Optical Network Virtualisation using Multi-technology Monitoring and SDN-enabled Optical Transceiver

We introduce the real-time multi-technology transport layer monitoring to facilitate the coordinated virtualisation of optical and Ethernet networks supported by optical virtualise-able transceivers (V-BVT). A monitoring and network resource configuration scheme is proposed to include the hardware monitoring in both Ethernet and Optical layers. The scheme depicts the data and control interactions among multiple network layers under the software defined network (SDN) background, as well as the application that analyses the monitored data obtained from the database. We also present a re-configuration algorithm to adaptively modify the composition of virtual optical networks based on two criteria. The proposed monitoring scheme is experimentally demonstrated with OpenFlow (OF) extensions for a holistic (re-)configuration across both layers in Ethernet switches and V-BVTs

Targeting HSP90 in ovarian cancers with multiple receptor tyrosine kinase coactivation

<p>Abstract</p> <p>Background</p> <p>Ovarian cancer has the highest mortality rate of all gynecologic malignancy. The receptor tyrosine kinases (RTKs), including EGFR, ERBB2, PDGFR, VEGFR and MET, are activated in subsets of ovarian cancer, suggesting that these kinases might represent novel therapeutic targets. However, clinical trials have not or just partially shown benefit to ovarian cancers treated with EGFR, ERBB2, or PDGFR inhibitors. Despite multiple RTK activation in ovarian cancer pathogenesis, it is unclear whether transforming activity is dependent on an individual kinase oncoprotein or the coordinated activity of multiple kinases. We hypothesized that a coordinated network of multi-RTK activation is important for the tumorigenesis of ovarian cancers.</p> <p>Results</p> <p>Herein, we demonstrate co-activation of multiple RTKs (EGFR, ERBB2, ERBB4, MET and/or AXL) in individual ovarian cancer cell lines and primary tumors. We also show that coordinate inhibition of this multi-kinase signaling has substantially greater effect on ovarian cancer proliferation and survival, compared to inhibition of individual activated kinases. The inhibition of this multi-RTK signaling by HSP90 suppression results in profound pro-apoptotic and anti-proliferative effects, and is associated with the inactivation of RTK downstream PI3-K/AKT/mTOR and RAF/MAPK signaling.</p> <p>Conclusion</p> <p>These studies suggest that anti-multiple RTK strategy could be useful in the treatment of ovarian cancer.</p

Support Vector Machine for Behavior-Based Driver Identification System

We present an intelligent driver identification system to handle vehicle theft based on modeling dynamic human behaviors. We propose to recognize illegitimate drivers through their driving behaviors. Since human driving behaviors belong to a dynamic biometrical feature which is complex and difficult to imitate compared with static features such as passwords and fingerprints, we find that this novel idea of utilizing human dynamic features for enhanced security application is more effective. In this paper, we first describe our experimental platform for collecting and modeling human driving behaviors. Then we compare fast Fourier transform (FFT), principal component analysis (PCA), and independent component analysis (ICA) for data preprocessing. Using machine learning method of support vector machine (SVM), we derive the individual driving behavior model and we then demonstrate the procedure for recognizing different drivers by analyzing the corresponding models. The experimental results of learning algorithms and evaluation are described

Implication of Production Tax Credit on Economic Dispatch for Electricity Merchants with Storage and Wind Farms

The production tax credit (PTC) promotes wind energy development, reduces power generation costs, and can affect merchants\u27 joint economic dispatch, particularly for electricity merchants with both energy storage and wind farms. Two common PTC policies are studied – in the first policy, a wind farm receives PTC by selling wind generation to the market and its storage can be used to store energy from the wind generation and energy purchased from the grid but the energy released from the storage cannot receive PTC; in the second policy, the energy released from the storage can also qualify for PTC but purchasing energy from the grid is not allowed. We then employ dynamic programming to study merchants\u27 optimal decision-making while considering PTC and the physical characteristics of storage systems. We analytically show that the state of charge (SOC) range can be segmented into different regions by SOC reference points under two PTC policies. The merchant\u27s optimal action can be conveniently and uniquely determined based on the region within which the current SOC falls. Moreover, this study illustrates that PTC could substantially alter the optimal scheduling policy structures by affecting reference points and their relationships. The results showed that the frequencies for charging and discharging storage decisions decreased with an increase in PTC subsidy. Last, we confirm that, although the first policy allows merchants to buy electricity from the market, the second policy can bring more profits when the PTC is large at the current PTC rates. The findings can provide multistage decision-making guidance to electricity merchants in the wholesale power market

Effects of Danqidihuang Granules on glucolipid metabolism in insulin-resistant rats

AbstractObjectiveTo explore whether the insulin resistance (IR) model could be established through feeding Sprague-Dawley (SD) rats high-sugar and high-fat diets and to further observe the preventive and treatment effects of different doses of Danqidihuang Granules in rats.MethodsThirty-two SD rats were divided randomly into control group A (given regular feed), model group B (food high in sugar and fat), intervention group C (food high in sugar and fat as well as regular doses of Danqidihuang Granules), and intervention group D (food high in sugar and fat as well as double doses of Danqidihuang Granules). The interventions were for 8 weeks. Motion, change in color, body weight, and food intake, as well as plasma lipids (including low-density lipoprotein-cholesterol (LDL-C), high-density lipoprotein-cholesterol (HDL-C), total cholesterol (TC) and triglyceride (TG), fasting blood glucose (FBG), fasting insulin (FINs) levels, insulin sensitivity index (ISI), and insulin resistance index (HOMO-IR) were observed.ResultsAt the end of the second week of the experiment, the appetite and activities of rats in groups B, C and D decreased significantly compared with group A. The fur of the rats in those three groups was curly. After the fourth week, the activities, food intake and color of rats in group B were worse than those in groups C and D, but there were no significant differences in weight (P>0.05). Compared with group A, LDL-C, TC, FBG and HOMO-IR in model group B were increased significantly (P<0.05), whereas the FINs and ISI increased obviously (P<0.05). The levels of LDL-C and TC in group D was decreased obviously compared with those in group C, and HOMO-IR in group D was less than that in group B (P<0.05).ConclusionsDanqidihuang Granules helped to prevent and improved the insulin resistance of rats