New mitochondrial and nuclear evidences support recent demographic expansion and an atypical phylogeographic pattern in the Spittlebug Philaenus spumarius (Hemiptera, Aphrophoridae)

Copyright: © 2014 Rodrigues et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Supporting learning through tagging systems

With the advent of Web 2.0, new kinds of tools became available, which are not seen as novel anymore but are widely used. For instance, according to Eurostat data, in 2010 32% of individuals aged 16 to 74 used the Internet to post messages to social media sites or instant messaging tools, ranging from 17% in Romania to 46% in Sweden (Eurostat, 2012). Web 2.0 applications have been used in technology-enhanced learning environments. Learning 2.0 is a concept that has been used to describe the use of social media for learning. Many Learning 2.0 initiatives have been launched by educational and training institutions in Europe. Web 2.0 applications have also been used for informal learning. Web 2.0 tools can be used in classrooms, virtual or not, not only to engage students but also to support collaborative activities. Many of these tools allow users to use tags to organize resources and facilitate their retrieval at a later date or time. The aim of this chapter is to describe how tagging has been used in systems that support formal or informal learning and to summarize the functionalities that are common to these systems. In addition, common and unusual tagging applications that have been used in some Learning Objects Repositories are analysed.

Pattern operators for grid

The definition and programming of distributed applications has become a major research issue due to the increasing availability of (large scale) distributed platforms and the requirements posed by the economical globalization. However, such a task requires a huge effort due to the complexity of the distributed environments: large amount of users may communicate and share information across different authority domains; moreover, the “execution environment” or “computations” are dynamic since the number of users and the computational infrastructure change in time. Grid environments, in particular, promise to be an answer to deal with such complexity, by providing high performance execution support to large amount of users, and resource sharing across different organizations. Nevertheless, programming in Grid environments is still a difficult task. There is a lack of high level programming paradigms and support tools that may guide the application developer and allow reusability of state-of-the-art solutions. Specifically, the main goal of the work presented in this thesis is to contribute to the simplification of the development cycle of applications for Grid environments by bringing structure and flexibility to three stages of that cycle through a commonmodel. The stages are: the design phase, the execution phase, and the reconfiguration phase. The common model is based on the manipulation of patterns through pattern operators, and the division of both patterns and operators into two categories, namely structural and behavioural. Moreover, both structural and behavioural patterns are first class entities at each of the aforesaid stages. At the design phase, patterns can be manipulated like other first class entities such as components. This allows a more structured way to build applications by reusing and composing state-of-the-art patterns. At the execution phase, patterns are units of execution control: it is possible, for example, to start or stop and to resume the execution of a pattern as a single entity. At the reconfiguration phase, patterns can also be manipulated as single entities with the additional advantage that it is possible to perform a structural reconfiguration while keeping some of the behavioural constraints, and vice-versa. For example, it is possible to replace a behavioural pattern, which was applied to some structural pattern, with another behavioural pattern. In this thesis, besides the proposal of the methodology for distributed application development, as sketched above, a definition of a relevant set of pattern operators was made. The methodology and the expressivity of the pattern operators were assessed through the development of several representative distributed applications. To support this validation, a prototype was designed and implemented, encompassing some relevant patterns and a significant part of the patterns operators defined. This prototype was based in the Triana environment; Triana supports the development and deployment of distributed applications in the Grid through a dataflow-based programming model. Additionally, this thesis also presents the analysis of a mapping of some operators for execution control onto the Distributed Resource Management Application API (DRMAA). This assessment confirmed the suitability of the proposed model, as well as the generality and flexibility of the defined pattern operators

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.

Mobile collaborative cloudless computing

Although the computational power of mobile devices has been increasing, it is still not enough for some classes of applications. In the present, these applications delegate the computing power burden on servers located on the Internet. This model assumes an always-on Internet connectivity and implies a non-negligible latency. The thesis addresses the challenges and contributions posed to the application of a mobile collaborative computing environment concept to wireless networks. The goal is to define a reference architecture for high performance mobile applications. Current work is focused on efficient data dissemination on a highly transitive environment, suitable to many mobile applications and also to the reputation and incentive system available on this mobile collaborative computing environment. For this we are improving our already published reputation/incentive algorithm with knowledge from the usage pattern from the eduroam wireless network in the Lisbon area.

Remote lab experiments: opening possibilities for distance learning in engineering fields

Remote experimentation laboratories are systems based on real equipment, allowing students to perform practical work through a computer connected to the internet. In engineering fields lab activities play a fundamental role. Distance learning has not demonstrated good results in engineering fields because traditional lab activities cannot be covered by this paradigm. These activities can be set for one or for a group of students who work from different locations. All these configurations lead to considering a flexible model that covers all possibilities (for an individual or a group). An inter-continental network of remote laboratories supported by both European and Latin American institutions of higher education has been formed. In this network context, a learning collaborative model for students working from different locations has been defined. The first considerations are presented.

Towards e-learning 2.0: case study of an e-learning environment

In these days the learning experience is no longer confined within the four walls of a classroom. Computers and primarily the internet have broadened this horizon by creating a way of delivering education that is known as e-learning. In the meantime, the internet, or more precisely, the Web is heading towards a new paradigm where the user is no longer just a consumer of information and becomes an active part in the communication. This two-way channel where the user takes the role of the producer of content triggered the appearance of new types of services such as Social Networks, Blogs and Wikis. To seize this second generation of communities and services, educational vendors are willing to develop e-learning systems focused on the new and emergent users needs. This paper describes the analysis and specification of an e-learning environment at our School (ESEIG) towards this new Web generation, called PEACE – Project for ESEIG Academic Environment. This new model relies on the integration of several services controlled by teachers and students such as social networks, repositories libraries, e-portfolios and e-conference sytems, intelligent tutors, recommendation systems, automatic evaluators, virtual classrooms and 3D avatars.

Teaching and learning with social software in higher education: content management systems integrated with Web-based applications as a key factor for success

The change of paradigm imposed by the Bologna process, in which the student will be responsible for their own learning, and the presence of a new generation of students with higher technological skills, represent a huge challenge for higher education institutions. The use of new Web Social concepts in teaching process, supported by applications commonly called Web 2.0, with which these new students feel at ease, can bring benefits in terms of motivation and the frequency and quality of students' involvement in academic activities. An e-learning platform with web-based applications as a complement can significantly contribute to the development of different skills in higher education students, covering areas which are usually in deficit.

Recommending media content based on machine learning methods

Dissertação para obtenção do Grau de Mestre em Engenharia Informática

Regulatory Cells, Cytokine Pattern and Clinical Risk Factors for Asthma in Infants and Young Children with Recurrent Wheeze

Several risk factors for asthma have been identified in infants and young children with recurrent wheeze. However, published literature has reported contradictory findings regarding the underlying immunological mechanisms. OBJECTIVES: This study was designed to assess and compare the immunological status during the first 2 years in steroid-naive young children with >or= three episodes of physician-confirmed wheeze (n=50), with and without clinical risk factors for developing subsequent asthma (i.e. parental asthma or a personal history of eczema and/or two of the following: wheezing without colds, a personal history of allergic rhinitis and peripheral blood eosinophilia >4%), with age-matched healthy controls (n=30). METHODS: Peripheral blood CD4(+)CD25(+) and CD4(+)CD25(high) T cells and their cytotoxic T-lymphocyte-associated antigen-4 (CTLA-4), GITR and Foxp3 expression were analysed by flow cytometry. Cytokine (IFN-gamma, TGF-beta and IL-10), CTLA-4 and Foxp3 mRNA expression were evaluated (real-time PCR) after peripheral blood mononuclear cell stimulation with phorbol 12-myristate 13-acetate (PMA) (24 h) and house dust mite (HDM) extracts (7th day). RESULTS: Flow cytometry results showed a significant reduction in the absolute number of CD4(+)CD25(high) and the absolute and percentage numbers of CD4(+)CD25(+)CTLA-4(+) in wheezy children compared with healthy controls. Wheezy children at a high risk of developing asthma had a significantly lower absolute number of CD4(+)CD25(+) (P=0.01) and CD4(+)CD25(high) (P=0.04), compared with those at a low risk. After PMA stimulation, CTLA-4 (P=0.03) and Foxp3 (P=0.02) expression was diminished in wheezy children compared with the healthy children. After HDM stimulation, CTLA-4 (P=0.03) and IFN-gamma (P=0.04) expression was diminished in wheezy children compared with healthy children. High-risk children had lower expression of IFN-gamma (P=0.03) compared with low-risk and healthy children and lower expression of CTLA-4 (P=0.01) compared with healthy children. CONCLUSIONS: Although our findings suggest that some immunological parameters are impaired in children with recurrent wheeze, particularly with a high risk for asthma, further studies are needed in order to assess their potential as surrogate predictor factors for asthma in early life.

The national physics and chemistry exams and the learning of sciences

Dissertação apresentada para obtenção do Grau de Doutor em Ciências da Educação, pela Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa

Real-time collaborative editing of OutSystems DSL models

Real-time collaborative editing systems are common nowadays, and their advantages are widely recognized. Examples of such systems include Google Docs, ShareLaTeX, among others. This thesis aims to adopt this paradigm in a software development environment. The OutSystems visual language lends itself very appropriate to this kind of collaboration, since the visual code enables a natural flow of knowledge between developers regarding the developed code. Furthermore, communication and coordination are simplified. This proposal explores the field of collaboration on a very structured and rigid model, where collaboration is made through the copy-modify-merge paradigm, in which a developer gets its own private copy from the shared repository, modifies it in isolation and later uploads his changes to be merged with modifications concurrently produced by other developers. To this end, we designed and implemented an extension to the OutSystems Platform, in order to enable real-time collaborative editing. The solution guarantees consistency among the artefacts distributed across several developers working on the same project. We believe that it is possible to achieve a much more intense collaboration over the same models with a low negative impact on the individual productivity of each developer.

Ensino, aprendizagem e avaliação no Ensino Superior: Perspetivas e práticas

Tese de Doutoramento em Ciências da Educação - Especialidade de Desenvolvimento Curricular

Gamification e game-based learning: uma abordagem lúdica à aprendizagem

Relatório de estágio de mestrado em Ensino de Informática

Geographic pattern of genetic diversity in natural populations of Rosewood (Aniba rosaeodora), in the Central Amazonia

Rosewood (Aniba rosaeodora Ducke, Lauraceae) is an Amazonian evergreen tree and a source of the purest linalool, the main component of its essential oil, which is very valuable in the international perfumery market. After decades of over-exploitation it is currently considered as threatened. We evaluated the genetic diversity and its distribution in four populations in Central Amazonia. Thirty-five reliable RAPD markers were generated, of which 32 were polymorphic (91.4%). Variation was higher within the populations (76.5%; p < 0.0001) and geographic distribution contributed to population differentiation (23.4%; p < 0.0001). The Amazon River had a small influence on gene flow (3.3%; p < 0.0001), but we identified evidence of gene flow across the river. There were significant differences in marker frequencies (p < 0.05), in agreement with the low gene flow (Nm = 2.02). The correlation between genetic distance and gene flow was - 0.95 (p = 0.06) and between geographic distance and gene flow was -0.78 (p = 0.12). There was a geographic cline of variability across an East-West axis, influenced as well by the Amazon River, suggesting the river could be a barrier to gene flow. Although threatened, these Rosewood populations retain high diversity, with the highest levels in the Manaus population, which has been protected for over 42 years in a Reserve.