Effects of elbow flexor muscle resistance training on strength, endurance and perceived exertion

Purpose. To verify the effects of resistance training at the electromyographic fatigue threshold (EMGFT) based on one-repetition maximum strength (1RM), heart rate (HR), rate of perceived exertion (PE) and endurance time (EndT). Methods. Nineteen subjects (training group [TG]: n = 10; control group [CG]: n = 9), performed 1-min bicep curl exercises sets at 25%, 30%, 35% and 40% 1RM. Electromyography (biceps brachii and brachiorradialis), HR and PE were registered. Biceps brachii EMGFT was used to create a load index for an eight-week resistance training programme (three sets until exhaustion/session, two sessions/week) for the TG. The CG only attended one session in the first week and another session in the last week of the eight-week training period for EndT measurement. EndT was determined from the number of repetitions of each of the three sets performed in the first and last training sessions. After training, 1RM, EMGFT, EndT, HR and PE at the different bicep curl load intensities were again measured for both groups. Results. Increases in 1RM (5.9%, p < 0.05) and EndT (> 60%, p < 0.001) after training were found. In addition, PE was reduced at all load intensities (p < 0.05), while no changes were found for HR and EMGFT after training. Conclusions. Strength-endurance training based on the EMGFT improved muscular endurance and also, to a lesser extent, muscular strength. Moreover, the reduced levels of physical exertion after training at the same intensity suggest that endurance training exercises may improve comfort while performing strength exercises.

Physiological adaptations during endurance training below anaerobic threshold in rats

To assess the effects of continuous exercise training at intensities corresponding to 80 and 90 % of the lactate minimum test (LM), we evaluated antioxidant activity, hormone concentration, biochemical analyses and aerobic and anaerobic performance, as well as glycogen stores, during 12 weeks of swimming training in rats. One-hundred rats were separated into three groups: control (CG, n = 40), exercise at 80 (EG80, n = 30) and 90 % (EG90, n = 30) of LM. The training lasted 12 weeks, with sessions of 60 min/day, 6 days/week. The intensity was based at 80 and 90 % of the LM. The volume did not differ between training groups (Ẋ of EG80 = 52 ± 4 min; Ẋ of EG90 = 56 ± 2 min). The glycogen concentration (mg/100 mg) in the gastrocnemius increased after the training in EG80 (0.788 ± 0.118) and EG90 (0.795 ± 0.157) in comparison to the control (0.390 ± 0.132). The glycogen stores in the soleus enhanced after the training in EG90 (0.677 ± 0.230) in comparison to the control (0.343 ± 0.142). The aerobic performance increased by 43 and 34 % for EG80 and EG90, respectively, in relation to baseline. The antioxidant enzymes remain unchanged during the training. Creatine kinase (U/L) increased after 8 weeks in both groups (EG80 = 427.2 ± 97.4; EG90 = 641.1 ± 90.2) in relation to the control (246.9 ± 66.8), and corticosterone (ng/mL) increased after 12 weeks in EG90 (539 ± 54) in comparison to the control (362 ± 44). The continuous exercise at 80 and 90 % of the LM has a marked aerobic impact on endurance performance without significantly biomarkers changes compared to control. © 2013 Springer-Verlag Berlin Heidelberg.

ECG arrhythmia classification based on optimum-path forest

An important tool for the heart disease diagnosis is the analysis of electrocardiogram (ECG) signals, since the non-invasive nature and simplicity of the ECG exam. According to the application, ECG data analysis consists of steps such as preprocessing, segmentation, feature extraction and classification aiming to detect cardiac arrhythmias (i.e.; cardiac rhythm abnormalities). Aiming to made a fast and accurate cardiac arrhythmia signal classification process, we apply and analyze a recent and robust supervised graph-based pattern recognition technique, the optimum-path forest (OPF) classifier. To the best of our knowledge, it is the first time that OPF classifier is used to the ECG heartbeat signal classification task. We then compare the performance (in terms of training and testing time, accuracy, specificity, and sensitivity) of the OPF classifier to the ones of other three well-known expert system classifiers, i.e.; support vector machine (SVM), Bayesian and multilayer artificial neural network (MLP), using features extracted from six main approaches considered in literature for ECG arrhythmia analysis. In our experiments, we use the MIT-BIH Arrhythmia Database and the evaluation protocol recommended by The Association for the Advancement of Medical Instrumentation. A discussion on the obtained results shows that OPF classifier presents a robust performance, i.e.; there is no need for parameter setup, as well as a high accuracy at an extremely low computational cost. Moreover, in average, the OPF classifier yielded greater performance than the MLP and SVM classifiers in terms of classification time and accuracy, and to produce quite similar performance to the Bayesian classifier, showing to be a promising technique for ECG signal analysis. © 2012 Elsevier Ltd. All rights reserved.

Digital proficiency and digital inclusion: Comparison between students of computer science, public relations and engineering

New information and communication technologies may be useful for providing more in-depth knowledge to students in many ways, whether through online multimedia educational material, or through online debates with colleagues, teachers and other area professionals in a synchronous or asynchronous manner. This paper focuses on participation in online discussion in e-learning courses for promoting learning. Although an important theoretical aspect, an analysis of literature reveals there are few studies evaluating the personal and social aspects of online course users in a quantitative manner. This paper aims to introduce a method for diagnosing inclusion and digital proficiency and other personal aspects of the student through a case study comparing Information System, Public Relations and Engineering students at a public university in Brazil. Statistical analysis and analysis of variances (ANOVA) were used as the methodology for data analysis in order to understand existing relations between the components of the proposed method. The survey methodology was also used, in its online format, as a research instrument. The method is based on using online questionnaires that diagnose digital proficiency and time management, level of extroversion and social skills of the students. According to the sample studied, there is no strong correlation between digital proficiency and individual characteristics tied to the use of time, level of extroversion and social skills of students. The differences in course grades for some components are partly due to subject 'Introduction to Economics' being offered to freshmen in Public Relations, whereas subject 'Economics in Engineering' is offered in the final semesters of Engineering and Information Systems courses. Therefore, the difference could be more tied to the respondent's age than to the course. Information Systems students were observed to be older, with access to computers and Internet at the workplace, compared to the other students who access the Internet more often from home. This paper presents a pilot study aimed at conducting a diagnosis that permits proposing actions for information and communication technology to contribute towards student education. Three levels of digital inclusion are described as a scale to measure whether information technology increases personal performance and professional knowledge and skills. This study may be useful for other readers interested in themes related to education in engineering. © 2013 IEEE.

Multilayer perceptron neural networks training through charged system search and its Application for non-technical losses detection

The non-technical loss is not a problem with trivial solution or regional character and its minimization represents the guarantee of investments in product quality and maintenance of power systems, introduced by a competitive environment after the period of privatization in the national scene. In this paper, we show how to improve the training phase of a neural network-based classifier using a recently proposed meta-heuristic technique called Charged System Search, which is based on the interactions between electrically charged particles. The experiments were carried out in the context of non-technical loss in power distribution systems in a dataset obtained from a Brazilian electrical power company, and have demonstrated the robustness of the proposed technique against with several others nature-inspired optimization techniques for training neural networks. Thus, it is possible to improve some applications on Smart Grids. © 2013 IEEE.

Aquatic Exercise is as Effective as dry Land Training to Blood Pressure Reduction in Postmenopausal Hypertensive Women

Background and Purpose: The evidence of the benefits from regular physical activity to hypertensives is based on dry land training studies. Therefore, the aim of this study is to compare the effect of aquatic exercise with dry land training on hypertensive women. Methods: This is a randomized controlled study with 52 post-menopausal hypertensive women. The patients were randomly allocated in three groups: water aerobic training group (n=19), dry land aerobic training group (n=19) and a non-intervention control group (n=14). The training protocol was performed by 12weeks. Results: There were no differences among the three groups concerning basal blood pressure (BP) and biochemical variables. In water group, there was a statistically significant reduction of systolic BP from 136±16mmHg at zero week to 124±18mm Hg at 11th week and 124±15mmHg at 12th week. In dry land training group, there was a statistically significant reduction of systolic BP from 138±15mmHg at zero week to 125±10mmHg at 7th week, 127±10mmHg at 10th week and 126±9mmHg at 12th week. The control group presented no change in any of the assessed variables. No changes were carried out in any antihypertensive medications during study. Discussion: This is a randomized controlled study that demonstrates the antihypertensive efficacy of aerobic aquatic exercise. © 2013 John Wiley & Sons, Ltd.

Evaluation report of the training workshop on the use of the module to analyse growth of international commerce (Magic Plus) and the competitive analysis of nations (TRADECAN 2009) software

The aim of the workshop was to provide a functional overview of the software package, to enable participants to use the software in order to inform more evidence-based trade strategies, and build capacity for researchers and trade negotiators to provide more rigorous, analytical policy research to inform future trade negotiations. Participants came from the ministries of trade of the following CDCC member countries: Dominica, Grenada, Jamaica, Saint Lucia, Saint Kitts and Nevis, Saint Vincent and the Grenadines, and Trinidad and Tobago. Representatives of the following regional institutions were represented: the Caribbean Community/Caribbean Regional Negotiating Mechanism (CARICOM/CRNM); the Organisation of Eastern Caribbean States (OECS); the University of Guyana, University of Suriname and the University of the West Indies (UWI). It was hoped the workshop would be a stepping stone towards more advanced trade analysis training. The list of participants appears as Annex I.

A path- and label-cost propagation approach to speedup the training of the optimum-path forest classifier

In general, pattern recognition techniques require a high computational burden for learning the discriminating functions that are responsible to separate samples from distinct classes. As such, there are several studies that make effort to employ machine learning algorithms in the context of big data classification problems. The research on this area ranges from Graphics Processing Units-based implementations to mathematical optimizations, being the main drawback of the former approaches to be dependent on the graphic video card. Here, we propose an architecture-independent optimization approach for the optimum-path forest (OPF) classifier, that is designed using a theoretical formulation that relates the minimum spanning tree with the minimum spanning forest generated by the OPF over the training dataset. The experiments have shown that the approach proposed can be faster than the traditional one in five public datasets, being also as accurate as the original OPF. (C) 2014 Elsevier B. V. All rights reserved.

Greening the work force in Brazilian hotels: The role of environmental training

BACKGROUND: Organizations are increasingly required to reduce their environmental impact through the adoption of environmental management, which requires the support of human resource practices.OBJECTIVE: The objective of this study is to determine whether human resource management practices, especially training, are supporting environmental management practices at four hotels located in Brazil.METHODS: This research is qualitative, based on the analysis of four hotels in Brazil.RESULTS: Based on the systematized empirical evidence collected from four hotels (Hotels A, B, C, and D), it can be concluded that: (1) human resource management is still not fully aligned with environmental objectives at the hotels studied; (2) only Hotel B has implemented environmental management practices and aligned with human resource management in a more developed manner, which may indicate that these two variables of analysis could have interrelations; (3) environmental training as a human resource management practice was verified in all hotels analyzed.CONCLUSIONS: The greening of human resources practices is not fully aligned with environmental objectives in the hotels studied. If these hotels really wish to "go green," environmental training will be necessary. Hotel stakeholders play a major role in implementing the greening of the hotel industry.

Harmony Search applied for Support Vector Machines Training Optimization

Since the beginning, some pattern recognition techniques have faced the problem of high computational burden for dataset learning. Among the most widely used techniques, we may highlight Support Vector Machines (SVM), which have obtained very promising results for data classification. However, this classifier requires an expensive training phase, which is dominated by a parameter optimization that aims to make SVM less prone to errors over the training set. In this paper, we model the problem of finding such parameters as a metaheuristic-based optimization task, which is performed through Harmony Search (HS) and some of its variants. The experimental results have showen the robustness of HS-based approaches for such task in comparison against with an exhaustive (grid) search, and also a Particle Swarm Optimization-based implementation.

Competência lexical na proficiência do professor de inglês como língua estrangeira: uma análise do teste oral do epple

Pós-graduação em Estudos Linguísticos - IBILCE

Effects of Water-Based and Callisthenic Exercise on Freezing of Gait, Postural Control, and Functional Independence in Patients With Mild to Moderate Parkinson Disease

Objective: This study aimed to analyze and compare the role of a water-based exercise program versus a combination of water and callisthenic exercises on postural control, functional independence, and freezing of gait (FOG) in patients with mild to moderate Parkinson disease.Methods: Twenty-five community-dwelling participants with idiopathic Parkinson disease were recruited. Of these, 9 participants took part in a water-based program of physical exercises and the other 16 participants took part in a combined program that consisted of callisthenic exercises plus an aquatic exercise session. Both programs were 16 weeks in duration. The clinical evaluation assessed the festination by means of the FOG score test; postural control was verified by means of the balance test of the short physical performance battery, and the Spanish validated version of the Unified Parkinson's Disease Rating Scale part 2 was used to assess functional independence. Participants were evaluated before and after 16 weeks of both proposed programs.Results: The results showed improvement in FOG for both groups, although a significant main effect was observed only in the patients who performed the callisthenic exercise plus an aquatic exercise program. Postural control did not show significant improvements after both proposed physical exercise programs as soon as functional autonomy. Our preliminary results suggest that training sessions with the combination of water plus callisthenic exercises may be a useful physical rehabilitation strategy for individuals with mild to moderate Parkinson disease who have FOG.

Environmental training and environmental management maturity of Brazilian companies with ISO14001: empirical evidence

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

A educação a distância e a formação continuada de professores de matemática: contribuições de um contexto formativo para a base de conhecimento docente

Pós-graduação em Educação - FCT

Effect of community-based physical exercise interventions carried out in primary helath care on plasma inflammatory biomarkers and cardiorespiratory fitness

Pós-graduação em Ciências da Motricidade - IBRC