Self-assembly in chains, rings, and branches: a single component system with two critical points

Agências financiadoras: FCT - PEstOE/FIS/UI0618/2011; PTDC/FIS/098254/2008 ERC-PATCHYCOLLOIDS e MIUR-PRIN

Estimação de sub-registro de nascidos vivos pelo método de captura e recaptura, Sergipe

OBJETIVO: Estimar o número de ocorrências de nascidos vivos e, por conseqüência, o sub-registro civil de nascidos vivos. MÉTODOS: As bases de dados do Sistema Nacional de Informação sobre Nascidos Vivos e do Registro Civil do Instituto Brasileiro de Geografia e Estatística, nos segundo e terceiro trimestres de 2006 do estado de Sergipe, foram pareadas por relacionamento determinístico a partir do número da Declaração de Nascido Vivo. A desagregação geográfica adotada foi a de microrregião de residência da mãe. Os modelos de Huggins para populações fechadas foram aplicados para estimar as probabilidades de captura em cada base e o total de nascidos vivos ocorrido no período, dentro de cada desagregação geográfica. O aplicativo utilizado para as estimações foi o Software MARK®. RESULTADOS: O sub-registro civil no período analisado foi de 19,3%. A aplicação do método de captura-recaptura para estimar sub-registro de nascidos vivos é factível, inclusive para desagregações geográficas menores do que unidade da federação. O relacionamento determinístico foi prejudicado em quatro microrregiões, devido à falta de preenchimento do número da Declaração de Nascido Vivo na base do Instituto Brasileiro de Geografia e Estatística. Identificou-se que a idade da mãe afeta a probabilidade de captura pelo Registro Civil, característica de heterogeneidade na população de nascidos vivos. CONCLUSÕES: O método de captura-recaptura mostrou-se viável para a estimação de sub-registro de nascidos vivos.

Into a new phase of the research on restructuring of work in the knowledge society: the Third WORKS General Assembly in Sofia (Bulgaria)

The WORKS Project started two years ago (2005), involving the efforts of research institutes of 13 European countries with the main purpose of improving the understanding of the major changes in work in the knowledge-based society, taking account both of global forces and the regional diversity within Europe. This research meeting in Sofia (Bulgaria) aimed to present synthetically the massive amount of data collected in the case studies (occupational and organisational) and with the quantitative research during last year.

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.

Synthesis of Sub-5 NM Co-Doped SnO2 nanoparticles and their structural microstructural, optical and photocatalytic properties

A swift chemical route to synthesize Co-doped SnO2 nanopowders is described. Pure and highly stable Sn1-xCoxO2-delta (0 <= x <= 0.15) crystalline nanoparticles were synthesized, with mean grain sizes <5 nm and the dopant element homogeneously distributed in the SnO2 matrix. The UV-visible diffuse reflectance spectra of the Sn1-xCoxO2-delta samples reveal red shifts, the optical bandgap energies decreasing with increasing Co concentration. The samples' Urbach energies were calculated and correlated with their bandgap energies. The photocatalytic activity of the Sn1-xCoxO2-delta samples was investigated for the 4-hydroxylbenzoic acid (4-HBA) degradation process. A complete photodegradation of a 10 ppm 4-HBA solution was achieved using 0.02% (w/w) of Sn0.95Co0.05O2-delta nanoparticles in 60 min of irradiation. (C) 2014 Elsevier B.V. All rights reserved.

Quantitative description of the self-assembly of patchy particles into chains and rings

We numerically study a simple fluid composed of particles having a hard-core repulsion complemented by two patchy attractive sites on the particle poles. An appropriate choice of the patch angular width allows for the formation of ring structures which, at low temperatures and low densities, compete with the growth of linear aggregates. The simplicity of the model makes it possible to compare simulation results and theoretical predictions based on the Wertheim perturbation theory, specialized to the case in which ring formation is allowed. Such a comparison offers a unique framework for establishing the quality of the analytic predictions. We find that the Wertheim theory describes remarkably well the simulation results.

Sub-micron structuring of silicon using femtosecond laser interferometry

We report the fabrication of planar sub-micron gratings in silicon with a period of 720 nm using a modified Michelson interferometer and femtosecond laser radiation. The gratings consist of alternated stripes of laser ablated and unmodified material. Ablated stripes are bordered by parallel ridges which protrude above the unmodified material. In the regions where ridges are formed, the laser radiation intensity is not sufficient to cause ablation. Nevertheless, melting and a significant temperature increase are expected, and ridges may be formed due to expansion of silicon during resolidification or silicon oxidation. These conclusions are consistent with the evolution of the stripes morphology as a function of the distance from the center of the grating.

Mathematical modeling and simulation of heat flow through pultrusion die assembly system for thermoset composites

Pultrusion is an industrial process used to produce glass fibers reinforced polymers profiles. These materials are worldwide used when performing characteristics, such as great electrical and magnetic insulation, high strength to weight ratio, corrosion and weather resistance, long service life and minimal maintenance are required. In this study, we present the results of the modelling and simulation of heat flow through a pultrusion die by means of Finite Element Analysis (FEA). The numerical simulation was calibrated based on temperature profiles computed from thermographic measurements carried out during pultrusion manufacturing process. Obtained results have shown a maximum deviation of 7%, which is considered to be acceptable for this type of analysis, and is below to the 10% value, previously specified as maximum deviation. © 2011, Advanced Engineering Solutions.

Functional domains of Bacillus subtilis transcription factor AraR and identification of aminoacids important for nucleoprotein complex assembly and effector-binding.

Journal of Bacteriology (Apr 2006) 3024-3036

Sub-notificação de reacções adversas medicamentosas : um problema com solução? : contribuição para o conhecimento da sub-notificação de RAMs em Portugal e implementação de medidas minimizadoras do impacte

RESUMO - Introdução: As Reacções Adversas Medicamentosas (RAMs) constituem um grave problema de Saúde Pública em termos da mortalidade e morbilidade provocadas, tendo também um impacto económico considerável nos Sistemas de Saúde. Os Sistemas de Notificacão Espontânea de RAMs são considerados como o método de vigilância de medicamentos mais eficaz, sendo a sub-notificação de RAMs uma das suas maiores limitações. Em termos globais, foi estimado que apenas 6% de todas as reacções adversas são notificadas. Portugal apresenta uma taxa de notificação de RAMs relativamente baixa quando comparada com os países mais notificadores da Europa. São objectivos deste estudo: 1) caracterizar as atitudes e os comportamentos dos médicos, dos farmacêuticos e dos enfermeiros em Portugal Continental relativamente à notificação de RAMs; e 2) caracterizar a efectividade de intervenções educacionais destinadas a reduzir a sub-notificação de RAMs. Métodos: Numa primeira fase será efectuado um estudo de caso-controlo em médicos, farmacêuticos e enfermeiros de Portugal Continental, a exercer actividade no Servico Nacional de Saúde (SNS), de modo a caracterizar as suas atitudes e comportamentos relativamente à notificação de RAMs. Como casos serão considerados os Profissionais de Saúde que notificaram pelo menos uma RAM num determinado período e os controlos os Profissionais de Saúde que não notificaram qualquer RAM nesse mesmo período, sendo estes útimos seleccionados aleatoriamente. O estudo será conduzido através de um questionário de auto-resposta, em que as questões relativas às atitudes e comportamentos são baseadas nos “sete pecados mortais” de Inman. Será utilizada uma Escala Visual Analógica para registar as respostas, podendo estas ir de zero (totalmente em desacordo) até 10 (totalmente de acordo). Será utilizada uma análise de regressão logística para determinar o odds ratio ajustado (ORadj) da notificação de RAMs para uma mudança de exposição correspondente ao range interquartil para cada atitude. Numa segunda fase, será efectuado ensaio aleatorizado controlado de cluster, para caracterizar a efectividade das intervenções educacionais realizadas sobre as causas identificadas na primeira parte do trabalho, com o intuito de reduzir a sub-notificação de RAMs. Com base em informacão de 2007 foram identificados 43 clusters dispersos pelas várias Regiões de Saúde. As intervenções educacionais são compostas por uma apresentação com uma hora de duração complementada por um folheto recordatório. Serão ainda realizados dois sub-estudos, em que o V1.0, Final 28Set09 viii Sub-notificação de RAMs em Portugal – Um problema com solução ? primeiro tentará caracterizar o efeito de contaminação entre Profissionais de Saúde e o segundo pretende caracterizar a duração do efeito das intervenções educacionais. Resultados a atingir: Pretende-se, com a implementação deste projecto, aumentar o número de notificações de RAMs pelos médicos, farmacêuticos e enfermeiros em cerca de 110%, de modo a atingir-se uma taxa de notificação de aproximadamente 300 notificações por milhão de habitantes por ano (i.e., multiplicar por 2,1 o número notificações existentes). -------------------ABSTRACT - Introduction: The Adverse Drug Reactions (ADRs) are a serious Public Health problem in terms of mortality and morbidity caused, being also an economic burden for the health systems. The Spontaneous Adverse Event Reporting Systems are considered as the most effective drug surveillance methods, in which the ADR under-reporting represents one of its biggest limitations. It was estimated that only 6% of all adverse reactions are notified globally. When comparing with high ADR reporting rate countries Portugal shows a low ADR reporting rate. This study aims to: 1) characterize the physicians, pharmacists and nurses attitudes and behaviours related to ADR under-reporting; 2) characterize the educational interventions effectiveness to decrease the ADRs under-reporting. Methods: During a first phase a case-control study will be conducted in physicians, pharmacists and nurses in Continental Portugal working in the National Health System (NHS) in order to characterize their attitudes and behaviours related to ADR reporting. The Healthcare Professionals that have reported at least one ADR during a determined period will be considered as the cases and those that have not reported any ADR during the same period will be considered as the controls. The controls will be randomly selected. The study will be conducted through a self-administered questionnaire in which the questions related to the attitudes and behaviours are based in the Inmans’s “seven mortal sins”. A Visual Analogue Scale will be used to record the responses. The responses can range from 0 (totally disagree) to 10 (totally agree). Logistic regression will be used to determine the ADR reporting adjusted odds ratio (ORadj) for a change in the exposure corresponding to the interquartile range for each attitude. In the second phase of the study a cluster-randomized controlled trial will be conducted to characterize the educational interventions effectiveness focused on the first phase identified causes with the aim to decrease the ADRs under-reporting. Based in 2007’s information 43 clusters have been identified throughout the several Health Regions. The educational interventions are composed of one hour presentation complemented by an informational leaflet. Two sub-studies will be also conducted in which the first one will try to characterize the contamination effect between the Healthcare Professionals and the second to characterize the educational interventions effect duration. V1.0, Final 28Set09 x Sub-notificação de RAMs em Portugal – Um problema com solução ? Outcome: With the project implementation an increase of the ADR notifications performed by the physicians, pharmacists and nurses by 110% is aimed in order to obtain approximately 300 notifications per million habitants per year (i.e., multiply by 2,1 the existent notifications).

Saccharomyces cerevisiae Mutants Affected in Vacuole Assembly or Vacuolar H+-ATPase are Hypersensitive to Lead (Pb) Toxicity

Lead is an important environmental pollutant. The role of vacuole, in Pb detoxification, was studied using a vacuolar protein sorting mutant strain (vps16D), belonging to class C mutants. Cells disrupted in VPS16 gene, did not display a detectable vacuolar-like structure. Based on the loss of cell proliferation capacity, it was found that cells from vps16D mutant exhibited a hypersensitivity to Pb-induced toxicity, compared to wild type (WT) strain. The function of vacuolar H?-ATPase (VATPase), in Pb detoxification, was evaluated using mutants with structurally normal vacuoles but defective in subunits of catalytic (vma1D or vma2D) or membrane domain (vph1D or vma3D) of V-ATPase. All mutants tested, lacking a functional V-ATPase, displayed an increased susceptibility to Pb, comparatively to cells from WT strain. Modification of vacuolar morphology, in Pb-exposed cells, was visualized using a Vma2p-GFP strain. The treatment of yeast cells with Pb originated the fusion of the medium size vacuolar lobes into one enlarged vacuole. In conclusion, it was found that vacuole plays an important role in the detoxification of Pb in Saccharomyces cerevisiae; in addition, a functional V-ATPase was required for Pb compartmentalization.

Generalization of Wertheim's theory for the assembly of various types of rings

We generalize Wertheim's first order perturbation theory to account for the effect in the thermodynamics of the self-assembly of rings characterized by two energy scales. The theory is applied to a lattice model of patchy particles and tested against Monte Carlo simulations on a fcc lattice. These particles have 2 patches of type A and 10 patches of type B, which may form bonds AA or AB that decrease the energy by epsilon(AA) and by epsilon(AB) = r epsilon(AA), respectively. The angle theta between the 2 A-patches on each particle is fixed at 601, 90 degrees or 120 degrees. For values of r below 1/2 and above a threshold r(th)(theta) the models exhibit a phase diagram with two critical points. Both theory and simulation predict that rth increases when theta decreases. We show that the mechanism that prevents phase separation for models with decreasing values of theta is related to the formation of loops containing AB bonds. Moreover, we show that by including the free energy of B-rings ( loops containing one AB bond), the theory describes the trends observed in the simulation results, but that for the lowest values of theta, the theoretical description deteriorates due to the increasing number of loops containing more than one AB bond.

Evolução da ocupação e da perda de solo numa pequena sub-bacia da Bacia Hidrográfica do Rio Sado

Dissertação apresentada na Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa para a obtenção do grau de Mestre em Engenharia do Ambiente,Perfil Gestão de Sistemas Ambientais

Natural and amyloid self-assembly of S100 proteins: structural basis of functional diversity

The S100 proteins are 10-12 kDa EF-hand proteins that act as central regulators in a multitude of cellular processes including cell survival, proliferation, differentiation and motility. Consequently, many S100 proteins are implicated and display marked changes in their expression levels in many types of cancer, neurodegenerative disorders, inflammatory and autoimmune diseases. The structure and function of S100 proteins are modulated by metal ions via Ca2+ binding through EF-hand motifs and binding of Zn2+ and Cu2+ at additional sites, usually at the homodimer interfaces. Ca2+ binding modulates S100 conformational opening and thus promotes and affects the interaction with p53, the receptor for advanced glycation endproducts and Toll-like receptor 4, among many others. Structural plasticity also occurs at the quaternary level, where several S100 proteins self-assemble into multiple oligomeric states, many being functionally relevant. Recently, we have found that the S100A8/A9 proteins are involved in amyloidogenic processes in corpora amylacea of prostate cancer patients, and undergo metal-mediated amyloid oligomerization and fibrillation in vitro. Here we review the unique chemical and structural properties of S100 proteins that underlie the conformational changes resulting in their oligomerization upon metal ion binding and ultimately in functional control. The possibility that S100 proteins have intrinsic amyloid-forming capacity is also addressed, as well as the hypothesis that amyloid self-assemblies may, under particular physiological conditions, affect the S100 functions within the cellular milieu.

Voltage Magnitude Analysis Considering Load Curtailment Minimization in Sub-Transmission Networks with Distributed Generators

Most of distribution generation and smart grid research works are dedicated to the study of network operation parameters, reliability among others. However, many of this research works usually uses traditional test systems such as IEEE test systems. This work proposes a voltage magnitude study in presence of fault conditions considering the realistic specifications found in countries like Brazil. The methodology considers a hybrid method of fuzzy set and Monte Carlo simulation based on the fuzzyprobabilistic models and a remedial action algorithm which is based on optimal power flow. To illustrate the application of the proposed method, the paper includes a case study that considers a real 12 bus sub-transmission network.