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Background: Research using linked routine population-based data collected for non-research purposes has increased in recent years because they are a rich and detailed source of information. The objective of this study is to present an approach to prepare and link data from administrative sources in a middle-income country, to estimate its quality and to identify potential sources of bias by comparing linked and non-linked individuals.Methods: We linked two administrative datasets with data covering the period 2001 to 2015, using maternal attributes (name, age, date of birth, and municipally of residence) from Brazil: live birth information system and the 100 Million Brazilian Cohort (created using administrative records from over 114 million individuals whose families applied for social assistance via the Unified Register for Social Programmes) implementing an in house developed linkage tool CIDACS-RL. We then estimated the proportion of highly probably link and examined the characteristics of missed-matches to identify any potential source of bias.Results: A total of 27,699,891 live births were submited to linkage with maternal information recorded in the baseline of the 100 Million Brazilian Cohort dataset of those, 16,447,414 (59.4%) children were found registered in the 100 Million Brazilian Cohort dataset. The proportion of highly probably link ranged from 39.3% in 2001 to 82.1% in 2014. A substantial improvement in the linkage after the introduction of maternal date of birth attribute, in 2011, was observed. Our analyses indicated a slightly higher proportion of missing data among missed matches and a higher proportion of people living in an urban area and self-declared as Caucasian among linked pairs when compared with non-linked sets.Discussion: We demonstrated that CIDACS-RL is capable of performing high quality linkage even with a limited number of common attributes, using indexation as a blocking strategy in larg e routine databases from a middle-income country. However, residual records occurred more among people under worse living conditions. The results presented in this study reinforce the need of evaluating linkage quality and when necessary to take linkage error into account for the analyses of any generated dataset. [ABSTRACT FROM AUTHOR]

Abstract The reliability and accuracy of a flowmeter depends on its installation conditions, as an improper installation may distort the end results. The objective of this work was to determine the errors obtained in an electromagnetic flowmeter of 100 mm diameter, installed in common real conditions, that is, not obeying the straight pipelines length recommended in flowmeter standards. To achieve this objective of the work, the electromagnetic flowmeter was installed in four different conditions: installed downstream of a 90° curve and downstream of two curves of 90°, both of short radius; downstream of a gate valve, openings of 100% and 50%. During the research, flow velocity profiles were obtained, with the purpose of evaluating the influence of profile distortion on the performance of the meter. The tests were carried out in the Laboratory of Hydraulics and Fluid Mechanics of FEC-Unicamp, Brazil, and the results are consubstantiated in comparative graphs, which demonstrate the influence of the velocity profile on the flowmeter response and accuracy for each setup bench. Highlights • The reliability and accuracy of a flowmeter depends on the installation conditions; • An improper installation may distort the results. • Deformed velocity profile affects measurement in electromagnetic flowmeters. • Installation has a strong influence on profile and a few less in measurement. • Meter evaluation should be executed case-by-case with field evaluation. [ABSTRACT FROM AUTHOR]

In this essay we discussed the resolutions of 198 students from four universities from State of Bahia related to combinatorics. In this study we aimed to identify what the students comprehended from combinatory concepts, if they knew how to differentiate conceptually array from combination, what strategies they employed to solve the questions and the errors made. We used works from error analysis and taxonomy of educational objectives as the theoretical foundations to the research. We developed a qualitative inquiry and the data analysis indicated that the university students from 3rd and 8th semesters still presented conceptual and procedural difficulties with respect to combinatorics. [ABSTRACT FROM AUTHOR]

This note acknowledges and corrects a programming error in our paper ' Inequality of Opportunity in Brazil' ( Review of Income and Wealth, 53(4), 585-618, 2007). Once the error is corrected, our bounds approach to the identification of individual model parameters in the presence of omitted variable biases is much less useful than indicated in the original paper. In the specific context of the measurement of inequality of opportunity, this implies that the decomposition of overall inequality of opportunity into direct and indirect effects is not reliable. However, the parametric approach introduced in our paper remains useful for obtaining a lower-bound estimate of overall ex-ante inequality of opportunity, as proposed by Ferreira and Gignoux (2011). [ABSTRACT FROM AUTHOR]

Abstract: Estimation of large area forest attributes, such as area of forest cover, from remote sensing-based maps is challenging because of image processing, logistical, and data acquisition constraints. In addition, techniques for estimating and compensating for misclassification and estimating uncertainty are often unfamiliar. Forest area for the state of Santa Catarina in southern Brazil was estimated from each of four satellite image-based land cover maps, and an independent estimate was obtained using observations of forest/non-forest for more than 1000 points assessed as part of the Santa Catarina Forest and Floristic Inventory. The latter data were also used as an accuracy assessment sample for evaluating the four maps. The map analyses consisted of identifying classification errors, constructing error matrices, calculating associated accuracy measures, estimating bias, and constructing 95% confidence intervals for proportion forest estimates using a model-assisted regression estimator. Overall accuracies for the maps ranged from 0.876 to 0.929. The standard errors of the estimates were all smaller than the standard error of the simple random sampling estimate by factors ranging from approximately1.23 to approximately 1.69. The model-assisted regression estimator lends itself to easy implementation for adjusting for estimated classification bias and for constructing confidence intervals. [Copyright &y& Elsevier]

The present study investigated direct and indirect methods using optical and acoustic instruments for the acquisition of information required to estimate the concentration of suspended particulate matter (SPM) in Vitória Bay, a shallow estuarine system in SE Brazil. The aim was to calibrate and compare the use of different instruments (OBS, ADP, and ADV) to estimate SPM concentration in the water column and near the bed. Concentration was determined by correlating filtered water samples with the optical and acoustic measurements. In general, the methodology proved tenable for the chosen shallow estuarine environment with low SPM concentration (<60 mg/L). Pearson's coefficient ranged from 0.75 to 0.85, when correlating measurements taken at three sampled depths. Differences in the correlation coefficient values showed that calibration at three depths (near the bed, mid-water column, and near the surface) was more effective than for surface samples alone, even in shallow (∼3 m deep) water. When calibration was attempted for concentration in the entire water column with samples at just one elevation, the correlation value was very low, thus increasing the error in estimating the SPM concentration. [ABSTRACT FROM AUTHOR]

Nonlinear adjustment toward long-run price equilibrium relationships in the sugar-ethanol-oil nexus in Brazil is examined. We develop generalized bivariate error correction models that allow for cointegration between sugar, ethanol, and oil prices, where dynamic adjustments are potentially nonlinear functions of the disequilibrium errors. A range of models are estimated using Bayesian Monte Carlo Markov Chain algorithms and compared using Bayesian model selection methods. The results suggest that the long-run drivers of Brazilian sugar prices are oil prices and that there are nonlinearities in the adjustment processes of sugar and ethanol prices to oil price but linear adjustment between ethanol and sugar prices. [ABSTRACT FROM AUTHOR]