931 resultados para STATIONARY-POINTS
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[Bible. A.T. (hébreu-français). 1831-1851]
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[Bible. A.T. (hébreu-français). 1831-1851]
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[Bible. A.T. (hébreu-français). 1831-1851]
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We present simple procedures for the prediction of a real valued sequence. The algorithms are based on a combinationof several simple predictors. We show that if the sequence is a realization of a bounded stationary and ergodic random process then the average of squared errors converges, almost surely, to that of the optimum, given by the Bayes predictor. We offer an analog result for the prediction of stationary gaussian processes.
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Basic Points about the CASE (Career And Self Awareness) prototype.
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Staphylococcus aureus is a highly successful pathogen responsible of a wide variety of diseases, from minor skin infection to life-threatening sepsis or infective endocarditis, as well as food poisoning and toxic shock syndrome. This heterogeneity of infections and the ability of S. aureus to develop antibiotic-resistance to virtually any available drugs reflect its extraordinary capacity to adapt and survive in a great variety of environments. The pathogenesis of S. aureus infection involves a wide range of cell wall-associated adhesins and extracellular toxins that promote host colonization and invasion. In addition, S. aureus is extremely well equipped with regulatory systems that sense environmental conditions and respond by fine tuning the expression of metabolic and virulence determinants. Surface adhesins referred to MSCRAMMs - for Microbial Surface Component Recognizing Adherence Matrix Molecules - mediate binding to the host extracellular matrix or serum components, including fibrinogen, fibronectin, collagen and elastin, and promote tissue colonization and invasion. Major MSCRAMMs include a family of surface-attached proteins covalently bound to the cell wall peptidoglycan via a conserved LPXTG motif. Genomic analyses indicate that S. aureus contain up to 22 LPXTG surface proteins, which could potentially act individually or in synergy to promote infection. In the first part of this study we determined the range of adherence phenotypes to fibrinogen and fibronectin among 30 carriage isolates of S. aureus and compared it to the adherence phenotypes of 30 infective endocarditis and 30 blood culture isolates. Overall there were great variations in in vitro adherence, but no differences were observed between carriage and infection strains. We further determined the relation between in vitro adherence and in vivo infectivity in a rat model of experimental endocarditis, using 4 isolates that displayed either extremely low or high adherence phenotypes. Unexpectedly, no differences were observed between the in vivo infectivity of isolates that were poorly and highly adherent in vitro. We concluded that the natural variability of in vitro adherence to fibrinogen and fibronectin did not correlate with in vivo infectivity, and thus that pathogenic differences between various strains might only be expressed in in vivo conditions, but not in vitro. Therefore, considering the importance of adhesins expression for infection, direct measurement of those adhesins present on the bacterial surface were made by proteomic approach. 5 In the second series of experiments we assessed the physical presence of the LPXTG species at the staphylococcal surface, as measured at various time points during growth in different culture media. S. aureus Newman was grown in either tryptic soy broth (TSB) or in Roswell Park Memorial Institute (RPMI) culture medium, and samples were removed from early exponential growth phase to late stationary phase. Experiments were performed with mutants in the global accessory-gene regulator (agr), surface protein A (Spa) and clumping factor A (ClfA). Peptides of surface proteins were recovered by "trypsin-shaving" of live bacteria, and semi-quantitative proteomic analysis was performed by tandem liquid-chromatography and mass-spectrometry (LC-MS). We also determined in parallel the mRNA expression by microarrays analysis, as well as the phenotypic adherence of the bacteria to fibrinogen in vitro. The surface proteome was highly complex and contained numerous proteins theoretically not belonging to the bacterial envelope, including ribosomal proteins and metabolic enzymes. Sixteen of the 21 known LPXTG species were detected, but were differentially expressed. As expected, 9 known agr-regulated proteins (e.g. including Spa, FnBPA, ClfA, IsdA, IsdB, SasH, SasD, SasG and FmtB) increased up to the late exponential growth phase, and were abrogated in agr-negative mutants. However, only Spa and SasH modified their proteomic and mRNA profiles in parallel in the parent and its agr negative mutant, while all other LPXTG proteins modified their proteomic profiles independently of their mRNA. Moreover, ClfA became highly transcribed and active in in vitro fibrinogen adherence tests during late growth (24h), whereas it remained poorly detected by proteomics. Differential expression was also detected in iron-rich TSB versus iron-poor RPMI. Proteins from the iron-regulated surface determinant (isd) system, including IsdA, IsdB and IsdH were barely expressed in iron-rich TSB, whereas they increased their expression by >10 time in iron-poor RPMI. We conclude that semi-quantitative proteomic analysis of specific protein species is feasible in S. aureus and that proteomic, transcriptomic and adherence phenotypes demonstrated differential profiles in S. aureus. Furthermore, peptide signatures released by trypsin shaving suggested differential protein domain exposures in various environments, which might be relevant for antiadhesins vaccines. A comprehensive understanding of the S. aureus physiology should integrate all these approaches.
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Principal curves have been defined Hastie and Stuetzle (JASA, 1989) assmooth curves passing through the middle of a multidimensional dataset. They are nonlinear generalizations of the first principalcomponent, a characterization of which is the basis for the principalcurves definition.In this paper we propose an alternative approach based on a differentproperty of principal components. Consider a point in the space wherea multivariate normal is defined and, for each hyperplane containingthat point, compute the total variance of the normal distributionconditioned to belong to that hyperplane. Choose now the hyperplaneminimizing this conditional total variance and look for thecorresponding conditional mean. The first principal component of theoriginal distribution passes by this conditional mean and it isorthogonal to that hyperplane. This property is easily generalized todata sets with nonlinear structure. Repeating the search from differentstarting points, many points analogous to conditional means are found.We call them principal oriented points. When a one-dimensional curveruns the set of these special points it is called principal curve oforiented points. Successive principal curves are recursively definedfrom a generalization of the total variance.
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The rehabilitation process after total knee arthroplasty (TKA) relies more and more on the family doctor. Many factors contribute to this development: the constantly increasing number of TKA performed, the reduced length of stay at the hospital and the rehabilitation process after TKA requiring care for 3 to 4 months. After this time, it is also of major importance to encourage patients to take up physical activities in order to limit the negative effects of sedentarity. The goal of this paper is to give family doctors an overview of the current knowledge in the area of rehabilitation after TKA for physicians.
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A new parametric minimum distance time-domain estimator for ARFIMA processes is introduced in this paper. The proposed estimator minimizes the sum of squared correlations of residuals obtained after filtering a series through ARFIMA parameters. The estimator iseasy to compute and is consistent and asymptotically normally distributed for fractionallyintegrated (FI) processes with an integration order d strictly greater than -0.75. Therefore, it can be applied to both stationary and non-stationary processes. Deterministic components are also allowed in the DGP. Furthermore, as a by-product, the estimation procedure provides an immediate check on the adequacy of the specified model. This is so because the criterion function, when evaluated at the estimated values, coincides with the Box-Pierce goodness of fit statistic. Empirical applications and Monte-Carlo simulations supporting the analytical results and showing the good performance of the estimator in finite samples are also provided.