Bias was substantial even for references with small departure from the standard and persisted with increasing sample size. Coverage of interval estimates was far from nominal level.

Conclusion: In the selleck chemicals llc presence of varying reference tests, avoidance of bias and invalid confidence intervals for diagnostic performance requires applying a model that accounts for differences in reference test and heterogeneity among

studies. (C) 2013 Elsevier Inc. All rights reserved.”
“Phaleria macrocarpa (Mahkota dewa) seed was examined to determine the optimal conditions of oil yield by solvent extraction method using n-hexane as extracting solvent. Response surface methodology (RSM) was employed to describe explicitly the influence of extraction time, temperature and solvent-to-feed ratio on the yield of oil using central composite design (CCD). The linear, quadratic and interaction terms of the studied variables have significant (P<0.05) effect on the oil yield. The temperature of 72 degrees C, extraction time selleck of 8.4h and solvent-to-feed ratio of 10.9 ml/g were the optimal conditions for seed oil extraction. The maximum oil yield was 55.32 g/100 g dry weight under these optimal conditions. Main chemical constituents of oil were determined by Gas chromatography-mass spectroscopy (GC-MS) and Fourier transform infrared spectroscopy

(FTIR). Twelve components were identified by GC-MS analysis after formation of fatty acid methyl ester (FAME). Total saturated fatty acids were 19.38% whereas monounsaturated

fatty acids and polyunsaturated fatty acids were 44.23% and 36.38%, respectively. Oleic acid, 18:1(43.56%) and linoleic acid, 18:2(36.25%) were the main fatty acid constituents of Mahkota dewa seed oil. The quantity of unsaturated fatty acids was higher than saturated fatty acids in P. macrocarpa Danusertib chemical structure seed oil. (C) 2013 Elsevier B.V. All rights reserved.”
“This work addresses the problem of real-time online reconstruction of dynamic magnetic resonance imaging sequences. The proposed method reconstructs the difference between the previous and the current image frames. This difference image is sparse. We recover the sparse difference image from its partial k-space scans by using a nonconvex compressed sensing algorithm. As there was no previous fast enough algorithm for real-time reconstruction, we derive a novel algorithm for this purpose. Our proposed method has been compared against state-of-the-art offline and online reconstruction methods. The accuracy of the proposed method is less than offline methods but noticeably higher than the online techniques. For real-time reconstruction we are also concerned about the reconstruction speed. Our method is capable of reconstructing 128 x 128 images at the rate of 6 frames/s, 180 x 180 images at the rate of 5 frames/s and 256 256 images at the rate of 2.5 frames/s.