Type D personality and the development of PTSD symptoms: A prospective study.

Psychological trauma and prolonged stress may cause mental disorders such as posttraumatic stress disorder (PTSD). Pretrauma personality is an important determinant of posttraumatic adjustment. Specifically, trait neuroticism has been identified as a risk factor for PTSD. Additionally, the combination of high negative affectivity or neuroticism with marked social inhibition or introversion, also called Type D personality (Denollet, 2000), may compose a risk factor for PTSD. There is no research available that examined pretrauma Type D personality in relation to PTSD. The present study examined the predictive validity of the Type D personality construct in a sample of Dutch soldiers. Data were collected prior to and 6 months after military deployment to Afghanistan. Separate multiple regression analyses were performed to examine the predictive validity of Type D personality. First, Type D personality was defined as the interaction between negative affect and social inhibition (Na × Si). In a second analysis, Type D was defined following cutoff criteria recommended by Denollet (2000). Results showed that negative affectivity was a significant predictor of PTSD symptoms. Social inhibition and the interaction Na × Si did not add to the amount of explained variance in postdeployment PTSD scores over the effects of childhood abuse, negative affectivity, and prior psychological symptoms. A second analysis showed that Type D personality (dichotomous) did not add to the amount of explained variance in postdeployment PTSD scores over the effects of childhood abuse, and prior psychological symptoms. Therefore, Type D personality appears to be of limited value to explain development of combat-related PTSD symptoms. (PsycINFO Database Record (c) 2011 APA, all rights reserved)     

The Influence of an Ozone,Chlorine and Chlorine Dioxide Treatment on Mutagentic Activity in (Drinking) Water

Three disinfectants, viz. chlorine, chlorine dioxide, and ozone, were compared with respect to the formation of organic mutagens and halogenated organic compounds in drinking water. Chlorine increased the mutagenic activity (Ames test) drastically, as well as the level of halogenated organics. High chlorine dioxide doses (5 – 15 mg/L C10₂) also showed a drastic increase of mutagenic activity, while relatively low doses of chlorine dioxide (< 5 mg/L CIO₂) in most cases showed no effect or a slight increase in mutagenic activity. Hardly any increase in the level of halogenated organics was observed after this treatment.     

Modelling Highly Inflected Slovenian Language

This paper concerns the development of statistical language models of the Slovenian language for use in an automatic speech recognition system. The proposed techniques are language-independent and can be applied to other highly inflected Slavic languages. The large number of unique words in inflected languages is identified as the primary reason for performance degradation. This article discusses the concept of word-formation in the Slovenian language, which is also common to all Slavic languages. The main problems are outlined for word-based language models. A novel variation on the N-gram modelling theme is examined where, instead of using words, modelling units are chosen to be stems and endings. Only data-driven algorithms are employed, which decompose words automatically. A significant reduction in the OOV rate results when using stems and endings for modelling the Slovenian language. The final part of this article focuses on building a speech recogniser. Two different decoding strategies have been employed: one-pass and two-pass search decoders. Language modelling experiments have been performed using the VEER newswire text corpus, and recognition experiments have been conducted using the SNABI Slovenian speech database. The new language model resulted in the reduction of the OOV rate by 64%, and the recognition accuracy was improved by 4.34%.     

Personalising speech-to-speech translation: Unsupervised cross-lingual speaker adaptation for HMM-based speech synthesis

In this paper we present results of unsupervised cross-lingual speaker adaptation applied to text-to-speech synthesis. The application of our research is the personalisation of speech-to-speech translation in which we employ a HMM statistical framework for both speech recognition and synthesis. This framework provides a logical mechanism to adapt synthesised speech output to the voice of the user by way of speech recognition. In this work we present results of several different unsupervised and cross-lingual adaptation approaches as well as an end-to-end speaker adaptive speech-to-speech translation system. Our experiments show that we can successfully apply speaker adaptation in both unsupervised and cross-lingual scenarios and our proposed algorithms seem to generalise well for several language pairs. We also discuss important future directions including the need for better evaluation metrics.     

Time Resolved Infrared Spectroscopic Analysis of Aerosol Formed by Photo-Oxidation of 1,3,5-Trimethylbenzene and α-Pinene

Secondary organic aerosol generated from the photo-oxidation of 1,3,5-trimethylbenzene and α-pinene in a smog chamber was investigated. Fourier Transform Infrared Spectroscopy (FT-IR) was used to monitor the time dependent change of five different functional groups in the aerosol (carboxylic acids, alcohols, organonitrates, ketones/aldehydes═carbonyls, and aliphatic carbon) sampled with an impactor on zinc-selenide discs. Based on model compounds for oxidation products of 1,3,5-trimethylbenzene and α-pinene, calibration factors for the different functional groups were calculated, and relative molar fractions of the functional groups were estimated from the analysis of the FT-IR spectra of the smog chamber samples. We show chemical evolutions of secondary organic aerosol on a time scale of up to 20 h. Time series with up to eight measurements per experiment show a strong increase in the relative amounts of carboxylic acid groups and a moderate increase of alcohol and carbonyl groups, whereas the relative amounts of organonitrates and the aliphatic carbon decrease. These findings support the assumption that the chemical composition of the aerosol continues to change for a long time after the particle formation has considerably slowed down. According to these observed changes with time, average, sum formulas of the molecules in the secondary organic aerosol are suggested.     

Structure and Replication of yDNA: A Novel Genetic Set Widened by Benzo‐Homologation

In a functioning genetic system, the information‐encoding molecule must form a regular self‐complementary complex (for example, the base‐paired double helix of DNA) and it must be able to encode information and pass it on to new generations. Here we study a benzo‐widened DNA‐like molecule (yDNA) as a candidate for an alternative genetic set, and we explicitly test these two structural and functional requirements. The solution structure of a 10 bp yDNA duplex is measured by using 2D‐NMR methods for a simple sequence composed of T–yA/yA–T pairs. The data confirm an antiparallel, right‐handed, hydrogen‐bonded helix resembling B‐DNA but with a wider diameter and enlarged base‐pair size. In addition to this, the abilities of two different polymerase enzymes (Klenow fragment of DNA pol I (Kf) and the repair enzyme Dpo4) to synthesize and extend the yDNA pairs T–yA, A–yT, and G–yC are measured by steady‐state kinetics studies. Not surprisingly, insertion of complementary bases opposite yDNA bases is inefficient due to the larger base‐pair size. We find that correct pairing occurs in several cases by both enzymes, but that common and relatively efficient mispairing involving T–yT and T–yC pairs interferes with fully correct formation and extension of pairs by these polymerases. Interestingly, the data show that extension of the large pairs is considerably more efficient with the flexible repair enzyme (Dpo4) than with the more rigid Kf enzyme. The results shed light on the properties of yDNA as a candidate for an alternative genetic information‐encoding molecule and as a tool for application in basic science and biomedicine.     

Self-adaptive differential evolution algorithm using population size reduction and three strategies

Many real-world optimization problems are large-scale in nature. In order to solve these problems, an optimization algorithm is required that is able to apply a global search regardless of the problems’ particularities. This paper proposes a self-adaptive differential evolution algorithm, called jDElscop, for solving large-scale optimization problems with continuous variables. The proposed algorithm employs three strategies and a population size reduction mechanism. The performance of the jDElscop algorithm is evaluated on a set of benchmark problems provided for the Special Issue on the Scalability of Evolutionary Algorithms and other Metaheuristics for Large Scale Continuous Optimization Problems. Non-parametric statistical procedures were performed for multiple comparisons between the proposed algorithm and three well-known algorithms from literature. The results show that the jDElscop algorithm can deal with large-scale continuous optimization effectively. It also behaves significantly better than other three algorithms used in the comparison, in most cases.