Potential of a New Technique for Remote Sensing of Hydrocarbon Accumulations and Blind Uranium Deposits: Buried Lif Thermoluminescence Dosimeters

Buried thermoluminescence dosimeters may be useful in remote sensing of petroleum and natural gas accumulations and blind uranium deposits. They act as integrating detectors that smooth out the effects of environmental variations that affect other measuring systems and result in irregularities and poor repeatability in measurements made during gas and radiometric surveys

Do Naked Singularities Form?

A naked singularity is formed by the collapse of a Sine-Gordon soliton in 1+1 dimensional dilaton gravity with a negative cosmological constant. We examine the quantum stress tensor resulting from the formation of the singularity. Consistent boundary conditions require that the incoming soliton is accompanied by a flux of incoming radiation across past null infinity, but neglecting the back reaction of the spacetime leads to the absurd conclusion that the total energy entering the system by the time the observer is able to receive information from the singularity is infinite. We conclude that the back reaction must prevent the formation of the naked singularity.Comment: 7 pages (21 Kb), PHYZZX. Revised version to appear in Class. & Quant. Grav. Letts. A discussion of the consistency of the Sine-Gordon model is include

The Eastward Enlargement of the Eurozone: Trade and FDI

Trade and FDI, Economic Integration

An application of semi-infinite programming to air pollution control

Environment issues are more then ever important in a modern society. Complying with stricter legal thresholds on pollution emissions raises an important economic issue. This talk presents some ideas in the use of optimization tools to help in the planning and control of non mobile pollution sources. We assume a Gaussian plume model where a plume rise and weather stabilities classes are considered. Three main semi-infinite programming formulations are described and numerical results are shown

Optimização e controlo da poluição atmosférica

Alguns problemas de controlo da poluição atmosférica podem ser formulados como problemas de programação semi-infinita (PSI). Estas formulações, das quais descrevemos três abordagens, permitem que as instalações fabris cumpram a legislação da poluição atmosférica enquanto que o impacto económico é minimizado. As mesmas ferramentas da programação matemática podem também ser usadas pelas autoridades competentes no sentido de verificar que os limites impostos por lei são cumpridos, através do planeamento da localização dos postos de amostragem/controlo. A primeira das formulações consiste em optimizar um determinado objectivo enquanto que o nível de poluição atmosférica é mantido abaixo de um valor de referência. A segunda consiste no cálculo da poluição atmosférica máxima atingida numa determinada região e a terceira considera um problemas de redução da poluição. Estas formulações permitem obter os melhores parâmetros de controlo e as posições onde os valores máximos da poluição são atingidos, posições essas que correspondem ao melhor posicionamento dos postos de amostragem/controlo. As abordagens propostas são ilustradas com quatro problemas académicos. As ferramentas actualmente existentes apoiam a PSI desde a modelação do problema até à sua resolução. A linguagem de modelação (SIP)AMPL foi usada para codificar os problemas propostos e o solver NSIPS foi empregue na resolução dos mesmos

Semi-infinite air pollution control problems

Semi-infinite programming (SIP) problems arise in many engineering areas. Robot trajectory planning and optimal signal sets are two fine examples. Air pollution abatement problems, which are linear SIP problems, were proposed in the seventies by Gustafson and Kortanek [Analytical properties of some multiple-source urban diffusion models, Environment and Planning 4, pp. 31- 41, 1972]. Recent available tools for non-linear SIP allow the formulation of more general air control problems, namely the optimum stack design. In the air control SIP problem an objective function is to be optimised (minimum stack height or minimum cleaning costs), where the air pollution, at ground level, is kept bellow a given threshold. A Gaussian model is used to provide estimates of air pollution in a region where mean weather conditions are assumed. In this talk, we present three formulated air pollution control problems coded in the (SIP)AMPL modelling language and numerical results obtained with the discretization method of the NSIPS solver

Optimal control of fed-batch processes with particle swarm optimization

Optimal control problems appear in several engineering fields. These problems are often described by sets of nonlinear differential and algebraic equations, usually subject to constraints in the state and control variables. Some bioprocess optimal control problems are revisited and a numerical approach to its solution is introduced. The numerical procedure used to solve the problems takes advantage of the well know modeling AMPL language, providing an external dynamic library that solve the nonlinear differential equations. The optimal control problem as generally presented belongs to the class of semi-infinite programming (SIP) problems. A transformation of the SIP problem results in a nonlinear optimization problem (NLP) that can be address by off-the-shelf optimization software. The NLP formulation results in nondifferentiable optimization problems were the global solution is mostly desirable. We apply a particle swarm optimization strategy implemented in the MLOCPSOA [13] solver. Particle swarm optimization (PSO) is a stochastic technique that mimics the social behavior of a swarm