985 resultados para Induction Learning


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As a global profession, engineering is integral to the maintenance and further development of society. Indeed, contemporary social problems requiring engineering solutions are not only a consequence of natural and ‘manmade’ disasters (such as the Japanese earthquake or the oil leakage in the Gulf of Mexico) but also encapsulate 21st Century dilemmas around sustainability, poverty and pollution [2,6,7]. Given the complexity of such problems and the constant need for innovation, the demand for engineering education to provide a ready supply of suitably qualified engineering graduates, able to make innovative decisions has never been higher [3,5]. Bearing this in mind, and taking account problems of attrition in engineering education [1,6,4] innovation in the way in which the curriculum is developed and delivered is crucial. CDIO [Conceive, Design, Implement, Operate] provides a potentially ground-breaking solution to such dilemmas. Aimed at equipping students with practical engineering skills supported by the necessary theoretical background, CDIO could potentially change the way engineering is perceived and experienced within higher education. Aston University introduced CDIO into its Mechanical Engineering and Design programmes in October 2011. From its induction, engineering education researchers have ‘shadowed’ the staff responsible for developing and teaching the programme. Utilising an Action Research Design, and adopting a mixed methodological research design, the researchers have worked closely with the teaching team to critically reflect on the processes involved in introducing CDIO into the curriculum. Concurrently, research has been conducted to capture students’ perspectives of CDIO. In evaluating the introduction of CDIO at Aston, the researchers have developed a distinctive research strategy with which to evaluate CDIO. It is the emergent findings from this research that form the basis of this paper. Although early-on in its development CDIO is making a significant difference to engineering education at the University. The paper draws attention to pedagogical, practical and professional issues – discussing each one in turn and in doing so critically analysing the value of CDIO from academic, student and industrial perspectives. The paper concludes by noting that whilst CDIO represents a forwardthinking approach to engineering education, the need for constant innovation in learning and teaching should not be forgotten. Indeed, engineering education needs to put itself at the forefront of pedagogic practice. Providing all-rounded engineers, ready to take on the challenges of the 21st Century!

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Direct-drive linear reciprocating compressors offer numerous advantages over conventional counterparts which are usually driven by a rotary induction motor via a crank shaft. However, to ensure efficient and reliable operation under all conditions, it is essential that motor current of a linear compressor follows a sinusoidal current command with a frequency which matches the system resonant frequency. The design of a high-performance current controller for linear compressor drive presents a challenge since the system is highly nonlinear, and an effective solution must be low cost. In this paper, a learning feed-forward current controller for the linear compressors is proposed. It comprises a conventional feedback proportional-integral controller and a feed-forward B-spline neural network (BSNN). The feed-forward BSNN is trained online and in real time in order to minimize the current tracking error. Extensive simulation and experiment results with a prototype linear compressor show that the proposed current controller exhibits high steady state and transient performance. © 2009 IEEE.

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Discovery of microRNAs (miRNAs) relies on predictive models for characteristic features from miRNA precursors (pre-miRNAs). The short length of miRNA genes and the lack of pronounced sequence features complicate this task. To accommodate the peculiarities of plant and animal miRNAs systems, tools for both systems have evolved differently. However, these tools are biased towards the species for which they were primarily developed and, consequently, their predictive performance on data sets from other species of the same kingdom might be lower. While these biases are intrinsic to the species, their characterization can lead to computational approaches capable of diminishing their negative effect on the accuracy of pre-miRNAs predictive models. We investigate in this study how 45 predictive models induced for data sets from 45 species, distributed in eight subphyla/classes, perform when applied to a species different from the species used in its induction. Results: Our computational experiments show that the separability of pre-miRNAs and pseudo pre-miRNAs instances is species-dependent and no feature set performs well for all species, even within the same subphylum/class. Mitigating this species dependency, we show that an ensemble of classifiers reduced the classification errors for all 45 species. As the ensemble members were obtained using meaningful, and yet computationally viable feature sets, the ensembles also have a lower computational cost than individual classifiers that rely on energy stability parameters, which are of prohibitive computational cost in large scale applications. Conclusion: In this study, the combination of multiple pre-miRNAs feature sets and multiple learning biases enhanced the predictive accuracy of pre-miRNAs classifiers of 45 species. This is certainly a promising approach to be incorporated in miRNA discovery tools towards more accurate and less species-dependent tools.

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IKK epsilon (IKKε) is induced by the activation of nuclear factor-κB (NF-κB). Whole-body IKKε knockout mice on a high-fat diet (HFD) were protected from insulin resistance and showed altered energy balance. We demonstrate that IKKε is expressed in neurons and is upregulated in the hypothalamus of obese mice, contributing to insulin and leptin resistance. Blocking IKKε in the hypothalamus of obese mice with CAYMAN10576 or small interfering RNA decreased NF-κB activation in this tissue, relieving the inflammatory environment. Inhibition of IKKε activity, but not TBK1, reduced IRS-1(Ser307) phosphorylation and insulin and leptin resistance by an improvement of the IR/IRS-1/Akt and JAK2/STAT3 pathways in the hypothalamus. These improvements were independent of body weight and food intake. Increased insulin and leptin action/signaling in the hypothalamus may contribute to a decrease in adiposity and hypophagia and an enhancement of energy expenditure accompanied by lower NPY and increased POMC mRNA levels. Improvement of hypothalamic insulin action decreases fasting glycemia, glycemia after pyruvate injection, and PEPCK protein expression in the liver of HFD-fed and db/db mice, suggesting a reduction in hepatic glucose production. We suggest that IKKε may be a key inflammatory mediator in the hypothalamus of obese mice, and its hypothalamic inhibition improves energy and glucose metabolism.

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Ecological science contributes to solving a broad range of environmental problems. However, lack of ecological literacy in practice often limits application of this knowledge. In this paper, we highlight a critical but often overlooked demand on ecological literacy: to enable professionals of various careers to apply scientific knowledge when faced with environmental problems. Current university courses on ecology often fail to persuade students that ecological science provides important tools for environmental problem solving. We propose problem-based learning to improve the understanding of ecological science and its usefulness for real-world environmental issues that professionals in careers as diverse as engineering, public health, architecture, social sciences, or management will address. Courses should set clear learning objectives for cognitive skills they expect students to acquire. Thus, professionals in different fields will be enabled to improve environmental decision-making processes and to participate effectively in multidisciplinary work groups charged with tackling environmental issues.

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studies have shown that rate of propofol infusion may influence the predicted propofol concentration at the effect site (Es). The aim of this study was to evaluate the Es predicted by the Marsh pharmacokinetic model (ke0 0.26min(-1)) in loss of consciousness during fast or slow induction. the study included 28 patients randomly divided into two equal groups. In slow induction group (S), target-controlled infusion (TCI) of propofol with plasma, Marsh pharmacokinetic model (ke0 0.26min(-1)) with target concentration (Tc) at 2.0-μg.mL(-1) were administered. When the predicted propofol concentration at the effect site (Es) reached half of Es value, Es was increased to previous Es + 1μg.mL(-1), successively, until loss of consciousness. In rapid induction group (R), patients were induced with TCI of propofol with plasma (6.0μg.ml(-1)) at Es, and waited until loss of consciousness. in rapid induction group, Tc for loss of consciousness was significantly lower compared to slow induction group (1.67±0.76 and 2.50±0.56μg.mL(-1), respectively, p=0.004). the predicted propofol concentration at the effect site for loss of consciousness is different for rapid induction and slow induction, even with the same pharmacokinetic model of propofol and the same balance constant between plasma and effect site.

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PURPOSE: To determine the mean critical fusion frequency and the short-term fluctuation, to analyze the influence of age, gender, and the learning effect in healthy subjects undergoing flicker perimetry. METHODS: Study 1 - 95 healthy subjects underwent flicker perimetry once in one eye. Mean critical fusion frequency values were compared between genders, and the influence of age was evaluated using linear regression analysis. Study 2 - 20 healthy subjects underwent flicker perimetry 5 times in one eye. The first 3 sessions were separated by an interval of 1 to 30 days, whereas the last 3 sessions were performed within the same day. The first 3 sessions were used to investigate the presence of a learning effect, whereas the last 3 tests were used to calculate short-term fluctuation. RESULTS: Study 1 - Linear regression analysis demonstrated that mean global, foveal, central, and critical fusion frequency per quadrant significantly decreased with age (p<0.05).There were no statistically significant differences in mean critical fusion frequency values between males and females (p>0.05), with the exception of the central area and inferonasal quadrant (p=0.049 and p=0.011, respectively), where the values were lower in females. Study 2 - Mean global (p=0.014), central (p=0.008), and peripheral (p=0.03) critical fusion frequency were significantly lower in the first session compared to the second and third sessions. The mean global short-term fluctuation was 5.06±1.13 Hz, the mean interindividual and intraindividual variabilities were 11.2±2.8% and 6.4±1.5%, respectively. CONCLUSION: This study suggests that, in healthy subjects, critical fusion frequency decreases with age, that flicker perimetry is associated with a learning effect, and that a moderately high short-term fluctuation is expected.

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PURPOSE: To evaluate the sensitivity and specificity of machine learning classifiers (MLCs) for glaucoma diagnosis using Spectral Domain OCT (SD-OCT) and standard automated perimetry (SAP). METHODS: Observational cross-sectional study. Sixty two glaucoma patients and 48 healthy individuals were included. All patients underwent a complete ophthalmologic examination, achromatic standard automated perimetry (SAP) and retinal nerve fiber layer (RNFL) imaging with SD-OCT (Cirrus HD-OCT; Carl Zeiss Meditec Inc., Dublin, California). Receiver operating characteristic (ROC) curves were obtained for all SD-OCT parameters and global indices of SAP. Subsequently, the following MLCs were tested using parameters from the SD-OCT and SAP: Bagging (BAG), Naive-Bayes (NB), Multilayer Perceptron (MLP), Radial Basis Function (RBF), Random Forest (RAN), Ensemble Selection (ENS), Classification Tree (CTREE), Ada Boost M1(ADA),Support Vector Machine Linear (SVML) and Support Vector Machine Gaussian (SVMG). Areas under the receiver operating characteristic curves (aROC) obtained for isolated SAP and OCT parameters were compared with MLCs using OCT+SAP data. RESULTS: Combining OCT and SAP data, MLCs' aROCs varied from 0.777(CTREE) to 0.946 (RAN).The best OCT+SAP aROC obtained with RAN (0.946) was significantly larger the best single OCT parameter (p<0.05), but was not significantly different from the aROC obtained with the best single SAP parameter (p=0.19). CONCLUSION: Machine learning classifiers trained on OCT and SAP data can successfully discriminate between healthy and glaucomatous eyes. The combination of OCT and SAP measurements improved the diagnostic accuracy compared with OCT data alone.

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Universidade Estadual de Campinas . Faculdade de Educação Física

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This study evaluated histopathologically different methods of experimental induction of periapical periodontitis. The radiographic and microbiological evaluations have been performed in a previous investigation. Fifty-seven root canals from dogs' teeth were assigned to 4 groups. In GI (n=14) and GII (n=14), the root canals were exposed to oral environment for 180 days; in GIII (n=14) and GIV (n=15) the root canals were exposed for 7 days and then the access cavities were restored and remained sealed for 53 days. The root apices of GI and GIII were perforated, whilst those of GII and GIV remained intact. After induction of periapical periodontitis, the dogs were euthanized. Serial sections were obtained and stained with hematoxylin and eosin. Data of the histopathological evaluation were submitted to Kruskal-Wallis and Dunn's tests at 5% significance level. The inflammatory periapical reaction and resorption of mineralized tissues were less intense in GII than in the other groups (p<0.05). There was no histopathological difference among the experimentally induced periapical lesions in the teeth with coronal sealing. On the other hand, when coronal sealing was not performed, greater intensity of induced periapical periodontitis was observed in the teeth with apical perforation.

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The aim of this study was to evaluate the microbial distribution in the root canal system after periapical lesion induction in dogs' teeth using different methods. Fifty-two root canals were assigned to 4 groups (n=13). Groups I and II: root canals were exposed to the oral cavity for 180 days; groups III and IV: root canals were exposed for 7 days and then the coronal openings were sealed for 53 days. The root apices of groups I and III were perforated, while those of groups II and IV remained intact. After the experimental periods, the animals were euthanized and the anatomic pieces containing the roots were processed and stained with the Brown & Brenn method to assess the presence and distribution of microorganisms. The incidence of microorganisms at different sites of the roots and periapical lesions was analyzed statistically by the chi-square test at 5% significance level. All groups presented microorganisms in the entire root canal system. A larger number of microorganisms was observed on the root canal walls, apical delta and dentinal tubules (p<0.05), followed by cementum and cemental resorption areas. In spite of the different periods of exposure to the oral environment, the methods used for induction of periapical periodontitis yielded similar distribution of microorganisms in the root canal system.

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OBJECTIVE: Despite the relevance of irritability emotions to the treatment, prognosis and classification of psychiatric disorders, the neurobiological basis of this emotional state has been rarely investigated to date. We assessed the brain circuitry underlying personal script-driven irritability in healthy subjects (n = 11) using functional magnetic resonance imaging. METHOD: Blood oxygen level-dependent signal changes were recorded during auditory presentation of personal scripts of irritability in contrast to scripts of happiness or neutral emotional content. Self-rated emotional measurements and skin conductance recordings were also obtained. Images were acquired using a 1,5T magnetic resonance scanner. Brain activation maps were constructed from individual images, and between-condition differences in the mean power of experimental response were identified by using cluster-wise nonparametric tests. RESULTS: Compared to neutral scripts, increased blood oxygen level-dependent signal during irritability scripts was detected in the left subgenual anterior cingulate cortex, and in the left medial, anterolateral and posterolateral dorsal prefrontal cortex (cluster-wise p-value < 0.05). While the involvement of the subgenual cingulate and dorsal anterolateral prefrontal cortices was unique to the irritability state, increased blood oxygen level-dependent signal in dorsomedial and dorsal posterolateral prefrontal regions were also present during happiness induction. CONCLUSION: Irritability induction is associated with functional changes in a limited set of brain regions previously implicated in the mediation of emotional states. Changes in prefrontal and cingulate areas may be related to effortful cognitive control aspects that gain salience during the emergence of irritability.

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In this study, we evaluated the expression of the Zenk protein within the nucleus taeniae of the pigeon’s amygdala (TnA) after training in a classical aversive conditioning, in order to improve our understanding of its functional role in birds. Thirty-two 18-month-old adult male pigeons (Columba livia), weighing on average 350 g, were trained under different conditions: with tone-shock associations (experimental group; EG); with shock-alone presentations (shock group; SG); with tone-alone presentations (tone group; TG); with exposure to the training chamber without stimulation (context group; CG), and with daily handling (naive group; NG). The number of immunoreactive nuclei was counted in the whole TnA region and is reported as density of Zenk-positive nuclei. This density of Zenk-positive cells in the TnA was significantly greater for the EG, SG and TG than for the CG and NG (P < 0.05). The data indicate an expression of Zenk in the TnA that was driven by experience, supporting the role of this brain area as a critical element for neural processing of aversive stimuli as well as meaningful novel stimuli.

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Diatraea saccharalis (Fabricius, 1794) (Lepidoptera: Crambidae) is an important pest for Brazilian sugarcane. In the present study, we detected two distinct spots in hemolymph from septic injured larvae (HDs1 and HDs2), which are separated by 2DE gel electrophoresis. Both spots were subjected to in-gel tryptic digestion and MALDI-TOF/TOF analysis, which revealed the sequence VFGTLGSDDSGLFGK present in both HDs1 and HDs2. This sequence had homology and 80% identity with specific Lepidoptera antimicrobial peptides called gloverins. Analyses using the ImageMaster 2D software showed pI 8.94 of the HDs1 spot, which is similar to that described to Hyalophora gloveri gloverin (pI 8.5). Moreover, the 14-kDa molecular mass of the spot HDs1 is compatible to that of gloverins isolated from the hemolymph of Trichoplusia ni, Helicoverpa armigera and H. gloveri. Antimicrobial assays with partially purified fractions containing the HDs1 and HDs2 polypeptides demonstrated activity against Escherichia coli. This is the first report of antimicrobial polypeptides in D. saccharalis, and the identification of these peptides may help in the generation of new strategies to control this pest.