Learning joint representations for order and timing of perceptual-motor sequences: a dynamic neural field approach

Many of our everyday tasks require the control of the serial order and the timing of component actions. Using the dynamic neural field (DNF) framework, we address the learning of representations that support the performance of precisely time action sequences. In continuation of previous modeling work and robotics implementations, we ask specifically the question how feedback about executed actions might be used by the learning system to fine tune a joint memory representation of the ordinal and the temporal structure which has been initially acquired by observation. The perceptual memory is represented by a self-stabilized, multi-bump activity pattern of neurons encoding instances of a sensory event (e.g., color, position or pitch) which guides sequence learning. The strength of the population representation of each event is a function of elapsed time since sequence onset. We propose and test in simulations a simple learning rule that detects a mismatch between the expected and realized timing of events and adapts the activation strengths in order to compensate for the movement time needed to achieve the desired effect. The simulation results show that the effector-specific memory representation can be robustly recalled. We discuss the impact of the fast, activation-based learning that the DNF framework provides for robotics applications.

Off-line simulation inspires insight: a neurodynamics approach to efficient robot task learning

There is currently an increasing demand for robots able to acquire the sequential organization of tasks from social learning interactions with ordinary people. Interactive learning-by-demonstration and communication is a promising research topic in current robotics research. However, the efficient acquisition of generalized task representations that allow the robot to adapt to different users and contexts is a major challenge. In this paper, we present a dynamic neural field (DNF) model that is inspired by the hypothesis that the nervous system uses the off-line re-activation of initial memory traces to incrementally incorporate new information into structured knowledge. To achieve this, the model combines fast activation-based learning to robustly represent sequential information from single task demonstrations with slower, weight-based learning during internal simulations to establish longer-term associations between neural populations representing individual subtasks. The efficiency of the learning process is tested in an assembly paradigm in which the humanoid robot ARoS learns to construct a toy vehicle from its parts. User demonstrations with different serial orders together with the correction of initial prediction errors allow the robot to acquire generalized task knowledge about possible serial orders and the longer term dependencies between subgoals in very few social learning interactions. This success is shown in a joint action scenario in which ARoS uses the newly acquired assembly plan to construct the toy together with a human partner.

Paving the way for predictive diagnostics and personalized treatment of invasive aspergillosis

Invasive aspergillosis (IA) is a life-threatening fungal disease commonly diagnosed among individuals with immunological deficits, namely hematological patients undergoing chemotherapy or allogeneic hematopoietic stem cell transplantation. Vaccines are not available, and despite the improved diagnosis and antifungal therapy, the treatment of IA is associated with a poor outcome. Importantly, the risk of infection and its clinical outcome vary significantly even among patients with similar predisposing clinical factors and microbiological exposure. Recent insights into antifungal immunity have further highlighted the complexity of host-fungus interactions and the multiple pathogen-sensing systems activated to control infection. How to decode this information into clinical practice remains however, a challenging issue in medical mycology. Here, we address recent advances in our understanding of the host-fungus interaction and discuss the application of this knowledge in potential strategies with the aim of moving toward personalized diagnostics and treatment (theranostics) in immunocompromised patients. Ultimately, the integration of individual traits into a clinically applicable process to predict the risk and progression of disease, and the efficacy of antifungal prophylaxis and therapy, holds the promise of a pioneering innovation benefiting patients at risk of IA.

“Learning-by-producing” in the fashion value chain

Proceedings da AUTEX 2015, Bucareste, Roménia.

La formación b-learning en el máster de español segunda lengua y lengua extranjera de la Universidade do Minho: innovación pedagógica y desafíos educativos

En el actual marco de creciente innovación pedagógica, debido entre otros factores, a la irrupción de nuevas herramientas informáticas, la enseñanza a distancia (e-learning y/o b-learning) va ocupando cada vez más espacio en la oferta educativa de diversas instituciones. En esta dirección, en la Universidade do Minho, y concretamente en el Área de Estudos Espanhóis e Hispano-Americanos,[1] hemos dedicado considerables esfuerzos a la ampliación de nuestra oferta desde 2010: primero en la elaboración e implementación del Curso de Formación Especializada en Español Lengua Extranjera, modalidad b-learning (3 ediciones; 2010-2013), y, actualmente, con el Máster Universitario en Español Lengua Segunda / Lengua Extranjera (vid. www.melsle.ilch.uminho.pt), también b-learning. En las siguientes páginas, nos proponemos compartir una serie de experiencias y reflexiones que han ido surgiendo durante estos años acerca de la formación universitária de profesores de Español Lengua Extranjera, en general, con recurso a la modalidade b-learning; para ello, nos centraremos en los siguientes aspectos: (i) caracterización general y problematización de la enseñanza a distancia en la Universidade do Minho; (ii) descripción del Máster Universitario en Español Lengua Segunda / Lengua Extranjera, acerca del cual detallaremos algunas prácticas adoptadas, relacionadas com la enseñanza e-learning como, por ejemplo, (iii) la coordinación pedagógica o (iv) los enfoques metodológicos adoptados a partir de la experiencia de una Unidad Curricular concreta.

Metabolic profiling and classification of propolis samples from Southern Brazil: an NMR-based platform coupled with machine learning

The chemical composition of propolis is affected by environmental factors and harvest season, making it difficult to standardize its extracts for medicinal usage. By detecting a typical chemical profile associated with propolis from a specific production region or season, certain types of propolis may be used to obtain a specific pharmacological activity. In this study, propolis from three agroecological regions (plain, plateau, and highlands) from southern Brazil, collected over the four seasons of 2010, were investigated through a novel NMR-based metabolomics data analysis workflow. Chemometrics and machine learning algorithms (PLS-DA and RF), including methods to estimate variable importance in classification, were used in this study. The machine learning and feature selection methods permitted construction of models for propolis sample classification with high accuracy (>75%, reaching 90% in the best case), better discriminating samples regarding their collection seasons comparatively to the harvest regions. PLS-DA and RF allowed the identification of biomarkers for sample discrimination, expanding the set of discriminating features and adding relevant information for the identification of the class-determining metabolites. The NMR-based metabolomics analytical platform, coupled to bioinformatic tools, allowed characterization and classification of Brazilian propolis samples regarding the metabolite signature of important compounds, i.e., chemical fingerprint, harvest seasons, and production regions.

Personalized-based dietary recommendation for weightlifting

Dissertação de mestrado integrado em Engenharia Eletrónica Industrial e Computadores

Hand gesture recognition system based in computer vision and machine learning: Applications on human-machine interaction

Tese de Doutoramento em Engenharia de Eletrónica e de Computadores

“Learning through Radio, Learning for Life!”: Notas sobre o desenvolvimento de uma rádio participativa online

(Excerto) Olhando para o percurso do RadioActive, há uma ideia que parece ser transversal a todo o projeto. Referimo-nos a um princípio que chamaríamos de “identificação” e que foi determinante – é determinante – nos processos de investigação participativa. Falamos da identificação dos investigadores com os princípios da investigação-ação, da identificação das intervenções com as particularidades de cada contexto. Da imprescindível e progressiva identificação dos participantes com o projeto. Na verdade, sem esta multifacetada identificação é impossível pensar em resultados sustentáveis e persistentes. Investigadores e demais participantes têm de sentir que o projeto é “seu”, que os objetivos são “seus”, embora o façam necessariamente a velocidades diferentes. A aprendizagem, neste âmbito, expande-se sempre de dentro para fora, emerge dos interesses do sujeito e não de uma estrutura pré-concebida e imposta pelos que chegam (Ravenscroft et al., 2011), neste caso, os investigadores. Uma das diferenças das pesquisas participativas em relação às tradicionais é, precisamente, a atuação coletiva e não solitária do investigador. Os pesquisadores fazem parte de um processo participatório em que estão envolvidos numa estrutura (Cammarota & Fine, 2008: 5). Paulo Freire é o autor primordial em todos os projetos e países onde a RA101 foi aplicada. As suas concepções em torno da investigação-ação participativa tentam apontar sempre para uma ação e também para uma reflexão sobre os processos.

Current approaches and future perspectives on strategies for the development of personalized tissue engineering therapies

Personalized tissue engineering and regenerative medicine (TERM) therapies propose patient-oriented effective solutions, considering individual needs. Cell-based therapies, for example, may benefit from cell sources that enable easier autologous set-ups or from recent developments on IPS cells technologies towards effective personalized therapeutics. Furthermore, the customization of scaffold materials to perfectly fit a patientâ s tissue defect through rapid prototyping technologies, also known as 3D printing, is now a reality. Nevertheless, the timing to expand cells or to obtain functional in vitrotissue substitutes prior to implantation prevents advancements towards routine use upon patient´s needs. Thus, personalized therapies also anticipate the importance of creating off-the-shelf solutions to enable immediately available tissue engineered products. This paper reviews the main recent developments and future challenges to enable personalized TERM approaches and to bring these technologies closer to clinical applications.

O desenvolvimento do pensamento abstrato através de game-based learning e do Scratch

Relatório de estágio de mestrado em Ensino de Informática

Educating for sociability and learning for citizenship: developing communicational skills and mediation in educational contexts

This text concerns a program about the Promotion of Social and Communicational Skills and Mediation (PSCSM) developed with children aged between 10 and 13 years in a non-formal educational institution. The program of intervention had, as its purpose, the promotion of social and communicational competencies and mediation, thus enabling the children involved to have a healthy and responsible sociability in the different contexts in which they find themselves: family, school, peer group, amongst others. It was developed over 13 sessions with objectives and activities intentionally planned with the view of promoting competencies of communication, co-operation, responsibility, a critical spirit, solidarity, autonomy, respect, integration, inclusion and the recognition of rights and duties. This work was carried out with an action-research methodology that resorted to various techniques and instruments to gather and record information. The results obtained showed the impact and benefits of the program and they also revealed the necessity of educational institutions investing in the promotion of an ethical literacy and the empowerment of the children and young people for healthy sociability and active citizenship.