13,443 research outputs found

    Bulk transitions of twelve flavor QCD and UA(1)U_A(1) symmetry

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    We present an update on our ongoing study on the nature of the bulk transition observed at strong coupling in the SU(3) gauge theory with N_f = 12 flavors in the fundamental representation. We show evidence that there is a first order chiral symmetry breaking bulk transition separating a region at weak coupling where chiral symmetry is restored from a region at strong coupling where chiral symmetry is broken. We also discuss hints of a separate partial restoration of U_A(1) at weaker coupling. The results are in agreement with restoration of conformality in non abelian gauge theories as the number of flavors is increased.Comment: 7 pages, 10 figures, XXIX International Symposium on Lattice Field Theor

    Detecció de la relació malaltia-símptoma entre termes de l'àmbit mèdic: una aproximació basada en corpus

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    Els especialistes en terminologia afirmen que els textos especialitzats són, quant al contingut, estructures formades per termes relacionats conceptualment (Cabré, 1999). L'objectiu principal d'aquest article és mostrar que existeixen patrons lingüístics que evidencien la relació malaltia-símptoma i que poden servir per detectar semiautomàticament o automàtica aquesta relació, mitjançant una metodologia concreta. Aquesta metodologia es basa en el fet que, un cop obtinguts i analitzats uns determinats contextos, s'extreuen marques lingüístiques que evidenciïn la relació i serveixin per realitzar una generalització de patrons lingüístics. En l'estudi observem que molts dels símptomes no apareixen en les definicions dels recursos terminològics mèdics, però sí en els textos especialitzats del corpus. També detectem que molts dels símptomes apareixen mitjançant col·locacions especialitzades.Experts in terminology state that specialised texts are, with respect to their content, structures formed by terms, and these terms are conceptually connected (Cabré, 1999). The main goal of this article is to prove the existence of linguistic patterns that show the disease–symptom relation. These patterns can be useful to detect the relation semiautomatically or automatically by means of a specific methodology. This methodology is based on the fact that, once we extract and analyse certain contexts, we can obtain linguistic marks that show this relation, allowing a generalisation of patterns. Our results show that most symptoms are not included in the definitions given in medical terminological resources, but they are indeed included in the medical corpus that has been analysed in this project. Moreover, most symptoms are described with specialised collocations

    EVALUASI PELAKSANAAN INVESTIGASI KONTAK KASUS TUBERKULOSIS DI KABUPATEN TULUNGAGUNG, PROVINSI JAWA TIMUR

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    Angka penemuan kasus Tuberkulosis baru di Kabupaten Tulungagung selama tiga tahun terakhir belum memenuhi target yang telah ditetapkan dan cenderung menurun, hal ini didukung dengan rendahnya cakupan kegiatan Investigasi kontak kasus Tuberkulosis yang merupakan salah satu cara penemuan kasus Tuberkulosis secara aktif. Penelitian ini bertujuan melakukan evaluasi pelaksanaan investigasi kontak kasus tuberkulosis yang diimplementasikan di Kabupaten Tulungagung pada tahun 2021. Penelitian ini menggunakan rancangan studi deskriptif dengan pendekatan evaluasi yang dilakukan pada Bulan Juli Tahun 2022. Data sekunder dikumpulkan dari laporan SITB. Evaluasi dilakukan pada capaian indikator utama, proses dan output dalam implementasi pelaksanaan investigasi kontak. Hasil penelitian menunjukan pada indikator utama, capaian kasus indeks yang diinvestigasi kontak, temuan kasus TB baru dari hasil investigasi kontak, dan pemberian pengobatan pencegahan TB bagi kontak anak <5 masih belum maksimal. Pada indikator proses, kontak yang diskrining TBC dan terduga TBC yang dirujuk dan dilakukan pemeriksaan sudah baik. Pada indikator output, kasus TBC yang terkonfirmasi dan memulai pengobatan sudah memenuhi target sedangkan kasus TBC yang menyelesaikan pengobatan belum memenuhi target program. Pelaksanaan investigasi kontak kasus tuberkulosis di Kabupaten Tulungagung belum maksimal, perlu adanya monitoring dan evaluasi yang rutin secara berjenjang

    Fast Community Identification by Hierarchical Growth

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    A new method for community identification is proposed which is founded on the analysis of successive neighborhoods, reached through hierarchical growth from a starting vertex, and on the definition of communities as a subgraph whose number of inner connections is larger than outer connections. In order to determine the precision and speed of the method, it is compared with one of the most popular community identification approaches, namely Girvan and Newman's algorithm. Although the hierarchical growth method is not as precise as Girvan and Newman's method, it is potentially faster than most community finding algorithms.Comment: 6 pages, 5 figure

    Strong correlations between text quality and complex networks features

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    Concepts of complex networks have been used to obtain metrics that were correlated to text quality established by scores assigned by human judges. Texts produced by high-school students in Portuguese were represented as scale-free networks (word adjacency model), from which typical network features such as the in/outdegree, clustering coefficient and shortest path were obtained. Another metric was derived from the dynamics of the network growth, based on the variation of the number of connected components. The scores assigned by the human judges according to three text quality criteria (coherence and cohesion, adherence to standard writing conventions and theme adequacy/development) were correlated with the network measurements. Text quality for all three criteria was found to decrease with increasing average values of outdegrees, clustering coefficient and deviation from the dynamics of network growth. Among the criteria employed, cohesion and coherence showed the strongest correlation, which probably indicates that the network measurements are able to capture how the text is developed in terms of the concepts represented by the nodes in the networks. Though based on a particular set of texts and specific language, the results presented here point to potential applications in other instances of text analysis.Comment: 8 pages, 8 figure

    An Analytical Approach to Neuronal Connectivity

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    This paper describes how realistic neuromorphic networks can have their connectivity properties fully characterized in analytical fashion. By assuming that all neurons have the same shape and are regularly distributed along the two-dimensional orthogonal lattice with parameter Δ\Delta, it is possible to obtain the accurate number of connections and cycles of any length from the autoconvolution function as well as from the respective spectral density derived from the adjacency matrix. It is shown that neuronal shape plays an important role in defining the spatial spread of network connections. In addition, most such networks are characterized by the interesting phenomenon where the connections are progressively shifted along the spatial domain where the network is embedded. It is also shown that the number of cycles follows a power law with their respective length. Morphological measurements for characterization of the spatial distribution of connections, including the adjacency matrix spectral density and the lacunarity of the connections, are suggested. The potential of the proposed approach is illustrated with respect to digital images of real neuronal cells.Comment: 4 pages, 6 figure
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