Literacy practices in adult learning biographies: possibilities and constraints

[Extrat] The answer to the social and economic challenges that it is assumed literacy (or its lack) puts to developed countries deeply concerns public policies of governments namely those of the OECD area. In the last decades, these concerns gave origin to several and diverse monitoring devices, initiatives and programmes for reading (mainly) development, putting a strong stress on education. UNESCO (2006, p. 6), for instance, assumes that the literacy challenge can only be met raising the quality of primary and secondary education and intensifying programmes explicitly oriented towards youth and adult literacy. (...)

Discrimination of Brazilian propolis according to the seasoning using chemometrics and machine learning based on UV-Vis scanning data

Propolis is a chemically complex biomass produced by honeybees (Apis mellifera) from plant resins added of salivary enzymes, beeswax, and pollen. The biological activities described for propolis were also identified for donor plants resin, but a big challenge for the standardization of the chemical composition and biological effects of propolis remains on a better understanding of the influence of seasonality on the chemical constituents of that raw material. Since propolis quality depends, among other variables, on the local flora which is strongly influenced by (a)biotic factors over the seasons, to unravel the harvest season effect on the propolis chemical profile is an issue of recognized importance. For that, fast, cheap, and robust analytical techniques seem to be the best choice for large scale quality control processes in the most demanding markets, e.g., human health applications. For that, UV-Visible (UV-Vis) scanning spectrophotometry of hydroalcoholic extracts (HE) of seventy-three propolis samples, collected over the seasons in 2014 (summer, spring, autumn, and winter) and 2015 (summer and autumn) in Southern Brazil was adopted. Further machine learning and chemometrics techniques were applied to the UV-Vis dataset aiming to gain insights as to the seasonality effect on the claimed chemical heterogeneity of propolis samples determined by changes in the flora of the geographic region under study. Descriptive and classification models were built following a chemometric approach, i.e. principal component analysis (PCA) and hierarchical clustering analysis (HCA) supported by scripts written in the R language. The UV-Vis profiles associated with chemometric analysis allowed identifying a typical pattern in propolis samples collected in the summer. Importantly, the discrimination based on PCA could be improved by using the dataset of the fingerprint region of phenolic compounds ( = 280-400m), suggesting that besides the biological activities of those secondary metabolites, they also play a relevant role for the discrimination and classification of that complex matrix through bioinformatics tools. Finally, a series of machine learning approaches, e.g., partial least square-discriminant analysis (PLS-DA), k-Nearest Neighbors (kNN), and Decision Trees showed to be complementary to PCA and HCA, allowing to obtain relevant information as to the sample discrimination.

Learning Robotics for youngsters - the RoboParty experience

Series: "Advances in intelligent systems and computing , ISSN 2194-5357, vol. 417"

Um modelo para a gestão do conhecimento organizacional no contexto dos serviços partilhados com recurso à utilização do e-Learning

Tese de Doutoramento em Tecnologias e Sistemas de Informação

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.

Biological markers in noninvasive brain stimulation trials in major depressive disorder: a systematic review

Objectives: The therapeutic effects of transcranial magnetic stimulation (TMS) and transcranial direct current stimulation in patients with major depression have shown promising results; however, there is a lack of mechanistic studies using biological markers (BMs) as an outcome. Therefore, our aim was to review noninvasive brain stimulation trials in depression using BMs. Methods: The following databases were used for our systematic review: MEDLINE, Web of Science, Cochrane, and SCIELO. We examined articles published before November 2012 that used TMS and transcranial direct current stimulation as an intervention for depression and had BM as an outcome measure. The search was limited to human studies written in English. Results: Of 1234 potential articles, 52 articles were included. Only studies using TMS were found. Biological markers included immune and endocrine serum markers, neuroimaging techniques, and electrophysiological outcomes. In 12 articles (21.4%), end point BM measurements were not significantly associated with clinical outcomes. All studies reached significant results in the main clinical rating scales. Biological marker outcomes were used as predictors of response, to understand mechanisms of TMS, and as a surrogate of safety. Conclusions: Functional magnetic resonance imaging, single-photon emission computed tomography, positron emission tomography, magnetic resonance spectroscopy, cortical excitability, and brain-derived neurotrophic factor consistently showed positive results. Brain-derived neurotrophic factor was the best predictor of patients’ likeliness to respond. These initial results are promising; however, all studies investigating BMs are small, used heterogeneous samples, and did not take into account confounders such as age, sex, or family history. Based on our findings, we recommend further studies to validate BMs in noninvasive brain stimulation trials in MDD.

Inferior frontal gyrus white matter abnormalities in obsessive-compulsive disorder

The aim of the present study is to explore obsessive-compulsive disorder (OCD)-related abnormalities in white matter connectivity in OCD for a core region associated with inhibitory control [i.e. inferior frontal gyrus (IFG)]. Fifteen patients with OCD (11 men) and 15 healthy controls (nine men) underwent diffusion tensor imaging scanning to study four diffusivity indexes of white matter integrity [fractional anisotropy, mean diffusivity (MD), axial diffusivity and radial diffusivity (RD)]. The results showed that persons with OCD manifested significantly lower fractional anisotropy levels in the bilateral IFG as well as its parcellations in the pars opercularis, pars triangularis, and pars orbitalis. Significantly higher levels of MD, RD were evident for the OCD group in the IFG as a whole as well as in the bilateral subregions of the pars triangularis and pars opercularis (for MD and RD), the right side of the pars orbitalis (for RD), and the left side of the pars triangularis and right side pars opercularis (for axial diffusivity). Overall, the results suggest significant alterations in structural connectivity, probably associated with myelination and axonal abnormalities in the IFG of OCD patients.

“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.

Some notes on a historical perspective of panic disorder

This article aims to describe important points in the history of panic disorder concept, as well as to highlight the importance of its diagnosis for clinical and research developments. Panic disorder has been described in several literary reports and folklore. One of the oldest examples lies in Greek mythology - the god Pan, responsible for the term panic. The first half of the 19th century witnessed the culmination of medical approach. During the second half of the 19th century came the psychological approach of anxiety. The 20th century associated panic disorder to hereditary, organic and psychological factors, dividing anxiety into simple and phobic anxious states. Therapeutic development was also observed in psychopharmacological and psychotherapeutic fields. Official classifications began to include panic disorder as a category since the third edition of the American Classification Manual (1980). Some biological theories dealing with etiology were widely discussed during the last decades of the 20th century. They were based on laboratory studies of physiological, cognitive and biochemical tests, as the false suffocation alarm theory and the fear network. Such theories were important in creating new diagnostic paradigms to modern psychiatry. That suggests the need to consider a wide range of historical variables to understand how particular features for panic disorder diagnosis have been developed and how treatment has emerged.

Trans-cultural aspects of social anxiety disorder and related conditions: a Brazilian case series and a review of international clinical studies

Cross-cultural studies have much to teach clinicians and researchers alike about psychopathology in general and about social anxiety disorder (SAD) in particular. Unfortunately, little is known about the degree and the mechanisms through which cultural environment may influence clinical manifestations of SAD. OBJECTIVE: Our objective was to identify culture-related clinical patterns in SAD and related disorders. METHODS: We described socio-demographic and clinical characteristics of a sample of 62 adult outpatients with SAD seen at a university clinic for anxiety and depressive disorders in Rio de Janeiro, Brazil, and compared them with those reported in clinical samples from North America, Europe, Asia and Oceania identified through a systematic review in Medline, PsychINFO, and LILACS. RESULTS: Our comparison of trans-cultural features of SAD lends partial support to Heimberg's (1997) contention that the majority of socio-demographic features and symptoms of this disorder are relatively independent of geographic and cultural differences. CONCLUSION: Patients with SAD were almost universally characterized by: 1) a predominance of males in clinical samples; 2) early onset of the disorder; 3) high educational attainment; and 4) great frequency of comorbidities.

A five year follow-up study of 11 patients with bipolar disorder

OBJECTIVE: To study the long-term follow-up of patients with bipolar disorder (BPD). METHOD: Eleven outpatients with BPD type I were followed up naturalistically for five years at a university teaching hospital. The Clinical Global Impression Scale (BPD version) was used to evaluate the occurrence of affective episodes, and the Strauss-Carpenter Outcome Scale was used to evaluate social and occupational functioning. RESULTS: The majority of patients were symptomatic most of the time, with predominantly depressive episodes. Overall, patients remained euthymic a mean of 47.7% of the time. Despite a low rate of hospitalization, social and occupational functioning was poor in the majority of patients. A poor disease course with respect to work-related functioning was associated with fewer months of euthymia with a longer duration of depressive episodes. The total number of months of euthymia negatively correlated with the patient's age and disease duration. CONCLUSION: Despite the small sample size, the present findings appear to corroborate previous studies on the evolution of BPD. Most of the patients had a poor disease course, with long symptomatic periods, particularly depressive episodes, and significantly impaired social and occupational functioning.

Self-evaluated burden in adults with attention-deficit hyperactivity disorder (ADHD): a pilot study

OBJECTIVES: To investigate feasibility and easiness of administration of a brief and simple instrument addressing impairment associated with adult attention deficit hyperactivity disorder (ADHD) and if ADHD subtypes were correlated to specific profiles of self-reported impairment. METHODS: Thirty-five adults (19 men and 16 women; mean age of 31.74 years) diagnosed with ADHD according to DSM-IV with a semi-structured interview (K-SADS PL) were asked to fill out a Likert scale covering six different functional areas (academic, professional, marital, familiar, social and daily activities). Clinicians questioned patients about their understanding of the questionnaire and investigated their answers in more details to check consistency of their answers. RESULTS: No patient reported difficulties in understanding the questionnaire. Further questioning of patients' answers confirmed their choices in the six areas. Academic burden had the highest average score in the whole sample, followed by professional burden. Social area had the lowest average score in this sample.