494 resultados para Surface deformation


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Background Aquatic exercise has been widely used for rehabilitation and functional recovery due to its physical and physiological benefits. However, there is a high variability in reporting on the muscle activity from surface electromyographic (sEMG) signals. The aim of this study is to present an updated review of the literature on the state of the art of muscle activity recorded using sEMG during activities and exercise performed by humans in water. Methods A literature search was performed to identify studies of aquatic exercise movement. Results Twenty-one studies were selected for critical appraisal. Sample size, functional tasks analyzed, and muscles recorded were studied for each paper. The clinical contribution of the paper was evaluated. Conclusions Muscle activity tends to be lower in water-based compared to land-based activity; however more research is needed to understand why. Approaches from basic and applied sciences could support the understanding of relevant aspects for clinical practice.

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Objectives Currently, there are no studies combining electromyography (EMG) and sonography to estimate the absolute and relative strength values of erector spinae (ES) muscles in healthy individuals. The purpose of this study was to establish whether the maximum voluntary contraction (MVC) of the ES during isometric contractions could be predicted from the changes in surface EMG as well as in fiber pennation and thickness as measured by sonography. Methods Thirty healthy adults performed 3 isometric extensions at 45° from the vertical to calculate the MVC force. Contractions at 33% and 100% of the MVC force were then used during sonographic and EMG recordings. These measurements were used to observe the architecture and function of the muscles during contraction. Statistical analysis was performed using bivariate regression and regression equations. Results The slope for each regression equation was statistically significant (P < .001) with R2 values of 0.837 and 0.986 for the right and left ES, respectively. The standard error estimate between the sonographic measurements and the regression-estimated pennation angles for the right and left ES were 0.10 and 0.02, respectively. Conclusions Erector spinae muscle activation can be predicted from the changes in fiber pennation during isometric contractions at 33% and 100% of the MVC force. These findings could be essential for developing a regression equation that could estimate the level of muscle activation from changes in the muscle architecture.

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Background The aim of this study was to compare through surface electromyographic (sEMG) recordings of the maximum voluntary contraction (MVC) on dry land and in water by manual muscle test (MMT). Method Sixteen healthy right-handed subjects (8 males and 8 females) participated in measurement of muscle activation of the right shoulder. The selected muscles were the cervical erector spinae, trapezius, pectoralis, anterior deltoid, middle deltoid, infraspinatus and latissimus dorsi. The MVC test conditions were random with respect to the order on the land/in water. Results For each muscle, the MVC test was performed and measured through sEMG to determine differences in muscle activation in both conditions. For all muscles except the latissimus dorsi, no significant differences were observed between land and water MVC scores (p = 0.063–0.679) and precision (%Diff = 7–10%) were observed between MVC conditions in the muscles trapezius, anterior deltoid and middle deltoid. Conclusions If the procedure for data collection is optimal, under MMT conditions it appears that comparable MVC sEMG values were achieved on land and in water and the integrity of the EMG recordings were maintained during wáter immersion.

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We developed and validated a new method to create automated 3D parametric surface models of the lateral ventricles, designed for monitoring degenerative disease effects in clinical neuroscience studies and drug trials. First we used a set of parameterized surfaces to represent the ventricles in a manually labeled set of 9 subjects' MRIs (atlases). We fluidly registered each of these atlases and mesh models to a set of MRIs from 12 Alzheimer's disease (AD) patients and 14 matched healthy elderly subjects, and we averaged the resulting meshes for each of these images. Validation experiments on expert segmentations showed that (1) the Hausdorff labeling error rapidly decreased, and (2) the power to detect disease-related alterations monotonically improved as the number of atlases, N, was increased from 1 to 9. We then combined the segmentations with a radial mapping approach to localize ventricular shape differences in patients. In surface-based statistical maps, we detected more widespread and intense anatomical deficits as we increased the number of atlases, and we formulated a statistical stopping criterion to determine the optimal value of N. Anterior horn anomalies in Alzheimer's patients were only detected with the multi-atlas segmentation, which clearly outperformed the standard single-atlas approach.

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This work describes the development of a model of cerebral atrophic changes associated with the progression of Alzheimer's disease (AD). Linear registration, region-of-interest analysis, and voxel-based morphometry methods have all been employed to elucidate the changes observed at discrete intervals during a disease process. In addition to describing the nature of the changes, modeling disease-related changes via deformations can also provide information on temporal characteristics. In order to continuously model changes associated with AD, deformation maps from 21 patients were averaged across a novel z-score disease progression dimension based on Mini Mental State Examination (MMSE) scores. The resulting deformation maps are presented via three metrics: local volume loss (atrophy), volume (CSF) increase, and translation (interpreted as representing collapse of cortical structures). Inspection of the maps revealed significant perturbations in the deformation fields corresponding to the entorhinal cortex (EC) and hippocampus, orbitofrontal and parietal cortex, and regions surrounding the sulci and ventricular spaces, with earlier changes predominantly lateralized to the left hemisphere. These changes are consistent with results from post-mortem studies of AD.

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We study the influence of the choice of template in tensor-based morphometry. Using 3D brain MR images from 10 monozygotic twin pairs, we defined a tensor-based distance in the log-Euclidean framework [1] between each image pair in the study. Relative to this metric, twin pairs were found to be closer to each other on average than random pairings, consistent with evidence that brain structure is under strong genetic control. We also computed the intraclass correlation and associated permutation p-value at each voxel for the determinant of the Jacobian matrix of the transformation. The cumulative distribution function (cdf) of the p-values was found at each voxel for each of the templates and compared to the null distribution. Surprisingly, there was very little difference between CDFs of statistics computed from analyses using different templates. As the brain with least log-Euclidean deformation cost, the mean template defined here avoids the blurring caused by creating a synthetic image from a population, and when selected from a large population, avoids bias by being geometrically centered, in a metric that is sensitive enough to anatomical similarity that it can even detect genetic affinity among anatomies.

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The 3D Water Chemistry Atlas is an intuitive, open source, Web-based system that enables the three-dimensional (3D) sub-surface visualization of ground water monitoring data, overlaid on the local geological model (formation and aquifer strata). This paper firstly describes the results of evaluating existing virtual globe technologies, which led to the decision to use the Cesium open source WebGL Virtual Globe and Map Engine as the underlying platform. Next it describes the backend database and search, filtering, browse and analysis tools that were developed to enable users to interactively explore the groundwater monitoring data and interpret it spatially and temporally relative to the local geological formations and aquifers via the Cesium interface. The result is an integrated 3D visualization system that enables environmental managers and regulators to assess groundwater conditions, identify inconsistencies in the data, manage impacts and risks and make more informed decisions about coal seam gas extraction, waste water extraction, and water reuse.

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The influence of fluid flow, surface roughness and immersion time on the electrochemical behaviour of carbon steel in coal seam gas produced water under static and hydrodynamic conditions has been studied. The disc electrode surface morphology before and after the corrosion test was characterized using scanning electron microscopy (SEM). The corrosion product was examined using X-ray photoelectron spectroscopy (XPS) and X-ray diffractometry (XRD).The results show that the anodic current density increased with increasing surface roughness and consequently a decrease in corrosion surface resistance. Under dynamic flow conditions, the corrosion rate increased with increasing rotating speed due to the high mass transfer coefficient and formation of non-protective akaganeite β- FeO(OH) and goethite α- FeO(OH) corrosion scale at the electrode surface.The corrosion rate was lowest at 0 rpm.The corrosion rate decreased in both static and dynamic conditions with increasing immersion time. The decrease in corrosion rate is attributed to the deposition of corrosion products on the electrode surface. SEM results revealed that the rougher surface exhibited a great tendency toward pitting corrosion.

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This paper aims to trace surface evolution in the wheel-rail interface using data obtained from a twin-disc testing machine and the surface replication technique. Changes in the surface profile of the rail testing disc are explicitly analysed according to the wear mechanism, which helps elaborate a better understanding of the attrition of asperities during the wearing-in process of surface modification. The surface profile amplitude was seen to decrease during the initial running-in phase of the experiment cycle, and after reaching a saturation value, the profile amplitude then increased. Ultimately the results show that grinding will roughen the rail surface and the wheel-rail contact conditions will then remove this surface damage to some saturation value of the profile height. The variation in the rail surface profile beyond this point is then only dependant on the contact conditions which exist between the wheel and rail during normal operation.

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Particle analysis methodology is presented, together with the morphology of the wear debris formed during rolling contact fatigue. Wear particles are characterised by their surface topography and in terms of wear mechanism. Rail-wheel materials are subjected to severe plastic deformation as the contact loading progresses, which contributes to a mechanism of major damage in head-hardened rail steel. Most of the current methodologies involve sectioning of the rail-wheel discs to trace material damage phenomena such as crack propagation and plastic strain accumulation. This paper proposes methodology to analyse the development of the plastically deformed layer by sectioning wear particles using the focussed ion beam (FIB) milling method. Moreover, it highlights the processes of oxidation and rail surface delamination during unlubricated rolling contact fatigue.

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Electrospun nanofiber meshes have emerged as a new generation of scaffold membranes possessing a number of features suitable for tissue regeneration. One of these features is the flexibility to modify their structure and composition to orchestrate specific cellular responses. In this study, we investigated the effects of nanofiber orientation and surface functionalization on human mesenchymal stem cell (hMSC) migration and osteogenic differentiation. We used an in vitro model to examine hMSC migration into a cell-free zone on nanofiber meshes and mitomycin C treatment to assess the contribution of proliferation to the observed migration. Poly (ɛ-caprolactone) meshes with oriented topography were created by electrospinning aligned nanofibers on a rotating mandrel, while randomly oriented controls were collected on a stationary collector. Both aligned and random meshes were coated with a triple-helical, type I collagen-mimetic peptide, containing the glycine-phenylalanine-hydroxyproline-glycine-glutamate-arginine (GFOGER) motif. Our results indicate that nanofiber GFOGER peptide functionalization and orientation modulate cellular behavior, individually, and in combination. GFOGER significantly enhanced the migration, proliferation, and osteogenic differentiation of hMSCs on nanofiber meshes. Aligned nanofiber meshes displayed increased cell migration along the direction of fiber orientation compared to random meshes; however, fiber alignment did not influence osteogenic differentiation. Compared to each other, GFOGER coating resulted in a higher proliferation-driven cell migration, whereas fiber orientation appeared to generate a larger direct migratory effect. This study demonstrates that peptide surface modification and topographical cues associated with fiber alignment can be used to direct cellular behavior on nanofiber mesh scaffolds, which may be exploited for tissue regeneration.

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Nanofibers of sodium vanadate, consisting of very thin negatively charged layers and exchangeable sodium ions between the layers, are efficient sorbents for the removal of radioactive 137Cs+ and 85Sr2+ cations from water. The exchange of 137Cs+ or 85Sr2+ ions with the interlayer Na+ ions eventually triggered structural deformation of the thin layers, trapping the 137Cs+ and 85Sr2+ ions in the nanofibers. Furthermore, when the nanofibers were dispersed in a AgNO3 solution at pH >7, well-dispersed Ag2O nanocrystals formed by firmly anchoring themselves on the fiber surfaces along planes of crystallographic similarity with those of Ag2O. These nanocrystals can efficiently capture I– anions by forming a AgI precipitate, which was firmly attached to the substrates. We also designed sorbents that can remove 137Cs+ and 125I– ions simultaneously for safe disposal by optimizing the Ag2O loading and sodium content of the vanadate. This study confirms that sorbent features such as fibril morphology, negatively charged thin layers and readily exchangeable Na+ ions between the layers, and the crystal planes for the formation of a coherent interface with Ag2O nanocrystals on the fiber surface are very important for the simultaneous uptake of cations and anions.

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A key component of robotic path planning is ensuring that one can reliably navigate a vehicle to a desired location. In addition, when the features of interest are dynamic and move with oceanic currents, vehicle speed plays an important role in the planning exercise to ensure that vehicles are in the right place at the right time. Aquatic robot design is moving towards utilizing the environment for propulsion rather than traditional motors and propellers. These new vehicles are able to realize significantly increased endurance, however the mission planning problem, in turn, becomes more difficult as the vehicle velocity is not directly controllable. In this paper, we examine Gaussian process models applied to existing wave model data to predict the behavior, i.e., velocity, of a Wave Glider Autonomous Surface Vehicle. Using training data from an on-board sensor and forecasting with the WAVEWATCH III model, our probabilistic regression models created an effective method for forecasting WG velocity.

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The uniform growth of copper oxide nanowires on the top of copper plate has been investigated during the exposure to radiofrequency plasma discharge in respect to plasma properties and its localization. The copper samples of 10 mm radius and 1 mm in thickness were exposed to argon-oxygen plasma created at discharge power of 150 W. After 10 min, almost uniform growth of nanowires was achieved over large surface. There were significant distortions in nanowire length and shape near the edges. Based on the experimental results, we developed a theoretical model, which took into account a balance in heat released at the flow of the current to the nanowire and rejected from the nanowire. This model established a dependence of the maximal length of the nanowire at dependence on the plasma parameters, where the limiting factor for nanowire growth and distortions in distribution are ballistic effects of ions and their local fluxes. In contrast, the plasma heating by potential interactions of species has very little influence on the length and smaller deviations in flux are allowed for uniformity of growth

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In this article, natural convection boundary layer flow is investigated over a semi-infinite horizontal wavy surface. Such an irregular (wavy) surface is used to exchange heat with an external radiating fluid which obeys Rosseland diffusion approximation. The boundary layer equations are cast into dimensionless form by introducing appropriate scaling. Primitive variable formulations (PVF) and stream function formulations (SFF) are independently used to transform the boundary layer equations into convenient form. The equations obtained from the former formulations are integrated numerically via implicit finite difference iterative scheme whereas equations obtained from lateral formulations are simulated through Keller-box scheme. To validate the results, solutions produced by above two methods are compared graphically. The main parameters: thermal radiation parameter and amplitude of the wavy surface are discussed categorically in terms of shear stress and rate of heat transfer. It is found that wavy surface increases heat transfer rate compared to the smooth wall. Thus optimum heat transfer is accomplished when irregular surface is considered. It is also established that high amplitude of the wavy surface in the boundary layer leads to separation of fluid from the plate.