8 resultados para Rothesay (GB)

em Biblioteca Digital da Produção Intelectual da Universidade de São Paulo


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This paper presents a theoretical model developed for estimating the power, the optical signal to noise ratio and the number of generated carriers in a comb generator, having as a reference the minimum optical signal do noise ratio at the receiver input, for a given fiber link. Based on the recirculating frequency shifting technique, the generator relies on the use of coherent and orthogonal multi-carriers (Coherent-WDM) that makes use of a single laser source (seed) for feeding high capacity (above 100 Gb/s) systems. The theoretical model has been validated by an experimental demonstration, where 23 comb lines with an optical signal to noise ratio ranging from 25 to 33 dB, in a spectral window of similar to 3.5 nm, are obtained.

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We present a simultaneous optical signal-to-noise ratio (OSNR) and differential group delay (DGD) monitoring method based on degree of polarization (DOP) measurements in optical communications systems. For the first time in the literature (to our best knowledge), the proposed scheme is demonstrated to be able to independently and simultaneously extract OSNR and DGD values from the DOP measurements. This is possible because the OSNR is related to maximum DOP, while DGD is related to the ratio between the maximum and minimum values of DOP. We experimentally measured OSNR and DGD in the ranges from 10 to 30 dB and 0 to 90 ps for a 10 Gb/s non-return-to-zero signal. A theoretical analysis of DOP accuracy needed to measure low values of DGD and high OSNRs is carried out, showing that current polarimeter technology is capable of yielding an OSNR measurement within 1 dB accuracy, for OSNR values up to 34 dB, while DGD error is limited to 1.5% for DGD values above 10 ps. For the first time to our knowledge, the technique was demonstrated to accurately measure first-order polarization mode dispersion (PMD) in the presence of a high value of second-order PMD (as high as 2071 ps(2)). (C) 2012 Optical Society of America

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The polychaetes assemblage structure was used in order to investigate taxonomic sufficiency in a heavily polluted tropical bay. Species abundance was aggregated into progressively higher taxa matrices (genus, family, order) and was analyzed using univariate and multivariate techniques. Polychaetes distribution in Guanabara Bay (GB) was in accordance with a pollution gradient, probably ruled by the organic enrichment, consequent effects of hypoxia and altered redox conditions coupled with prevailing patterns of circulation. Within the sectors of GB, an increasing gradient in species richness and occurrence was observed, ranging from the azoic and impoverished stations in the inner sector to a well-structured community in terms of species composition and abundance inhabiting the outer sector. Multivariate statistical analysis showed similar results when species were aggregated into genera and families, while greater difference occurred at coarser taxonomic identification (order). The literature about taxonomic sufficiency has demonstrated that faunal patterns at different taxonomic levels tend to become similar with increased pollution. In GB, an analysis carried out solely at family level is perfectly adequate to describe the environmental gradient, considered a useful tool for a quick environmental assessment. (C) 2011 Elsevier Ltd. All rights reserved.

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Abstract Background Cocaine abuse is a serious and socially damaging illegal drug problem. Different routes of administration are associated with a specific progression of use, different degrees of abuse liability, propensity for dependence and treatment response. There have been relatively few studies comparing different cocaine users groups and no studies into the characterization of the group of individuals reporting concurrent use of powder cocaine and crack cocaine. Methods Six hundred and ninety-nine cocaine users were assessed during the period August 1997 to October 1998 in one outpatient and six inpatient clinics located in the São Paulo, Brazil. Patients were interviewed using a structured questionnaire schedule in Portuguese, designed specifically for the Brazilian population. The statistical analyses were performed using either ANOVA or a chi-squared test and focusing on their preferred form of use/route of administration and other variables. Results For 83% of the variables tested in this study, the Dual Users subgroup (using both powder and crack cocaine) demonstrated statistical differences from the single drug user subgroups. Those differences include the initiation of cocaine, the abuse of other illicit drugs, and rates of criminal history. Conclusion These data suggest cocaine-dependent individuals who report use of both powder and crack cocaine are an at least partially, distinct subgroup. However, further studies will be necessary to confirm this and to determine if they also show a different treatment response.

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Abstract Background Oral squamous cell carcinoma (OSCC) is a frequent neoplasm, which is usually aggressive and has unpredictable biological behavior and unfavorable prognosis. The comprehension of the molecular basis of this variability should lead to the development of targeted therapies as well as to improvements in specificity and sensitivity of diagnosis. Results Samples of primary OSCCs and their corresponding surgical margins were obtained from male patients during surgery and their gene expression profiles were screened using whole-genome microarray technology. Hierarchical clustering and Principal Components Analysis were used for data visualization and One-way Analysis of Variance was used to identify differentially expressed genes. Samples clustered mostly according to disease subsite, suggesting molecular heterogeneity within tumor stages. In order to corroborate our results, two publicly available datasets of microarray experiments were assessed. We found significant molecular differences between OSCC anatomic subsites concerning groups of genes presently or potentially important for drug development, including mRNA processing, cytoskeleton organization and biogenesis, metabolic process, cell cycle and apoptosis. Conclusion Our results corroborate literature data on molecular heterogeneity of OSCCs. Differences between disease subsites and among samples belonging to the same TNM class highlight the importance of gene expression-based classification and challenge the development of targeted therapies.

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Abstract Background RNAs transcribed from intronic regions of genes are involved in a number of processes related to post-transcriptional control of gene expression. However, the complement of human genes in which introns are transcribed, and the number of intronic transcriptional units and their tissue expression patterns are not known. Results A survey of mRNA and EST public databases revealed more than 55,000 totally intronic noncoding (TIN) RNAs transcribed from the introns of 74% of all unique RefSeq genes. Guided by this information, we designed an oligoarray platform containing sense and antisense probes for each of 7,135 randomly selected TIN transcripts plus the corresponding protein-coding genes. We identified exonic and intronic tissue-specific expression signatures for human liver, prostate and kidney. The most highly expressed antisense TIN RNAs were transcribed from introns of protein-coding genes significantly enriched (p = 0.002 to 0.022) in the 'Regulation of transcription' Gene Ontology category. RNA polymerase II inhibition resulted in increased expression of a fraction of intronic RNAs in cell cultures, suggesting that other RNA polymerases may be involved in their biosynthesis. Members of a subset of intronic and protein-coding signatures transcribed from the same genomic loci have correlated expression patterns, suggesting that intronic RNAs regulate the abundance or the pattern of exon usage in protein-coding messages. Conclusion We have identified diverse intronic RNA expression patterns, pointing to distinct regulatory roles. This gene-oriented approach, using a combined intron-exon oligoarray, should permit further comparative analysis of intronic transcription under various physiological and pathological conditions, thus advancing current knowledge about the biological functions of these noncoding RNAs.

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The effects of fluoride, which is present in different oral hygiene products, deserve more investigation because little is known about their impact on the surface of titanium, which is largely used in Implantology. This study evaluated the surface of commercially pure titanium (cpTi) after exposure to different concentrations of sodium fluoride (NaF). The hypothesis tested in this study was that different concentrations of NaF applied at different time intervals can affect the titanium surface in different ways. The treatments resulted in the following groups: GA (control): immersion in distilled water; GB: immersion in 0.05% NaF for 3 min daily; GC: immersion in 0.2% NaF for 3 min daily; GD: immersion in 0.05% NaF for 3 min every 2 weeks; and GE: immersion in 0.2% NaF for 3 min every 2 weeks. The experiment lasted 60 days. Roughness was measured initially and every 15 days subsequently up to 60 days. After 60 days, corrosion analysis and anodic polarization were done. The samples were examined by scanning electron microscopy (SEM). The roughness data were analyzed by ANOVA and there was no significant difference among groups and among time intervals. The corrosion data (i corr) were analyzed by the Mann-Whitney test, and significant differences were found between GA and GC, GB and GC, GC and GD, GC and GE. SEM micrographs showed that the titanium surface exposed to NaF presented corrosion that varied with the different concentrations. This study suggests that the use of 0.05% NaF solution on cpTi is safe, whereas the 0.2% NaF solution should be carefully evaluated with regard to its daily use.

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Given a large image set, in which very few images have labels, how to guess labels for the remaining majority? How to spot images that need brand new labels different from the predefined ones? How to summarize these data to route the user’s attention to what really matters? Here we answer all these questions. Specifically, we propose QuMinS, a fast, scalable solution to two problems: (i) Low-labor labeling (LLL) – given an image set, very few images have labels, find the most appropriate labels for the rest; and (ii) Mining and attention routing – in the same setting, find clusters, the top-'N IND.O' outlier images, and the 'N IND.R' images that best represent the data. Experiments on satellite images spanning up to 2.25 GB show that, contrasting to the state-of-the-art labeling techniques, QuMinS scales linearly on the data size, being up to 40 times faster than top competitors (GCap), still achieving better or equal accuracy, it spots images that potentially require unpredicted labels, and it works even with tiny initial label sets, i.e., nearly five examples. We also report a case study of our method’s practical usage to show that QuMinS is a viable tool for automatic coffee crop detection from remote sensing images.