Adaptivity and a posteriori error control for bifurcation problems I: the Bratu problem

This article is concerned with the numerical detection of bifurcation points of nonlinear partial differential equations as some parameter of interest is varied. In particular, we study in detail the numerical approximation of the Bratu problem, based on exploiting the symmetric version of the interior penalty discontinuous Galerkin finite element method. A framework for a posteriori control of the discretization error in the computed critical parameter value is developed based upon the application of the dual weighted residual (DWR) approach. Numerical experiments are presented to highlight the practical performance of the proposed a posteriori error estimator.

A New Multi-Objective Approach for Molecular Docking Based on RMSD and Binding Energy

Ligand-protein docking is an optimization problem based on predicting the position of a ligand with the lowest binding energy in the active site of the receptor. Molecular docking problems are traditionally tackled with single-objective, as well as with multi-objective approaches, to minimize the binding energy. In this paper, we propose a novel multi-objective formulation that considers: the Root Mean Square Deviation (RMSD) difference in the coordinates of ligands and the binding (intermolecular) energy, as two objectives to evaluate the quality of the ligand-protein interactions. To determine the kind of Pareto front approximations that can be obtained, we have selected a set of representative multi-objective algorithms such as NSGA-II, SMPSO, GDE3, and MOEA/D. Their performances have been assessed by applying two main quality indicators intended to measure convergence and diversity of the fronts. In addition, a comparison with LGA, a reference single-objective evolutionary algorithm for molecular docking (AutoDock) is carried out. In general, SMPSO shows the best overall results in terms of energy and RMSD (value lower than 2A for successful docking results). This new multi-objective approach shows an improvement over the ligand-protein docking predictions that could be promising in in silico docking studies to select new anticancer compounds for therapeutic targets that are multidrug resistant.

Évaluation de la plateforme de formation en ligne MOTIV@CŒUR sur les interventions motivationnelles brèves auprès d’infirmières en soins aigus cardiovasculaires

Dans un contexte de prévention secondaire, les interventions motivationnelles brèves (IMB) effectuées par les infirmières ont le potentiel de réduire les facteurs de risque cardiovasculaires. De par sa flexibilité, la formation en ligne s’impose aujourd’hui comme une méthode pédagogique essentielle au développement des habiletés cliniques des professionnels de la santé. Le but de ce projet était d’évaluer la faisabilité, l’acceptabilité et l’effet préliminaire d’une plateforme de formation en ligne sur les IMB (MOTIV@CŒUR) sur les habiletés perçues et l’utilisation clinique des IMB chez des infirmières en soins cardiovasculaires. Pour ce faire, une étude pilote pré-post à groupe unique a été menée. MOTIV@CŒUR est composée de deux sessions d’une durée totale de 50 minutes incluant des vidéos d’interactions infirmière-patient. Dans chaque session, une introduction théorique aux IMB est suivie de situations cliniques dans lesquelles une infirmière évalue la motivation à changer et intervient selon les principes des IMB. Les situations ciblent le tabagisme, la non-adhérence au traitement médicamenteux, la sédentarité et une alimentation riche en gras et en sel. Il était suggéré aux infirmières de compléter les deux sessions de formation en ligne en moins de 20 jours. Les données sur la faisabilité, l'acceptabilité et les effets préliminaires (habiletés perçues et utilisation clinique auto-rapportée des IMB) ont été recueillies à 30 jours (± 5 jours) après la première session. Nous avons recruté 27 femmes et 4 hommes (âge moyen 37 ans ± 9) en mars 2016. Vingt-quatre des 31 participants (77%) ont terminé les deux sessions de formation en moins de 20 jours. À un mois suite à l’entrée dans l’étude, 28 des 31 participants avaient complété au moins une session. Un haut niveau d’acceptabilité a été observé vu les scores élevés quant à la qualité de l'information, la facilité d'utilisation perçue et la qualité de la plateforme MOTIV@CŒUR. Le score d'utilisation clinique auto-rapporté des interventions visant la confiance était plus élevé après les deux sessions qu’avant les sessions (P = .032). Bien que tous les scores fussent plus élevés après les deux sessions qu’au début, les autres résultats n’étaient pas statistiquement significatifs. En conclusion, l’implantation d’une plateforme de formation en ligne sur les IMB est à la fois faisable et acceptable auprès d’infirmières en soins aigus cardiovasculaires. De plus, une telle formation peut avoir un effet positif sur l'utilisation clinique d’interventions motivationnelles visant la confiance face au changement de comportement de santé.

A PHENOMENOLOGY OF MIMETIC LEARNING AND MULTIMODAL COGNITION: INTEGRATING EXPERIENTIAL KNOWLEDGE INTO PROGRAMS IN RHETORIC, COMPOSITION, AND TECHNICAL COMMUNICATION

My dissertation emphasizes a cognitive account of multimodality that explicitly integrates experiential knowledge work into the rhetorical pedagogy that informs so many composition and technical communication programs. In these disciplines, multimodality is widely conceived in terms of what Gunther Kress calls “socialsemiotic” modes of communication shaped primarily by culture. In the cognitive and neurolinguistic theories of Vittorio Gallese and George Lakoff, however, multimodality is described as a key characteristic of our bodies’ sensory-motor systems which link perception to action and action to meaning, grounding all communicative acts in knowledge shaped through body-engaged experience. I argue that this “situated” account of cognition – which closely approximates Maurice Merleau-Ponty’s phenomenology of perception, a major framework for my study – has pedagogical precedence in the mimetic pedagogy that informed ancient Sophistic rhetorical training, and I reveal that training’s multimodal dimensions through a phenomenological exegesis of the concept mimesis. Plato’s denigration of the mimetic tradition and his elevation of conceptual contemplation through reason, out of which developed the classic Cartesian separation of mind from body, resulted in a general degradation of experiential knowledge in Western education. But with the recent introduction into college classrooms of digital technologies and multimedia communication tools, renewed emphasis is being placed on the “hands-on” nature of inventive and productive praxis, necessitating a revision of methods of instruction and assessment that have traditionally privileged the acquisition of conceptual over experiential knowledge. The model of multimodality I construct from Merleau-Ponty’s phenomenology, ancient Sophistic rhetorical pedagogy, and current neuroscientific accounts of situated cognition insists on recognizing the significant role knowledges we acquire experientially play in our reading and writing, speaking and listening, discerning and designing practices.

Évaluation de la plateforme de formation en ligne MOTIV@CŒUR sur les interventions motivationnelles brèves auprès d’infirmières en soins aigus cardiovasculaires

Dans un contexte de prévention secondaire, les interventions motivationnelles brèves (IMB) effectuées par les infirmières ont le potentiel de réduire les facteurs de risque cardiovasculaires. De par sa flexibilité, la formation en ligne s’impose aujourd’hui comme une méthode pédagogique essentielle au développement des habiletés cliniques des professionnels de la santé. Le but de ce projet était d’évaluer la faisabilité, l’acceptabilité et l’effet préliminaire d’une plateforme de formation en ligne sur les IMB (MOTIV@CŒUR) sur les habiletés perçues et l’utilisation clinique des IMB chez des infirmières en soins cardiovasculaires. Pour ce faire, une étude pilote pré-post à groupe unique a été menée. MOTIV@CŒUR est composée de deux sessions d’une durée totale de 50 minutes incluant des vidéos d’interactions infirmière-patient. Dans chaque session, une introduction théorique aux IMB est suivie de situations cliniques dans lesquelles une infirmière évalue la motivation à changer et intervient selon les principes des IMB. Les situations ciblent le tabagisme, la non-adhérence au traitement médicamenteux, la sédentarité et une alimentation riche en gras et en sel. Il était suggéré aux infirmières de compléter les deux sessions de formation en ligne en moins de 20 jours. Les données sur la faisabilité, l'acceptabilité et les effets préliminaires (habiletés perçues et utilisation clinique auto-rapportée des IMB) ont été recueillies à 30 jours (± 5 jours) après la première session. Nous avons recruté 27 femmes et 4 hommes (âge moyen 37 ans ± 9) en mars 2016. Vingt-quatre des 31 participants (77%) ont terminé les deux sessions de formation en moins de 20 jours. À un mois suite à l’entrée dans l’étude, 28 des 31 participants avaient complété au moins une session. Un haut niveau d’acceptabilité a été observé vu les scores élevés quant à la qualité de l'information, la facilité d'utilisation perçue et la qualité de la plateforme MOTIV@CŒUR. Le score d'utilisation clinique auto-rapporté des interventions visant la confiance était plus élevé après les deux sessions qu’avant les sessions (P = .032). Bien que tous les scores fussent plus élevés après les deux sessions qu’au début, les autres résultats n’étaient pas statistiquement significatifs. En conclusion, l’implantation d’une plateforme de formation en ligne sur les IMB est à la fois faisable et acceptable auprès d’infirmières en soins aigus cardiovasculaires. De plus, une telle formation peut avoir un effet positif sur l'utilisation clinique d’interventions motivationnelles visant la confiance face au changement de comportement de santé.

Efectos de una intervención educativa en los conocimientos y comportamientos relacionados con la fotoprotección durante la práctica de la actividad física en los estudiantes de un colegio público de Bogotá D.C., Colombia

Introducción: La incidencia del cáncer de piel melanoma y no melanoma es un problema de salud pública a nivel mundial. El incremento en la incidencia del cáncer de piel en los últimos años se debe a múltiples factores como: cambios en los estilos de vida, el envejecimiento de la población, cambios ambientales, el desconocimiento a la exposición a la radiación ultravioleta (RUV) durante la práctica de actividad física sin elementos de fotoprotección, siendo éste último reconocido como el principal factor de riesgo. Objetivo: Evaluar los efectos de una intervención educativa en los conocimientos y comportamientos relacionados con la fotoprotección durante la práctica de la actividad física en estudiantes de un colegio público de Bogotá D.C., Colombia. Métodos: Estudio de intervención, antes y después, no controlado en 281 estudiantes de los grados noveno, décimo y once de estratos 1-3 de un colegio público de Bogotá, con seguimiento a 1, 3 y 6 meses post-intervención. Se evaluaron los conocimientos y los hábitos de fotoprotección mediante un cuestionario Cancer Awareness Measure (CAM) y el modelo Transteórico de cambio comportamental de Prochaska y Di Clemente. El estudio se realizó durante el primer semestre de 2015 con 4 sesiones educativas de 60 minutos apoyadas con material audiovisual y pedagógico, acorde a la Guía para la Comunicación Educativa en el marco el control del cáncer publicada por el Instituto Nacional de Cancerología. Resultados: Del grupo de estudiantes que participaron del estudio, el 52,3% eran hombres, el promedio de edad fue de 15,46 ± 1,2 años. El tipo de piel predominante fue la trigueña con 65,8%. La intervención educativa produjo cambios significativos en los conocimientos de foto protección, finalizado el seguimiento al sexto mes. En cuanto a la prevención los estudiantes refirieron tener conocimiento de cómo examinar su piel en el momento basal (12,5% n=35), presentándose un aumento significativo de 62,6% (n=211) al sexto mes (p<0,05). Conclusión: El estudio demostró la efectividad de la intervención educativa, evidenciando cambios significativos en los conocimientos en fotoprotección y comportamientos preventivos del cáncer de piel durante la práctica de la actividad física en estudiantes de un colegio público de Bogotá D.C., Colombia.

El videojuego League of legends y su efecto en memoria de trabajo visual y solución de problemas

El propósito de este estudio es medir los efectos que tiene el videojuego League of Legends en los procesos cognitivos de memoria de trabajo visual (MVT) y solución de problemas (SP). Para medir dichos efectos se implementó un diseño pre test-post con un grupo experimental y uno control, compuestos cada uno por siete participantes, en donde se evaluaron los procesos previamente mencionados utilizando los cubos de Corsi para MVT y las matrices del WAIS III para SP. Después de realizar los respectivos entrenamientos se encontraron resultados significativos en los diferentes momentos de aplicación. En el grupo experimental se encontraron diferencias en la variable dependiente SP, mientras que en el grupo control en MVT, pero no en la interacción entre grupos ni diferencias entre grupos, lo que sugiere un efecto de familiarización a la prueba.

Collaborative technologies, higher order thinking and self-sufficient learning: A case study of adult learners

The inclusion of online elements in learning environments is becoming commonplace in Post Compulsory Education. A variety of research into the value of such elements is available, and this study aims to add further evidence by looking specifically at the use of collaborative technologies such as online discussion forums and wikis to encourage higher order thinking and self-sufficient learning. In particular, the research examines existing pedagogical models including Salmon’s five-stage model, along with other relevant literature. A case study of adult learners in community-based learning centres forms the basis of the research, and as a result of the findings, an arrow model is suggested as a framework for online collaboration that emphasises the learner, mentions pre-course preparation and then includes three main phases of activity: post, interact and critique. This builds on Salmon’s five-stage model and has the benefit of being flexible and responsive, as well as allowing for further development beyond the model, particularly in a blended learning environment.

How should we measure online learning activity?

The proliferation of Web-based learning objects makes finding and evaluating resources a considerable hurdle for learners to overcome. While established learning analytics methods provide feedback that can aid learner evaluation of learning resources, the adequacy and reliability of these methods is questioned. Because engagement with online learning is different from other Web activity, it is important to establish pedagogically relevant measures that can aid the development of distinct, automated analysis systems. Content analysis is often used to examine online discussion in educational settings, but these instruments are rarely compared with each other which leads to uncertainty regarding their validity and reliability. In this study, participation in Massive Open Online Course (MOOC) comment forums was evaluated using four different analytical approaches: the Digital Artefacts for Learning Engagement (DiAL-e) framework, Bloom's Taxonomy, Structure of Observed Learning Outcomes (SOLO) and Community of Inquiry (CoI). Results from this study indicate that different approaches to measuring cognitive activity are closely correlated and are distinct from typical interaction measures. This suggests that computational approaches to pedagogical analysis may provide useful insights into learning processes.

Big Code Applications and Approaches

The availability of a huge amount of source code from code archives and open-source projects opens up the possibility to merge machine learning, programming languages, and software engineering research fields. This area is often referred to as Big Code where programming languages are treated instead of natural languages while different features and patterns of code can be exploited to perform many useful tasks and build supportive tools. Among all the possible applications which can be developed within the area of Big Code, the work presented in this research thesis mainly focuses on two particular tasks: the Programming Language Identification (PLI) and the Software Defect Prediction (SDP) for source codes. Programming language identification is commonly needed in program comprehension and it is usually performed directly by developers. However, when it comes at big scales, such as in widely used archives (GitHub, Software Heritage), automation of this task is desirable. To accomplish this aim, the problem is analyzed from different points of view (text and image-based learning approaches) and different models are created paying particular attention to their scalability. Software defect prediction is a fundamental step in software development for improving quality and assuring the reliability of software products. In the past, defects were searched by manual inspection or using automatic static and dynamic analyzers. Now, the automation of this task can be tackled using learning approaches that can speed up and improve related procedures. Here, two models have been built and analyzed to detect some of the commonest bugs and errors at different code granularity levels (file and method levels). Exploited data and models’ architectures are analyzed and described in detail. Quantitative and qualitative results are reported for both PLI and SDP tasks while differences and similarities concerning other related works are discussed.

Kernel machines for epilepsy diagnosis via EEG signal classification: A comparative study

Objective: We carry out a systematic assessment on a suite of kernel-based learning machines while coping with the task of epilepsy diagnosis through automatic electroencephalogram (EEG) signal classification. Methods and materials: The kernel machines investigated include the standard support vector machine (SVM), the least squares SVM, the Lagrangian SVM, the smooth SVM, the proximal SVM, and the relevance vector machine. An extensive series of experiments was conducted on publicly available data, whose clinical EEG recordings were obtained from five normal subjects and five epileptic patients. The performance levels delivered by the different kernel machines are contrasted in terms of the criteria of predictive accuracy, sensitivity to the kernel function/parameter value, and sensitivity to the type of features extracted from the signal. For this purpose, 26 values for the kernel parameter (radius) of two well-known kernel functions (namely. Gaussian and exponential radial basis functions) were considered as well as 21 types of features extracted from the EEG signal, including statistical values derived from the discrete wavelet transform, Lyapunov exponents, and combinations thereof. Results: We first quantitatively assess the impact of the choice of the wavelet basis on the quality of the features extracted. Four wavelet basis functions were considered in this study. Then, we provide the average accuracy (i.e., cross-validation error) values delivered by 252 kernel machine configurations; in particular, 40%/35% of the best-calibrated models of the standard and least squares SVMs reached 100% accuracy rate for the two kernel functions considered. Moreover, we show the sensitivity profiles exhibited by a large sample of the configurations whereby one can visually inspect their levels of sensitiveness to the type of feature and to the kernel function/parameter value. Conclusions: Overall, the results evidence that all kernel machines are competitive in terms of accuracy, with the standard and least squares SVMs prevailing more consistently. Moreover, the choice of the kernel function and parameter value as well as the choice of the feature extractor are critical decisions to be taken, albeit the choice of the wavelet family seems not to be so relevant. Also, the statistical values calculated over the Lyapunov exponents were good sources of signal representation, but not as informative as their wavelet counterparts. Finally, a typical sensitivity profile has emerged among all types of machines, involving some regions of stability separated by zones of sharp variation, with some kernel parameter values clearly associated with better accuracy rates (zones of optimality). (C) 2011 Elsevier B.V. All rights reserved.

Evaluation of Adaptive Genetic Algorithm to Environmental Modeling of Peponapis and Cucurbita

This paper presents a free software tool that supports the next-generation Mobile Communications, through the automatic generation of models of components and electronic devices based on neural networks. This tool enables the creation, training, validation and simulation of the model directly from measurements made on devices of interest, using an interface totally oriented to non-experts in neural models. The resulting model can be exported automatically to a traditional circuit simulator to test different scenarios.

Root Water Extraction under Combined Water and Osmotic Stress

Using a numerical implicit model for root water extraction by a single root in a symmetric radial flow problem, based on the Richards equation and the combined convection-dispersion equation, we investigated some aspects of the response of root water uptake to combined water and osmotic stress. The model implicitly incorporates the effect of simultaneous pressure head and osmotic head on root water uptake, and does not require additional assumptions (additive or multiplicative) to derive the combined effect of water and salt stress. Simulation results showed that relative transpiration equals relative matric flux potential, which is defined as the matric flux potential calculated with an osmotic pressure head-dependent lower bound of integration, divided by the matric flux potential at the onset of limiting hydraulic conditions. In the falling rate phase, the osmotic head near the root surface was shown to increase in time due to decreasing root water extraction rates, causing a more gradual decline of relative transpiration than with water stress alone. Results furthermore show that osmotic stress effects on uptake depend on pressure head or water content, allowing a refinement of the approach in which fixed reduction factors based on the electrical conductivity of the saturated soil solution extract are used. One of the consequences is that osmotic stress is predicted to occur in situations not predicted by the saturation extract analysis approach. It is also shown that this way of combining salinity and water as stressors yields results that are different from a purely multiplicative approach. An analytical steady state solution is presented to calculate the solute content at the root surface, and compared with the outputs of the numerical model. Using the analytical solution, a method has been developed to estimate relative transpiration as a function of system parameters, which are often already used in vadose zone models: potential transpiration rate, root length density, minimum root surface pressure head, and soil theta-h and K-h functions.

Effects of temperature-dependent viscosity variation on entropy generation, heat and fluid flow through a porous-saturated duct of rectangular cross-section

Effect of temperature-dependent viscosity on fully developed forced convection in a duct of rectangular cross-section occupied by a fluid-saturated porous medium is investigated analytically. The Darcy flow model is applied and the viscosity-temperature relation is assumed to be an inverse-linear one. The case of uniform heat flux on the walls, i.e. the H boundary condition in the terminology of Kays and Crawford, is treated. For the case of a fluid whose viscosity decreases with temperature, it is found that the effect of the variation is to increase the Nusselt number for heated walls. Having found the velocity and the temperature distribution, the second law of thermodynamics is invoked to find the local and average entropy generation rate. Expressions for the entropy generation rate, the Bejan number, the heat transfer irreversibility, and the fluid flow irreversibility are presented in terms of the Brinkman number, the Péclet number, the viscosity variation number, the dimensionless wall heat flux, and the aspect ratio (width to height ratio). These expressions let a parametric study of the problem based on which it is observed that the entropy generated due to flow in a duct of square cross-section is more than those of rectangular counterparts while increasing the aspect ratio decreases the entropy generation rate similar to what previously reported for the clear flow case.

Teaching of medical ethics: Implications for an integrated curriculum

This paper reports on an investigation into the teaching of medical ethics and related areas in the medical undergraduate course at the University of Queensland. The project was designed in the context of a major curriculum change to replace the current 6 year course by an integrated, problem-based, 4 year graduate medical course, which began in 1997. A survey of clinical students, observations of clinical teaching sessions, and interviews with clinical teachers were conducted. Data obtained have contributed to curriculum development and will provide a baseline for comparison and evaluation of the graduate course in this field. A view of integrated ethics teaching is advanced in the light of the data obtained.