357 resultados para Llasere frequency measurements


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Articular cartilage (AC), an avascular connective tissue lining articulating surfaces of the long bones, comprises extracellular biopolymers. In functionally compromised states such as osteoarthritis, thinned or lost AC causes reduced mobility and increased health-care costs. Understanding of the characteristics responsible for the load bearing efficiency of AC and the factors leading to its degradation are incomplete. DTI shows the structural alignment of collagen in AC [1] and T2 relaxation measurements suggest that the average director of reorientational motion of water molecules depends on the degree of alignment of collagen in AC [2]. Information on the nature of the chemical interactions involved in functional AC is lacking. The need for AC structural integrity makes solid state NMR an ideal tool to study this tissue. We examined the contribution of water in different functional ‘compartments’ using 1H-MAS, 13C-MAS and 13C-CPMAS NMR of bovine patellar cartilage incubated in D2O. 1H-MAS spectra signal intensity was reduced due to H/D exchange without a measureable redistribution of relative signal intensity. Chemical shift anisotropy was estimated by lineshape analysis of multiple peaks in the 1H-MAS spinning sidebands. These asymmetrical sidebands suggested the presence of multiple water species in AC. Therefore, water was added in small aliquots to D2O saturated AC and the influence of H2O and D2O on organic components was studied with 13C-MAS-NMR and 13C-CPMAS-NMR. Signal intensity in 13C-MAS spectra showed no change in relative signal intensity throughout the spectrum. In 13C-CPMAS spectra, displacement of water by D2O resulted in a loss of signal in the aliphatic region due to a reduction in proton availability for cross-polarization. These results complement dehydration studies of cartilage using osmotic manipulation [3] and demonstrate components of cartilage that are in contact with mobile water.

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Articular cartilage (AC), an avascular connective tissue lining articulating surfaces of the long bones, comprises extracellular biopolymers. In functionally compromised states such as osteoarthritis, thinned or lost AC causes reduced mobility and increased health-care costs. Understanding of the characteristics responsible for the load bearing efficiency of AC and the factors leading to its degradation are incomplete. DTI shows the structural alignment of collagen in AC [1] and T2 relaxation measurements suggest that the average director of reorientational motion of water molecules depends on the degree of alignment of collagen in AC [2]. Information on the nature of the chemical interactions involved in functional AC is lacking. The need for AC structural integrity makes solid state NMR an ideal tool to study this tissue. We examined the contribution of water in different functional ‘compartments’ using 1H-MAS, 13C-MAS and 13C-CPMAS NMR of bovine patellar cartilage incubated in D2O. 1H-MAS spectra signal intensity was reduced due to H/D exchange without a measureable redistribution of relative signal intensity. Chemical shift anisotropy was estimated by lineshape analysis of multiple peaks in the 1H-MAS spinning sidebands. These asymmetrical sidebands suggested the presence of multiple water species in AC. Therefore, water was added in small aliquots to D2O saturated AC and the influence of H2O and D2O on organic components was studied with 13C-MAS-NMR and 13C-CPMAS-NMR. Signal intensity in 13C-MAS spectra showed no change in relative signal intensity throughout the spectrum. In 13C-CPMAS spectra, displacement of water by D2O resulted in a loss of signal in the aliphatic region due to a reduction in proton availability for cross-polarization. These results complement dehydration studies of cartilage using osmotic manipulation [3] and demonstrate components of cartilage that are in contact with mobile water.

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An improved Phase-Locked Loop (PLL) for extracting phase and frequency of the fundamental component of a highly distorted grid voltage is presented. The structure of the single-phase PLL is based on the Synchronous Reference Frame (SRF) PLL and uses an All Pass Filter (APF) to generate the quadrature component from the single phase input voltage. In order to filter the harmonic content, a Moving Average Filter (MAF) is used, and performance is improved by designing a lead compensator and also a feed-forward compensator. The simulation results are compared to show the improved performance with feed-forward. In addition, the frequency dependency of MAF is dealt with by a proposed method for adaption to the frequency. This method changes the window size based on the frequency on a sample-by-sample basis. By using this method, the speed of resizing can be reduced in order to decrease the output ripples caused by window size variations.

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Frequency domain spectroscopy (FDS) is being used to assess the insulation condition of oil–paper power transformers. However, it has to date only been implemented on de-energised transformers, which requires the transformers to be shut down for an extended period and may cause significant costs. To solve this issue, a newly improved monitoring method based on the FDS principle is proposed to implement the dielectric measurement on energised transformers. Moreover, a chirp waveform excitation and its novel processing method are introduced. Compared with the conventional FDS results, dielectric results from the energised insulation system have higher tanδ values because of the increased losses. To further understand the insulation ageing process, the effects of the geometric capacitance are removed from the measured imaginary admittance of the insulation system to enhance the ageing signature. The resulting imaginary admittance is then shown to correlate well with the central time constant in return voltage measurements results. The proposed methods address the issues on techniques used on energised transformers and provide a clue for on-line FDS diagnostic application.

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Determining the condition as well as the remaining life of an insulation system is essential for the reliable operation of large oil-filled power transformers. Frequency-domain spectroscopy (FDS) is one of the diagnostic techniques used to identify the dielectric status of a transformer. Currently, this technique can only be implemented on a de-energized transformer. This paper presents an initial investigation into a novel online monitoring method based on FDS dielectric measurements for transformers. The proposed technique specifically aims to address the real operational constraints of online testing. This is achieved by designing an online testing model extending the basic “extended Debye” linear dielectric model and taking unique noise issues only experienced during online measurements into account via simulations. Approaches to signal denoising and potential problems expected to be encountered during online measurements will also be discussed. Using fixed-frequency sinusoidal excitation waveforms will result in a long measurement times. The use of alternatives such as a chirp has been investigated using simulations. The results presented in the paper predict that reliable measurements should be possible during online testing.

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Detailed knowledge of the past history of an active volcano is crucial for the prediction of the timing, frequency and style of future eruptions, and for the identification of potentially at-risk areas. Subaerial volcanic stratigraphies are often incomplete, due to a lack of exposure, or burial and erosion from subsequent eruptions. However, many volcanic eruptions produce widely-dispersed explosive products that are frequently deposited as tephra layers in the sea. Cores of marine sediment therefore have the potential to provide more complete volcanic stratigraphies, at least for explosive eruptions. Nevertheless, problems such as bioturbation and dispersal by currents affect the preservation and subsequent detection of marine tephra deposits. Consequently, cryptotephras, in which tephra grains are not sufficiently concentrated to form layers that are visible to the naked eye, may be the only record of many explosive eruptions. Additionally, thin, reworked deposits of volcanic clasts transported by floods and landslides, or during pyroclastic density currents may be incorrectly interpreted as tephra fallout layers, leading to the construction of inaccurate records of volcanism. This work uses samples from the volcanic island of Montserrat as a case study to test different techniques for generating volcanic eruption records from marine sediment cores, with a particular relevance to cores sampled in relatively proximal settings (i.e. tens of kilometres from the volcanic source) where volcaniclastic material may form a pervasive component of the sedimentary sequence. Visible volcaniclastic deposits identified by sedimentological logging were used to test the effectiveness of potential alternative volcaniclastic-deposit detection techniques, including point counting of grain types (component analysis), glass or mineral chemistry, colour spectrophotometry, grain size measurements, XRF core scanning, magnetic susceptibility and X-radiography. This study demonstrates that a set of time-efficient, non-destructive and high-spatial-resolution analyses (e.g. XRF core-scanning and magnetic susceptibility) can be used effectively to detect potential cryptotephra horizons in marine sediment cores. Once these horizons have been sampled, microscope image analysis of volcaniclastic grains can be used successfully to discriminate between tephra fallout deposits and other volcaniclastic deposits, by using specific criteria related to clast morphology and sorting. Standard practice should be employed when analysing marine sediment cores to accurately identify both visible tephra and cryptotephra deposits, and to distinguish fallout deposits from other volcaniclastic deposits.

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Objective Migraine is a highly disabling disease affecting a significant proportion of the Australian population. The Methylenetetrahydrofolate Reductase (MTHFR) C677T variant has been associated with increased levels of homocysteine and risk of migraine with aura (MA). Folic acid, Vitamin B6 and B12 supplementation has been previously shown to reduce increased levels of homocysteine and decrease migraine symptoms. However the influence of dietary folate intake on migraine has been unclear. The aim of the current study was to analyse the association of dietary folate intake in the form of dietary folate equivalent (DFE), folic acid (FA) and total food folate (TFF) on migraine frequency, severity and disability. Methods A cohort of 141 adult females of Caucasian descent with MA was genotyped for the MTHFRC677T variant using restriction enzyme digestion. Dietary folate information was collected from all participants and analysed using the “FoodWorks” 2009 package. Folate consumption was compared to migraine frequency, severity and disability using linear regression. Results A significant inverse relation was observed between DFE [R2= 0.201, P= 0.045, CI (-0.004, -0.001)] and FA [R2= 0.255, P= 0.036, 95% CI (-0.009, -0.002)] consumption and migraine frequency. It was also observed that in individuals with the CC genotype for the MTHFR C677T variant, migraine frequency was significantly linked to FA consumption [R2= 0.077, P= 0.029, CI (-0.009, -0.005)]. Conclusions The results from this study indicate that folate intake in the form of folic acid may influence migraine frequency in female MA sufferers.

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This work deals with estimators for predicting when parametric roll resonance is going to occur in surface vessels. The roll angle of the vessel is modeled as a second-order linear oscillatory system with unknown parameters. Several algorithms are used to estimate the parameters and eigenvalues of the system based on data gathered experimentally on a 1:45 scale model of a tanker. Based on the estimated eigenvalues, the system predicts whether or not parametric roll occurred. A prediction accuracy of 100% is achieved for regular waves, and up to 87.5% for irregular waves.

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Background and Aims Research into craving is hampered by lack of theoretical specification and a plethora of substance-specific measures. This study aimed to develop a generic measure of craving based on elaborated intrusion (EI) theory. Confirmatory factor analysis (CFA) examined whether a generic measure replicated the three-factor structure of the Alcohol Craving Experience (ACE) scale over different consummatory targets and time-frames. Design Twelve studies were pooled for CFA. Targets included alcohol, cigarettes, chocolate and food. Focal periods varied from the present moment to the previous week. Separate analyses were conducted for strength and frequency forms. Setting Nine studies included university students, with single studies drawn from an internet survey, a community sample of smokers and alcohol-dependent out-patients. Participants A heterogeneous sample of 1230 participants. Measurements Adaptations of the ACE questionnaire. Findings Both craving strength [comparative fit indices (CFI = 0.974; root mean square error of approximation (RMSEA) = 0.039, 95% confidence interval (CI) = 0.035–0.044] and frequency (CFI = 0.971, RMSEA = 0.049, 95% CI = 0.044–0.055) gave an acceptable three-factor solution across desired targets that mapped onto the structure of the original ACE (intensity, imagery, intrusiveness), after removing an item, re-allocating another and taking intercorrelated error terms into account. Similar structures were obtained across time-frames and targets. Preliminary validity data on the resulting 10-item Craving Experience Questionnaire (CEQ) for cigarettes and alcohol were strong. Conclusions The Craving Experience Questionnaire (CEQ) is a brief, conceptually grounded and psychometrically sound measure of desires. It demonstrates a consistent factor structure across a range of consummatory targets in both laboratory and clinical contexts.

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To enhance the efficiency of regression parameter estimation by modeling the correlation structure of correlated binary error terms in quantile regression with repeated measurements, we propose a Gaussian pseudolikelihood approach for estimating correlation parameters and selecting the most appropriate working correlation matrix simultaneously. The induced smoothing method is applied to estimate the covariance of the regression parameter estimates, which can bypass density estimation of the errors. Extensive numerical studies indicate that the proposed method performs well in selecting an accurate correlation structure and improving regression parameter estimation efficiency. The proposed method is further illustrated by analyzing a dental dataset.

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Background: Hot air ballooning incidents are relatively rare, however, when they do occur they are likely to result in a fatality or serious injury. Human error is commonly attributed as the cause of hot air ballooning incidents; however, error in itself is not an explanation for safety failures. This research aims to identify, and establish the relative importance of factors contributing towards hot air ballooning incidents. Methods: Twenty-two Australian Ballooning Federation (ABF) incident reports were thematically coded using a bottom up approach to identify causal factors. Subsequently, 69 balloonists (mean 19.51 years’ experience) participated in a survey to identify additional causal factors and rate (out of seven) the perceived frequency and potential impact to ballooning operations of each of the previously identified causal factors. Perceived associated risk was calculated by multiplying mean perceived frequency and impact ratings. Results: Incident report coding identified 54 causal factors within nine higher level areas: Attributes, Crew resource management, Equipment, Errors, Instructors, Organisational, Physical Environment, Regulatory body and Violations. Overall, ‘weather’, ‘inexperience’ and ‘poor/inappropriate decisions’ were rated as having greatest perceived associated risk. Discussion: Although errors were nominated as a prominent cause of hot air ballooning incidents, physical environment and personal attributes are also particularly important for safe hot air ballooning operations. In identifying a range of causal factors the areas of weakness surrounding ballooning operations have been defined; it is hoped that targeted safety and training strategies can now be put into place removing these contributing factors and reducing the chance of pilot error.

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The sensory systems of the New Zealand kiwi appear to be uniquely adapted to occupy a nocturnal ground-dwelling niche. In addition to well-developed tactile and olfactory systems, the auditory system shows specializations of the ear, which are maintained along the central nervous system. Here, we provide a detailed description of the auditory nerve, hair cells, and stereovillar bundle orientation of the hair cells in the North Island brown kiwi. The auditory nerve of the kiwi contained about 8,000 fibers. Using the number of hair cells and innervating nerve fibers to calculate a ratio of average innervation density showed that the afferent innervation ratio in kiwi was denser than in most other birds examined. The average diameters of cochlear afferent axons in kiwi showed the typical gradient across the tonotopic axis. The kiwi basilar papilla showed a clear differentiation of tall and short hair cells. The proportion of short hair cells was higher than in the emu and likely reflects a bias towards higher frequencies represented on the kiwi basilar papilla. The orientation of the stereovillar bundles in the kiwi basilar papilla showed a pattern similar to that in most other birds but was most similar to that of the emu. Overall, many features of the auditory nerve, hair cells, and stereovilli bundle orientation in the kiwi are typical of most birds examined. Some features of the kiwi auditory system do, however, support a high-frequency specialization, specifically the innervation density and generally small size of hair-cell somata, whereas others showed the presumed ancestral condition similar to that found in the emu.