A fast cross-entropy method for estimating buffer overflows in queuing networks

In this paper, we propose a fast adaptive importance sampling method for the efficient simulation of buffer overflow probabilities in queueing networks. The method comprises three stages. First, we estimate the minimum cross-entropy tilting parameter for a small buffer level; next, we use this as a starting value for the estimation of the optimal tilting parameter for the actual (large) buffer level. Finally, the tilting parameter just found is used to estimate the overflow probability of interest. We study various properties of the method in more detail for the M/M/1 queue and conjecture that similar properties also hold for quite general queueing networks. Numerical results support this conjecture and demonstrate the high efficiency of the proposed algorithm.

An improved novel method for solving nonlinear boundary value problems

A modified formula for the integral transform of a nonlinear function is proposed for a class of nonlinear boundary value problems. The technique presented in this paper results in analytical solutions. Iterations and initial guess, which are needed in other techniques, are not required in this novel technique. The analytical solutions are found to agree surprisingly well with the numerically exact solutions for two examples of power law reaction and Langmuir-Hinshelwood reaction in a catalyst pellet.

Non-Equilibrium Reaction Rates in the Macroscopic Chemistry Method for DSMC Calculations

The Direct Simulation Monte Carlo (DSMC) method is used to simulate the flow of rarefied gases. In the Macroscopic Chemistry Method (MCM) for DSMC, chemical reaction rates calculated from local macroscopic flow properties are enforced in each cell. Unlike the standard total collision energy (TCE) chemistry model for DSMC, the new method is not restricted to an Arrhenius form of the reaction rate coefficient, nor is it restricted to a collision cross-section which yields a simple power-law viscosity. For reaction rates of interest in aerospace applications, chemically reacting collisions are generally infrequent events and, as such, local equilibrium conditions are established before a significant number of chemical reactions occur. Hence, the reaction rates which have been used in MCM have been calculated from the reaction rate data which are expected to be correct only for conditions of thermal equilibrium. Here we consider artificially high reaction rates so that the fraction of reacting collisions is not small and propose a simple method of estimating the rates of chemical reactions which can be used in the Macroscopic Chemistry Method in both equilibrium and non-equilibrium conditions. Two tests are presented: (1) The dissociation rates under conditions of thermal non-equilibrium are determined from a zero-dimensional Monte-Carlo sampling procedure which simulates ‘intra-modal’ non-equilibrium; that is, equilibrium distributions in each of the translational, rotational and vibrational modes but with different temperatures for each mode; (2) The 2-D hypersonic flow of molecular oxygen over a vertical plate at Mach 30 is calculated. In both cases the new method produces results in close agreement with those given by the standard TCE model in the same highly nonequilibrium conditions. We conclude that the general method of estimating the non-equilibrium reaction rate is a simple means by which information contained within non-equilibrium distribution functions predicted by the DSMC method can be included in the Macroscopic Chemistry Method.

A hybrid planning method for transmission networks in a deregulated environment

The reconstruction of power industries has brought fundamental changes to both power system operation and planning. This paper presents a new planning method using multi-objective optimization (MOOP) technique, as well as human knowledge, to expand the transmission network in open access schemes. The method starts with a candidate pool of feasible expansion plans. Consequent selection of the best candidates is carried out through a MOOP approach, of which multiple objectives are tackled simultaneously, aiming at integrating the market operation and planning as one unified process in context of deregulated system. Human knowledge has been applied in both stages to ensure the selection with practical engineering and management concerns. The expansion plan from MOOP is assessed by reliability criteria before it is finalized. The proposed method has been tested with the IEEE 14-bus system and relevant analyses and discussions have been presented.

Using the level set method to model endogenous lava dome growth

Modeling volcanic phenomena is complicated by free-surfaces often supporting large rheological gradients. Analytical solutions and analogue models provide explanations for fundamental characteristics of lava flows. But more sophisticated models are needed, incorporating improved physics and rheology to capture realistic events. To advance our understanding of the flow dynamics of highly viscous lava in Peléean lava dome formation, axi-symmetrical Finite Element Method (FEM) models of generic endogenous dome growth have been developed. We use a novel technique, the level-set method, which tracks a moving interface, leaving the mesh unaltered. The model equations are formulated in an Eulerian framework. In this paper we test the quality of this technique in our numerical scheme by considering existing analytical and experimental models of lava dome growth which assume a constant Newtonian viscosity. We then compare our model against analytical solutions for real lava domes extruded on Soufrière, St. Vincent, W.I. in 1979 and Mount St. Helens, USA in October 1980 using an effective viscosity. The level-set method is found to be computationally light and robust enough to model the free-surface of a growing lava dome. Also, by modeling the extruded lava with a constant pressure head this naturally results in a drop in extrusion rate with increasing dome height, which can explain lava dome growth observables more appropriately than when using a fixed extrusion rate. From the modeling point of view, the level-set method will ultimately provide an opportunity to capture more of the physics while benefiting from the numerical robustness of regular grids.

A PCR-based method of screening individuals of all ages, from neonates to the elderly, for familial hyperaldosteronism type I

Aim: Unless specifically treated (glucocorticoids in low doses), Familial Hyperaldosteronism Type I(FH-I) may result in early death from stroke. We report the successful application of a rapid, polymerase chain reaction (PCR)-based method of detecting the 'hybrid' 11 beta-hydroxylase (11 beta-OHase)/aldosterone synthase (AS) gene as a screening test for FH-I. Methods: 'Long-PCR' was used to amplify, concurrently, a 4 kb fragment of AS gene (both primers AS-specific) and a 4 kb fragment of the hybrid gene (5' primer 11 beta-OHase-specific, 3'primer AS-specific) from DNA extracted from blood either collected locally or transported from elsewhere. Sample collection and transport were straightforward. This 4 kb fragment contains all the currently recognised hybrid gene 'crossover' points. Results: Within a single family, long-PCR identified all 21 individuals known to have FH-I. Hypertension was corrected in all 11 treated with glucocorticoids. Nine with normal blood pressure are being closely followed for development of hypertension. Long-PCR cord blood analysis excluded FH-I in three neonates born to affected individuals. Long-PCR newly identified two other affected families: (1) a female (60 years) with a personal and family history of stroke and her normotensive daughter (40 years), and (2) a female (51 years) previously treated for primary aldosteronism with amiloride, her two hypertensive sons (14 and 16 years) and her hypertensive mother (78 years). No false negative or false positive results have yet been encountered. At least seven other centres have successfully performed this test. Conclusion: Long-PCR is a reliable method of screening individuals of all ages for FH-I.

Electrical impedance particle size method (Coulter Counter) detects the large fat globules in poorly homogenised UHT processed milk

The large fat globules that can be present in UHT milk due to inadequate homogenisation cause a cream layer to form that limits the shelf life of UHT milk. Four different particle size measurement techniques were used to measure the size of fat globules in poorly homogenised UHT milk processed in a UHT pilot plant. The thickness of the cream layer that formed during storage was negatively correlated with homogenisation pressure. It was positively correlated with the mass mean diameter and the percentage volume of particles between 1.5 and 2 mu m diameter, as determined by laser light scattering using the Malvern Mastersizer. Also, the thickness of the cream layer was positively correlated with the volume mode diameter and the percentage volume of particles between 1.5 and 2 mu m diameter, as determined by electrical impedance using the Coulter Counter. The cream layer thickness did not correlate significantly with the Coulter Counter measurements of volume mean diameter, or volume percentages of particles between 2 and 5 mu m or 5 and 10 mu m diameter. Spectroturbidimetry (Emulsion Quality Analyser) and light microscopy analyses were found to be unsuitable for assessing the size of the fat particles. This study suggests that the fat globule size distribution as determined by the electrical impedance method (Coulter Counter) is the most useful for determining the efficiency of homogenisation and therefore for predicting the stability of the fat emulsion in UHT milk during storage.

Speciation of arsenic metabolites in the urine of occupational workers and experimental rats using an optimised hydride cold-trapping method

A hydride cold-trapping technique was developed and optimised for the measurement of urinary arsenic metabolites. The analytical precision of the method was found to be 6.1, 4.0 and 4.8% (n = 5) for inorganic arsenic (As-i), monomethylarsonate (MMA) and dimethylarsinate (DMA), respectively, with recoveries close to 100%, The detection limits were 1.0, 1.3 and 3 ng for As-i, MMA and DMA, respectively. The method was then used to analyse urine samples obtained from three groups of workers for occupational exposure in three companies where copper chrome arsenate was used for timber treatment. The results were compared with those for a normal control group of laboratory workers. Arsenic and its metabolites were also measured in experimental rats given 5 mg As kg(-1) body mass by oral gavage in the form of sodium arsenite, calcium arsenite or sodium arsenate. Occupational workers showed a significantly higher excretion of As-i, Up to two fold increases of urinary As-i excretion in rats compared with control rats were also observed in animals dosed with various forms of arsenicals. The method is suitable for the measurement of arsenic metabolites in urine of both humans and experimental animals.

A novel method for selection of chymotrypsin inhibitors from a phage peptide library

A novel screening strategy has been developed for the identification of alpha-chymotrypsin inhibitors from a phage peptide library. In this strategy, the standard affinity selection protocol was modified by adding a proteolytic cleavage period to avoid recovery of alpha-chymotrypsin substrates. After four cycles of selection and further activity assay, a group of related peptides were identified by DNA sequencing. These peptides share a consensus sequence motif as (S/T)RVPR(R/H). Then, a corresponding short peptide (Ac-ASRVPRRG-NH2) was synthesized chemically and proved to be an inhibitor of alpha-chymotrypsin. The present work provides a useful way for searching proteinase inhibitors without detailed knowledge of the molecular structure.

Prediction of MHC class II-binding peptides using an evolutionary algorithm and artificial neural network

Motivation: Prediction methods for identifying binding peptides could minimize the number of peptides required to be synthesized and assayed, and thereby facilitate the identification of potential T-cell epitopes. We developed a bioinformatic method for the prediction of peptide binding to MHC class II molecules. Results: Experimental binding data and expert knowledge of anchor positions and binding motifs were combined with an evolutionary algorithm (EA) and an artificial neural network (ANN): binding data extraction --> peptide alignment --> ANN training and classification. This method, termed PERUN, was implemented for the prediction of peptides that bind to HLA-DR4(B1*0401). The respective positive predictive values of PERUN predictions of high-, moderate-, low- and zero-affinity binder-a were assessed as 0.8, 0.7, 0.5 and 0.8 by cross-validation, and 1.0, 0.8, 0.3 and 0.7 by experimental binding. This illustrates the synergy between experimentation and computer modeling, and its application to the identification of potential immunotheraaeutic peptides.

Rapid isolation of high-quality RNA from symbiotic dinoflagellates

This report details a reliable and efficient RNA extraction protocol for the symbiotic dinoflagellate Symbiodinium microadriaticum Freudenthal (Gymnodiniales, Dinophyceae). The method typically gives yields of 500 mu g total RNA from 0.4 g wet weight of algae, and, in comparison to current protocols, it is technically simple and less time consuming. This method isolates high-quality, intact RNA from in vine cultured as well as host-isolated cells, as demonstrated by spectrophotometry, gel electrophoresis, and northern analysis. The total RNA obtained was suitable for reverse transcription and PCR amplification of Symbiodinium cDNAs. We have successfully applied our method to isolate total RNA from a different dinoflagellate, Amphidinium carterae Hulburt (Gymnodiniales, Dinophyceae), found in symbiotic association with marine invertebrates.

Chemical treatment of Escherichia coli: 3. Selective extraction of a recombinant protein from cytoplasmic inclusion bodies in intact cells

In previous parts of this study we developed procedures for the high-efficiency chemical extraction of soluble and insoluble protein from intact Escherichia coli cells. Although high yields were obtained, extraction of recombinant protein directly from cytoplasmic inclusion bodies led to low product purity due to coextraction of soluble contaminants. In this work, a two-stage procedure for the selective extraction of recombinant protein at high efficiency and high purity is reported. In the first stage, inclusion-body stability is promoted by the addition of 15 mM 2-hydroxyethyldisulfide (2-HEDS), also known as oxidized P-mercaptoethanol, to the permeabil ization buffer (6 M urea + 3 mM ethylenediaminetetra-acetate [EDTA]). 2-HEDS is an oxidizing agent believed to promote disulfide bond formation, rendering the inclusion body resistant to solubilization in 6 M urea. Contaminating proteins are separated from the inclusion-body fraction by centrifugation. in the second stage, disulfide bonds are readily eliminated by including reducing agent (20 mM dithiothreitol [DTT]) into the permeabilization buffer. Extraction using this selective two-stage process yielded an 81% (w/w) recovery of the recombinant protein Long-R-3-IGF-I from inclusion bodies located in the cytoplasm of intact E. coli, at a purity of 46% (w/w). This was comparable to that achieved by conventional extraction (mechanical disruption followed by centrifugation and solubilization). A pilot-scale procedure was also demonstrated using a stirred reactor and diafiltration. This is the first reported study that achieves both high extraction efficiency and selectivity by the chemical treatment of cytoplasmic inclusion bodies in intact bacterial cells. (C) 1999 John Wiley & Sons, Inc.

A novel method for tailoring the pore-opening size of MCM-41 materials

A novel pore tailoring method is proposed by which the pore-opening sizes of MCM-41 materials can be finely tuned without significant loss in pore volume and surface area.