126 resultados para 6807


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Date of Acceptance: 27/10/2015

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The chemical composition of surface associated metabolites of two Fucus species (Fucus vesiculosus and Fucus serratus) was analysed by means of gas chromatography-mass spectrometry (GC-MS) to describe temporal patterns in chemical surface composition. Method: The two perennial brown macroalgae F. vesiculosus and F. serratus were sampled monthly at Bülk, outer Kiel Fjord, Germany (54°27'21 N / 10°11'57 E) over an entire year (August 2012 - July 2013). Per month and species six non-fertile Fucus individuals were collected from mixed stands at a depth of 0.5 m under mid water level. For surface extraction approx. 50 g of the upper 5-10 cm apical thalli tips were cut off per species. The surface extraction of Fucus was performed according to the protocol of de Nys and co-workers (1998) with minor modifications (see Rickert et al. 2015). GC/EI-MS measurements were performed with a Waters GCT premier (Waters, Manchester, UK) coupled to an Agilent 6890N GC equipped with a DB-5 ms 30 m column (0.25 mm internal diameter, 0.25 mM film thickness, Agilent, USA). The inlet temperature was maintained at 250°C and samples were injected in split 10 mode. He carrier gas flow was adjusted to 1 ml min-1. Alkanes were used for referencing of retention times. For further details (GC-MS sample preparation and analysis) see the related publication (Rickert et al. submitted to PLOS ONE).

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The present article reflects the progress of an ongoing master’s dissertation on language engineering. The main goal of the work here described, is to infer a programmer’s profile through the analysis of his source code. After such analysis the programmer shall be placed on a scale that characterizes him on his language abilities. There are several potential applications for such profiling, namely, the evaluation of a programmer’s skills and proficiency on a given language or the continuous evaluation of a student’s progress on a programming course. Throughout the course of this project and as a proof of concept, a tool that allows the automatic profiling of a Java programmer is under development. This tool is also introduced in the paper and its preliminary outcomes are discussed.

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The purpose of this study was to examine the reliability and validity of the School Anxiety Inventory (SAI) using a sample of 646 Slovenian adolescents (48% boys), ranging in age from 12 to 19 years. Single confirmatory factor analyses replicated the correlated four-factor structure of scores on the SAI for anxiety-provoking school situations (Anxiety about School Failure and Punishment, Anxiety about Aggression, Anxiety about Social Evaluation, and Anxiety about Academic Evaluation), and the three-factor structure of the anxiety response systems (Physiological Anxiety, Cognitive Anxiety, and Behavioral Anxiety). Equality of factor structures was compared using multigroup confirmatory factor analyses. Measurement invariance for the four- and three-factor models was obtained across gender and school-level samples. The scores of the instrument showed high internal reliability and adequate test–retest reliability. The concurrent validity of the SAI scores was also examined through its relationship with the Social Anxiety Scale for Adolescents (SASA) scores and the Questionnaire about Interpersonal Difficulties for Adolescents (QIDA) scores. Correlations of the SAI scores with scores on the SASA and the QIDA were of low to moderate effect sizes.