Avaliação da dose absorvida na tiróide, em cintigrafias com 123I e Na99mTcO4 utilizando modelos biocinéticos e métodos de Monte Carlo

Mestrado em Radiações Aplicadas às Tecnologias da Saúde. Área de especialização: Protecção contra Radiações

Estimating the Impact on Efficiency of the Adoption of a Voluntary Environmental Standard: An Empirical Study of the Global Copper Mining Industry

This paper uses data on the world's copper mining industry to measure the impact on efficiency of the adoption of the ISO 14001 environmental standard. Anecdotal and case study literature suggests that firms are motivated to adopt this standard so as to achieve greater efficiency through changes in operating procedures and processes. Using plant level panel data from 1992-2007 on most of the world's industrial copper mines, the study uses stochastic frontier methods to investigate the effects of ISO adoption. The variety of models used in this study find that adoption either tends to improve efficiency or has no impact on efficiency, but no evidence is found that ISO adoption decreases efficiency.

Traffic forecasts under uncertainty and capacity constraints

Traffic forecasts provide essential input for the appraisal of transport investment projects. However, according to recent empirical evidence, long-term predictions are subject to high levels of uncertainty. This paper quantifies uncertainty in traffic forecasts for the tolled motorway network in Spain. Uncertainty is quantified in the form of a confidence interval for the traffic forecast that includes both model uncertainty and input uncertainty. We apply a stochastic simulation process based on bootstrapping techniques. Furthermore, the paper proposes a new methodology to account for capacity constraints in long-term traffic forecasts. Specifically, we suggest a dynamic model in which the speed of adjustment is related to the ratio between the actual traffic flow and the maximum capacity of the motorway. This methodology is applied to a specific public policy that consists of suppressing the toll on a certain motorway section before the concession expires.

Use of high-resolution geophysical data to characterize heterogeneous aquifers: influence of data integration method on hydrological predictions

The integration of geophysical data into the subsurface characterization problem has been shown in many cases to significantly improve hydrological knowledge by providing information at spatial scales and locations that is unattainable using conventional hydrological measurement techniques. The investigation of exactly how much benefit can be brought by geophysical data in terms of its effect on hydrological predictions, however, has received considerably less attention in the literature. Here, we examine the potential hydrological benefits brought by a recently introduced simulated annealing (SA) conditional stochastic simulation method designed for the assimilation of diverse hydrogeophysical data sets. We consider the specific case of integrating crosshole ground-penetrating radar (GPR) and borehole porosity log data to characterize the porosity distribution in saturated heterogeneous aquifers. In many cases, porosity is linked to hydraulic conductivity and thus to flow and transport behavior. To perform our evaluation, we first generate a number of synthetic porosity fields exhibiting varying degrees of spatial continuity and structural complexity. Next, we simulate the collection of crosshole GPR data between several boreholes in these fields, and the collection of porosity log data at the borehole locations. The inverted GPR data, together with the porosity logs, are then used to reconstruct the porosity field using the SA-based method, along with a number of other more elementary approaches. Assuming that the grid-cell-scale relationship between porosity and hydraulic conductivity is unique and known, the porosity realizations are then used in groundwater flow and contaminant transport simulations to assess the benefits and limitations of the different approaches.

Population pharmacokinetic study of gentamicin: A retrospective analysis in a large cohort of neonate patients

Objectives: Gentamicin is one of the most commonly prescribed antibiotics for suspected or proven infection in newborns. Because of age-associated (pre- and post- natal) changes in body composition and organ function, large interindividual variability in gentamicin drug levels exists, thus requiring a close monitoring of this drug due to its narrow therapeutic index. We aimed to investigate clinical and demographic factors influencing gentamicin pharmacokinetics (PK) in a large cohort of unselected newborns and to explore optimal regimen based on simulation. Methods: All gentamicin concentration data from newborns treated at the University Hospital Center of Lausanne between December 2006 and October 2011 were retrieved. Gentamicin concentrations were measured within the frame of a routine therapeutic drug monitoring program, in which 2 concentrations (at 1h and 12h) are systematically collected after the first administered dose, and a few additional concentrations are sampled along the treatment course. A population PK analysis was performed by comparing various structural models, and the effect of clinical and demographic factors on gentamicin disposition was explored using NONMEM®. Results: A total of 3039 concentrations collected in 994 preterm (median gestational age 32.3 weeks, range 24.2-36.5 weeks) and 455 term newborns were used in the analysis. Most of the data (86%) were sampled after the first dose (C1 h and C12 h). A two-compartment model best characterized gentamicin PK. Average clearance (CL) was 0.044 L/h/kg (CV 25%), central volume of distribution (Vc) 0.442 L/kg (CV 18%), intercompartmental clearance (Q) 0.040 L/h/kg and peripheral volume of distribution (Vp) 0.122 L/kg. Body weight, gestational age and postnatal age positively influenced CL. The use of both gestational age and postnatal age better predicted CL than postmenstrual age alone. CL was affected by dopamine and furosemide administration and non-significantly by indometacin. Body weight, gestational age and dopamine coadminstration significantly influenced Vc. Model based simulation confirms that preterm infants need higher dose, superior to 4 mg/kg, and extended interval dosage regimen to achieve adequate concentration. Conclusions: This study, performed on a very large cohort of neonates, identified important factors influencing gentamicin PK. The model will serve to elaborate a Bayesian tool for dosage individualization based on a single measurement.

An ATM distributed simulator for network management research

Due to the high cost of a large ATM network working up to full strength to apply our ideas about network management, i.e., dynamic virtual path (VP) management and fault restoration, we developed a distributed simulation platform for performing our experiments. This platform also had to be capable of other sorts of tests, such as connection admission control (CAC) algorithms, routing algorithms, and accounting and charging methods. The platform was posed as a very simple, event-oriented and scalable simulation. The main goal was the simulation of a working ATM backbone network with a potentially large number of nodes (hundreds). As research into control algorithms and low-level, or rather cell-level methods, was beyond the scope of this study, the simulation took place at a connection level, i.e., there was no real traffic of cells. The simulated network behaved like a real network accepting and rejecting SNMP ones, or experimental tools using the API node

Inference of distributional parameters from compositional samples containing nondetects

Low concentrations of elements in geochemical analyses have the peculiarity of beingcompositional data and, for a given level of significance, are likely to be beyond thecapabilities of laboratories to distinguish between minute concentrations and completeabsence, thus preventing laboratories from reporting extremely low concentrations of theanalyte. Instead, what is reported is the detection limit, which is the minimumconcentration that conclusively differentiates between presence and absence of theelement. A spatially distributed exhaustive sample is employed in this study to generateunbiased sub-samples, which are further censored to observe the effect that differentdetection limits and sample sizes have on the inference of population distributionsstarting from geochemical analyses having specimens below detection limit (nondetects).The isometric logratio transformation is used to convert the compositional data in thesimplex to samples in real space, thus allowing the practitioner to properly borrow fromthe large source of statistical techniques valid only in real space. The bootstrap method isused to numerically investigate the reliability of inferring several distributionalparameters employing different forms of imputation for the censored data. The casestudy illustrates that, in general, best results are obtained when imputations are madeusing the distribution best fitting the readings above detection limit and exposes theproblems of other more widely used practices. When the sample is spatially correlated, itis necessary to combine the bootstrap with stochastic simulation

Anàlisi paramètrica de l'assaig a compressió d'un panell de material compost rigiditzat amb tres nervis

L’objectiu d’aquest treball és desenvolupar una metodologia per realitzar l’anàlisiparamètrica de l’assaig de compressió d’un panell de material compost rigiditzat ambtres nervis. En primer lloc és necessari desenvolupar un sistema automatitzat per generar i avaluar el conjunt de parametritzacions. A continuació, s’estudiaran quines variables d’estat són les més adequades per representar el vinclament local, la flexió global, la càrrega crítica de desestabilització i l’índex de fallada en l’anàlisi paramètrica. La modelització amb el mètode dels elements finits serveix per simular l’assaig a compressió del panell. La simulació es realitza mitjançant un càlcul no lineal, per estudiar la desestabilització i els fenòmens no lineals que pateix el panell. L’estudi es complementa amb una anàlisi modal i una anàlisi lineal

Estudi de l’eficiència aerodinàmica de vehicles pesants de transport de passatgers

Estudi de l’eficiència aerodinàmica de les carrosseries de vehicles pesants de cara a reduir el consum de combustible en autocars de llarg trajecte. L’estudi es basa en tres aspectes: validació del programa de simulació, estudi aerodinàmic de diferents carrosseries d’autocar de mercat i estudi aerodinàmic de diferents complements

Infohabitants: laboratori per la simulació d’ infohabitants com agents recomanadors (SIRA)

L’ objectiu del projecte és la implementació d’un simulador de sistema de recomanació que permeti estudiar algoritmes de dissociació entre agent-recomanador i usuari, combinant-los amb diverses tècniques de recomanació i fent servir infohabitants com Agents Recomanadors i veure com treballen en un sistema recomanador

Solving Large Location-Allocation problems by Clustering and Simulated Annealing

Globalization involves several facility location problems that need to be handled at large scale. Location Allocation (LA) is a combinatorial problem in which the distance among points in the data space matter. Precisely, taking advantage of the distance property of the domain we exploit the capability of clustering techniques to partition the data space in order to convert an initial large LA problem into several simpler LA problems. Particularly, our motivation problem involves a huge geographical area that can be partitioned under overall conditions. We present different types of clustering techniques and then we perform a cluster analysis over our dataset in order to partition it. After that, we solve the LA problem applying simulated annealing algorithm to the clustered and non-clustered data in order to work out how profitable is the clustering and which of the presented methods is the most suitable

Simulació d'un magatzem automàtic amb Citect Scada

Creació d’una simulació amb Scada d’un magatzem automàtic. Aquest funcionarà amb un autòmat Omron CQ1M, i en el nostre cas l’autòmat serà qui controlarà tot el procés

The contribution of patch topology and demographic parameters to PVA predictions: the case of the European tree frog

Population viability analyses (PVA) are increasingly used in metapopulation conservation plans. Two major types of models are commonly used to assess vulnerability and to rank management options: population-based stochastic simulation models (PSM such as RAMAS or VORTEX) and stochastic patch occupancy models (SPOM). While the first set of models relies on explicit intrapatch dynamics and interpatch dispersal to predict population levels in space and time, the latter is based on spatially explicit metapopulation theory where the probability of patch occupation is predicted given the patch area and isolation (patch topology). We applied both approaches to a European tree frog (Hyla arborea) metapopulation in western Switzerland in order to evaluate the concordances of both models and their applications to conservation. Although some quantitative discrepancies appeared in terms of network occupancy and equilibrium population size, the two approaches were largely concordant regarding the ranking of patch values and sensitivities to parameters, which is encouraging given the differences in the underlying paradigms and input data.

Are agent-based simulations robust? The wholesale electricity trading case

Agent-based computational economics is becoming widely used in practice. This paperexplores the consistency of some of its standard techniques. We focus in particular on prevailingwholesale electricity trading simulation methods. We include different supply and demandrepresentations and propose the Experience-Weighted Attractions method to include severalbehavioural algorithms. We compare the results across assumptions and to economic theorypredictions. The match is good under best-response and reinforcement learning but not underfictitious play. The simulations perform well under flat and upward-slopping supply bidding,and also for plausible demand elasticity assumptions. Learning is influenced by the number ofbids per plant and the initial conditions. The overall conclusion is that agent-based simulationassumptions are far from innocuous. We link their performance to underlying features, andidentify those that are better suited to model wholesale electricity markets.