Treatment of geophysical data as a non-stationary process

ABSTRACT: The Kalman-Bucy method is here analized and applied to the solution of a specific filtering problem to increase the signal message/noise ratio. The method is a time domain treatment of a geophysical process classified as stochastic non-stationary. The derivation of the estimator is based on the relationship between the Kalman-Bucy and Wiener approaches for linear systems. In the present work we emphasize the criterion used, the model with apriori information, the algorithm, and the quality as related to the results. The examples are for the ideal well-log response, and the results indicate that this method can be used on a variety of geophysical data treatments, and its study clearly offers a proper insight into modeling and processing of geophysical problems.

A utilização do Resource Description and Access (RDA) na criação de registros de autoridade para pessoas, famílias e entidades coletivas

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

Bias na Representação de Assunto: Uma Discussão de Oposições Binárias nos Functional Requirements for Subject Authority Data (FRSAD)

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

Interactive Correlation Environment (ICE) - A Statistical Web Tool for Data Collinearity Analysis

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

BtoxDB: a comprehensive database of protein structural data on toxin-antitoxin systems

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

The utility of open-access biodiversity information in representing anurans in the Brazilian Atlantic Forest and Cerrado

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

Access of children to the oral health service

Dental caries still affect a considerable proportion of children, however the epidemiological profile of oral diseases is changing, social inequalities cause different disease patterns. The same problems occur for the use of services, which damage those who are more susceptible to oral diseases in numerous ways. To verify the association between the variables: socioeconomic condition, oral health and access to dental services providing oral health care for preschool children. The study population consisted of 2,759 children up to 6 years-old. The clinical exams followed the World Health Organization (WHO) criteria. The data were collected using a self-applied questionnaire, answered by the carers of children, with questions about socioeconomic variables and access to dental services. In terms of social class, a majority of the subjects came from the middle socioeconomic level (babies, 84.7%; children, 82.8%). Babies who had caries, 48.4% and 67.2% of the children that had decayed teeth had access to dental service. There was a association between the variables: the reason for the last dental appointment and the parent's perception of the treatment need of their children (babies p=0.0004 and children p < 0.0001); the parent's perception of the treatment need of their children and the oral health condition (babies p=0.0008 and children p < 0.0001); access to dental services and oral health condition (babies p=0.0021 and children p < 0.0001). The majority of the population studied sought care from public dental service and was from the middle class.

The briefing in paleodesign: selection and arrangement of data for the reconstruction of Paleovertebrates

Representing visually the external appearance of an extinct animal requires, for a reasonably reliable and expressive reconstitution, a good compilation and arrangement of the scientific conclusions on the fossil findings. It is proposed in this work an initial model of a briefing to be applied in a paleodesign process of a paleovertebrate. Briefing can be understood as a gathering of all necessary data to perform a project. We point out what must be known about the relevant structures in order to access all the data and the importance of such information. It is expected that the present briefing suggested might be faced with flexibility, serving as a facilitating interface of the relation between paleoartists and paleontologists.

Improving IRT parameter estimates with small sample sizes: Evaluating the efficacy of a new data augmentation technique

The 3PL model is a flexible and widely used tool in assessment. However, it suffers from limitations due to its need for large sample sizes. This study introduces and evaluates the efficacy of a new sample size augmentation technique called Duplicate, Erase, and Replace (DupER) Augmentation through a simulation study. Data are augmented using several variations of DupER Augmentation (based on different imputation methodologies, deletion rates, and duplication rates), analyzed in BILOG-MG 3, and results are compared to those obtained from analyzing the raw data. Additional manipulated variables include test length and sample size. Estimates are compared using seven different evaluative criteria. Results are mixed and inconclusive. DupER augmented data tend to result in larger root mean squared errors (RMSEs) and lower correlations between estimates and parameters for both item and ability parameters. However, some DupER variations produce estimates that are much less biased than those obtained from the raw data alone. For one DupER variation, it was found that DupER produced better results for low-ability simulees and worse results for those with high abilities. Findings, limitations, and recommendations for future studies are discussed. Specific recommendations for future studies include the application of Duper Augmentation (1) to empirical data, (2) with additional IRT models, and (3) the analysis of the efficacy of the procedure for different item and ability parameter distributions.

Managing Large Data Sets Using Support Vector Machines

Hundreds of Terabytes of CMS (Compact Muon Solenoid) data are being accumulated for storage day by day at the University of Nebraska-Lincoln, which is one of the eight US CMS Tier-2 sites. Managing this data includes retaining useful CMS data sets and clearing storage space for newly arriving data by deleting less useful data sets. This is an important task that is currently being done manually and it requires a large amount of time. The overall objective of this study was to develop a methodology to help identify the data sets to be deleted when there is a requirement for storage space. CMS data is stored using HDFS (Hadoop Distributed File System). HDFS logs give information regarding file access operations. Hadoop MapReduce was used to feed information in these logs to Support Vector Machines (SVMs), a machine learning algorithm applicable to classification and regression which is used in this Thesis to develop a classifier. Time elapsed in data set classification by this method is dependent on the size of the input HDFS log file since the algorithmic complexities of Hadoop MapReduce algorithms here are O(n). The SVM methodology produces a list of data sets for deletion along with their respective sizes. This methodology was also compared with a heuristic called Retention Cost which was calculated using size of the data set and the time since its last access to help decide how useful a data set is. Accuracies of both were compared by calculating the percentage of data sets predicted for deletion which were accessed at a later instance of time. Our methodology using SVMs proved to be more accurate than using the Retention Cost heuristic. This methodology could be used to solve similar problems involving other large data sets.

Evaluating Measurement Invariance with Censored Ordinal Data: A Monte Carlo Comparison of Alternative Model Estimators and Scales of Measurement

Evaluations of measurement invariance provide essential construct validity evidence. However, the quality of such evidence is partly dependent upon the validity of the resulting statistical conclusions. The presence of Type I or Type II errors can render measurement invariance conclusions meaningless. The purpose of this study was to determine the effects of categorization and censoring on the behavior of the chi-square/likelihood ratio test statistic and two alternative fit indices (CFI and RMSEA) under the context of evaluating measurement invariance. Monte Carlo simulation was used to examine Type I error and power rates for the (a) overall test statistic/fit indices, and (b) change in test statistic/fit indices. Data were generated according to a multiple-group single-factor CFA model across 40 conditions that varied by sample size, strength of item factor loadings, and categorization thresholds. Seven different combinations of model estimators (ML, Yuan-Bentler scaled ML, and WLSMV) and specified measurement scales (continuous, censored, and categorical) were used to analyze each of the simulation conditions. As hypothesized, non-normality increased Type I error rates for the continuous scale of measurement and did not affect error rates for the categorical scale of measurement. Maximum likelihood estimation combined with a categorical scale of measurement resulted in more correct statistical conclusions than the other analysis combinations. For the continuous and censored scales of measurement, the Yuan-Bentler scaled ML resulted in more correct conclusions than normal-theory ML. The censored measurement scale did not offer any advantages over the continuous measurement scale. Comparing across fit statistics and indices, the chi-square-based test statistics were preferred over the alternative fit indices, and ΔRMSEA was preferred over ΔCFI. Results from this study should be used to inform the modeling decisions of applied researchers. However, no single analysis combination can be recommended for all situations. Therefore, it is essential that researchers consider the context and purpose of their analyses.

Evolution in access to fluoridated water in Sao Paulo State, Brazil, from the 1950s to the early 21st century

Access to fluoridated water is a known protective factor against dental caries. In 1974, fluoridation of the public water supply became mandatory by law in Brazil, resulting in improved coverage, especially in more developed regions of the country. Coverage increased across the country as a priority under the national oral health policy. This article systematizes information on the implementation and expansion of fluoridation in Sao Paulo State from 1956 to 2009, using secondary data from technical reports, official documents, and the Information System for Surveillance of Water Quality for Human Consumption (SISAGUA). In 2009, fluoridation covered 546 of 645 counties in Sao Paulo State (84.7%), reaching 85.1% of the total population and 93.5% of the population with access to the public water supply. The results indicate that fluoridation has been consolidated as part of State health policy. However, the challenge remains to implement and maintain fluoridation in 99 counties, benefiting 6.2 million inhabitants that are still excluded from this service.

VALIDATION OF THE LAND WATER STORAGE FROM GRAVITY RECOVERY AND CLIMATE EXPERIMENT (GRACE) WITH GAUGE DATA IN THE AMAZON BASIN

The Amazon basin is a region of constant scientific interest due to its environmental importance and its biodiversity and climate on a global scale. The seasonal variations in water volume are one of the examples of topics studied nowadays. In general, the variations in river levels depend primarily on the climate and physics characteristics of the corresponding basins. The main factor which influences the water level in the Amazon Basin is the intensive rainfall over this region as a consequence of the humidity of the tropical climate. Unfortunately, the Amazon basin is an area with lack of water level information due to difficulties in access for local operations. The purpose of this study is to compare and evaluate the Equivalent Water Height (Ewh) from GRACE (Gravity Recovery And Climate Experiment) mission, to study the connection between water loading and vertical variations of the crust due to the hydrologic. In order to achieve this goal, the Ewh is compared with in-situ information from limnimeter. For the analysis it was computed the correlation coefficients, phase and amplitude of GRACE Ewh solutions and in-situ data, as well as the timing of periods of drought in different parts of the basin. The results indicated that vertical variations of the lithosphere due to water mass loading could reach 7 to 5 cm per year, in the sedimentary and flooded areas of the region, where water level variations can reach 10 to 8 m.

Post-trial access to study medication: a Brazilian e-survey with major stakeholders in clinical research

Objectives To analyse the perspective of clinical research stakeholders concerning post-trial access to study medication. Methods Questionnaires and informed consents were sent through e-mail to 599 ethics committee (EC) members, 290 clinical investigators (HIV/AIDS and Diabetes) and 53 sponsors in Brazil. Investigators were also asked to submit the questionnaire to their research patients. Two reminders were sent to participants. Results The response rate was 21%, 20% and 45% in EC, investigators and sponsors' groups, respectively. 54 patients answered the questionnaire through their doctors. The least informative item in the consent form was how to obtain the study medication after trial. If a benefit were demonstrated in the study, 60% of research participants and 35% of EC answered that all patients should continue receiving study medication after trial; 43% of investigators believed the medication should be given to participants, and 40% to subjects who participated and benefited from treatment. For 50% of the sponsors, study medication should be assured to participants who had benefited from treatment. The majority of responders answered that medication should be provided free by sponsors; investigators and sponsors believed the medication should be kept until available in the public health sector; EC members said that the patient should keep the benefit; patients answered that benefits should be assured for life. Conclusions Due to the study limitations, the results cannot be generalised; however, the data can contribute to discussion of this complex topic through analysing the views of stakeholders in clinical research in Brazil.

Access to healthcare services for tuberculosis: analysis of patient satisfaction

Tuberculosis remains a pubic health challenge. Uncountable efforts are made to control the disease, and patient treatment and accessibility to healthcare can hinder reaching a cure. The objective of this article is to analyze the satisfaction of tuberculosis patients regarding tuberculosis control services. This is an epidemiological, prospective study, using both a quantitative and qualitative approach. Data were collected using a semi-structured questionnaire. Participants included 77 patients. The quantitative data were positively evaluated, and the qualitative data permitted an understanding of the patients' experience regarding their accessibility and treatment. Aspects such as the criteria for performing Directly Observed Treatment and the proximity of the healthcare facility to the patients' residence affected their satisfaction, which implies the need to reorganize healthcare services in order to provide more appropriate care to tuberculosis patients.