20 resultados para seminar-based training


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PURPOSE: To evaluate the effect of inspiratory muscle training (IMT) on cardiac autonomic modulation and on peripheral nerve sympathetic activity in patients with chronic heart failure (CHF). METHODS: Functional capacity, low-frequency (LF) and high-frequency (HF) components of heart rate variability, muscle sympathetic nerve activity inferred by microneurography, and quality of life were determined in 27 patients with CHF who had been sequentially allocated to 1 of 2 groups: (1) control group (with no intervention) and (2) IMT group. Inspiratory muscle training consisted of respiratory exercises, with inspiratory threshold loading of seven 30-minute sessions per week for a period of 12 weeks, with a monthly increase of 30% in maximal inspiratory pressure (PImax) at rest. Multivariate analysis was applied to detect differences between baseline and followup period. RESULTS: Inspiratory muscle training significantly increased PImax (59.2 +/- 4.9 vs 87.5 +/- 6.5 cmH(2)O, P = .001) and peak oxygen uptake (14.4 +/- 0.7 vs 18.9 +/- 0.8 mL.kg(-1).min(-1), P = .002); decreased the peak ventilation (V. E) +/- carbon dioxide production (V-CO2) ratio (35.8 +/- 0.8 vs 32.5 +/- 0.4, P = .001) and the (V) over dotE +/-(V) over dotCO(2) slope (37.3 +/- 1.1 vs 31.3 +/- 1.1, P = .004); increased the HF component (49.3 +/- 4.1 vs 58.4 +/- 4.2 normalized units, P = .004) and decreased the LF component (50.7 +/- 4.1 vs 41.6 +/- 4.2 normalized units, P = .001) of heart rate variability; decreased muscle sympathetic nerve activity (37.1 +/- 3 vs 29.5 +/- 2.3 bursts per minute, P = .001); and improved quality of life. No significant changes were observed in the control group. CONCLUSION: Home-based IMT represents an important strategy to improve cardiac and peripheral autonomic controls, functional capacity, and quality of life in patients with CHF.

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Purpose. To use a randomized design to evaluate the effectiveness of voice training programs for telemarketers via multidimensional analysis. Methods. Forty-eight telemarketers were randomly assigned to two groups: voice training group (n = 14) who underwent training over an 8-week period and a nontraining control group (n = 34). Before and after training, recordings of the sustained vowel /epsilon/ and connected were collected for acoustic and perceptual analyses. Results. Based on pre- and posttraining comparisons, the voice training group presented with a significant reduction in percent jitter (P = 0.044). No other significant differences were observed, and inter-rater reliability varied from poor to fair. Conclusions. These findings suggest that voice training improved a single acoustic dimension, but do not change perceptual dimension of telemarketers' voices.

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ABSTRACT: Purpose: To describe a research-based global curriculum in speech-language pathology and audiology that is part of a funded cross-linguistic consortium among 2 U.S. and 2 Brazilian universities. Method: The need for a global curriculum in speechlanguage pathology and audiology is outlined, and different funding sources are identified to support development of a global curriculum. The U.S. Department of Education’s Fund for the Improvement of Post-Secondary Education (FIPSE), in conjunction with the Brazilian Ministry of Education (Fundacao Coordenacao de Aperfeicoamento de Pessoal de Nivel Superior; CAPES), funded the establishment of a shared research curriculum project, “Consortium for Promoting Cross-Linguistic Understanding of Communication Disabilities in Children” for East Tennessee State University and the University of Northern Iowa and 2 Brazilian universities (Universidade Federal de Santa Maria and Universidade de São Paulo-Baurú). Results: The goals and objectives of the research-based global curriculum are summarized, and a description of an Internet-based course, “Different Languages, One World,” is provided Conclusion: Partnerships such as the FIPSE–CAPES consortium provide a foundation for training future generations of globally and research-prepared practitioners in speechlanguage pathology and audiology.

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Background: In epidemiological surveys, a good reliability among the examiners regarding the caries detection method is essential. However, training and calibrating those examiners is an arduous task because it involves several patients who are examined many times. To facilitate this step, we aimed to propose a laboratory methodology to simulate the examinations performed to detect caries lesions using the International Caries Detection and Assessment System (ICDAS) in epidemiological surveys. Methods: A benchmark examiner conducted all training sessions. A total of 67 exfoliated primary teeth, varying from sound to extensive cavitated, were set in seven arch models to simulate complete mouths in primary dentition. Sixteen examiners (graduate students) evaluated all surfaces of the teeth under illumination using buccal mirrors and ball-ended probe in two occasions, using only coronal primary caries scores of the ICDAS. As reference standard, two different examiners assessed the proximal surfaces by direct visual inspection, classifying them in sound, with non-cavitated or with cavitated lesions. After, teeth were sectioned in the bucco-lingual direction, and the examiners assessed the sections in stereomicroscope, classifying the occlusal and smooth surfaces according to lesion depth. Inter-examiner reproducibility was evaluated using weighted kappa. Sensitivities and specificities were calculated at two thresholds: all lesions and advanced lesions (cavitated lesions in proximal surfaces and lesions reaching the dentine in occlusal and smooth surfaces). Conclusion: The methodology purposed for training and calibration of several examiners designated for epidemiological surveys of dental caries in preschool children using the ICDAS is feasible, permitting the assessment of reliability and accuracy of the examiners previously to the survey´s development.

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Semi-supervised learning is a classification paradigm in which just a few labeled instances are available for the training process. To overcome this small amount of initial label information, the information provided by the unlabeled instances is also considered. In this paper, we propose a nature-inspired semi-supervised learning technique based on attraction forces. Instances are represented as points in a k-dimensional space, and the movement of data points is modeled as a dynamical system. As the system runs, data items with the same label cooperate with each other, and data items with different labels compete among them to attract unlabeled points by applying a specific force function. In this way, all unlabeled data items can be classified when the system reaches its stable state. Stability analysis for the proposed dynamical system is performed and some heuristics are proposed for parameter setting. Simulation results show that the proposed technique achieves good classification results on artificial data sets and is comparable to well-known semi-supervised techniques using benchmark data sets.