10 resultados para normal-mode analysis

em University of Queensland eSpace - Australia


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This comment points out an inaccurate formula relating the signal correlation coefficient to the mutual impedance and corrects it. © 2005 IEEE.

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A new mutual impedance - the receiving mutual impedance - between two normal-mode helical antennas is defined, measured, and theoretically calculated. The variations of the receiving mutual impedance with antenna separation, with frequency, and with excitation source direction are critically investigated. An application of the receiving mutual impedance in direction finding demonstrates its more accurate description of the mutual coupling effect than that using the conventional mutual impedance.

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This study examined the utility of the Attachment Style Questionnaire (ASQ) in an Italian sample of 487 consecutively admitted psychiatric participants and an independent sample of 605 nonclinical participants. Minimum average partial analysis of data from the psychiatric sample supported the hypothesized five-factor structure of the items; furthermore, multiple-group component analysis showed that this five-factor structure was not an artifact of differences in item distributions. The five-factor structure of the ASQ was largely replicated in the nonclinical sample. Furthermore, in both psychiatric and nonclinical samples, a two-factor higher order structure of the ASQ scales was observed. The higher order factors of Avoidance and Anxious Attachment showed meaningful relations with scales assessing parental bonding, but were not redundant with these scales. Multivariate normal mixture analysis supported the hypothesis that adult attachment patterns, as measured by the ASQ, are best considered as dimensional constructs.

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Crys.m is a MATLAB routine that combines a micrograph of a crystal with a scaleable, rotatable three-dimensional cage structure to determine the orientation of the crystal axes. The example presented here uses the morphology of tetragonal lysozyme. Rotation of the cage until it aligns with the crystal in the image yields the orientation of the c axis of the crystal relative to the image normal. This analysis can be used for quantitative determination of crystal orientation effects induced by electric, magnetic and/or gravitational fields.

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Loading of the femoral neck (FN) is dominated by bending and compressive stresses. We hypothesize that adaptation of the FN to physical activity would be manifested in the cross-sectional area (CSA) and section modulus (Z) of bone, indices of axial and bending strength, respectively. We investigated the influence of physical activity on bone strength during adolescence using 7 years of longitudinal data from 109 boys and 121 girls from the Saskatchewan Paediatric Bone and Mineral Accrual Study (PBMAS). Physical activity data (PAC-Q physical activity inventory) and anthropometric measurements were taken every 6 months and DXA bone scans were measured annually (Hologic QDR2000, array mode). We applied hip structural analysis to derive strength and geometric indices of the femoral neck using DXA scans. To control for maturation, we determined a biological maturity age defined as years from age at peak height velocity (APHV). To account for the repeated measures within individual nature of longitudinal data, multilevel random effects regression analyses were used to analyze the data. When biological maturity age and body size (height and weight) were controlled, in both boys and girls, physical activity was a significant positive independent predictor of CSA and Z of the narrow region of the femoral neck (P < 0.05). There was no independent effect of physical activity on the subperiosteal width of the femoral neck. When leg length and leg lean mass were introduced into the random effects models to control for size and muscle mass of the leg (instead of height and weight), all significant effects of physical activity disappeared. Even among adolescents engaged in normal levels of physical activity, the statistically significant relationship between physical activity and indices of bone strength demonstrate that modifiable lifestyle factors like exercise play an important role in optimizing bone strength during the growing years. Physical activity differences were explained by the interdependence between activity and lean mass considerations. Physical activity is important for optimal development of bone strength. (c) 2005 Elsevier Inc. All rights reserved.

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Background: Automated measurement of LV function could extend the clinical utility of echo by less expert readers. We sought to define normal ranges of global 2D strain (2DS) and strain-rate (SR) in an international, multicenter study of healthy subjects, and to assess the determinants of variation. Methods: SR and 2DS were measured in 18 myocardial segts in both apical and short axis views of 227 normal subjects (38% men, 48±14y) with no cardiac history, risk factors or drug therapy. The association of age and resting hemodynamics with global strain indices was sought using multiple regression. Differences in variance were expressed as F values. Results: Baseline SBP was 127±18 mmHg, pulse was 76±13/min and ejection fraction 50±20%. Although global longitudinal strain was influenced by endsystolic volume (F=4.2, p

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We report the case study of a 68-year-old female with cardiac syndrome X presenting with abnormal pressure waveforms and a hypertensive response to exercise with ST-segment depression. After amlodipine treatment, pressure waveform morphology was significantly improved, exercise testing was normal and symptoms had resolved. This case emphasizes the potential clinical value of arterial waveform analysis.

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Formal methods have significant benefits for developing safety critical systems, in that they allow for correctness proofs, model checking safety and liveness properties, deadlock checking, etc. However, formal methods do not scale very well and demand specialist skills, when developing real-world systems. For these reasons, development and analysis of large-scale safety critical systems will require effective integration of formal and informal methods. In this paper, we use such an integrative approach to automate Failure Modes and Effects Analysis (FMEA), a widely used system safety analysis technique, using a high-level graphical modelling notation (Behavior Trees) and model checking. We inject component failure modes into the Behavior Trees and translate the resulting Behavior Trees to SAL code. This enables us to model check if the system in the presence of these faults satisfies its safety properties, specified by temporal logic formulas. The benefit of this process is tool support that automates the tedious and error-prone aspects of FMEA.