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.

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.

Residual stresses in titanium nitride thin films obtained with step variation of substrate bias voltage during deposition

In this work, a series of depositions of titanium nitride (TiN) films on M2 and D2 steel substrates were conducted in a Triode Magnetron Sputtering chamber. The temperature; gas flow and pressure were kept constant during each run. The substrate bias was either decreased or increased in a sequence of steps. Residual stress measurements were later conducted through the grazing X-ray diffraction method. Different incident angles were used in order to change the penetration depth and to obtain values of residual stress at different film depths. A model described by Dolle was adapted as an attempt to calculate the values of residual stress at each incident angle as a function of the value from each individual layer. Stress results indicated that the decrease in bias voltage during the deposition has produced compressive residual stress gradients through the film thickness. On the other hand, much less pronounced gradients were found in one of the films deposited with increasing bias voltage. (C) 2010 Elsevier B.V. All rights reserved.

Parameter setting and statistical learning

Three main models of parameter setting have been proposed: the Variational model proposed by Yang (2002; 2004), the Structured Acquisition model endorsed by Baker (2001; 2005), and the Very Early Parameter Setting (VEPS) model advanced by Wexler (1998). The VEPS model contends that parameters are set early. The Variational model supposes that children employ statistical learning mechanisms to decide among competing parameter values, so this model anticipates delays in parameter setting when critical input is sparse, and gradual setting of parameters. On the Structured Acquisition model, delays occur because parameters form a hierarchy, with higher-level parameters set before lower-level parameters. Assuming that children freely choose the initial value, children sometimes will miss-set parameters. However when that happens, the input is expected to trigger a precipitous rise in one parameter value and a corresponding decline in the other value. We will point to the kind of child language data that is needed in order to adjudicate among these competing models.

Mummy! Ball! Fish!: Why English-learning children produce nouns earlier than verbs

When English-learning children begin using words the majority of their early utterances (around 80%) are nouns. Compared to nouns, there is a paucity of verbs or non-verb relational words, such as 'up' meaning 'pick me up'. The primary explanations to account for these differences in use either argue in support of a 'cognitive account', which claims that verbs entail more cognitive complexity than nouns, or they provide evidence challenging this account. In this paper I propose an additional explanation for children's noun/verb asymmetry. Presenting a 'multi-modal account' of word-learning based on children's gesture and word combinations, I show that at the one-word stage English-learning children use gestures to express verb-like elements which leaves their words free to express noun-like elements.

Extending teaching and learning initiatives in the cross-disciplinary field of biotechnology

Our AUTC Biotechnology study (Phases 1 and 2) identified a range of areas that could benefit from a common approach by universities nationally. A national network of biotechnology educators needs to be solidified through more regular communication, biennial meetings, and development of methods for sharing effective teaching practices and industry placement strategies, for example. Our aims in this proposed study are to: a. Revisit the state of undergraduate biotechnology degree programs nationally to determine their rate of change in content, growth or shrinkage in student numbers (as the biotech industry has had its ups and downs in recent years), and sustainability within their institutions in light of career movements of key personnel, tightening budgets, and governmental funding priorities. b. Explore the feasibility of a range of initiatives to benefit university biotechnology education to determine factors such as how practical each one is, how much buy-in could be gained from potentially participating universities and industry counterparts, and how sustainable such efforts are. One of many such initiatives arising in our AUTC Biotech study was a national register of industry placements for final-year students. c. During scoping and feasibility study, to involve our colleagues who are teaching in biotechnology – and contributing disciplines. Their involvement is meant to yield not only meaningful insight into how to strengthen biotechnology teaching and learning but also to generate ‘buy-in’ on any initiatives that result from this effort.

Special issue on advances in data mining and its applications

Data mining is the process to identify valid, implicit, previously unknown, potentially useful and understandable information from large databases. It is an important step in the process of knowledge discovery in databases, (Olaru & Wehenkel, 1999). In a data mining process, input data can be structured, seme-structured, or unstructured. Data can be in text, categorical or numerical values. One of the important characteristics of data mining is its ability to deal data with large volume, distributed, time variant, noisy, and high dimensionality. A large number of data mining algorithms have been developed for different applications. For example, association rules mining can be useful for market basket problems, clustering algorithms can be used to discover trends in unsupervised learning problems, classification algorithms can be applied in decision-making problems, and sequential and time series mining algorithms can be used in predicting events, fault detection, and other supervised learning problems (Vapnik, 1999). Classification is among the most important tasks in the data mining, particularly for data mining applications into engineering fields. Together with regression, classification is mainly for predictive modelling. So far, there have been a number of classification algorithms in practice. According to (Sebastiani, 2002), the main classification algorithms can be categorized as: decision tree and rule based approach such as C4.5 (Quinlan, 1996); probability methods such as Bayesian classifier (Lewis, 1998); on-line methods such as Winnow (Littlestone, 1988) and CVFDT (Hulten 2001), neural networks methods (Rumelhart, Hinton & Wiliams, 1986); example-based methods such as k-nearest neighbors (Duda & Hart, 1973), and SVM (Cortes & Vapnik, 1995). Other important techniques for classification tasks include Associative Classification (Liu et al, 1998) and Ensemble Classification (Tumer, 1996).

Conditioning training and retrieval increase phospholipase A(2) activity in the cerebral cortex of rats

In rats, phospholipase A(2) (PLA(2)) activity was found to be increased in the hippocampus immediately after training and retrieval of a contextual fear conditioning paradigm (step-down inhibitory avoidance [IA] task). In the present study we investigated whether PLA(2) is also activated in the cerebral cortex of rats in association with contextual fear learning and retrieval. We observed that IA training induces a rapid (immediately after training) and long-lasting (3 h after training) activation of PLA(2) in both frontal and parietal cortices. However, immediately after retrieval (measured 24 h after training), PLA(2) activity was increased just in the parietal cortex. These findings suggest that PLA(2) activity is differentially required in the frontal and parietal cortices for the mechanisms of contextual learning and retrieval. Because reduced brain PLA(2) activity has been reported in Alzheimer disease, our results suggest that stimulation of PLA(2) activity may offer new treatment strategies for this disease.

Effects of progressive resistance strength training on knee biomechanics during single leg step-up in persons with mild knee osteoarthritis

Background: The goal of this study was to determine if increasing strength in primary knee extensors and flexors would directly affect net knee joint moments during a common functional task in persons with knee osteoarthritis. Methods: An exploratory single sample clinical trial with pre-post treatment measures was used to study volunteers with clinical diagnosis of mild knee osteoarthritis (OA) in one knee. Subjects participated in an individually supervised training program 3 times a week for eight weeks consisting of progressive resistive exercises for knee extensors and knee flexors. Pre and post training outcome assessments included: 1. Net internal knee joint moments, 2. Electromyography of primary knee extensors and flexors, and 3. Self-report measures of knee pain and function. The distribution of lower extremity joint moments as a percent of the total support moment was also investigated. Findings: Pain, symptoms, activities of daily life, quality of life, stiffness, and function scores showed significant improvement following strength training. Knee internal valgus and hip internal rotation moments showed increasing but non-statistically significant changes post-training. There were no significant differences in muscle co-contraction activation of the Quadriceps and Hamstrings. Interpretation: While exercise continues to be an important element of OA management, the results of this study suggest improvements in function, pain, and other symptoms, as a result of strength training may not be causally related to specific biomechanical changes in net joint moments. (C) 2011 Elsevier Ltd. All rights reserved.

Micromorphology of Resin-Dentin Interfaces Using One-Bottle Etch&Rinse and Self-Etching Adhesive Systems on Laser-Treated Dentin Surfaces: A Confocal Laser Scanning Microscope Analysis

Background and Objectives: This study evaluated the hybrid layer (HL) morphology created by three adhesive systems (AS) on dentin surfaces treated with Er:YAG laser using two irradiation parameters. Study Design: Occlusal flat dentin surfaces of 36 human third molars were assigned into nine groups (n = 4) according to the following ASs: one bottle etch&rinse Single Bond Plus (3M ESPE), two-step Clearfil Protect Bond (Kuraray), and all-in-one S3 Bond (Kuraray) self-etching, which were labeled with rhodamine B or fluorescein isothiocyanate dextran and were applied to dentin surfaces that were irradiated with Er:YAG laser at either 120 (38.7 J/cm(2)) or 200 mJ/pulse (64.5 J/cm(2)), or were applied to untreated dentin surfaces (control group). The ASs were light-activated following MI and the bonded surfaces were restored with resin composite Z250 (3M ESPE). After 24 hours of storage in vegetable oil, the restored teeth were vertically, serially sectioned into 1-mm thick slabs, which had the adhesive interfaces analyzed with confocal laser microscope (CLSM-LSM 510 Meta). CLSM images were recorded in the fluorescent mode from three different regions along each bonded interface. Results: Non-uniform HL was created on laser-irradiated dentin surfaces regardless of laser irradiation protocol for all AS, while regular and uniform HL was observed in the control groups. ""Stretch mark""-like red lines were found within the HL as a result of resin infiltration into dentin microfissures, which were predominantly observed in 200 mJ/pulse groups regardless of AS. Poor resin infiltration into peritubular dentin was observed in most regions of adhesive interfaces created by all ASs on laser-irradiated dentin, resulting in thin resin tags with neither funnel-shaped morphology nor lateral resin projections. Conclusion: Laser irradiation of dentin surfaces at 120 or 200 mJ/pulse resulted in morphological changes in HL and resin tags for all ASs evaluated in the study. Lasers Surg. Med. 42:662-670, 2010. (C) 2010 Wiley-Liss, Inc.

Influence of the Additional Er:YAG Laser Conditioning Step on the Microleakage of Class V Restorations

The purpose of this study was to evaluate the influence of an additional Er:YAG laser conditioning step after laser cavity preparations, on the microleakage of class V composite restorations. Forty-eight bovine incisors were randomly divided into four groups: G1(control) cavities prepared with bur, G2- cavities prepared with laser (400 mJ/2 Hz), G3-cavities prepared and subsequently conditioned with Er:YAG laser (60 mJ/2 Hz); G4-idem for G3, but the laser conditioning was carried out without water-spray. All the cavities were restored using Clearfill SE Bond (R) and Z-250 (R) composite resin. The samples were thermal cycled for 700 cycles and then immersed in 50% silver nitrate solution. The sectioned restorations were exposed to a photoflood lamp to reveal silver nitrate penetration. The Kruskal-Walis one-way analyses of variance test and post hoc Wilcoxon pair-wise comparison were used to compare microleakage degrees. At the gingival margin G2 showed a lower microleakage mean than the control bur-prepared cavities (p = 0.0003). At occlusal margins there were no statistically significant differences between the groups (p = 0.28). It may be concluded that Er:YAG laser class V cavity preparations do not need to be followed by an additional laser conditioning step to result in levels of microleakage similar to or lower than those obtained after bur preparations. (C) 2008 Wiley Periodicals, Inc. J Biomed Mater Res Part B: Appl Biomater 87B: 538-543, 2008

One-year stability of resin-dentin bonds created with a hydrophobic ethanol-wet bonding technique

Dentin bonding performed with hydrophobic resins using ethanol-wet bonding should be less susceptible to degradation but this hypothesis has never been validated. Objectives. This in vitro study evaluated stability of resin-dentin bonds created with an experimental three-step BisGMA/TEGDMA hydrophobic adhesive or a three-step hydrophilic adhesive after one year of accelerated aging in artificial saliva. Methods. Flat surfaces in mid-coronal dentin were obtained from 45 sound human molars and randomly divided into three groups (n = 15): an experimental three-step BisGMA/TEGDMA hydrophobic adhesive applied to ethanol (ethanol-wet bonding-GI) or water-saturated dentin (water-wet bonding-GII) and Adper Scotchbond Multi-Purpose [MP-GIII] applied, according to manufacturer instructions, to water-saturated dentin. Resin composite crowns were incrementally formed and light-cured to approximately 5 mm in height. Bonded specimens were stored in artificial saliva at 37 degrees C for 24h and sectioned into sticks. They were subjected to microtensile bond test and TEM analysis immediately and after one year. Data were analyzed with two-way ANOVA and Tukey tests. Results. MP exhibited significant reduction in microtensile bond strength after aging (24 h: 40.6 +/- 2.5(a); one year: 27.5 +/- 3.3(b); in MPa). Hybrid layer degradation was evident in all specimens examined by TEM. The hydrophobic adhesive with ethanol-wet bonding preserved bond strength (24 h: 43.7 +/- 7.4(a); one year: 39.8 +/- 2.7(a)) and hybrid layer integrity, with the latter demonstrating intact collagen fibrils and wide interfibrillar spaces. Significance. Coaxing hydrophobic resins into acid-etched dentin using ethanol-wet bonding preserves resin-dentin bond integrity without the adjunctive use of MMPs inhibitors and warrants further biocompatibility and patient safety`s studies and clinical testing. (C) 2009 Academy of Dental Materials. Published by Elsevier Ltd. All rights reserved.

Stimulus competition in affective and relational learning

Evaluative learning theory states that affective learning, the acquisition of likes and dislikes, is qualitatively different from relational learning, the learning of predictive relationships among stimuli. Three experiments tested the prediction derived from evaluative learning theory that relational learning, but not affective learning, is affected by stimulus competition by comparing performance during two conditional stimuli, one trained in a superconditioning procedure and the other in a blocking procedure. Ratings of unconditional stimulus expectancy and electrodermal responses indicated stimulus competition in relational learning. Evidence for stimulus competition in affective learning was provided by verbal ratings of conditional stimulus pleasantness and by measures of blink startle modulation. Taken together, the present experiments demonstrate stimulus competition in relational and affective learning, a result inconsistent with evaluative learning theory. (C) 2001 Academic Press.

Step size control for efficient discrete element simulation

The step size determines the accuracy of a discrete element simulation. The position and velocity updating calculation uses a pre-calculated table and hence the control of step size can not use the integration formulas for step size control. A step size control scheme for use with the table driven velocity and position calculation uses the difference between the calculation result from one big step and that from two small steps. This variable time step size method chooses the suitable time step size for each particle at each step automatically according to the conditions. Simulation using fixed time step method is compared with that of using variable time step method. The difference in computation time for the same accuracy using a variable step size (compared to the fixed step) depends on the particular problem. For a simple test case the times are roughly similar. However, the variable step size gives the required accuracy on the first run. A fixed step size may require several runs to check the simulation accuracy or a conservative step size that results in longer run times. (C) 2001 Elsevier Science Ltd. All rights reserved.

Host selection in phytophagous insects: a new explanation for learning in adults

Insect learning can change the preferences an egg laying female displays towards different host plant species. Current hypotheses propose that learning may be advantageous in adult host selection behaviour through improved recognition, accuracy or selectivity in foraging. In this paper, we present a hypothesis for when learning can be advantageous without such improvements in adult host foraging. Specifically, that learning can be an advantageous strategy for egg laying females when larvae must feed on more than one plant in order to complete development, if the fitness of larvae is reduced when they switch to a different host species. Here, larvae benefit from developing on the most abundant host species, which is the most likely choice of host for an adult insect which increases its preference for a host species through learning. The hypothesis is formalised with a mathematical model and we provide evidence from studies on the behavioural ecology, of a number of insect species which demonstrate that the assumptions of this hypothesis may frequently be fulfilled in nature. We discuss how multiple mechanisms may convey advantages in insect learning and that benefits to larval development, which have so far been overlooked, should be considered in explanations for the widespread occurrence of learning.