Relativistic deuteron structure function at large Q^2

The deuteron deep inelastic unpolarized structure function F_2^D is calculated using the Wilson operator product expansion method. The long distance behaviour, related to the deuteron bound state properties, is evaluated using the Bethe-Salpeter equation with one particle on mass shell. The calculation of the ratio F_2^D/F_2^N is compared with other convolution models showing important deviations in the region of large x. The implications in the evaluation of the neutron structure function from combined data on deuterons and protons are discussed.Comment: 7 pages, 1 ps figure, RevTeX source, 1 tar.gz file. Submited to Physical Letter

The Hamiltonian BRST quantization of a noncommutative nonabelian gauge theory and its Seiberg-Witten map

We consider the Hamiltonian BRST quantization of a noncommutative non abelian gauge theory. The Seiberg-Witten map of all phase-space variables, including multipliers, ghosts and their momenta, is given in first order in the noncommutative parameter $\theta$. We show that there exists a complete consistence between the gauge structures of the original and of the mapped theories, derived in a canonical way, once we appropriately choose the map solutions.Comment: 10 pages, Latex. Address adde

Novel Approaches for Fungal Transcriptomics from Host Samples.

Candida albicans adaptation to the host requires a profound reprogramming of the fungal transcriptome as compared to in vitro laboratory conditions. A detailed knowledge of the C. albicans transcriptome during the infection process is necessary in order to understand which of the fungal genes are important for host adaptation. Such genes could be thought of as potential targets for antifungal therapy. The acquisition of the C. albicans transcriptome is, however, technically challenging due to the low proportion of fungal RNA in host tissues. Two emerging technologies were used recently to circumvent this problem. One consists of the detection of low abundance fungal RNA using capture and reporter gene probes which is followed by emission and quantification of resulting fluorescent signals (nanoString). The other is based first on the capture of fungal RNA by short biotinylated oligonucleotide baits covering the C. albicans ORFome permitting fungal RNA purification. Next, the enriched fungal RNA is amplified and subjected to RNA sequencing (RNA-seq). Here we detail these two transcriptome approaches and discuss their advantages and limitations and future perspectives in microbial transcriptomics from host material

HERA-B Framework for Online Calibration and Alignment

This paper describes the architecture and implementation of the HERA-B framework for online calibration and alignment. At HERA-B the performance of all trigger levels, including the online reconstruction, strongly depends on using the appropriate calibration and alignment constants, which might change during data taking. A system to monitor, recompute and distribute those constants to online processes has been integrated in the data acquisition and trigger systems.Comment: Submitted to NIM A. 4 figures, 15 page

Identifying meaningful clusters in malware data

Finding meaningful clusters in drive-by-download malware data is a particularly difficult task. Malware data tends to contain overlapping clusters with wide variations of cardinality. This happens because there can be considerable similarity between malware samples (some are even said to belong to the same family), and these tend to appear in bursts. Clustering algorithms are usually applied to normalised data sets. However, the process of normalisation aims at setting features with different range values to have a similar contribution to the clustering. It does not favour more meaningful features over those that are less meaningful, an effect one should perhaps expect of the data pre-processing stage. In this paper we introduce a method to deal precisely with the problem above. This is an iterative data pre-processing method capable of aiding to increase the separation between clusters. It does so by calculating the within-cluster degree of relevance of each feature, and then it uses these as a data rescaling factor. By repeating this until convergence our malware data was separated in clear clusters, leading to a higher average silhouette width

In silico validation of personalized safe intervals for carbohydrate counting errors

For patients with Type 1 diabetes mellitus (T1DM), accurate carbohydrate counting (CC) is essential for successful blood glucose regulation. Unfortunately, mistakes are common and may lead to an incorrect dosage of prandial insulin. In this work, we aim to demonstrate that each person has their own limits for CC errors, which can be computed using patient-specific data. To validate the proposed method, we tested it using several scenarios to investigate the effect of different CC errors on postprandial blood glucose. Virtual subjects from the T1DM Simulator were used in a clinical trial involving 450 meals over 90 days, all following the same daily meal plan but with different intervals for CC errors near, below, and above the limit computed for each patient. The results show that CC errors within personalized limits led to acceptable postprandial glycemic fluctuations. In contrast, experiments where 50% and 97.5% of the meals present a CC error outside the computed safe interval revealed a pronounced degradation of the time in range. Given these results, we consider the proposed method for obtaining personalized limits for CC errors an excellent starting point for an initial assessment of patients? capabilities in CC and to provide appropriate ongoing education.511F-603F-4B30 | Francisco MirandaN/

Resultados preliminares do projeto zoneamento do déficit hídrico do TSA utilizando técnicas de teledetecção espacial.

Definição do problema; Apresentação do organograma de trabalho a ser realizado; Dados tratados; Constituição do arquivo bruto.bitstream/item/143278/1/ID-31857.pdfNão publicado