924 resultados para Mean Field Analysis


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Mode of access: Internet.

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Issued in cooperation with Iowa State University of Science and Technology, Agriculture and Home Economics Experiment Station, and the Center for Agricultural and Economic Development.

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Understanding, and controlling, the conditions under which calcite precipitates within geothermal energy production systems is a key step in maintaining production efficiency. In this study, I apply methods of bulk and clumped isotope thermometry to an operating geothermal energy facility in northern Nevada to see how those methods can better inform the facility owner, AltaRock Energy, Inc., about the occurrence of calcite scale in their power plant. I have taken water samples from five production wells, the combined generator effluent, shallow cold-water wells, monitoring wells, and surface water. I also collected calcite scale samples from within the production system. Water samples were analyzed for stable oxygen isotope composition (d18O). Calcite samples were analyzed for stable oxygen and carbon (d13C) composition, and clumped isotope composition (D47). With two exceptions, the water compositions are very similar, likely indicating common origin and a well-mixed hydrothermal system. The calcite samples are likewise similar to one another. Apparent temperatures calculated from d18O values of water and calcite are lower than those recorded for the system. Apparent temperatures calculated from D47 are several degrees higher than the recorded well temperatures. The lower temperatures from the bulk isotope data are consistent with temperatures that could be expected during a de-pressurization of the production system, which would cause boiling in the pipes, a reduction in system temperature, and rapid precipitation of calcite scale. However, the high apparent temperature indicated by the D47 data suggests that the calcite is depleted in clumped isotopes given the known temperature of the system, which is inconsistent with this hypothesis. This depletion could instead result from disequilibrium isotopic fractionation during the aforementioned boil events, which would make both the apparent d18O-based and D47-based temperatures unrepresentative of the actual water temperature. This research can help improve our understanding of how isotopic analyses can better inform us about the movement of water through geothermal systems of the past and how it now moves through modern systems. Increased understanding of water movement in these systems could potentially allow for more efficient utilization of geothermal energy as a renewable resource.

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Aim Cardiovascular disease (CVD) rates are substantially higher among patients with Type 2 diabetes than in the general population. The objective of this study was to identify the determinants of carotid intima media thickness (IMT) in patients with Type 2 diabetes. Methods We measured the thickness of the intima media layer of the carotid artery, a strong predictor of the risk of future vascular events, in 397 Type 2 diabetic patients drawn from the Fenofibrate Intervention and Event Lowering in Diabetes study, prior to treatment allocation. Results The mean IMT was 0.78 mm [interquartile range (IQR) 0.23 mm], and the maximum IMT was 1.17 mm (IQR 0.36 mm). By multivariate analysis, age, sex, duration of diabetes, triglycerides, and total cholesterol were independently correlated with IMT, as was urine albumin-creatinine ratio (ACR) (P < 0.001). The effect of ACR on IMT was further examined by tertile. Clinically significant differences in IMT were associated with ACR > 0.65 mg/mmol, approximately one-fifth the standard clinical threshold for microalbuminuria (P < 0.01). Long-term diabetes, independent of other parameters, was associated with a 50% increase in age-related thickening. Conclusions IMT in people with Type 2 diabetes is independently and continuously related to urine albumin levels and to the duration of diabetes. These results support previous data linking urine albumin measurements within the normal range with increased ischaemic cardiac mortality in the setting of Type 2 diabetes, and strongly suggest that urine albumin levels within this range should trigger a formal evaluation for CVD.

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This paper presents a finite-difference time-domain (FDTD) simulator for electromagnetic analysis and design applications in MRI. It is intended to be a complete FDTD model of an MRI system including all RF and low-frequency field generating units and electrical models of the patient. The pro-ram has been constructed in an object-oriented framework. The design procedure is detailed and the numerical solver has been verified against analytical solutions for simple cases and also applied to various field calculation problems. In particular, the simulator is demonstrated for inverse RF coil design, optimized source profile generation, and parallel imaging in high-frequency situations. The examples show new developments enabled by the simulator and demonstrate that the proposed FDTD framework can be used to analyze large-scale computational electromagnetic problems in modern MRI engineering. (C) 2004 Elsevier Inc. All rights reserved.

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In early generation variety trials, large numbers of new breeders' lines need to be compared, and usually there is little seed available for each new line. A so-called unreplicated trial has each new line on just one plot at a site, but includes several (often around five) replicated check or control (or standard) varieties. The total proportion of check plots is usually between 10% and 20%. The aim of the trial is to choose some good performing lines (usually around 1/3 of those tested) to go on for further testing, rather than precise estimation of their mean yield. Now that spatial analyses of data from field experiments are becoming more common, there is interest in an efficient layout of an experiment given a proposed spatial analysis. Some possible design criteria are discussed, and efficient layouts under spatial dependence are considered.

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This report outlines the derivation and application of a non-zero mean, polynomial-exponential covariance function based Gaussian process which forms the prior wind field model used in 'autonomous' disambiguation. It is principally used since the non-zero mean permits the computation of realistic local wind vector prior probabilities which are required when applying the scaled-likelihood trick, as the marginals of the full wind field prior. As the full prior is multi-variate normal, these marginals are very simple to compute.

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Principal components analysis (PCA) has been described for over 50 years; however, it is rarely applied to the analysis of epidemiological data. In this study PCA was critically appraised in its ability to reveal relationships between pulsed-field gel electrophoresis (PFGE) profiles of methicillin- resistant Staphylococcus aureus (MRSA) in comparison to the more commonly employed cluster analysis and representation by dendrograms. The PFGE type following SmaI chromosomal digest was determined for 44 multidrug-resistant hospital-acquired methicillin-resistant S. aureus (MR-HA-MRSA) isolates, two multidrug-resistant community-acquired MRSA (MR-CA-MRSA), 50 hospital-acquired MRSA (HA-MRSA) isolates (from the University Hospital Birmingham, NHS Trust, UK) and 34 community-acquired MRSA (CA-MRSA) isolates (from general practitioners in Birmingham, UK). Strain relatedness was determined using Dice band-matching with UPGMA clustering and PCA. The results indicated that PCA revealed relationships between MRSA strains, which were more strongly correlated with known epidemiology, most likely because, unlike cluster analysis, PCA does not have the constraint of generating a hierarchic classification. In addition, PCA provides the opportunity for further analysis to identify key polymorphic bands within complex genotypic profiles, which is not always possible with dendrograms. Here we provide a detailed description of a PCA method for the analysis of PFGE profiles to complement further the epidemiological study of infectious disease. © 2005 Elsevier B.V. All rights reserved.