991 resultados para Quit Attempt Methods


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The aim of this study was to compare two nucleic acid extraction methods for the recovery of enteric viruses from activated sludge. Test samples were inoculated with human adenovirus (AdV), hepatitis A virus (HAV), poliovirus (PV) and rotavirus (RV) and were then processed by an adsorption-elution-precipitation method. Two extraction methods were used: an organic solvent-based method and a silica method. The organic-based method was able to recoup 20% of the AdV, 90% of the RV and 100% of both the PV and HAV from seeded samples. The silica method was able to recoup 1.8% of the AdV and 90% of the RV. These results indicate that the organic-based method is more suitable for detecting viruses in sewage sludge.

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In most psychological tests and questionnaires, a test score is obtained bytaking the sum of the item scores. In virtually all cases where the test orquestionnaire contains multidimensional forced-choice items, this traditionalscoring method is also applied. We argue that the summation of scores obtained with multidimensional forced-choice items produces uninterpretabletest scores. Therefore, we propose three alternative scoring methods: a weakand a strict rank preserving scoring method, which both allow an ordinalinterpretation of test scores; and a ratio preserving scoring method, whichallows a proportional interpretation of test scores. Each proposed scoringmethod yields an index for each respondent indicating the degree to whichthe response pattern is inconsistent. Analysis of real data showed that withrespect to rank preservation, the weak and strict rank preserving methodresulted in lower inconsistency indices than the traditional scoring method;with respect to ratio preservation, the ratio preserving scoring method resulted in lower inconsistency indices than the traditional scoring method

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Functional Data Analysis (FDA) deals with samples where a whole function is observedfor each individual. A particular case of FDA is when the observed functions are densityfunctions, that are also an example of infinite dimensional compositional data. In thiswork we compare several methods for dimensionality reduction for this particular typeof data: functional principal components analysis (PCA) with or without a previousdata transformation and multidimensional scaling (MDS) for diferent inter-densitiesdistances, one of them taking into account the compositional nature of density functions. The difeerent methods are applied to both artificial and real data (householdsincome distributions)

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Many multivariate methods that are apparently distinct can be linked by introducing oneor more parameters in their definition. Methods that can be linked in this way arecorrespondence analysis, unweighted or weighted logratio analysis (the latter alsoknown as "spectral mapping"), nonsymmetric correspondence analysis, principalcomponent analysis (with and without logarithmic transformation of the data) andmultidimensional scaling. In this presentation I will show how several of thesemethods, which are frequently used in compositional data analysis, may be linkedthrough parametrizations such as power transformations, linear transformations andconvex linear combinations. Since the methods of interest here all lead to visual mapsof data, a "movie" can be made where where the linking parameter is allowed to vary insmall steps: the results are recalculated "frame by frame" and one can see the smoothchange from one method to another. Several of these "movies" will be shown, giving adeeper insight into the similarities and differences between these methods

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An epidemic of sporotrichosis, a subcutaneous mycosis caused by the fungus Sporothrix schenckii, is ongoing in Rio de Janeiro, Brazil, in which cases of human infection are related to exposure to cats. In an attempt to demonstrate the zoonotic character of this epidemic using molecular methodology, we characterised by DNA-based typing methods 19 human and 25 animal S. schenckii isolates from the epidemic, as well as two control strains. To analyse the isolates, the random amplified polymorphic DNA (RAPD) technique was performed using three different primers, together with DNA fingerprinting using the minisatellite derived from the wild-type phage M13 core-sequence. The analyses generated amplicons with considerable polymorphism. Although isolates exhibited high levels of genetic relatedness, they could be clustered into 5-10 genotypes. The RAPD profiles of epidemic S. schenckii isolates could be distinguished from that of the United States isolate, displaying 20% similarity to each primer and 60% when amplified with the M13 primer. DNA fingerprinting of S. schenckii isolated from the nails (42.8%) and the oral cavities (66%) of cats were identical to related human samples, suggesting that there is a common infection source for animals and humans in this epidemic. It is clear that cats act as a vehicle for dissemination of S. schenckii.

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Influenza surveillance networks must detect early the viruses that will cause the forthcoming annual epidemics and isolate the strains for further characterization. We obtained the highest sensitivity (95.4%) with a diagnostic tool that combined a shell-vial assay and reverse transcription-PCR on cell culture supernatants at 48 h, and indeed, recovered the strain

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Autonomous underwater vehicles (AUV) represent a challenging control problem with complex, noisy, dynamics. Nowadays, not only the continuous scientific advances in underwater robotics but the increasing number of subsea missions and its complexity ask for an automatization of submarine processes. This paper proposes a high-level control system for solving the action selection problem of an autonomous robot. The system is characterized by the use of reinforcement learning direct policy search methods (RLDPS) for learning the internal state/action mapping of some behaviors. We demonstrate its feasibility with simulated experiments using the model of our underwater robot URIS in a target following task

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Interpretability and power of genome-wide association studies can be increased by imputing unobserved genotypes, using a reference panel of individuals genotyped at higher marker density. For many markers, genotypes cannot be imputed with complete certainty, and the uncertainty needs to be taken into account when testing for association with a given phenotype. In this paper, we compare currently available methods for testing association between uncertain genotypes and quantitative traits. We show that some previously described methods offer poor control of the false-positive rate (FPR), and that satisfactory performance of these methods is obtained only by using ad hoc filtering rules or by using a harsh transformation of the trait under study. We propose new methods that are based on exact maximum likelihood estimation and use a mixture model to accommodate nonnormal trait distributions when necessary. The new methods adequately control the FPR and also have equal or better power compared to all previously described methods. We provide a fast software implementation of all the methods studied here; our new method requires computation time of less than one computer-day for a typical genome-wide scan, with 2.5 M single nucleotide polymorphisms and 5000 individuals.

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In the accounting literature, interaction or moderating effects are usually assessed by means of OLS regression and summated rating scales are constructed to reduce measurement error bias. Structural equation models and two-stage least squares regression could be used to completely eliminate this bias, but large samples are needed. Partial Least Squares are appropriate for small samples but do not correct measurement error bias. In this article, disattenuated regression is discussed as a small sample alternative and is illustrated on data of Bisbe and Otley (in press) that examine the interaction effect of innovation and style of use of budgets on performance. Sizeable differences emerge between OLS and disattenuated regression

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A total of 138 isolates, 118 methicillin-resistant Staphylococcus aureus (MRSA) isolates (staphylococcal cassette chromosome type II, 20 isolates, type III, 39 isolates and type IV, 59 isolates) and 20 methicillin-sensitive S. aureus isolates were evaluated by phenotypic methods: cefoxitin and oxacillin disk diffusion (DD), agar dilution (AD), latex agglutination (LA), oxacillin agar screening (OAS) and chromogenic agar detection. All methods showed 100% specificity, but only the DD tests presented 100% sensitivity. The sensitivity of the other tests ranged from 82.2% (OAS)-98.3% (AD). The LA test showed the second lowest sensitivity (86.4%). The DD test showed high accuracy in the detection of MRSA isolates, but there was low precision in the detection of type IV isolates by the other tests, indicating that the genotypic characteristics of the isolates should be considered.

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The generation of an antigen-specific T-lymphocyte response is a complex multi-step process. Upon T-cell receptor-mediated recognition of antigen presented by activated dendritic cells, naive T-lymphocytes enter a program of proliferation and differentiation, during the course of which they acquire effector functions and may ultimately become memory T-cells. A major goal of modern immunology is to precisely identify and characterize effector and memory T-cell subpopulations that may be most efficient in disease protection. Sensitive methods are required to address these questions in exceedingly low numbers of antigen-specific lymphocytes recovered from clinical samples, and not manipulated in vitro. We have developed new techniques to dissect immune responses against viral or tumor antigens. These allow the isolation of various subsets of antigen-specific T-cells (with major histocompatibility complex [MHC]-peptide multimers and five-color FACS sorting) and the monitoring of gene expression in individual cells (by five-cell reverse transcription-polymerase chain reaction [RT-PCR]). We can also follow their proliferative life history by flow-fluorescence in situ hybridization (FISH) analysis of average telomere length. Recently, using these tools, we have identified subpopulations of CD8+ T-lymphocytes with distinct proliferative history and partial effector-like properties. Our data suggest that these subsets descend from recently activated T-cells and are committed to become differentiated effector T-lymphocytes.

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This study compares the diagnostic accuracy of the TF-Test® (TFT) for human parasitosis with results obtained using the traditional Kato-Katz (KK), Hoffman-Pons-Janer (HPJ), Willis and Baermann-Moraes (BM) techniques. Overall, four stool samples were taken from each individual; three alternate-day TFT stool samples and another sample that was collected in a universal container. Stool samples were taken from 331 inhabitants of the community of Quilombola Santa Cruz. The gold standard (GS) for protozoa detection was defined as the combined results for TFT, HPJ and Willis coproscopic techniques; for helminth detection, GS was defined as the combined results for all five coproscopic techniques (TFT, KK, HPJ, Willis and BM). The positivity rate of each method was compared using the McNemar test. While the TFT exhibited similar positivity rates to the GS for Entamoeba histolytica/dispar (82.4%) and Giardia duodenalis (90%), HPJ and Willis techniques exhibited significantly lower positivity rates for these protozoa. All tests exhibited significantly lower positivity rates compared with GS for the diagnosis of helminths. The KK technique had the highest positivity rate for diagnosing Schistosoma mansoni (74.6%), while the TFT had the highest positivity rates for Ascaris lumbricoides (58.1%) and hookworm (75%); HPJ technique had the highest positivity rate for Strongyloides stercoralis (50%). Although a combination of tests is the most accurate method for the diagnosis of enteral parasites, the TFT reliably estimates the prevalence of protozoa and selected helminths, such as A. lumbricoides and hookworm. Further studies are needed to evaluate the detection accuracy of the TFT in samples with varying numbers of parasites.

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In this study we compared two polymerase chain reaction (PCR) methods using either 16S ribosomal RNA (rRNA) or 23S rRNA gene primers for the detection of different Leptospira interrogans serovars. The performance of these two methods was assessed using DNA extracted from bovine tissues previously inoculated with several bacterial suspensions. PCR was performed on the same tissues before and after the formalin-fixed, paraffin-embedding procedure (FFPE tissues). The 23S rDNA PCR detected all fresh and FFPE positive tissues while the 16S rDNA-based protocol detected primarily the positive fresh tissues. Both methods are specific for pathogenic L. interrogans. The 23S-based PCR method successfully detected Leptospira in four dubious cases of human leptospirosis from archival tissue specimens and one leptospirosis-positive canine specimen. A sensitive method for leptospirosis identification in FFPE tissues would be a useful tool to screen histological specimen archives and gain a better assessment of human leptospirosis prevalence, especially in tropical countries, where large outbreaks can occur following the rainy season.