Abstract

Abstract
Como espacios de aprendizaje y fruición, los museos están constantemente adaptando sus contenidos y acciones para hacer frente a la dinámica de las transformaciones sociales. La introducción de nuevas tecnologías digitales en los espacios de exhibición permitió a los equipos del museo comunicar sus colecciones e interactuar con sus visitantes de formas muy diferenciadas. El fenómeno de la gamificación y sus estrategias implícitas plantean la posibilidad de mejorar el compromiso entre personas, objetos e información asociada, y puede permitir a los museos establecer nuevos enfoques y resultados. El trabajo a presentar forma parte de un programa de investigación de doctorado centrado en el desarrollo de experiencias gamificadas y sus implicaciones en el proceso infocomunicacional y de aprendizaje no formal en museos, específicamente aplicado a un grupo de visitantes entre 8 a 12 años. El objetivo es compartir reflexiones y consideraciones sobre el despliegue de un prototipo digital gamificado en un museo en Portugal, con el fin de mejorar el conocimiento sobre las colecciones y la conciencia sobre el trabajo entre bastidores invisible, complejo e interdisciplinario rico de los equipos del museo, que se ocupan de la curaduría y gestión de riesgos para asegurar su preservación, así como su fruición incluyente. Basándonos en literatura relevante y en marcos de gamificación identificados, nos enfocamos en la descripción de posibles soluciones gamificadas con la yuxtaposición de objetivos de aprendizaje y posibles resultados. Como parte de un enfoque exploratorio, pretendemos enumerar las mejores prácticas para cumplir con los requisitos educativos iniciales, así como proceder con posibles soluciones para responder a ellos. También pretendemos fusionar estas reflexiones con inferencias plausibles de motivaciones intrínsecas y extrínsecas en grupos y comprender cómo pueden influir en las acciones deseadas y en toda la experiencia de aprendizaje gamificada.  

Abstract

Abstract
Due to the rising of both economic and environmental concerns in the energy sector, each subdivision of the community is investigating new solutions to overcome this critical issue. For this reason, electric vehicles (EVs) have gained more significance in the transportation sector owing to their efficient and clean operation chance. These improvements, however, bring new challenges such as installation costs, infrastructure renovation, and loading of the existing power system. Here, optimal sizing and siting of EV charging stations (CSs) are examined in a mixed-integer linear programming framework with the aim of minimizing the number of EVCSs in the distribution system (which in turn means to minimize CS-related investment while satisfying EV owners' needs) while satisfying constraints. The proposed optimization model considers EVCS types with different charging rate capabilities to provide opportunities for demand-side management. Moreover, the model takes the actual behaviour of the battery charging pattern into account by using real measured EV charging data together with the consideration of an actual distribution system belonging to a region in Turkey. Lastly, a bunch of case studies is conducted in order to validate the accuracy and effectiveness of the devised model.

Abstract
Late diagnoses of patients affected by pulmonary artery hypertension (PH) have a poor outcome. This observation has led to a call for earlier, non-invasive PH detection. Cardiac auscultation offers a non-invasive and cost-effective alternative to both right heart catheterization and doppler analysis in analysis of PH. We propose to detect PH via analysis of digital heart sound recordings with over-parameterized deep neural networks. In contrast with previous approaches in the literature, we assess the impact of a pre-processing step aiming to separate S2 sound into the aortic (A2) and pulmonary (P2) components. We obtain an area under the ROC curve of. 95, improving over our adaptation of a state-of-the-art Gaussian mixture model PH detector by +.17. Post-hoc explanations and analysis show that the availability of separated A2 and P2 components contributes significantly to prediction. Analysis of stethoscope heart sound recordings with deep networks is an effective, low-cost and non-invasive solution for the detection of pulmonary hypertension.

Abstract
Palatal consonants in Portuguese are considered complex or marked segments because they are inherently heavy and restricted in terms of their distribution, in relation to other consonants. Moreover, they appear to display differences between themselves, as first language acquisition and creoles' adaptation suggest that /L/ is more complex than /n/. The arguments for complexity are endorsed by some qualitative studies but are still lacking quantitative support. This paper aims at analyzing the phonological restrictiveness of these consonants by comparing their actual frequency in several different corpora, reporting both lexical entries and usage in discourse. In addition to their context-free frequency, we control for their word position and phonetic adjacency. We find that palatals are less frequent than other consonants. However, relative to each other, they do not display proportional lexical and usage frequencies. These results shed new light not only on the representation of /n/ and /L/ but also on the relation between frequency and markedness in language studies.