Colloidal interactions in two-dimensional nematics

The interaction between two disks immersed in a 2D nernatic is investigated i) analytically using the tenser order parameter formalism for the nematic configuration around isolated disks and ii) numerically using finite-element methods with adaptive meshing to minimize the corresponding Landau-de Gennes free energy. For strong homeotropic anchoring, each disk generates a pair of defects with one-half topological charge responsible for the 2D quadrupolar interaction between the disks at large distances. At short distance, the position of the defects may change, leading to unexpected complex interactions with the quadrupolar repulsive interactions becoming attractive. This short-range attraction in all directions is still anisotropic. As the distance between the disks decreases, their preferred relative orientation with respect to the far-field nernatic director changes from oblique to perpendicular.

Synthesis and properties of Co-doped titanate nanotubes and their optical sensitization with methylene blue

Agência Financiadora - Fundação para a Ciência e Tecnologia - PTDC/CTM NAN/113021/2009

Feature selection for clustering categorical data with an embedded modelling approach

Research on the problem of feature selection for clustering continues to develop. This is a challenging task, mainly due to the absence of class labels to guide the search for relevant features. Categorical feature selection for clustering has rarely been addressed in the literature, with most of the proposed approaches having focused on numerical data. In this work, we propose an approach to simultaneously cluster categorical data and select a subset of relevant features. Our approach is based on a modification of a finite mixture model (of multinomial distributions), where a set of latent variables indicate the relevance of each feature. To estimate the model parameters, we implement a variant of the expectation-maximization algorithm that simultaneously selects the subset of relevant features, using a minimum message length criterion. The proposed approach compares favourably with two baseline methods: a filter based on an entropy measure and a wrapper based on mutual information. The results obtained on synthetic data illustrate the ability of the proposed expectation-maximization method to recover ground truth. An application to real data, referred to official statistics, shows its usefulness.

Categorical data clustering using a minimum message length criterion

Research on cluster analysis for categorical data continues to develop, new clustering algorithms being proposed. However, in this context, the determination of the number of clusters is rarely addressed. We propose a new approach in which clustering and the estimation of the number of clusters is done simultaneously for categorical data. We assume that the data originate from a finite mixture of multinomial distributions and use a minimum message length criterion (MML) to select the number of clusters (Wallace and Bolton, 1986). For this purpose, we implement an EM-type algorithm (Silvestre et al., 2008) based on the (Figueiredo and Jain, 2002) approach. The novelty of the approach rests on the integration of the model estimation and selection of the number of clusters in a single algorithm, rather than selecting this number based on a set of pre-estimated candidate models. The performance of our approach is compared with the use of Bayesian Information Criterion (BIC) (Schwarz, 1978) and Integrated Completed Likelihood (ICL) (Biernacki et al., 2000) using synthetic data. The obtained results illustrate the capacity of the proposed algorithm to attain the true number of cluster while outperforming BIC and ICL since it is faster, which is especially relevant when dealing with large data sets.

Determining the number of clusters in categorical data

Cluster analysis for categorical data has been an active area of research. A well-known problem in this area is the determination of the number of clusters, which is unknown and must be inferred from the data. In order to estimate the number of clusters, one often resorts to information criteria, such as BIC (Bayesian information criterion), MML (minimum message length, proposed by Wallace and Boulton, 1968), and ICL (integrated classification likelihood). In this work, we adopt the approach developed by Figueiredo and Jain (2002) for clustering continuous data. They use an MML criterion to select the number of clusters and a variant of the EM algorithm to estimate the model parameters. This EM variant seamlessly integrates model estimation and selection in a single algorithm. For clustering categorical data, we assume a finite mixture of multinomial distributions and implement a new EM algorithm, following a previous version (Silvestre et al., 2008). Results obtained with synthetic datasets are encouraging. The main advantage of the proposed approach, when compared to the above referred criteria, is the speed of execution, which is especially relevant when dealing with large data sets.

Clustering and selecting categorical features

In data clustering, the problem of selecting the subset of most relevant features from the data has been an active research topic. Feature selection for clustering is a challenging task due to the absence of class labels for guiding the search for relevant features. Most methods proposed for this goal are focused on numerical data. In this work, we propose an approach for clustering and selecting categorical features simultaneously. We assume that the data originate from a finite mixture of multinomial distributions and implement an integrated expectation-maximization (EM) algorithm that estimates all the parameters of the model and selects the subset of relevant features simultaneously. The results obtained on synthetic data illustrate the performance of the proposed approach. An application to real data, referred to official statistics, shows its usefulness.

Implementação de uma marca de produção e distribuição de citrinos biológicos: Orange made in Algarve

Trabalho de projeto apresentado à Escola Superior de Comunicação Social como parte dos requisitos para obtenção de grau de mestre em Publicidade e Marketing.

Recent advances in vacum sciences and applications

Recent advances in vacuum sciences and applications are reviewed. Novel optical interferometer cavity devices enable pressure measurements with ppm accuracy. The innovative dynamic vacuum standard allows for pressure measurements with temporal resolution of 2 ms. Vacuum issues in the construction of huge ultra-high vacuum devices worldwide are reviewed. Recent advances in surface science and thin films include new phenomena observed in electron transport near solid surfaces as well as novel results on the properties of carbon nanomaterials. Precise techniques for surface and thin-film characterization have been applied in the conservation technology of cultural heritage objects and recent advances in the characterization of biointerfaces are presented. The combination of various vacuum and atmospheric-pressure techniques enables an insight into the complex phenomena of protein and other biomolecule conformations on solid surfaces. Studying these phenomena at solid-liquid interfaces is regarded as the main issue in the development of alternative techniques for drug delivery, tissue engineering and thus the development of innovative techniques for curing cancer and cardiovascular diseases. A review on recent advances in plasma medicine is presented as well as novel hypotheses on cell apoptosis upon treatment with gaseous plasma. Finally, recent advances in plasma nanoscience are illustrated with several examples and a roadmap for future activities is presented.

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.

Influence of the Sodium/Proton replacement on the structural, morphological and photocatalytic properties of titanate nanotubes

Titanate nanotubes (TNT) with different sodium contents have been synthesised using a hydrothermal approach and a swift and highly controllable post-washing processes. The influence of the sodium/proton replacement on the structural and morphological characteristics of the prepared materials was analysed. Different optical behaviour was observed depending on the Na+/H+ samples’ content. A band gap energy of 3.27±0.03 eV was estimated for the material with higher sodium content while a value of 2.81±0.02 eV was inferred for the most protonated material, which therefore exhibits an absorption edge in the near visible region. The point of zero charge of the materials was determined and the influence of the sodium content on the adsorption of both cationic and anionic organic dyes was studied. The photocatalytic performance of the TNT samples was evaluated in the rhodamine 6G degradation process. Best photodegradation results were obtained when using the most protonated material as catalyst, although this material has shown the lowest R6G adsorption capability.

Synthesis of titanate nanostructures using amorphous precursor material and their adsorption/photocatalytic properties

This article reports on a new and swift hydrothermal chemical route to prepare titanate nanostructures (TNS) avoiding the use of crystalline TiO2 as starting material. The synthesis approach uses a commercial solution of TiCl3 as titanium source to prepare an amorphous precursor, circumventing the use of hazardous chemical compounds. The influence of the reaction temperature and dwell autoclave time on the structure and morphology of the synthesised materials was studied. Homogeneous titanate nanotubes with a high length/diameter aspect ratio were synthesised at 160 degrees C and 24 h. A band gap of 3.06 +/- 0.03 eV was determined for the TNS samples prepared in these experimental conditions. This value is red shifted by 0.14 eV compared to the band gap value usually reported for the TiO2 anatase. Moreover, such samples show better adsorption capacity and photocatalytic performance on the dye rhodamine 6G (R6G) photodegradation process than TiO2 nanoparticles. A 98% reduction of the R6G concentration was achieved after 45 min of irradiation of a 10 ppm dye aqueous solution and 1 g L-1 of TNS catalyst.

Melhores dados, melhores vidas: boletim comemorativo do 2º Dia Mundial da Estatística

A 20 de outubro celebra-se o Dia Mundial da Estatística, esta data foi instituída pela Assembleia Geral da ONU e celebrada pela primeira vez em 2010. Com esta iniciativa pretende-se destacar o papel que a Estatística desempenha a nível mundial para o conhecimento e desenvolvimento das nossas sociedades, bem como a importância das instituições nacionais e internacionais que produzem estatísticas oficiais. Este trabalho que apresentamos resulta da reflexão dos alunos do 1º ano do curso de Relações Públicas e Comunicação Empresarial sobre o tema deste ano – Melhores Dados. Melhores Vidas.

Synthesis of titanate nanofibers co-sensitized with ZnS and Bi2S3 nanocrystallites and their application on pollutants removal

The synthesis of nanocomposite materials combining titanate nanofibers (TNF) with nanocrystalline ZnS and Bi2S3 semiconductors is described in this work. The TNF were produced via hydrothermal synthesis and sensitized with the semiconductor nanoparticles, through a single-source precursor decomposition method. ZnS and Bi2S3 nanoparticles were successfully grown onto the TNF's surface and Bi2S3-ZnS/TNF nanocomposite materials with different layouts. The samples' photocatalytic performance was first evaluated through the production of the hydroxyl radical using terephthalic acid as probe molecule. All the tested samples show photocatalytic ability for the production of this oxidizing species. Afterwards, the samples were investigated for the removal of methylene blue. The nanocomposite materials with best adsorption ability were the ZnS/TNF and Bi2S3ZnS/TNF. The dye removal was systematically studied, and the most promising results were obtained considering a sequential combination of an adsorption-photocatalytic degradation process using the Bi2S3ZnS/TNF powder as a highly adsorbent and photocatalyst material. (C) 2015 Elsevier Ltd. All rights reserved.

Trabalho de estatística multivariada

Trabalho realizado pelos alunos do 1º ano, 2º semestre, da licenciatura de RPCE, 2015, no âmbito da unidade curricular de Estatística Multivariada