453 resultados para structural reliability
Resumo:
The aim of this study was to develop a new method for quantifying intersegmental motion of the spine in an instrumented motion segment L4–L5 model using ultrasound image post-processing combined with an electromagnetic device. A prospective test–retest design was employed, combined with an evaluation of stability and within- and between-day intra-tester reliability during forward bending by 15 healthy male patients. The accuracy of the measurement system using the model was calculated to be ± 0.9° (standard deviation = 0.43) over a 40° range and ± 0.4 cm (standard deviation = 0.28) over 1.5 cm. The mean composite range of forward bending was 15.5 ± 2.04° during a single trial (standard error of the mean = 0.54, coefficient of variation = 4.18). Reliability (intra-class correlation coefficient = 2.1) was found to be excellent for both within-day measures (0.995–0.999) and between-day measures (0.996–0.999). Further work is necessary to explore the use of this approach in the evaluation of biomechanics, clinical assessments and interventions.
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Understanding how the brain matures in healthy individuals is critical for evaluating deviations from normal development in psychiatric and neurodevelopmental disorders. The brain's anatomical networks are profoundly re-modeled between childhood and adulthood, and diffusion tractography offers unprecedented power to reconstruct these networks and neural pathways in vivo. Here we tracked changes in structural connectivity and network efficiency in 439 right-handed individuals aged 12 to 30 (211 female/126 male adults, mean age=23.6, SD=2.19; 31 female/24 male 12 year olds, mean age=12.3, SD=0.18; and 25 female/22 male 16 year olds, mean age=16.2, SD=0.37). All participants were scanned with high angular resolution diffusion imaging (HARDI) at 4 T. After we performed whole brain tractography, 70 cortical gyral-based regions of interest were extracted from each participant's co-registered anatomical scans. The proportion of fiber connections between all pairs of cortical regions, or nodes, was found to create symmetric fiber density matrices, reflecting the structural brain network. From those 70 × 70 matrices we computed graph theory metrics characterizing structural connectivity. Several key global and nodal metrics changed across development, showing increased network integration, with some connections pruned and others strengthened. The increases and decreases in fiber density, however, were not distributed proportionally across the brain. The frontal cortex had a disproportionate number of decreases in fiber density while the temporal cortex had a disproportionate number of increases in fiber density. This large-scale analysis of the developing structural connectome offers a foundation to develop statistical criteria for aberrant brain connectivity as the human brain matures.
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Studies of cerebral asymmetry can open doors to understanding the functional specialization of each brain hemisphere, and how this is altered in disease. Here we examined hemispheric asymmetries in fiber architecture using diffusion tensor imaging (DTI) in 100 subjects, using high-dimensional fluid warping to disentangle shape differences from measures sensitive to myelination. Confounding effects of purely structural asymmetries were reduced by using co-registered structural images to fluidly warp 3D maps of fiber characteristics (fractional and geodesic anisotropy) to a structurally symmetric minimal deformation template (MDT). We performed a quantitative genetic analysis on 100 subjects to determine whether the sources of the remaining signal asymmetries were primarily genetic or environmental. A twin design was used to identify the heritable features of fiber asymmetry in various regions of interest, to further assist in the discovery of genes influencing brain micro-architecture and brain lateralization. Genetic influences and left/right asymmetries were detected in the fiber architecture of the frontal lobes, with minor differences depending on the choice of registration template.
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To classify each stage for a progressing disease such as Alzheimer’s disease is a key issue for the disease prevention and treatment. In this study, we derived structural brain networks from diffusion-weighted MRI using whole-brain tractography since there is growing interest in relating connectivity measures to clinical, cognitive, and genetic data. Relatively little work has usedmachine learning to make inferences about variations in brain networks in the progression of the Alzheimer’s disease. Here we developed a framework to utilize generalized low rank approximations of matrices (GLRAM) and modified linear discrimination analysis for unsupervised feature learning and classification of connectivity matrices. We apply the methods to brain networks derived from DWI scans of 41 people with Alzheimer’s disease, 73 people with EMCI, 38 people with LMCI, 47 elderly healthy controls and 221 young healthy controls. Our results show that this new framework can significantly improve classification accuracy when combining multiple datasets; this suggests the value of using data beyond the classification task at hand to model variations in brain connectivity.
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The development of Electric Energy Storage (EES) integrated with Renewable Energy Resources (RER) has increased use of optimum scheduling strategy in distribution systems. Optimum scheduling of EES can reduce cost of purchased energy by retailers while improve the reliability of customers in distribution system. This paper proposes an optimum scheduling strategy for EES and the evaluation of its impact on reliability of distribution system. Case study shows the impact of the proposed strategy on reliability indices of a distribution system.
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This paper presents the results of a research project aimed at examining the capabilities and challenges of two distinct but not mutually exclusive approaches to in-service bridge assessment: visual inspection and installed monitoring systems. In this study, the intended functionality of both approaches was evaluated on its ability to identify potential structural damage and to provide decision-making support. Inspection and monitoring are compared in terms of their functional performance, cost, and barriers (real and perceived) to implementation. Both methods have strengths and weaknesses across the metrics analyzed, and it is likely that a hybrid evaluation technique that adopts both approaches will optimize efficiency of condition assessment and ultimately lead to better decision making.
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This research investigates how to obtain accurate and reliable positioning results with global navigation satellite systems (GNSS). The work provides a theoretical framework for reliability control in GNSS carrier phase ambiguity resolution, which is the key technique for precise GNSS positioning in centimetre levels. The proposed approach includes identification and exclusion procedures of unreliable solutions and hypothesis tests, allowing the reliability of solutions to be controlled in the aspects of mathematical models, integer estimation and ambiguity acceptance tests. Extensive experimental results with both simulation and observed data sets effectively demonstrate the reliability performance characteristics based on the proposed theoretical framework and procedures.
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Graphitic like layered materials exhibit intriguing electronic structures and thus the search for new types of two-dimensional (2D) monolayer materials is of great interest for developing novel nano-devices. By using density functional theory (DFT) method, here we for the first time investigate the structure, stability, electronic and optical properties of monolayer lead iodide (PbI2). The stability of PbI2 monolayer is first confirmed by phonon dispersion calculation. Compared to the calculation using generalized gradient approximation, screened hybrid functional and spin–orbit coupling effects can not only predicts an accurate bandgap (2.63 eV), but also the correct position of valence and conduction band edges. The biaxial strain can tune its bandgap size in a wide range from 1 eV to 3 eV, which can be understood by the strain induced uniformly change of electric field between Pb and I atomic layer. The calculated imaginary part of the dielectric function of 2D graphene/PbI2 van der Waals type hetero-structure shows significant red shift of absorption edge compared to that of a pure monolayer PbI2. Our findings highlight a new interesting 2D material with potential applications in nanoelectronics and optoelectronics.
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This article reports the main features of an innovative full-scale Structural Health Monitoring (SHM) system which has been implemented onto a landmark building on QUT Gardens Point Campus and its efficacy in capturing the recent Queensland earthquakes although they occurred almost 300 km away from where the system is located.
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This paper investigates the influence of structural sealant joints on the blast performance of laminated glass (LG) panels, using a comprehensive numerical procedure. A parametric study was carried out by varying the width, thickness and the Young’s modulus (E) of the structural silicone sealant joints and the behavior of the LG panel was studied under two different blast loads. Results show that these parameters influence the blast response of LG panels, especially under the higher blast load. Sealant joints that are thicker, have smaller widths and lower E values increase the flexibility at the supports and hence increase the energy absorption of the LG panel while reducing the support reactions. Results also confirmed that sealant joints designed according to current standards perform well under blast loads. Modeling techniques presented in this paper could be used to complement and supplement the guidance in existing design standards. The new information generated in this paper will contribute towards safer and more economical designs of entire facade systems including window glazing, frames and supporting structures.
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Background Although there are many structural neuroimaging studies of attention-deficit/hyperactivity disorder (ADHD) in children, there are inconsistencies across studies and no consensus regarding which brain regions show the most robust area or volumetric reductions relative to control subjects. Our goal was to statistically analyze structural imaging data via a meta-analysis to help resolve these issues. Methods We searched the MEDLINE and PsycINFO databases through January 2005. Studies must have been written in English, used magnetic resonance imaging, and presented the means and standard deviations of regions assessed. Data were extracted by one of the authors and verified independently by another author. Results Analyses were performed using STATA with metan, metabias, and metainf programs. A meta-analysis including all regions across all studies indicated global reductions for ADHD subjects compared with control subjects, standardized mean difference equal to .408, p less than .001. Regions most frequently assessed and showing the largest differences included cerebellar regions, the splenium of the corpus callosum, total and right cerebral volume, and right caudate. Several frontal regions assessed in only two studies also showed large significant differences. Conclusions This meta-analysis provides a quantitative analysis of neuroanatomical abnormalities in ADHD and information that can be used to guide future studies.
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Objective Evaluation of scapular posture is an integral component of the clinical assessment of painful neck disorders. The aim of this study was to evaluate agreement between therapist judgements of scapula posture in multiple biomechanical planes in individuals with neck pain. Design Inter-therapist reliability study. Setting Research laboratory. Participants Fifteen participants with chronic neck pain. Main outcome measures Four physiotherapists recorded ratings of scapular orientation (relative to the thorax) in five different scapula postural planes (plane of scapula, sagittal plane, transverse plane, horizontal plane, and vertical plane) under four test conditions (at rest, and during three isometric shoulder conditions) in all participants. Inter-therapist reliability was expressed using both generalized and paired kappa coefficient. Results Following adjustment for expected agreement and the high prevalence of neutral ratings (81%), on average both the generalised kappa (0.37) as well as Cohen's Kappa for the two therapist pairs (0.45 and 0.42) demonstrated only slight to moderate inter-therapist reliability. Conclusions The findings suggest that ratings of scapular posture in individuals with neck pain by visual inspection has only slight to moderate reliability and should only be used in conjunction with other clinical tests when judging scapula function in these patients.
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Background: The Simple Shoulder Test (SST-Sp) is a widely used outcome measure. Objective: The purpose of this study was to develop and validate a Spanish-version SST (SST-Sp). Methods: A two-stage observational study was conducted. The SST was initially cross-culturally adapted to Spanish through double forward and backward translation and then validated for its psychometric characteristics. Participants (n = 66) with several shoulder disorders completed the SST-Sp, DASH, VAS and SF-12. The full sample was employed to determine factor structure, internal consistency and concurrent criterion validity. Reliability was determined in the first 24–48 h in a subsample of 21 patients. Results: The SST-Sp showed three factors that explained the 56.1 % of variance, and the internal consistency for each factor was α = 0.738, 0.723 and 0.667, and reliability was ICC = 0.687–0.944. The factor structure was three-dimensional and supported construct validity. Criterion validity determined from the relationship between the SST-Sp and DASH was strong (r = −0.73; p < 0.001) and fair for VAS (r = −0.537; p < 0.001). Relationships between SST-Sp and SF-12 were weak for both physical (r = −0.47; p < 0.001) and mental (r = −0.43; p < 0.001) dimensions. Conclusions: The SST-Sp supports the findings of the original English version as being a valid shoulder outcome measure with similar psychometric properties to the original English version.
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Impulse propagation in biological tissues is known to be modulated by structural heterogeneity. In cardiac muscle, improved understanding on how this heterogeneity influences electrical spread is key to advancing our interpretation of dispersion of repolarization. We propose fractional diffusion models as a novel mathematical description of structurally heterogeneous excitable media, as a means of representing the modulation of the total electric field by the secondary electrical sources associated with tissue inhomogeneities. Our results, analysed against in vivo human recordings and experimental data of different animal species, indicate that structural heterogeneity underlies relevant characteristics of cardiac electrical propagation at tissue level. These include conduction effects on action potential (AP) morphology, the shortening of AP duration along the activation pathway and the progressive modulation by premature beats of spatial patterns of dispersion of repolarization. The proposed approach may also have important implications in other research fields involving excitable complex media.
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Structural equation modeling (SEM) is a powerful statistical approach for the testing of networks of direct and indirect theoretical causal relationships in complex data sets with intercorrelated dependent and independent variables. SEM is commonly applied in ecology, but the spatial information commonly found in ecological data remains difficult to model in a SEM framework. Here we propose a simple method for spatially explicit SEM (SE-SEM) based on the analysis of variance/covariance matrices calculated across a range of lag distances. This method provides readily interpretable plots of the change in path coefficients across scale and can be implemented using any standard SEM software package. We demonstrate the application of this method using three studies examining the relationships between environmental factors, plant community structure, nitrogen fixation, and plant competition. By design, these data sets had a spatial component, but were previously analyzed using standard SEM models. Using these data sets, we demonstrate the application of SE-SEM to regularly spaced, irregularly spaced, and ad hoc spatial sampling designs and discuss the increased inferential capability of this approach compared with standard SEM. We provide an R package, sesem, to easily implement spatial structural equation modeling.