989 resultados para Training Technique


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Introduction: This article aims to show an alternative intervention for the prevention and control of back pain to the people of a production plant of geotextiles for the construction exposed to handling and awkward postures through the implementation of the Back School using the CORE technique. This technique being understood as trainer of the stability musculature of the spine; whose benefit is proportionate the muscular complex of the back, stability and avoid osteomuscular lesions and improved posture. Objective: To present the results about the implementation of the back school by the CORE technique for prevention of back pain in a population of forty-eight male collaborators. Materials and methods: The back school began with talks of awareness by the occupational health physician explaining the objectives and benefits of it to all participants. Once this activity was done, was continued to evaluate all plant employees to establish health status through the PAR-Q questionnaire, who were surveyed for the perception of pain using visual analog scale (VAS) and stability was determined column through the CORE assessment, to determine the training plan. Then, were made every six months the revaluations and implementation of a survey of assistant public perception to identify the impact of the implementation of the school back on the two variables referred (pain perception and stability of column). Results: The pain perception according VAS increased in the number of workers asymptomatic in 12% and based in the satisfaction survey 94% of population reported that with the development of this technique decrease the muscle fatigue in lumbar level; and 96% of population reported an improvement in the performance of their work activities. Discussion: Posterior to the analysis of all results, it is interpreted that back schools practice through CORE technique, contributes to the prevention and / or control of symptoms at the lumbar level in population of productive sector exposed to risks derived from the physical load, provided that ensure its continuously development and supervised for a competent professional.

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This paper details a technique for training auditory memory for length of speech sounds in preschool children with a profound hearing loss.

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Presents a technique for incorporating a priori knowledge from a state space system into a neural network training algorithm. The training algorithm considered is that of chemotaxis and the networks being trained are recurrent neural networks. Incorporation of the a priori knowledge ensures that the resultant network has behaviour similar to the system which it is modelling.

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This paper reports part of a qualitative study into evolving practice in the implementation of the Dispute Adjudication Board (DAB) construction dispute resolution technique, a variant of the Dispute Review Board (DRB) concept used in the US and Canada. Data was collected through a focus group interview of 20 highly experienced dispute resolution practitioners from engineering and the law. The group was assembled from members of FIDIC-NET with direct experience of project DABs. The part reported here concerns practice and procedure for establishing DABs. The main findings are that: constitution of the DABs is often delayed because of either project owners' ignorance of the DAB process or deterrence by the cost of the DABs; such owners also tend to insist on appointing DAB members from local engineers and lawyers without sufficient understanding of the DAB process; rates of remuneration of DAB members vary widely; the training provision for DAB membership and advocacy skills is inadequate; the process of selecting candidates for DAB membership and negotiating the tripartite agreement between each member and the contractual parties needs to be navigated with great care to avoid raising ethical problems. The research contribution is threefold. First, it highlights the importance of realistic fees for DAB members within a standard framework in achieving timely establishment of a board that works well as a team. Second, it illustrates the use of qualitative focus group interview to study the impact of new contract terms from multiple stakeholder perspectives. Finally, it identifies areas where further research is needed.

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The tissue microarray (TMA) technique allows multiple tissue samples in a single block. Commercial adhesive tape is used to avoid the loss of tissue samples during the immunostaining process. Few reports exist in the literature comparing the use of these adhesive tapes to other adhesive techniques. The objective of this study was to compare loss of sections adhered to slides using commercial adhesive tapes versus using silanized only slides. TMA was constructed with varying tissues using a fixed-base device (Beecher Instruments), placing 108 cylinders of 1 mm diameter in duplicate, spaced 1.2 mm apart. Section of 4 mu m were cut from the TMA block and adhered to 30 silanized slides and 30 commercial glass slides using adhesive tape, according to manufacturer's recommendations. Vimentin immunoexpression was evaluated by immunohistochemistry. Antigenic recovery was realized in citrate buffer using a microwave oven. Cylinder loss in the immunohistochemical process was quantified and expressed as: total (>80%), almost complete (75-79%), or partial (50-74%). The commercial adhesive tape group presented lesser total loss (1.1 versus 6.4%), almost complete loss (2.2 versus 3.5%), and partial loss (2.1 versus 3.8%) than the silanized slide group (ANOVA, P < 0.05). The sum of total and almost complete losses in the silanized slide group was 9.9%, greater than the losses in slides using commercial adhesive tapes (3.3%) and less than reported and considered acceptable in the literature (10-30%). In conclusion, the use of silanized only slides presents very satisfactory results, requires less training, and reduces costs significantly, thus justifying their use in research.

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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

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This work describes an application of a multilayer perceptron neural network technique to correct dome emission effects on longwave atmospheric radiation measurements carried out using an Eppley Precision Infrared Radiometer (PIR) pyrgeometer. It is shown that approximately 7-month-long measurements of dome and case temperatures and meteorological variables available in regular surface stations (global solar radiation, air temperature, and air relative humidity) are enough to train the neural network algorithm and correct the observed longwave radiation for dome temperature effects in surface stations with climates similar to that of the city of São Paulo, Brazil. The network was trained using data from 15 October 2003 to 7 January 2004 and verified using data, not present during the network-training period, from 8 January to 30 April 2004. The longwave radiation values generated by the neural network technique were very similar to the values obtained by Fairall et al., assumed here as the reference approach to correct dome emission effects in PIR pyrgeometers. Compared to the empirical approach the neural network technique is less limited to sensor type and time of day (allows nighttime corrections).

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Background: We describe an experimental model for transanal endorectal pull-through surgery using the method of de]a Torre and Ortega that can be used for training purposes in experimental laboratories.Methods: Ten rabbits were submitted to the transanal endorectal pull-through technique of de la Torre and Ortega. Animals were randomly selected in the Botucatu School of Medicine experimental laboratory. Animals weighted between 2800 and 4400 g. Colons were not prepared, and antibiotic therapy was not used; dipyrone(1) was administered postoperatively for analgesic purposes. We standardized resected segment size, recorded surgical time, and observed Survival and possible complications for 1 month.Results: All animals survived the initial follow-up period without infection. Bowel movements returned quickly, and all animals were evacuating regularly within the first 24 hours. Mean surgical time was 48.6 minutes.Conclusions: the experimental model proposed in this study is very useful for training and improving surgical techniques using the method of de la Torre and Ortega. The rabbit is an excellent animal for this surgery because of its size and postoperative resistance. (c) 2005 Elsevier B.V. All rights reserved.

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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Background: Because of ethical and medico-legal aspects involved in the training of cutaneous surgical skills on living patients, human cadavers and living animals, it is necessary the search for alternative and effective forms of training simulation. Aims: To propose and describe an alternative methodology for teaching and learning the principles of cutaneous surgery in a medical undergraduate program by using a chicken-skin bench model. Materials and Methods: One instructor for every four students, teaching materials on cutaneous surgical skills, chicken trunks, wings, or thighs, a rigid platform support, needled threads, needle holders, surgical blades with scalpel handles, rat-tooth tweezers, scissors, and marking pens were necessary for training simulation. Results: A proposal for simulation-based training on incision, suture, biopsy, and on reconstruction techniques using a chicken-skin bench model distributed in several sessions and with increasing levels of difficultywas structured. Both feedback and objective evaluations always directed to individual students were also outlined. Conclusion: The teaching of a methodology for the principles of cutaneous surgery using a chicken-skin bench model versatile, portable, easy to assemble, and inexpensive is an alternative and complementary option to the armamentarium of methods based on other bench models described. © Indian Journal of Dermatology 2013.

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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.

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Purpose: To apply the technique of Isostretching in a group of people over age 50 years and compare the flexibility of the posterior muscular chain before and after treatment, observing whether there was improvement in quality of life after the end of the sessions. Method: Eleven healthy and sedentary people from 51 to 74 years old participated in the study, which was conducted in Brazil. To evaluate the flexibility we applied the SF-36 questionnaire and test flexion of the spine before and after the study. Eight domains were accessed with the scores ranging form zero to one hundred. Results And Discussion:The technique was effective to gain flexibility of the posterior muscle group, which results in better quality of life for the participants. The results show that the domains related to physical health obtained the highest scores (“functional capacity”, “limitation in physical aspects” and “pain”). These aspects are strongly emphasised in a physical therapy treatment.

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Background: Exercise training is a non-pharmacological strategy for treatment of heart failure. Exercise training improves functional capacity and quality of life in patients. Moreover, exercise training reduces muscle sympathetic nerve activity (MSNA) and peripheral vasoconstriction. However, most of these studies have been conducted in middle-aged patients. Thus, the effects of exercise training in older patients are much less understood. The present study was undertaken to investigate whether exercise training improves functional capacity, muscular sympathetic activation and muscular blood flow in older heart failure patients, as it does in middle-aged heart failure patients. Design: Fifty-two consecutive outpatients with heart failure from the database of the Unit of Cardiovascular Rehabilitation and Physiology Exercise were divided by age (middle-aged, defined as 45-59 years, and older, defined as 60-75 years) and exercise status (trained and untrained). Methods: MSNA was recorded directly from the peroneal nerve using the microneurography technique. Forearm Blood Flow (FBF) was measured by venous occlusion plethysmography. Functional capacity was evaluated by cardiopulmonary exercise test. Results: Exercise training significantly and similarly increased FBF and peak VO2 in middle-aged and older heart failure patients. In addition, exercise training significantly and similarly reduced MSNA and forearm vascular resistance in these patients. No significant changes were found in untrained patients. Conclusion: Exercise training improves neurovascular control and functional capacity in heart failure patients regardless of age.

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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.