52 resultados para Neighborhood Caju
Resumo:
In a study of socioeconomically disadvantaged children's acquisition of school literacies, a university research team investigated how a group of teachers negotiated critical literacies and explored notions of social power with elementary children in a suburban school located in an area of high poverty. Here we focus on a grade 2/3 classroom where the teacher and children became involved in a local urban renewal project and on how in the process the children wrote about place and power. Using the students' concerns about their neighborhood, the teacher engaged her class in a critical literacy project that not only involved a complex set of literate practices but also taught the children about power and the possibilities for local civic action. In particular, we discuss examples of children's drawing and writing about their neighborhoods and their lives. We explore how children's writing and drawing might be key elements in developing "critical literacies" in elementary school settings. We consider how such classroom writing can be a mediator of emotions, intellectual and academic learning, social practice, and political activism.
Resumo:
BACKGROUND: While companion animals have been previously identified as a direct source of companionship and support to their owners, their role as a catalyst for friendship formation or social support networks among humans has received little attention. This study investigated the indirect role of pets as facilitators for three dimensions of social relatedness; getting to know people, friendship formation and social support networks. METHODS: A telephone survey of randomly selected residents in four cities, one in Australia (Perth; n = 704) and three in the U.S. (San Diego, n = 690; Portland, n = 634; Nashville, n = 664) was conducted. All participants were asked about getting to know people within their neighborhood. Pet owners were asked additional questions about the type/s of pet/s they owned, whether they had formed friendships as a result of their pet, and if they had received any of four different types of social support from the people they met through their pet. RESULTS: Pet owners were significantly more likely to get to know people in their neighborhood than non-pet owners (OR 1.61; 95%CI: 1.30, 1.99). When analyzed by site, this relationship was significant for Perth, San Diego and Nashville. Among pet owners, dog owners in the three U.S. cities (but not Perth) were significantly more likely than owners of other types of pets to regard people whom they met through their pet as a friend (OR 2.59; 95%CI: 1.94, 3.46). Around 40% of pet owners reported receiving one or more types of social support (i.e. emotional, informational, appraisal, instrumental) via people they met through their pet. CONCLUSION: This research suggests companion animals can be a catalyst for several dimensions of human social relationships in neighborhood settings, ranging from incidental social interaction and getting to know people, through to formation of new friendships. For many pet owners, their pets also facilitated relationships from which they derived tangible forms of social support, both of a practical and emotionally supportive nature. Given growing evidence for social isolation as a risk factor for mental health, and, conversely, friendships and social support as protective factors for individual and community well-being, pets may be an important factor in developing healthy neighborhoods.
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We report the first 3D maps of genetic effects on brain fiber complexity. We analyzed HARDI brain imaging data from 90 young adult twins using an information-theoretic measure, the Jensen-Shannon divergence (JSD), to gauge the regional complexity of the white matter fiber orientation distribution functions (ODF). HARDI data were fluidly registered using Karcher means and ODF square-roots for interpol ation; each subject's JSD map was computed from the spatial coherence of the ODFs in each voxel's neighborhood. We evaluated the genetic influences on generalized fiber anisotropy (GFA) and complexity (JSD) using structural equation models (SEM). At each voxel, genetic and environmental components of data variation were estimated, and their goodness of fit tested by permutation. Color-coded maps revealed that the optimal models varied for different brain regions. Fiber complexity was predominantly under genetic control, and was higher in more highly anisotropic regions. These methods show promise for discovering factors affecting fiber connectivity in the brain.
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In this paper we present a robust method to detect handwritten text from unconstrained drawings on normal whiteboards. Unlike printed text on documents, free form handwritten text has no pattern in terms of size, orientation and font and it is often mixed with other drawings such as lines and shapes. Unlike handwritings on paper, handwritings on a normal whiteboard cannot be scanned so the detection has to be based on photos. Our work traces straight edges on photos of the whiteboard and builds graph representation of connected components. We use geometric properties such as edge density, graph density, aspect ratio and neighborhood similarity to differentiate handwritten text from other drawings. The experiment results show that our method achieves satisfactory precision and recall. Furthermore, the method is robust and efficient enough to be deployed in a mobile device. This is an important enabler of business applications that support whiteboard-centric visual meetings in enterprise scenarios. © 2012 IEEE.
Resumo:
We consider the problem of controlling a Markov decision process (MDP) with a large state space, so as to minimize average cost. Since it is intractable to compete with the optimal policy for large scale problems, we pursue the more modest goal of competing with a low-dimensional family of policies. We use the dual linear programming formulation of the MDP average cost problem, in which the variable is a stationary distribution over state-action pairs, and we consider a neighborhood of a low-dimensional subset of the set of stationary distributions (defined in terms of state-action features) as the comparison class. We propose a technique based on stochastic convex optimization and give bounds that show that the performance of our algorithm approaches the best achievable by any policy in the comparison class. Most importantly, this result depends on the size of the comparison class, but not on the size of the state space. Preliminary experiments show the effectiveness of the proposed algorithm in a queuing application.
Resumo:
To evaluate the underreporting rate of death -cause data in Shandong province during 2012 to 2013 by capture -mark -recapture method and to provide the base for health strategy. Methods All counties were divided into 5 stratifications according the death rates of 2012, and 14 counties were selected, then 3 towns or streets were selected in each country, 10 villages or neighborhood committees were selected in each town (street). The death data collected from security bureau and civil affairs bureau were compared with the reporting death data from the National Cause of Death Surveillance, and the underreporting rate was calculated. Results In present study, 6 929 death cases were collected, it was found that 1 556 cases were underreported. The death cases estimated by CMR method were 6 227 cases (95%CI: 7 593-7 651), and the average underreporting rate was 23.15%. There were significantly differences between different stratifications (P<0.01). The underreporting rate in 0-4 years old group was 56.93%, the male underreporting rate was 22.31% and the female underreporting rate was 24.09%. There was no significant difference between male and female groups (P>0.05). Conclusion There is an obvious underreport in the cause of death surveillance of Shandong province, and the underreporting rates are different among the 5 stratifications. The underreporting rate is higher in 0-4 years old group, and the investigation of the death cause surveillance for young residents is not perfect in some countries. The investigation quality of the death cause surveillance should be improved, increasing the integrity of the report data and adjusting the mortalities in different stratifications for obtaining a accurate mortality in Shandong province.
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We examine the moving and housing preferences of middle-aged and older in Finland, a country where population composition and movement through the life course are changing. A logistic regression reveals that middle-aged, moderate income residents, renters, those who have lived in their houses only a short time, and residents who are generally dissatisfied are most likely to consider moving. Downsizing appeals to residents with lower incomes who live alone, and who have been in their current houses longer. All potential movers agree on the importance of transportation access and a neighborhood grocery store; however, those preferring to downsize are also interested in house and neighborhood design as well as services that will allow aging in place. Income limitations may create affordability problems for some potential movers.