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.

Análise da expressão dos genes da subfamília DREB em resposta à seca em plantas de Coffea canephora Conilon

Coffea canephora is one of the most economically important coffee species and in Brazil, Conilon is the most widely cultivated plant of this species. Abiotic stresses such as temperature variations and drought periods are factors that significantly affect their production and tend to worsen with globally recognized climate changes. In an attempt to understand the molecular responses of coffee plants in water deficit conditions, recent studies have identified candidate genes (CGs) as CcDREB1D. This gene showed increased expression in response to drought in the leaves of clone 14 (drought tolerant) in relation to the clone 22 (sensitive to drought) of C. canephora Conilon. Based on these results, the identification of DREB genes and their subgroups (SGs) of C. canephora, the objective is to analyze in silico and also in vivo these genes expression in leaf and root of tolerant (14, 73 and 120) and sensitive clones (22) of C. canephora Conilon submitted or not to a water deficit. In silico expressions of all DREB genes were analyzed from the Coffee Genome Hub Database and in vivo expression was performed by the technique "reverse transcription-quantitative PCR" (RT-qPCR). In silico gene expression analysis was possible to identify DREB genes with potential responses to abiotic stresses, corroborating some validated in vivo results. In this analysis, several genes showed differential expression in response to drought among the SGs (IIV), the tolerant and sensitive clones and the leaf and root. These differentially expressed genes were identified as potential CGs and among them, it was found that most tolerant clones showed increased expression in relation to sensitive in response to drought, with higher expression levels for clones 14 and 73. These highest levels were observed in leaves compared to the roots and SG-I stood at greater number of genes expressed in response to drought. These results suggest that DREB CGs, as Cc05_g06840, Cc02_g03420 e Cc08_g13960, play an important role in the regulatory mechanisms of response to drought in C. canephora Conilon.

Análise do teor de cocaína em amostras apreendidas pela polícia utilizando-se a técnica de cromatografia liquida de alta eficiência com detector UV-Vis

The HPLC technique with UV-Vis detection was employed in the analysis of cocaine content in apprehended samples of cocaine and crack. A peak signal for cocaine was obtained in 3.5 minutes run by using acetonitrile/water (95:5v/v) as a mobile phase. Optimized spectrophotometric signal was obtained at a wavelength of 224 nm. The analytical curve from 1.0 to 40.0 ppm of cocaine was obtained, showing a linear correlation coefficient of 0.9989, with detection and quantification limits of 0.75 ppm and 3.78 ppm, respectively. This methodology was employed at the dosage of confiscated samples of cocaine and crack in the Scientific Police Laboratory of Ribeirão Preto-SP city.

Análise de experimentos fatoriais de dois fatores com tratamentos adicionais

Experiments using factorial arrangement of treatments are rather common and useful in agricultural research. The main advantage is the possibility of testing many hypotheses, allowing broader conclusions over different factors, studied simultaneously. Factorial arrangements are used to compare levels of each factor (main effects), and also to verify if the differences among levels of a given factor are dependent on the levels of the other factors (interacions). In the analysis of data from factorial experiments, difficulty is increased when additional treatments are included. Inclusion of one or more additional treatments is a quite common practice, since such treatments are usually taken as reference or standard for evaluation and comparasion of the remaimng treatments, or aiming complementary information. This increase of difficulty is however low, compared to the advantages. As in literature there are few references about the statistical analysis of factorial experiments with additonal treatments, and given straightforward use in experimentation, the objective of this work was the presentation of approach for the use of factorial experiments with additonal treatments trough the analysis of some examples using the SAS® software, with the corresponding theoretical development, obtaining the system of normal equations, estimators of the parameters and variance of contrasts among two treatment means. It is suggested that additional treatments should be used with caution. The analysis of variance of such kind of experiment was presented using matrix notation.

Análise energética da madeira e do carvão de híbridos entre Corymbia citriodora (Hook.) K.D. Hill & L.A.S. Johnson e Corymbia torelliana (F. Muell.) K.D. Hill & L.A.S. Johnson

This research aimed to evaluate the wood and charcoal quality of hybrids clone of the crossing C. citriodora with C. torelliana in two different locations for charcoal production. Seven with 3,75 years old clones, planted at country of Itamarandiba – MG, and six 6,42 years old clones, planted in Dionísio – MG, were studied. For wood and charcoal quality analysis, samples were collected along the stem of the trees until the commercial height. Properties study of the wood was done by chemical analysis, basic density, superior heat power, and thermogravimetric analysis. The wood samples were carbonized in laboratory conditions with heating rate of 1.67 0 C.min -1 , starting at 100 0 C until 450 0 C and keeping on this temperature for 30 minutes. It were determined the carbonizations gravimetric yield, all in dry basis. The wood quality was evaluated based on the chemical immediate analysis, relative apparent density, and gross heating value. The experiment was installed according to the completely randomized design, with five repetitions. The collected data were submitted to analysis of variance and, when the evaluated effects were significant by “F” test, was applied the Scott-Knott test at 5% probability for multiple comparisons. For correlation analysis, Pearson correlation coefficient, tested by the "t" test at 5% probability was used. Results showed variability of wood between the genetic materials evaluated in relation to place and plant crossing. The thermal analysis of the wood showed significant variation between clones and it was possible to differentiate two stages of degradation (hemicelluloses and cellulose). The majority of the clones presented satisfactory properties for the charcoal production, while, clone 3, planted in Itamarandiba, obtained the best performance due it have the higher yield and energetic efficiency, thus, achieving the best potential for charcoal production. However, clone 9, planted in Dionísio, was the less indicated for charcoal production since it presented the lowest energetic efficiency, gravimetric yield, and densities.