972 resultados para gait kinematic parameters


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The development of artificial neural network (ANN) models to predict the rheological behavior of grouts is described is this paper and the sensitivity of such parameters to the variation in mixture ingredients is also evaluated. The input parameters of the neural network were the mixture ingredients influencing the rheological behavior of grouts, namely the cement content, fly ash, ground-granulated blast-furnace slag, limestone powder, silica fume, water-binder ratio (w/b), high-range water-reducing admixture, and viscosity-modifying agent (welan gum). The six outputs of the ANN models were the mini-slump, the apparent viscosity at low shear, and the yield stress and plastic viscosity values of the Bingham and modified Bingham models, respectively. The model is based on a multi-layer feed-forward neural network. The details of the proposed ANN with its architecture, training, and validation are presented in this paper. A database of 186 mixtures from eight different studies was developed to train and test the ANN model. The effectiveness of the trained ANN model is evaluated by comparing its responses with the experimental data that were used in the training process. The results show that the ANN model can accurately predict the mini-slump, the apparent viscosity at low shear, the yield stress, and the plastic viscosity values of the Bingham and modified Bingham models of the pseudo-plastic grouts used in the training process. The results can also predict these properties of new mixtures within the practical range of the input variables used in the training with an absolute error of 2%, 0.5%, 8%, 4%, 2%, and 1.6%, respectively. The sensitivity of the ANN model showed that the trend data obtained by the models were in good agreement with the actual experimental results, demonstrating the effect of mixture ingredients on fluidity and the rheological parameters with both the Bingham and modified Bingham models.

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The studies on PKMs have attracted a great attention to robotics community. By deploying a parallel kinematic structure, a parallel kinematic machine (PKM) is expected to possess the advantages of heavier working load, higher speed, and higher precision. Hundreds of new PKMs have been proposed. However, due to the considerable gaps between the desired and actual performances, the majorities of the developed PKMs were the prototypes in research laboratories and only a few of them have been practically applied for various applications; among the successful PKMs, the Exechon machine tool is recently developed. The Exechon adopts unique over-constrained structure, and it has been improved based on the success of the Tricept parallel kinematic machine. Note that the quantifiable theoretical studies have yet been conducted to validate its superior performances, and its kinematic model is not publically available. In this paper, the kinematic characteristics of this new machine tool is investigated, the concise models of forward and inverse kinematics have been developed. These models can be used to evaluate the performances of an existing Exechon machine tool and to optimize new structures of an Exechon machine to accomplish some specific tasks.

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Variation in wear paths is known to greatly affect wear rates in vitro, with multidirectional paths producing much greater wear than unidirectional paths. This study investigated the relationship between multidirectional motion at the hip joint, as measured by aspect ratio, sliding distance, and wear rate for 164 hip replacements. Kinematic input from three-dimensional gait analysis was used to determine the wear paths. Activity cycles were determined for a subgroup of 100 patients using a pedometer study, and the relationship between annual sliding distance and wear rate was analyzed. Poor correlations were found between both aspect ratio and sliding distance and wear rate for the larger group and between annual sliding distance and wear rate for the subgroup. However, patients who experienced a wear rate <0.08 mm/year showed a strong positive correlation between the combination of sliding distance, activity levels, and aspect ratio and wear rate (adjusted r2?=?55.4%). This group may represent those patients who experience conditions that most closely match those that prevail in simulator and laboratory tests. Although the shape of wear paths, their sliding distance, and the number of articulation cycles at the hip joint affect wear rates in simulator studies, this relationship was not seen in this clinical study. Other factors such as lubrication, loading conditions and roughness of the femoral head may influence the wear rate.

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We retrieved synovial tissue and fluid samples from patients undergoing primary total hip replacement (THR) (n 15), revision of aseptically loose THR (n 12), primary total knee replacement (TKR) (n 13) and revision of aseptically loose TKR (n 6). Several histological parameters were assessed on a relative scale of 1-4. Primary TJRs were clinically evaluated for degree of osteoarthrosis. Revision TJRs were assessed for migration of the implant, gross loosening and the degree of radiolucency. Cytokine levels in synovial fluid were determined with ELISA.

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When the dominant mechanism for ion acceleration is the laser radiation pressure, the conversion efficiency of the laser energy into the energy of relativistic ions may be very high. Stability analysis of a thin plasma layer accelerated by the radiation pressure shows that Raleigh-Taylor instability may enhance plasma inhomogeneity. In the linear stage of instability, the plasma layer decays into separate bunches, which are accelerated by the radiation pressure similarly to clusters accelerated under the action of an electromagnetic wave. The energy and luminosity of an ion beam accelerated in the radiation-pressure-dominated regime are calculated.