New remarks on the linear constraint self-dual boson and Wess-Zumino terms

In this work we prove in a precise way that the soldering formalism can be applied to the Srivastava chiral boson (SCB), in contradiction with some results appearing in the literature. We promote a canonical transformation that shows directly that the SCB is composed of two Floreanini-Jackiw particles with the same chirality in which the spectrum is a vacuumlike one. As another conflicting result, we prove that a Wess-Zumino (WZ) term used in the literature consists of a scalar field, once again denying the assertion that the WZ term adds a new degree of freedom to the SCB theory in order to modify the physics of the system. © 2001 The American Physical Society.

Metabolic analysis of poly(3-hydroxybutyrate) production by recombinant Escherichia coli

Poly(3-hydroxybutyrate) (PHB) production by fermentation was examined under both restricted- and ample-oxygen supply conditions in a single fed-batch fermentation. Recombinant Escherichia coli transformed with the PHB production plasmid pSYL107 was grown to reach high cell density (227 g/l dry cell weight) with a high PHB content (78% of dry cell weight), using a glucose-based minimal medium. A simple flux model containing 12 fluxes was developed and applied to the fermentation data. A superior closure (95%) of the carbon mass balance was achieved. When the data were put into use, the results demonstrated a surprisingly large excretion of formate and lactate. Even though periods of severe oxygen limitation coincided with rapid acetate and lactate excretion, PHB productivity and carbon utilization efficiency were not significantly impaired. These results are very positive in reducing oxygen demand in an industrial PHA fermentation without sacrificing its PHA productivity, thereby reducing overall production costs.

Constraints implementation for IQML and mode direction-of-arrival estimators

The iterative quadratic maximum likelihood IQML and the method of direction estimation MODE are well known high resolution direction-of-arrival DOA estimation methods. Their solutions lead to an optimization problem with constraints. The usual linear constraint presents a poor performance for certain DOA values. This work proposes a new linear constraint applicable to both DOA methods and compare their performance with two others: unit norm and usual linear constraint. It is shown that the proposed alternative performs better than others constraints. The resulting computational complexity is also investigated.

Photodynamic Efficiency of Cationic meso-Porphyrins at Lipid Bilayers: Insights from Molecular Dynamics Simulations

Porphyrin derivatives have applications as photoactive drugs in photodynamic therapy. However, little is known about their interactions with phospholipid membranes at the molecular level. We employed molecular dynamics simulations to model the binding between a series of cationic meso-(N-methyl-4-pyridinium)phenylporphyrins and anionic phosphatidylglycerol lipid bilayers. This was done in the presence of molecular oxygen within the membrane. The ability of various porphyrins to cause photodamage was quantified in terms of their immersion depth and degree of exposition to a higher oxygen concentration inside the membrane. Simulations showed that the photodynamic efficiency could be improved as the number of hydrophobic phenyl substituents attached to the porphyrinic ring increased. In the specific case of porphyrins containing two hydrophobic and two charged substituents, the cis isomer was significantly more efficient than the trans. These results correlate well with previous experimental observations. They highlight the importance of both the total charge and amphiphilicity of the photosensitizer for its performance in photodynamic therapy.

Game Theoretic Bidding Strategies for Auctions in Green Electricity Markets

Electricity markets in the United States presently employ an auction mechanism to determine the dispatch of power generation units. In this market design, generators submit bid prices to a regulation agency for review, and the regulator conducts an auction selection in such a way that satisfies electricity demand. Most regulators currently use an auction selection method that minimizes total offer costs ["bid cost minimization" (BCM)] to determine electric dispatch. However, recent literature has shown that this method may not minimize consumer payments, and it has been shown that an alternative selection method that directly minimizes total consumer payments ["payment cost minimization" (PCM)] may benefit social welfare in the long term. The objective of this project is to further investigate the long term benefit of PCM implementation and determine whether it can provide lower costs to consumers. The two auction selection methods are expressed as linear constraint programs and are implemented in an optimization software package. Methodology for game theoretic bidding simulation is developed using EMCAS, a real-time market simulator. Results of a 30-day simulation showed that PCM reduced energy costs for consumers by 12%. However, this result will be cross-checked in the future with two other methods of bid simulation as proposed in this paper.

Aerobic cultivation of Streptococcus zooepidemicus and the role of NADH oxidase

A metabolic flux model was developed for Streptococcus zooepidemicus to compare the metabolism of glucose and maltose during aerobic batch cultivation. Lactic acid was the main product of glucose metabolism whereas acetic acid was the main product of maltose metabolism. This difference was chiefly attributed to the two-fold higher flux through NADH oxidase in maltose-grown cells that enabled the ATP generation rate to remain high despite a slower maltose consumption rate. The two-fold higher flux was matched by a two-fold increase in NADH oxidase activity, 2.53 +/- 0.1 mumol NADH min(-1) mg(-1) protein on maltose versus 1.07 +/- 0.04 Rmol NADH min(-1) mg(-1) protein on glucose, indicating that NADH oxidase activity is regulated by the energy status of the cell. Surprisingly, the energy status of the cell had little impact on hyaluronic acid (HA) yield and molecular weight. (C) 2003 Elsevier Science B.V. All rights reserved.

Constraint release in entangled binary blends of linear polymers: a molecular dynamics study

We present extensive molecular dynamics simulations of the dynamics of diluted long probe chains entangled with a matrix of shorter chains. The chain lengths of both components are above the entanglement strand length, and the ratio of their lengths is varied over a wide range to cover the crossover from the chain reptation regime to tube Rouse motion regime of the long probe chains. Reducing the matrix chain length results in a faster decay of the dynamic structure factor of the probe chains, in good agreement with recent neutron spin echo experiments. The diffusion of the long chains, measured by the mean square displacements of the monomers and the centers of mass of the chains, demonstrates a systematic speed-up relative to the pure reptation behavior expected for monodisperse melts of sufficiently long polymers. On the other hand, the diffusion of the matrix chains is only weakly perturbed by the diluted long probe chains. The simulation results are qualitatively consistent with the theoretical predictions based on constraint release Rouse model, but a detailed comparison reveals the existence of a broad distribution of the disentanglement rates, which is partly confirmed by an analysis of the packing and diffusion of the matrix chains in the tube region of the probe chains. A coarse-grained simulation model based on the tube Rouse motion model with incorporation of the probability distribution of the tube segment jump rates is developed and shows results qualitatively consistent with the fine scale molecular dynamics simulations. However, we observe a breakdown in the tube Rouse model when the short chain length is decreased to around N-S = 80, which is roughly 3.5 times the entanglement spacing N-e(P) = 23. The location of this transition may be sensitive to the chain bending potential used in our simulations.

Augmented Lagrangian methods under the constant positive linear dependence constraint qualification

Two Augmented Lagrangian algorithms for solving KKT systems are introduced. The algorithms differ in the way in which penalty parameters are updated. Possibly infeasible accumulation points are characterized. It is proved that feasible limit points that satisfy the Constant Positive Linear Dependence constraint qualification are KKT solutions. Boundedness of the penalty parameters is proved under suitable assumptions. Numerical experiments are presented.

A relaxed constant positive linear dependence constraint qualification and applications

In this work we introduce a relaxed version of the constant positive linear dependence constraint qualification (CPLD) that we call RCPLD. This development is inspired by a recent generalization of the constant rank constraint qualification by Minchenko and Stakhovski that was called RCRCQ. We show that RCPLD is enough to ensure the convergence of an augmented Lagrangian algorithm and that it asserts the validity of an error bound. We also provide proofs and counter-examples that show the relations of RCRCQ and RCPLD with other known constraint qualifications. In particular, RCPLD is strictly weaker than CPLD and RCRCQ, while still stronger than Abadie's constraint qualification. We also verify that the second order necessary optimality condition holds under RCRCQ.

Constraint qualifications in linear vector semi-infinite optimization

Linear vector semi-infinite optimization deals with the simultaneous minimization of finitely many linear scalar functions subject to infinitely many linear constraints. This paper provides characterizations of the weakly efficient, efficient, properly efficient and strongly efficient points in terms of cones involving the data and Karush–Kuhn–Tucker conditions. The latter characterizations rely on different local and global constraint qualifications. The global constraint qualifications are illustrated on a collection of selected applications.

Robust Solutions of MultiObjective Linear Semi-Infinite Programs under Constraint Data Uncertainty

The multiobjective optimization model studied in this paper deals with simultaneous minimization of finitely many linear functions subject to an arbitrary number of uncertain linear constraints. We first provide a radius of robust feasibility guaranteeing the feasibility of the robust counterpart under affine data parametrization. We then establish dual characterizations of robust solutions of our model that are immunized against data uncertainty by way of characterizing corresponding solutions of robust counterpart of the model. Consequently, we present robust duality theorems relating the value of the robust model with the corresponding value of its dual problem.

Linear amplification with multiple nonlinear devices

Dissertação para obtenção do Grau de Mestre em Engenharia Electrotécnica e Computadores

Probabilistic constraint reasoning

Dissertação apresentada para obtenção do Grau de Doutor em Engenharia Informática, pela Universidade Nova de Lisboa, Faculdade de Ciências e Tecnologia

Bayesian nash equilibrium in ''linear'' cournot models with private information about costs

Calculating explicit closed form solutions of Cournot models where firms have private information about their costs is, in general, very cumbersome. Most authors consider therefore linear demands and constant marginal costs. However, within this framework, the nonnegativity constraint on prices (and quantities) has been ignored or not properly dealt with and the correct calculation of all Bayesian Nash equilibria is more complicated than expected. Moreover, multiple symmetric and interior Bayesianf equilibria may exist for an open set of parameters. The reason for this is that linear demand is not really linear, since there is a kink at zero price: the general ''linear'' inverse demand function is P (Q) = max{a - bQ, 0} rather than P (Q) = a - bQ.

SAT Modulo Linear Arithmetic for Solving Polynomial

Polynomial constraint solving plays a prominent role in several areas of hardware and software analysis and verification, e.g., termination proving, program invariant generation and hybrid system verification, to name a few. In this paper we propose a new method for solving non-linear constraints based on encoding the problem into an SMT problem considering only linear arithmetic. Unlike other existing methods, our method focuses on proving satisfiability of the constraints rather than on proving unsatisfiability, which is more relevant in several applications as we illustrate with several examples. Nevertheless, we also present new techniques based on the analysis of unsatisfiable cores that allow one to efficiently prove unsatisfiability too for a broad class of problems. The power of our approach is demonstrated by means of extensive experiments comparing our prototype with state-of-the-art tools on benchmarks taken both from the academic and the industrial world.