986 resultados para Power series
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Résumé Les glissements de terrain représentent un des principaux risques naturels dans les régions montagneuses. En Suisse, chaque année les glissements de terrains causent des dégâts qui affectent les infrastructures et ont des coûts financiers importants. Une bonne compréhension des mécanismes des glissements peut permettre d'atténuer leur impact. Celle-ci passe notamment par la connaissance de la structure interne du glissement, la détermination de son volume et de son ou ses plans de glissement. Dans un glissement de terrain, la désorganisation et la présence de fractures dans le matériel déplacé engendre un changement des paramètres physiques et en particulier une diminution des vitesses de propagation des ondes sismiques ainsi que de la densité du matériel. Les méthodes sismiques sont de ce fait bien adaptées à l'étude des glissements de terrain. Parmi les méthodes sismiques, l'analyse de la dispersion des ondes de surface est une méthode simple à mettre en oeuvre. Elle présente l'avantage d'estimer les variations des vitesses de cisaillement avec la profondeur sans avoir spécifiquement recours à l'utilisation d'une source d'onde S et de géophones horizontaux. Sa mise en oeuvre en trois étapes implique la mesure de la dispersion des ondes de surface sur des réseaux étendus, la détermination des courbes de dispersion pour finir par l'inversion de ces courbes. Les modèles de vitesse obtenus à partir de cette procédure ne sont valides que lorsque les milieux explorés ne présentent pas de variations latérales. En pratique cette hypothèse est rarement vérifiée, notamment pour un glissement de terrain dans lequel les couches remaniées sont susceptibles de présenter de fortes hétérogénéités latérales. Pour évaluer la possibilité de déterminer des courbes de dispersion à partir de réseaux de faible extension des mesures testes ont été effectuées sur un site (Arnex, VD) équipé d'un forage. Un profil sismique de 190 m de long a été implanté dans une vallée creusée dans du calcaire et remplie par des dépôts glacio-lacustres d'une trentaine de mètres d'épaisseur. Les données acquises le long de ce profil ont confirmé que la présence de variations latérales sous le réseau de géophones affecte l'allure des courbes de dispersion jusqu'à parfois empêcher leur détermination. Pour utiliser l'analyse de la dispersion des ondes de surface sur des sites présentant des variations latérales, notre approche consiste à déterminer les courbes de dispersions pour une série de réseaux de faible extension, à inverser chacune des courbes et à interpoler les différents modèles de vitesse obtenus. Le choix de la position ainsi que de l'extension des différents réseaux de géophones est important. Il tient compte de la localisation des hétérogénéités détectées à partir de l'analyse de sismique réfraction, mais également d'anomalies d'amplitudes observées sur des cartes qui représentent dans le domaine position de tir - position du récepteur, l'amplitude mesurée pour différentes fréquences. La procédure proposée par Lin et Lin (2007) s'est avérée être une méthode efficace permettant de déterminer des courbes de dispersion à partir de réseaux de faible extension. Elle consiste à construire à partir d'un réseau de géophones et de plusieurs positions de tir un enregistrement temps-déports qui tient compte d'une large gamme de distances source-récepteur. Au moment d'assembler les différentes données une correction de phase est appliquée pour tenir compte des hétérogénéités situées entre les différents points de tir. Pour évaluer cette correction nous suggérons de calculer pour deux tir successif la densité spectrale croisée des traces de même offset: Sur le site d'Arnex, 22 courbes de dispersions ont été déterminées pour de réseaux de géophones de 10 m d'extension. Nous avons également profité du forage pour acquérir un profil de sismique verticale en ondes S. Le modèle de vitesse S déduit de l'interprétation du profil de sismique verticale est utilisé comme information à priori lors l'inversion des différentes courbes de dispersion. Finalement, le modèle en deux dimension qui a été établi grâce à l'analyse de la dispersion des ondes de surface met en évidence une structure tabulaire à trois couches dont les limites coïncident bien avec les limites lithologiques observées dans le forage. Dans celui-ci des argiles limoneuses associées à une vitesse de propagation des ondes S de l'ordre de 175 m/s surmontent vers 9 m de profondeur des dépôts de moraine argilo-sableuse caractérisés par des vitesses de propagation des ondes S de l'ordre de 300 m/s jusqu'à 14 m de profondeur et supérieur ou égal à 400 m/s entre 14 et 20 m de profondeur. Le glissement de la Grande Combe (Ballaigues, VD) se produit à l'intérieur du remplissage quaternaire d'une combe creusée dans des calcaires Portlandien. Comme dans le cas du site d'Arnex les dépôts quaternaires correspondent à des dépôts glacio-lacustres. Dans la partie supérieure la surface de glissement a été localisée à une vingtaine de mètres de profondeur au niveau de l'interface qui sépare des dépôts de moraine jurassienne et des dépôts glacio-lacustres. Au pied du glissement 14 courbes de dispersions ont été déterminées sur des réseaux de 10 m d'extension le long d'un profil de 144 m. Les courbes obtenues sont discontinues et définies pour un domaine de fréquence de 7 à 35 Hz. Grâce à l'utilisation de distances source-récepteur entre 8 et 72 m, 2 à 4 modes de propagation ont été identifiés pour chacune des courbes. Lors de l'inversion des courbes de dispersion la prise en compte des différents modes de propagation a permis d'étendre la profondeur d'investigation jusqu'à une vingtaine de mètres de profondeur. Le modèle en deux dimensions permet de distinguer 4 couches (Vs1 < 175 m/s, 175 m/s < Vs2 < 225 m/s, 225 m/s < Vs3 < 400 m/s et Vs4 >.400 m/s) qui présentent des variations d'épaisseur. Des profils de sismiques réflexion en ondes S acquis avec une source construite dans le cadre de ce travail, complètent et corroborent le modèle établi à partir de l'analyse de la dispersion des ondes de surface. Un réflecteur localisé entre 5 et 10 m de profondeur et associé à une vitesse de sommation de 180 m/s souligne notamment la géométrie de l'interface qui sépare la deuxième de la troisième couche du modèle établi à partir de l'analyse de la dispersion des ondes de surface. Abstract Landslides are one of the main natural hazards in mountainous regions. In Switzerland, landslides cause damages every year that impact infrastructures and have important financial costs. In depth understanding of sliding mechanisms may help limiting their impact. In particular, this can be achieved through a better knowledge of the internal structure of the landslide, the determination of its volume and its sliding surface or surfaces In a landslide, the disorganization and the presence of fractures in the displaced material generate a change of the physical parameters and in particular a decrease of the seismic velocities and of the material density. Therefoe, seismic methods are well adapted to the study of landslides. Among seismic methods, surface-wave dispersion analysis is a easy to implement. Through it, shearwave velocity variations with depth can be estimated without having to resort to an S-wave source and to horizontal geophones. Its 3-step implementation implies measurement of surface-wave dispersion with long arrays, determination of the dispersion curves and finally inversion of these curves. Velocity models obtained through this approach are only valid when the investigated medium does not include lateral variations. In practice, this assumption is seldom correct, in particular for landslides in which reshaped layers likely include strong lateral heterogeneities. To assess the possibility of determining dispersion curves from short array lengths we carried out tests measurements on a site (Arnex, VD) that includes a borehole. A 190 m long seismic profile was acquired in a valley carved into limestone and filled with 30 m of glacio-lacustrine sediments. The data acquired along this profile confirmed that the presence of lateral variations under the geophone array influences the dispersion-curve shape so much that it sometimes preventes the dispersion curves determination. Our approach to use the analysis of surface-wave dispersion on sites that include lateral variations consists in obtaining dispersion curves for a series of short length arrays; inverting each so obtained curve and interpolating the different obtained velocity model. The choice of the location as well as the geophone array length is important. It takes into account the location of the heterogeneities that are revealed by the seismic refraction interpretation of the data but also, the location of signal amplitude anomalies observed on maps that represent, for a given frequency, the measured amplitude in the shot position - receiver position domain. The procedure proposed by Lin and Lin (2007) turned out to be an efficient one to determine dispersion curves using short extension arrays. It consists in building a time-offset from an array of geophones with a wide offset range by gathering seismograms acquired with different source-to-receiver offsets. When assembling the different data, a phase correction is applied in order to reduce static phase error induced by lateral variation. To evaluate this correction, we suggest to calculate, for two successive shots, the cross power spectral density of common offset traces. On the Arnex site, 22 curves were determined with 10m in length geophone-arrays. We also took advantage of the borehole to acquire a S-wave vertical seismic profile. The S-wave velocity depth model derived from the vertical seismic profile interpretation is used as prior information in the inversion of the dispersion-curves. Finally a 2D velocity model was established from the analysis of the different dispersion curves. It reveals a 3-layer structure in good agreement with the observed lithologies in the borehole. In it a clay layer with a shear-wave of 175 m/s shear-wave velocity overlies a clayey-sandy till layer at 9 m depth that is characterized down to 14 m by a 300 m/s S-wave velocity; these deposits have a S-wave velocity of 400 m/s between depths of 14 to 20 m. The La Grand Combe landslide (Ballaigues, VD) occurs inside the Quaternary filling of a valley carved into Portlandien limestone. As at the Arnex site, the Quaternary deposits correspond to glaciolacustrine sediments. In the upper part of the landslide, the sliding surface is located at a depth of about 20 m that coincides with the discontinuity between Jurassian till and glacio-lacustrine deposits. At the toe of the landslide, we defined 14 dispersion curves along a 144 m long profile using 10 m long geophone arrays. The obtained curves are discontinuous and defined within a frequency range of 7 to 35 Hz. The use of a wide range of offsets (from 8 to 72 m) enabled us to determine 2 to 4 mode of propagation for each dispersion curve. Taking these higher modes into consideration for dispersion curve inversion allowed us to reach an investigation depth of about 20 m. A four layer 2D model was derived (Vs1< 175 m/s, 175 m/s <Vs2< 225 m/s, 225 m/s < Vs3 < 400 m/s, Vs4> 400 m/s) with variable layer thicknesses. S-wave seismic reflection profiles acquired with a source built as part of this work complete and the velocity model revealed by surface-wave analysis. In particular, reflector at a depth of 5 to 10 m associated with a 180 m/s stacking velocity image the geometry of the discontinuity between the second and third layer of the model derived from the surface-wave dispersion analysis.
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In this paper we study the relevance of multiple kernel learning (MKL) for the automatic selection of time series inputs. Recently, MKL has gained great attention in the machine learning community due to its flexibility in modelling complex patterns and performing feature selection. In general, MKL constructs the kernel as a weighted linear combination of basis kernels, exploiting different sources of information. An efficient algorithm wrapping a Support Vector Regression model for optimizing the MKL weights, named SimpleMKL, is used for the analysis. In this sense, MKL performs feature selection by discarding inputs/kernels with low or null weights. The approach proposed is tested with simulated linear and nonlinear time series (AutoRegressive, Henon and Lorenz series).
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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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Theorem 1 of Euler s paper of 1737 'Variae Observationes Circa Series Infinitas', states the astonishing result that the series of all unit fractions whose denominators are perfect powers of integers minus unity has sum one. Euler attributes the Theorem to Goldbach. The proof is one of those examples of misuse of divergent series to obtain correct results so frequent during the seventeenth and eighteenth centuries. We examine this proof closelyand, with the help of some insight provided by a modern (and completely dierent) proof of the Goldbach-Euler Theorem, we present a rational reconstruction in terms which could be considered rigorous by modern Weierstrassian standards. At the same time, with a few ideas borrowed from nonstandard analysis we see how the same reconstruction can be also be considered rigorous by modern Robinsonian standards. This last approach, though, is completely in tune with Goldbach and Euler s proof. We hope to convince the reader then how, a few simple ideas from nonstandard analysis, vindicate Euler's work.
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Condence intervals in econometric time series regressions suffer fromnotorious coverage problems. This is especially true when the dependencein the data is noticeable and sample sizes are small to moderate, as isoften the case in empirical studies. This paper suggests using thestudentized block bootstrap and discusses practical issues, such as thechoice of the block size. A particular data-dependent method is proposedto automate the method. As a side note, it is pointed out that symmetricconfidence intervals are preferred over equal-tailed ones, since theyexhibit improved coverage accuracy. The improvements in small sampleperformance are supported by a simulation study.
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A cytochemical marker such as alpha-naphthyl acetate esterase (ANAE) has been found useful for the morphological identification of the subset of T lymphocytes having receptors for Fcμ (TM cells). ANAE reaction on TM cells gives a typical pattern of one to four positive spots, whereas this pattern is not found on T cells with receptors for Fcγ (TG cells). ANAE is abundant in monocytes but not detectable in granulocytes. Herein another type of esterase activity, naphthol-AS-D chloroacetate esterase (NCAE), is described; it is known to be abundant in granulocytes and was found to give a specific pattern of reactivity with the subpopulation of large granular lymphocytes (LGL). This pattern of fine granular staining was observed not only on LGL present in the TG cell subpopulation but also in LGL present in the non-T, non-B cells. Fractions of peripheral blood mononuclear cells which were ènriched up to 80% in LGL by Percoll discontinuous density gradient gave a similar percentage of specific NCAE pattern. In addition, among the different fractions from Percoll gradient, there was a good correlation (r = 0.94) between the number of NCAE-positive cells and the natural killer activity against the natural killer susceptible K562 target cells. It will be important to determine whether or not this enzymatic activity plays a role in the cytotoxic activities of LGL.
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This booklet is designed to assist those who have been appointed as an attorney-in-fact, those who are considering the need for a power of attorney, or those who have an interest in the subject. This is a general overview.
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Power transformations of positive data tables, prior to applying the correspondence analysis algorithm, are shown to open up a family of methods with direct connections to the analysis of log-ratios. Two variations of this idea are illustrated. The first approach is simply to power the original data and perform a correspondence analysis this method is shown to converge to unweighted log-ratio analysis as the power parameter tends to zero. The second approach is to apply the power transformation to thecontingency ratios, that is the values in the table relative to expected values based on the marginals this method converges to weighted log-ratio analysis, or the spectral map. Two applications are described: first, a matrix of population genetic data which is inherently two-dimensional, and second, a larger cross-tabulation with higher dimensionality, from a linguistic analysis of several books.
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There is very limited data on isolated systemic relapses of primary central nervous system lymphomas (PCNSL). We retrospectively reviewed the clinical characteristics and outcome of 10 patients with isolated systemic disease among 209 patients with PCNSL mainly treated with methotrexate-based chemotherapy (CT) with or without radiation therapy (RT). Isolated systemic relapse remained rare (4.8%, 10/209 patients). Median time from initial diagnosis to relapse was 33 months (range, 3-94). Sites of relapse were mostly extranodal. Three patients presented with early extra-cerebral (EC) relapse 3, 5 and 8 months from the beginning of initial treatment, respectively, and 7 patients had later relapses (range, 17-94 months). Treatment at relapse included surgery alone, RT alone, CT with or without radiotherapy, or CT with autologous stem cell transplantation (ASCT). Median overall survival (OS) after relapse was 15.5 months (range, 5.8-24.5) compared to 4.6 months (range, 3.6-6.5) for patients with central nervous system (CNS) relapse (p = 0.35). In conclusion, isolated systemic relapses exist but are infrequent. Early EC relapse suggests the presence of systemic disease undetectable by conventional evaluation at initial diagnosis. Patient follow-up must be prolonged because systemic relapse can occur as late as 10 years after initial diagnosis. Whether EC relapses of PCNSL have a better prognosis than CNS relapses needs to be assessed in a larger cohort. Copyright © 2010 John Wiley & Sons, Ltd.