Agreement between direct, oscillometric and Doppler ultrasound blood pressures using three different cuff positions in anesthetized dogs

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

Estimates of covariance functions for growth from birth to 630 days of age in Nelore cattle

Weight records of Brazilian Nelore cattle, from birth to 630 d of age, recorded every 3 mo, were analyzed using random regression models. Independent variables were Legendre polynomials of age at recording. The model of analysis included contemporary groups as fixed effects and age of dam as a linear and quadratic covariable. Mean trends were modeled through a cubic regression on orthogonal polynomials of age. Up to four sets of random regression coefficients were fitted for animals' direct and maternal, additive genetic, and permanent environmental effects. Changes in measurement error variances with age were modeled through a variance function. Orders of polyno-mial fit from three to six were considered, resulting in up to 77 parameters to be estimated. Models fitting random regressions modeled the pattern of variances in the data adequately, with estimates similar to those from corresponding univariate analysis. Direct heritability estimates decreased after birth and tended to be lowest at ages at which maternal effect estimates tended to be highest. Maternal heritability estimates increased after birth to a peak around 110 to 120 d of age and decreased thereafter. Additive genetic direct correlation estimates between weights at standard ages (birth, weaning, yearling, and final weight) were moderate to high and maternal genetic and environmental correlations were consistently high. © 2001 American Society of Animal Science. All rights reserved.

Análise de perdas na rede de distribuição de água em um subsetor da cidade de Presidente Prudente - SP

Pós-graduação em Engenharia Civil - FEIS

Comparação entre métodos de estimativa da evapotranspiração de referência (ETo) em regiões citrícolas paulistas

As regiões escolhidas para o estudo são importantes no cenário citrícola irrigado, tanto em expansão quanto em atuação. Os dados meteorológicos utilizados para as estimativas são integrantes do banco de dados climáticos do software IRRIPLUS®. Com este software, estimou-se a evapotranspiração de referência (ETo) diária, utilizando as metodologias propostas por Penman-Monteith (EToPM), Hargreaves & Samani (EToHG) e Blaney-Criddle-FAO (EToBC), para o período de um ano. O objetivo deste estudo foi comparar os métodos de estimativa com EToPM, utilizando parâmetros de regressão (β0, β1), coeficiente de determinação (r²), e correlação (r), estimativa do erro-padrão (SEE), índices de concordância (d) e confiança (c). Os resultados indicam tendência de EToHG à superestimativa dos valores de ETo, exceto na região de Jaú, e subestimativa por EToBC, para todas as regiões estudadas. Nos valores mensais de ETo, os três métodos apresentam a mesma distribuição. O método de EToHG apresenta-se como uma excelente alternativa na estimativa de consumo de água pela cultura.

A new sampling strategy for the Shewhart control chart monitoring a process with wandering mean

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Estimates of covariance functions for growth from birth to 630 days of age in Nelore cattle

Weight records of Brazilian Nelore cattle, from birth to 630 d of age, recorded every 3 mo, were analyzed using random regression models. Independent variables were Legendre polynomials of age at recording. The model of analysis included contemporary groups as fixed effects and age of dam as a linear and quadratic covariable. Mean trends were modeled through a cubic regression on orthogonal polynomials of age. Up to four sets of random regression coefficients were fitted for animals' direct and maternal, additive genetic, and permanent environmental effects. Changes in measurement error variances with age were modeled through a variance function. Orders of polynomial fit from three to six were considered, resulting in up to 77 parameters to be estimated. Models fitting random regressions modeled the pattern of variances in the data adequately, with estimates similar to those from corresponding univariate analysis. Direct heritability estimates decreased after birth and tended to be lowest at ages at which maternal effect estimates tended to be highest. Maternal heritability estimates increased after birth to a peak around 110 to 120 d of age and decreased thereafter. Additive genetic direct correlation estimates between weights at standard ages (birth, weaning, yearling, and final weight) were moderate to high and maternal genetic and environmental correlations were consistently high.

Alternative distributions to estimate usual intake of nutrients for groups

When assessing food intake patterns in groups of individuals, a major problem is finding usual intake distribution. This study aimed at searching for a probability distribution to estimate the usual intake of nutrients using data from a cross-sectional investigation on nutrition students from a public university in São Paulo state, Brazil. Data on 119 women aged 19 to 30 years old were used. All women answered a questionnaire about their lifestyle, diet and demographics. Food intake was evaluated from a non-consecutive three-day 24-hour food record. Different probability distributions were tested for vitamins C and E, panthotenic acid, folate, zinc, copper and calcium where data normalization was not possible. Empirical comparisons were performed, and inadequacy prevalence was calculated by comparing with the NRC method. It was concluded that if a more realistic distribution for usual intake is found, results can be more accurate as compared to those achieved by other methods.

Qualidade das medidas antropométricas produzidas em unidades de atenção básica à saúde da região de Botucatu-SP, Brasil

The aim of this study was to evaluate the quality of weight measurements produced in Primary Health Care Centers in Botucatu and surroundings. 14 Health Care Centers were included, all of them located in four towns in the area of Botucatu (4,555; 5,656; 18,761 and 128,397 inhabitants). General conditions and scale calibration conditions found in those Health Care Centers were evaluated. In order to evaluate the weight accuracy obtained by the local team, 10 adult users of each Center were addressed by the rater during the service routine in order to get a new weight evaluation, immediately after the measurement made by the team. The statistic method applied for checking the weight measurement held in the Heath Care Center and the scales accuracy was the measurement error technique (MET). The results have showed that out of 19 scales, 6 of them overestimated the weight by 50 grams, 1 of them underestimated the weight by 200 grams and the others were accurate. Evaluated as a group, the result of the scale MET was 44.3g. Regarding the conformity of the measures obtained by the MET of the adults weighing in the Health Care Centers compared to the ones obtained by the researcher, the expected result was obtained in only one Center (< 100g). The results have showed data compromise, rather due to lack of health team training than due to the conditions of the equipment used for the measurement.

Cross-cultural adaptation and assessment of the reliability and validity of the Core Outcome Measures Index (COMI) for the Brazilian-Portuguese language

The use of patient-orientated questionnaires is of utmost importance in assessing the outcome of spine surgery. Standardisation, using a common set of outcome measures, is essential to aid comparisons across studies/in registries. The Core Outcome Measures Index (COMI) is a short, multidimensional outcome instrument validated for patients with spinal disorders. This study aimed to produce a Brazilian-Portuguese version of the COMI. A cross-cultural adaptation of the COMI into Brazilian-Portuguese was carried out using established guidelines. 104 outpatients with chronic LBP (> 3 months) were recruited from a Public Health Spine Medical Care Centre. They completed a questionnaire booklet containing the newly translated COMI, and other validated symptom-specific questionnaires: Oswestry Disability Index (ODI) and Roland Morris disability scale (RM), and a pain visual analogue scale. All patients completed a second questionnaire within 7-10 days to assess reproducibility. The COMI summary score displayed minimal floor and ceiling effects. On re-test, the responses for each individual domain of the COMI were within 1 category in 98% patients for the domain 'function', 96% for 'symptom-specific well-being', 97% for 'general quality of life', 99% for 'social disability' and 100% for 'work disability'. The intraclass correlation coefficients (ICC2,1) for COMI pain and COMI summary scores were 0.91-0.96, which compared favourably with the corresponding values for the RM (ICC, 0.99) and ODI (ICC, 0.98). The standard error of measurement for the COMI was 0.6, giving a "minimum detectable change" (MDC95%) of approximately 1.7 points i.e., the minimum change to be considered "real change" beyond measurement error. The COMI scores correlated as hypothesised (Rho, 0.4-0.8) with the other symptom-specific questionnaires. The reproducibility of the Brazilian-Portuguese version of the COMI was comparable to that of other language versions. The COMI scores correlated in the expected manner with existing but longer symptom-specific questionnaires suggesting good convergent validity for the COMI. The Brazilian-Portuguese COMI represents a valuable tool for Brazilian study-centres in future multicentre clinical studies and surgical registries.

Diagnosis and Fault detection in Electrical Machines and Drives based on Advanced Signal Processing Techniques

In the present thesis, a new methodology of diagnosis based on advanced use of time-frequency technique analysis is presented. More precisely, a new fault index that allows tracking individual fault components in a single frequency band is defined. More in detail, a frequency sliding is applied to the signals being analyzed (currents, voltages, vibration signals), so that each single fault frequency component is shifted into a prefixed single frequency band. Then, the discrete Wavelet Transform is applied to the resulting signal to extract the fault signature in the frequency band that has been chosen. Once the state of the machine has been qualitatively diagnosed, a quantitative evaluation of the fault degree is necessary. For this purpose, a fault index based on the energy calculation of approximation and/or detail signals resulting from wavelet decomposition has been introduced to quantify the fault extend. The main advantages of the developed new method over existing Diagnosis techniques are the following: - Capability of monitoring the fault evolution continuously over time under any transient operating condition; - Speed/slip measurement or estimation is not required; - Higher accuracy in filtering frequency components around the fundamental in case of rotor faults; - Reduction in the likelihood of false indications by avoiding confusion with other fault harmonics (the contribution of the most relevant fault frequency components under speed-varying conditions are clamped in a single frequency band); - Low memory requirement due to low sampling frequency; - Reduction in the latency of time processing (no requirement of repeated sampling operation).

Educational mismathc in Italian an European labour markets (starting from the UK)

The present doctoral thesis is structured as a collection of three essays. The first essay, “SOC(HE)-Italy: a classification for graduate occupations” presents the conceptual basis, the construction, the validation and the application to the Italian labour force of the occupational classification termed SOC(HE)-Italy. I have developed this classification under the supervision of Kate Purcell during my period as a visiting research student at the Warwick Institute for Emplyment Research. This classification links the constituent tasks and duties of a particular job to the relevant knowledge and skills imparted via Higher Education (HE). It is based onto the SOC(HE)2010, an occupational classification first proposed by Kate Purcell in 2013, but differently constructed. In the second essay “Assessing the incidence and wage effects of overeducation among Italian graduates using a new measure for educational requirements” I utilize this classification to build a valid and reliable measure for job requirements. The lack of an unbiased measure for this dimension constitutes one of the major constraints to achieve a generally accepted measurement of overeducation. Estimations of overeducation incidence and wage effects are run onto AlmaLaurea data from the survey on graduates career paths. I have written this essay and obtained these estimates benefiting of the help and guidance of Giovanni Guidetti and Giulio Pedrini. The third and last essay titled “Overeducation in the Italian labour market: clarifying the concepts and addressing the measurement error problem” addresses a number of theoretical issues concerning the concepts of educational mismatch and overeducation. Using Istat data from RCFL survey I run estimates of the ORU model for the whole Italian labour force. In my knowledge, this is the first time ever such model is estimated on such population. In addition, I adopt the new measure of overeducation based onto the SOC(HE)-Italy classification.

Body Mass Index and Cancer Risk: The Evidence for Causal Association

Increased body mass index (BMI), as an approximation of body adiposity, is a risk factor for developing several adult malignancies. To quantify these risks, we reported a comprehensive systematic review (Lancet 2008; 371: 569-78) of prospective observational studies determining associations between BMI and risk of incident cancer for 20 cancer types. We demonstrated that associations are: (i) sex-specific; (ii) exist for a wider range of malignancies than previously thought; and (iii) are broadly consistent across geographic populations. In the present paper, we tested these data against the Bradford-Hill criteria of causal association, and argue that the available data support strength of association, consistency, specificity, temporality, biological gradient, plausibility, coherence and probably analogy. However, the experimental evidence supporting reversibility is currently lacking, though indirect evidence from longitudinal data in cohort studies and long-term follow-up post-bariatric surgery is emerging. We additionally assessed these data against appropriate adjustment for available confounding factors; measurement error and study design; and residual confounding; and found lack of alternative explanations. We conclude that there is considerable evidence to support a causal association between BMI and risk for many cancer types, but in order to establish the role of weight control in cancer prevention, there is a need to develop trial frameworks in which to better test reversibility.

The Lower Limb Functional Index: development and clinimetric properties

Background Existing lower-limb, region-specific, patient-reported outcome measures have clinimetric limitations, including limitations in psychometric characteristics (eg, lack of internal consistency, lack of responsiveness, measurement error) and the lack of reported practical and general characteristics. A new patient-reported outcome measure, the Lower Limb Functional Index (LLFI), was developed to address these limitations. Objective The purpose of this study was to overcome recognized deficiencies in existing lower-limb, region-specific, patient-reported outcome measures through: (1) development of a new lower-extremity outcome scale (ie, the LLFI) and (2) evaluation of the clinimetric properties of the LLFI using the Lower Extremity Functional Scale (LEFS) as a criterion measure. Design This was a prospective observational study. Methods The LLFI was developed in a 3-stage process of: (1) item generation, (2) item reduction with an expert panel, and (3) pilot field testing (n=18) for reliability, responsiveness, and sample size requirements for a larger study. The main study used a convenience sample (n=127) from 10 physical therapy clinics. Participants completed the LLFI and LEFS every 2 weeks for 6 weeks and then every 4 weeks until discharge. Data were used to assess the psychometric, practical, and general characteristics of the LLFI and the LEFS. The characteristics also were evaluated for overall performance using the Measurement of Outcome Measures and Bot clinimetric assessment scales. Results The LLFI and LEFS demonstrated a single-factor structure, comparable reliability (intraclass correlation coefficient [2,1]=.97), scale width, and high criterion validity (Pearson r=.88, with 95% confidence interval [CI]). Clinimetric performance was higher for the LLFI compared with the LEFS on the Measurement of Outcome Measures scale (96% and 95%, respectively) and the Bot scale (100% and 83%, respectively). The LLFI, compared with the LEFS, had improved responsiveness (standardized response mean=1.75 and 1.64, respectively), minimal detectable change with 90% CI (6.6% and 8.1%, respectively), and internal consistency (α=.91 and .95, respectively), as well as readability with reduced user error and completion and scoring times. Limitations Limitations of the study were that only participants recruited from outpatient physical therapy clinics were included and that no specific conditions or diagnostic subgroups were investigated. Conclusion The LLFI demonstrated sound clinimetric properties. There was lower response error, efficient completion and scoring, and improved responsiveness and overall performance compared with the LEFS. The LLFI is suitable for assessment of lower-limb function.

First middle-atmospheric zonal wind profile measurements with a new ground-based microwave Doppler-spectro-radiometer

We report on the wind radiometer WIRA, a new ground-based microwave Doppler-spectro-radiometer specifically designed for the measurement of middle-atmospheric horizontal wind by observing ozone emission spectra at 142.17504 GHz. Currently, wind speeds in five levels between 30 and 79 km can be retrieved which makes WIRA the first instrument able to continuously measure horizontal wind in this altitude range. For an integration time of one day the measurement error on each level lies at around 25 m s−1. With a planned upgrade this value is expected to be reduced by a factor of 2 in the near future. On the altitude levels where our measurement can be compared to wind data from the European Centre for Medium-Range Weather Forecasts (ECMWF) very good agreement in the long-term statistics as well as in short time structures with a duration of a few days has been found. WIRA uses a passive double sideband heterodyne receiver together with a digital Fourier transform spectrometer for the data acquisition. A big advantage of the radiometric approach is that such instruments can also operate under adverse weather conditions and thus provide a continuous time series for the given location. The optics enables the instrument to scan a wide range of azimuth angles including the directions east, west, north, and south for zonal and meridional wind measurements. The design of the radiometer is fairly compact and its calibration does not rely on liquid nitrogen which makes it transportable and suitable for campaign use. WIRA is conceived in a way that it can be operated remotely and does hardly require any maintenance. In the present paper, a description of the instrument is given, and the techniques used for the wind retrieval based on the determination of the Doppler shift of the measured atmospheric ozone emission spectra are outlined. Their reliability was tested using Monte Carlo simulations. Finally, a time series of 11 months of zonal wind measurements over Bern (46°57′ N, 7°26′ E) is presented and compared to ECMWF wind data.

A Data-Analytic Strategy for Protein-Biomarker Discovery: Profiling of High-Dimensional Proteomic Data for Cancer Detection

With recent advances in mass spectrometry techniques, it is now possible to investigate proteins over a wide range of molecular weights in small biological specimens. This advance has generated data-analytic challenges in proteomics, similar to those created by microarray technologies in genetics, namely, discovery of "signature" protein profiles specific to each pathologic state (e.g., normal vs. cancer) or differential profiles between experimental conditions (e.g., treated by a drug of interest vs. untreated) from high-dimensional data. We propose a data analytic strategy for discovering protein biomarkers based on such high-dimensional mass-spectrometry data. A real biomarker-discovery project on prostate cancer is taken as a concrete example throughout the paper: the project aims to identify proteins in serum that distinguish cancer, benign hyperplasia, and normal states of prostate using the Surface Enhanced Laser Desorption/Ionization (SELDI) technology, a recently developed mass spectrometry technique. Our data analytic strategy takes properties of the SELDI mass-spectrometer into account: the SELDI output of a specimen contains about 48,000 (x, y) points where x is the protein mass divided by the number of charges introduced by ionization and y is the protein intensity of the corresponding mass per charge value, x, in that specimen. Given high coefficients of variation and other characteristics of protein intensity measures (y values), we reduce the measures of protein intensities to a set of binary variables that indicate peaks in the y-axis direction in the nearest neighborhoods of each mass per charge point in the x-axis direction. We then account for a shifting (measurement error) problem of the x-axis in SELDI output. After these pre-analysis processing of data, we combine the binary predictors to generate classification rules for cancer, benign hyperplasia, and normal states of prostate. Our approach is to apply the boosting algorithm to select binary predictors and construct a summary classifier. We empirically evaluate sensitivity and specificity of the resulting summary classifiers with a test dataset that is independent from the training dataset used to construct the summary classifiers. The proposed method performed nearly perfectly in distinguishing cancer and benign hyperplasia from normal. In the classification of cancer vs. benign hyperplasia, however, an appreciable proportion of the benign specimens were classified incorrectly as cancer. We discuss practical issues associated with our proposed approach to the analysis of SELDI output and its application in cancer biomarker discovery.