824 resultados para training methods


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Objective: The purpose of this study was to investigate whether an endurance-strength training program is effective in reducing myoelectric manifestations of sternocleidomastoid (SCM) and anterior scalene (AS) muscle fatigue which have been found to be greater in people with chronic neck pain. Methods: Fifty-eight female patients with chronic non-severe neck pain were randomized into one of two 6-week exercise intervention groups: an endurance-strength training regime for the cervical flexor muscles or a referent exercise intervention involving low load retraining of the cranio-cervical flexor muscles. The primary outcomes were a change in maximum voluntary contraction (MVC) force and change of the initial value and rate of change of the mean frequency, average rectified value and conduction velocity detected from the SCM and AS muscles during sub-maximal isometric cervical flexion contractions at 50, 25 and 10% MVC. Results: At the 7th week follow-up assessment, the endurance-strength training group revealed a significant increase in MVC force and a reduction in the estimates of the initial value and rate of change of the mean frequency for both the SCM and AS muscles (P < 0.05). Both exercise groups reported a reduced average intensity of neck pain and reduced neck disability index score (P < 0.05). Conclusions: An endurance-strength exercise regime for the cervical flexor muscles is effective in reducing myoelectric manifestations of superficial cervical flexor muscle fatigue as well as increasing cervical flexion strength in a group of patients with chronic non-severe neck pain. Significance: Provision of load to challenge the neck flexor muscles is required to reduce the fatigability of the SCM and AS muscles in people with neck pain. Improvements in cervical muscle strength and reduced fatigability may be responsible for the reported efficacy with this type of exercise program. (c) 2006 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All fights reserved.

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OBJECTIVE - The purpose of this study was to determine whether beneficial effects on glycemic control of an initial laboratory-supervised resistance training program could be sustained through a community center-based maintenance program. RESEARCH DESIGN AND METHODS - We studied 57 overweight (BMI >= 27 kg/m(2)) sedentary men and women aged 40-80 years with established (> 6 months) type 2 diabetes. initially, all participants attended a twice-weekly 2-month supervised resistance training program conducted in the exercise laboratory. Thereafter, participants undertook a resistance training maintenance program (2 times/week) for 12 months and were randomly assigned to carry this out either in a community fitness and recreation center (center) or in their domestic environment (home). Glycemic control (HbA(1c) [A1C]) was assessed at 0, 2, and 14 months. RESULTS - Pooling data from the two groups for the 2-month supervised resistance training program showed that compared with baseline, mean A1C fell by -0.4% [95% CI -0.6 to -0.2]. Within-group comparisons showed that A I C remained lower than baseline values at 14 months in the center group (- 0.4% [-0.7 to -0.03]) but not in the home group (-0.1% [-0.4 to 0.3]). However, no between-group differences were observed at each time point. Changes in AIC during the maintenance period were positively associated with exercise adherence in the center group only. CONCLUSIONS - Center-based but not home-based resistance training was associated with the maintenance of modestly improved glycemic control from baseline, which was proportional to program adherence. Our findings emphasize the need to develop and test behavioral methods to promote healthy lifestyles including increased physical activity in adults with type 2 diabetes.

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Background: Currently 1 in 11 women over the age of 60 in Australia are diagnosed with breast cancer. Following treatment, most breast cancer patients are left with shoulder and arm impairments which can impact significantly on quality of life and interfere substantially with activities of daily living. The primary aim of the proposed study is to determine whether upper limb impairments can be prevented by undertaking an exercise program of prolonged stretching and resistance training, commencing soon after surgery. Methods/design: We will recruit 180 women who have had surgery for early stage breast cancer to a multicenter single-blind randomized controlled trial. At 4 weeks post surgery, women will be randomly assigned to either an exercise group or a usual care ( control) group. Women allocated to the exercise group will perform exercises daily, and will be supervised once a week for 8 weeks. At the end of the 8 weeks, women will be given a home-based training program to continue indefinitely. Women in the usual care group will receive the same care as is now typically provided, i.e. a visit by the physiotherapist and occupational therapist while an inpatient, and receipt of pamphlets. All subjects will be assessed at baseline, 8 weeks, and 6 months later. The primary measure is arm symptoms, derived from a breast cancer specific questionnaire (BR23). In addition, range of motion, strength, swelling, pain and quality of life will be assessed. Discussion: This study will determine whether exercise commencing soon after surgery can prevent secondary problems associated with treatment of breast cancer, and will thus provide the basis for successful rehabilitation and reduction in ongoing problems and health care use. Additionally, it will identify whether strengthening exercises reduce the incidence of arm swelling. Trial Registration: The protocol for this study is registered with the Australian Clinical Trials Registry (ACTRN012606000050550).

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Purpose: To examine the effect of progressive resistance training on muscle function, functional performance, balance, body composition, and muscle thickness in men receiving androgen deprivation for prostate cancer. Methods: Ten men aged 59-82 yr on androgen deprivation for localized prostate cancer undertook progressive resistance training for 20 wk at 6- to 12-repetition maximum (RM) for 12 upper- and lower-body exercises in a university exercise rehabilitation clinic. Outcome measures included muscle strength and muscle endurance for the upper and lower body, functional performance (repeated chair rise, usual and fast 6-m walk, 6-m backwards walk, stair climb, and 400-m walk time), and balance by sensory organization test. Body composition was measured by dual-energy x-ray absorptiometry and muscle thickness at four anatomical sites by B-mode ultrasound. Blood samples were assessed for prostate specific antigen (PSA), testosterone, growth hormone (GH), cortisol, and hemoglobin. Results: Muscle strength (chest press, 40.5%; seated row, 41.9%; leg press, 96.3%; P < 0.001) and muscle endurance (chest press, 114.9%; leg press, 167.1%; P < 0.001) increased significantly after training. Significant improvement (P < 0.05) occurred in the 6-m usual walk (14.1%), 6-m backwards walk (22.3%), chair rise (26.8%), stair climbing (10.4%), 400-m walk (7.4%), and balance (7.8%). Muscle thickness increased (P < 0.05) by 15.7% at the quadriceps site. Whole-body lean mass was preserved with no change in fat mass. There were no significant changes in PSA, testosterone, GH, cortisol, or hemoglobin. Conclusions: Progressive resistance exercise has beneficial effects on muscle strength, functional performance and balance in older men receiving androgen deprivation for prostate cancer and should be considered to preserve body composition and reduce treatment side effects.

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Erythrocytes transport oxygen to tissues and exercise-induced oxidative stress increases erythrocyte damage and turnover. Increased use of antioxidant supplements may alter protective erythrocyte antioxidant mechanisms during training. Aim of study: To examine the effects of antioxidant supplementation, (alpha-lipoic acid and a-tocopherol) and/or endurance training on the antioxidant defenses of erythrocytes. Methods: Young male Wistar rats were. assigned to (1) sedentary; (2) sedentary and antioxidant-supplemented; (3) endurance-trained; or (4) endurance-trained and antioxidant-supplemented groups for 14 weeks. Erythrocyte superoxide dismutase (SOD), glutathione peroxidase (GPX), and catalase (CAT) activities, and plasma malondialdehyde (MDA) were then measured. Results: Antioxidant supplementation had no significant effect (p > 0.05) on activities of antioxidant enzymes in sedentary animals. Similarly, endurance training alone also bad no effect (p > 0.05). GPX (125.9 2.8 vs. 121.5 3.0 U.gHb(-1), p < 0.05) and CAT (6.1 0.2 vs. 5.6 0.2 U.mgHb-1, p < 0.05) activities were increased in supplemented trained animals compared to non-supplemented sedentary animals whereas SOD (61.8 4.3 vs. 52.0 5.2 U.mgHb(-1), p < 0.05) activity was decreased. Plasma MDA was not different among groups (p > 0.05). Conclusions: In a rat model, the combination of exercise training and antioxidant supplementation increased antioxidant enzyme activities (GPX, CAT) compared with each individual intervention.

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This presentation outlines the results of an eighteen month study examining the effect of an emotions focused training intervention on the emotional intelligence of employees from a large public sector organisation. Utilising an experimental methodology, 280 staff attended a two-day program focused on training emotional intelligence skills and abilities. These interventions were created around Mayer and Salovey’s four-branch model of emotional intelligence (awareness, understanding, facilitation and management of emotions). The experimental group’s emotional intelligence was tested pre and post training using the Workgroup Emotional Intelligence Profile (WEIP). In addition, a control group from the same organisation also completed the same measure at three points during the same eighteen month period. Analysis of the control and experimental group data were conducted, and whilst no changes were found in the control group, the experimental group’s overall emotional intelligence significantly improved post training. To further strengthen these findings, a measure of effect size using Cohen’s d was also conducted to assess the magnitude of the training intervention’s overall effect. Full results will be presented during the presentation, with feedback on the study and methods utilised encouraged from participants.

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It is well known that resistance training improves muscle strength in older adults and may enhance or preserve functional performance. However, it is unclear if the volume of work undertaken in the elderly alters the response in functional performance. PURPOSE: To investigate the effect of a high- versus low-volume resistance training program on functional performance in older adults. METHODS: Thirty-two healthy men and women aged 65-78 years were randomly assigned to either a single-set (SS, n = 16) or 3-set (MS, n = 16) progressive resistance training program for 20 weeks. Groups trained 2 days per week using machine weights at 8 repetitions maximum (8-RM) for 7 upper and lower body exercises. Muscle strength was assessed by the 1-RM and functional performance by a battery of tests (repeated chair rise, usual and fast 6-m walk, 6-m backwards walk, floor rise to standing, stair climb, and 400-m walk time). RESULTS: Twenty-eight subjects completed the study. There was no difference between groups at baseline in muscle strength or functional performance. Whole body muscle strength significantly increased in both groups with greater gains in the 3-set group (MS 32.9 ± 3.1%; SS 18.6 ± 2.7%, mean ± SE; P < 0.01). Significant improvement (time effect, P < 0.01) occurred for both groups in the chair rise (MS 13.6 ± 3.2%; SS 10.2 ± 3.0%), 6-m backwards walk (MS 14.9 ± 3.3%; SS 14.3 ± 4.2%), stair climb (MS 6.4 ± 2.8%; SS 7.7 ± 3.1%) and 400-m walk (MS 7.4 ± 1.4%; SS 3.9 ± 1.2%). There were no interaction (group × time) effects for functional performance and no differences by sex. CONCLUSION: Resistance training that utilizes either a singleset or 3-set regimen may significantly and similarly improve functional performance in community-dwelling older adults. Enhancement of functional performance may prolong independence and improve quality of life. ©2004The American College of Sports Medicine

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Background: Determination of the subcellular location of a protein is essential to understanding its biochemical function. This information can provide insight into the function of hypothetical or novel proteins. These data are difficult to obtain experimentally but have become especially important since many whole genome sequencing projects have been finished and many resulting protein sequences are still lacking detailed functional information. In order to address this paucity of data, many computational prediction methods have been developed. However, these methods have varying levels of accuracy and perform differently based on the sequences that are presented to the underlying algorithm. It is therefore useful to compare these methods and monitor their performance. Results: In order to perform a comprehensive survey of prediction methods, we selected only methods that accepted large batches of protein sequences, were publicly available, and were able to predict localization to at least nine of the major subcellular locations (nucleus, cytosol, mitochondrion, extracellular region, plasma membrane, Golgi apparatus, endoplasmic reticulum (ER), peroxisome, and lysosome). The selected methods were CELLO, MultiLoc, Proteome Analyst, pTarget and WoLF PSORT. These methods were evaluated using 3763 mouse proteins from SwissProt that represent the source of the training sets used in development of the individual methods. In addition, an independent evaluation set of 2145 mouse proteins from LOCATE with a bias towards the subcellular localization underrepresented in SwissProt was used. The sensitivity and specificity were calculated for each method and compared to a theoretical value based on what might be observed by random chance. Conclusion: No individual method had a sufficient level of sensitivity across both evaluation sets that would enable reliable application to hypothetical proteins. All methods showed lower performance on the LOCATE dataset and variable performance on individual subcellular localizations was observed. Proteins localized to the secretory pathway were the most difficult to predict, while nuclear and extracellular proteins were predicted with the highest sensitivity.

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Mixture Density Networks (MDNs) are a well-established method for modelling the conditional probability density which is useful for complex multi-valued functions where regression methods (such as MLPs) fail. In this paper we extend earlier research of a regularisation method for a special case of MDNs to the general case using evidence based regularisation and we show how the Hessian of the MDN error function can be evaluated using R-propagation. The method is tested on two data sets and compared with early stopping.

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We are concerned with the problem of image segmentation in which each pixel is assigned to one of a predefined finite number of classes. In Bayesian image analysis, this requires fusing together local predictions for the class labels with a prior model of segmentations. Markov Random Fields (MRFs) have been used to incorporate some of this prior knowledge, but this not entirely satisfactory as inference in MRFs is NP-hard. The multiscale quadtree model of Bouman and Shapiro (1994) is an attractive alternative, as this is a tree-structured belief network in which inference can be carried out in linear time (Pearl 1988). It is an hierarchical model where the bottom-level nodes are pixels, and higher levels correspond to downsampled versions of the image. The conditional-probability tables (CPTs) in the belief network encode the knowledge of how the levels interact. In this paper we discuss two methods of learning the CPTs given training data, using (a) maximum likelihood and the EM algorithm and (b) emphconditional maximum likelihood (CML). Segmentations obtained using networks trained by CML show a statistically-significant improvement in performance on synthetic images. We also demonstrate the methods on a real-world outdoor-scene segmentation task.

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Objectives — To map the tasks, activities and training provision for primary care pharmacists (PCPs) and to identify perceived future training needs. Methods — Survey undertaken in 1998/1999 using a pre-piloted, postal, self-completion questionnaire to two samples of PCPs. Setting — PCPs in (a) the West Midlands and (b) England (outside West Midlands). Key findings — The response rate was 66 per cent. A majority (68 per cent) had worked in the role for less than two years. Eighty per cent had some form of continuing education or training for the role although only 50 per cent had a formal qualification. Over two-thirds had contributed to the funding of their training, with one-third providing all funding. Seventy-four per cent of PCPs agreed that pharmacists should go through a procedure to ensure competence (accreditation) before being allowed to work for a general medical practice or primary care group. Views on the need for formal education/training prior to work differed: 82 per cent of those with formal qualifications, but only 46 per cent of those without, considered that this should be a requirement. There was general agreement that training/education had met training needs. Views on future training closely reflected previous training experiences, with a focus upon pharmaceutical roles rather than upon generic skill development and the acquisition of management skills. Conclusions — The study provides a snapshot in time of the experience of pioneer PCPs and the training available to them. PCPs will need further training or updating if they are to provide the wider roles required by the developing needs of the National Health Service. Consideration should be given to formal recognition of the training of PCPs in order to assure competence. The expectation that pharmacists should fund their own training is likely to be a barrier to uptake of training and uncertainties over funding will militate against consistency of training.

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Background: Early, intensive phonological awareness and phonics training is widely held to be beneficial for children with poor phonological awareness. However, most studies have delivered this training separately from children's normal whole-class reading lessons. Aims: We examined whether integrating this training into whole class, mixed-ability reading lessons could impact on children with poor phonological awareness, whilst also benefiting normally developing readers. Sample: Teachers delivered the training within a broad reading programme to whole classes of children from Reception to the end of Year 1 (N=251). A comparison group of children received standard teaching methods (N=213). Method: Children's literacy was assessed at the beginning of Reception, and then at the end of each year until 1 year post-intervention. Results: The strategy significantly impacted on reading performance for normally developing readers and those with poor phonological awareness, vastly reducing the incidence of reading difficulties from 20% in comparison schools to 5% in intervention schools. Conclusions: Phonological and phonics training is highly effective for children with poor phonological awareness, even when incorporated into whole-class teaching.

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This thesis introduces a flexible visual data exploration framework which combines advanced projection algorithms from the machine learning domain with visual representation techniques developed in the information visualisation domain to help a user to explore and understand effectively large multi-dimensional datasets. The advantage of such a framework to other techniques currently available to the domain experts is that the user is directly involved in the data mining process and advanced machine learning algorithms are employed for better projection. A hierarchical visualisation model guided by a domain expert allows them to obtain an informed segmentation of the input space. Two other components of this thesis exploit properties of these principled probabilistic projection algorithms to develop a guided mixture of local experts algorithm which provides robust prediction and a model to estimate feature saliency simultaneously with the training of a projection algorithm.Local models are useful since a single global model cannot capture the full variability of a heterogeneous data space such as the chemical space. Probabilistic hierarchical visualisation techniques provide an effective soft segmentation of an input space by a visualisation hierarchy whose leaf nodes represent different regions of the input space. We use this soft segmentation to develop a guided mixture of local experts (GME) algorithm which is appropriate for the heterogeneous datasets found in chemoinformatics problems. Moreover, in this approach the domain experts are more involved in the model development process which is suitable for an intuition and domain knowledge driven task such as drug discovery. We also derive a generative topographic mapping (GTM) based data visualisation approach which estimates feature saliency simultaneously with the training of a visualisation model.

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This thesis covers two major aspects of pharmacy education; undergraduate education and pre-registration training. A cohort of pharmacy graduates were surveyed over a period of four years, on issues related to undergraduate education, pre-registration training and continuing education. These graduates were the first-ever to sit the pre-registration examination. In addition, the opinions of pre-registration tutors were obtained on pre-registration training, during the year that competence-based assessment was introduced. It was concluded that although the undergraduate course provided a broad base of knowledge suitable for graduates in all branches of pharmacy, several issues were identified which would require attention in future developments of the course. These were: 1. the strong support for the expansion of clinical, social and practice-based teaching. 2. the strong support to retain the scientific content to the same extent as in the three-year course. 3. a greater use of problem-based learning methods. The graduates supported the provision of a pre-registration continuing education course to help prepare for the examination and in areas inadequately covered in the undergraduate course. There was also support for the introduction of some form of split branch training. There was no strong evidence to suggest that the training had been an application of undergraduate education. In general, competence-based training was well regarded by tutors as an appropriate and effective method of skill assessment. However, community tutors felt it was difficult to carry out effectively due to day-to-day time constraints. The assistant tutors in hospital pharmacy were found to have a very important role in provision of training, and should be adequately trained and supported. The study recommends the introduction of uniform training and a quality assurance mechanism for all tutors and assistants undertaking this role.

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Sentiment analysis concerns about automatically identifying sentiment or opinion expressed in a given piece of text. Most prior work either use prior lexical knowledge defined as sentiment polarity of words or view the task as a text classification problem and rely on labeled corpora to train a sentiment classifier. While lexicon-based approaches do not adapt well to different domains, corpus-based approaches require expensive manual annotation effort. In this paper, we propose a novel framework where an initial classifier is learned by incorporating prior information extracted from an existing sentiment lexicon with preferences on expectations of sentiment labels of those lexicon words being expressed using generalized expectation criteria. Documents classified with high confidence are then used as pseudo-labeled examples for automatical domain-specific feature acquisition. The word-class distributions of such self-learned features are estimated from the pseudo-labeled examples and are used to train another classifier by constraining the model's predictions on unlabeled instances. Experiments on both the movie-review data and the multi-domain sentiment dataset show that our approach attains comparable or better performance than existing weakly-supervised sentiment classification methods despite using no labeled documents.