INSTABILITY OF A NIELSEN-OLESEN VORTEX EMBEDDED IN THE ELECTROWEAK THEORY: II. ELECTROWEAK VORTICES AND GAUGE EQUIVALENCE

Vortex configurations in the electroweak gauge theory are investigated. Two gauge-inequivalent solutions of the field equations, the Z and W vortices, have previously been found. They correspond to embeddings of the abelian Nielsen-Olesen vortex solution into a U(1) subgroup of SU(2)xU(1). It is shown here that any electroweak vortex solution can be mapped into a solution of the same energy with a vanishing upper component of the Higgs field. The correspondence is a gauge equivalence for all vortex solutions except those for which the winding numbers of the upper and lower Higgs components add to zero. This class of solutions, which includes the W vortex, instead corresponds to a singular solution in the one-component gauge. The results, combined with numerical investigations, provide an argument against the existence of other vortex solutions in the gauge-Higgs sector of the Standard Model.Comment: 6 pages, plain latex, no figures, submitted to Mod. Phys. Lett. A as "Electroweak Vortices and Gauge Equivalence"

Small Extended Formulation for Knapsack Cover Inequalities from Monotone Circuits

Initially developed for the min-knapsack problem, the knapsack cover inequalities are used in the current best relaxations for numerous combinatorial optimization problems of covering type. In spite of their widespread use, these inequalities yield linear programming (LP) relaxations of exponential size, over which it is not known how to optimize exactly in polynomial time. In this paper we address this issue and obtain LP relaxations of quasi-polynomial size that are at least as strong as that given by the knapsack cover inequalities. For the min-knapsack cover problem, our main result can be stated formally as follows: for any $\varepsilon >0$, there is a $(1/\varepsilon)^{O(1)}n^{O(\log n)}$-size LP relaxation with an integrality gap of at most $2+\varepsilon$, where $n$ is the number of items. Prior to this work, there was no known relaxation of subexponential size with a constant upper bound on the integrality gap. Our construction is inspired by a connection between extended formulations and monotone circuit complexity via Karchmer-Wigderson games. In particular, our LP is based on $O(\log^2 n)$-depth monotone circuits with fan-in~$2$ for evaluating weighted threshold functions with $n$ inputs, as constructed by Beimel and Weinreb. We believe that a further understanding of this connection may lead to more positive results complementing the numerous lower bounds recently proved for extended formulations.Comment: 21 page

Charge scheduling for electric freight vehicles

We consider a fleet of electric freight vehicles (EFVs) that must deliver goods to a set of customers over the course of multiple days. In an urban environment, EFVs are typically charged at a central depot and rarely use public charging stations during delivery routes. Therefore, the charging schedule at the depot must be planned ahead of time so as to allow the vehicles to complete their routes at minimal cost. Vehicle fleet operators are subject to commercial electricity rate plans, which should be accounted for in order to provide an accurate estimation of the energy-related costs and restrictions. In addition, high vehicle utilization rates can accelerate battery aging, thereby requiring degradation mitigation considerations. We develop and solve a comprehensive mathematical model that incorporates a large variety of features associated with the use of EFVs. These include a realistic charging process, time-dependent energy costs, battery degradation, grid restrictions, and facility-related demand charges. Extensive numerical experiments are conducted in order to draw managerial insights regarding the impact of such features on the charging schedules of EFVs.</p

The electric vehicle routing problem with energy consumption uncertainty

Compared with conventional freight vehicles, electric freight vehicles create less local pollution and are thus generally perceived as a more sustainable means of goods distribution. In urban areas, such vehicles must often perform the entirety of their delivery routes without recharging. However, their energy consumption is subject to a fair amount of uncertainty, which is due to exogenous factors such as the weather and road conditions, endogenous factors such as driver behaviour, and several energy consumption parameters that are difficult to measure precisely. Hence we propose a robust optimization framework to take into account these energy consumption uncertainties in the context of an electric vehicle routing problem. The objective is to determine minimum cost delivery routes capable of providing strong guarantees that a given vehicle will not run out of charge during its route. We formulate the problem as a robust mixed integer linear program and solve small instances to optimality using robust optimization techniques. Furthermore, we develop a two-phase heuristic method based on large neighbourhood search to solve larger instances of the problem, and we conduct several numerical tests to assess the quality of the methodology. The computational experiments illustrate the trade-off between cost and risk, and demonstrate the influence of several parameters on best found solutions. Furthermore, our heuristic identifies 42 new best solutions when tested on instances of the closely related robust capacitated vehicle routing problem.</p

Charge scheduling for electric freight vehicles

We consider a fleet of electric freight vehicles (EFVs) that must deliver goods to a set of customers over the course of multiple days. In an urban environment, EFVs are typically charged at a central depot and rarely use public charging stations during delivery routes. Therefore, the charging schedule at the depot must be planned ahead of time so as to allow the vehicles to complete their routes at minimal cost. Vehicle fleet operators are subject to commercial electricity rate plans, which should be accounted for in order to provide an accurate estimation of the energy-related costs and restrictions. In addition, high vehicle utilization rates can accelerate battery aging, thereby requiring degradation mitigation considerations. We develop and solve a comprehensive mathematical model that incorporates a large variety of features associated with the use of EFVs. These include a realistic charging process, time-dependent energy costs, battery degradation, grid restrictions, and facility-related demand charges. Extensive numerical experiments are conducted in order to draw managerial insights regarding the impact of such features on the charging schedules of EFVs

The electric vehicle routing problem with energy consumption uncertainty

Compared with conventional freight vehicles, electric freight vehicles create less local pollution and are thus generally perceived as a more sustainable means of goods distribution. In urban areas, such vehicles must often perform the entirety of their delivery routes without recharging. However, their energy consumption is subject to a fair amount of uncertainty, which is due to exogenous factors such as the weather and road conditions, endogenous factors such as driver behaviour, and several energy consumption parameters that are difficult to measure precisely. Hence we propose a robust optimization framework to take into account these energy consumption uncertainties in the context of an electric vehicle routing problem. The objective is to determine minimum cost delivery routes capable of providing strong guarantees that a given vehicle will not run out of charge during its route. We formulate the problem as a robust mixed integer linear program and solve small instances to optimality using robust optimization techniques. Furthermore, we develop a two-phase heuristic method based on large neighbourhood search to solve larger instances of the problem, and we conduct several numerical tests to assess the quality of the methodology. The computational experiments illustrate the trade-off between cost and risk, and demonstrate the influence of several parameters on best found solutions. Furthermore, our heuristic identifies 42 new best solutions when tested on instances of the closely related robust capacitated vehicle routing problem

Studies on the Catalytic Properties of Partially Purified Alkaline Proteases from Some Selected Microorganisms

Aims: The research was done to study the conditions enhancing catalytic activities of alkaline proteases from Vibro sp., Lactobacillus brevis, Zymomonas sp., Athrobacter sp., Corynebacterium sp. and Bacillus subtilis.Methodology and Results: The proteolytic enzymes were purified in 2-step procedures involving ammonium sulphate precipitation and sephadex G-150 gel permeation chromatography. The upper and lower limits for the specific activities of proteases from the selected microorganisms were estimated at 20.63 and 47.51 units/mg protein with Zymomonas protease having the highest specific activity towards casein as its substrate and purification fold of 3.46, while that ofLactobacillus brevis protease was 8.06. The native molecular weights of these active proteins ranged from 30.4 to 45.7 kDa with Athrobacter sp. protease having the highest weight for its subunits. The proteolytic enzymes had optimum pH range of 8 to 10 and temperature range of 50 to 62 ºC accounting for the percentage relative activity range of 75 to 94% and 71 to 84 % respectively. The activities of Lactobacillus brevis and Bacillus subtilis proteases were maximum at pH 9 and 10 respectively. Lactobacillus brevis protease activity was maximum at temperature of 62 ºC, while beyond this value, a general thermal instability of these active proteins was observed. At above 70 ºC, the catalytic activities of Corynebacterium sp., Vibrio sp., Zymomonas sp. and Arthrobacter sp. proteases were progressively reduced over a period of 120 min of incubation, while Bacillus subtlis and Lactobacillus brevis proteases were relatively stable. Effect of metal ions was investigated on the catalytic activity of protease from the microorganisms. Lactobacillus brevis,Zymomonas sp., Arthrobacter sp., Corynebacterium sp. and Bacillus subtilis protease activities were strongly activated by metal ions such as Ca+2 and Mg+2. Enzyme activities were inhibited strongly by Cu2+ and Hg2+ but were not inhibited by ethylene diamine tetra acetic acid (EDTA), while a slight inhibition was observed with K+, Na+ and Fe2+.Conclusion, significance and impact of study: The outcome of this present study indicated useful physico-chemical properties of proteolytic enzymes that could be of biotechnological use in enhancing enzyme catalytic efficiency

Applications of the InChI in cheminformatics with the CDK and Bioclipse.

RIGHTS : This article is licensed under the BioMed Central licence at http://www.biomedcentral.com/about/license which is similar to the 'Creative Commons Attribution Licence'. In brief you may : copy, distribute, and display the work; make derivative works; or make commercial use of the work - under the following conditions: the original author must be given credit; for any reuse or distribution, it must be made clear to others what the license terms of this work are.BACKGROUND: The InChI algorithms are written in C++ and not available as Java library. Integration into software written in Java therefore requires a bridge between C and Java libraries, provided by the Java Native Interface (JNI) technology. RESULTS: We here describe how the InChI library is used in the Bioclipse workbench and the Chemistry Development Kit (CDK) cheminformatics library. To make this possible, a JNI bridge to the InChI library was developed, JNI-InChI, allowing Java software to access the InChI algorithms. By using this bridge, the CDK project packages the InChI binaries in a module and offers easy access from Java using the CDK API. The Bioclipse project packages and offers InChI as a dynamic OSGi bundle that can easily be used by any OSGi-compliant software, in addition to the regular Java Archive and Maven bundles. Bioclipse itself uses the InChI as a key component and calculates it on the fly when visualizing and editing chemical structures. We demonstrate the utility of InChI with various applications in CDK and Bioclipse, such as decision support for chemical liability assessment, tautomer generation, and for knowledge aggregation using a linked data approach. CONCLUSIONS: These results show that the InChI library can be used in a variety of Java library dependency solutions, making the functionality easily accessible by Java software, such as in the CDK. The applications show various ways the InChI has been used in Bioclipse, to enrich its functionality