Intimate partner violence after the diagnosis of sexually transmitted diseases

OBJECTIVE To assess the prevalence and factors associated with intimate partner violence after the diagnosis of sexually transmitted diseases.METHODS This cross-sectional study was conducted in Fortaleza, CE, Northeastern Brazil, in 2012 and involved 221 individuals (40.3% male and 59.7% female) attended to at reference health care units for the treatment of sexually transmitted diseases. Data were collected using a questionnaire applied during interviews with each participant. A multivariate analysis with a logistic regression model was conducted using the stepwise technique. Only the variables with a p value < 0.05 were included in the adjusted analysis. The odds ratio (OR) with 95% confidence interval (CI) was used as the measure of effect.RESULTS A total of 30.3% of the participants reported experiencing some type of violence (27.6%, psychological; 5.9%, physical; and 7.2%, sexual) after the diagnosis of sexually transmitted disease. In the multivariate analysis adjusted to assess intimate partner violence after the revelation of the diagnosis of sexually transmitted diseases, the following variables remained statistically significant: extramarital relations (OR = 3.72; 95%CI 1.91;7.26; p = 0.000), alcohol consumption by the partner (OR = 2.16; 95%CI 1.08;4.33; p = 0.026), history of violence prior to diagnosis (OR = 2.87; 95%CI 1.44;5.69; p = 0.003), and fear of disclosing the diagnosis to the partner (OR = 2.66; 95%CI 1.32;5.32; p = 0.006).CONCLUSIONS Individuals who had extramarital relations, experienced violence prior to the diagnosis of sexually transmitted disease, feared disclosing the diagnosis to the partner, and those whose partner consumed alcohol had an increased likelihood of suffering violence. The high prevalence of intimate partner violence suggests that this population is vulnerable and therefore intervention efforts should be directed to them. Referral health care services for the treatment of sexually transmitted diseases can be strategic places to identify and prevent intimate partner violence.

Analysis of financial data series using fractional Fourier transform and multidimensional scaling

The goal of this study is the analysis of the dynamical properties of financial data series from worldwide stock market indexes during the period 2000–2009. We analyze, under a regional criterium, ten main indexes at a daily time horizon. The methods and algorithms that have been explored for the description of dynamical phenomena become an effective background in the analysis of economical data. We start by applying the classical concepts of signal analysis, fractional Fourier transform, and methods of fractional calculus. In a second phase we adopt the multidimensional scaling approach. Stock market indexes are examples of complex interacting systems for which a huge amount of data exists. Therefore, these indexes, viewed from a different perspectives, lead to new classification patterns.

Preservice teachers' knowledge on elementary geometry concepts

This text is based on a research, which is still in progress, whose main objective is to identify and understand what are the main difficulties of future mathematics teachers of basic education are, regarding their content knowledge in geometry in the context of the curricular unit of Geometry during their undergraduate degree. We chose a qualitative approach in the form of case study, in which data collection was done through observation, interviews, a diverse set of tasks, a diagnostic test and other documents. This paper focuses on the test given to prospective teachers at the beginning of the course. The preliminary analysis of the data points to a weak performance of preservice teachers in the test issues addressing elementary knowledge of Geometry

Decision-making on childhood vaccination by highly educated parents

OBJECTIVE To analyze the sociocultural aspects involved in the decision-making process of vaccination in upper-class and highly educated families.METHODS A qualitative approach based on in-depth interviews with 15 couples from the city of Sao Paulo, Southeastern Brazil, falling into three categories: vaccinators, late or selective vaccinators, and nonvaccinators. The interpretation of produced empirical material was performed through content analysis.RESULTS The study showed diverse and particular aspects surrounding the three groups’ decisions whether to vaccinate their children. The vaccinators’ decision to vaccinate their children was spontaneous and raised no questions. Most late or selective vaccinators experienced a wide range of situations that were instrumental in the decision to delay or not apply certain vaccines. The nonvaccinator’s decision-making process expressed a broader context of both criticism of hegemonic obstetric practices in Brazil and access to information transmitted via social networks and the internet. The data showed that the problematization of vaccines (culminating in the decision to not vaccinate their children) occurred in the context of humanized birth, was protagonized by women and was greatly influenced by health information from the internet.CONCLUSIONS Sociocultural aspects of the singular Brazilian context and the contemporary society were involved in the decision-making on children’s vaccination. Understanding this process can provide a real basis for a deeper reflection on health and immunization practices in Brazil in light of the new contexts and challenges of the world today.

Lesion detection performance in an anthropomorphic chest phantom: comparative analysis of low-dose CT data on two hybrid imaging systems

Introduction: multimodality environment; requirement for greater understanding of the imaging technologies used, the limitations of these technologies, and how to best interpret the results; dose optimization; introduction of new techniques; current practice and best practice; incidental findings, in low-dose CT images obtained as part of the hybrid imaging process, are an increasing phenomenon with advancing CT technology; resultant ethical and medico-legal dilemmas; understanding limitations of these procedures important when reporting images and recommending follow-up; free-response observer performance study was used to evaluate lesion detection in low-dose CT images obtained during attenuation correction acquisitions for myocardial perfusion imaging, on two hybrid imaging systems.

Occupational conditions and the risk of the use of amphetamines by truck drivers

OBJECTIVE To test whether the occupational conditions of professional truck drivers are associated with amphetamine use after demographic characteristics and ones regarding mental health and drug use are controlled for.METHODS Cross-sectional study, with a non-probabilistic sample of 684 male truck drivers, which was collected in three highways in Sao Paulo between years 2012 and 2013. Demographic and occupational information was collected, as well as data on drug use and mental health (sleep quality, emotional stress, and psychiatric disorders). A logistic regression model was developed to identify factors associated with amphetamine use. Odds ratio (OR; 95%CI) was defined as the measure for association. The significance level was established as p < 0.05.RESULTS The studied sample was found to have an average age of 36.7 (SD = 7.8) years, as well as low education (8.6 [SD = 2.3] years); 29.0% of drivers reported having used amphetamines within the twelve months prior to their interviews. After demographic and occupational variables had been controlled for, the factors which indicated amphetamine use among truck drivers were the following: being younger than 38 years (OR = 3.69), having spent less than nine years at school (OR = 1.76), being autonomous (OR = 1.65), working night shifts or irregular schedules (OR = 2.05), working over 12 hours daily (OR = 2.14), and drinking alcohol (OR = 1.74).CONCLUSIONS Occupational aspects are closely related to amphetamine use among truck drivers, which reinforces the importance of closely following the application of law (Resting Act (“Lei do Descanso”); Law 12,619/2012) which regulates the workload and hours of those professionals. Our results show the need for increased strictness on the trade and prescription of amphetamines in Brazil.

Spatial data infrastructures model for developing countries: A case study of Nigeria

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

Access to childbirth care by adolescents and young people in the Northeastern region of Brazil

ABSTRACT OBJECTIVE To identify the factors that interfere with the access of adolescents and young people to childbirth care for in the Northeast region of Brazil. METHODS Cross-sectional study with 3,014 adolescents and young people admitted to the selected maternity wards to give birth in the Northeast region of Brazil. The sample design was probabilistic, in two stages: the first corresponded to the health establishments and the second to women who had recently given birth and their babies. The data was collected by means of interviews and consulting the hospital records, from pre-tested electronic form. Descriptive statistics were used for the univariate analysis, Pearson’s Chi-square test for the bivariate analysis and multiple logistic regressions for the multivariate analysis. Sociodemographic variables, obstetrical history, and birth care were analyzed. RESULTS Half of the adolescents and young people interviewed had not been given guidance on the location that they should go to when in labor, and among those who had, 23.5% did not give birth in the indicated health service. Furthermore, one third (33.3%) had to travel in search of assisted birth, and the majority (66.7%) of the postpartum women came to maternity by their own means. In the bivariate analysis, the variables marital status, paid work, health insurance, number of previous pregnancies, parity, city location, and type of health establishment showed a significant association (p < 0.20) with inadequate access to childbirth care. The multivariate analysis showed that married adolescents and young people (p < 0.015), with no health insurance (p < 0.002) and from the countryside (p < 0.001) were more likely to have inadequate access to childbirth care. CONCLUSIONS Adolescents and young women, married, without health insurance, and from the countryside are more likely to have inadequate access to birth care. The articulation between outpatient care and birth care can improve this access and, consequently, minimize the maternal and fetal risks that arise from a lack of systematic hospitalization planning.

Preservice teachers' knowledge on elementary geometry concepts

This text is based on a research, which is still in progress, whose main objective is to identify and understand what are the main difficulties of future mathematics teachers of basic education are, regarding their content knowledge in geometry in the context of the curricular unit of Geometry during their undergraduate degree. We chose a qualitative approach in the form of case study, in which data collection was done through observation, interviews, a diverse set of tasks, a diagnostic test and other documents. This paper focuses on the test given to prospective teachers at the beginning of the course. The preliminary analysis of the data points to a weak performance of preservice teachers in the test issues addressing elementary knowledge of Geometry.

Dynamic network data envelopment analysis for university hospitals evaluation

ABSTRACT OBJECTIVE To develop an assessment tool to evaluate the efficiency of federal university general hospitals. METHODS Data envelopment analysis, a linear programming technique, creates a best practice frontier by comparing observed production given the amount of resources used. The model is output-oriented and considers variable returns to scale. Network data envelopment analysis considers link variables belonging to more than one dimension (in the model, medical residents, adjusted admissions, and research projects). Dynamic network data envelopment analysis uses carry-over variables (in the model, financing budget) to analyze frontier shift in subsequent years. Data were gathered from the information system of the Brazilian Ministry of Education (MEC), 2010-2013. RESULTS The mean scores for health care, teaching and research over the period were 58.0%, 86.0%, and 61.0%, respectively. In 2012, the best performance year, for all units to reach the frontier it would be necessary to have a mean increase of 65.0% in outpatient visits; 34.0% in admissions; 12.0% in undergraduate students; 13.0% in multi-professional residents; 48.0% in graduate students; 7.0% in research projects; besides a decrease of 9.0% in medical residents. In the same year, an increase of 0.9% in financing budget would be necessary to improve the care output frontier. In the dynamic evaluation, there was progress in teaching efficiency, oscillation in medical care and no variation in research. CONCLUSIONS The proposed model generates public health planning and programming parameters by estimating efficiency scores and making projections to reach the best practice frontier.

Calculation of fractional derivatives of noisy data with genetic algorithms

This paper addresses the calculation of derivatives of fractional order for non-smooth data. The noise is avoided by adopting an optimization formulation using genetic algorithms (GA). Given the flexibility of the evolutionary schemes, a hierarchical GA composed by a series of two GAs, each one with a distinct fitness function, is established.

Reconstructing the architectural evolution of volcanic islands from combined K/AR, morphologic, tectonic, and magnetic data. The Faial Island exemple (Azores)

The morpho-structural evolution of oceanic islands results from competition between volcano growth and partial destruction by mass-wasting processes. We present here a multi-disciplinary study of the successive stages of development of Faial (Azores) during the last 1 Myr. Using high-resolution digital elevation model (DEM), and new K/Ar, tectonic, and magnetic data, we reconstruct the rapidly evolving topography at successive stages, in response to complex interactions between volcanic construction and mass wasting, including the development of a graben. We show that: (1) sub-aerial evolution of the island first involved the rapid growth of a large elongated volcano at ca. 0.85 Ma, followed by its partial destruction over half a million years; (2) beginning about 360 ka a new small edifice grew on the NE of the island, and was subsequently cut by normal faults responsible for initiation of the graben; (3) after an apparent pause of ca. 250 kyr, the large Central Volcano (CV) developed on the western side of the island at ca 120 ka, accumulating a thick pile of lava flows in less than 20 kyr, which were partly channelized within the graben; (4) the period between 120 ka and 40 ka is marked by widespread deformation at the island scale, including westward propagation of faulting and associated erosion of the graben walls, which produced sedimentary deposits; subsequent growth of the CV at 40 ka was then constrained within the graben, with lava flowing onto the sediments up to the eastern shore; (5) the island evolution during the Holocene involves basaltic volcanic activity along the main southern faults and pyroclastic eruptions associated with the formation of a caldera volcano-tectonic depression. We conclude that the whole evolution of Faial Island has been characterized by successive short volcanic pulses probably controlled by brief episodes of regional deformation. Each pulse has been separated by considerable periods of volcanic inactivity during which the Faial graben gradually developed. We propose that the volume loss associated with sudden magma extraction from a shallow reservoir in different episodes triggered incremental downward graben movement, as observed historically, when immediate vertical collapse of up to 2 m was observed along the western segments of the graben at the end of the Capelinhos eruptive crises (1957-58).

Assessment of data-driven modeling strategies for water delivery canals

Conferência: CONTROLO’2012 - 16-18 July 2012 - Funchal

Data analytics in the cloud with flexible mapreduced workflows

Data analytic applications are characterized by large data sets that are subject to a series of processing phases. Some of these phases are executed sequentially but others can be executed concurrently or in parallel on clusters, grids or clouds. The MapReduce programming model has been applied to process large data sets in cluster and cloud environments. For developing an application using MapReduce there is a need to install/configure/access specific frameworks such as Apache Hadoop or Elastic MapReduce in Amazon Cloud. It would be desirable to provide more flexibility in adjusting such configurations according to the application characteristics. Furthermore the composition of the multiple phases of a data analytic application requires the specification of all the phases and their orchestration. The original MapReduce model and environment lacks flexible support for such configuration and composition. Recognizing that scientific workflows have been successfully applied to modeling complex applications, this paper describes our experiments on implementing MapReduce as subworkflows in the AWARD framework (Autonomic Workflow Activities Reconfigurable and Dynamic). A text mining data analytic application is modeled as a complex workflow with multiple phases, where individual workflow nodes support MapReduce computations. As in typical MapReduce environments, the end user only needs to define the application algorithms for input data processing and for the map and reduce functions. In the paper we present experimental results when using the AWARD framework to execute MapReduce workflows deployed over multiple Amazon EC2 (Elastic Compute Cloud) instances.

Efficient feature selection filters for high-dimensional data

Feature selection is a central problem in machine learning and pattern recognition. On large datasets (in terms of dimension and/or number of instances), using search-based or wrapper techniques can be cornputationally prohibitive. Moreover, many filter methods based on relevance/redundancy assessment also take a prohibitively long time on high-dimensional. datasets. In this paper, we propose efficient unsupervised and supervised feature selection/ranking filters for high-dimensional datasets. These methods use low-complexity relevance and redundancy criteria, applicable to supervised, semi-supervised, and unsupervised learning, being able to act as pre-processors for computationally intensive methods to focus their attention on smaller subsets of promising features. The experimental results, with up to 10(5) features, show the time efficiency of our methods, with lower generalization error than state-of-the-art techniques, while being dramatically simpler and faster.