An agent-based control mechanism for WFQ in IP networks

This paper presents a new packet scheduling scheme called agent-based WFQ to control and maintain QoS parameters in virtual private networks (VPNs) within the confines of adaptive networks. Future networks are expected to be open heterogeneous environments consisting of more than one network operator. In this adaptive environment, agents act on behalf of users or third-party operators to obtain the best service for their clients and maintain those services through the modification of the scheduling scheme in routers and switches spanning the VPN. In agent-based WFQ, an agent on the router monitors the accumulated queuing delay for each service. In order to control and to keep the end-to-end delay within the bounds, the weights for services are adjusted dynamically by agents on the routers spanning the VPN. If there is an increase or decrease in queuing delay of a service, an agent on a downstream router informs the upstream routers to adjust the weights of their queues. This keeps the end-to-end delay of services within the specified bounds and offers better QoS compared to VPNs using static WFQ. This paper also describes the algorithm for agent-based WFQ, and presents simulation results. (C) 2003 Elsevier Science Ltd. All rights reserved.

Diagnostic based modeling for determining absolute atomic oxygen densities in atmospheric pressure helium-oxygen plasmas

Absolute atomic oxygen ground state densities in a radio-frequency driven atmospheric pressure plasma jet, operated in a helium-oxygen mixture, are determined using diagnostic based modeling. One-dimensional numerical simulations of the electron dynamics are combined with time integrated optical emission spectroscopy. The population dynamics of the upper O 3p 3P (l=844 nm) atomic oxygen state is governed by direct electron impact excitation, dissociative excitation, radiation losses, and collisional induced quenching. Absolute values for atomic oxygen densities are obtained through comparison with the upper Ar 2p1 (l=750.4 nm) state. Results for spatial profiles and power variations are presented and show excellent quantitative agreement with independent two-photon laser-induced fluorescence measurements.

Diagnostic-based modeling on a micro-scale atmospheric-pressure plasma jet

Diagnostic-based modeling (DBM) actively combines complementary advantages of numerical plasma simulations and relatively simple optical emission spectroscopy (OES). DBM is applied to determine spatial absolute atomic oxygen ground-state density profiles in a micro atmospheric-pressure plasma jet operated in He–O2. A 1D fluid model with semi-kinetic treatment of the electrons yields detailed information on the electron dynamics and the corresponding spatio-temporal electron energy distribution function. Benchmarking this time- and space-resolved simulation with phase-resolved OES (PROES) allows subsequent derivation of effective excitation rates as the basis for DBM. The population dynamics of the upper O(3p3P) oxygen state (? = 844 nm) is governed by direct electron impact excitation, dissociative excitation, radiation losses, and collisional induced quenching. Absolute values for atomic oxygen densities are obtained through tracer comparison with the upper Ar(2p1) state (? = 750.4 nm). The resulting spatial profile for the absolute atomic oxygen density shows an excellent quantitative agreement to a density profile obtained by two-photon absorption laser-induced fluorescence spectroscopy.

P2Y(1) antagonists: Combining receptor-based modeling and QSAR for a quantitative prediction of the biological activity based on consensus scoring

P2Y(1) is an ADP-activated G protein-coupled receptor (GPCR). Its antagonists impede platelet aggregation in vivo and are potential antithrombotic agents. Combining ligand and structure-based modeling we generated a consensus model (LIST-CM) correlating antagonist structures with their potencies. We docked 45 antagonists into our rhodopsin-based human P2Y(1) homology model and calculated docking scores and free binding energies with the Linear Interaction Energy (LIE) method in continuum-solvent. The resulting alignment was also used to build QSAR based on CoMFA, CoMSIA, and molecular descriptors. To benefit from the strength of each technique and compensate for their limitations, we generated our LIST-CM with a PLS regression based on the predictions of each methodology. A test set featuring untested substituents was synthesized and assayed in inhibition of 2-MeSADP-stimulated PLC activity and in radioligand binding. LIST-CM outperformed internal and external predictivity of any individual model to predict accurately the potency of 75% of the test set.