971 resultados para ROTATION CURVES
Resumo:
Species accumulation curves (SACs) chart the increase in recovery of new species as a function of some measure of sampling effort. Studies of parasite diversity can benefit from the application of SACs, both as empirical tools to guide sampling efforts and predict richness, and because their properties are informative about community patterns and the structure of parasite diversity. SACs can be used to infer interactivity in parasite infra-communities, to partition species richness into contributions from different spatial scales and different levels of the host hierarchy (individuals, populations and communities) or to identify modes of community assembly (niche versus dispersal). A historical tendency to treat individual hosts as statistically equivalent replicates (quadrats) seemingly satisfies the sample-based subgroup of SACs but care is required in this because of the inequality of hosts as sampling units. Knowledge of the true distribution of parasite richness over multiple host-derived and spatial scales is far from complete but SACs can improve the understanding of diversity patterns in parasite assemblages.
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Study Design. Development of an automatic measurement algorithm and comparison with manual measurement methods. Objectives. To develop a new computer-based method for automatic measurement of vertebral rotation in idiopathic scoliosis from computed tomography images and to compare the automatic method with two manual measurement techniques. Summary of Background Data. Techniques have been developed for vertebral rotation measurement in idiopathic scoliosis using plain radiographs, computed tomography, or magnetic resonance images. All of these techniques require manual selection of landmark points and are therefore subject to interobserver and intraobserver error. Methods. We developed a new method for automatic measurement of vertebral rotation in idiopathic scoliosis using a symmetry ratio algorithm. The automatic method provided values comparable with Aaro and Ho's manual measurement methods for a set of 19 transverse computed tomography slices through apical vertebrae, and with Aaro's method for a set of 204 reformatted computed tomography images through vertebral endplates. Results. Confidence intervals (95%) for intraobserver and interobserver variability using manual methods were in the range 5.5 to 7.2. The mean (+/- SD) difference between automatic and manual rotation measurements for the 19 apical images was -0.5 degrees +/- 3.3 degrees for Aaro's method and 0.7 degrees +/- 3.4 degrees for Ho's method. The mean (+/- SD) difference between automatic and manual rotation measurements for the 204 endplate images was 0.25 degrees +/- 3.8 degrees. Conclusions. The symmetry ratio algorithm allows automatic measurement of vertebral rotation in idiopathic scoliosis without intraobserver or interobserver error due to landmark point selection.
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In this study, 3-D Lattice Solid Model (LSMearth or LSM) was extended by introducing particle-scale rotation. In the new model, for each 3-D particle, we introduce six degrees of freedom: Three for translational motion, and three for orientation. Six kinds of relative motions are permitted between two neighboring particles, and six interactions are transferred, i.e., radial, two shearing forces, twisting and two bending torques. By using quaternion algebra, relative rotation between two particles is decomposed into two sequence-independent rotations such that all interactions due to the relative motions between interactive rigid bodies can be uniquely decided. After incorporating this mechanism and introducing bond breaking under torsion and bending into the LSM, several tests on 2-D and 3-D rock failure under uni-axial compression are carried out. Compared with the simulations without the single particle rotational mechanism, the new simulation results match more closely experimental results of rock fracture and hence, are encouraging. Since more parameters are introduced, an approach for choosing the new parameters is presented.
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Study Design. A comparative study of trunk and hip extensor muscle recruitment patterns in 2 subject groups. Objective. To examine for changes in recruitment of the hip and back extensor muscles during low level isometric trunk rotation efforts in chronic low back pain (CLBP) subjects by comparison with matched asymptomatic control subjects. Summary of Background Data. Anatomic and biomechanical models have provided evidence that muscles attaching to the thoracolumbar fascia (TLF) are important for providing stabilization to the lumbopelvic region during trunk rotation. This has guided rehabilitation programs. The muscles that link diagonally to the posterior layer of the TLF have not previously been examined individually and compared during low-level trunk rotation efforts in CLBP patients and matched controls. Methods. Thirty CLBP patients and 30 matched controls were assessed using surface electromyography (EMG) as they performed low-level isometric rotation efforts while standing upright. Muscles studied included latissimus dorsi, erector spinae, upper and lower gluteus maximus, and biceps femoris. Subjects performed the rotation exertion with various levels of external trunk support, related to different functional tasks. Results. EMG results demonstrated that subjects with CLBP had significantly higher levels of recruitment for the lower and upper gluteus maximus (P < 0.05), hamstrings (P < 0.05), and erector spinae muscles (P < 0.05) during rotation to the left compared with the control subjects. Conclusion. This study provided evidence of increased muscle recruitment in CLBP patients when performing a standardized trunk rotation task. These results may have implications for the design of therapeutic exercise programs for CLBP patients.
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TITLE: The Rural Medicine Rotation: Increasing Rural Recruitment through Quality Undergraduate Rural Experiences Eley Diann, University of Queensland, School of Medicine, Rural Clinical Division, Toowoomba 4350, Queensland Australia Baker Peter, University of Queensland, School of Medicine Rural, Clinical Division, Toowoomba 4350, Queensland Australia Chater Bruce, University of Queensland, Chair, Clinical School Management Committee, School of Medicine Rural Clinical Division, Queensland Australia CONTEXT: While rural background and rural exposure during medical training increases the likelihood of rural recruitment (Wilkinson, 2003), the quality and content of that exposure is the key to altering undergraduatesâ?? perceptions of rural practice. The Rural Clinical Division at University of Queensland (UQ) runs the Rural Medicine Rotation (RMR) within the School of Medicine. The RMR is one of five eight week clinical rotations in Year three and is compulsory for all students. The RMR provides the opportunity to learn from a wide range of health professionals and clinical exposure is not restricted to general practice but also includes remote area nursing, Indigenous health care, allied health professionals and medical specialists. Week 1 involves preparation for their rural placement with workshops and seminars and Week 8 consolidates their placement and includes case and project presentations and a summative assessment. Weeks 2-7 are spent living and working as part of the health team in different rural communities. SETTING: Rural communities in and around Queensland including locations such as Arnham Land, Thursday Island, Mt. Isa and Alice Springs METHOD: All aspects of the RMR are evaluated with surveys using both qualitative and quantitative free response questions, completed by all students at the end of the Week 8. RESULTS: Overall the RMR is evaluated highly and narratives offered by students show that the RMR provides a positive rural experience. The overall impact of the RMR for students in 2004 ranked 3.45 on a scale of 1 to 4 (1 = lowest and 4 = highest), and is exemplified by the following quote; â??I enjoyed my placement so much I am now considering rural medicine something I definitely had not considered beforeâ??. OUTCOME: The positive impact of the RMR on studentâ??s perceptions of rural medicine is encouraging and can help achieve the overall aim of increasing recruitment of the rural workforce in Australia.
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Traditionally, machine learning algorithms have been evaluated in applications where assumptions can be reliably made about class priors and/or misclassification costs. In this paper, we consider the case of imprecise environments, where little may be known about these factors and they may well vary significantly when the system is applied. Specifically, the use of precision-recall analysis is investigated and compared to the more well known performance measures such as error-rate and the receiver operating characteristic (ROC). We argue that while ROC analysis is invariant to variations in class priors, this invariance in fact hides an important factor of the evaluation in imprecise environments. Therefore, we develop a generalised precision-recall analysis methodology in which variation due to prior class probabilities is incorporated into a multi-way analysis of variance (ANOVA). The increased sensitivity and reliability of this approach is demonstrated in a remote sensing application.