Characteristics of the double-torsion test to determine the R-curve of ceramic materials

Double-torsion tests were carried out on a commercial ceramic floor tile to verify whether this test is suitable for determining the R-curve of ceramics. The instantaneous crack length was obtained by means of compliance calibration, and it was found that the experimental compliance underestimates the real crack length. The load vs. displacement curves were also found to drop after maximum loading, causing the stress intensity factor to decline. The R-curves were calculated by two methods: linear elastic fracture mechanics and the energetic method. It was obtained that the average values of crack resistance, R, and the double of the work of fracture, 2 · γwof, did not depend on notch length, a0, which is a highly relevant finding, indicating that these parameters were less dependent on the test specimen's geometry. The proposal was to use small notches, which produce long stable crack propagation paths that in turn are particularly important in the case of coarse microstructures.

Modelos no lineales para describir el crecimiento de bufalinos de la raza Murrah

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Reduced calibration curve for proton computed tomography

The pCT deals with relatively thick targets like the human head or trunk. Thus, the fidelity of pCT as a tool for proton therapy planning depends on the accuracy of physical formulas used for proton interaction with thick absorbers. Although the actual overall accuracy of the proton stopping power in the Bethe-Bloch domain is about 1%, the analytical calculations and the Monte Carlo simulations with codes like TRIM/SRIM, MCNPX and GEANT4 do not agreed with each other. A tentative to validate the codes against experimental data for thick absorbers bring some difficulties: only a few data is available and the existing data sets have been acquired at different initial proton energies, and for different absorber materials. In this work we compare the results of our Monte Carlo simulations with existing experimental data in terms of reduced calibration curve, i.e. the range - energy dependence normalized on the range scale by the full projected CSDA range for given initial proton energy in a given material, taken from the NIST PSTAR database, and on the final proton energy scale - by the given initial energy of protons. This approach is almost energy and material independent. The results of our analysis are important for pCT development because the contradictions observed at arbitrary low initial proton energies could be easily scaled now to typical pCT energies. © 2010 American Institute of Physics.

Comparison of the GEANT4 releases 8.2 and 9.2 in terms of a pCT reduced calibration curve

The GEANT4 simulations are essential for the development of medical tomography with proton beams pCT. In the case of thin absorbers the latest releases of GEANT4 generate very similar final spectra which agree well with the results of other popular Monte Carlo codes like TRIM/SRIM, or MCNPX. For thick absorbers, however, the disagreements became evident. In a part, these disagreements are due to the known contradictions in the NIST PSTAR and SRIM reference data. Therefore, it is interesting to compare the GEANT4 results with each other, with experiment, and with diverse code results in a reduced form, which is free from this kind of doubts. In this work such comparison is done within the Reduced Calibration Curve concept elaborated for the proton beam tomography. © 2010 IEEE.

Solving the Levins' paradox in the logistic model to the population growth

We introduce a new method to improve Markov maps by means of a Bayesian approach. The method starts from an initial map model, wherefrom a likelihood function is defined which is regulated by a temperature-like parameter. Then, the new constraints are added by the use of Bayes rule in the prior distribution. We applied the method to the logistic map of population growth of a single species. We show that the population size is limited for all ranges of parameters, allowing thus to overcome difficulties in interpretation of the concept of carrying capacity known as the Levins paradox. © Published under licence by IOP Publishing Ltd.

Time in the stair-climbing test as a predictor of thoracotomy postoperative complications

Objectives: The stair-climbing test as measured in meters or number of steps has been proposed to predict the risk of postoperative complications. The study objective was to determine whether the stair-climbing time can predict the risk of postoperative complications. Methods: Patients aged more than 18 years with a recommendation of thoracotomy for lung resection were included in the study. Spirometry was performed according to the criteria by the American Thoracic Society. The stair-climbing test was performed on shaded stairs with a total of 12.16 m in height, and the stair-climbing time in seconds elapsed during the climb of the total height was measured. The accuracy test was applied to obtain stair-climbing time predictive values, and the receiver operating characteristic curve was calculated. Variables were tested for association with postoperative cardiopulmonary complications using the Student t test for independent populations, the Mann-Whitney test, and the chi-square or Fisher exact test. Logistic regression analysis was performed. Results: Ninety-eight patients were evaluated. Of these, 27 showed postoperative complications. Differences were found between the groups for age and attributes obtained from the stair-climbing test. The cutoff point for stair-climbing time obtained from the receiver operating characteristic curve was 37.5 seconds. No differences were found between the groups for forced expiratory volume in 1 second. In the logistic regression, stair-climbing time was the only variable associated with postoperative complications, suggesting that the risk of postoperative complications increases with increased stair-climbing time. Conclusions: The only variable showing association with complications, according to multivariate analysis, was stair-climbing time. © 2013 by The American Association for Thoracic Surgery.

Índice preditor de reserva ovariana (ORPI) para controle de estimulação ovariana individualizado

Objective: to expand the evaluation of a new ovarian response prediction index (ORPI), which was based on the AMH, AFC and age, and to verify its reability as a predictor of ovarian response to stimulation in assisted reproductive technology (ART) cycles. Methods: A total of 129 patients enrolled in the ICSI programme were included. The ORPI values were calculated by multiplying the AMH level (ng/ml) by the number of antral follicles (2-9 mm), and the result was divided by the age (years) of the patient (ORPI=(AMH × AFC)/Patient age). Results: Spearman's test revealed significant correlations (P<0.0001) between the ORPI and the number of oocytes collected and the number of follicles. Logistic regression revealed that ORPI values were significantly associated with the likelihood of collecting ≥4 oocytes (OR=45.56), ≥4 MII oocytes (OR=6.01) and ≥15 oocytes (OR=6.15; P<0.0001). Based on the ROC curves, the ORPI accurately predicted a low ovarian response (<4 oocytes retrieved; area under the curve (AUC):0.91), collection of ≥4 MII oocytes (AUC:0.85) and an excessive ovarian response (≥15 oocytes retrieved; AUC:0.89). Conclusions: The ORPI exhibited an excellent ability to predict a low ovarian response and a good ability to predict a collection of ≥ 4 MII oocytes, an excessive ovarian response. The ORPI might be used to improve the cost-benefit ratio of ovarian stimulation regimens by guiding the selection of medications and by modulating the doses and regimens according to the actual needs of the patients. © Todos os direitos reservados a SBRA - Sociedade Brasileira de Reprodução Assistida.

Interval multivariate curve resolution in the dereplication of HPLC-DAD data from Jatropha gossypifolia

Introduction Jatropha gossypifolia has been used quite extensively by traditional medicine for the treatment of several diseases in South America and Africa. This medicinal plant has therapeutic potential as a phytomedicine and therefore the establishment of innovative analytical methods to characterise their active components is crucial to the future development of a quality product. Objective To enhance the chromatographic resolution of HPLC-UV-diode-array detector (DAD) experiments applying chemometric tools. Methods Crude leave extracts from J. gossypifolia were analysed by HPLC-DAD. A chromatographic band deconvolution method was designed and applied using interval multivariate curve resolution by alternating least squares (MCR-ALS). Results The MCR-ALS method allowed the deconvolution from up to 117% more bands, compared with the original HPLC-DAD experiments, even in regions where the UV spectra showed high similarity. The method assisted in the dereplication of three C-glycosylflavones isomers: vitexin/isovitexin, orientin/homorientin and schaftoside/isoschaftoside. Conclusion The MCR-ALS method is shown to be a powerful tool to solve problems of chromatographic band overlapping from complex mixtures such as natural crude samples. Copyright © 2013 John Wiley & Sons, Ltd. Extracts from J. gossypifolia were analyzed by HPLC-DAD and, dereplicated applying MCR-ALS. The method assisted in the detection of three C-glycosylflavones isomers: vitexin/isovitexin, orientin/homorientin and schaftoside/isoschaftoside. The application of MCR-ALS allowed solving problems of chromatographic band overlapping from complex mixtures such as natural crude samples. Copyright © 2013 John Wiley & Sons, Ltd.

Estudo de modelos não-lineares na descrição do crescimento de fêmeas da raça Canchim

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Logistic platforms: conceptual elements and the role of the public sector

This edition of the FAL Bulletin approaches the issue of logistic platforms and the public sector’s role in the development of the logistic sector.

Epidemiologia da mancha de phaeosphaeria e da cercosporiose em milho

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Curvas de progresso de doenças foliares do milho, sob diferentes tratamentos fungicidas

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Risco de crédito: uma abordagem utilizando análise discriminante, regressão logística e redes neurais artificiais

Considering the relevance of researches concerning credit risk, model diversity and the existent indicators, this thesis aimed at verifying if the Fleuriet Model contributes in discriminating Brazilian open capital companies in the analysis of credit concession. We specifically intended to i) identify the economic-financial indicators used in credit risk models; ii) identify which economic-financial indicators best discriminate companies in the analysis of credit concession; iii) assess which techniques used (discriminant analysis, logistic regression and neural networks) present the best accuracy to predict company bankruptcy. To do this, the theoretical background approached the concepts of financial analysis, which introduced themes relative to the company evaluation process; considerations on credit, risk and analysis; Fleuriet Model and its indicators, and, finally, presented the techniques for credit analysis based on discriminant analysis, logistic regression and artificial neural networks. Methodologically, the research was defined as quantitative, regarding its nature, and explanatory, regarding its type. It was developed using data derived from bibliographic and document analysis. The financial demonstrations were collected by means of the Economática ® and the BM$FBOVESPA website. The sample was comprised of 121 companies, being those 70 solvents and 51 insolvents from various sectors. In the analyses, we used 22 indicators of the Traditional Model and 13 of the Fleuriet Model, totalizing 35 indicators. The economic-financial indicators which were a part of, at least, one of the three final models were: X1 (Working Capital over Assets), X3 (NCG over Assets), X4 (NCG over Net Revenue), X8 (Type of Financial Structure), X9 (Net Thermometer), X16 (Net Equity divided by the total demandable), X17 (Asset Turnover), X20 (Net Equity Profitability), X25 (Net Margin), X28 (Debt Composition) and X31 (Net Equity over Asset). The final models presented setting values of: 90.9% (discriminant analysis); 90.9% (logistic regression) and 97.8% (neural networks). The modeling in neural networks presented higher accuracy, which was confirmed by the ROC curve. In conclusion, the indicators of the Fleuriet Model presented relevant results for the research of credit risk, especially if modeled by neural networks.

Modelos duplo sigmoidais para o crescimento de frutos do cafeeiro

Coffee is one of the main products of Brazilian agriculture, the country is currently the largest producer and exporter. Knowing the growth pattern of a fruit can assist in the development of culture indicating for example, the times of increased fruit weight and its optimum harvest, essential to improve the management and quality of coffee. Some authors indicate that the growth curve of the coffee fruit has a double sigmoid shape. However, it consists of just a visual observation without exploring the use of regression models. The aims of this study were: i) determine if the growth pattern of the coffee fruit is really double sigmoidal; ii) to propose a new approach in weighted importance re-sampling to estimate the parameters of regression models and select the most suitable double sigmoidal model to describe the growth of coffee fruits; iii) to study the spatial distribution effect of the crop in the growth curve of coffee fruits. In the first article the aim was determine if the growth pattern of the coffee fruit is really double sigmoidal. The models double Gompertz and double Logistic showed significantly superior fit to models of simple sigmoid confirming that the standard of coffee fruits growth is really double sigmoidal. In the second article we propose to consider an approximation of the likelihood as the candidate distribution of the weighted importance resampling, aiming to facilitate the process of obtaining samples of marginal distributions of each parameter. This technique was effective since it provided parameters with practical interpretation and low computational effort, therefore, it can be used to estimate parameters of double sigmoidal growth curves. The nonlinear model double Logistic was the most appropriate to describe the growth curve of coffee fruits. In the third article aimed to verify the influence of different planting alignments and sun exposure faces in the fruits growth curve. A difference between the growth rates in the two stages of fruit development was identified, regardless the side. Although it has been proven differences in productivity and quality of coffee, there was no difference between the growth curves in the different planting alignments herein studied.