The Care and Shelter of Children and Adolescents in Brazil: Expressions of Social Issues

The future of Brazilian children who have the protection offered by familial bonds is threatened by social inequities that force them to seek shelter and grow up in shelters. According to the Institute of Applied Economic Research, an estimated 20,000 children and adolescents are served by institutions. The majority of these children are afro-descendent males between the ages of seven and fifteen years old. Of those researched, 87.6% have families (58.2% receive visits from their families, 22.7% are rarely visited by their families and 5.8 are legally prohibited from contacting or being by their families). The percentage of children and adolescents “without families” or with “missing families” is 11.3%. There is no information available for 2% of the children and adolescents residing in shelters. The principle factors that necessitate the placement of Brazilian children in institutions that provide care and shelter include poverty (including children forced to work, sell drugs or beg, for example); domestic violence; chemical dependence of parents or guardians; homelessness; death or parents or guardian; imprisonment of their parents; and sexual abuse committed by their parents or guardians. The issue of abandoned children and adolescents and their care and shelter in the Brazilian context expresses a perverse violation of Child and Adolescent Rights.

Learning software-maintenance tasks in offshoring projects: a cognitive-load perspective

Individual learning is central to the success of the transition phase in software mainte-nance offshoring projects. However, little is known on how learning activities, such as on-the-job training and formal presentations, are effectively combined during the tran-sition phase. In this study, we present and test propositions derived from cognitive load theory. The results of a multiple-case study suggest that learning effectiveness was highest when learning tasks such as authentic maintenance requests were used. Con-sistent with cognitive load theory, learning tasks were most effective when they imposed moderate cognitive load. Our data indicate that cognitive load was influenced by the expertise of the onsite coordinator, by intrinsic task complexity, by the degree of specifi-cation of tasks, and by supportive information. Cultural and semantic distances may in-fluence learning by inhibiting supportive information, specification, and the assignment of learning tasks.

Everolimus dual effects of an area vasculosa angiogenesis and lymphangiogenesis

Recently approved as treatment for astrocytoma, kidney and pancreatic cancer, everolimus acts on tumor cells by inhibiting tumor cell growth and proliferation, as well as by inhibition of angiogenic activity by both direct effects on vascular cell proliferation and indirect effects on growth factor production. The effects of everolimus on early stages of normal vasculogenesis, angiogenesis and lymphangiogenesis are not yet available. We found increased development of intravascular pillars by using area vasculosa of the chick chorioallantoic membrane treated with everolimus. An active lymphangiogenic response was highlighted by the expression of Prospero homeobox protein 1 (Prox1) and podoplanin, together with vascular endothelial growth factor receptor C (Vegf-C) and vascular endothelial growth factor receptor 3 (Vegfr-3) expression on day 4 in the treated group. These findings suggest a potential role of everolimus in the activation of lymphangiogenesis.

Code-specific learning rules improve action selection by populations of spiking neurons

Population coding is widely regarded as a key mechanism for achieving reliable behavioral decisions. We previously introduced reinforcement learning for population-based decision making by spiking neurons. Here we generalize population reinforcement learning to spike-based plasticity rules that take account of the postsynaptic neural code. We consider spike/no-spike, spike count and spike latency codes. The multi-valued and continuous-valued features in the postsynaptic code allow for a generalization of binary decision making to multi-valued decision making and continuous-valued action selection. We show that code-specific learning rules speed up learning both for the discrete classification and the continuous regression tasks. The suggested learning rules also speed up with increasing population size as opposed to standard reinforcement learning rules. Continuous action selection is further shown to explain realistic learning speeds in the Morris water maze. Finally, we introduce the concept of action perturbation as opposed to the classical weight- or node-perturbation as an exploration mechanism underlying reinforcement learning. Exploration in the action space greatly increases the speed of learning as compared to exploration in the neuron or weight space.

Linkage in narratives: A comparison between monolingual speakers of French and Italian, and early and late French-Italian bilinguals

In the course of language acquisition learners have to deal with the task of producing narrative texts that are coherent across a range of conceptual domains (space, time, entities) -- both within as well as across utterances. The organization of information is analyzed in this study, on the basis of retellings of a silent film, in terms of devices used in the coordination and subordination of events within the narrative sequence. The focus on subordination reflects a core grammatical difference between Italian and French, as Italian is a null-subject language while French is not. The implications of this contrast for information structure include differences in topic management within the sequence of events. The present study investigates in how far Italian-French bilingual speakers acquire the patterns of monolingual speakers of Italian. It compares how early and late bilinguals of these two languages proceed when linking information in narratives in Italian.

Integrated Segmentation of Brain Tumor Images for Radiotherapy and Neurosurgery

Image-based modeling of tumor growth combines methods from cancer simulation and medical imaging. In this context, we present a novel approach to adapt a healthy brain atlas to MR images of tumor patients. In order to establish correspondence between a healthy atlas and a pathologic patient image, tumor growth modeling in combination with registration algorithms is employed. In a first step, the tumor is grown in the atlas based on a new multi-scale, multi-physics model including growth simulation from the cellular level up to the biomechanical level, accounting for cell proliferation and tissue deformations. Large-scale deformations are handled with an Eulerian approach for finite element computations, which can operate directly on the image voxel mesh. Subsequently, dense correspondence between the modified atlas and patient image is established using nonrigid registration. The method offers opportunities in atlasbased segmentation of tumor-bearing brain images as well as for improved patient-specific simulation and prognosis of tumor progression.

It’s all about networking! Empirical investigation of social capital formation on social network sites

As Social Network Sites (SNS) permeate our daily routines, the question whether participation results in value for SNS users becomes particularly acute. This study adopts a 'participation-source-outcome' perspective to explore how distinct uses of SNS generate various types of social capital benefits. Building on existing research, extensive qualitative findings and an empirical study with 253 Facebook users, we uncover the process of social capital formation on SNS. We find that even though active communication is an important prerequisite, it is the diversified network structure and the increased social connectedness that are responsible for the attainment of the four benefits of social capital on SNS: emotional support, networking value, horizon broadening and offline participation. Moreover, we propose and validate scales to measure social capital benefits in the novel context of SNS.

I like it because I (‘m) like You – measuring user attitudes towards information on Facebook

Limited in motivation and cognitive ability to process the increasing amount of information on their Newsfeed, users apply heuristic processing to form their attitudes. Rather than extensively analysing the content, they increasingly rely on heuristic cues – such as the amount of comments and likes as well as the level of relationship with the “poster” – to process the incoming information. In the paper we explore what impact these heuristic cues have on the affective and cognitive attitude of users towards the posts on their Newsfeed. We conduct a survey on based on a Facebook application that allows users to evaluate Newsfeed posts in real time. Applying two distinct panel-regression methods we report robust results that indicate that there is a certain relationship primacy effect when users are processing information: only if the level of relationship with the “poster” is low, the impact of comments and likes on the attitude is considered, whereby likes trigger positive, whereas comments – negative evaluations.

Investigation of the Network Construction Behaviour on Social Networking Sites

By enabling connections between individuals, Social Networking Sites, such as Facebook, promise to create significant individual as well as social value. Encouraging connections between users is also crucial for service providers who increasingly rely on social advertising and viral marketing campaigns as important sources of their revenue. Consequently, understanding user’s network construction behavior becomes critical. However, previous studies offer only few scattered insights into this research question. In order to fill this gap, we employ Grounded Theory methodology to derive a comprehensive model of network construction behavior on social networking sites. In the following step we assess two Structural Equation Models to gain refined insights into the motivation to send and accept friendship requests – two network expansion strategies. Based on our findings, we offer recommendations for social network providers.