Reentrant Phase Diagram of Network Fluids

We introduce a microscopic model for particles with dissimilar patches which displays an unconventional "pinched'' phase diagram, similar to the one predicted by Tlusty and Safran in the context of dipolar fluids [Science 290, 1328 (2000)]. The model-based on two types of patch interactions, which account, respectively, for chaining and branching of the self-assembled networks-is studied both numerically via Monte Carlo simulations and theoretically via first-order perturbation theory. The dense phase is rich in junctions, while the less-dense phase is rich in chain ends. The model provides a reference system for a deep understanding of the competition between condensation and self-assembly into equilibrium-polymer chains.

Branching points in the low-temperature dipolar hard sphere fluid

In this contribution, we investigate the low-temperature, low-density behaviour of dipolar hard-sphere (DHS) particles, i.e., hard spheres with dipoles embedded in their centre. We aim at describing the DHS fluid in terms of a network of chains and rings (the fundamental clusters) held together by branching points (defects) of different nature. We first introduce a systematic way of classifying inter-cluster connections according to their topology, and then employ this classification to analyse the geometric and thermodynamic properties of each class of defects, as extracted from state-of-the-art equilibrium Monte Carlo simulations. By computing the average density and energetic cost of each defect class, we find that the relevant contribution to inter-cluster interactions is indeed provided by (rare) three-way junctions and by four-way junctions arising from parallel or anti-parallel locally linear aggregates. All other (numerous) defects are either intra-cluster or associated to low cluster-cluster interaction energies, suggesting that these defects do not play a significant part in the thermodynamic description of the self-assembly processes of dipolar hard spheres. (C) 2013 AIP Publishing LLC.

The influence of count's number in myocardium in the determination of reproducible parameters in Gated-SPECT studies simulated with GATE

Myocardial Perfusion Gated Single Photon Emission Tomography (Gated-SPET) imaging is used for the combined evaluation of myocardial perfusion and left ventricular (LV). The purpose of this study is to evaluate the influence of the total number of counts acquired from myocardium, in the calculation of myocardial functional parameters using routine software procedures. Methods: Gated-SPET studies were simulated using Monte Carlo GATE package and NURBS phantom. Simulated data were reconstructed and processed using the commercial software package Quantitative Gated-SPECT. The Bland-Altman and Mann-Whitney-Wilcoxon tests were used to analyze the influence of the number of total counts in the calculation of LV myocardium functional parameters. Results: In studies simulated with 3MBq in the myocardium there were significant differences in the functional parameters: Left ventricular ejection fraction (LVEF), end-systolic volume (ESV), Motility and Thickness; between studies acquired with 15s/projection and 30s/projection. Simulations with 4.2MBq show significant differences in LVEF, end-diastolic volume (EDV) and Thickness. Meanwhile in the simulations with 5.4MBq and 8.4MBq the differences were statistically significant for Motility and Thickness. Conclusion: The total number of counts per simulation doesn't significantly interfere with the determination of Gated-SPET functional parameters using the administered average activity of 450MBq to 5.4MBq in myocardium.

Dosimetric effect of tissue heterogeneity for 125I prostate implants

Aim - To use Monte Carlo (MC) together with voxel phantoms to analyze the tissue heterogeneity effect in the dose distributions and equivalent uniform dose (EUD) for (125)I prostate implants. Background - Dose distribution calculations in low dose-rate brachytherapy are based on the dose deposition around a single source in a water phantom. This formalism does not take into account tissue heterogeneities, interseed attenuation, or finite patient dimensions effects. Tissue composition is especially important due to the photoelectric effect. Materials and Methods - The computed tomographies (CT) of two patients with prostate cancer were used to create voxel phantoms for the MC simulations. An elemental composition and density were assigned to each structure. Densities of the prostate, vesicles, rectum and bladder were determined through the CT electronic densities of 100 patients. The same simulations were performed considering the same phantom as pure water. Results were compared via dose-volume histograms and EUD for the prostate and rectum. Results - The mean absorbed doses presented deviations of 3.3-4.0% for the prostate and of 2.3-4.9% for the rectum, when comparing calculations in water with calculations in the heterogeneous phantom. In the calculations in water, the prostate D 90 was overestimated by 2.8-3.9% and the rectum D 0.1cc resulted in dose differences of 6-8%. The EUD resulted in an overestimation of 3.5-3.7% for the prostate and of 7.7-8.3% for the rectum. Conclusions - The deposited dose was consistently overestimated for the simulation in water. In order to increase the accuracy in the determination of dose distributions, especially around the rectum, the introduction of the model-based algorithms is recommended.

Reabilitação de um imóvel industrial em Marvila: projeto de investimento

Trabalho de Projeto para obtenção do grau de Mestre em Engenharia Civil

Automatic learning for the classification of chemical reactions and in statistical thermodynamics

This Thesis describes the application of automatic learning methods for a) the classification of organic and metabolic reactions, and b) the mapping of Potential Energy Surfaces(PES). The classification of reactions was approached with two distinct methodologies: a representation of chemical reactions based on NMR data, and a representation of chemical reactions from the reaction equation based on the physico-chemical and topological features of chemical bonds. NMR-based classification of photochemical and enzymatic reactions. Photochemical and metabolic reactions were classified by Kohonen Self-Organizing Maps (Kohonen SOMs) and Random Forests (RFs) taking as input the difference between the 1H NMR spectra of the products and the reactants. The development of such a representation can be applied in automatic analysis of changes in the 1H NMR spectrum of a mixture and their interpretation in terms of the chemical reactions taking place. Examples of possible applications are the monitoring of reaction processes, evaluation of the stability of chemicals, or even the interpretation of metabonomic data. A Kohonen SOM trained with a data set of metabolic reactions catalysed by transferases was able to correctly classify 75% of an independent test set in terms of the EC number subclass. Random Forests improved the correct predictions to 79%. With photochemical reactions classified into 7 groups, an independent test set was classified with 86-93% accuracy. The data set of photochemical reactions was also used to simulate mixtures with two reactions occurring simultaneously. Kohonen SOMs and Feed-Forward Neural Networks (FFNNs) were trained to classify the reactions occurring in a mixture based on the 1H NMR spectra of the products and reactants. Kohonen SOMs allowed the correct assignment of 53-63% of the mixtures (in a test set). Counter-Propagation Neural Networks (CPNNs) gave origin to similar results. The use of supervised learning techniques allowed an improvement in the results. They were improved to 77% of correct assignments when an ensemble of ten FFNNs were used and to 80% when Random Forests were used. This study was performed with NMR data simulated from the molecular structure by the SPINUS program. In the design of one test set, simulated data was combined with experimental data. The results support the proposal of linking databases of chemical reactions to experimental or simulated NMR data for automatic classification of reactions and mixtures of reactions. Genome-scale classification of enzymatic reactions from their reaction equation. The MOLMAP descriptor relies on a Kohonen SOM that defines types of bonds on the basis of their physico-chemical and topological properties. The MOLMAP descriptor of a molecule represents the types of bonds available in that molecule. The MOLMAP descriptor of a reaction is defined as the difference between the MOLMAPs of the products and the reactants, and numerically encodes the pattern of bonds that are broken, changed, and made during a chemical reaction. The automatic perception of chemical similarities between metabolic reactions is required for a variety of applications ranging from the computer validation of classification systems, genome-scale reconstruction (or comparison) of metabolic pathways, to the classification of enzymatic mechanisms. Catalytic functions of proteins are generally described by the EC numbers that are simultaneously employed as identifiers of reactions, enzymes, and enzyme genes, thus linking metabolic and genomic information. Different methods should be available to automatically compare metabolic reactions and for the automatic assignment of EC numbers to reactions still not officially classified. In this study, the genome-scale data set of enzymatic reactions available in the KEGG database was encoded by the MOLMAP descriptors, and was submitted to Kohonen SOMs to compare the resulting map with the official EC number classification, to explore the possibility of predicting EC numbers from the reaction equation, and to assess the internal consistency of the EC classification at the class level. A general agreement with the EC classification was observed, i.e. a relationship between the similarity of MOLMAPs and the similarity of EC numbers. At the same time, MOLMAPs were able to discriminate between EC sub-subclasses. EC numbers could be assigned at the class, subclass, and sub-subclass levels with accuracies up to 92%, 80%, and 70% for independent test sets. The correspondence between chemical similarity of metabolic reactions and their MOLMAP descriptors was applied to the identification of a number of reactions mapped into the same neuron but belonging to different EC classes, which demonstrated the ability of the MOLMAP/SOM approach to verify the internal consistency of classifications in databases of metabolic reactions. RFs were also used to assign the four levels of the EC hierarchy from the reaction equation. EC numbers were correctly assigned in 95%, 90%, 85% and 86% of the cases (for independent test sets) at the class, subclass, sub-subclass and full EC number level,respectively. Experiments for the classification of reactions from the main reactants and products were performed with RFs - EC numbers were assigned at the class, subclass and sub-subclass level with accuracies of 78%, 74% and 63%, respectively. In the course of the experiments with metabolic reactions we suggested that the MOLMAP / SOM concept could be extended to the representation of other levels of metabolic information such as metabolic pathways. Following the MOLMAP idea, the pattern of neurons activated by the reactions of a metabolic pathway is a representation of the reactions involved in that pathway - a descriptor of the metabolic pathway. This reasoning enabled the comparison of different pathways, the automatic classification of pathways, and a classification of organisms based on their biochemical machinery. The three levels of classification (from bonds to metabolic pathways) allowed to map and perceive chemical similarities between metabolic pathways even for pathways of different types of metabolism and pathways that do not share similarities in terms of EC numbers. Mapping of PES by neural networks (NNs). In a first series of experiments, ensembles of Feed-Forward NNs (EnsFFNNs) and Associative Neural Networks (ASNNs) were trained to reproduce PES represented by the Lennard-Jones (LJ) analytical potential function. The accuracy of the method was assessed by comparing the results of molecular dynamics simulations (thermal, structural, and dynamic properties) obtained from the NNs-PES and from the LJ function. The results indicated that for LJ-type potentials, NNs can be trained to generate accurate PES to be used in molecular simulations. EnsFFNNs and ASNNs gave better results than single FFNNs. A remarkable ability of the NNs models to interpolate between distant curves and accurately reproduce potentials to be used in molecular simulations is shown. The purpose of the first study was to systematically analyse the accuracy of different NNs. Our main motivation, however, is reflected in the next study: the mapping of multidimensional PES by NNs to simulate, by Molecular Dynamics or Monte Carlo, the adsorption and self-assembly of solvated organic molecules on noble-metal electrodes. Indeed, for such complex and heterogeneous systems the development of suitable analytical functions that fit quantum mechanical interaction energies is a non-trivial or even impossible task. The data consisted of energy values, from Density Functional Theory (DFT) calculations, at different distances, for several molecular orientations and three electrode adsorption sites. The results indicate that NNs require a data set large enough to cover well the diversity of possible interaction sites, distances, and orientations. NNs trained with such data sets can perform equally well or even better than analytical functions. Therefore, they can be used in molecular simulations, particularly for the ethanol/Au (111) interface which is the case studied in the present Thesis. Once properly trained, the networks are able to produce, as output, any required number of energy points for accurate interpolations.

The influence of number of counts in the myocardium in the determination of reproducible functional parameters in gated-SPECT studies simulated with GATE

Myocardial perfusion gated-single photon emission computed tomography (gated-SPECT) imaging is used for the combined evaluation of myocardial perfusion and left ventricular (LV) function. The aim of this study is to analyze the influence of counts/pixel and concomitantly the total counts in the myocardium for the calculation of myocardial functional parameters. Material and methods: Gated-SPECT studies were performed using a Monte Carlo GATE simulation package and the NCAT phantom. The simulations of these studies use the radiopharmaceutical 99mTc-labeled tracers (250, 350, 450 and 680MBq) for standard patient types, effectively corresponding to the following activities of myocardium: 3, 4.2, 5.4-8.2MBq. All studies were simulated using 15 and 30s/projection. The simulated data were reconstructed and processed by quantitative-gated-SPECT software, and the analysis of functional parameters in gated-SPECT images was done by using Bland-Altman test and Mann-Whitney-Wilcoxon test. Results: In studies simulated using different times (15 and 30s/projection), it was noted that for the activities for full body: 250 and 350MBq, there were statistically significant differences in parameters Motility and Thickness. For the left ventricular ejection fraction (LVEF), end-systolic volume (ESV) it was only for 250MBq, and 350MBq in the end-diastolic volume (EDV), while the simulated studies with 450 and 680MBq showed no statistically significant differences for global functional parameters: LVEF, EDV and ESV. Conclusion: The number of counts/pixel and, concomitantly, the total counts per simulation do not significantly interfere with the determination of gated-SPECT functional parameters, when using the administered average activity of 450MBq, corresponding to the 5.4MBq of the myocardium, for standard patient types.

Three-dimensial patchy lattice model: Ring formation and phase separation

We investigate the structural and thermodynamic properties of a model of particles with 2 patches of type A and 10 patches of type B. Particles are placed on the sites of a face centered cubic lattice with the patches oriented along the nearest neighbor directions. The competition between the self- assembly of chains, rings, and networks on the phase diagram is investigated by carrying out a systematic investigation of this class of models, using an extension ofWertheim's theory for associating fluids and Monte Carlo numerical simulations. We varied the ratio r epsilon(AB)/epsilon(AA) of the interaction between patches A and B, epsilon(AB), and between A patches, epsilon(AA) (epsilon(BB) is set to theta) as well as the relative position of the A patches, i.e., the angle. between the (lattice) directions of the A patches. We found that both r and theta (60 degrees, 90 degrees, or 120 degrees) have a profound effect on the phase diagram. In the empty fluid regime (r < 1/2) the phase diagram is reentrant with a closed miscibility loop. The region around the lower critical point exhibits unusual structural and thermodynamic behavior determined by the presence of relatively short rings. The agreement between the results of theory and simulation is excellent for theta = 120 degrees but deteriorates as. decreases, revealing the need for new theoretical approaches to describe the structure and thermodynamics of systems dominated by small rings. (C) 2014 AIP Publishing LLC.

Optimisation of paediatrics computed radiography for full spine curvature measurements using a phantom: a pilot study

Aim: Optimise a set of exposure factors, with the lowest effective dose, to delineate spinal curvature with the modified Cobb method in a full spine using computed radiography (CR) for a 5-year-old paediatric anthropomorphic phantom. Methods: Images were acquired by varying a set of parameters: positions (antero-posterior (AP), posteroanterior (PA) and lateral), kilo-voltage peak (kVp) (66-90), source-to-image distance (SID) (150 to 200cm), broad focus and the use of a grid (grid in/out) to analyse the impact on E and image quality (IQ). IQ was analysed applying two approaches: objective [contrast-to-noise-ratio/(CNR] and perceptual, using 5 observers. Monte-Carlo modelling was used for dose estimation. Cohen’s Kappa coefficient was used to calculate inter-observer-variability. The angle was measured using Cobb’s method on lateral projections under different imaging conditions. Results: PA promoted the lowest effective dose (0.013 mSv) compared to AP (0.048 mSv) and lateral (0.025 mSv). The exposure parameters that allowed lower dose were 200cm SID, 90 kVp, broad focus and grid out for paediatrics using an Agfa CR system. Thirty-seven images were assessed for IQ and thirty-two were classified adequate. Cobb angle measurements varied between 16°±2.9 and 19.9°±0.9. Conclusion: Cobb angle measurements can be performed using the lowest dose with a low contrast-tonoise ratio. The variation on measurements for this was ±2.9° and this is within the range of acceptable clinical error without impact on clinical diagnosis. Further work is recommended on improvement to the sample size and a more robust perceptual IQ assessment protocol for observers.

Temperature-induced structural transitions in self-assembling magnetic nanocolloids

With the help of a unique combination of density functional theory and computer simulations, we discover two possible scenarios, depending on concentration, for the hierarchical self-assembly of magnetic nanoparticles on cooling. We show that typically considered low temperature clusters, i.e. defect-free chains and rings, merge into more complex branched structures through only three types of defects: four-way X junctions, three-way Y junctions and two-way Z junctions. Our accurate calculations reveal the predominance of weakly magnetically responsive rings cross-linked by X defects at the lowest temperatures. We thus provide a strategy to fine-tune magnetic and thermodynamic responses of magnetic nanocolloids to be used in medical and microfluidics applications.

Study of forbidden transitions in atomic systems

A Thesis submitted for the co-tutelle degree of Doctor in Physics at Universidade Nova de Lisboa and Université Pierre et Marie Curie

Modelação da degradação de pontes considerando a incerteza associada às inspecções

Dissertação para obtenção do Grau de Mestre em Engenharia Civil - Perfil Estruturas

In situ measured cross section geometry of old timber structures and its influence on structural safety

Old timber structures may show significant variation in the cross section geometry along the same element, as a result of both construction methods and deterioration. As consequence, the definition of the geometric parameters in situ may be both time consuming and costly. This work presents the results of inspections carried out in different timber structures. Based on the obtained results, different simplified geometric models are proposed in order to efficiently model the geometry variations found. Probabilistic modelling techniques are also used to define safety parameters of existing timber structures, when subjected to dead and live loads, namely self-weight and wind actions. The parameters of the models have been defined as probabilistic variables, and safety of a selected case study was assessed using the Monte Carlo simulation technique. Assuming a target reliability index, a model was defined for both the residual cross section and the time dependent deterioration evolution. As a consequence, it was possible to compute probabilities of failure and reliability indices, as well as, time evolution deterioration curves for this structure. The results obtained provide a proposal for definition of the cross section geometric parameters of existing timber structures with different levels of decay, using a simplified probabilistic geometry model and considering a remaining capacity factor for the decayed areas. This model can be used for assessing the safety of the structure at present and for predicting future performance.

Reliability analysis of a timber truss system subjected to decay

Assessing the safety of existing timber structures is of paramount importance for taking reliable decisions on repair actions and their extent. The results obtained through semi-probabilistic methods are unrealistic, as the partial safety factors present in codes are calibrated considering the uncertainty present in new structures. In order to overcome these limitations, and also to include the effects of decay in the safety analysis, probabilistic methods, based on Monte-Carlo simulation are applied here to assess the safety of existing timber structures. In particular, the impact of decay on structural safety is analyzed and discussed, using a simple structural model, similar to that used for current semi-probabilistic analysis.

Pharmacokinetic/pharmacodynamic target attainment of intravenous β-lactam regimens against Gram-negative bacteria isolated in a Brazilian teaching hospital

ABSTRACTINTRODUCTION: Monte Carlo simulations have been used for selecting optimal antibiotic regimens for treatment of bacterial infections. The aim of this study was to assess the pharmacokinetic and pharmacodynamic target attainment of intravenous β-lactam regimens commonly used to treat bloodstream infections (BSIs) caused by Gram-negative rod-shaped organisms in a Brazilian teaching hospital.METHODS: In total, 5,000 patients were included in the Monte Carlo simulations of distinct antimicrobial regimens to estimate the likelihood of achieving free drug concentrations above the minimum inhibitory concentration (MIC; fT > MIC) for the requisite periods to clear distinct target organisms. Microbiological data were obtained from blood culture isolates harvested in our hospital from 2008 to 2010.RESULTS: In total, 614 bacterial isolates, including Escherichia coli, Enterobacterspp., Klebsiella pneumoniae, Acinetobacter baumannii, and Pseudomonas aeruginosa, were analyzed Piperacillin/tazobactam failed to achieve a cumulative fraction of response (CFR) > 90% for any of the isolates. While standard dosing (short infusion) of β-lactams achieved target attainment for BSIs caused by E. coliand Enterobacterspp., pharmacodynamic target attainment against K. pneumoniaeisolates was only achieved with ceftazidime and meropenem (prolonged infusion). Lastly, only prolonged infusion of high-dose meropenem approached an ideal CFR against P. aeruginosa; however, no antimicrobial regimen achieved an ideal CFR against A. baumannii.CONCLUSIONS:These data reinforce the use of prolonged infusions of high-dose β-lactam antimicrobials as a reasonable strategy for the treatment of BSIs caused by multidrug resistant Gram-negative bacteria in Brazil.