PREDICTION OF NETILMICIN DISPOSITION IN NEONATES

Multiple regression analyses of data from 33 neonates who received netilmicin therapy showed that concurrent treatment with other drugs (Drg), creatinine clearance (CL(cr)), gestational age (GA), and an apgar score of less than 6 at 1 min (Agl') were significant determinants of netilmicin clearance. Apparent volume of distribution was significantly affected by postnatal age (PNA), gender, the presence of ascites and/or oedema (A/O), and whether or not the neonate was small for gestational age (SGA). The following formulae were obtained: CL (ml min-1 kg-1) = -0.108 - 0.210 (Drg) + 0.152(CL(cr)) + 0.019(GA) -0.128(Agl') (multiple R = 0.725, p

SLA Brokering and Bandwidth Reservation Negotiation Schemes for QoS-aware Internet

We present a novel Service Level Agreement (SLA)-driven service provisioning architecture, which enables dynamic and flexible bandwidth reservation schemes on a per-user or per-application basis. Various session level SLA negotiation schemes involving bandwidth allocation, service start time and service duration parameters are introduced and analyzed. The results show that these negotiation schemes can be utilized for the benefit of both end users and network providers in achieving the highest individual SLA optimization in terms of key Quality of Service (QoS) metrics and price. The inherent characteristics of software agents such as autonomy, adaptability and social abilities offer many advantages in this dynamic, complex, and distributed network environment especially when performing Service Level Agreements (SLA) definition negotiations and brokering tasks. This article also presents a service broker prototype based on Fujitsu's Phoenix Open Agent Mediator (OAM) agent technology, which was used to demonstrate a range of SLA brokering scenarios.

Low pressure carbon dioxide solubility in pure electrolyte solvents for lithium-ion batteries as a function of temperature. Measurement and prediction

Experimental values for the carbon dioxide solubility in eight pure electrolyte solvents for lithium ion batteries – such as ethylene carbonate (EC), propylene carbonate (PC), dimethyl carbonate (DMC), ethyl methyl carbonate (EMC), diethyl carbonate (DEC), ?-butyrolactone (?BL), ethyl acetate (EA) and methyl propionate (MP) – are reported as a function of temperature from (283 to 353) K and atmospheric pressure. Based on experimental solubility data, the Henry’s law constant of the carbon dioxide in these solvents was then deduced and compared with reported values from the literature, as well as with those predicted by using COSMO-RS methodology within COSMOthermX software and those calculated by the Peng–Robinson equation of state implemented into Aspen plus. From this work, it appears that the CO2 solubility is higher in linear carbonates (such as DMC, EMC, DEC) than in cyclic ones (EC, PC, ?BL). Furthermore, the highest CO2 solubility was obtained in MP and EA solvents, which are comparable to the solubility values reported in classical ionicliquids. The precision and accuracy of the experimental values, considered as the per cent of the relative average absolute deviations of the Henry’s law constants from appropriate smoothing equations and from literature values, are close to (1% and 15%), respectively. From the variation of the Henry’s law constants with temperature, the partial molar thermodynamic functions of dissolution such as the standard Gibbs free energy, the enthalpy, and the entropy are calculated, as well as the mixing enthalpy of the solvent with CO2 in its hypothetical liquid state.

Serum eosinophilic cationic protein and blood eosinophil counts for the prediction of the presence of airways inflammation in children with wheezing

Background Serum eosinophilic cationic protein (ECP) concentrations may be useful noninvasive markers of airways inflammation in atopic asthma. However, the usefulness of serum ECP measurement for the prediction of airways inflammation in children with a history of wheezing is unknown.

Behavior-Based branch prediction by dynamically clustering branch instructions

Conditional branches frequently exhibit similar behavior (bias, time-varying behavior,...), a property that can be used to improve branch prediction accuracy. Branch clustering constructs groups or clusters of branches with similar behavior and applies different branch prediction techniques to each branch cluster. We revisit the topic of branch clustering with the aim of generalizing branch clustering. We investigate several methods to measure cluster information, with the most effective the storage of information in the branch target buffer. Also, we investigate alternative methods of using the branch cluster identification in the branch predictor. By these improvements we arrive at a branch clustering technique that obtains higher accuracy than previous approaches presented in the literature for the gshare predictor. Furthermore, we evaluate our branch clustering technique in a wide range of predictors to show the general applicability of the method. Branch clustering improves the accuracy of the local history (PAg) predictor, the path-based perceptron and the PPM-like predictor, one of the 2004 CBP finalists.