766 resultados para fuzzy coding


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Canonical correspondence analysis and redundancy analysis are two methods of constrained ordination regularly used in the analysis of ecological data when several response variables (for example, species abundances) are related linearly to several explanatory variables (for example, environmental variables, spatial positions of samples). In this report I demonstrate the advantages of the fuzzy coding of explanatory variables: first, nonlinear relationships can be diagnosed; second, more variance in the responses can be explained; and third, in the presence of categorical explanatory variables (for example, years, regions) the interpretation of the resulting triplot ordination is unified because all explanatory variables are measured at a categorical level.

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When continuous data are coded to categorical variables, two types of coding are possible: crisp coding in the form of indicator, or dummy, variables with values either 0 or 1; or fuzzy coding where each observation is transformed to a set of "degrees of membership" between 0 and 1, using co-called membership functions. It is well known that the correspondence analysis of crisp coded data, namely multiple correspondence analysis, yields principal inertias (eigenvalues) that considerably underestimate the quality of the solution in a low-dimensional space. Since the crisp data only code the categories to which each individual case belongs, an alternative measure of fit is simply to count how well these categories are predicted by the solution. Another approach is to consider multiple correspondence analysis equivalently as the analysis of the Burt matrix (i.e., the matrix of all two-way cross-tabulations of the categorical variables), and then perform a joint correspondence analysis to fit just the off-diagonal tables of the Burt matrix - the measure of fit is then computed as the quality of explaining these tables only. The correspondence analysis of fuzzy coded data, called "fuzzy multiple correspondence analysis", suffers from the same problem, albeit attenuated. Again, one can count how many correct predictions are made of the categories which have highest degree of membership. But here one can also defuzzify the results of the analysis to obtain estimated values of the original data, and then calculate a measure of fit in the familiar percentage form, thanks to the resultant orthogonal decomposition of variance. Furthermore, if one thinks of fuzzy multiple correspondence analysis as explaining the two-way associations between variables, a fuzzy Burt matrix can be computed and the same strategy as in the crisp case can be applied to analyse the off-diagonal part of this matrix. In this paper these alternative measures of fit are defined and applied to a data set of continuous meteorological variables, which are coded crisply and fuzzily into three categories. Measuring the fit is further discussed when the data set consists of a mixture of discrete and continuous variables.

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A biplot, which is the multivariate generalization of the two-variable scatterplot, can be used to visualize the results of many multivariate techniques, especially those that are based on the singular value decomposition. We consider data sets consisting of continuous-scale measurements, their fuzzy coding and the biplots that visualize them, using a fuzzy version of multiple correspondence analysis. Of special interest is the way quality of fit of the biplot is measured, since it is well-known that regular (i.e., crisp) multiple correspondence analysis seriously under-estimates this measure. We show how the results of fuzzy multiple correspondence analysis can be defuzzified to obtain estimated values of the original data, and prove that this implies an orthogonal decomposition of variance. This permits a measure of fit to be calculated in the familiar form of a percentage of explained variance, which is directly comparable to the corresponding fit measure used in principal component analysis of the original data. The approach is motivated initially by its application to a simulated data set, showing how the fuzzy approach can lead to diagnosing nonlinear relationships, and finally it is applied to a real set of meteorological data.

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MicroRNAs are short non-coding RNAs that can regulate gene expression during various crucial cell processes such as differentiation, proliferation and apoptosis. Changes in expression profiles of miRNA play an important role in the development of many cancers, including CRC. Therefore, the identification of cancer related miRNAs and their target genes are important for cancer biology research. In this paper, we applied TSK-type recurrent neural fuzzy network (TRNFN) to infer miRNA–mRNA association network from paired miRNA, mRNA expression profiles of CRC patients. We demonstrated that the method we proposed achieved good performance in recovering known experimentally verified miRNA–mRNA associations. Moreover, our approach proved successful in identifying 17 validated cancer miRNAs which are directly involved in the CRC related pathways. Targeting such miRNAs may help not only to prevent the recurrence of disease but also to control the growth of advanced metastatic tumors. Our regulatory modules provide valuable insights into the pathogenesis of cancer

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Non-coding RNAs (ncRNAs) were recently given much higher attention due to technical advances in sequencing which expanded the characterization of transcriptomes in different organisms. ncRNAs have different lengths (22 nt to >1, 000 nt) and mechanisms of action that essentially comprise a sophisticated gene expression regulation network. Recent publication of schistosome genomes and transcriptomes has increased the description and characterization of a large number of parasite genes. Here we review the number of predicted genes and the coverage of genomic bases in face of the public ESTs dataset available, including a critical appraisal of the evidence and characterization of ncRNAs in schistosomes. We show expression data for ncRNAs in Schistosoma mansoni. We analyze three different microarray experiment datasets: (1) adult worms' large-scale expression measurements; (2) differentially expressed S. mansoni genes regulated by a human cytokine (TNF-α) in a parasite culture; and (3) a stage-specific expression of ncRNAs. All these data point to ncRNAs involved in different biological processes and physiological responses that suggest functionality of these new players in the parasite's biology. Exploring this world is a challenge for the scientists under a new molecular perspective of host-parasite interactions and parasite development.

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In this paper, we present a fuzzy approach to the Reed-Frost model for epidemic spreading taking into account uncertainties in the diagnostic of the infection. The heterogeneities in the infected group is based on the clinical signals of the individuals (symptoms, laboratorial exams, medical findings, etc.), which are incorporated into the dynamic of the epidemic. The infectivity level is time-varying and the classification of the individuals is performed through fuzzy relations. Simulations considering a real problem with data of the viral epidemic in a children daycare are performed and the results are compared with a stochastic Reed-Frost generalization

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Background: Ticks secrete a cement cone composed of many salivary proteins, some of which are rich in the amino acid glycine in order to attach to their hosts' skin. Glycine-rich proteins (GRPs) are a large family of heterogeneous proteins that have different functions and features; noteworthy are their adhesive and tensile characteristics. These properties may be essential for successful attachment of the metastriate ticks to the host and the prolonged feeding necessary for engorgement. In this work, we analyzed Expressed Sequence Tags (ESTs) similar to GRPs from cDNA libraries constructed from salivary glands of adult female ticks representing three hard, metastriate species in order to verify if their expression correlated with biological differences such as the numbers of hosts ticks feed on during their parasitic life cycle, whether one (monoxenous parasite) or two or more (heteroxenous parasite), and the anatomy of their mouthparts, whether short (Brevirostrata) or long (Longirostrata). These ticks were the monoxenous Brevirostrata tick, Rhipicephalus (Boophilus) microplus, a heteroxenous Brevirostrata tick, Rhipicephalus sanguineus, and a heteroxenous Longirostrata tick, Amblyomma cajennense. To further investigate this relationship, we conducted phylogenetic analyses using sequences of GRPs from these ticks as well as from other species of Brevirostrata and Longirostrata ticks. Results: cDNA libraries from salivary glands of the monoxenous tick, R. microplus, contained more contigs of glycine-rich proteins than the two representatives of heteroxenous ticks, R. sanguineus and A. cajennense (33 versus, respectively, 16 and 11). Transcripts of ESTs encoding GRPs were significantly more numerous in the salivary glands of the two Brevirostrata species when compared to the number of transcripts in the Longirostrata tick. The salivary gland libraries from Brevirostrata ticks contained numerous contigs significantly similar to silks of true spiders (17 and 8 in, respectively, R. microplus and R. sanguineus), whereas the Longirostrata tick contained only 4 contigs. The phylogenetic analyses of GRPs from various species of ticks showed that distinct clades encoding proteins with different biochemical properties are represented among species according to their biology. Conclusions: We found that different species of ticks rely on different types and amounts of GRPs in order to attach and feed on their hosts. Metastriate ticks with short mouthparts express more transcripts of GRPs than a tick with long mouthparts and the tick that feeds on a single host during its life cycle contain a greater variety of these proteins than ticks that feed on several hosts.

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Despite the wide distribution of transposable elements (TEs) in mammalian genomes, part of their evolutionary significance remains to be discovered. Today there is a substantial amount of evidence showing that TEs are involved in the generation of new exons in different species. In the present study, we searched 22,805 genes and reported the occurrence of TE-cassettes in coding sequences of 542 cow genes using the RepeatMasker program. Despite the significant number (542) of genes with TE insertions in exons only 14 (2.6%) of them were translated into protein, which we characterized as chimeric genes. From these chimeric genes, only the FAST kinase domains 3 (FASTKD3) gene, present on chromosome BTA 20, is a functional gene and showed evidence of the exaptation event. The genome sequence analysis showed that the last exon coding sequence of bovine FASTKD3 is similar to 85% similar to the ART2A retrotransposon sequence. In addition, comparison among FASTKD3 proteins shows that the last exon is very divergent from those of Homo sapiens, Pan troglodytes and Canis familiares. We suggest that the gene structure of bovine FASTKD3 gene could have originated by several ectopic recombinations between TE copies. Additionally, the absence of TE sequences in all other species analyzed suggests that the TE insertion is clade-specific, mainly in the ruminant lineage.

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Background: Myelodysplastic syndromes (MDS) are a group of clonal hematological disorders characterized by ineffective hematopoiesis with morphological evidence of marrow cell dysplasia resulting in peripheral blood cytopenia. Microarray technology has permitted a refined high-throughput mapping of the transcriptional activity in the human genome. Non-coding RNAs (ncRNAs) transcribed from intronic regions of genes are involved in a number of processes related to post-transcriptional control of gene expression, and in the regulation of exon-skipping and intron retention. Characterization of ncRNAs in progenitor cells and stromal cells of MDS patients could be strategic for understanding gene expression regulation in this disease. Methods: In this study, gene expression profiles of CD34(+) cells of 4 patients with MDS of refractory anemia with ringed sideroblasts (RARS) subgroup and stromal cells of 3 patients with MDS-RARS were compared with healthy individuals using 44 k combined intron-exon oligoarrays, which included probes for exons of protein-coding genes, and for non-coding RNAs transcribed from intronic regions in either the sense or antisense strands. Real-time RT-PCR was performed to confirm the expression levels of selected transcripts. Results: In CD34(+) cells of MDS-RARS patients, 216 genes were significantly differentially expressed (q-value <= 0.01) in comparison to healthy individuals, of which 65 (30%) were non-coding transcripts. In stromal cells of MDS-RARS, 12 genes were significantly differentially expressed (q-value <= 0.05) in comparison to healthy individuals, of which 3 (25%) were non-coding transcripts. Conclusions: These results demonstrated, for the first time, the differential ncRNA expression profile between MDS-RARS and healthy individuals, in CD34(+) cells and stromal cells, suggesting that ncRNAs may play an important role during the development of myelodysplastic syndromes.

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The power transformer is a piece of electrical equipment that needs continuous monitoring and fast protection since it is very expensive and an essential element for a power system to perform effectively. The most common protection technique used is the percentage differential logic, which provides discrimination between an internal fault and different operating conditions. Unfortunately, there are some operating conditions of power transformers that can affect the protection behavior and the power system stability. This paper proposes the development of a new algorithm to improve the differential protection performance by using fuzzy logic and Clarke`s transform. An electrical power system was modeled using Alternative Transients Program (ATP) software to obtain the operational conditions and fault situations needed to test the algorithm developed. The results were compared to a commercial relay for validation, showing the advantages of the new method.

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This paper presents a compact embedded fuzzy system for three-phase induction-motor scalar speed control. The control strategy consists in keeping constant the voltage-frequency ratio of the induction-motor supply source. A fuzzy-control system is built on a digital signal processor, which uses speed error and speed-error variation to change both the fundamental voltage amplitude and frequency of a sinusoidal pulsewidth modulation inverter. An alternative optimized method for embedded fuzzy-system design is also proposed. The controller performance, in relation to reference and load-torque variations, is evaluated by experimental results. A comparative analysis with conventional proportional-integral controller is also achieved.