Evaluation of the prevalence and nutritional and social determinants of overweight in a population of schoolchildren: a cross-sectional analysis of 5,037 children

Objective: To evaluate the prevalence and nutritional and social determinants of overweight in a population of schoolchildren in Southern Brazil. Methods: Cross-sectional descriptive study of 5,037 children of both genders, between 6 and 10.9 years of age, from public and private schools of Maringa, Parana, Brazil. Evaluation of factors associated with excess weight (overweight and obesity) included gender, age, school type, socioeconomic level, education of the head of the family, eating habits, and means of commuting to school. After univariate analysis (Fisher's exact test), we adjusted a logistic regression model and used Wald's test for decision-making (p < 0.05). Results: The mean age was 8.7 +/- 1.3 years, with 52.8% females; 79.1% of the students attended public school and 54.6% had families of socioeconomic class A or B. Regarding nutritional status, 24% of children were overweight (7% obesity, 17% overweight). Being male, attending a private school, and having a head of the family with over four years of education were significantly associated with excess weight. In relation to food, inadequate intake of,carbohydrates was associated with a 48% greater chance of overweight/obesity (p < 0.001; OR: 1.48; 95% CI: 1.25-1.76), Conclusion: The prevalence of overweight found in this study is approximate to that reported in national studies. Its association with gender and inadequate food intake indicates that these factors should be considered in initiatives aimed at preventive measures in childhood.

Evaluation of a multimedia online tool for teaching bronchial hygiene to physical therapy students

Background: Advances in information technology have been widely used in teaching health care professionals. The use of multimedia resources may be important for clinical learning and we are not aware of previous reports using such technology in respiratory physical therapy education. Objectives: Our approach was to evaluate a conventional bronchial hygiene techniques (BHTs) course with an interactive online environment, including multimedia resources. Methods: Previous developed audiovisual support material comprised: physiology, physiopathology and BHTs, accessible to students through the Internet in conjunction with BHTs classes. Two groups of students were compared and both attended regular classes: the on-line group (n=8) received access to online resources, while the control group (n=8) received conventional written material. Student's performance was evaluated before and after the course. Results: A preliminary test (score 0 to 10) was applied before the beginning of the course, showing that the initial knowledge of both groups was comparable [online, 6.75 (SD=0.88) vs. control, 6.125 (SD=1.35); p>0.05]. Two weeks after the end of the course, a second test showed that the online group performed significantly better than the control group [respectively, 7.75 (SD=1.28) vs. 5.93 (SD=0.72); p>0.05]. Conclusions: The use of a multimedia online resource had a positive impact on student's learning in respiratory therapy field in which instrumental and manual resources are often used and can be explored using this technology.

Nutritional transition of school children from low income families of a northeastern urban area, Brazil

Background: Evaluating child growth is, in practice, performed by measuring the development of a child's weight, height, and body composition in comparison to averages observed among a reference population. Objective: To describe the nutritional status of children of low income families who live in urban region in northeastern Brazil. Methods: This study is a population case series with a transversal and observational design. The study population consisted of 257 children, aged 5 to 10 years, who were enrolled in a public school to children of low income families. We used the cutoff point for short stature of -2 Z scores for age, and underweight, overweight, and obese were classified as the 5th, 85th, and 95th percentiles, respectively, of the body mass index (BMI) for age, with both classifications in accordance with the Center for Disease Control and Prevention (CDC 2000). Comparisons by gender were performed for the measures of the central tendency and the frequency of diagnoses, in addition to the tendency of the evolution of BMI by age. Results: The prevalence of short stature was 3.5% (95% CI: 1.9-6.5). In the evaluation of BMI for age, the prevalences found for underweight, overweight, and obese were 5.8% (95% CI: 3.6-9.4), 4.7% (95% CI: 2.7-8.0), and 2.3% (95% CI: 1.1-5.0), respectively. We found a significant trend in the reduction of BMI with the increase in age. Conclusions: According to CDC references, the prevalences of underweight and short stature were higher than expected and for the overweight and obesity were lower than expected, indicating that the nutritional transition had still not reached, as commonly is described, these low income children from the urban outskirts of the Northeast region.

Literacy Practices in and out of School in Karagwe : the Case of Primary School Literacy in Rural Tanzania

This study has investigated the question of relation between literacy practices in and out of school in rural Tanzania. By using the perspective of linguistic anthropology, literacy practices in five villages in Karagwe district in the northwest of Tanzania have been analysed. The outcome may be used as a basis for educational planning and literacy programs. The analysis has revealed an intimate relation between language, literacy and power. In Karagwe, traditional élites have drawn on literacy to construct and reconstruct their authority, while new élites, such as individual women and some young people have been able to use literacy as one tool to get access to power. The study has also revealed a high level of bilingualism and a high emphasis on education in the area, which prove a potential for future education in the area. At the same time discontinuity in language use, mainly caused by stigmatisation of what is perceived as local and traditional, such as the mother-tongue of the majority of the children, and the high status accrued to all that is perceived as Western, has turned out to constitute a great obstacle for pupils’ learning. The use of ethnographic perspectives has enabled comparisons between interactional patterns in schools and outside school. This has revealed communicative patterns in school that hinder pupils’ learning, while the same patterns in other discourses reinforce learning. By using ethnography, relations between explicit and implicit language ideologies and their impact in educational contexts may be revealed. This knowledge may then be used to make educational plans and literacy programmes more relevant and efficient, not only in poor post-colonial settings such as Tanzania, but also elsewhere, such as in Western settings.

Design, implementation and evaluation of a virtual laboratory for Computer Engineering Education

Broad consensus has been reached within the Education and Cognitive Psychology research communities on the need to center the learning process on experimentation and concrete application of knowledge, rather than on a bare transfer of notions. Several advantages arise from this educational approach, ranging from the reinforce of students learning, to the increased opportunity for a student to gain greater insight into the studied topics, up to the possibility for learners to acquire practical skills and long-lasting proficiency. This is especially true in Engineering education, where integrating conceptual knowledge and practical skills assumes a strategic importance. In this scenario, learners are called to play a primary role. They are actively involved in the construction of their own knowledge, instead of passively receiving it. As a result, traditional, teacher-centered learning environments should be replaced by novel learner-centered solutions. Information and Communication Technologies enable the development of innovative solutions that provide suitable answers to the need for the availability of experimentation supports in educational context. Virtual Laboratories, Adaptive Web-Based Educational Systems and Computer-Supported Collaborative Learning environments can significantly foster different learner-centered instructional strategies, offering the opportunity to enhance personalization, individualization and cooperation. More specifically, they allow students to explore different kinds of materials, to access and compare several information sources, to face real or realistic problems and to work on authentic and multi-facet case studies. In addition, they encourage cooperation among peers and provide support through coached and scaffolded activities aimed at fostering reflection and meta-cognitive reasoning. This dissertation will guide readers within this research field, presenting both the theoretical and applicative results of a research aimed at designing an open, flexible, learner-centered virtual lab for supporting students in learning Information Security.

Nondestructive evaluation of concrete compression strength by means of Artificial Neural Network (ANN)

The evaluation of structural performance of existing concrete buildings, built according to standards and materials quite different to those available today, requires procedures and methods able to cover lack of data about mechanical material properties and reinforcement detailing. To this end detailed inspections and test on materials are required. As a consequence tests on drilled cores are required; on the other end, it is stated that non-destructive testing (NDT) cannot be used as the only mean to get structural information, but can be used in conjunction with destructive testing (DT) by a representative correlation between DT and NDT. The aim of this study is to verify the accuracy of some formulas of correlation available in literature between measured parameters, i.e. rebound index, ultrasonic pulse velocity and compressive strength (SonReb Method). To this end a relevant number of DT and NDT tests has been performed on many school buildings located in Cesena (Italy). The above relationships have been assessed on site correlating NDT results to strength of core drilled in adjacent locations. Nevertheless, concrete compressive strength assessed by means of NDT methods and evaluated with correlation formulas has the advantage of being able to be implemented and used for future applications in a much more simple way than other methods, even if its accuracy is strictly limited to the analysis of concretes having the same characteristics as those used for their calibration. This limitation warranted a search for a different evaluation method for the non-destructive parameters obtained on site. To this aim, the methodology of neural identification of compressive strength is presented. Artificial Neural Network (ANN) suitable for the specific analysis were chosen taking into account the development presented in the literature in this field. The networks were trained and tested in order to detect a more reliable strength identification methodology.

Lesion detection and classification in breast cancer: evaluation of approaches based on morphological features, tracer kinetic modelling and semi-quantitative parameters in MR functional imaging (DCE-MRI)

The diagnosis, grading and classification of tumours has benefited considerably from the development of DCE-MRI which is now essential to the adequate clinical management of many tumour types due to its capability in detecting active angiogenesis. Several strategies have been proposed for DCE-MRI evaluation. Visual inspection of contrast agent concentration curves vs time is a very simple yet operator dependent procedure, therefore more objective approaches have been developed in order to facilitate comparison between studies. In so called model free approaches, descriptive or heuristic information extracted from time series raw data have been used for tissue classification. The main issue concerning these schemes is that they have not a direct interpretation in terms of physiological properties of the tissues. On the other hand, model based investigations typically involve compartmental tracer kinetic modelling and pixel-by-pixel estimation of kinetic parameters via non-linear regression applied on region of interests opportunely selected by the physician. This approach has the advantage to provide parameters directly related to the pathophysiological properties of the tissue such as vessel permeability, local regional blood flow, extraction fraction, concentration gradient between plasma and extravascular-extracellular space. Anyway, nonlinear modelling is computational demanding and the accuracy of the estimates can be affected by the signal-to-noise ratio and by the initial solutions. The principal aim of this thesis is investigate the use of semi-quantitative and quantitative parameters for segmentation and classification of breast lesion. The objectives can be subdivided as follow: describe the principal techniques to evaluate time intensity curve in DCE-MRI with focus on kinetic model proposed in literature; to evaluate the influence in parametrization choice for a classic bi-compartmental kinetic models; to evaluate the performance of a method for simultaneous tracer kinetic modelling and pixel classification; to evaluate performance of machine learning techniques training for segmentation and classification of breast lesion.

Evaluation of a web-based application versus conventional instruction in the undergraduate curriculum of fixed prosthodontics

The present study aims to investigate the implications of web-based delivery of identical learning content for time efficiency and students' performance, as compared to conventional textbook resources.

First clinical trial of tomographic neurofeedback in attention-deficit/hyperactivity disorder: evaluation of voluntary cortical control

Tomographic neurofeedback (tNF) training was evaluated as a treatment for attention-deficit/hyperactivity disorder (ADHD). To investigate the specificity of the treatment, outcomes were related to learning during tNF.

Evaluation of sugar maple dieback in the Upper Great Lakes region and development of a forest health youth education program

Acer saccharum Marsh., is one of the most valuable trees in the northern hardwood forests. Severe dieback was recently reported by area foresters in the western Upper Great Lakes Region. Sugar Maple has had a history of dieback over the last 100 years throughout its range and different variables have been identified as being the predisposing and inciting factors in different regions at different times. Some of the most common factors attributed to previous maple dieback episodes were insect defoliation outbreaks, inadequate precipitation, poor soils, atmospheric deposition, fungal pathogens, poor management, or a combination of these. The current sugar maple dieback was evaluated to determine the etiology, severity, and change in dieback on both industry and public lands. A network of 120 sugar maple health evaluation plots was established in the Upper Peninsula, Michigan, northern Wisconsin, and eastern Minnesota and evaluated annually from 2009-2012. Mean sugar maple crown dieback between 2009-2012 was 12.4% (ranging from 0.8-75.5%) across the region. Overall, during the sampling period, mean dieback decreased by 5% but individual plots and trees continued to decline. Relationships were examined between sugar maple dieback and growth, habitat conditions, ownership, climate, soil, foliage nutrients, and the maple pathogen sapstreak. The only statistically significant factor was found to be a high level of forest floor impacts due to exotic earthworm activity. Sugar maple on soils with lower pH had less earthworm impacts, less dieback, and higher growth rates than those on soils more favorable to earthworms. Nutritional status of foliage and soil was correlated with dieback and growth suggesting perturbation of nutrient cycling may be predisposing or contributing to dieback. The previous winter's snowfall totals, length of stay on the ground, and number of days with freezing temperatures had a significant positive relationship to sugar maple growth rates. Sapstreak disease, Ceratocystis virescens, may be contributing to dieback in some stands but was not related to the amount of dieback in the region. The ultimate goal of this research is to help forest managers in the Great Lakes Region prevent, anticipate, reduce, and/or salvage stands with dieback and loss in the future. An improved understanding of the complex etiology associated with sugar maple dieback in the Upper Great Lakes Region is necessary to make appropriate silvicultural decisions. Forest Health education helps increase awareness and proactive forest management in the face of changing forest ecosystems. Lessons are included to assist educators in incorporating forest health into standard biological disciplines at the secondary school curricula.

Activity of anidulafungin in a murine model of Candida krusei infection: evaluation of mortality and disease burden by quantitative tissue cultures and measurement of serum (1,3)-beta-D-glucan levels.

Experience with anidulafungin against Candida krusei is limited. Immunosuppressed mice were injected with 1.3 x 10(7) to 1.5 x 10(7) CFU of C. krusei. Animals were treated with saline, 40 mg/kg fluconazole, 1 mg/kg amphotericin B, or 10 and 20 mg/kg anidulafungin for 5 days. Anidulafungin improved survival and significantly reduced the number of CFU/g in kidneys and serum beta-glucan levels.

Mechanisms of perceptual learning of depth discrimination in random dot stereograms.

Perceptual learning is a training induced improvement in performance. Mechanisms underlying the perceptual learning of depth discrimination in dynamic random dot stereograms were examined by assessing stereothresholds as a function of decorrelation. The inflection point of the decorrelation function was defined as the level of decorrelation corresponding to 1.4 times the threshold when decorrelation is 0%. In general, stereothresholds increased with increasing decorrelation. Following training, stereothresholds and standard errors of measurement decreased systematically for all tested decorrelation values. Post training decorrelation functions were reduced by a multiplicative constant (approximately 5), exhibiting changes in stereothresholds without changes in the inflection points. Disparity energy model simulations indicate that a post-training reduction in neuronal noise can sufficiently account for the perceptual learning effects. In two subjects, learning effects were retained over a period of six months, which may have application for training stereo deficient subjects.

Improving executive functions in 5- and 6-year-olds: Evaluation of a small group intervention in prekindergarten and kindergarten children

Research suggests a central role of executive functions for children's cognitive and social development during preschool years, especially in promoting school readiness. Interventions aiming to improve executive functions are therefore being called for. The present study examined the effect of a small group intervention implemented in kindergarten settings focusing on basic components of executive functions, i.e., working memory, interference control and cognitive flexibility. A total of 135 children enrolled in Swiss prekindergarten (5-year-olds) and kindergarten (6-year-olds) were involved. Results revealed that the small group intervention promoted gains in all three included components of executive functions: prekindergarten children substantially improved their working memory and cognitive flexibility processes, whereas significant training effects were found for the kindergarten children in interference control. Implications of these findings for early intervention programs and for tailoring preschool curricula are discussed, particularly with respect to children's school readiness. Copyright © 2011 John Wiley & Sons, Ltd.

An epidemiological evaluation of pediatric long bone fractures - a retrospective cohort study of 2716 patients from two Swiss tertiary pediatric hospitals.

BACKGROUND Children and adolescents are at high risk of sustaining fractures during growth. Therefore, epidemiological assessment is crucial for fracture prevention. The AO Comprehensive Injury Automatic Classifier (AO COIAC) was used to evaluate epidemiological data of pediatric long bone fractures in a large cohort. METHODS Data from children and adolescents with long bone fractures sustained between 2009 and 2011, treated at either of two tertiary pediatric surgery hospitals in Switzerland, were retrospectively collected. Fractures were classified according to the AO Pediatric Comprehensive Classification of Long Bone Fractures (PCCF). RESULTS For a total of 2716 patients (60% boys), 2807 accidents with 2840 long bone fractures (59% radius/ulna; 21% humerus; 15% tibia/fibula; 5% femur) were documented. Children's mean age (SD) was 8.2 (4.0) years (6% infants; 26% preschool children; 40% school children; 28% adolescents). Adolescent boys sustained more fractures than girls (p < 0.001). The leading cause of fractures was falls (27%), followed by accidents occurring during leisure activities (25%), at home (14%), on playgrounds (11%), and traffic (11%) and school accidents (8%). There was boy predominance for all accident types except for playground and at home accidents. The distribution of accident types differed according to age classes (p < 0.001). Twenty-six percent of patients were classed as overweight or obese - higher than data published by the WHO for the corresponding ages - with a higher proportion of overweight and obese boys than in the Swiss population (p < 0.0001). CONCLUSION Overall, differences in the fracture distribution were sex and age related. Overweight and obese patients seemed to be at increased risk of sustaining fractures. Our data give valuable input into future development of prevention strategies. The AO PCCF proved to be useful in epidemiological reporting and analysis of pediatric long bone fractures.

Evaluation of Three State-of-the-Art Classifiers for Recognition of Activities of Daily Living from Smart Home Ambient Data

Smart homes for the aging population have recently started attracting the attention of the research community. The "health state" of smart homes is comprised of many different levels; starting with the physical health of citizens, it also includes longer-term health norms and outcomes, as well as the arena of positive behavior changes. One of the problems of interest is to monitor the activities of daily living (ADL) of the elderly, aiming at their protection and well-being. For this purpose, we installed passive infrared (PIR) sensors to detect motion in a specific area inside a smart apartment and used them to collect a set of ADL. In a novel approach, we describe a technology that allows the ground truth collected in one smart home to train activity recognition systems for other smart homes. We asked the users to label all instances of all ADL only once and subsequently applied data mining techniques to cluster in-home sensor firings. Each cluster would therefore represent the instances of the same activity. Once the clusters were associated to their corresponding activities, our system was able to recognize future activities. To improve the activity recognition accuracy, our system preprocessed raw sensor data by identifying overlapping activities. To evaluate the recognition performance from a 200-day dataset, we implemented three different active learning classification algorithms and compared their performance: naive Bayesian (NB), support vector machine (SVM) and random forest (RF). Based on our results, the RF classifier recognized activities with an average specificity of 96.53%, a sensitivity of 68.49%, a precision of 74.41% and an F-measure of 71.33%, outperforming both the NB and SVM classifiers. Further clustering markedly improved the results of the RF classifier. An activity recognition system based on PIR sensors in conjunction with a clustering classification approach was able to detect ADL from datasets collected from different homes. Thus, our PIR-based smart home technology could improve care and provide valuable information to better understand the functioning of our societies, as well as to inform both individual and collective action in a smart city scenario.