Intoxicação crônica por chumbo e implicação no desenvolvimento escolar

To understand the implications of lead contamination contributes to more effective public politics to eliminate exposure to the metal and orientation of interventions that minimize their effects. In this paper we intended to evaluate the effects of lead contamination in children, with the Teste de Desempenho Escolar (TDE). In Study 1, transversal, aimed to evaluate the influence of blood lead levels in 28 participants of both sexes, of seven to fifteen years, divided into two groups according to the level of contamination. In Study 2, longitudinal study aimed to evaluate the effects of contamination on the school ,performance of 10 children at an interval of four years. Results showed significant underperformance for children with higher levels of contamination and that the level of academic performance remains significantly lower than expected for the series in which they find themselves. The data seem to indicate the deleterious effects of lead contamination in school performance.

Avaliação do desempenho escolar de crianças contaminadas por chumbo

The lead contamination in children has been the subject of research in the field of public health. This study evaluated the academic performance of 102 children from first to fourth grade. The subjects were divided into two groups. The first group was composed of 34 children without lead poisoning or with poison at levels lower than 5 µg/dl. The second group was composed of 68 children with blood lead levels between 10 and 40 µg/ dl. The instruments used to evaluate the academic performance were anamnesis and a scholarly performance test called Teste de Desempenho Escolar, TDE. The results indicated better academic performances from the second group with significant differences in arithmetic, reading and general scores. In a comparison between genders, the girls had better performances than the boys. These results were consistent with the parents’ perception in anamnesis. Although other variables were present, the data showed great academic damage for children with higher leadpoison. These outcomes require political policies to control contamination and intervention in this population.

Um Modelo de otimização inteira mista na programação de produção de mangueiras hidráulicas

This work deals with a problem of mixed integer optimization model applied to production planning of a real world factory that aims for hydraulic hose production. To optimize production planning, a mathematic model of MILP Mixed Integer Linear Programming, so that, along with the Analytic Hierarchy process method, would be possible to create a hierarchical structure of the most import criteria for production planning, thus finding through a solving software the optimum hose attribution to its respective machine. The hybrid modeling of Analytic Hierarchy Process along with Linear Programming is the focus of this work. The results show that using this method we could unite factory reality and quantitative analysis and had success on improving performance of production planning efficiency regarding product delivery and optimization of the production flow

Um Modelo de otimização inteira mista na programação de produção de mangueiras hidráulicas

This work deals with a problem of mixed integer optimization model applied to production planning of a real world factory that aims for hydraulic hose production. To optimize production planning, a mathematic model of MILP Mixed Integer Linear Programming, so that, along with the Analytic Hierarchy process method, would be possible to create a hierarchical structure of the most import criteria for production planning, thus finding through a solving software the optimum hose attribution to its respective machine. The hybrid modeling of Analytic Hierarchy Process along with Linear Programming is the focus of this work. The results show that using this method we could unite factory reality and quantitative analysis and had success on improving performance of production planning efficiency regarding product delivery and optimization of the production flow

Introducing education for sustainable development in the undergraduate laboratory: quantitative analysis of bioethanol fuel and its blends with gasoline by using solvatochromic dyes

The concept of Education for Sustainable Development, ESD, has been introduced in a period where chemistry education is undergoing a major change, both in emphasis and methods of teaching. Studying an everyday problem, with an important socio-economic impact in the laboratory is a part of this approach. Presently, the students in many countries go to school in vehicles that run, at least partially, on biofuels; it is high time to let them test these fuels. The use of renewable fuels is not new: since 1931 the gasoline sold in Brazil contains 20 to 25 vol-% of bioethanol; this composition is being continually monitored. With ESD in mind, we have employed a constructivist approach in an undergraduate course, where UV-vis spectroscopy has been employed for the determination of the composition of two fuel blends, namely, bioethanol/water, and bioethanol/gasoline. The activities started by giving a three-part quiz. The first and second ones introduced the students to historical and practical aspects of the theme (biofuels). In the third part, we asked them to develop a UV-vis experiment for the determination of the composition of fuel blends. They have tested two approaches: (i) use of a solvatochromic dye, followed by determination of fuel composition from plots of the empirical fuel polarity versus its composition; (ii) use of an ethanol-soluble dye, followed by determination of the blend composition from a Beer's law plot; the former proved to be much more convenient. Their evaluation of the experiment was highly positive, because of the relevance of the problem; the (constructivist) approach employed, and the bright colors that the solvatochromic dye acquire in these fuel blends. Thus ESD can be fruitfully employed in order to motivate the students; make the laboratory "fun", and teach them theory (solvation). The experiments reported here can also be given to undergraduate students whose major is not chemistry (engineering, pharmacy, biology, etc.). They are low-cost and safe to be introduced at high-school level.

Weight and neuro-psycho-motor development in children discharged from neonatal intensive care unit

Background: Low birth weight affects child growth and development, requiring the intensive use of health services. There are conversely proportional associations between prematurity and academic performance around the world. In this study we evaluated factors involved in weight and neuropsychomotor profile in one and two years old discharged from Intensive Care Units (ICU). Methods/Design: We investigated 203 children from the ICU who were followed for 24 +/- 4 months. The research was conducted by collecting data from medical records of patients in a Follow-up program. We investigated the following variables: inadequate weight at one year old; inadequate weight at two years old and a severe neurological disorder at two years old. Results: We observed increase of almost 20% in the proportion of children which weighted between the 10th and 90th percentiles and decrease of around 40% of children below the 15th percentile, from one to two years old. In almost 60% of the cases neuropsychomotor development was normal at 2 years old, less than 15% of children presented abnormal development. Variables that remained influential for clinical outcome at 1 and 2 years old were related to birth weight and gestational age, except for hypoglycemia. Neurological examination was the most influential variable for severe neurological disturbance. Conclusion: Hypoglycemia was considered a new fact to explain inadequate weight. The results, new in Brazil and difficult in terms of comparison, could be used to identify risk factors and for a better approach of newborn discharged from ICUs.

Sleep length, working hours and socio-demographic variables are associated with time attending evening classes among working college students

It is the aim of the present study to assess factors associated with time spent in class among working college students. Eighty-two working students from 21 to 26 years old participated in this study. They were enrolled in an evening course of the University of Sao Paulo, Brazil. Participants answered a questionnaire on living and working conditions. During seven consecutive days, they wore an actigraph, filled out daily activity diaries (including time spent in classes) and the Karolinska Sleepiness Scale every three hours from waking until bedtime. Linear regression analyses were performed in order to assess the variables associated with time spent in classes. The results showed that gender, sleep length, excessive sleepiness, alcoholic beverage consumption (during workdays) and working hours were associated factors with time spent in class. Thus, those who spent less time in class were males, slept longer hours, reported excessive sleepiness on Saturdays, worked longer hours, and reported alcohol consumption. The combined effects of long work hours (>40 h/week) and reduced sleep length may affect lifestyles and academic performance. Future studies should aim to look at adverse health effects induced by reduced sleep duration, even among working students who spent more time attending evening classes.

Relación entre actitudes hacia la actividad física y el deporte y rendimiento académico de los estudiantes universitarios españoles y portugueses

[ES] El presente estudio trata de analizar la existencia de relaciones entre las actitudes hacia la actividad físico-deportiva y el rendimiento académico universitario desde una perspectiva transcultural. Este estudio se ha basado en dos muestras de estudiantes universitarios españoles y portugueses matriculados en estudios de Turismo.

What users think about the differences between caffeine and illicit,prescription stimulants for cognitive enhancement

Pharmacological cognitive enhancement (CE) is a topic of increasing public awareness. In the scientific literature on studentrnuse of CE as a study aid for academic performance enhancement, there are high prevalence rates regarding the use ofrncaffeinated substances (coffee, caffeinated drinks, caffeine tablets) but remarkably lower prevalence rates regarding the usernof illicit/prescription stimulants such as amphetamines or methylphenidate. While the literature considers the reasons andrnmechanisms for these different prevalence rates from a theoretical standpoint, it lacks empirical data to account for healthyrnstudents who use both, caffeine and illicit/prescription stimulants, exclusively for the purpose of CE. Therefore, wernextensively interviewed a sample of 18 healthy university students reporting non-medical use of caffeine as well as illicit/rnprescription stimulants for the purpose of CE in a face-to-face setting about their opinions regarding differences in generalrnand morally-relevant differences between caffeine and stimulant use for CE. 44% of all participants answered that there is arngeneral difference between the use of caffeine and illicit/prescription stimulants for CE, 28% did not differentiate, 28% couldrnnot decide. Furthermore, 39% stated that there is a moral difference, 56% answered that there is no moral difference andrnone participant was not able to comment on moral aspects. Participants came to their judgements by applying threerndimensions: medical, ethical and legal. Weighing the medical, ethical and legal aspects corresponded to the students’rnindividual preferences of substances used for CE. However, their views only partly depicted evidence-based medical aspectsrnand the ethical issues involved. This result shows the need for well-directed and differentiated information to prevent thernpotentially harmful use of illicit or prescription stimulants for CE.

Trait emotional intelligence: Evidence from italian adolescents and adults

Emotional intelligence (EI) represents an attribute of contemporary attractiveness for the scientific psychology community. Of particular interest for the present thesis are the conundrum related to the representation of this construct conceptualized as a trait (i.e., trait EI), which are in turn reflected in the current lack of agreement upon its constituent elements, posing significant challenges to research and clinical progress. Trait EI is defined as an umbrella personality-alike construct reflecting emotion-related dispositions and self-perceptions. The Trait Emotional Intelligence Questionnaire (TEIQue) was chosen as main measure, given its strong theoretical and psychometrical basis, including superior predictive validity when compared to other trait EI measures. Studies 1 and 2 aimed at validating the Italian 153-items forms of the TEIQue devoted to adolescents and adults. Analyses were done to investigate the structure of the questionnaire, its internal consistencies and gender differences at the facets, factor, and global level of both versions. Despite some low reliabilities, results from Studies 1 and 2 confirm the four-factor structure of the TEIQue. Study 3 investigated the utility of trait EI in a sample of adolescents over internalizing conditions (i.e., symptoms of anxiety and depression) and academic performance (grades at math and Italian language/literacy). Beyond trait EI, concurrent effects of demographic variables, higher order personality dimensions and non-verbal cognitive ability were controlled for. Study 4a and Study 4b addressed analogue research questions, through a meta-analysis and new data in on adults. In the latter case, effects of demographics, emotion regulation strategies, and the Big Five were controlled. Overall, these studies showed the incremental utility of the TEIQue in different domains beyond relevant predictors. Analyses performed at the level of the four-TEIQue factors consistently indicated that its predictive effects were mainly due to the factor Well-Being. Findings are discussed with reference to potential implication for theory and practice.

"From Dartboards to Dashboards: The Imperative of using Data to Improve Student Achievement"

Aimee Guidera, Director of the National Data Quality Campaign, delivered the second annual Lee Gurel '48 Lecture in Education, "From Dartboards to Dashboards: The Imperative of Using Data to Improve Student Outcomes." Aimee Rogstad Guidera is the Founding Executive Director of the Data Quality Campaign. She manages a growing partnership among national organizations collaborating to improve the quality, accessibility and use of education data to improve student achievement. Working with 10 Founding Partners, Aimee launched the DQC in 2005 with the goal of every state having a robust longitudinal data system in place by 2009. The Campaign is now in the midst of its second phase focusing on State Actions to ensure effective data use. Aimee joined the National Center for Educational Accountability as Director of the Washington, DC office in 2003. During her eight previous years in various roles at the National Alliance of Business, Aimee supported the corporate community's efforts to increase achievement at all levels of learning. As NAB Vice President of Programs, she managed the Business Coalition Network, comprised of over 1,000 business led coalitions focused on improving education in communities across the country. Prior to joining the Alliance, Aimee focused on school readiness, academic standards, education goals and accountability systems while in the Center for Best Practices at the National Governors Association. She taught for the Japanese Ministry of Education in five Hiroshima high schools where she interviewed educators and studied the Japanese education system immediately after receiving her AB from Princeton University’s Woodrow Wilson School of Public & International Affairs. Aimee also holds a Masters Degree in Public Policy from Harvard’s John F. Kennedy School of Government.

Identifying indicators of sustainable development using the global sustainability quadrant approach

Advances in information technology and global data availability have opened the door for assessments of sustainable development at a truly macro scale. It is now fairly easy to conduct a study of sustainability using the entire planet as the unit of analysis; this is precisely what this work set out to accomplish. The study began by examining some of the best known composite indicator frameworks developed to measure sustainability at the country level today. Most of these were found to value human development factors and a clean local environment, but to gravely overlook consumption of (remote) resources in relation to nature’s capacity to renew them, a basic requirement for a sustainable state. Thus, a new measuring standard is proposed, based on the Global Sustainability Quadrant approach. In a two‐dimensional plot of nations’ Human Development Index (HDI) vs. their Ecological Footprint (EF) per capita, the Sustainability Quadrant is defined by the area where both dimensions satisfy the minimum conditions of sustainable development: an HDI score above 0.8 (considered ‘high’ human development), and an EF below the fair Earth‐share of 2.063 global hectares per person. After developing methods to identify those countries that are closest to the Quadrant in the present‐day and, most importantly, those that are moving towards it over time, the study tackled the question: what indicators of performance set these countries apart? To answer this, an analysis of raw data, covering a wide array of environmental, social, economic, and governance performance metrics, was undertaken. The analysis used country rank lists for each individual metric and compared them, using the Pearson Product Moment Correlation function, to the rank lists generated by the proximity/movement relative to the Quadrant measuring methods. The analysis yielded a list of metrics which are, with a high degree of statistical significance, associated with proximity to – and movement towards – the Quadrant; most notably: Favorable for sustainable development: use of contraception, high life expectancy, high literacy rate, and urbanization. Unfavorable for sustainable development: high GDP per capita, high language diversity, high energy consumption, and high meat consumption. A momentary gain, but a burden in the long‐run: high carbon footprint and debt. These results could serve as a solid stepping stone for the development of more reliable composite index frameworks for assessing countries’ sustainability.

Prevalence of depressive symptoms in urban middle and high school Hispanic and African American students

This cross-sectional study examined the prevalence of depressive symptoms in urban Hispanic and African American middle and high school students (N=1,292) using data collected from a multi-component, multi-wave violence and substance use intervention program targeted at a large urban school district in Texas. Chi-square analysis was used to examine differences in race/ethnicity, gender, grade level and whether or not a student had been held back/repeated a grade in school. Univariate and multivariate logistic regression were used to analyze the association between depressive symptoms and demographic variables. Being female and being held back/repeating a grade was significantly associated with depressive symptoms in both univariate and multivariate analyses. Overall 16% of the students reported depressive symptoms; Hispanic youth had a higher prevalence of depressive symptoms (16.8%) than the African American youth (14.8%). Minority females and those who had been held back/repeated a grade reported a prevalence of 19.4% and 21.2%, respectively. Further research is needed to understand why Hispanic youth continue to report a higher prevalence of depressive symptoms than other minorities. Additionally research is required to further explore the association between academic performance and depressive symptoms in urban minorities, specifically the effect of being held back/repeating a grade.^

Regularized model learning in EDAs for continuous and multi-objective optimization

Probabilistic modeling is the de�ning characteristic of estimation of distribution algorithms (EDAs) which determines their behavior and performance in optimization. Regularization is a well-known statistical technique used for obtaining an improved model by reducing the generalization error of estimation, especially in high-dimensional problems. `1-regularization is a type of this technique with the appealing variable selection property which results in sparse model estimations. In this thesis, we study the use of regularization techniques for model learning in EDAs. Several methods for regularized model estimation in continuous domains based on a Gaussian distribution assumption are presented, and analyzed from di�erent aspects when used for optimization in a high-dimensional setting, where the population size of EDA has a logarithmic scale with respect to the number of variables. The optimization results obtained for a number of continuous problems with an increasing number of variables show that the proposed EDA based on regularized model estimation performs a more robust optimization, and is able to achieve signi�cantly better results for larger dimensions than other Gaussian-based EDAs. We also propose a method for learning a marginally factorized Gaussian Markov random �eld model using regularization techniques and a clustering algorithm. The experimental results show notable optimization performance on continuous additively decomposable problems when using this model estimation method. Our study also covers multi-objective optimization and we propose joint probabilistic modeling of variables and objectives in EDAs based on Bayesian networks, speci�cally models inspired from multi-dimensional Bayesian network classi�ers. It is shown that with this approach to modeling, two new types of relationships are encoded in the estimated models in addition to the variable relationships captured in other EDAs: objectivevariable and objective-objective relationships. An extensive experimental study shows the e�ectiveness of this approach for multi- and many-objective optimization. With the proposed joint variable-objective modeling, in addition to the Pareto set approximation, the algorithm is also able to obtain an estimation of the multi-objective problem structure. Finally, the study of multi-objective optimization based on joint probabilistic modeling is extended to noisy domains, where the noise in objective values is represented by intervals. A new version of the Pareto dominance relation for ordering the solutions in these problems, namely �-degree Pareto dominance, is introduced and its properties are analyzed. We show that the ranking methods based on this dominance relation can result in competitive performance of EDAs with respect to the quality of the approximated Pareto sets. This dominance relation is then used together with a method for joint probabilistic modeling based on `1-regularization for multi-objective feature subset selection in classi�cation, where six di�erent measures of accuracy are considered as objectives with interval values. The individual assessment of the proposed joint probabilistic modeling and solution ranking methods on datasets with small-medium dimensionality, when using two di�erent Bayesian classi�ers, shows that comparable or better Pareto sets of feature subsets are approximated in comparison to standard methods.

REFLEXOS INDIVIDUAIS DO USO PESSOAL E EXCESSIVO DE COMUNICADORES INSTANTÂNEOS NO AMBIENTE DE TRABALHO

A Internet está inserida no cotidiano do indivíduo, e torna-se cada vez mais acessível por meio de diferentes tipos de dispositivos. Com isto, diversos estudos foram realizados com o intuito de avaliar os reflexos do seu uso excessivo na vida pessoal, acadêmica e profissional. Esta dissertação buscou identificar se a perda de concentração e o isolamento social são alguns dos reflexos individuais que o uso pessoal e excessivo de aplicativos de comunicação instantânea podem resultar no ambiente de trabalho. Entre as variáveis selecionadas para avaliar os aspectos do uso excessivo de comunicadores instantâneos tem-se a distração digital, o controle reduzido de impulso, o conforto social e a solidão. Através de uma abordagem de investigação quantitativa, utilizaram-se escalas aplicadas a uma amostra de 283 pessoas. Os dados foram analisados por meio de técnicas estatísticas multivariadas como a Análise Fatorial Exploratória e para auferir a relação entre as variáveis, a Regressão Linear Múltipla. Os resultados deste estudo confirmam que o uso excessivo de comunicadores instantâneos está positivamente relacionado com a perda de concentração, e a variável distração digital exerce uma influência maior do que o controle reduzido de impulso. De acordo com os resultados, não se podem afirmar que a solidão e o conforto social exercem relações com aumento do isolamento social, devido à ausência do relacionamento entre os construtos.