Projection Pursuit through Φ\Phi-Divergence Minimisation

Consider a defined density on a set of very large dimension. It is quite difficult to find an estimate of this density from a data set. However, it is possible through a projection pursuit methodology to solve this problem. Touboul's article "Projection Pursuit Through Relative Entropy Minimization", 2009, demonstrates the interest of the author's method in a very simple given case. He considers the factorization of a density through an Elliptical component and some residual density. The above Touboul's work is based on minimizing relative entropy. In the present article, our proposal will aim at extending this very methodology to the $\Phi-$divergence. Furthermore, we will also consider the case when the density to be factorized is estimated from an i.i.d. sample. We will then propose a test for the factorization of the estimated density. Applications include a new test of fit pertaining to the Elliptical copulas.Comment: 32 pages, 4 figures, 5 tableaux, elsarticle clas

Goodness-of-fit Tests For Elliptical And Independent Copulas Through Projection Pursuit

Two goodness-of-fit tests for copulas are being investigated. The first one deals with the case of elliptical copulas and the second one deals with independent copulas. These tests result from the expansion of the projection pursuit methodology we will introduce in the present article. This method enables us to determine on which axis system these copulas lie as well as the exact value of these very copulas in the basis formed by the axes previously determined irrespective of their value in their canonical basis. Simulations are also presented as well as an application to real datasets.Comment: 31 page

Prognostic Significance of New Immunohistochemical Markers in Refractory Classical Hodgkin Lymphoma: A Study of 59 Cases

Although most classical Hodgkin lymphoma patients are cured, a significant minority fail after primary therapy and may die as result of their disease. To date, there is no consensus on biological markers that add value to usual parameters (which comprise the International Prognostic Score) used at diagnosis to predict outcome. We evaluated 59 patients (18 with primary refractory or early relapse disease and 41 responders) for bcl2, Ki67, CD20, TiA1 and c-kit expression by semi-quantitative immunohistochemical study and correlated the results with the response to treatment

Rituximab in addition to LMB-based chemotherapy regimen in children and adolescents with primary mediastinal large B-cell lymphoma: results of the French LMB2001 prospective study

Primary mediastinal large B-cell lymphoma (PMLBL) is a rare entity predominantly affecting adolescents and young adults. Recently, an international phase II trial in pediatric patients using dose-adjusted etoposide, doxorubicin, and cyclophosphamide with vincristine and prednisone plus rituximab (DA-EPOCH-R) failed to reproduce excellent survival reported in some adult studies. The optimal therapy regimen needs to be determined in this disease. The French prospective LMB2001 trial included all patients ≤18 years with mature B-cell lymphoma treated in French centers. For patients with PMLBL, treatment included four to eight courses of Lymphomes Malins B (LMB)-based chemotherapy without radiotherapy. From 2008, rituximab was added before each chemotherapy course. From 09/2001 to 03/2012, 42 patients with PMLBL were registered. The median age was 15 years (range, 8-18). Twenty-one patients were treated with chemotherapy plus rituximab. The median follow-up was 7.1 years (interquartile range, 5.8-11.1). Five-year event-free and overall survival were 88.1% (95% confidence interval (CI): 75.0-94.8) and 95.2% (95% CI: 84.0-98.7) for the whole population. The 5-year EFS was 81.0% (95% CI: 60.0-92.3) and 95.2% (95% CI: 77.3-99.2) (hazard ratio =0.24; 95% CI: 0.03- 2.2) and 5-year overall survival was 90.5% (95% CI: 71.1-97.3) and 100% for patients treated without and with rituximab, respectively. Only one of 21 patients treated with rituximab and LMB-based chemotherapy had local early treatment failure but achieved prolonged complete remission with second-line chemotherapy and radiotherapy. Intensive LMBbased chemotherapy with rituximab achieved excellent survival in children/adolescents with PMLBL. Further international prospective studies are required to confirm these results in this population

High Resolution Genome-Wide Analysis of Chromosomal Alterations in Burkitt's Lymphoma

Additional chromosomal abnormalities are currently detected in Burkitt's lymphoma. They play major roles in the progression of BL and in prognosis. The genes involved remain elusive. A whole-genome oligonucleotide array CGH analysis correlated with karyotype and FISH was performed in a set of 27 Burkitt's lymphoma-derived cell lines and primary tumors. More than half of the 145 CNAs<2 Mb were mapped to Mendelian CNVs, including GSTT1, glutathione s-transferase and BIRC6, an anti-apoptotic protein, possibly predisposing to some cancers. Somatic cell line-specific CNVs localized to the IG locus were consistently observed with the 244 K aCGH platform. Among 136 CNAs >2 Mb, gains were found in 1q (12/27), 13q (7/27), 7q (6/27), 8q(4/27), 2p (3/27), 11q (2/27) and 15q (2/27). Losses were found in 3p (5/27), 4p (4/27), 4q (4/27), 9p (4/27), 13q (4/27), 6p (3/27), 17p (3/27), 6q (2/27),11pterp13 (2/27) and 14q12q21.3 (2/27). Twenty one minimal critical regions (MCR), (range 0.04–71.36 Mb), were delineated in tumors and cell lines. Three MCRs were localized to 1q. The proximal one was mapped to 1q21.1q25.2 with a 6.3 Mb amplicon (1q21.1q21.3) harboring BCA2 and PIAS3. In the other 2 MCRs, 1q32.1 and 1q44, MDM4 and AKT3 appeared as possible drivers of these gains respectively. The 13q31.3q32.1 <89.58–96.81> MCR contained an amplicon and ABCC4 might be the driver of this amplicon. The 40 Kb 2p16.1 <60.96–61> MCR was the smallest gained MCR and specifically encompassed the REL oncogene which is already implicated in B cell lymphomas. The most frequently deleted MCR was 3p14.1 <60.43–60.53> that removed the fifth exon of FHIT. Further investigations which combined gene expression and functional studies are essential to understand the lymphomagenesis mechanism and for the development of more effective, targeted therapeutic strategies

Crystallization of Polytetrafluoroethylene in a Wide Range of Cooling Rates: Nucleation and Diffusion in the Presence of Nanosilica Clusters

Polytetrafluoroethylene (PTFE) is a polymer that displays exceptional properties. This synthetic fluoropolymer is also known to crystallize very fast upon cooling. The present work highlights for the first time the influence of nanosilica clusters on PTFE crystallization at fast cooling rates (up to 5000 K&#183;s&#8722;1). The silica was synthesized from aqueous silicate solution and the surface modification was performed using TriEthoxyFluoroSilane (TEFS). In order to understand the crystallization behavior of PTFE/silica nanocomposite at a fast cooling rate, the measurements were carried out by Fast Scanning Calorimetry (FSC). The data were consequently combined with the measurements performed by conventional Differential Scanning Calorimetry (DSC). Interestingly, the results displayed variation of the crystallization behavior for the nanocomposite at fast cooling rates compared to slow cooling rates. The differences in crystal morphologies were then observed by Scanning Electron Microscopy (SEM) after slow and fast cooling rates. Finally, the effective activation energies (E&#945;) obtained from the crystallization under various cooling rates were combined in order to obtain one set of Hoffman-Lauritzen parameters. This procedure allowed us to show that the crystallization of PTFE in the presence of silica is promoted or hampered according to the cooling rates employed

Elaboration and characterization of a novel biobasedPoly(furfurylalcohol)/silicananocomposite

International audienc

Impact of Silica Nanoclusters on Furfuryl Alcohol Polymerization and Molecular Mobility

International audienceNanocomposite materials present attractive properties and are widely employed in various applications. Most of the time, the insertion of nanoparticles in a polymer matrix induces an enhancement of its performances, yet the effect of the filler on the polymerization mechanisms and the glass transition is less often investigated. In the present study, the PFA/silica nanocomposite was studied to highlight the variation of its polymerization behavior, thermomechanical properties and glass transition induced by the presence of a clustered silica nanoparticles network. The structure of nanosilica clusters was studied by thermogravimetric analysis (TGA), Fourier transform infrared spectroscopy (FTIR). The furfuryl alcohol (FA) polymerization was studied via its activation energy variation in the presence of nanosilica clusters and anhydride maleic (MA) that led to some modifications of the polymerization mechanism. An enhancement of thermal stability and an increase of glass transition temperature have been put in relief by dynamic mechanical analysis (DMA) and were correlated to the presence of silica. Finally, the activation energy associated with the glass transition highlighted a change of the polymer chain motion process in the presence of silica

Short-Term Electricity Demand Forecasting Using a Functional State Space Model

In the past several years, the liberalization of the electricity supply, the increase in variability of electric appliances and their use, and the need to respond to the electricity demand in real time has made electricity demand forecasting a challenge. To this challenge, many solutions are being proposed. The electricity demand involves many sources such as economic activities, household need and weather sources. All of these sources make electricity demand forecasting difficult. To forecast the electricity demand, some proposed parametric methods that integrate main variables that are sources of electricity demand. Others proposed a non parametric method such as pattern recognition methods. In this paper, we propose to take only the past electricity consumption information embedded in a functional vector autoregressive state space model to forecast the future electricity demand. The model we proposed aims to be applied at some aggregation level between regional and nation-wide grids. To estimate the parameters of this model, we use likelihood maximization, spline smoothing, functional principal components analysis and Kalman filtering. Through numerical experiments on real datasets, both from supplier Enercoop and from the Transmission System Operator of the French nation-wide grid, we show the appropriateness of the approach