Effect of L-carnitine treatment on very low density lipoprotein kinetics in the hyperlipidemic rabbit

This study examined the hypolipidemic effect of 4 weeks of L-carnitine treatment (170 mg/kg b.w./day) in New Zealand White rabbits fed a high fat diet (5% corn oil/0.5% cholesterol). Specifically, [3H] glycerol and [125I] very low density lipoprotein (VLDL) turnover studies were conducted to examine the effect of treatment on VLDL kinetics. The masses of plasma VLDL-triglycerides (VLDL-TG) and VLDL-apoprotein B (VLDL-apoB) were significantly increased by the high-fat diet. Four weeks of treatment with L-carnitine significantly reduced these masses. Kinetic analysis indicated that fat feeding reduced the fractional catabolic rates (FCRs) of VLDL-TG and VLDL-apoB relative to chow-fed controls. The transport of these VLDL components was not altered by the diet. L-carnitine treatment had no effect on the FCRs of VLDL-TG and VLDL-apoB or on the transport of VLDL-apoB. Yet, treatment significantly lowered the transport of VLDL-TG. These data indicate that the lipid-lowering effect of L-carnitine in this animal model was due, in part, to a decrease in the transport and not due to an alteration in the fractional catabolic rate of VLDL-TG.     

Prediction-based energy-efficient target tracking protocol in wireless sensor networks

A prediction based energy-efficient target tracking protocol in wireless sensor networks (PET) was proposed for tracking a mobile target in terms of sensing and communication energy consumption. In order to maximize the lifetime of a wireless sensor network (WSN), the volume of messages and the time for neighbor discovery operations were minimized. The target was followed in a special region known as a face obtained by planarization technique in face-aware routing. An election process was conducted to choose a minimal number of appropriate sensors that are the nearest to the target and a wakeup strategy was proposed to wakeup the appropriate sensors in advance to track the target. In addition, a tracking algorithm to track a target step by step was introduced. Performance analysis and simulation results show that the proposed protocol efficiently tracks a target in WSNs and outperforms some existing protocols of target tracking with energy saving under certain ideal situations.     

A comparative study of GPU programming models and architectures using neural networks

Recently, General Purpose Graphical Processing Units (GP-GPUs) have been identified as an intriguing technology to accelerate numerous data-parallel algorithms. Several GPU architectures and programming models are beginning to emerge and establish their niche in the High-Performance Computing (HPC) community. New massively parallel architectures such as the Nvidia??s Fermi and AMD/ATi??s Radeon pack tremendous computing power in their large number of multiprocessors. Their performance is unleashed using one of the two GP-GPU programming models: Compute Unified Device Architecture (CUDA) and Open Computing Language (OpenCL). Both of them offer constructs and features that have direct bearing on the application runtime performance. In this paper, we compare the two GP-GPU architectures and the two programming models using a two-level character recognition network. The two-level network is developed using four different Spiking Neural Network (SNN) models, each with different ratios of computation-to-communication requirements. To compare the architectures, we have chosen the two extremes of the SNN models for implementation of the aforementioned two-level network. An architectural performance comparison of the SNN application running on Nvidia??s Fermi and AMD/ATi??s Radeon is done using the OpenCL programming model exhausting all of the optimization strategies plausible for the two architectures. To compare the programming models, we implement the two-level network on Nvidia??s Tesla C2050 based on the Fermi architecture. We present a hierarchy of implementations, where we successively add optimization techniques associated with the two programming models. We then compare the two programming models at these different levels of implementation and also present the effect of the network size (problem size) on the performance. We report significant application speed-up, as high as 1095× for the most computation intensive SNN neuron model, against a serial implementation on the Intel Core 2 Quad host. A comprehensive study presented in this paper establishes connections between programming models, architectures and applications.     

A Study of the flow phenomenon of water in a channel with flat plate obstruction geometry at the entry

The flow ina parallel walled test channel, when obstructed with a geometry at the entrance, can be forward, reverse and stagnant depending on the position of the obstruction. This interesting flow phenomenon has potential benefit in the control of energy and various flows in the process industry. In this experiment, the flat plate obstruction geometry was used as an obstruction at the entry of the test channel. The parameters that influence the flow inside and around the test channel were the gap (g) between the test channel and the obstruction geometry, the length (L) of the test channel and the Reynolds number (Re). The effect of the gap to channel width ratio (g/w) on the magnitude of the velocity ratio (V₁/V₀ : velocity inside/ velocity outside the test channel) was investigated for a range of Reynolds numbers. The maximum reverse flow observed was nearly 20% to 60% of the outside velocity for Reynolds number ranging from 1000 to 9000 at g/w ratio of 1.5. The maximum forward velocity inside the test channel was found 80% of the outside velocity at higher g/w ratio of 8. The effect of the test channel length on the velocity ratio was investigated for different g/w ratios and a fixed Reynolds number of 4000. The influence of the Reynolds number on the velocity ratio is also discussed and presented for different gap to width ratio (g/w). The flow visualisation photo-graphs showing fluid motion inside and around the test channel are also presented and discussed.     

Radiation crosslinked polyvinyl alcohol/polyvinyl pyrrolidone/acrylic acid hydrogels: swelling,crosslinking and dye adsorption study

Iranian Polymer Journal - Hydrogels were produced from mixtures of polyvinyl alcohol (PVA), polyvinyl pyrrolidone (PVP), and acrylic acid (AAc) using γ-radiation at doses of 3, 7, and...     

Optimal utilisation level for lean product development in a multitasking context

Flow of information is of utmost importance during product development (PD) endeavours with timely feedback supporting the resolution of higher risk elements. PD task size, multitasking and resource utilisation levels of the PD system influence information flow and the value ultimately realised from the investment in PD. In this paper, a model incorporating a methodology developed using queuing theory, and in particular, results obtained for Jackson networks are extended to help engineering management to improve PD task flow and consequently become more ‘lean’. Considered factors include: optimal PD task size and multitasking (focus) level as well as the utilisation level of PD resources. Empirical data were collected from a case study company and compared to optimal values. The benefits of the proposed model and approaches are discussed.     

Transfer between pose and illumination training in face recognition.

The relationship between pose and illumination learning in face recognition was examined in a yes–no recognition paradigm. The authors assessed whether pose training can transfer to a new illumination or vice versa. Results show that an extensive level of pose training through a face–name association task was able to generalize to a new illumination (Experiments 1 and 3), but an equal level of illumination training failed to generalize to a new pose (Experiment 2). The transfer of pose training was likely to depend on a relatively extensive level of training because the same faces with reduced level of exposure (Experiment 4) were unable to reproduce the transfer effect. The findings suggest that generalization of pose training may be extended to different types of image variation, whereas generalization of illumination training may be confined within the trained type of variation. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Preparation of L-talose and D-gulose from L-tagatose and D-sorbose, respectively, using immobilized L-rhamnose isomerase

L-rhamnose isomerase of Pseudomonas sp. LL172 immobilized on BCW 2603 Chitopearl beads was used to produce L-talose and D-gulose. At equilibrium, the production yields of L-talose and D-gulose were determined to be 12 and 10% from L-tagatose and D-sorbose, respectively. The crystallized products were confirmed by HPLC, IR and NMR spectra, and optical rotation measurement analyses.