Measures of fit in multiple correspondence analysis of crisp and fuzzy coded data

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.

Pliocene and Pleistocene diversification and multiple refugia in a Eurasian shrew (Crocidura suaveolens group).

We sequenced 998 base pairs (bp) of mitochondrial DNA cytochrome b and 799 bp of nuclear gene BRCA1 in the Lesser white-toothed shrew (Crocidura suaveolens group) over its geographic range from Portugal to Japan. The aims of the study were to identify the main clades within the group and respective refugia resulting from Pleistocene glaciations. Analyses revealed the Asian lesser white-toothed shrew (C. shantungensis) as the basal clade, followed by a major branch of C. suaveolens, subdivided sensu stricto into six clades, which split-up in the Upper Pliocene and Lower Pleistocene (1.9-0.9 Myr). The largest clade, occurring over a huge range from east Europe to Mongolia, shows evidence of population expansion after a bottleneck. West European clades originated from Iberian and Italo-Balkanic refugia. In the Near East, three clades evolved in an apparent hotspot of refugia (west Turkey, south-west and south-east of the Caucasus). Most clades include specimens of different morphotypes and the validity of many taxa in the C. suaveolens group has to be re-evaluated.

Paediatric cardiac CT examinations: impact of the iterative reconstruction method ASIR on image quality--preliminary findings.

BACKGROUND: Radiation dose exposure is of particular concern in children due to the possible harmful effects of ionizing radiation. The adaptive statistical iterative reconstruction (ASIR) method is a promising new technique that reduces image noise and produces better overall image quality compared with routine-dose contrast-enhanced methods. OBJECTIVE: To assess the benefits of ASIR on the diagnostic image quality in paediatric cardiac CT examinations. MATERIALS AND METHODS: Four paediatric radiologists based at two major hospitals evaluated ten low-dose paediatric cardiac examinations (80 kVp, CTDI(vol) 4.8-7.9 mGy, DLP 37.1-178.9 mGy·cm). The average age of the cohort studied was 2.6 years (range 1 day to 7 years). Acquisitions were performed on a 64-MDCT scanner. All images were reconstructed at various ASIR percentages (0-100%). For each examination, radiologists scored 19 anatomical structures using the relative visual grading analysis method. To estimate the potential for dose reduction, acquisitions were also performed on a Catphan phantom and a paediatric phantom. RESULTS: The best image quality for all clinical images was obtained with 20% and 40% ASIR (p < 0.001) whereas with ASIR above 50%, image quality significantly decreased (p < 0.001). With 100% ASIR, a strong noise-free appearance of the structures reduced image conspicuity. A potential for dose reduction of about 36% is predicted for a 2- to 3-year-old child when using 40% ASIR rather than the standard filtered back-projection method. CONCLUSION: Reconstruction including 20% to 40% ASIR slightly improved the conspicuity of various paediatric cardiac structures in newborns and children with respect to conventional reconstruction (filtered back-projection) alone.

Social Representations Of Violence Against Rural Women: Unveiling Senses In Multiple Views

We analyze the social representations of violence against women from the perspective of city managers, professionals and health workers in rural settings of the southern half of Rio Grande do Sul. The study has a qualitative approach and adds a theoretical/methodological perspective of social representations. The data were generated by means of the associative method, question-stimulus of words and expressions emergence. The analysis of word association was performed with EVOC software, considering frequency and order of association with inducing terms. Participants recognize violence against women as gender destination that induces consent, resignation, guilt and fear, and results in naturalization and trivialization of this social phenomenon. We highlight the need to produce ruptures in established and traditional forms of health care, in the conservative and stereotypical views of violence, favoring access to friendly service and avoiding the reproduction of gender inequalities.


Le multiple evanescent white dot syndrome: une prédisposition génétique [Multiple evanescent white dot syndrome: a genetic predisposition?]

BACKGROUND: Multiple evanescent white dot syndrome (MEWDS) is a benign acquired isolated chorioretinal disorder. Symptoms include photopsia, visual blur and scotomas. Ocular examination reveals multiple white dots at the level of the deep retina. A parainfectious disorder was suggested but the exact mechanism of MEWDS is still unknown. Postulating that MEWDS might be an antigen driven inflammatory reaction, we analyzed HLA subtypes in patients with MEWDS. PATIENTS AND METHODS: Sixteen patients were diagnosed with MEWDS in Lausanne from 1985 to 1994. Blood was withdrawn in 9/16 patients. HLA-A, -B and -DR were sought. RESULTS: HLA-B51 was detected in 4/9 patients (44.4%). Other HLA subtypes were detected sporadically. CONCLUSIONS: The frequency of HLA-B51 haplotype was found to be 3.7 times more elevated than in a normal control caucasian group. This suggests the possibility that MEWDS might be a genetically determined disorder as it is the case for other ocular diseases like Birdshot chorioretinopathy (HLA-A29), Harada's disease (HLA-DRMT3), acute anterior uveitis (HLA-B27) or Behçet's disease (HLA-B51). We have no explanation for the presence of HLA-B51 in both Behçet's disease and MEWDS. The association of HLA-B51 and MEWDS needs confirmation by further testing.

Time Series Input Selection using Multiple Kernel Learning

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).

Current multiple myeloma treatment strategies with novel agents: a European perspective.

The treatment of multiple myeloma (MM) has undergone significant developments in recent years. The availability of the novel agents thalidomide, bortezomib, and lenalidomide has expanded treatment options and has improved the outcome of patients with MM. Following the introduction of these agents in the relapsed/refractory setting, they are also undergoing investigation in the initial treatment of MM. A number of phase III trials have demonstrated the efficacy of novel agent combinations in the transplant and nontransplant settings, and based on these results standard induction regimens are being challenged and replaced. In the transplant setting, a number of newer induction regimens are now available that have been shown to be superior to the vincristine, doxorubicin, and dexamethasone regimen. Similarly, in the front-line treatment of patients not eligible for transplantation, regimens incorporating novel agents have been found to be superior to the traditional melphalan plus prednisone regimen. Importantly, some of the novel agents appear to be active in patients with high-risk disease, such as adverse cytogenetic features, and certain comorbidities, such as renal impairment. This review presents an overview of the most recent data with these novel agents and summarizes European treatment practices incorporating the novel agents.

Interferon-gamma impacts at multiple points during the progression of autoimmune diabetes.

The role of interferon-gamma in autoimmune diabetes was assessed by breeding a null mutation of the interferon-gamma receptor alpha chain into the nonobese diabetic mouse strain, as well as into a simplified T cell receptor transgenic model of diabetes. In contrast to a previous report on abrogation of the interferon-gamma gene, mutation of the gene encoding its receptor led to drastic effects on disease in both mouse lines. Nonobese diabetic mice showed a marked inhibition of insulitis-both the kinetics and penetrance-and no signs of diabetes; the transgenic model exhibited near-normal insulitis, but this never evolved into diabetes, either spontaneously or after experimental provocation. This failure could not be explained by perturbations in the ratio of T helper cell phenotypes; rather, it reflected a defect in antigen-presenting cells or in the islet beta cell targets.