914 resultados para predictive coding


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Although the study of factors affecting career success has shown connections between biographical and other aspects related to ability, knowledge and personality, few studies have examined the relationship be-tween emotional intelligence and professional success at the initial career stage. When these studies were carried out, the results showed significant relationships between the dimensions of emotional intelligence (emotional self-awareness, self-regulation, social awareness or social skills) and the level of professional competence. In this paper, we analyze the relationship between perceived emotional intelligence, measured by the Trait Meta-Mood Scale (TMMS-24) questionnaire, general intelligence assessed by the Cattell factor "g" test, scale 3, and extrinsic indicators of career success, in a sample of 130 graduates at the beginning of their careers. Results from hierarchical regression analysis indicate that emotional intelligence makes a specific contribution to the prediction of salary, after controlling the general intelligence effect. The perceived emotional intelligence dimensions of TMMS repair, TMMS attention and sex show a higher correlation and make a greater contribution to professional success than general intelligence. The implications of these results for the development of socio-emotional skills among University graduates are discussed.

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Two predictive models are developed in this article: the first is designed to predict people's attitudes to alcoholic drinks, while the second sets out to predict the use of alcohol in relation to selected individual values. University students (N = 1,500) were recruited through stratified sampling based on sex and academic discipline. The questionnaire used obtained information on participants' alcohol use, attitudes and personal values. The results show that the attitudes model correctly classifies 76.3% of cases. Likewise, the model for level of alcohol use correctly classifies 82% of cases. According to our results, we can conclude that there are a series of individual values that influence drinking and attitudes to alcohol use, which therefore provides us with a potentially powerful instrument for developing preventive intervention programs.

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The modeling of complex dynamic systems depends on the solution of a differential equations system. Some problems appear because we do not know the mathematical expressions of the said equations. Enough numerical data of the system variables are known. The authors, think that it is very important to establish a code between the different languages to let them codify and decodify information. Coding permits us to reduce the study of some objects to others. Mathematical expressions are used to model certain variables of the system are complex, so it is convenient to define an alphabet code determining the correspondence between these equations and words in the alphabet. In this paper the authors begin with the introduction to the coding and decoding of complex structural systems modeling.

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The insulin-like growth factor 2 antisense (Igf2as) gene is part of the Ins-Igf2-H19 imprinted gene cluster. The function of the paternally expressed Igf2as is still elusive. In our previous work, we showed that Igf2as transcripts were located in the cytoplasm of C2C12 mouse myoblast cells, associated with polysomes and polyadenylated suggesting that Igf2as is protein coding. In the present work, the protein coding capacity of Igf2as was investigated. We demonstrate for the first time the existence of a polypeptide translated from an Igf2as construct. Furthermore, an RNA-Seq analysis was performed using RNA prepared from skeletal muscles of newborn wild-type and ∆ DMR1-U2 mice to further elucidate the function of Igf2as transcripts. We found no evidence for a regulatory role of Igf2as in the imprinted gene cluster. Interestingly, the RNA-Seq analysis indicated that Igf2as plays a role in the energy metabolism, the cell cycle, histone acetylation and muscle contraction pathways. Our Igf2as investigations further elucidated that there are two distinct Igf2as transcripts corresponding to two putative ORFs.

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As translation is the final step in gene expression it is particularly important to understand the processes involved in translation regulation. It was shown in the last years that a class of RNA, the nonprotein-coding RNAs (ncRNAs), is involved in regulation of gene expression via various mechanisms (e.g. gene silencing by microRNAs). Almost all of these ncRNA discovered so far target the mRNA in order to modulate protein biosynthesis, this is rather unexpected considering the crucial role of the ribosome during gene expression. However, recent data from our laboratory showed that there is a new class of ncRNAs, which target the ribosome itself [Gebetsberger et al., 2012/ Pircher et al, 2014]. These so called ribosome-associated ncRNAs (rancRNAs) have an impact on translation regulation, mainly by interfering / modulating the rate of protein biosynthesis. The main goal of this project is to identify and describe novel potential regulatory rancRNAs in H. volcanii with the focus on intergenic candidates. Northern blot analyses already revealed interactions with the ribosome and showed differential expression of rancRNAs during different growth phases or under specific stress conditions. To investigate the biological relevance of these rancRNAs, knock-outs were generated in H. volcanii which were used for phenotypic characterization studies. The rancRNA s194 showed association with the 50S ribosomal subunit in vitro and in vivo and was capable of inhibiting peptide bond formation. These preliminary data for the rancRNA s194 make it an interesting candidate for further functional studies to identify the molecular mechanisms by which rancRNAs can modulate protein biosynthesis. Characterization of further rancRNA candidates are also underway.

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National Highway Traffic Safety Administration, Washington, D.C.

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National Highway Traffic Safety Administration, Washington, D.C.

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National Highway Traffic Safety Administration, National Center for Statistics and Analysis, Washington, D.C.

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National Highway Safety Bureau, Washington, D.C.

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Mode of access: Internet.