Non invasive classification system of scoliosis curve types using least-squares support vector machines

Objective To determine scoliosis curve types using non invasive surface acquisition, without prior knowledge from X-ray data. Methods Classification of scoliosis deformities according to curve type is used in the clinical management of scoliotic patients. In this work, we propose a robust system that can determine the scoliosis curve type from non invasive acquisition of the 3D back surface of the patients. The 3D image of the surface of the trunk is divided into patches and local geometric descriptors characterizing the back surface are computed from each patch and constitute the features. We reduce the dimensionality by using principal component analysis and retain 53 components using an overlap criterion combined with the total variance in the observed variables. In this work, a multi-class classifier is built with least-squares support vector machines (LS-SVM). The original LS-SVM formulation was modified by weighting the positive and negative samples differently and a new kernel was designed in order to achieve a robust classifier. The proposed system is validated using data from 165 patients with different scoliosis curve types. The results of our non invasive classification were compared with those obtained by an expert using X-ray images. Results The average rate of successful classification was computed using a leave-one-out cross-validation procedure. The overall accuracy of the system was 95%. As for the correct classification rates per class, we obtained 96%, 84% and 97% for the thoracic, double major and lumbar/thoracolumbar curve types, respectively. Conclusion This study shows that it is possible to find a relationship between the internal deformity and the back surface deformity in scoliosis with machine learning methods. The proposed system uses non invasive surface acquisition, which is safe for the patient as it involves no radiation. Also, the design of a specific kernel improved classification performance.

Elastic-net prefiltering for two-class classification

A two-stage linear-in-the-parameter model construction algorithm is proposed aimed at noisy two-class classification problems. The purpose of the first stage is to produce a prefiltered signal that is used as the desired output for the second stage which constructs a sparse linear-in-the-parameter classifier. The prefiltering stage is a two-level process aimed at maximizing a model's generalization capability, in which a new elastic-net model identification algorithm using singular value decomposition is employed at the lower level, and then, two regularization parameters are optimized using a particle-swarm-optimization algorithm at the upper level by minimizing the leave-one-out (LOO) misclassification rate. It is shown that the LOO misclassification rate based on the resultant prefiltered signal can be analytically computed without splitting the data set, and the associated computational cost is minimal due to orthogonality. The second stage of sparse classifier construction is based on orthogonal forward regression with the D-optimality algorithm. Extensive simulations of this approach for noisy data sets illustrate the competitiveness of this approach to classification of noisy data problems.

Photo-electrochemical investigation of anodic oxide films on cast Ti-Mo alloys I. Anodic behaviour and effect of alloy composition

The anodic behaviour of cast Ti-Mo alloys, having different Mo contents (6-20 wt.%), was investigated in acidic and neutral aerated aqueous solutions. All sample showed a valve-metal behaviour, owing to formation and thickening of barrier-type anodic oxides displaying interference colours Growth kinetics. of passive films is influenced by both anodizing electrolyte and composition of the starting alloy. This last parameter was found to change also the solid-state properties of the films, explored by photoelectrochemical and impedance spectroscopy experiments. Thicker films (U(f) = 8 V/MSE) grown on alloys richer in Mo showed more resistive character and a photocurrent sign inversion under negative bias, that revealed an insulating character, whereas corresponding films grown on alloys with lower Mo content, as well as thinner films, behaved as n-type semiconductors. Results are discussed in terms of formation of a mixed Ti-Mo oxide phase. (C) 2008 Elsevier Ltd. All rights reserved

Neural networks in chemosystematic studies of asteraceae: A classification based on a dichotomic approach

This paper describes the application of artificial neural nets as an alternative and efficient method for the classification of botanical taxa based on chemical data (chemosystematics). A total of 28,000 botanical occurrences of chemical compounds isolated from the Asteraceae family were chosen from the literature, and grouped by chemical class for each species. Four tests were carried out to differentiate and classify different botanical taxa. The qualifying capacity of the artificial neural nets was dichotomically tested at different hierarchical levels of the family, such as subfamilies and groups of Heliantheae subtribes. Furthermore, two specific subtribes of the Heliantheae and two genera of one of these subtribes were also tested. In general, the artificial neural net gave rise to good results, with multiple-correlation values R > 0.90. Hence, it was possible to differentiate the dichotomic character of the botanical taxa studied.

Submucous myomas: A new presurgical classification to evaluate the viability of hysteroscopic surgical treatment - Preliminary report

STUDY OBJECTIVE: To develop a new preoperative classification of submucous myomas for evaluating the viability and the degree of difficulty of hysteroscopic myomectomy.DESIGN: Retrospective study (Canadian Task Force classification II-3)SETTING: University teaching hospitals.PATIENTS: Fifty-five patients who underwent hysteroscopic resection of submucous myomas.INTERVENTION: the possibility of total resection of the myoma, the operating time, the fluid deficit, and the frequency of any complications were considered. The myomas were classified according to the Classification of the European Society for Gynaecological Endoscopy (ESGE) and by our group's new classification (NC), which considers not only the degree of penetration of the myoma into the myometrium, but also adds in such parameters as the distance of the base of the myoma from the uterine wall, the size of the nodule (cm), and the topography of the uterine cavity. The Fisher's exact test, the Student's t test, and the analysis of variance test were used in the statistical analysis. A p value less than .05 in the two-tailed test was considered significant.MEASUREMENTS AND MAIN RESULTS: In 57 myomas, hysteroscopic surgery was considered complete. There was no significant difference among the three ESGE levels (0, 1, and 2). Using the NC, the difference between the numbers of complete surgeries was significant (p < .001) for the two levels (groups I and H). The difference between the operating times was significant for the two classifications. With respect to the fluid deficit, only the NC showed significant differences between the levels (p = .02).CONCLUSIONS: We believe that the NC gives more clues as to the difficulties of a hysteroscopic myomectomy than the standard ESGE classification. It should be stressed that the number of hysteroscopic myomectomies used in this analysis was low, and it would be interesting to evaluate the performance of the classification in a larger number of patients. (c) 2005 AAGL. All rights reserved.

Estimation of growth fraction in fine needle aspirates from non-Hodgkin's lymphoma using anti-proliferating cell nuclear antigen - Correlation with the Kiel classification

OBJECTIVE: This study was undertaken to assess whether fine needle aspirates from non-Hodgkins lymphoma (NHL) could be used for growth fraction analysis with proliferating cell nuclear antigen (PCNA) staining and if there was a relationship between the growth fraction and cytomorphologic classification according to the Kiel classification.STUDY DESIGN: the study group consisted of 40 patients with NHL diagnosed by fine needle aspiration (FNA) cytology. The cytologic classification of the lymphomas was made by two cytopathologists on May-Grunwald-Giemsa-stained slides using the Kiel classification. There were 27 cases of low and 13 of high grade lymphoma. The estimation of the growth fraction was made by PCNA immunoreactivity. The PCNA index was quantitated in smears by counting an average of 1,000 cells, and the count teas correlated with the cytomorphologic classification.RESULTS: There was It strong correlation between the PCNA index and lymphoma grading. High grade lymphomas exhibited a mean PCNA positivity of 74.0%, which was significantly higher (P <.001) than that of low grade lymphomas (17.6%).CONCLUSION: Our study showed that PCNA evalua tion is suitable for smears obtained by FNA on NHL, correlates with increasing grades of lymphoma according to the Kiel classification and may offer a method of monitoring treatment of lymphoma.

A REAPPRAISAL OF GENERIC AND SUBGENERIC CLASSIFICATION IN THE BATRACHOSPERMACEAE (RHODOPHYTA)

The generic and subgeneric classification of the family Batrachospermaceae (Rhodophyta) has long been recognized as ambiguous and often inconsistent. One of the prime features used to delineate sections of Batrachospermum, trichogyne shape, is variable even within given species. However, characters associated with the carposporophyte and the carpogonial branch, as well as carpogonial symmetry, are practical and consistent taxonomic criteria. These features have been used to redefine sectional delineation in Batrachospermum. Based on phylogenetic reasoning and practicality, it is proposed that the three genera Nothocladus, Sirodotia and Tuomeya be reduced to sectional level within Batrachospermum. The genus Batrachospermum would thus become the sole member of the Batrachospermaceae and would include two subgenera, Batrachospermum and Acarposporophytum, the former with nine clearly defined sections (Aristata, Batrachospermum, Contorta, Hybrida, Nothocladus (Skuja) stat. nov., Sirodotia (Kylin) stat. nov., Tuomeya (Harvey) stat. nov., Turficola and Viridia). As a result, the following nomenclatural changes are proposed: Batrachospermum lindaueri (Skuja) comb. nov., B. nodosum (Skuja) comb. nov., B. delicatulum (Skuja) comb. nov., B. fennicum (Skuja) comb. nov., B. suecicum (Kylin) comb. nov. and B. americanum (Kutzing) comb. nov.

The Mexican maquila industry and the environment: an overview of the issues

Includes bibliography

Computer techniques towards the automatic characterization of graphite particles in metallographic images of industrial materials

The automatic characterization of particles in metallographic images has been paramount, mainly because of the importance of quantifying such microstructures in order to assess the mechanical properties of materials common used in industry. This automated characterization may avoid problems related with fatigue and possible measurement errors. In this paper, computer techniques are used and assessed towards the accomplishment of this crucial industrial goal in an efficient and robust manner. Hence, the use of the most actively pursued machine learning classification techniques. In particularity, Support Vector Machine, Bayesian and Optimum-Path Forest based classifiers, and also the Otsu's method, which is commonly used in computer imaging to binarize automatically simply images and used here to demonstrated the need for more complex methods, are evaluated in the characterization of graphite particles in metallographic images. The statistical based analysis performed confirmed that these computer techniques are efficient solutions to accomplish the aimed characterization. Additionally, the Optimum-Path Forest based classifier demonstrated an overall superior performance, both in terms of accuracy and speed. © 2012 Elsevier Ltd. All rights reserved.

A new approach to soil classification mapping based on the spatial distribution of soil properties

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Classificação morfológica e imunostoquímica em microarranjo de tecido (TMA) de linfomas não-Hodgkin em cães conforme os critérios da Histological Classification od Hematopoietic Tumors of Domestic Animals (WHO)

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

Estimation of croplands using indicator kriging and fuzzy classification

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Developing a classification system of social communication functioning of preschool children with autism spectrum disorder

Background: Impairments in social communication are the hallmark feature of autism spectrum disorder (ASD). Operationalizing ‘severity’ in ASD has been challenging; thus stratifying by functioning has not been possible. Purpose: To describe the development of the Autism Classification System of Functioning: Social Communication (ACSF:SC) and evaluate its consistency within and between parent and professional ratings. Methodology: (1)ACSF:SC development based on focus groups and surveys involving parents, educators and clinicians familiar with preschoolers with ASD; and (2)Evaluation of the intra- and inter-rater agreement of the ACSF:SC using weighted kappa(кw). Results: Seventy-six participants were involved in the development process. Core characteristics of social communication were ascertained: communicative intent; communicative skills and reciprocity; and impact of environment. Five ACSF:SC levels were created and content-validated across participants. Best capacity and typical performance agreement ratings varied as follows: intra-rater on 41 children was кw=0.61-0.69 for parents and кw=0.71-0.95 for professionals; inter-rater between professionals were кw=0.47-0.61 and between parents and professionals кw=0.33-0.53. Conclusions: Perspectives from parents, and professionals informed ACSF:SC development, providing common descriptions of the levels of everyday communicative abilities of children with ASD to complement DSM-5. Rater agreement demonstrates the ACSF:SC can be utilized with acceptable consistency in comparison to other functional classification systems.

[pediatric Patient Classification System: Improvement Of An Instrument].

Improve the content validity of the instrument for classification of pediatric patients and evaluate its construct validity. A descriptive exploratory study in the measurement of the content validity index, and correlational design for construct validation through exploratory factor analysis. The content validity index for indicators was 0.99 and it was 0.97 for graded situations. Three domains were extracted in the construct validation, namely: patient, family and therapeutic procedures, with 74.97% of explained variance. The instrument showed evidences of content and construct validity. The validation of the instrument occurred under the approach of family-centered care, and allowed incorporating some essential needs of childhood such as playing, interaction and affection in the content of the instrument.

Bond Strength of Multicomponent White Cast Iron Coatings Applied by HVOF Thermal Spray Process

Multicomponent white cast iron is a new alloy that belongs to system Fe-C-Cr-W-Mo-V, and because of its excellent wear resistance it is used in the manufacture of hot rolling mills rolls. To date, this alloy has been processed by casting, powder metallurgy, and spray forming. The high-velocity oxyfuel process is now also considered for the manufacture of components with this alloy. The effects of substrate, preheating temperature, and coating thickness on bond strength of coatings have been determined. Substrates of AISI 1020 steel and of cast iron with preheating of 150 A degrees C and at room temperature were used to apply coatings with 200 and 400 mu m nominal thickness. The bond strength of coatings was measured with the pull-off test method and the failure mode by scanning electron microscopic analysis. Coatings with thickness of 200 mu m and applied on substrates of AISI 1020 steel with preheating presented bond strength of 87 +/- A 4 MPa.