871 resultados para Panel data analysis


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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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Apert Syndrome, also called acrocephalosyndactylia type 1, is characterized by craniostenosis with early fusion of sutures of the vault and/ or cranial base, associated to mid-face hypoplasia, symmetric syndactylia of the hands and feet and other systemic malformations. CNS malformations and intracranial hypertension are frequently observed in these patients. Early surgical treatment aims to minimize the deleterious effects of intracranial hypertension. Fronto-orbital advancement, the usual surgical technique, increases the intracranial volume and improves the disposition of encephalic structures previously deformed by a short skull. This study analyzes CNS alterations revealed by magnetic resonance in 18 patients presenting Apert Syndrome, and the conformational alterations in the encephalic structures after surgical treatment. The patients' age in February 2001 ranged from 14 to 322 months (m=107). Image study included brain magnetic resonance showing ventricular enlargement in five cases (27.8%), corpus callosum hypoplasia in five cases (27.8%), septum pellucidum hypoplasia in five cases (27.8%), cavum vergae in two cases (11.1%) and, arachnoid cyst in the posterior fossa in two cases (11.1%). Absence of CNS alterations was noted in 44.4% of cases. A corpus callosum morphologic index was established by dividing its height by its length, which revealed values that ranged from 0.4409 to 1.0237. The values of this index were correlated to the occurrence or absence of surgical treatment (p=0.012; t=2.83). Data analysis allowed the conclusion that the corpus callosum morphologic measure quantified the conformational alterations of the cerebral structures determined by the surgical treatment.

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Interactive visual representations complement traditional statistical and machine learning techniques for data analysis, allowing users to play a more active role in a knowledge discovery process and making the whole process more understandable. Though visual representations are applicable to several stages of the knowledge discovery process, a common use of visualization is in the initial stages to explore and organize a sometimes unknown and complex data set. In this context, the integrated and coordinated - that is, user actions should be capable of affecting multiple visualizations when desired - use of multiple graphical representations allows data to be observed from several perspectives and offers richer information than isolated representations. In this paper we propose an underlying model for an extensible and adaptable environment that allows independently developed visualization components to be gradually integrated into a user configured knowledge discovery application. Because a major requirement when using multiple visual techniques is the ability to link amongst them, so that user actions executed on a representation propagate to others if desired, the model also allows runtime configuration of coordinated user actions over different visual representations. We illustrate how this environment is being used to assist data exploration and organization in a climate classification problem.

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Diplopods belonging to the subclass Helminthomorpha may present one or both leg pairs of the seventh diplosegment modified into structures that aid copulation, called gonopods. These structures are used as a taxonomic trait for the description of most species. In the genus Rhinocricus these structures are closely similar, so that it is difficult to distinguish species only on the basis of this trait. Two species, R. padbergi and R. varians, are found in the same habitat and present gonopods practically identical in shape; together they present a broad colour gradient, ranging from dark brown to light beige. Morphometric data for individuals of the experimental group were submitted to ANOVA and MANOVA, using Hotelling-Lawley Trace and generalized Mahalanobis distances (D 2) tests. The results demonstrated a relationship between size and colour, with darker individuals being larger. On the basis of this preliminary analysis, we may suggest that the two species are distinct since dark individuals are distant from medium- and light-coloured individuals according to the D 2 values. This seems to indicate a possible polymorphism of individuals belonging to R. padbergi which present close proximity in the values obtained. In all analyses, we observed that the main variables were diameter, length and telson size.

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Cuttings return analysis is an important tool to detect and prevent problems during the petroleum well drilling process. Several measurements and tools have been developed for drilling problems detection, including mud logging, PWD and downhole torque information. Cuttings flow meters were developed in the past to provide information regarding cuttings return at the shale shakers. Their use, however, significantly impact the operation including rig space issues, interferences in geological analysis besides, additional personel required. This article proposes a non intrusive system to analyze the cuttings concentration at the shale shakers, which can indicate problems during drilling process, such as landslide, the collapse of the well borehole walls. Cuttings images are acquired by a high definition camera installed above the shakers and sent to a computer coupled with a data analysis system which aims the quantification and closure of a cuttings material balance in the well surface system domain. No additional people at the rigsite are required to operate the system. Modern Artificial intelligence techniques are used for pattern recognition and data analysis. Techniques include the Optimum-Path Forest (OPF), Artificial Neural Network using Multilayer Perceptrons (ANN-MLP), Support Vector Machines (SVM) and a Bayesian Classifier (BC). Field test results conducted on offshore floating vessels are presented. Results show the robustness of the proposed system, which can be also integrated with other data to improve the efficiency of drilling problems detection. Copyright 2010, IADC/SPE Drilling Conference and Exhibition.

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Includes bibliography

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Background: Uterine Leiomyomas (ULs) are the most common benign tumours affecting women of reproductive age. ULs represent a major problem in public health, as they are the main indication for hysterectomy. Approximately 40-50% of ULs have non-random cytogenetic abnormalities, and half of ULs may have copy number alterations (CNAs). Gene expression microarrays studies have demonstrated that cell proliferation genes act in response to growth factors and steroids. However, only a few genes mapping to CNAs regions were found to be associated with ULs. Methodology: We applied an integrative analysis using genomic and transcriptomic data to identify the pathways and molecular markers associated with ULs. Fifty-one fresh frozen specimens were evaluated by array CGH (JISTIC) and gene expression microarrays (SAM). The CONEXIC algorithm was applied to integrate the data. Principal Findings: The integrated analysis identified the top 30 significant genes (P<0.01), which comprised genes associated with cancer, whereas the protein-protein interaction analysis indicated a strong association between FANCA and BRCA1. Functional in silico analysis revealed target molecules for drugs involved in cell proliferation, including FGFR1 and IGFBP5. Transcriptional and protein analyses showed that FGFR1 (P = 0.006 and P<0.01, respectively) and IGFBP5 (P = 0.0002 and P = 0.006, respectively) were up-regulated in the tumours when compared with the adjacent normal myometrium. Conclusions: The integrative genomic and transcriptomic approach indicated that FGFR1 and IGFBP5 amplification, as well as the consequent up-regulation of the protein products, plays an important role in the aetiology of ULs and thus provides data for potential drug therapies development to target genes associated with cellular proliferation in ULs. © 2013 Cirilo et al.

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The aimof this study was to evaluate the stress distribution on bone tissue with a single prosthesis supported by implants of large and conventional diameter and presenting different veneering materials using the 3-D finite elementmethod. Sixteenmodels were fabricated to reproduce a bone block with implants, using two diameters (3.75 × 10 mmand 5.00 × 10 mm), four different veneering materials (composite resin, acrylic resin, porcelain, and NiCr crown), and two loads (axial (200 N) and oblique (100 N)). For data analysis, the maximum principal stress and vonMises criterion were used. For the axial load, the cortical bone in allmodels did not exhibit significant differences, and the trabecular bone presented higher tensile stresswith reduced implant diameter. For the oblique load, the cortical bone presented a significant increase in tensile stress on the same side as the loading for smaller implant diameters. The trabecular bone showed a similar but more discreet trend. There was no difference in bone tissue with different veneering materials. The veneering material did not influence the stress distribution in the supporting tissues of single implant-supported prostheses. The large-diameter implants improved the transference of occlusal loads to bone tissue and decreased stress mainly under oblique loads.Oblique loading was more detrimental to distribution stresses than axial loading. © 2013 Elsevier B.V. All rights reserved.

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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We examine the problem of combining Mexican inflation predictions or projections provided by a biweekly survey of professional forecasters. Consumer price inflation in Mexico is measured twice a month. We consider several combining methods and advocate the use of dimension reduction techniques whose performance is compared with different benchmark methods, including the simplest average prediction. Missing values in the database are imputed by two different databased methods. The results obtained are basically robust to the choice of the imputation method. A preliminary analysis of the data was based on its panel data structure and showed the potential usefulness of using dimension reduction techniques to combine the experts' predictions. The main findings are: the first monthly predictions are best combined by way of the first principal component of the predictions available; the best second monthly prediction is obtained by calculating the median prediction and is more accurate than the first one.

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The objective of this work was to identify a possible relation between corporate governance, through the structure of the boards of directors and the levels of earnings management of Brazilian public companies. The study is characterized as a descriptive, of a hypothetical-deductive nature, with quantitative approach guided by the estimation model proposed by Kang and Sivaramakrishnan (1995). The sample was comprised by 56 companies, analyzed in the period from 2011 to 2014. The information on the companies were extracted from Economatica databank. For the data analysis, we used multivariate techniques, such as Pearson correlation and panel data in POLS, Fixed Effects and Random Effects approaches. Furthermore, we applied the mean comparison test ANOVA. The results obtained show that, generally, the organizations tend to follow the profile of boards of directors recommended by the codes of corporative governance. However, the characteristics of the composition of the board, regarding its size and the duality of positions that are not yet sufficient to be considered capable of inhibiting the discretionary practice of the studied companies. Relative the control variables, only size and return on equity presented no significant relation with result management. It is important to highlight that literature point many factors that explain the different impacts caused by the formation of the administration board in different regions or countries. Among the factors pointed, we highlight the legal system of the country, the economic and political development, the importance of the capital market, and the level of accounting education.