The role of apoptosis in the modulation of colon carcinogenesis by dietary fat and by the organoselenium compound 1,4-phenylenebis(methylene)selenocyanate

Studies in laboratory animals have demonstrated that dietary supplements of organoselenium, 1,4-phenylenebis(methylene)selenocyanate (p-XSC) inhibit colon carcinogenesis. Diverse chemopreventive agents and clinically used anticancer drugs have been shown to induce apoptosis in colonic tumors. Inducing apoptosis is a key mechanism for the effectiveness of some chemopreventive agents; however, failure of apoptosis is now believed to contribute to the development of human cancer. In this study, we determined the number of apoptotic bodies in the colon tumors of rats fed a low-fat (LF) or a high-fat (HF) diet with or without p-XSC treatment. At 5 weeks of age, male F344 rats were divided into four groups, which were then maintained on one of the following diets: LF, 5% corn oil; HF, 23.5% corn oil; and LF and HF supplemented with 20 ppm p-XSC. In addition, the LF or HF diet with p-XSC supplements was administered either during the initiation stage or postinitiation. At 7 weeks of age, all rats except those intended for vehicle (normal saline) treatment were given 15 mg/kg of body weight of azoxymethane once weekly for 2 weeks. The animals were sacrificed 38 weeks after carcinogen treatment, and their colonic tumors were examined for appearance of apoptosis. The LF diet significantly increased the percentage of apoptosis as compared to the HF diet; the percentage of apoptosis in LF and HF diets were 12.4 and 2.9. The colon tumors that were present in the groups fed p-XSC together with a LF or a HF diet after carcinogen administration (postinitiation period) had a higher number of apoptotic bodies than those that were present in the animals fed p-XSC before carcinogen treatment (initiation period). The extent of apoptosis was weak when p-XSC was given with a HF diet (4.4%) during the initiation phase, but it was high significant when p-XSC was administered with LF diet (25.2%). Taken together, our data suggest that administration of LF diet supplemented with p-XSC increases apoptosis as compared to a HF diet alone.     

Robust control of polytopic systems by convex optimization

Robust control synthesis of linear time-invariant SISO polytopic systems is investigated using the polynomial approach. A convex set of all stabilizing controllers for a polytopic system is given over an infinite-dimensional space. A finite-dimensional approximation of this set is obtained using the orthonormal basis functions and represented by a set of LMIs thanks to the KYP lemma. Then, an LMI based convex optimization problem for robust pole placement with sensitivity function shaping in two- and infinity-norm is proposed. The simulation results show the effectiveness of the proposed method.     

Effects of Inhibition of Carotenoids on the Lipids Synthesis by Micrococcus colpogenes

Effect of glucose concentration and the inhibition of carotenoids on the lipids synthesis by Micrococcus colpogenes were studied. It was observed that the maximum lipid production was obtained when 2 % glucose was used as carbon source. The inhibition of carotenoids with diphenylaminc (25 mg/L) showed 37 % increase in the lipid synthesis.     

Adaptive synchronization of master–slave systems with mixed neutral and discrete time‐delays and nonlinear perturbations

This paper investigates the delay‐dependent adaptive synchronization problem of the master and slave structure of linear systems with both constant neutral and time‐varying discrete time‐delays and nonlinear perturbations based on the Barbalat lemma and matching conditions. An adaption law which includes the master‐slave parameters is obtained by using the Lyapunov functional method and inequality techniques to synchronize the master‐slave systems without the knowledge of upper bounds of perturbation terms. Particularly, it is shown that the synchronization speed can be controlled by adjusting the update gain of the synchronization signal. A numerical example has been given to show the effectiveness of the method. Copyright © 2011 John Wiley and Sons Asia Pte Ltd and Chinese Automatic Control Society     

Energy-efficient clustering in mobile ad-hoc networks using multi-objective particle swarm optimization

A mobile ad hoc network (MANET) is dynamic in nature and is composed of wirelessly connected nodes that perform hop-by-hop routing without the help of any fixed infrastructure. One of the important requirements of a MANET is the efficiency of energy, which increases the lifetime of the network. Several techniques have been proposed by researchers to achieve this goal and one of them is clustering in MANETs that can help in providing an energy-efficient solution. Clustering involves the selection of cluster-heads (CHs) for each cluster and fewer CHs result in greater energy efficiency as these nodes drain more power than noncluster-heads. In the literature, several techniques are available for clustering by using optimization and evolutionary techniques that provide a single solution at a time. In this paper, we propose a multi-objective solution by using multi-objective particle swarm optimization (MOPSO) algorithm to optimize the number of clusters in an ad hoc network as well as energy dissipation in nodes in order to provide an energy-efficient solution and reduce the network traffic. In the proposed solution, inter-cluster and intra-cluster traffic is managed by the cluster-heads. The proposed algorithm takes into consideration the degree of nodes, transmission power, and battery power consumption of the mobile nodes. The main advantage of this method is that it provides a set of solutions at a time. These solutions are achieved through optimal Pareto front. We compare the results of the proposed approach with two other well-known clustering techniques; WCA and CLPSO-based clustering by using different performance metrics. We perform extensive simulations to show that the proposed approach is an effective approach for clustering in mobile ad hoc networks environment and performs better than the other two approaches.     

Mesoporous SBA-15@n-Pr-THAM-ZrO organic–inorganic hybrid: as a highly efficient reusable nanocatalyst for the synthesis of polyhydroquinolines and 2,3-dihydroquinazolin-4 (1h)-ones

Journal of Porous Materials - In this work, tris(hydroxymethyl)aminomethane-Zirconium complex supported on modified SBA-15 (SBA-15@n-Pr-THMAM-ZrO) prepared as a novel mesoporous catalyst. The...     

Proactive task migration with a self-adjusting migration threshold for dynamic thermal management of multi-core processors

Request for more computation power steadily forces designers to provide more powerful processors using more number of cores on a single chip. The increasing complexity of processors leads to higher integration density, power density, and temperature. For avoiding thermal emergencies, various dynamic thermal management techniques have been presented. In this paper, we present a novel online self-adjusting temperature threshold schema for dynamic thermal management to minimize both average and peak temperature with very low performance overhead. Our proposed algorithm adjusts migration threshold according to workload and hardware platforms. The experimental results indicate that our technique can significantly decrease the average and peak temperature compared to Linux standard scheduler, and two well-known thermal management techniques: PDTM and TAS.     

A localization algorithm for large scale mobile wireless sensor networks: a learning approach

Localization is a crucial problem in wireless sensor networks and most of the localization algorithms given in the literature are non-adaptive and designed for fixed sensor networks. In this paper, we propose a learning based localization algorithm for mobile wireless sensor networks. By this technique, mobility in the network will be discovered by two crucial methods in the beacons: position and distance checks methods. These two methods help to have accurate localization and constrain communication just when it is necessary. The proposed method localizes the nodes based on connectivity information (hop count), which doesn’t need extra hardware and is cost efficient. The experimental results show that the proposed algorithm is scalable with a small set of beacons in large scale network with a high density of nodes. The given algorithm is fast and free from a pre-deployment requirement. The simulation results show the high performance of the proposed algorithm.