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https://www.selleckchem.com/products/c646.html To correct the intensity difference of static background signal between bright blood images and dark blood images in subtractive non-contrast-enhanced MR angiography using robust regression, thereby improving static background signal suppression on subtracted angiograms. Robust regression (RR), usingiteratively reweighted least squares,is used to calculate the regression coefficient of background tissues from a scatter plot showing the voxel intensity of bright blood images versus dark blood images. The weighting function is based on either the Euclidean distance from the estimated regression line or the deviation angle. Results from RR using the deviation angle (RRDA), conventional RR using the Euclidean distance, and ordinary leastsquares regression were compared with reference values determined manually by two observers. Performance was evaluated over studies using different sequences, including 36 thoracic flow-sensitive dephasing data sets, 13 iliac flow-sensitive dephasing data sets, and 26 femoral ground signal and improve background suppression of subtractive non-contrast-enhanced MR angiography techniques. RR deviation angle has the most robust and accurate overall performance among three regression methods.In this work, we discuss representative examples of the application of nonuniform sampling (NUS) in small-molecule structure determination in a pharmaceutical research and development and quality control setting. We demonstrate the advantages of NUS over traditional sampling in various industrial applications of nuclear magnetic resonance (NMR). We propose an optimal trade-off between the quality and the time efficiency of 'routine' measurements, as demonstrated via a test sample of vinpocetine analyzed on a 'work horse' NMR spectrometer. In addition, we present case studies where the application of NUS contributed significantly to the successful completion of some challenging structure determination task at

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