where inference of broader transitive relationships may be misleading. We define Extended properties (BTGE, BTPE, BTIE) and analyze which compositions of the original “one-step” properties and the Extended properties are appropriate. This enables providing the new properties with valuable semantics usable, e.g., for fine-grained information retrieval purposes. In addition, we relax some of the constraints assigned to the ISO properties, namely the fact that hierarchical relationships apply to SKOS concepts only. This allows us to apply them to the Getty Art and Architecture Thesaurus (AAT), where they are also used for non-concepts (facets, hierarchy names, guide terms). In this paper, we present extensive examples derived from the recent publication of AAT as linked open data.     

Support vector classification of proteomic profile spectra based on feature extraction with the bi-orthogonal discrete wavelet transform

Automatic classification of high-resolution mass spectrometry data has increasing potential to support physicians in diagnosis of diseases like cancer. The proteomic data exhibit variations among different disease states. A precise and reliable classification of mass spectra is essential for a successful diagnosis and treatment. The underlying process to obtain such reliable classification results is a crucial point. In this paper such a method is explained and a corresponding semi automatic parameterization procedure is derived. Thereby a simple straightforward classification procedure to assign mass spectra to a particular disease state is derived. The method is based on an initial preprocessing stage of the whole set of spectra followed by the bi-orthogonal discrete wavelet transform (DWT) for feature extraction. The approximation coefficients calculated from the scaling function exhibit a high peak pattern matching property and feature a denoising of the spectrum. The discriminating coefficients, selected by the Kolmogorov–Smirnov test are finally used as features for training and testing a support vector machine with both a linear and a radial basis kernel. For comparison the peak areas obtained with the it ClinProt-System ¹ [33] were analyzed using the same support vector machines. The introduced approach was evaluated on clinical MALDI-MS data sets with two classes each originating from cancer studies. The cross validated error rates using the wavelet coefficients where better than those obtained from the peak areas².     

Semi-Supervised Deep Learning for Multi-Tissue Segmentation from Multi-Contrast MRI

Journal of Signal Processing Systems - Segmentation of thigh tissues (muscle, fat, inter-muscular adipose tissue (IMAT), bone, and bone marrow) from magnetic resonance imaging (MRI) scans is useful...     

Remembering the Good, Forgetting the Bad: Intentional Forgetting of Emotional Material in Depression.

The authors examined intentional forgetting of negative material in depression. Participants were instructed to not think about emotional nouns that they had learned to associate with a neutral cue word. The authors provided participants with multiple occasions to suppress the unwanted words. Overall, depressed participants successfully forgot negative words. Moreover, the authors obtained a clear practice effect. However, forgetting came at a cost: Compared with the nondepressed participants and with the depressed participants who were instructed to forget positive words, depressed participants who were instructed to forget negative words showed significantly worse recall of the baseline words. These results indicate that training depressed individuals in intentional forgetting could prove to be an effective strategy to counteract automatic ruminative tendencies and mood-congruent biases. (PsycINFO Database Record (c) 2010 APA, all rights reserved)