O financiamento da economia dos Açores

Dissertação de Mestrado em Ciências Económicas e Empresariais.

The significance of Traveler's Route Knowledge for Choice of commuting mode of transport

Dissertation submitted in partial fulfillment of the requirements for the Degree of Master of Science in Geospatial Technologies.

Trends of the Risk of Death due to Circulatory, Cerebrovascular, and Ischemic Heart Diseases in 11 Brazilian Capitals from 1980 to 1998

OBJECTIVE: To assess the trends of the risk of death due to circulatory (CD), cerebrovascular (CVD), and ischemic heart diseases (IHD) in 11 Brazilian capitals from 1980 to 1998. METHODS: Data on mortality due to CD, CVD and IHD were obtained from the Brazilian Health Ministry, and the population estimates were calculated by interpolation with the Lagrange method based on census data from 1980 and 1991 and the population count of 1996. The trends were analyzed with the multiple linear regression method. RESULTS: CD showed a trend towards a decrease in most capitals, except for Brasília, where a mild increase was observed. The cities of Porto Alegre, Curitiba, Rio de Janeiro, Cuiabá, Goiânia, Belém, and Manaus showed a decrease in the risk of death due to CVD and IHD, while the city of Brasília showed an increase in CVD and IHD. The city of São Paulo showed a mild increase in IHD for individuals of both sexes aged 30 to 39 years and for females aged 40 to 59 years. In the cities of Recife and Salvador, a reduction in CD was observed for all ages and both sexes. In the city of Recife, however, an increase in IHD was observed at younger ages (30 to 49 years), and this trend decreased until a mild reduction (-4%) was observed in males ³ 70 years. CONCLUSION: In general, a reduction in the risk of death due to CD and an increase in IHD were observed, mainly in the cities of Recife and Brasília.

Heterogeneity across immigrants in the Spanish labour

The purpose of this paper is to analyze the diferences that immigrants have in the Spanish labour market. Immigrants in Spain come from a diversity of continents (Africa, South America, Eastern Europe, Asia, etc.), and there are substantial diferences in characteristics not only among continents but also among countries in each continent. Using a quantile regression method of decomposition we estimate these diferences that are reflected in the labour market and in particular are mirrored in the wage, so some immigrants are more discriminated or segregated that others because they have less advantage. For example Argentineans and Peruvians have the same origin and culture but we can find diferences in the wage that they receive in the Spanish labor market, or for example Moroccans have a advantage with respect to the Rest of Africans, due to the geographical proximity to Spain. So when we study the pay gap and the gender pay gap we need to take into consideration the origin of immigrants. We also want to study how the integration of immigrants evolved across years, whether the wage gap that we find in the first episode of work between immigrants and natives disappears or continues to be present in the Spain labour market.

Correcting Measurement Error Bias in Interaction Models with Small Samples

Several methods have been suggested to estimate non-linear models with interaction terms in the presence of measurement error. Structural equation models eliminate measurement error bias, but require large samples. Ordinary least squares regression on summated scales, regression on factor scores and partial least squares are appropriate for small samples but do not correct measurement error bias. Two stage least squares regression does correct measurement error bias but the results strongly depend on the instrumental variable choice. This article discusses the old disattenuated regression method as an alternative for correcting measurement error in small samples. The method is extended to the case of interaction terms and is illustrated on a model that examines the interaction effect of innovation and style of use of budgets on business performance. Alternative reliability estimates that can be used to disattenuate the estimates are discussed. A comparison is made with the alternative methods. Methods that do not correct for measurement error bias perform very similarly and considerably worse than disattenuated regression

Soil infiltration based on bp neural network and grey relational analysis

Soil infiltration is a key link of the natural water cycle process. Studies on soil permeability are conducive for water resources assessment and estimation, runoff regulation and management, soil erosion modeling, nonpoint and point source pollution of farmland, among other aspects. The unequal influence of rainfall duration, rainfall intensity, antecedent soil moisture, vegetation cover, vegetation type, and slope gradient on soil cumulative infiltration was studied under simulated rainfall and different underlying surfaces. We established a six factor-model of soil cumulative infiltration by the improved back propagation (BP)-based artificial neural network algorithm with a momentum term and self-adjusting learning rate. Compared to the multiple nonlinear regression method, the stability and accuracy of the improved BP algorithm was better. Based on the improved BP model, the sensitive index of these six factors on soil cumulative infiltration was investigated. Secondly, the grey relational analysis method was used to individually study grey correlations among these six factors and soil cumulative infiltration. The results of the two methods were very similar. Rainfall duration was the most influential factor, followed by vegetation cover, vegetation type, rainfall intensity and antecedent soil moisture. The effect of slope gradient on soil cumulative infiltration was not significant.

Cycle length of spermatogenesis in shrews (mammalia: soricidae) with high and low metabolic rates and different mating systems.

The aim of the present study was to establish and compare the durations of the seminiferous epithelium cycles of the common shrew Sorex araneus, which is characterized by a high metabolic rate and multiple paternity, and the greater white-toothed shrew Crocidura russula, which is characterized by a low metabolic rate and a monogamous mating system. Twelve S. araneus males and fifteen C. russula males were injected intraperitoneally with 5-bromodeoxyuridine, and the testes were collected. For cycle length determinations, we applied the classical method of estimation and linear regression as a new method. With regard to variance, and even with a relatively small sample size, the new method seems to be more precise. In addition, the regression method allows the inference of information for every animal tested, enabling comparisons of different factors with cycle lengths. Our results show that not only increased testis size leads to increased sperm production, but it also reduces the duration of spermatogenesis. The calculated cycle lengths were 8.35 days for S. araneus and 12.12 days for C. russula. The data obtained in the present study provide the basis for future investigations into the effects of metabolic rate and mating systems on the speed of spermatogenesis.

Application of Multi-SNP Approaches Bayesian LASSO and AUC-RF to Detect Main Effects of Inflammatory-Gene Variants Associated with Bladder Cancer Risk

The relationship between inflammation and cancer is well established in several tumor types, including bladder cancer. We performed an association study between 886 inflammatory-gene variants and bladder cancer risk in 1,047 cases and 988 controls from the Spanish Bladder Cancer (SBC)/EPICURO Study. A preliminary exploration with the widely used univariate logistic regression approach did not identify any significant SNP after correcting for multiple testing. We further applied two more comprehensive methods to capture the complexity of bladder cancer genetic susceptibility: Bayesian Threshold LASSO (BTL), a regularized regression method, and AUC-Random Forest, a machine-learning algorithm. Both approaches explore the joint effect of markers. BTL analysis identified a signature of 37 SNPs in 34 genes showing an association with bladder cancer. AUC-RF detected an optimal predictive subset of 56 SNPs. 13 SNPs were identified by both methods in the total population. Using resources from the Texas Bladder Cancer study we were able to replicate 30% of the SNPs assessed. The associations between inflammatory SNPs and bladder cancer were reexamined among non-smokers to eliminate the effect of tobacco, one of the strongest and most prevalent environmental risk factor for this tumor. A 9 SNP-signature was detected by BTL. Here we report, for the first time, a set of SNP in inflammatory genes jointly associated with bladder cancer risk. These results highlight the importance of the complex structure of genetic susceptibility associated with cancer risk.

Techniques for Estimating Flood-Frequency Discharges for Streams in Iowa, HR-395A, 2001

A statewide study was conducted to develop regression equations for estimating flood-frequency discharges for ungaged stream sites in Iowa. Thirty-eight selected basin characteristics were quantified and flood-frequency analyses were computed for 291 streamflow-gaging stations in Iowa and adjacent States. A generalized-skew-coefficient analysis was conducted to determine whether generalized skew coefficients could be improved for Iowa. Station skew coefficients were computed for 239 gaging stations in Iowa and adjacent States, and an isoline map of generalized-skew-coefficient values was developed for Iowa using variogram modeling and kriging methods. The skew map provided the lowest mean square error for the generalized-skew- coefficient analysis and was used to revise generalized skew coefficients for flood-frequency analyses for gaging stations in Iowa. Regional regression analysis, using generalized least-squares regression and data from 241 gaging stations, was used to develop equations for three hydrologic regions defined for the State. The regression equations can be used to estimate flood discharges that have recurrence intervals of 2, 5, 10, 25, 50, 100, 200, and 500 years for ungaged stream sites in Iowa. One-variable equations were developed for each of the three regions and multi-variable equations were developed for two of the regions. Two sets of equations are presented for two of the regions because one-variable equations are considered easy for users to apply and the predictive accuracies of multi-variable equations are greater. Standard error of prediction for the one-variable equations ranges from about 34 to 45 percent and for the multi-variable equations range from about 31 to 42 percent. A region-of-influence regression method was also investigated for estimating flood-frequency discharges for ungaged stream sites in Iowa. A comparison of regional and region-of-influence regression methods, based on ease of application and root mean square errors, determined the regional regression method to be the better estimation method for Iowa. Techniques for estimating flood-frequency discharges for streams in Iowa are presented for determining ( 1) regional regression estimates for ungaged sites on ungaged streams; (2) weighted estimates for gaged sites; and (3) weighted estimates for ungaged sites on gaged streams. The technique for determining regional regression estimates for ungaged sites on ungaged streams requires determining which of four possible examples applies to the location of the stream site and its basin. Illustrations for determining which example applies to an ungaged stream site and for applying both the one-variable and multi-variable regression equations are provided for the estimation techniques.

Implisiittisen kalibroinnin soveltamismahdollisuudet kemiantekniikassa

Työn taustalla oli tavoite parantaa erään teollisuusprosessin toimintaa ja sen tuottoa mallintamalla reaktiovaiheen alussa tapahtuvan välituotteen muodostumisen reaktiokinetiikka sekä perinteisellä tavalla että implisiittisellä kalibroinnilla. Toisena tavoitteena oli selvittää, kuinka implisiittistä kalibrointia voidaan yleisemmin hyödyntää kemiantekniikassa. Implisiittinen kalibrointi on menetelmä, jolla voidaan ratkaista jonkin teoreettisen mallin parametrit suoraan epäsuorasta mittausdatasta (esimerkiksi spektreistä) lähes kokonaan ilman off-line analyysejä. Tämän työn kirjallisuusosassa on esitetty implisiittisen kalibroinnin toimintaperiaate sekä lyhyesti FTIR-spektrometrian perusteita. Työn kokeellisessa osassa on estimoitu tutkitun välituotteen muodostumisen kineettiset parametrit sekä tavanomaisella parametriestimoinnilla että implisiittisellä kalibroinnilla. Lisäksi kokeellisessa osassa on selvitetty lyhyesti tutkitun prosessin FTIR-spektrien lämpötilariippuvuuksia ja esitetty neljä mahdollista uutta sovelluskohdetta implisiittiselle kalibroinnille. Tavanomaisella parametriestimoinnilla saatiin estimoitua varsin yksiselitteiset arvot kineettisille parametreille. Myös mallin sovitus koedataan on hyvä kolmessa kokeessa viidestä. Parametriestimointi implisiittisellä kalibroinnilla onnistui lupaavasti vaikka tulokset eivät ole aivan niin hyviä kuin tavanomaisessa parametriestimoinnissa. Parhaat tulokset implisiittisessä kalibroinnissa saavutettiin suoralla kalibrointitavalla GRR (Generalized Ridge Regression)-kalibrointimenetelmää käyttämällä.

A mechanistic approach to methylene blue sorption on two vegetable wastes: Cork bark and grape stalks

Two vegetable wastes, cork bark and grape stalks, were investigated for the removal of methylene blue from aqueous solution. The effects of contact time, dye concentration, pH, and temperature on sorption were studied relative to adsorption on a commercially-activated carbon. The highest adsorption yield was obtained within the pH range 5 to 10 for grape stalks and 7 to 10 for cork bark. The sorption kinetics of dye onto activated carbon and grape stalks was very fast. Kinetics data were fitted to the pseudo-first and second order kinetic equations, and the values of the pseudo-second-order initial rate constants were found to be 1.69 mg g-1 min-1 for activated carbon, 2.24 mg g-1 min-1 for grape stalks, and 0.90 mg g-1 min-1 for cork bark. Langmuir maximum sorption capacities for activated carbon, grape stalks, and cork bark for methylene blue estimated by the Orthogonal Distance Regression method (ODR) were 157.5 mg g-1, 105.6 mg g-1, and 30.52 mg g-1, respectively. FTIR spectra indicated that carboxylic groups and lignin play a significant role in the sorption of methylene blue. Electrostatic forces, n-p interactions, cation-p, and p-p stacking interactions contribute to methylene blue sorption onto grape stalks and cork bark. Grape stalks can be considered an efficient biosorbent and as a viable alternative to activated carbon and ion-exchange resins for the removal of methylene blue

Cinética e caracterização de ramnolipídeos produzidos por Pseudomonas aeruginosa MSIC02 utilizando glicerol como fonte de carbono

Glycerol, a co-product of biodiesel production, was used as a carbon source for the kinetics studies and production of biosurfactants by P. aeruginosa MSIC02. The highest fermentative parameters (Y PX = 3.04 g g-1; Y PS = 0.189 g g-1, P B = 31.94 mg L-1 h-1 and P X = 10.5 mg L-1 h-1) were obtained at concentrations of 0.4% (w/v) NaNO3 and 2% (w/v) glycerol. The rhamnolipid exhibited 80% of emulsification on kerosene, surface tension of 32.5 mN m-1, CMC = 28.2 mg L-1, C20 (concentration of surfactant in the bulk phase that produces a reduction of 20 dyn/cm in the surface tension of the solvent) = 0.99 mg L-1, Γm (surface concentration excess) = 2.4 x 10-26 mol Å-2 and S (surface area) = 70.4 Ų molecule-1 with solutions containing 10% NaCl. A mathematical model based on logistic equation was considered to representing the process. Model parameters were estimated by non-linear regression method. This approach was able to give a good description of the process.

Increased oxidative stress markers may be a promising indicator of risk for primary ovarian insufficiency: a cross-sectional case control study

PURPOSE: The aim of this study was to evaluate serum levels of inducible nitric oxide synthase (INOS), myeloperoxidase (MPO), total antioxidant status (TAS), and total oxidative status (TOS) in women with primary ovarian insufficiency (POI) and to compare them with healthy fertile women. We also examined the possible risk factors associated with POI.METHODS: This cross-sectional case control study was conducted in Zekai Tahir Burak Women's Health Education and Research Hospital. The study population consisted of 44 women with POI (study group) and 36 healthy fertile women (control group). In all patients, serum levels of INOS, MPO, TAS, and TOS were determined. INOS and MPO levels were measured by enzyme-linked immunosorbent assay whereas colorimetric method was used for evaluating TAS and TOS levels. Age, body mass index (BMI), obstetric history, smoking status, family history, comorbidities, sonographic findings, complete blood count values, C-reactive protein and baseline hormone levels were also analyzed. Student's t-test or Mann-Whitney U test was used to compare continuous variables between the groups; categorical data were evaluated by using Pearson χ2 or Fisher exact test, when appropriate. Binary logistic regression method was used to identify risk factors for POI.RESULTS: We found significantly elevated levels of INOS (234.1±749.5 versus133.8±143.0; p=0.005), MPO (3,438.7±1,228.6 versus 2,481.9±1,230.1; p=0.001), and TOS (4.3±1.4 versus 3.6±1.4; p=0.02) in the sera of the study group when compared to the BMI-age matched control group. However, difference in serum levels of TAS were not significant between the 2 groups (1.7±0.2 versus 1.6±0.2; p=0.15). Logistic regression method demonstrated that BMI <25 kg/m2, nulliparity, family history of POI, smoking, and elevated serum levels of INOS, MPO, and TOS were independent risk factors for POI.CONCLUSION: We found an increase in INOS, MPO, and TOS in women with POI. These serum markers may be promising in early diagnosis of POI. Further large-scale studies are required to determine whether oxidative stress markers have a role in diagnosing POI.

Amniotic fluid amino acid levels in non-immune hydrops fetalis: a case-control study

In a prospective case-control study, we compared the amniotic fluid amino acid levels in non-immune hydrops fetalis (NIHF) and normal fetuses. Eighty fetuses underwent amniocentesis for different reasons at the prenatal diagnosis unit of the Department of Obstetrics and Gynecology, Faculty of Medicine, Dicle University. Forty of these fetuses were diagnosed with NIHF. The study included 40 women each in the NIHF (mean age: 27.69 ± 4.56 years) and control (27.52 ± 5.49 years) groups, who had abnormal double- or triple-screening test values with normal fetuses with gestational ages of 23.26 ± 1.98 and 23.68 ± 1.49 weeks at the time of sample collection, respectively. Amniotic fluid amino acid concentrations (intra-assay variation: 2.26-7.85%; interassay variation: 3.45-8.22%) were measured using EZ:faast kits (EZ:faast GC/FID free (physiological) amino acid kit; Phenomenex, USA) by gas chromatography. The standard for quantitation was a mixture of free amino acids from Phenomenex. The levels of 21 amino acids were measured. The mean phosphoserine and serine levels were significantly lower in the NIHF group, while the taurine, α-aminoadipic acid (aaa), glycine, cysteine, NH4, and arginine (Arg) levels were significantly higher compared to control. Significant risk variables for the NIHF group and odds coefficients were obtained using a binary logistic regression method. The respective odds ratios and 95% confidence intervals for the risk variables phosphoserine, taurine, aaa, Arg, and NH4 were 3.31 (1.84-5.97), 2.45 (1.56-3.86), 1.78 (1.18-2.68), 2.18 (1.56-3.04), and 2.41 (1.66-3.49), respectively. The significant difference between NIHF and control fetuses suggests that the amniotic fluid levels of some amino acids may be useful for the diagnosis of NIHF.

Determinants of capital expenditures: Evidence from oil and mining sectors in Russia

This master’s thesis investigates the significant macroeconomic and firm level determinants of CAPEX in Russian oil and mining sectors. It also studies the Russian oil and mining sectors, its development, characteristics and current situation. The panel data methodology was implemented to identify the determinants of CAPEX in Russian oil and mining sectors and to test derived hypotheses. The core sample consists of annual financial data of 45 publicly listed Russian oil and mining sector companies. The timeframe of the thesis research is a six year period from 2007 to 2013. The findings of the master’s thesis have shown that Gross Sales, Return On Assets, Free Cash Flow and Long Term Debt are firm level performance variables along with Russian GDP, Export, Urals and the Reserve Fund are macroeconomic variables that determine the magnitude of new capital expenditures reported by publicly listed Russian oil and mining sector companies. These results are not controversial to the previous research paper, indeed they confirm them. Furthermore, the findings from the emerging countries, such as Malaysia, India and Portugal, are analogous to Russia. The empirical research is edifying and novel. Findings from this master’s thesis are highly valuable for the scientific community, especially, for researchers who investigate the determinant of CAPEX in developing countries. Moreover, the results can be utilized as a cogent argument, when companies and investors are doing strategic decisions, considering the Russian oil and mining sectors.