959 resultados para Clustering methods


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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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BACKGROUND: Sequence data from resistance testing offer unique opportunities to characterize the structure of human immunodeficiency virus (HIV) infection epidemics. METHODS: We analyzed a representative set of HIV type 1 (HIV-1) subtype B pol sequences from 5700 patients enrolled in the Swiss HIV Cohort Study. We pooled these sequences with the same number of sequences from foreign epidemics, inferred a phylogeny, and identified Swiss transmission clusters as clades having a minimal size of 10 and containing >or=80% Swiss sequences. RESULTS: More than one-half of Swiss patients were included within 60 transmission clusters. Most transmission clusters were significantly dominated by specific transmission routes, which were used to identify the following patient groups: men having sex with men (MSM) (38 transmission clusters; average cluster size, 29 patients) or patients acquiring HIV through heterosexual contact (HETs) and injection drug users (IDUs) (12 transmission clusters; average cluster size, 144 patients). Interestingly, there were no transmission clusters dominated by sequences from HETs only. Although 44% of all HETs who were infected between 1983 and 1986 clustered with injection drug users, this percentage decreased to 18% for 2003-2006 (P<.001), indicating a diminishing role of injection drug users in transmission among HETs over time. CONCLUSIONS: Our analysis suggests (1) the absence of a self-sustaining epidemic of HIV-1 subtype B in HETs in Switzerland and (2) a temporally decreasing clustering of HIV infections in HETs and IDUs.

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In image segmentation, clustering algorithms are very popular because they are intuitive and, some of them, easy to implement. For instance, the k-means is one of the most used in the literature, and many authors successfully compare their new proposal with the results achieved by the k-means. However, it is well known that clustering image segmentation has many problems. For instance, the number of regions of the image has to be known a priori, as well as different initial seed placement (initial clusters) could produce different segmentation results. Most of these algorithms could be slightly improved by considering the coordinates of the image as features in the clustering process (to take spatial region information into account). In this paper we propose a significant improvement of clustering algorithms for image segmentation. The method is qualitatively and quantitative evaluated over a set of synthetic and real images, and compared with classical clustering approaches. Results demonstrate the validity of this new approach

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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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Wake-promoting drugs are widely used to treat excessive daytime sleepiness. The neuronal pathways involved in wake promotion are multiple and often not well characterized. We tested d-amphetamine, modafinil, and YKP10A, a novel wake-promoting compound, in three inbred strains of mice. The wake duration induced by YKP10A and d-amphetamine depended similarly on genotype, whereas opposite strain differences were observed after modafinil. Electroencephalogram (EEG) analysis during drug-induced wakefulness revealed a transient approximately 2 Hz slowing of theta oscillations and an increase in beta-2 (20-35 Hz) activity only after YKP10A. Gamma activity (35-60 Hz) was induced by all drugs in a drug- and genotype-dependent manner. Brain transcriptome and clustering analyses indicated that the three drugs have both common and specific molecular signatures. The correlation between specific EEG and gene-expression signatures suggests that the neuronal pathways activated to stay awake vary among drugs and genetic background.

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Estudi, disseny i implementació de diferents tècniques d’agrupament defibres (clustering) per tal d’integrar a la plataforma DTIWeb diferentsalgorismes de clustering i tècniques de visualització de clústers de fibres de forma quefaciliti la interpretació de dades de DTI als especialistes

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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.

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A methodology of exploratory data analysis investigating the phenomenon of orographic precipitation enhancement is proposed. The precipitation observations obtained from three Swiss Doppler weather radars are analysed for the major precipitation event of August 2005 in the Alps. Image processing techniques are used to detect significant precipitation cells/pixels from radar images while filtering out spurious effects due to ground clutter. The contribution of topography to precipitation patterns is described by an extensive set of topographical descriptors computed from the digital elevation model at multiple spatial scales. Additionally, the motion vector field is derived from subsequent radar images and integrated into a set of topographic features to highlight the slopes exposed to main flows. Following the exploratory data analysis with a recent algorithm of spectral clustering, it is shown that orographic precipitation cells are generated under specific flow and topographic conditions. Repeatability of precipitation patterns in particular spatial locations is found to be linked to specific local terrain shapes, e.g. at the top of hills and on the upwind side of the mountains. This methodology and our empirical findings for the Alpine region provide a basis for building computational data-driven models of orographic enhancement and triggering of precipitation. Copyright (C) 2011 Royal Meteorological Society .

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The diagnosis of schistosomiasis is problematic in low-intensity transmission areas because parasitological methods lack sensitivity and molecular methods are neither widely available nor extensively validated. Helmintex is a method for isolating eggs from large faecal samples. We report preliminary results of a comparative evaluation of the Helmintex and Kato-Katz (KK) methods for the diagnosis of schistosomiasis in a low-intensity transmission area in Bandeirantes, Paraná, southern Brazil. Eggs were detected by both methods in seven patients, whereas only Helmintex yielded positive results in four individuals. The results confirm the previously demonstrated higher sensitivity of the Helmintex method compared with the KK method.

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Laboratory diagnosis of intestinal schistosomiasis mansoni can be accomplished through various methods of stool examination to detect parasites, ranging from the most classic tests (Kato-Katz) to several methods that are still undergoing validation. This study was conducted to assess two new parasite identification methods for diagnosing schistosomiasis mansoni in residents of a low endemic area in the municipality of Maranguape, in the state of Ceará, Brazil using the Kato-Katz method as a reference and serology (enzyme-linked immunosorbent assay) for the screening of patients. The Kato-Katz, the saline gradient method and the Helmintex® method parasite identification methods were employed only in subjects who exhibited positive serologic tests. The test results were then analysed and treatment of positive individuals was subsequently performed. After comparing the test results, we observed that the saline gradient method and the Helmintex® method were more effective in diagnosing schistosomiasis mansoni in the study area compared with the Kato-Katz method.