QSAR modeling: um novo pacote computacional open source para gerar e validar modelos QSAR

QSAR modeling is a novel computer program developed to generate and validate QSAR or QSPR (quantitative structure- activity or property relationships) models. With QSAR modeling, users can build partial least squares (PLS) regression models, perform variable selection with the ordered predictors selection (OPS) algorithm, and validate models by using y-randomization and leave-N-out cross validation. An additional new feature is outlier detection carried out by simultaneous comparison of sample leverage with the respective Studentized residuals. The program was developed using Java version 6, and runs on any operating system that supports Java Runtime Environment version 6. The use of the program is illustrated. This program is available for download at lqta.iqm.unicamp.br.

VIS-NIR SPECTROMETRY, SOIL PHOSPHATE EXTRACTION METHODS AND INTERACTIONS OF SOIL ATTRIBUTES

The objective of this study was to evaluate the relationships between the spectra in the Vis-NIR range and the soil P concentrations obtained from the PM and Prem extraction methods as well as the effects of these relationships on the construction of models predicting P concentration in Oxisols. Soil samples' spectra and their PM and Prem extraction solutions were determined for the Vis-NIR region between 400 and 2500 nm. Mineralogy and/or organic matter content act as primary attributes allowing correlation of these soil phosphorus fractions with the spectra, mainly at wavelengths between 450-550, 900-1100 nm, near 1400 nm and between 2200-2300 nm. However, the regression models generated were not suitable for quantitative phosphate analysis. Solubilization of organic matter and reactions during the PM extraction process hindered correlations between the spectra and these P soil fractions. For Prem,, the presence of Ca in the extractant and preferential adsorption by gibbsite and iron oxides, particularly goethite, obscured correlations with the spectra.

Description of epidemics of coffee rust with neural networks

The objective of this paper was to evaluate the potential of neural networks (NN) as an alternative method to the basic epidemiological approach to describe epidemics of coffee rust. The NN was developed from the intensities of coffee (Coffea arabica) rust along with the climatic variables collected in Lavras-MG between 13 February 1998 and 20 April 2001. The NN was built with climatic variables that were either selected in a stepwise regression analysis or by the Braincel® system, software for NN building. Fifty-nine networks and 26 regression models were tested. The best models were selected based on small values of the mean square deviation (MSD) and of the mean prediction error (MPE). For the regression models, the highest coefficients of determination (R²) were used. The best model developed with neural networks had an MSD of 4.36 and an MPE of 2.43%. This model used the variables of minimum temperature, production, relative humidity of the air, and irradiance 30 days before the evaluation of disease. The best regression model was developed from 29 selected climatic variables in the network. The summary statistics for this model were: MPE=6.58%, MSE=4.36, and R²=0.80. The elaborated neural networks from a time series also were evaluated to describe the epidemic. The incidence of coffee rust at four previous fortnights resulted in a model with MPE=4.72% and an MSD=3.95.

Accounting Beta Measuring Systematic Risk: Empirical Evidence from the Finnish Markets

The main purpose of this study is to examine whether accounting-based variables can be used to measure systematic risk of a company using Finnish data. When the fundamental sources of systematic risk are known, companies are able to manage these risks and increase company value. Accounting beta was formed based on OLS regression models. Theoretical background for the study was based on the findings of studies according to which business risk, financial risk, operating risk and growth risk can be theoretically regarded as determinants of the systematic risk. The results reveal that accounting variables describe systematic risk of a company. The accounting beta is found to be particularly sensitive to the changes in the risk components. The investigation is confidential until 15.10.2012.

Venture capital investment on SME

This thesis studies venture capital investment on small and medium-sized enterprises (SMEs). The specific objective of the study is to test whether venture capitalists have a positive effect on SMEs. In addition effect of several other factors is studied in financial crisis. Used determinants are formulated based on three capital structure theories. The pecking order theory concerns favoring on financing source over another. The agency theory and the tradeoff theory concentrate on the search of optimal capital structure. The data of this study consist of financial statement data and results of corporate questionnaire. Regression analysis was used to find out the effects of several determinants. Regression models were formed based on the presented theories. SMEs with and without venture capitalists were considered separately. It was found that venture capitalists have a positive effect on SMEs. Although some results between SMEs with and without venture capitalists were mixed.

Determinants of cash holdings in Finnish industrial sector: measuring the impact of financial crisis 2007- 2010

This thesis studies cash and short term investments to net assets ratio of Finnish industrial companies during financial crisis, and how different firm specific and macro economical variables affect cash and short term investments. The data consists of quarter level interim reports. Regression analysis was used to find out the effects of different variables. Regression models were formed based on previous studies on cash holdings. It was found that firms studied held more cash during financial crisis than before it. Cash and short-term investments acted as substitute of net working capital. Leverage had a positive and significant relationship to cash and short term investment ratio. It was also found out that firms have a target cash and short term investments ratio.

Fractures in older people - incidence, predictors and consequences

In older populations, fractures are common and the consequences of fractures may be serious both for an individual and for society. However, information is scarce about the incidence, predictors and consequences of fractures in population-based unselected cohorts including both men and women and a long follow-up. The objective of this study was to analyse the incidence and predictors of fractures as well as functional decline and excess mortality due to fractures, among 482 men and 695 women aged 65 or older in the municipality of Lieto, Finland from 1991 until 2002. In analyses, Poisson’s, Cox proportional Hazards and Cumulative Logistic regression models were used for the control of several confounding variables. During the 12-year follow-up with a total of 10 040 person-years (PY), 307 (26%) persons sustained altogether 425 fractures of which 77% were sustained by women. The total incidence of fractures was 53.4 per 1000 PY (95% confidence intervals [95% CI]: 47.9 - 59.5) in women and 24.9 per 1000 PY (95% CI: 20.4 - 30.4) in men. The incidence rates of fractures at any sites and hip fractures were associated with increasing age. No significant changes in the ageadjusted incidence rates of fractures were found in either gender during the 12-year follow-up. The predictors of fractures varied by gender. In multivariate analyses, reduced handgrip strength and body mass index (BMI) lower than 30 in women and a large number of depressive symptoms in men were independent predictors of fractures. A compression fracture in one or more thoracic or upper lumbar vertebras on chest radiography at baseline was associated with subsequent fractures in both genders. Lower body fractures independently predicted both short- (0-2 years) and long-term (up to 8 years) functional decline in mobility and activities of daily living (ADL) performance during the 8-year follow-up. Upper body fractures predicted decline in ADL performance during longterm follow-up. In the 12-year follow-up, hip fractures in men (Hazard Ratio [HR] 8.1, 95% CI: 4.4-14.9) and in women (HR 3.0, 95% CI: 1.9-4.9), and fractures at the proximal humerus in men (HR 5.4, 95% CI: 1.6-17.7) were independently associated with excess mortality. In addition, leisure time inactivity in physical exercise predicted independently both functional decline and excess mortality. Fractures are common among older people posing serious individual consequences. Further studies about the effectiveness of preventing falls and fractures as well as improving care and rehabilitation after fractures are needed.

Thermal comfort temperature update for broiler chickens up to 21 days of age

Due to changes in genetics and nutrition, as well as in acclimatization of broiler chickens to the Brazilian climate, temperature values currently accepted as optimal may be outdated. The objective of this research was to update the environment temperatures that characterize the thermal comfort for broilers chickens from one to 21 days of age, under Brazilian production conditions. This research was conducted with 600 COBB birds, which were distributed in five growth chambers maintained at different temperatures during the first three weeks of age. During the experimental period, temperature values were progressively reduced, consisting in five treatments: T2724/21, T30/27/24, T33/30/27, T36/33/30 and T39/36/33. It was observed that the birds maintained in the T30(27-24) treatment presented better performance compared to other environment conditions. Based on the obtained regression models, the environment temperature values that provide greater weighing gain for the broiler chicken growth in the initial period were 31.3, 25.5 and 21.8 ºC, respectively for the first, second and third week of age.

Software for design of experiments and response modelling of cake ltration applications

Filtration is a widely used unit operation in chemical engineering. The huge variation in the properties of materials to be ltered makes the study of ltration a challenging task. One of the objectives of this thesis was to show that conventional ltration theories are di cult to use when the system to be modelled contains all of the stages and features that are present in a complete solid/liquid separation process. Furthermore, most of the ltration theories require experimental work to be performed in order to obtain critical parameters required by the theoretical models. Creating a good overall understanding of how the variables a ect the nal product in ltration is somewhat impossible on a purely theoretical basis. The complexity of solid/liquid separation processes require experimental work and when tests are needed, it is advisable to use experimental design techniques so that the goals can be achieved. The statistical design of experiments provides the necessary tools for recognising the e ects of variables. It also helps to perform experimental work more economically. Design of experiments is a prerequisite for creating empirical models that can describe how the measured response is related to the changes in the values of the variable. A software package was developed that provides a ltration practitioner with experimental designs and calculates the parameters for linear regression models, along with the graphical representation of the responses. The developed software consists of two software modules. These modules are LTDoE and LTRead. The LTDoE module is used to create experimental designs for di erent lter types. The lter types considered in the software are automatic vertical pressure lter, double-sided vertical pressure lter, horizontal membrane lter press, vacuum belt lter and ceramic capillary action disc lter. It is also possible to create experimental designs for those cases where the variables are totally user de ned, say for a customized ltration cycle or di erent piece of equipment. The LTRead-module is used to read the experimental data gathered from the experiments, to analyse the data and to create models for each of the measured responses. Introducing the structure of the software more in detail and showing some of the practical applications is the main part of this thesis. This approach to the study of cake ltration processes, as presented in this thesis, has been shown to have good practical value when making ltration tests.

Software for design of experiments and response modelling of cake filtration applications

Filtration is a widely used unit operation in chemical engineering. The huge variation in the properties of materials to be ltered makes the study of ltration a challenging task. One of the objectives of this thesis was to show that conventional ltration theories are di cult to use when the system to be modelled contains all of the stages and features that are present in a complete solid/liquid separation process. Furthermore, most of the ltration theories require experimental work to be performed in order to obtain critical parameters required by the theoretical models. Creating a good overall understanding of how the variables a ect the nal product in ltration is somewhat impossible on a purely theoretical basis. The complexity of solid/liquid separation processes require experimental work and when tests are needed, it is advisable to use experimental design techniques so that the goals can be achieved. The statistical design of experiments provides the necessary tools for recognising the e ects of variables. It also helps to perform experimental work more economically. Design of experiments is a prerequisite for creating empirical models that can describe how the measured response is related to the changes in the values of the variable. A software package was developed that provides a ltration practitioner with experimental designs and calculates the parameters for linear regression models, along with the graphical representation of the responses. The developed software consists of two software modules. These modules are LTDoE and LTRead. The LTDoE module is used to create experimental designs for di erent lter types. The lter types considered in the software are automatic vertical pressure lter, double-sided vertical pressure lter, horizontal membrane lter press, vacuum belt lter and ceramic capillary action disc lter. It is also possible to create experimental designs for those cases where the variables are totally user de ned, say for a customized ltration cycle or di erent piece of equipment. The LTRead-module is used to read the experimental data gathered from the experiments, to analyse the data and to create models for each of the measured responses. Introducing the structure of the software more in detail and showing some of the practical applications is the main part of this thesis. This approach to the study of cake ltration processes, as presented in this thesis, has been shown to have good practical value when making ltration tests.

Maternal age and adverse perinatal outcomes in a birth cohort (BRISA) from a Northeastern Brazilian city

PURPOSE:To verify the existence of associations between different maternal ages and the perinatal outcomes of preterm birth and intrauterine growth restriction in the city of São Luís, Maranhão, Northeastern Brazil.METHODS:A cross-sectional study using a sample of 5,063 hospital births was conducted in São Luís, from January to December 2010. The participants comprise the birth cohort for the study "Etiological factors of preterm birth and consequences of perinatal factors for infant health: birth cohorts from two Brazilian cities" (BRISA). Frequencies and 95% confidence intervals were used to describe the results. Multiple logistic regression models were applied to assess the adjusted odds ratio (OR) of maternal age associated with the following outcomes: preterm birth and intrauterine growth restriction.RESULTS:The percentage of early teenage pregnancy (12–15 years old) was 2.2%, and of late (16–19 years old) was 16.4%, while pregnancy at an advanced maternal age (>35 years) was 5.9%. Multivariate analyses showed a statistically significant increase in preterm births among females aged 12–15 years old (OR=1.6; p=0.04) compared with those aged 20–35 years. There was also a higher rate in preterm births among females aged 16–19 years old (OR=1.3; p=0.01). Among those with advanced maternal age (>35 years old), the increase in the prevalence of preterm birth had only borderline statistical significance (OR=1.4; p=0.05). There was no statistically significant association between maternal age and increased prevalence of intrauterine growth restriction.

Predictors of fluid intravasation during operative hysteroscopy: a preplanned prospective observational study with 200 cases

PURPOSE: To verify the predictors of intravasation rate during hysteroscopy.METHODS: Prospective observational study (Canadian Task Force classification II-1). All cases (n=200 women; 22 to 86 years old) were treated in an operating room setting. Considering respective bag overfill to calculate water balance, we tested two multiple linear regression models: one for total intravasation (mL) and the other for absorption rate (mL.min-1). The predictors tested (independent variables) were energy (mono/bipolar), tube patency (with/without tubal ligation), hysterometry (cm), age≤50 years, body surface area (m2), surgical complexity (with/without myomectomy) and duration (min).RESULTS: Mean intravasation was significantly higher when myomectomy was performed (442±616 versus 223±332 mL; p<0.01). In the proposed multiple linear regression models for total intravasation (adjusted R2=0.44; p<0.01), the only significant predictors were myomectomy and duration (p<0.01).In the proposed model for intravasation rate (R2=0.39; p<0.01), only myomectomy and hysterometry were significant predictors (p=0.02 and p<0.01, respectively).CONCLUSIONS: Not only myomectomy but also hysterometry were significant predictors of intravasation rate during operative hysteroscopy.

Babesia canis vogeli infection in dogs and ticks in the semiarid region of Pernambuco, Brazil

Abstract:This study aimed to report the prevalence of Babesia canis vogeli in dogs and ticks in the urban and rural areas of Petrolina, Pernambuco. Serum and peripheral blood samples of 404 dogs were tested by indirect immunofluorescence assay (IFA) and by blood smears, respectively. The presence of tick infestation was evaluated, and some specimens were submitted to DNA amplification by polymerase chain reaction (PCR). The presence of antibodies anti-B. canis vogeli was determinate in 57.9% (234/404) of dogs. The direct detection of Babesia spp was obtained in 0.5% (2/404) dogs by visualization of intraerythrocytic forms. Infestation by Rhipicephalus sanguineus sensu lato was observed in 54.5% (220/404) of dogs in both urban and rural areas. DNA of Babesia canis vogeli were obtained by PCR in 6% individual (3/50) and 8.7% of pool of ticks (7/80). The risk factors for the presence of anti-B. canis vogeli antibodies, as determined through the application of logistic regression models (P<0.05), were the following: medium breed size variables (P<0.001); contact with areas of forest (P=0.021); and access on the street (P=0.046). This study describes, for the first time, the confirmation of infection of B. canis vogeli in dogs and ticks in the semiarid region of Pernambuco, Brazil.

Growth of the crabgrass species Digitaria ciliaris and Digitaria nuda

The aim of this research paper was to compare the growth of D. ciliaris and D. nuda crabgrass species under non-competitive conditions. To this end, two experiments were conducted, one from March - July 2010 and the other from February - June 2011. The experimental design of both trials was completely randomized making a factorial (2 seasons x 2 species crabgrass x 12 evaluation periods) with four replications. Assessments began at 15 days after sowing (DAS), and repeated weekly until 92 DAS. The variables evaluated were total dry matter (roots+leaves+stems), leaf area, leaf number and tiller. The results were submitted to analysis of variance and the absolute growth rate, relative growth rate and leaf area ratio were calculated using the means, which were adjusted regression models. The crabgrass species were significantly different in leaf area, leaf number, tiller number and dry matter per plant. D. ciliaris for all variables was statistically higher than D. nuda. Regarding the speed at which the growth of the species occurred, the absolute growth rate and relative growth rate of D. ciliaris was also greater than D. nuda. In addition, D. ciliaris also had a lower leaf area ratio indicating greater efficiency in converting light energy into carbohydrates. It can be concluded that D. ciliaris has a higher growth rate in conditions where there is no limitation of nutrients and water availability in relation to D. nuda, mainly due to D. ciliaris have greater leaf area, number of leaves and dry matter accumulation per plant.

Comparison of model-based above ground biomass predictions from LiDAR

In order to reduce greenhouse emissions from forest degradation and deforestation the international programme REDD (Reducing Emissions from Deforestation and forest Degradation) was established in 2005 by the United Nations Framework Convention on Climate Change (UNFCCC). This programme is aimed to financially reward to developing countries for any emissions reductions. Under this programm the project of setting up the payment system in Nepal was established. This project is aimed to engage local communities in forest monitoring. The major objective of this thesis is to compare and verify data obtained from di erect sources - remotely sensed data, namely LiDAR and field sample measurements made by two groups of researchers using two regression models - Sparse Bayesian Regression and Bayesian Regression with Orthogonal Variables.