Development of a novel continuous statistical modelling technique for detecting the adulteration of extra virgin olive oil with hazelnut oil by using spectroscopic data

The adulteration of extra virgin olive oil with other vegetable oils is a certain problem with economic and health consequences. Current official methods have been proved insufficient to detect such adulterations. One of the most concerning and undetectable adulterations with other vegetable oils is the addition of hazelnut oil. The main objective of this work was to develop a novel dimensionality reduction technique able to model oil mixtures as a part of an integrated pattern recognition solution. This final solution attempts to identify hazelnut oil adulterants in extra virgin olive oil at low percentages based on spectroscopic chemical fingerprints. The proposed Continuous Locality Preserving Projections (CLPP) technique allows the modelling of the continuous nature of the produced in house admixtures as data series instead of discrete points. This methodology has potential to be extended to other mixtures and adulterations of food products. The maintenance of the continuous structure of the data manifold lets the better visualization of this examined classification problem and facilitates a more accurate utilisation of the manifold for detecting the adulterants.

Robust visual tracking using structurally random projection and weighted least squares

Sparse representation based visual tracking approaches have attracted increasing interests in the community in recent years. The main idea is to linearly represent each target candidate using a set of target and trivial templates while imposing a sparsity constraint onto the representation coefficients. After we obtain the coefficients using L1-norm minimization methods, the candidate with the lowest error, when it is reconstructed using only the target templates and the associated coefficients, is considered as the tracking result. In spite of promising system performance widely reported, it is unclear if the performance of these trackers can be maximised. In addition, computational complexity caused by the dimensionality of the feature space limits these algorithms in real-time applications. In this paper, we propose a real-time visual tracking method based on structurally random projection and weighted least squares techniques. In particular, to enhance the discriminative capability of the tracker, we introduce background templates to the linear representation framework. To handle appearance variations over time, we relax the sparsity constraint using a weighed least squares (WLS) method to obtain the representation coefficients. To further reduce the computational complexity, structurally random projection is used to reduce the dimensionality of the feature space while preserving the pairwise distances between the data points in the feature space. Experimental results show that the proposed approach outperforms several state-of-the-art tracking methods.

Probing the Unfolded Configurations of a β-Hairpin Using Sketch-Map

This work examines the conformational ensemble involved in β-hairpin folding by means of advanced molecular dynamics simulations and dimensionality reduction. A fully atomistic description of the protein and the surrounding solvent molecules is used, and this complex energy landscape is sampled by means of parallel tempering metadynamics simulations. The ensemble of configurations explored is analyzed using the recently proposed sketch-map algorithm. Further simulations allow us to probe how mutations affect the structures adopted by this protein. We find that many of the configurations adopted by a mutant are the same as those adopted by the wild-type protein. Furthermore, certain mutations destabilize secondary-structure-containing configurations by preventing the formation of hydrogen bonds or by promoting the formation of new intramolecular contacts. Our analysis demonstrates that machine-learning techniques can be used to study the energy landscapes of complex molecules and that the visualizations that are generated in this way provide a natural basis for examining how the stabilities of particular configurations of the molecule are affected by factors such as temperature or structural mutations.

Discovering subgroups of patients from DNA copy number data using NMF on compacted matrices

In the study of complex genetic diseases, the identification of subgroups of patients sharing similar genetic characteristics represents a challenging task, for example, to improve treatment decision. One type of genetic lesion, frequently investigated in such disorders, is the change of the DNA copy number (CN) at specific genomic traits. Non-negative Matrix Factorization (NMF) is a standard technique to reduce the dimensionality of a data set and to cluster data samples, while keeping its most relevant information in meaningful components. Thus, it can be used to discover subgroups of patients from CN profiles. It is however computationally impractical for very high dimensional data, such as CN microarray data. Deciding the most suitable number of subgroups is also a challenging problem. The aim of this work is to derive a procedure to compact high dimensional data, in order to improve NMF applicability without compromising the quality of the clustering. This is particularly important for analyzing high-resolution microarray data. Many commonly used quality measures, as well as our own measures, are employed to decide the number of subgroups and to assess the quality of the results. Our measures are based on the idea of identifying robust subgroups, inspired by biologically/clinically relevance instead of simply aiming at well-separated clusters. We evaluate our procedure using four real independent data sets. In these data sets, our method was able to find accurate subgroups with individual molecular and clinical features and outperformed the standard NMF in terms of accuracy in the factorization fitness function. Hence, it can be useful for the discovery of subgroups of patients with similar CN profiles in the study of heterogeneous diseases.

Differential evolution combined with clonal selection for dynamic economic dispatch

Dynamic economic load dispatch (DELD) is one of the most important steps in power system operation. Various optimisation algorithms for solving the problem have been developed; however, due to the non-convex characteristics and large dimensionality of the problem, it is necessary to explore new methods to further improve the dispatch results and minimise the costs. This article proposes a hybrid differential evolution (DE) algorithm, namely clonal selection-based differential evolution (CSDE), to solve the problem. CSDE is an artificial intelligence technique that can be applied to complex optimisation problems which are for example nonlinear, large scale, non-convex and discontinuous. This hybrid algorithm combines the clonal selection algorithm (CSA) as the local search technique to update the best individual in the population, which enhances the diversity of the solutions and prevents premature convergence in DE. Furthermore, we investigate four mutation operations which are used in CSA as the hyper-mutation operations. Finally, an efficient solution repair method is designed for DELD to satisfy the complicated equality and inequality constraints of the power system to guarantee the feasibility of the solutions. Two benchmark power systems are used to evaluate the performance of the proposed method. The experimental results show that the proposed CSDE/best/1 approach significantly outperforms nine other variants of CSDE and DE, as well as most other published methods, in terms of the quality of the solution and the convergence characteristics.

General, PDB-based collective variables for protein folding

New, automated forms of data-analysis are required in order to understand the high-dimensional trajectories that are obtained from molecular dynamics simulations on proteins. Dimensionality reduction algorithms are particularly appealing in this regard as they allow one to construct unbiased, low-dimensional representations of the trajectory using only the information encoded in the trajectory. The downside of this approach is that different sets of coordinates are required for each different chemical systems under study precisely because the coordinates are constructed using information from the trajectory. In this paper we show how one can resolve this problem by using the sketch-map algorithm that we recently proposed to construct a low-dimensional representation of the structures contained in the protein data bank (PDB). We show that the resulting coordinates are as useful for analysing trajectory data as coordinates constructed using landmark configurations taken from the trajectory and that these coordinates can thus be used for understanding protein folding across a range of systems.

Slot width augmentation in a slotted-wall transonic linear cascade wind tunnel

Transonic tests in linear cascade wind tunnels can suffer
from significant test section boundary interference effects in pitch. A slotted tailboard has been designed and optimised with an in-house Euler numerical method to reduce such ef- fects. Wind tunnel measurements on an overspeed Mach 1.27 discharge from a Rolls-Royce T2 cascade, featuring strong end-wall shock-induced interference, showed a 77% reduction in the flow pitchwise periodicity error with the optimised tail- board, with respect to the baseline open-jet cascade flow. Two-dimensional Euler predictions were also cross-validated against a three-dimensional Reynolds averaged computation, to explore the three-dimensionality of the discharge

Real-space grids and the Octopus code as tools for the development of new simulation approaches for electronic systems

Real-space grids are a powerful alternative for the simulation of electronic systems. One of the main advantages of the approach is the flexibility and simplicity of working directly in real space where the different fields are discretized on a grid, combined with competitive numerical performance and great potential for parallelization. These properties constitute a great advantage at the time of implementing and testing new physical models. Based on our experience with the Octopus code, in this article we discuss how the real-space approach has allowed for the recent development of new ideas for the simulation of electronic systems. Among these applications are approaches to calculate response properties, modeling of photoemission, optimal control of quantum systems, simulation of plasmonic systems, and the exact solution of the Schrödinger equation for low-dimensionality systems.

Portuguese Adaptation of Students Engagement in Schools International Scale (SESIS)

The importance of student’s engagement has been recently pointed out in research. However, there has been a lack of engagement assessment instrument, pertaining psychometric qualities. Objective: This paper presents the Portuguese adaptation of the “Student’s Engagement in School International Scale” (SESIS), drawn up from a12 countries international study (Lam et al., 2012; Lam et al., in press). Method: Psychometric properties of this scale were examined with data from 685 students from different grades (6th, 7th, 9th and 10th), from both sexes, and different regions of the country. Results: Factorial analysis of the results, with varimax rotation, lead to three different factors which explain 50.88% of the variance. The scale integrates the original 33 items, and cognitive, affective and behavioural dimensions. For the external validity study, the relationship between student’s engagement in school results and other school variables — academic performance, self-concept — was considered, and significant relations were observed, as expected. Conclusion: The data presented highlights the qualities of SESIS, as well as its usefulness for research purposes. Suggestion: It is suggested the investigation of the extension of SESIS’s three-dimensionality, in future studiesKeywords: Innovation, technology, research projects, etc. [Arial 10-point, justified alignment].

Portuguese Adaptation of Students Engagement in Schools International Scale (Sesis)

The importance of student’s engagement has been recently pointed out in research. However, there has been a lack of engagement assessment instruments, showing psychometric qualities, such as reliability and validity. Objective: This paper presents the Portuguese adaptation of the “Student’s Engagement in Schools International Scale” (SESIS), drawn up from 12 countries international study (Lam et al., 2012; Lam et al., in press). Method: Psychometric properties of this scale were examined using data from 685 students, of both sexes, and from different grades (6th, 7th, 9th and 10th), and regions of the country. Results: Factorial analysis of the results, with varimax rotation, conducted to three different factors which explain 62,19% of the variance. The scale integrates the original 33 items, and cognitive, affective and behavioural dimensions. For the external validity study, the relationship between student’s engagement in school results and other school variables — academic performance, school conduct — was considered, and significant relations were observed, as expected. Conclusion: The data presented highlights the qualities of SESIS, as well as its usefulness for research purpose. Suggestion: It is suggested the investigation of the extension of SESIS’s three-dimensionality, in future studies

Subspace-based techniques and applications

Este trabalho focou-se no estudo de técnicas de sub-espaço tendo em vista as aplicações seguintes: eliminação de ruído em séries temporais e extracção de características para problemas de classificação supervisionada. Foram estudadas as vertentes lineares e não-lineares das referidas técnicas tendo como ponto de partida os algoritmos SSA e KPCA. No trabalho apresentam-se propostas para optimizar os algoritmos, bem como uma descrição dos mesmos numa abordagem diferente daquela que é feita na literatura. Em qualquer das vertentes, linear ou não-linear, os métodos são apresentados utilizando uma formulação algébrica consistente. O modelo de subespaço é obtido calculando a decomposição em valores e vectores próprios das matrizes de kernel ou de correlação/covariância calculadas com um conjunto de dados multidimensional. A complexidade das técnicas não lineares de subespaço é discutida, nomeadamente, o problema da pre-imagem e a decomposição em valores e vectores próprios de matrizes de dimensão elevada. Diferentes algoritmos de préimagem são apresentados bem como propostas alternativas para a sua optimização. A decomposição em vectores próprios da matriz de kernel baseada em aproximações low-rank da matriz conduz a um algoritmo mais eficiente- o Greedy KPCA. Os algoritmos são aplicados a sinais artificiais de modo a estudar a influência dos vários parâmetros na sua performance. Para além disso, a exploração destas técnicas é extendida à eliminação de artefactos em séries temporais biomédicas univariáveis, nomeadamente, sinais EEG.

Radiation-induced defects in quantum-size structures of A3B5 semiconductors

As estruturas quânticas de semicondutores, nomeadamente baseadas em GaAs, têm tido nos últimos vinte anos um claro desenvolvimento. Este desenvolvimento deve-se principalmente ao potencial tecnológico que estas estruturas apresentam. As aplicações espaciais, em ambientes agressivos do ponto de vista do nível de radiação a que os dispositivos estão sujeitos, motivaram todo o desenrolar de estudos na área dos defeitos induzidos pela radiação. As propriedades dos semicondutores e dos dispositivos de semicondutores são altamente influenciadas pela presença de defeitos estruturais, em particular os induzidos pela radiação. As propriedades dos defeitos, os processos de criação e transformação de defeitos devem ser fortemente alterados quando se efectua a transição entre o semicondutor volúmico e as heteroestruturas de baixa dimensão. Este trabalho teve como principal objectivo o estudo de defeitos induzidos pela radiação em estruturas quânticas baseadas em GaAs e InAs. Foram avaliadas as alterações introduzidas pelos defeitos em estruturas de poços quânticos e de pontos quânticos irradiadas com electrões e com protões. A utilização de várias técnicas de espectroscopia óptica, fotoluminescência, excitação de fotoluminescência e fotoluminescência resolvida no tempo, permitiu caracterizar as diferentes estruturas antes e após a irradiação. Foi inequivocamente constatada uma maior resistência à radiação dos pontos quânticos quando comparados com os poços quânticos e os materiais volúmicos. Esta resistência deve-se principalmente a uma maior localização da função de onda dos portadores com o aumento do confinamento dos mesmos. Outra razão provável é a expulsão dos defeitos dos pontos quânticos para a matriz. No entanto, a existência de defeitos na vizinhança dos pontos quânticos promove a fuga dos portadores dos níveis excitados, cujas funções de onda são menos localizadas, provocando um aumento da recombinação nãoradiativa e, consequentemente, uma diminuição da intensidade de luminescência dos dispositivos. O desenvolvimento de um modelo bastante simples para a estatística de portadores fora de equilíbrio permitiu reproduzir os resultados de luminescência em função da temperatura. Os resultados demonstraram que a extinção da luminescência com o aumento da temperatura é determinada por dois factores: a redistribuição dos portadores minoritários entre os pontos quânticos, o poço quântico e as barreiras de GaAs e a diminuição na taxa de recombinação radiativa relacionada com a dependência, na temperatura, do nível de Fermi dos portadores maioritários.

Física e contemporaneidade no ensino secundário: um contributo no âmbito da formação de professores

O presente trabalho versa a problemática da abordagem da Física Moderna e Contemporânea (FMC) no Ensino Secundário no quadro dos desafios que se colocam à educação científica actual. Num mundo em mudança em que o futuro não está garantido, o esforço educativo deve incluir a dimensão da importância do conhecimento na transformação dos indivíduos com vista à intervenção. A literatura tem apresentado a transposição para a sala de aula da Física desenvolvida ao longo do século XX, como relevante neste domínio. Esta relevância prende-se com a actualidade do conhecimento, com a associação a grande parte da tecnologia actual e ainda com a ligação ao conhecimento mais profundo da natureza e, supostamente, ao sentido do universo. Porém, uma escola de cariz essencialmente transmissivo e desencorajadora de itinerâncias pessoais, tornará muito limitativa a referida transposição. Vários são os constrangimentos da abordagem da FMC neste nível de ensino. Trata-se de um conhecimento contra-intuitivo, que suscita interpretações diversificadas e que se desenvolve formalmente com base em ferramentas matemáticas, em grande parte, não acessíveis a alunos do Ensino Secundário. A formação de professores é uma vertente essencial dentro desta problemática, podendo ser considerada, em muitos casos, deficiente ou desadequada por via do mesmo tipo de constrangimentos referidos. Este trabalho propõe-se estudar as possibilidades e potencialidades da formação de professores no contexto apresentado, a partir de um cenário alternativo que consideramos inovador. Para isso foi concebido, implementado e avaliado um Círculo de Estudos no âmbito da formação em FMC. Utilizando uma estratégia de investigação/ acção/ formação, ensaiou-se a integração de uma certa transdisciplinaridade e multidimensionalidade humana num percurso de natureza complexa, procurando-se a emergência a partir da interacção. À partida eram procurados indicadores de construção identitária e desenvolvimento da profissionalidade. Era ainda esperada a participação dos professores formandos na construção de materiais didácticos. Utilizando uma metodologia de cariz qualitativo na tipologia de estudo de caso, os dados foram recolhidos a partir de instrumentos preparados para o efeito como questionários, mas também de outras fontes como textos reflexivos dos professores e materiais didácticos elaborados pelos mesmos. Os resultados obtidos são de dois tipos. Em primeiro lugar mostram que o percurso efectuado produziu alterações ao nível do discurso dos professores, que revela valorização da itinerância e abertura à incerteza na abordagem da FMC, bem como uma maior familiarização com os conceitos. Por outro lado, os materiais de utilização em sala de aula produzidos foram considerados de interesse como contributos didácticos para utilização futura. Pensamos ainda poder afirmar que são apresentados elementos importantes para a definição de um desenho de formação de professores em FMC, com vista a um ensino e a uma aprendizagem pertinentes.

Ferroelectric : CNTs structures fabrication for advanced functional nano devices

This work is about the combination of functional ferroelectric oxides with Multiwall Carbon Nanotubes for microelectronic applications, as for example potential 3 Dimensional (3D) Non Volatile Ferroelectric Random Access Memories (NVFeRAM). Miniaturized electronics are ubiquitous now. The drive to downsize electronics has been spurred by needs of more performance into smaller packages at lower costs. But the trend of electronics miniaturization challenges board assembly materials, processes, and reliability. Semiconductor device and integrated circuit technology, coupled with its associated electronic packaging, forms the backbone of high-performance miniaturized electronic systems. However, as size decreases and functionalization increases in the modern electronics further size reduction is getting difficult; below a size limit the signal reliability and device performance deteriorate. Hence miniaturization of siliconbased electronics has limitations. On this background the Road Map for Semiconductor Industry (ITRS) suggests since 2011 alternative technologies, designated as More than Moore; being one of them based on carbon (carbon nanotubes (CNTs) and graphene) [1]. CNTs with their unique performance and three dimensionality at the nano-scale have been regarded as promising elements for miniaturized electronics [2]. CNTs are tubular in geometry and possess a unique set of properties, including ballistic electron transportation and a huge current caring capacity, which make them of great interest for future microelectronics [2]. Indeed CNTs might have a key role in the miniaturization of Non Volatile Ferroelectric Random Access Memories (NVFeRAM). Moving from a traditional two dimensional (2D) design (as is the case of thin films) to a 3D structure (based on a tridimensional arrangement of unidimensional structures) will result in the high reliability and sensing of the signals due to the large contribution from the bottom electrode. One way to achieve this 3D design is by using CNTs. Ferroelectrics (FE) are spontaneously polarized and can have high dielectric constants and interesting pyroelectric, piezoelectric, and electrooptic properties, being a key application of FE electronic memories. However, combining CNTs with FE functional oxides is challenging. It starts with materials compatibility, since crystallization temperature of FE and oxidation temperature of CNTs may overlap. In this case low temperature processing of FE is fundamental. Within this context in this work a systematic study on the fabrication of CNTs - FE structures using low cost low temperature methods was carried out. The FE under study are comprised of lead zirconate titanate (Pb1-xZrxTiO3, PZT), barium titanate (BaTiO3, BT) and bismuth ferrite (BiFeO3, BFO). The various aspects related to the fabrication, such as effect on thermal stability of MWCNTs, FE phase formation in presence of MWCNTs and interfaces between the CNTs/FE are addressed in this work. The ferroelectric response locally measured by Piezoresponse Force Microscopy (PFM) clearly evidenced that even at low processing temperatures FE on CNTs retain its ferroelectric nature. The work started by verifying the thermal decomposition behavior under different conditions of the multiwall CNTs (MWCNTs) used in this work. It was verified that purified MWCNTs are stable up to 420 ºC in air, as no weight loss occurs under non isothermal conditions, but morphology changes were observed for isothermal conditions at 400 ºC by Raman spectroscopy and Transmission Electron Microscopy (TEM). In oxygen-rich atmosphere MWCNTs started to oxidized at 200 ºC. However in argon-rich one and under a high heating rate MWCNTs remain stable up to 1300 ºC with a minimum sublimation. The activation energy for the decomposition of MWCNTs in air was calculated to lie between 80 and 108 kJ/mol. These results are relevant for the fabrication of MWCNTs – FE structures. Indeed we demonstrate that PZT can be deposited by sol gel at low temperatures on MWCNTs. And particularly interesting we prove that MWCNTs decrease the temperature and time for formation of PZT by ~100 ºC commensurate with a decrease in activation energy from 68±15 kJ/mol to 27±2 kJ/mol. As a consequence, monophasic PZT was obtained at 575 ºC for MWCNTs - PZT whereas for pure PZT traces of pyrochlore were still present at 650 ºC, where PZT phase formed due to homogeneous nucleation. The piezoelectric nature of MWCNTs - PZT synthesised at 500 ºC for 1 h was proved by PFM. In the continuation of this work we developed a low cost methodology of coating MWCNTs using a hybrid sol-gel / hydrothermal method. In this case the FE used as a proof of concept was BT. BT is a well-known lead free perovskite used in many microelectronic applications. However, synthesis by solid state reaction is typically performed around 1100 to 1300 ºC what jeopardizes the combination with MWCNTs. We also illustrate the ineffectiveness of conventional hydrothermal synthesis in this process due the formation of carbonates, namely BaCO3. The grown MWCNTs - BT structures are ferroelectric and exhibit an electromechanical response (15 pm/V). These results have broad implications since this strategy can also be extended to other compounds of materials with high crystallization temperatures. In addition the coverage of MWCNTs with FE can be optimized, in this case with non covalent functionalization of the tubes, namely with sodium dodecyl sulfate (SDS). MWCNTs were used as templates to grow, in this case single phase multiferroic BFO nanorods. This work shows that the use of nitric solvent results in severe damages of the MWCNTs layers that results in the early oxidation of the tubes during the annealing treatment. It was also observed that the use of nitric solvent results in the partial filling of MWCNTs with BFO due to the low surface tension (<119 mN/m) of the nitric solution. The opening of the caps and filling of the tubes occurs simultaneously during the refluxing step. Furthermore we verified that MWCNTs have a critical role in the fabrication of monophasic BFO; i.e. the oxidation of CNTs during the annealing process causes an oxygen deficient atmosphere that restrains the formation of Bi2O3 and monophasic BFO can be obtained. The morphology of the obtained BFO nano structures indicates that MWCNTs act as template to grow 1D structure of BFO. Magnetic measurements on these BFO nanostructures revealed a week ferromagnetic hysteresis loop with a coercive field of 956 Oe at 5 K. We also exploited the possible use of vertically-aligned multiwall carbon nanotubes (VA-MWCNTs) as bottom electrodes for microelectronics, for example for memory applications. As a proof of concept BiFeO3 (BFO) films were in-situ deposited on the surface of VA-MWCNTs by RF (Radio Frequency) magnetron sputtering. For in situ deposition temperature of 400 ºC and deposition time up to 2 h, BFO films cover the VA-MWCNTs and no damage occurs either in the film or MWCNTs. In spite of the macroscopic lossy polarization behaviour, the ferroelectric nature, domain structure and switching of these conformal BFO films was verified by PFM. A week ferromagnetic ordering loop was proved for BFO films on VA-MWCNTs having a coercive field of 700 Oe. Our systematic work is a significant step forward in the development of 3D memory cells; it clearly demonstrates that CNTs can be combined with FE oxides and can be used, for example, as the next 3D generation of FERAMs, not excluding however other different applications in microelectronics.

Fuzzy rule extraction from input/output data

Several alternative approaches have been discussed: Levenberg-Marquardt - no satisfactory convergence speed + local minimum, Bacterial algorithm - problems with large dimensionality (speed), Clustering - no safe criterion for number of clusters + dimentionality problem.