Revealing the whiteboard to blind students: An inclusive approach to provide mediation in synchronous e-learning activities

Promoting the inclusion of students with disabilities in e-learning systems has brought many challenges for researchers and educators. The use of synchronous communication tools such as interactive whiteboards has been regarded as an obstacle for inclusive education. In this paper, we present the proposal of an inclusive approach to provide blind students with the possibility to participate in live learning sessions with whiteboard software. The approach is based on the provision of accessible textual descriptions by a live mediator. With the accessible descriptions, students are able to navigate through the elements and explore the content of the class using screen readers. The method used for this study consisted of the implementation of a software prototype within a virtual learning environment and a case study with the participation of a blind student in a live distance class. The results from the case study have shown that this approach can be very effective, and may be a starting point to provide blind students with resources they had previously been deprived from. The proof of concept implemented has shown that many further possibilities may be explored to enhance the interaction of blind users with educational content in whiteboards, and further pedagogical approaches can be investigated from this proposal. (C) 2009 Elsevier Ltd. All rights reserved.

Collaborative e-learning and Learning Objects

The Learning Object (OA) is any digital resource that can be reused to support learning with specific functions and objectives. The OA specifications are commonly offered in SCORM model without considering activities in groups. This deficiency was overcome by the solution presented in this paper. This work specified OA for e-learning activities in groups based on SCORM model. This solution allows the creation of dynamic objects which include content and software resources for the collaborative learning processes. That results in a generalization of the OA definition, and in a contribution with e-learning specifications.

Accelerating autonomous learning by using heuristic selection of actions

This paper investigates how to make improved action selection for online policy learning in robotic scenarios using reinforcement learning (RL) algorithms. Since finding control policies using any RL algorithm can be very time consuming, we propose to combine RL algorithms with heuristic functions for selecting promising actions during the learning process. With this aim, we investigate the use of heuristics for increasing the rate of convergence of RL algorithms and contribute with a new learning algorithm, Heuristically Accelerated Q-learning (HAQL), which incorporates heuristics for action selection to the Q-Learning algorithm. Experimental results on robot navigation show that the use of even very simple heuristic functions results in significant performance enhancement of the learning rate.

HANDEDNESS INFLUENCES PASSIVE SHOULDER RANGE OF MOTION IN NONATHLETE ADULT WOMEN

Objective: The Purpose of this study was to determine whether handedness influences bilateral shoulder range of motion in nonathlete adult women. Methods: This was an observational Study. Shoulder range of motion (flexion, abduction, horizontal adduction, extension, external and internal rotation) was passively and bilaterally measured in 50 female, right-handed, and healthy university students, ranging from 20 to 29 years of age, who were not practicing repetitive activities with the upper limbs at the time Of this study. The assessment was performed with a universal goniometer, twice for each subject by the same examiner. irst and second measurements were correlated using the intraclass correlation coefficient, which was high for all movements and ranged from 0.80 to 0.97. The Student t test and Wilcoxon test were used to compare the range of motion between the dominant and nondominant shoulders and the mean differences between the 2 sides. The effect of size vias alpha = .05. Results: There is statistically significance difference between the 2 sides when the rotational range of motion is compared the dominant shoulder presented increased external rotation (mean, 4.74 degrees; 95% confidence interval, 1.61-7.87) and decreased internal rotation (mean, 3.52 degrees; 95% confidence interval, 1.64-5.4) compared to the opposite Shoulder. Conclusion: Dominance should be considered when shoulder rotation is evaluated even in nonathlete adult women. (J Manipulative Physiol Ther 2009;32:149-153)

A visita domiciliária realizada pelo agente comunitário de saúde sob a ótica de adultos e idosos

A visita domiciliária constitui o principal instrumento de trabalho dos agentes comunitários na Estratégia Saúde da Família. O objetivo deste estudo foi descrever a percepção de adultos e idosos em relação à visita domiciliária realizada pelo agente comunitário de saúde. Como referencial metodológico foi utilizada a abordagem qualitativa embasada em algumas figuras metodológicas do Discurso do Sujeito Coletivo. Os dados foram coletados em maio de 2007, em uma Unidade de Saúde da Família de Botucatu-SP, por meio de formulário sociodemografico e entrevista semiestruturada aplicada a 14 usuários. A análise dos dados permitiu identificar dois temas: "Sentimentos e percepções em relação à visita e ao agente comunitário" e "O reconhecimento das ações do agente comunitário". Apesar de os entrevistados sentirem-se satisfeitos e gratos diante da visita, o fato de perceberem a frequência mensal como insuficiente e de alegarem desconhecer o conteúdo das anotações realizadas pelo agente no momento da visita sinalizam a necessidade de o enfermeiro investir de maneira mais intensa em atividades educativas junto a esses profissionais, priorizando questões que envolvem os processos de comunicação. Acredita-se que com essa medida será possível otimizar, qualitativamente, a realização da atividade.

Towards modular and coordinated manufacturing systems oriented to services

Nowadays, there is a trend for industry reorganization in geographically dispersed systems, carried out of their activities with autonomy. These systems must maintain coordinated relationship among themselves in order to assure an expected performance of the overall system. Thus, a manufacturing system is proposed, based on ""web services"" to assure an effective orchestration of services in order to produce final products. In addition, it considers special functions, such as teleoperation and remote monitoring, users` online request, among others. Considering the proposed system as discrete event system (DES), techniques derived from Petri nets (PN), including the Production Flow Schema (PFS), can be used in a PFS/PN approach for modeling. The system is approached in different levels of abstraction: a conceptual model which is obtained by applying the PFS technique and a functional model which is obtained by applying PN. Finally, a particular example of the proposed system is presented.

Rewarded associative and instrumental conditioning after neonatal ventral hippocampus lesions in rats

Sprague Dawley rats were submitted to bilateral ventral hippocampus lesions 7 days after birth. This corresponds to the Lipska and Weinberger`s procedure for modeling schizophrenia. The aim of the present work was to test the learning capacity of such rats with an associative Pavlovian and an instrumental learning paradigm, both methods using reward outcome (food, sucrose or polycose). The associative paradigm comprised also a second learning test with reversed learning contingencies. The instrumental conditioning comprised an extinction test under outcome devaluation conditions. Neonatally lesioned rats, once adults (over 60 days of age), showed a conditioning deficit in the associative paradigm but not in the instrumental one. Lesioned rats remained able to adapt as readily as controls to the reversed learning contingency and were as sensitive as controls to the devaluation of outcome. Such observations indicate that the active access (instrumental learning) to a reward could have compensated for the deficit observed under the ""passive"" stimulus-reward associative learning condition. This feature is compared to the memory management impairments observed in clinical patients. (c) 2008 Elsevier B.V. All rights reserved.

Cysteine Cathepsins in Human Dentin-Pulp Complex

Introduction: Collagen-degrading matrix metalloproteinases (MMPs) are expressed by odontoblasts and present in dentin. We hypothesized that odontoblasts express other collagen-degrading enzymes such as cysteine cathepsins, and their activity would be present in dentin, because odontoblasts are known to express at least cathepsin D. Effect of transforming growth factor beta (TGF-beta) on cathepsin expression was also analyzed. Methods: Human odontoblasts and pulp tissue were cultured with and without TGF-beta, and cathepsin gene expression was analyzed with DNA microarrays. Dentin cathepsin and MMP activities were analyzed by degradation of respective specific fluorogenic substrates. Results: Both odontoblasts and pulp tissue demonstrated a wide range of cysteine cathepsin expression that gave minor responses to TGF-beta. Cathepsin and MMP activities were observed in all dentin samples, with significant negative correlations in their activities with tooth age. Conclusions: These results demonstrate for the first time the presence of cysteine cathepsins in dentin and suggest their role, along with MMPs, in dentin modification with aging. (J Endod 2010;36:475-481)

Semantic mapping using mobile robots

Robotic mapping is the process of automatically constructing an environment representation using mobile robots. We address the problem of semantic mapping, which consists of using mobile robots to create maps that represent not only metric occupancy but also other properties of the environment. Specifically, we develop techniques to build maps that represent activity and navigability of the environment. Our approach to semantic mapping is to combine machine learning techniques with standard mapping algorithms. Supervised learning methods are used to automatically associate properties of space to the desired classification patterns. We present two methods, the first based on hidden Markov models and the second on support vector machines. Both approaches have been tested and experimentally validated in two problem domains: terrain mapping and activity-based mapping.