Learning benefits of self-controlled knowledge of results in 10-year-old children

PIBIC-CNPq-Conselho Nacional de Desenvolvimento Cientifico e Technologico

Constant-random practice and the adaptive process in motor learning with varying amounts of constant practice

The adaptive process in motor learning was examined in terms of effects of varying amounts of constant practice performed before random practice. Participants pressed five response keys sequentially, the last one coincident with the lighting of a final visual stimulus provided by a complex coincident timing apparatus. Different visual stimulus speeds were used during the random practice. 33 children (M age=11.6 yr.) were randomly assigned to one of three experimental groups: constant-random, constant-random 33%, and constant-random 66%. The constant-random group practiced constantly until they reached a criterion of performance stabilization three consecutive trials within 50 msec. of error. The other two groups had additional constant practice of 33 and 66%, respectively, of the number of trials needed to achieve the stabilization criterion. All three groups performed 36 trials under random practice; in the adaptation phase, they practiced at a different visual stimulus speed adopted in the stabilization phase. Global performance measures were absolute, constant, and variable errors, and movement pattern was analyzed by relative timing and overall movement time. There was no group difference in relation to global performance measures and overall movement time. However, differences between the groups were observed on movement pattern, since constant-random 66% group changed its relative timing performance in the adaptation phase.

Effect of bandwidth knowledge of results on the learning of a grip force control task

An experiment was conducted to investigate the persistence of the effect of ""bandwidth knowledge of results (KR)"" manipulated during the learning phase of performing a manual force-control task. The experiment consisted of two phases, an acquisition phase with the goal of maintaining 60% maximum force in 30 trials, and a second phase with the objective of maintaining 40% of maximum force in 20 further trials. There were four bandwidths of KR: when performance error exceeded 5, 10, or 15% of the target, and a control group (0% bandwidth). Analysis showed that 5, 10, and 15% bandwidth led to better performance than 0% bandwidth KR at the beginning of the second phase and persisted during the extended trials.

Association between nutritional status and blood pressure in schoolchildren

The aim of this study was to analyze the association between nutritional status and blood pressure in adolescents from a private school. Were recruited 316 young of both gender with age raging from 11 to 15 years old. Were measured body mass, stature, systolic blood pressure and diastolic blood pressure. The statistic procedures were composed by median, interquartile range, chi-square test and Poisson regression. The prevalence of overweight and high blood pressure was significantly higher in boys (38% and 24%, respectively) when compared to girls (19.3% and 14.4%, respectively). Overweight adolescents presented a higher risk (about 2-fold) to develop high blood pressure. In conclusion, overweight seems to be associate with high blood pressure in adolescents.

Modeling associations between genetic markers using Bayesian networks

Motivation: Understanding the patterns of association between polymorphisms at different loci in a population ( linkage disequilibrium, LD) is of fundamental importance in various genetic studies. Many coefficients were proposed for measuring the degree of LD, but they provide only a static view of the current LD structure. Generative models (GMs) were proposed to go beyond these measures, giving not only a description of the actual LD structure but also a tool to help understanding the process that generated such structure. GMs based in coalescent theory have been the most appealing because they link LD to evolutionary factors. Nevertheless, the inference and parameter estimation of such models is still computationally challenging. Results: We present a more practical method to build GM that describe LD. The method is based on learning weighted Bayesian network structures from haplotype data, extracting equivalence structure classes and using them to model LD. The results obtained in public data from the HapMap database showed that the method is a promising tool for modeling LD. The associations represented by the learned models are correlated with the traditional measure of LD D`. The method was able to represent LD blocks found by standard tools. The granularity of the association blocks and the readability of the models can be controlled in the method. The results suggest that the causality information gained by our method can be useful to tell about the conservability of the genetic markers and to guide the selection of subset of representative markers.

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.

Learning Profile Identification Based on the Analysis of the User Context of Interaction

One of the e-learning environment goal is to attend the individual needs of students during the learning process. The adaptation of contents, activities and tools into different visualization or in a variety of content types is an important feature of this environment, bringing to the user the sensation that there are suitable workplaces to his profile in the same system. Nevertheless, it is important the investigation of student behaviour aspects, considering the context where the interaction happens, to achieve an efficient personalization process. The paper goal is to present an approach to identify the student learning profile analyzing the context of interaction. Besides this, the learning profile could be analyzed in different dimensions allows the system to deal with the different focus of the learning.

HYBRID AND INCREMENTAL FUZZY LEARNING FOR HUMAN SKIN DETECTION

In this paper, a framework for detection of human skin in digital images is proposed. This framework is composed of a training phase and a detection phase. A skin class model is learned during the training phase by processing several training images in a hybrid and incremental fuzzy learning scheme. This scheme combines unsupervised-and supervised-learning: unsupervised, by fuzzy clustering, to obtain clusters of color groups from training images; and supervised to select groups that represent skin color. At the end of the training phase, aggregation operators are used to provide combinations of selected groups into a skin model. In the detection phase, the learned skin model is used to detect human skin in an efficient way. Experimental results show robust and accurate human skin detection performed by the proposed framework.

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.

Learning about knowledge management for improving environmental impact assessment in a government agency: The Western Australian experience

How does knowledge management (KM) by a government agency responsible for environmental impact assessment (EIA) potentially contribute to better environmental assessment and management practice? Staff members at government agencies in charge of the EIA process are knowledge workers who perform judgement-oriented tasks highly reliant on individual expertise, but also grounded on the agency`s knowledge accumulated over the years. Part of an agency`s knowledge can be codified and stored in an organizational memory, but is subject to decay or loss if not properly managed. The EIA agency operating in Western Australia was used as a case study. Its KM initiatives were reviewed, knowledge repositories were identified and staff surveyed to gauge the utilisation and effectiveness of such repositories in enabling them to perform EIA tasks. Key elements of KM are the preparation of substantive guidance and spatial information management. It was found that treatment of cumulative impacts on the environment is very limited and information derived from project follow-up is not properly captured and stored, thus not used to create new knowledge and to improve practice and effectiveness. Other opportunities for improving organizational learning include the use of after-action reviews. The learning about knowledge management in EIA practice gained from Western Australian experience should be of value to agencies worldwide seeking to understand where best to direct their resources for their own knowledge repositories and environmental management practice. (C) 2011 Elsevier Ltd. All rights reserved.

On Building a Memory Evolutive System for Application to Learning and Cognition Modeling

We address here aspects of the implementation of a memory evolutive system (MES), based on the model proposed by A. Ehresmann and J. Vanbremeersch (2007), by means of a simulated network of spiking neurons with time dependent plasticity. We point out the advantages and challenges of applying category theory for the representation of cognition, by using the MES architecture. Then we discuss the issues concerning the minimum requirements that an artificial neural network (ANN) should fulfill in order that it would be capable of expressing the categories and mappings between them, underlying the MES. We conclude that a pulsed ANN based on Izhikevich`s formal neuron with STDP (spike time-dependent plasticity) has sufficient dynamical properties to achieve these requirements, provided it can cope with the topological requirements. Finally, we present some perspectives of future research concerning the proposed ANN topology.

Occurrence of AFM(1) in urine samples of a Brazilian population and association with food consumption

This survey evaluated the presence of AFM(1) in human urine samples from a specific Brazilian population, as well as corn, peanut, and milk consumption measured by two types of food inquiry. Urine samples from donors who live in the city of Piracicaba, State of Sao Paulo, Brazil were analyzed to detect the presence of aflatoxin M(1) (AFM(1)). an aflatoxin B(1) metabolite, which may be used as aflatoxin B(1) exposure biomarker. The AFM(1) analysis was performed using immunoaffinity clean-up and detection by high-performance-liquid chromatography with fluorescence detector. A total of 69 samples were analyzed and 45 of them (65%) presented contaminations >= 1.8 pg ml(-1), which was the limit of quantification (LOQ). Seventy eight percent (n = 54) of the samples presented detectable concentrations of AFM(1) (>0.6 pg ml(-1)). The AFM(1) concentration among samples above LOQ ranged from 1.8 to 39.9 pg ml(-1). There were differences in food consumption profile among donors, although no association was found between food consumption and AFM(1) concentration in urine. The high frequency of positive samples suggests exposure of the populations studied to aflatoxins. (C) 2009 Elsevier Ltd. All rights reserved.

Association between decay fungi and subterranean termites in the wood biodeterioration process of Tipuana tipu (Benth.) O. Kuntze trees of Sao Paulo city, SP

In the present paper the process of wood biodeterioration of tipuana trees planted in 7 regions of the city of Sao Paulo, SP was evaluated. On the sidewalks, 1109 trees were analyzed taking into consideration the occurrence and association of the xylophagous organisms (decay fungi and subterranean termites), the wood deterioration and the BHD (breast height diameter). The percentage of wood internal deterioration (%) was obtained by non destructive analysis, using a penetrometer. The results had shown that 75% of the tipuana trees presented BHD superior to 50 cm, characterizing them as adult. Decay fungi in the roots and/or trunk had been observed in 338 trees (30.5%). Subterranean termites of Heterotermes sp. and Coptotermes gestroi species had occurred in 307 trees (27.7%), the latter in high infestation level. The association between the fungi and termites was observed, as well as its relation with the BHD, where a greater value of BHD meant higher wood biodeterioration intensity. For tipuana trees, the BHD was considered an indicative attribute of the internal deterioration intensity, caused by these xylophagous organisms.

Age-related association of rDNA and telomeres with the nuclear matrix in mouse hepatocytes

Transcribed sequences have been suggested to be associated with the nuclear matrix, differing from non-transcribing sequences, which have been reported to be contained in DNA loops. However, although a dozen of genes have their expression level affected by aging, data on chromatin-nuclear matrix interactions under this physiological condition are still scarce. In the present study, liver imprints from young, adult and old mice were subjected to FISH (fluorescence in situ hybridization) for 45S rDNA and telomeric sequences, with or without a lysis treatment to produce extended chromatin fibres. There was an increased amount of 45S rDNA sequences located in DNA loops as the animals grow older, while telomeric sequences were always observed in DNA loops irrespective of the animal age. We assume that active rRNA genes associate with the nuclear matrix, while DNA loops contain silent sequences. Transcription of each 45S rDNA repeat unit is suggested to be dependent on its interaction with the nuclear matrix.

Diet-induced milk fat depression: Association with changes in milk fatty acid composition and fluidity of milk fat

This experiment was designed to examine changes in milk fatty acids during fish oil-induced milk fat depression (MFD) and to test the theory that these changes are related to milk fat fluidity. The experiment was divided into three periods: 1) Baseline: all cows (n = 12) received a high fiber diet without fish oil (FO) for 12 days; 2) Treatment: 4 cows/group received the following treatments for 21 days: a) Low fiber diet without FO (LF), b) High fiber diet+FO (HF+FO) and c) Low fiber diet+FO (LF+FO); 3) Post-treatment: cows returned to the baseline diet and were monitored for 12 days. FO was included at 1.6% DM and HF and LF diets had 40 and 26% NDF, respectively. Milk fat content and yield were unchanged by the LF diet, but were reduced by FO diets at both dietary fiber levels and recovered in the post-treatment period. FO diets caused a pronounced reduction in stearic and oleic acid concentrations in milk fat and an equally pronounced increase in trans-18:1 fatty acid concentrations. Milk fat mean melting point (MMP) was correlated with MFD (r=0.73) and with milk oleic acid concentration (r=-0.92). The ratio of oleic:stearic in milk fat increased gradually and consistently in response to FO. Trans-C18:1 isomers with double bounds at carbon :<= 10 increased with greater MFD and those with double bonds at carbon ! I I decreased with greater MFD. Trans-9 cis-11 CLA explained more than 80% of MFD and was strongly correlated with trans-10 C18:1. Maintenance of MMP below 39-40 degrees C suggests that the mammary gland was able to secrete only milk fat with adequate fluidity and that MFD could be an adaptation mechanism to prevent secretion of milk with higher MMP. (C) 2007 Elsevier B.V. All rights reserved.