Capabilities and gender: a sum or system of inequalities? The case of Chile

Includes bibliography

Isolamento e caracterização de amostras comunitárias Staphylococcus aureus resistente à Meticilina (CA-MRSA) em uma população carcerária no município de Avaré

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Estimativas de (co) varância genética de pesos do nascimento até a maturidade em rebanhos da raça Nelore usando modelos de regressão aleatória e de características múltiplas

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

Modelos genéticos para a produção no dia do controle em bovinos Gir Leiteiro (Bos indicus)

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Fast determination of beef quality parameters with time-domain nuclear magnetic resonance spectroscopy and chemometrics

The noteworthy of this study is to predict seven quality parameters for beef samples using time-domain nuclear magnetic resonance (TD-NMR) relaxometry data and multivariate models. Samples from 61 Bonsmara heifers were separated into five groups based on genetic (breeding composition) and feed system (grain and grass feed). Seven sample parameters were analyzed by reference methods; among them, three sensorial parameters, flavor, juiciness and tenderness and four physicochemical parameters, cooking loss, fat and moisture content and instrumental tenderness using Warner Bratzler shear force (WBSF). The raw beef samples of the same animals were analyzed by TD-NMR relaxometry using Carr-Purcell-Meiboom-Gill (CPMG) and Continuous Wave-Free Precession (CWFP) sequences. Regression models computed by partial least squares (PLS) chemometric technique using CPMG and CWFP data and the results of the classical analysis were constructed. The results allowed for the prediction of aforementioned seven properties. The predictive ability of the method was evaluated using the root mean square error (RMSE) for the calibration (RMSEC) and validation (RMSEP) data sets. The reference and predicted values showed no significant differences at a 95% confidence level.

Prevalence of low back pain and associated factors in adults from a middle-size Brazilian city

Objective: To determine the prevalence of low back pain and some related variables among adults of both genders. Methods: Was conduct a cross-sectional study of population-based in the urban area of Presidente Prudente, São Paulo. The sample consisted of 743 adult residents for over two years in this city. Low back pain, quality of sleep and physical activity were collected through face to face interview at the residence of respondents. Was used the chi-square test to analyze the association between variables, later was created tree multivariate models with hierarchical inclusion of confounding factors. Results: The prevalence of low back pain reported last year was 50.2% (95% CI: 46.6, 53.8), and the last week 32.3% (95% CI: 28.9, 35.6). Was association among low back pain and females (p-value = 0.031), older age, lower education, altered sleep and overweight, the adjusted model found that people over the age of 45 years (45 to 59.9 years, OR = 13.1 [1.72-98.5] and ≥ 60 years, OR = 9.10 [1.15-71.7]), with some alteration of sleep (OR = 3.21 [1.84-5.61]) and obese (OR = 2.33 [1:26 to 4:33]) seems to be a risk group for low back pain. Conclusion: The prevalence of low back pain is high and obese people aged over 45 years, with any sleep disturbance are a group at higher risk for low back pain.

Prediction of soil shear strength in agricultural and natural environments of the Brazilian Cerrado

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Cointegration: Bayesian Significance Test

To estimate causal relationships, time series econometricians must be aware of spurious correlation, a problem first mentioned by Yule (1926). To deal with this problem, one can work either with differenced series or multivariate models: VAR (VEC or VECM) models. These models usually include at least one cointegration relation. Although the Bayesian literature on VAR/VEC is quite advanced, Bauwens et al. (1999) highlighted that "the topic of selecting the cointegrating rank has not yet given very useful and convincing results". The present article applies the Full Bayesian Significance Test (FBST), especially designed to deal with sharp hypotheses, to cointegration rank selection tests in VECM time series models. It shows the FBST implementation using both simulated and available (in the literature) data sets. As illustration, standard non informative priors are used.

Do Tobacco and Alcohol Modify Protective Effects of Diet on Oral Carcinogenesis?

Recent systematic reviews concluded that the frequent consumption of fruits and vegetables is inversely associated with the risk of oral cancer. We assessed this association, specifically comparing results obtained to nonsmokers and smokers, as well to nondrinkers and drinkers. We conducted a case-control study involving 296 patients with oral squamous cell carcinoma (cases) attended in 3 major hospitals of Sao Paulo, Brazil, paired with 296 controls, recruited from outpatient units of the same hospitals. Multivariate models assessed the effect of fruits and salads according to smoking and drinking. The intake of fruit was associated with the prevention of the disease in the specific assessment among light [odds ratio (OR) = 0.46; 95% confidence interval (CI) = 0.27-0.78) and heavy (OR = 0.30; 95% CI = 0.14-0.65) smokers. The same was observed for vegetables consumption. For nonsmokers, no fruit (OR = 50; 95% CI = 0.22-1.12) or vegetable (for tomato, OR = 0.53; 95% CI = 0.31-0.93) was associated with reduced risk of oral and oropharyngeal cancer. Similar results were found in the stratified analysis according to drinking status with OR = 0.51 (95% CI = 0.30-0.87) and 0.18 for fruits (95% CI = 0.07-0.45), respectively, for light and heavy drinkers. This observation suggests that the protective effect of fruit and salad intake may modulate the deleterious effects from tobacco and alcohol.

Second-trimester soft markers: relation to first-trimester nuchal translucency in unaffected pregnancies

Objective Genetic sonography following first-trimester combined screening appears to increase substantially detection rates for Down syndrome but it relies on the unproved assumption of independence between these tests. In this study we aimed to investigate the relationship between first-trimester nuchal translucency (NT) and a series of second-trimester soft markers and structural defects in unaffected pregnancies. Methods NT measurement in the first trimester was followed by second-trimester scan (18 to 23 + 6 weeks) including examination for three categorical markers (intracardiac echogenic foci, hyperechogenic bowel and structural defects) and measurement of nasal bone length, nuchal-fold thickness, femur length, humerus length, renal pelvis diameter and prenasal thickness. All continuous variables were expressed in multiples of the median (MoM) for gestation and correlation coefficients between log-transformed NT and second-trimester variables were calculated. In addition, frequencies of soft markers and structural defects in cases with increased NT were compared to those with normal NT, using MoM cut-offs. Results In a dataset of 1970 cases, NT was significantly correlated (P < 0.05) with all second-trimester continuous variables, the correlation being strongest for nuchal-fold thickness (r = 0.10). There was a higher frequency of cases with second-trimester nuchal-fold thickness above the 97.5th centile (10.7 vs. 2.2%) and hyperechogenic bowel (2.4 vs. 0.1%) in cases with increased NT. Conclusions Straightforward reassessment of risk using likelihood ratios derived from the second-trimester genetic sonogram might lead to inaccurate estimates. Multivariate models using continuous second-trimester variables might be preferable in sequential screening strategies. Copyright. 2012 ISUOG. Published by John Wiley & Sons, Ltd.

Severe lower respiratory tract infection in infants and toddlers from a non-affluent population: viral etiology and co-detection as risk factors

Abstract Background Lower respiratory tract infection (LRTI) is a major cause of pediatric morbidity and mortality, especially among non-affluent communities. In this study we determine the impact of respiratory viruses and how viral co-detections/infections can affect clinical LRTI severity in children in a hospital setting. Methods Patients younger than 3 years of age admitted to a tertiary hospital in Brazil during the months of high prevalence of respiratory viruses had samples collected from nasopharyngeal aspiration. These samples were tested for 13 different respiratory viruses through real-time PCR (rt-PCR). Patients were followed during hospitalization, and clinical data and population characteristics were collected during that period and at discharge to evaluate severity markers, especially length of hospital stay and oxygen use. Univariate regression analyses identified potential risk factors and multivariate logistic regressions were used to determine the impact of specific viral detections as well as viral co-detections in relation to clinical outcomes. Results We analyzed 260 episodes of LRTI with a viral detection rate of 85% (n = 222). Co-detection was observed in 65% of all virus-positive episodes. The most prevalent virus was Respiratory Syncytial Virus (RSV) (54%), followed by Human Metapneumovirus (hMPV) (32%) and Human Rhinovirus (HRV) (21%). In the multivariate models, infants with co-detection of HRV + RSV stayed 4.5 extra days (p = 0.004), when compared to infants without the co-detection. The same trends were observed for the outcome of days of supplemental oxygen use. Conclusions Although RSV remains as the main cause of LRTI in infants our study indicates an increase in the length of hospital stay and oxygen use in infants with HRV detected by RT-PCR compared to those without HRV. Moreover, one can speculate that when HRV is detected simultaneously with RSV there is an additive effect that may be reflected in more severe clinical outcome. Also, our study identified a significant number of children infected by recently identified viruses, such as hMPV and Human Bocavirus (HBov), and this is a novel finding for poor communities from developing countries.

Modelli non lineari statici e dinamici su dati microeconomici: analisi delle condizioni finanziarie delle famiglie italiane

The thesis studies the economic and financial conditions of Italian households, by using microeconomic data of the Survey on Household Income and Wealth (SHIW) over the period 1998-2006. It develops along two lines of enquiry. First it studies the determinants of households holdings of assets and liabilities and estimates their correlation degree. After a review of the literature, it estimates two non-linear multivariate models on the interactions between assets and liabilities with repeated cross-sections. Second, it analyses households financial difficulties. It defines a quantitative measure of financial distress and tests, by means of non-linear dynamic probit models, whether the probability of experiencing financial difficulties is persistent over time. Chapter 1 provides a critical review of the theoretical and empirical literature on the estimation of assets and liabilities holdings, on their interactions and on households net wealth. The review stresses the fact that a large part of the literature explain households debt holdings as a function, among others, of net wealth, an assumption that runs into possible endogeneity problems. Chapter 2 defines two non-linear multivariate models to study the interactions between assets and liabilities held by Italian households. Estimation refers to a pooling of cross-sections of SHIW. The first model is a bivariate tobit that estimates factors affecting assets and liabilities and their degree of correlation with results coherent with theoretical expectations. To tackle the presence of non normality and heteroskedasticity in the error term, generating non consistent tobit estimators, semi-parametric estimates are provided that confirm the results of the tobit model. The second model is a quadrivariate probit on three different assets (safe, risky and real) and total liabilities; the results show the expected patterns of interdependence suggested by theoretical considerations. Chapter 3 reviews the methodologies for estimating non-linear dynamic panel data models, drawing attention to the problems to be dealt with to obtain consistent estimators. Specific attention is given to the initial condition problem raised by the inclusion of the lagged dependent variable in the set of explanatory variables. The advantage of using dynamic panel data models lies in the fact that they allow to simultaneously account for true state dependence, via the lagged variable, and unobserved heterogeneity via individual effects specification. Chapter 4 applies the models reviewed in Chapter 3 to analyse financial difficulties of Italian households, by using information on net wealth as provided in the panel component of the SHIW. The aim is to test whether households persistently experience financial difficulties over time. A thorough discussion is provided of the alternative approaches proposed by the literature (subjective/qualitative indicators versus quantitative indexes) to identify households in financial distress. Households in financial difficulties are identified as those holding amounts of net wealth lower than the value corresponding to the first quartile of net wealth distribution. Estimation is conducted via four different methods: the pooled probit model, the random effects probit model with exogenous initial conditions, the Heckman model and the recently developed Wooldridge model. Results obtained from all estimators accept the null hypothesis of true state dependence and show that, according with the literature, less sophisticated models, namely the pooled and exogenous models, over-estimate such persistence.

Charakterisierung von plasmafunktionalisierten Oberflächen mittels ToF-SIMS und multivariaten Analysemethoden

Die grundlegenden Prinzipien und Möglichkeiten der Oberflächencharakterisierung mittels ToF-SIMS (Flugzeit-Sekundärionen Massenspektrometrie) werden an ausgewählten Beispielen aus einem aktuell laufenden und vom BMBF geförderten Verbundforschungsprojekt (Fkz: 03N8022A) zum Thema Nanofunktionalisierung von Grenzflächen vorgestellt. Ein Schwerpunkt innerhalb des Projekts stellen die nichtgeschlossenen Schichtsysteme dar, die entweder über Domänenstrukturen oder einer definierten Einzelfunktionalisierung neuartige funktionelle Oberflächen bereitstellen. Mithilfe der sehr oberflächensensitiven ToF-SIMS Methode sowie der Möglichkeit einer graphischen Darstellung lateraler Molekülionenverteilungen auf funktionalisierten Oberflächen können Informationen über Struktur und Belegungsdichte der Funktionsschicht gewonnen werden. Die Kombination des ToF-SIMS Experimentes und eines multivariaten Algorithmus (partial least squares, PLS) liefert eine interessante Möglichkeit zur quantitativen und simultanen Bestimmung von Oberflächeneigenschaften (Element- und molekulare Konzentrationen sowie Kontaktwinkelwerte). Da das ToF-SIMS Spektrum einer plasmafunktionalisierten Oberfläche im Allgemeinen eine Vielzahl unterschiedlicher Fragmentsignale enthält, lässt eine einfache eindimensionale Korrelation (z.B. CF3 - Fragmentintensität ßà CF3-Konzentration) den größten Teil der im Spektrum prinzipiell enthaltenen Information unberücksichtigt. Aufgrund der großen Anzahl von atomaren und molekularen Signalen, die repräsentativ für die chemische Struktur der analysierten Oberflächen sind, ist es sinnvoll, diese Fülle von Informationen zur Quantifizierung der Oberflächeneigenschaften (Elementkonzentrationen, Kontaktwinkel etc.) zu verwenden. Zusätzlich ermöglicht diese Methode eine quantitative Bestimmung der Oberflächeneigenschaften auf nur µm-großen Bereichen. Das ist vorteilhaft für Untersuchungen chemisch strukturierter Oberflächen, da die Größe der Strukturierung für viele Anwendungen in einem Bereich von mehreren µm liegt. Anhand eines Beispieles aus dem biologisch-medizinischen Fachgebiet, soll der erfolgreiche Einsatz multivariater Modelle aufgezeigt werden. In diesem Experiment wurden menschlichen Bindegewebs- (Fibroblasten) und Pankreaszellen auf plasmafunktionalisiserten Oberflächen kultiviert, um die Beeinflussung der Funktionalisierung auf das Zellwachstum zu untersuchen. Die plasmabehandelten Oberflächen wurden durch die Verwendung von TEM-Gittern mit µm-großen Öffnungen chemisch strukturiert und das Wachstumsverhalten der Zellen beobachtet. Jedem dieser µm-großen Bereiche können mithilfe der multivariaten Modelle quantitative Größen zugeordnet werden (Konzentrationen und Kontaktwinkelwerte), die zur Interpretation des Wachstumsverhaltens der Zellen beitragen.

Screening and prediction of erosive potential

The literature on the erosive potential of drinks and other products is summarised, and aspects of the conduct of screening tests as well as possible correlations of the erosive potential with various solution parameters are discussed. The solution parameters that have been suggested as important include pH, acid concentration (with respect to buffer capacity and concentration of undissociated acid), degree of saturation, calcium and phosphate concentrations, and inhibitors of erosion. Based on the available data, it is concluded that the dominant factor in erosion is pH. The effect of buffer capacity seems to be pH dependent. The degree of saturation probably has a non-linear relationship with erosion. While calcium at elevated concentrations is known to reduce erosion effectively, it is not known whether it is important at naturally occurring concentrations. Fluoride at naturally occurring concentrations is inversely correlated with erosive potential, but phosphate is probably not. Natural plant gums, notably pectin, do not inhibit erosion, so they are unlikely to interfere with the prediction of erosive potential. The non-linearity of some solution factors and interactions with pH need to be taken into account when developing multivariate models for predicting the erosive potential of different solutions. Finally, the erosive potential of solutions towards enamel and dentine might differ.

The influence of the surgeon's and the hospital's caseload on survival and local recurrence after colorectal cancer surgery

BACKGROUND: Past studies have identified surgeon- and institution- related characteristics as prognostic factors in colorectal cancer surgery. The present work assesses the influence of the surgeon's and the hospital's caseload on long-term results of colorectal cancer surgery. METHODS: The data on 2706 patients from 2, randomized, colorectal cancer trials (Swiss Group for Clinical Cancer Research [SAKK] 40/81, SAKK 40/87) investigating adjuvant intraportal and systemic chemotherapy and 1 concurrent registration study (SAKK 40/88) were reviewed. A first analysis included 1809 eligible, nonmetastatic patients from all 3 studies. A subsequent subgroup analysis included 915 eligible patients from both randomized trials. Overall survival (OS), disease-free survival (DFS), and local recurrence (LR) were analyzed in multivariate models taking into account the possible effect of clustering. The main potential covariates were surgeon's annual caseload (>5 operations/year vs < or =5 operations/year), hospital's annual caseload (>26 operations/year vs < or =26 operations/year), tumor site, T stage, and nodal status. RESULTS: Primary analysis of all 3 studies combined found a high surgeon's caseload to be positively associated with OS (P = .025) and marginally with DFS (P = .058). Separate analysis for each trial, however, showed that a high surgeon's caseload was beneficial for outcome in both randomized trials but not in the registration study. A subgroup analysis of 915 patients with 376 rectal and 539 colonic primaries from both randomized trials, therefore, was performed. Neither age, gender, year of operation, adjuvant chemotherapy (intraportal vs systemic vs operation alone), hospital academic status (university vs non-university), training status of the surgeon (certified surgeon vs surgeon-in-training), nor inclusion in 1 of the 2 randomized trials (SAKK 40/81 vs SAKK 40/87) was a significant predictor of outcome. However, both high surgeon's and high hospital's annual caseloads were independent, beneficial prognostic factors for OS (P = .0003, P = .044) and DFS (P = .0008, P = .020), and marginally significant factors for LR (P = .057, P = .055). CONCLUSIONS: High surgeon's and hospital's annual caseloads are strong, independent prognostic factors for extending overall and disease-free survival and reducing the rate of local recurrence in 2 randomized colorectal cancer trials.