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High impact events, political changes and new technologies are reflected in our language and lead to constant evolution of terms, expressions and names. Not knowing about names used in the past for referring to a named entity can severely decrease the performance of many computational linguistic algorithms. We propose NEER, an unsupervised method for named entity evolution recognition independent of external knowledge sources. We find time periods with high likelihood of evolution. By analyzing only these time periods using a sliding window co-occurrence method we capture evolving terms in the same context. We thus avoid comparing terms from widely different periods in time and overcome a severe limitation of existing methods for named entity evolution, as shown by the high recall of 90% on the New York Times corpus. We compare several relatedness measures for filtering to improve precision. Furthermore, using machine learning with minimal supervision improves precision to 94%.
Nicht allzu häufig wird man in den Schriftverzeichnissen deutscher Althistoriker auf Studien zur Zeitrechnung und zum antiken Kalenderwesen stoßen, wie dies bei Jürgen Malitz der Fall ist. Im Jahr 1987 ist sein viel beachteter Aufsatz zur Kalenderreform Caesars erschienen und jüngst hat er sich unter dem Titel "Die Ordnung der Zeit", wiederum ausgehend von Caesars Reform, verschiedensten Aspekten des antiken Kalenderwesens zugewandt und einen Bogen bis in die Gegenwart gespannt. Dieses Interessengebiet des Geehrten aufgreifend, möchte der vorliegende Beitrag einen wenig erforschten Aspekt dessen beleuchten, wie Zeit in der Antike als ökonomische Ressource begriffen und instrumentalisiert wurde. ...
Modelling protein structure seems a challenging enterprise because the number of structure parameters required ordinarily exceeds the amount of independent data points available from experimental observations. Expressing the predominant conformation of a protein in terms of a geometry model, a polypeptide chain consisting of N atoms would command 3N – 6 Cartesian coordinates be fixed. Even for small proteins, this becomes a daunting number. Fortunately, so-called holonomic constraints limit the number of variables, leaving substantially fewer, truly relevant parameters for folding the polypeptide chain into its native tertiary structure. For example, adjusting bond lengths and the many angles between the covalent bonds connecting the atoms is of little concern and appropriate standard values can be inserted from tableworks (Pople & Gordon, 1967; Engh & Huber, 1991, 2006). Table 1 exemplifies for the 147-residue protein Desulfovibrio vulgaris flavodoxin how the number of truly independent internal rotational degrees of freedom amounts to less than one-tenth of the Cartesian coordinate set size...
Quantum theory is the most successful physical theory ever. About one third of the gross national product in the developed countries results from its applications. These applications range from nuclear power to most of the high-tech tools for computing, laser, solar cells and so on. No limit for its range of validity has been found up to now...
1. Introduction: The autosomal dominant cerebellar ataxias (ADCA) are a clinically, pathologically and genetically heterogeneous group of neurodegenerative disorders caused by degeneration of cerebellum and its afferent and efferent connections. The degenerative process may additionally involves the ponto- medullar systems, pyramidal tracts, basal ganglia, cerebral cortex, peripheral nerves (ADCA I) and the retina (ADCA II), or can be limited to the cerebellum (ADCA III) (Harding et al., 1993). The most common of these dominantly inherited autosomal ataxias, ADCA I, includes many Spinocerebellar Ataxias (SCA) subtypes, some of which are caused by pathological CAG trinucleotide repeat expansion in the coding region on the mutated gene. Such is the case for SCA1, SCA2, SCA3/MJD, SCA6, SCA7, SCA17 and Dentatorubral-pallidoluysian atrophy (DRPLA) (Matilla et al., 2006). Among the almost 30 SCAs, the variant SCA2 is the second most prevalent subtype worldwide, only surpassed by SCA3 (Schöls et al., 2004; Matilla et al., 2006; Auburger, 2011)...