889 resultados para single-blind method
Resumo:
A number of routes to hydroxyiminodehydroquinate, one of the most potent inhibitors of type II dehydroquinase that is currently known, have been investigated. Methods based on the existing literature synthesis, i.e. oxime formation of a suitably C-4 and C-5 protected methyl 3-dehydroquinate derivative were initially studied. Benzoyl protection did give the desired product but in low overall yield. An alternative BBA protection strategy starting with a protected dehydroquinate was successful in generating a C4/C5 analogue of the desired oxime in high yield. Further investigation revealed that it was unecessary to protect the dehydroquinate precursor, hence the potassium salt corresponding to the desired oxime was simply synthesised as a single isomer from methyl dehydroquinate.
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In this paper we concentrate on the direct semi-blind spatial equalizer design for MIMO systems with Rayleigh fading channels. Our aim is to develop an algorithm which can outperform the classical training based method with the same training information used, and avoid the problems of low convergence speed and local minima due to pure blind methods. A general semi-blind cost function is first constructed which incorporates both the training information from the known data and some kind of higher order statistics (HOS) from the unknown sequence. Then, based on the developed cost function, we propose two semi-blind iterative and adaptive algorithms to find the desired spatial equalizer. To further improve the performance and convergence speed of the proposed adaptive method, we propose a technique to find the optimal choice of step size. Simulation results demonstrate the performance of the proposed algorithms and comparable schemes.
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Background: Effective bed use is crucial to an efficient NHS. Current targets suggest a decrease in mean occupancy as the most appropriate method of improving overall efficiency. The elderly and those suffering from complex medical problems are thought to account for a high proportion of overall bed occupancy.
Aim: To assess the effect of prolonged hospital stay (>100 days) on overall bed occupancy in a modern teaching hospital.
Design: Retrospective analysis.
Methods: Analysis of all admission episodes (n = 117 178) over a five-year period in a large teaching hospital in a single UK region, serving a population of approximately 200 000. A logistic regression multi-factorial model was used to assess the effect of demographic and diagnostic variables on duration of stay.
Results: A prolonged stay (>100 days) was seen in 648 admission episodes (0.6%). These accounted for 11% of the overall bed occupancy over the 5-year period. Excluding all prolonged admission episodes from our analysis made no difference to the overall median length of stay.
Discussion: Prolonged hospitalizations have a significant impact on bed occupancy. Targeting these very long (>100 days) hospital stays may better improve overall efficiency, compared to targeting mean or median length of stay.
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We present a new circuit-model approach which can be used to compute the mutual impedance between two dipoles fed at the same feed point. The validity of the method is confirmed by comparison with mutual impedance values obtained when the dipoles are individually excited and orientated at angles between 0degrees and 90degrees. (C) 2004 Wiley Periodicals, Inc.
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This paper investigates the learning of a wide class of single-hidden-layer feedforward neural networks (SLFNs) with two sets of adjustable parameters, i.e., the nonlinear parameters in the hidden nodes and the linear output weights. The main objective is to both speed up the convergence of second-order learning algorithms such as Levenberg-Marquardt (LM), as well as to improve the network performance. This is achieved here by reducing the dimension of the solution space and by introducing a new Jacobian matrix. Unlike conventional supervised learning methods which optimize these two sets of parameters simultaneously, the linear output weights are first converted into dependent parameters, thereby removing the need for their explicit computation. Consequently, the neural network (NN) learning is performed over a solution space of reduced dimension. A new Jacobian matrix is then proposed for use with the popular second-order learning methods in order to achieve a more accurate approximation of the cost function. The efficacy of the proposed method is shown through an analysis of the computational complexity and by presenting simulation results from four different examples.
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Aims/hypothesis: Diabetic nephropathy, characterised by persistent proteinuria, hypertension and progressive kidney failure, affects a subset of susceptible individuals with diabetes. It is also a leading cause of end-stage renal disease (ESRD). Non-synonymous (ns) single nucleotide polymorphisms (SNPs) have been reported to contribute to genetic susceptibility in both monogenic disorders and common complex diseases. The objective of this study was to investigate whether nsSNPs are involved in susceptibility to diabetic nephropathy using a case-control design.
Methods: White type 1 diabetic patients with (cases) and without (controls) nephropathy from eight centres in the UK and Ireland were genotyped for a selected subset of nsSNPs using Illumina's GoldenGate BeadArray assay. A ? 2 test for trend, stratified by centre, was used to assess differences in genotype distribution between cases and controls. Genomic control was used to adjust for possible inflation of test statistics, and the False Discovery Rate method was used to account for multiple testing.
Results: We assessed 1,111 nsSNPs for association with diabetic nephropathy in 1,711 individuals with type 1 diabetes (894 cases, 817 controls). A number of SNPs demonstrated a significant difference in genotype distribution between groups before but not after correction for multiple testing. Furthermore, neither subgroup analysis (diabetic nephropathy with ESRD or diabetic nephropathy without ESRD) nor stratification by duration of diabetes revealed any significant differences between groups.
Conclusions/interpretation: The nsSNPs investigated in this study do not appear to contribute significantly to the development of diabetic nephropathy in patients with type 1 diabetes.
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An HPLC method has been developed and validated for the rapid determination of mercaptopurine and four of its metabolites; thioguanine, thiouric acid, thioxanthine and methylmercaptopurine in plasma and red blood cells. The method involves a simple treatment procedure based on deproteinisation by perchloric acid followed by acid hydrolysis and heating for 45 min at 100 degrees C. The developed method was linear over the concentration range studied with a correlation coefficient >0.994 for all compounds in both plasma and erythrocytes. The lower limits of quantification were 13, 14, 3, 2, 95 pmol/8 x 101 RBCs and 2, 5, 2, 3, 20 ng/ml plasma for thioguanine, thiouric acid, mercaptopurine, thioxanthine and methylmercaptopurine, respectively. The method described is selective and sensitive enough to analyse the different metabolites in a single run under isocratic conditions. Furthermore, it has been shown to be applicable for monitoring these metabolites in paediatric patients due to the low volume requirement (200 mu l of plasma or erythrocytes) and has been successfully applied for investigating population pharmacokinetics, pharmacogenetics and non-adherence to therapy in these patients. (C) 2008 Elsevier B.V. All rights reserved.
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A rapid analytical optical biosensor-based immunoassay was developed and validated for the detection of okadaic acid (OA) and its structurally related toxins from shellfish matrix. The assay utilizes a monoclonal antibody which binds to the OA group of toxins in order of their toxicities, resulting in a pseudofunctional assay. Single-laboratory validation of the assay for quantitative detection of OA determined that it has an action limit of 120 mu g/kg, a limit of detection of 31 mu g/kg, and a working range of 31-174 mu g/kg. The midpoint on the standard matrix calibration curve is 80 mu g/kg, half the current regulatory limit. Inter- and intra-assay studies of negative mussel samples spiked with various OA concentrations produced average coefficient of variation (CV) and standard deviation (SD) values of 7.9 and 10.1, respectively. The assay was also validated to confirm the ability to accurately codetect and quantify dinophysistoxin-1 (DTX-1), DTX-2, and DTX-3 from shellfish matrix. Alkaline hydrolysis was not required for the detection of DTX-3 from matrix. Excellent correlations with the data generated by the biosensor method and liquid chromatography/tandem mass spectrometry (LC/MS/MS) were obtained using a certified reference material (R-2 = 0.99), laboratory reference material, and naturally contaminated mussel samples (R-2 = 0.97). This new procedure could be used as a rapid screening procedure replacing animal-based tests for DSP toxins.
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Most single-reed woodwind instrument models rely on a quasistationary approximation to describe the relationship between the volume flow and. the pressure difference across the reed channel. Semiempirical models based on the quasistationary approximation are very useful in explaining the fundamental characteristics of this family of instruments such as self-sustained oscillations and threshold of blowing pressure. However, they fail at explaining more complex phenomena associated with the fluid-structure interaction during dynamic flow regimes, such as the transient and steady-state behavior of the system as a function. of the mouthpiece geometry. Previous studies have discussed the accuracy of the quasistationary approximation but the amount of literature on the subject is sparse, mainly due to the difficulties involved in the measurement of dynamic flows in channels with an oscillating reed. In this paper, a numerical technique based on the lattice Boltzmann method and a finite difference scheme is proposed in order to investigate the characteristics of fully coupled fluid-structure interaction in single-reed mouthpieces with different channel configurations. Results obtained for a stationary simulation with a static reed agree very well with those predicted by the literature based on the quasistationary approximation. However, simulations carried out for a dynamic regime with dn oscillating reed show that the phenomenon associated with flow detachment and reattachment diverges considerably frorn the theoretical assumptions. Furthermore, in the case of long reed channels, the results obtained for the vena contracta factor are in significant disagreement with those predicted by theory. For short channels, the assumption of constant vena contracta was found to be valid for only 40% of the duty cycle. (c) 2007 Acoustical Society of America.
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In this work we present the theoretical framework for the solution of the time-dependent Schrödinger equation (TDSE) of atomic and molecular systems under strong electromagnetic fields with the configuration space of the electron’s coordinates separated over two regions; that is, regions I and II. In region I the solution of the TDSE is obtained by an R-matrix basis set representation of the time-dependent wave function. In region II a grid representation of the wave function is considered and propagation in space and time is obtained through the finite-difference method. With this, a combination of basis set and grid methods is put forward for tackling multiregion time-dependent problems. In both regions, a high-order explicit scheme is employed for the time propagation. While, in a purely hydrogenic system no approximation is involved due to this separation, in multielectron systems the validity and the usefulness of the present method relies on the basic assumption of R-matrix theory, namely, that beyond a certain distance (encompassing region I) a single ejected electron is distinguishable from the other electrons of the multielectron system and evolves there (region II) effectively as a one-electron system. The method is developed in detail for single active electron systems and applied to the exemplar case of the hydrogen atom in an intense laser field.
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Three-dimensional reconstruction from volumetric medical images (e.g. CT, MRI) is a well-established technology used in patient-specific modelling. However, there are many cases where only 2D (planar) images may be available, e.g. if radiation dose must be limited or if retrospective data is being used from periods when 3D data was not available. This study aims to address such cases by proposing an automated method to create 3D surface models from planar radiographs. The method consists of (i) contour extraction from the radiograph using an Active Contour (Snake) algorithm, (ii) selection of a closest matching 3D model from a library of generic models, and (iii) warping the selected generic model to improve correlation with the extracted contour.
This method proved to be fully automated, rapid and robust on a given set of radiographs. Measured mean surface distance error values were low when comparing models reconstructed from matching pairs of CT scans and planar X-rays (2.57–3.74 mm) and within ranges of similar studies. Benefits of the method are that it requires a single radiographic image to perform the surface reconstruction task and it is fully automated. Mechanical simulations of loaded bone with different levels of reconstruction accuracy showed that an error in predicted strain fields grows proportionally to the error level in geometric precision. In conclusion, models generated by the proposed technique are deemed acceptable to perform realistic patient-specific simulations when 3D data sources are unavailable.
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The association of very-low-density lipoprotein (VLDL) with atherosclerosis remains controversial. However, studies have shown that oxidative modification of VLDL can promote foam cell formation, leading to the development of atherosclerosis. A rapid method is described which will allow the significance of VLDL oxidation to be assessed in clinical studies. VLDL was isolated from heparinized plasma by a 1-h, single spin ultracentrifugation. Total protein was standardized to 25 mg/L. Oxidation was promoted by the addition of copper ions (17.5 mu mol/L, final concentration) incubated at 37 degrees C. Conjugated diene production was followed at 234 nm. Total assay preparation time was 2 h. Urate greatly inhibited the oxidation of VLDL and was successfully removed by size exclusion chromatography. VLDL isolated from frozen plasma (-70 degrees C) was stable for 15 weeks. This simple, rapid method for the isolation of VLDL may be applied to assess the significance of VLDL oxidation in disease.
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A surface plasmon resonance (SPR) optical biosensor method was developed for the detection of paralytic shellfish poisoning (PSP) toxins in shellfish. This application was transferred in the form of a prototype kit to seven laboratories using Biacore QSPR optical biosensor instrumentation for interlaboratory evaluation. Each laboratory received 20 shellfish samples across a range of species including blind duplicates for analysis. The samples consisted of 4 noncontaminated samples spiked in duplicate with a low level of PSP toxins (240 mu g STXcliHCl equivalents/kg), a high level of saxitoxin (825 mu g STXdiHCl/kg), 2 noncontarninated, and 14 naturally contaminated samples. All 7 participating laboratories completed the study, and HorRat values obtained were
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Indicator inks, previously shown to be capable of rapidly assessing photocatalytic activity via a novel photo-reductive mechanism, were simply applied via an aerosol spray onto commercially available pieces of Activ (TM) self-cleaning glass. Ink layers could be applied with high evenness of spread, with as little deviation as 5% upon UV-visible spectroscopic assessment of 25 equally distributed positions over a 10 cm x 10 cm glass cut. The inks were comprised of either a resazurin (Rz) or dichloroindophenol (DCIP) redox dye with a glycerol sacrificial electron donor in an aqueous hydroxyethyl cellulose (HEC) polymer media. The photo-reduction reaction under UVA light of a single spot was monitored by UV-vis spectroscopy and digital images attained from a flat-bed scanner in tandem for both inks. The photo-reduction of Rz ink underwent a two-step kinetic process, whereby the blue redox dye was initially reduced to a pink intermediate resorufin (Rf) and subsequently reduced to a bleached form of the dye. In contrast, a simple one-step kinetic process was observed for the reduction of the light blue redox dye DCIP to its bleached intermediates. Changes in red-green-blue colour extracted from digital images of the inks were inversely proportional to the changes seen at corresponding wavelengths via UV-visible absorption spectroscopy and wholly indicative of the reaction kinetics. The photocatalytic activity areas of cuts of Activ (TM) glass, 10 cm x 10 cm in size, were assessed using both Rz and DCIP indicator inks evenly sprayed over the films: firstly using UVA lamp light to activate the underlying Activ (TM) film (1.75 mW cm(-2)) and secondly under solar conditions (2.06 +/- 0.14 mW cm(-2)). The photo-reduction reactions were monitored solely by flat-bed digital scanning. Red-green-blue values of a generated 14 x 14 grid (196 positions) that covered the entire area of each film image were extracted using a Custom-built program entitled RGB Extractor(C). A homogenous degradation over the 196 positions analysed for both Rz (Red colour deviation = 19% UVA, 8% Solar: Green colour deviation = 17% UVA, 12% Solar) and DCIP (Red colour deviation = 22% UVA, 16% Solar) inks was seen in both UVA and solar experiments, demonstrating the consistency of the self-cleaning titania layer on Activ (TM). The method presented provides a good solution for the high-throughput photocatalytic screening of a number of homogenous photocatalytically active materials simultaneously or numerous positions on a single film; both useful in assessing the homogeneity of a film or determining the best combination of reaction components to produce the optimum performance photocatalytic film. (C) 2010 Elsevier B.V. All rights reserved.
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The mean velocity and turbulence intensity are the two main inputs to investigate the ship propeller induced seabed scouring resulting from a vessel is manoeuvring within a port where the underkeel clearances are low. More accurate data including the turbulence intensity is now available by using the laser doppler anemometry (LDA) measurement system and computational fluid dynamics (CFD) approach. Turbulence intensity has a loose definition, which is the velocity fluctuation as the root mean square (RMS) referenced to a mean flow velocity. However, the velocity fluctuation and mean velocity can be the overall value includingx, y and z directions or the value of a single component. LDA and CFD results were obtained from two different acquisition systems (Dantec LDA system and Fluent CFD package) and therefore the outputs cannot be compared directly. An effective method is proposed for comparing the turbulence intensity between the experimental measurements and the computational predictions within a ship propeller jet. The flow patterns of turbulence intensity within a ship propeller jet are presented by using the LDA measurements and CFD results from turbulence models of standard k-e, RNG k-e, realizable k–e, standard k–?, SST k–?and Reynolds stresses.