Antioxidant flavonol glycosides in mulberry (Morus alba L.) leaves isolated based on LDL antioxidant activity

Oxidation of low-density lipoprotein (LDL) has been implicated in atherogenesis. Antioxidants that prevent LDL from oxidation may reduce atherosclerosis. We investigated LDL antioxidant activity and extracted compounds of mulberry (Morus alba L.) leaves. The LDL antioxidant activity of 60% ethanol extracted of mulberry leaves, which inhibits human LDL oxidation induced by copper ion, was determined on the basis of oxidation lag time and calculated as epigallocatechin 3-gallate equivalents (58.3 μmol of EGCG equivalent/g of dry weight). Three flavonol glycosides [quercetin 3-(6-malonylglucoside), rutin (quercetin 3-rutinoside) and isoquercitrin (quercetin 3-glucoside)] were identified as the major LDL antioxidant compounds by LC-MS and NMR. The amounts of these flavonol glycosides in mulberry leaves and mulberry-leaf tea were determined by HPLC. Our results showed that quercetin 3-(6-malonylglucoside) and rutin were the predominant flavonol glycosides in the mulberry leaves.     

Image reconstruction only by phase data in phase-shifting digital holography

We describe data compression in phase-shifting digital holography. We demonstrate by experimentation that an image of a diffusely reflecting object can be reconstructed only by phase data of the derived complex amplitude. It is shown that reduction of the bit depth of the phase data does not seriously damage the image even down to 1 bit. We observe enhancement of halo in the image with low bit depths. This tendency is verified quantitatively by a one-dimensional simulation. Our procedure for smoothing the images that result from the data-compression methods is shown to be effective.     

Data‐driven execution of fast multipole methods

Fast multipole methods (FMMs) have complexity, are compute bound, and require very little synchronization, which makes them a favorable algorithm on next‐generation supercomputers. Their most common application is to accelerate N‐body problems, but they can also be used to solve boundary integral equations. When the particle distribution is irregular and the tree structure is adaptive, load balancing becomes a non‐trivial question. A common strategy for load balancing FMMs is to use the work load from the previous step as weights to statically repartition the next step. The authors discuss in the paper another approach based on data‐driven execution to efficiently tackle this challenging load balancing problem. The core idea consists of breaking the most time‐consuming stages of the FMMs into smaller tasks. The algorithm can then be represented as a directed acyclic graph where nodes represent tasks and edges represent dependencies among them. The execution of the algorithm is performed by asynchronously scheduling the tasks using the queueing and runtime for kernels runtime environment, in a way such that data dependencies are not violated for numerical correctness purposes. This asynchronous scheduling results in an out‐of‐order execution. The performance results of the data‐driven FMM execution outperform the previous strategy and show linear speedup on a quad‐socket quad‐core Intel Xeon system.Copyright © 2013 John Wiley & Sons, Ltd.