Use of drama techniques as a methodology to teach english in infant education by teachers in Catalonia

L’aprenentatge de la llengua anglesa com a llengua estrangera és una oportunitat que cada vegada més escoles de Catalunya presenten a l’etapa d’educació Infantil. La metodologia utilitzada per introduir aquesta llengua és variada en cada cas. Aquesta recerca es centra en l’estudi de l’ús de tècniques dramàtiques com a metodologia per ensenyar anglès a infantil. A partir d’un qüestionari contestat per 129 professors d’anglès de Catalunya s’ha analitzat la percepció que tenen sobre les tècniques dramàtiques i la seva utilització. Els resultats mostren una manca de coneixement general sobre la metodologia.

Multidetector-row computed tomography in the preoperative diagnosis of intestinal complications caused by clinically unsuspected ingested dietary foreign bodies: a case series emphasizing the use of volume rendering techniques

Objective The present study was aimed at describing a case series where a preoperative diagnosis of intestinal complications secondary to accidentally ingested dietary foreign bodies was made by multidetector-row computed tomography (MDCT), with emphasis on complementary findings yielded by volume rendering techniques (VRT) and curved multiplanar reconstructions (MPR). Materials and Methods The authors retrospectively assessed five patients with surgically confirmed intestinal complications (perforation and /or obstruction) secondary to unsuspected ingested dietary foreign bodies, consecutively assisted in their institution between 2010 and 2012. Demographic, clinical, laboratory and radiological data were analyzed. VRT and curved MPR were subsequently performed. Results Preoperative diagnosis of intestinal complications was originally performed in all cases. In one case the presence of a foreign body was not initially identified as the causal factor, and the use of complementary techniques facilitated its retrospective identification. In all cases these tools allowed a better depiction of the entire foreign bodies on a single image section, contributing to the assessment of their morphology. Conclusion Although the use of complementary techniques has not had a direct impact on diagnostic performance in most cases of this series, they may provide a better depiction of foreign bodies' morphology on a single image section.

Le reflux gastro-oesophagien de l'enfant: indications chirurgicales, techniques et suivi.

Contexte: Présent sous forme physiologique chez environ 60% des nourrissons normaux de moins de quatre mois, le reflux gastro-oesophagien (RGO) n'est symptomatique que chez 10% d'entre eux. Il est également plus fréquent chez les enfants atteints de troubles neurologiques quelque soit leur âge. Non traité, il peut avoir des conséquences graves (oesophagite, sténose peptique, endobrachyoesophage (Barrett) puis adénocarcinome de l'oesophage). Il s'agit donc d'un problème qu'il faut savoir détecter et traiter précocement. Les signes et symptômes du RGO sont multiples et varient en fonction de l'âge. Ils ne se limitent pas au seul vomissement. Le traitement initial du RGO chez l'enfant est médical. En cas d'échec de celui-ci ou dans certaines indications (comme les RGO récidivants, les malformations congénitales, les anomalies morphologiques ou les pathologies neurologiques) un traitement chirurgical est nécessaire. L'évolution des traitements conservateurs et des techniques chirurgicales lors de ces dernières années en font un bon sujet pour une étude rétrospective. Objectif: Le but de cette étude est de mettre en évidence dans une population d'enfants ayant bénéficié d'une cure chirurgicale anti-reflux la fréquence relative des symptômes selon la pathologie initiale de l'enfant, puis de préciser le choix de traitement et sa durée. Nous analyserons également les risques d'échec qui s'y rapportent. Ces conclusions devraient nous permettre de proposer un algorithme décisionnel de prise en charge du RGO de l'enfant en pré et post-opératoire. Méthodologie: Étude rétrospective sur 9 ans se basant sur les dossiers médicaux-chirurgicaux de 132 enfants opérés d'un reflux gastro-oesophagien dans le Service de Chirurgie Pédiatrique du Centre Hospitalier Universitaire Vaudois (CHUV) par le Professeur Olivier Reinberg et son équipe entre le 1er janvier 2003 et le 31 décembre 2012. Résultats: Sur les 132 enfants, 93 ont bénéficié d'une fundoplicature selon Toupet, 34 selon Nissen et 5 selon Dor. 57% des enfants présentant un déficit neurologique ont été opérés selon la technique de Nissen contre 7% des enfants "sains". Les taux de démontage et de récidive sont respectivement 5.4% et 3.5 % pour la technique selon Toupet et 2.9% et 0% pour la technique de Nissen. Le taux de démontage global de la fundoplicature est de 4.6% (N=6) Conclusions: La fundoplicature est une méthode de choix pour les enfants chez qui tous les autres traitements ont échoué ou chez qui la présence concomitante du RGO et des comorbidités est délétère à une croissance harmonieuse. Grâce à la chirurgie, la qualité de vie d'au moins 95% des enfants est grandement améliorée après la disparition de symptômes quotidiens et qui peuvent donner lieu à des complications graves.

Opinion Mining

In this thesis we study the field of opinion mining by giving a comprehensive review of the available research that has been done in this topic. Also using this available knowledge we present a case study of a multilevel opinion mining system for a student organization's sales management system. We describe the field of opinion mining by discussing its historical roots, its motivations and applications as well as the different scientific approaches that have been used to solve this challenging problem of mining opinions. To deal with this huge subfield of natural language processing, we first give an abstraction of the problem of opinion mining and describe the theoretical frameworks that are available for dealing with appraisal language. Then we discuss the relation between opinion mining and computational linguistics which is a crucial pre-processing step for the accuracy of the subsequent steps of opinion mining. The second part of our thesis deals with the semantics of opinions where we describe the different ways used to collect lists of opinion words as well as the methods and techniques available for extracting knowledge from opinions present in unstructured textual data. In the part about collecting lists of opinion words we describe manual, semi manual and automatic ways to do so and give a review of the available lists that are used as gold standards in opinion mining research. For the methods and techniques of opinion mining we divide the task into three levels that are the document, sentence and feature level. The techniques that are presented in the document and sentence level are divided into supervised and unsupervised approaches that are used to determine the subjectivity and polarity of texts and sentences at these levels of analysis. At the feature level we give a description of the techniques available for finding the opinion targets, the polarity of the opinions about these opinion targets and the opinion holders. Also at the feature level we discuss the various ways to summarize and visualize the results of this level of analysis. In the third part of our thesis we present a case study of a sales management system that uses free form text and that can benefit from an opinion mining system. Using the knowledge gathered in the review of this field we provide a theoretical multi level opinion mining system (MLOM) that can perform most of the tasks needed from an opinion mining system. Based on the previous research we give some hints that many of the laborious market research tasks that are done by the sales force, which uses this sales management system, can improve their insight about their partners and by that increase the quality of their sales services and their overall results.

Unsupervised active regions for multiresolution image segmentation

An unsupervised approach to image segmentation which fuses region and boundary information is presented. The proposed approach takes advantage of the combined use of 3 different strategies: the guidance of seed placement, the control of decision criterion, and the boundary refinement. The new algorithm uses the boundary information to initialize a set of active regions which compete for the pixels in order to segment the whole image. The method is implemented on a multiresolution representation which ensures noise robustness as well as computation efficiency. The accuracy of the segmentation results has been proven through an objective comparative evaluation of the method

Modeling and Classifying Breast Tissue Density in Mammograms

We present a new approach to model and classify breast parenchymal tissue. Given a mammogram, first, we will discover the distribution of the different tissue densities in an unsupervised manner, and second, we will use this tissue distribution to perform the classification. We achieve this using a classifier based on local descriptors and probabilistic Latent Semantic Analysis (pLSA), a generative model from the statistical text literature. We studied the influence of different descriptors like texture and SIFT features at the classification stage showing that textons outperform SIFT in all cases. Moreover we demonstrate that pLSA automatically extracts meaningful latent aspects generating a compact tissue representation based on their densities, useful for discriminating on mammogram classification. We show the results of tissue classification over the MIAS and DDSM datasets. We compare our method with approaches that classified these same datasets showing a better performance of our proposal

The Pelosi-type versus the modified Misgav-Ladach: a randomized trial of two surgical techniques for cesarean section

Cesarean section (CS) is now the most common major surgical procedure performed on women worldwide. A quarter of deliveries in Spain are performed by cesarean section. With the increasing rates of the operation, there is the need to use evidence-based techniques to optimize outcomes and minimize complications. The goal of this study is to employ a well-designed randomized controlled trial to evaluate the intraoperative blood loss of two surgical techniques for cesarean section, the Pelosi-type and the modified Misgav-Ladach. The trial will take place in Hospital Universitari de Girona Dr. Josep Trueta From 2014 to 2015, 512 pregnant women undergoing delivery by their first lower segment cesarean section in this center will be selected through a consecutive nonprobability sampling. We will collect the main obstetrical characteristics, intraoperative outcomes, short-term outcomes for the baby and postoperative outcomes. We will evaluate the intraoperative blood loss by comparing the changes in hemoglobin levels, pre and postoperatively. Patients will be followed during the postoperative period and in a two-week postoperative appointment. We will analyze the continuous variables, such as the differences in hemoglobin levels, using an unpaired two-sided Student’s t-test, while for the categorical variables Fischer’s exact test will be used

Unsupervised visual object categorization

The number of digital images has been increasing exponentially in the last few years. People have problems managing their image collections and finding a specific image. An automatic image categorization system could help them to manage images and find specific images. In this thesis, an unsupervised visual object categorization system was implemented to categorize a set of unknown images. The system is unsupervised, and hence, it does not need known images to train the system which needs to be manually obtained. Therefore, the number of possible categories and images can be huge. The system implemented in the thesis extracts local features from the images. These local features are used to build a codebook. The local features and the codebook are then used to generate a feature vector for an image. Images are categorized based on the feature vectors. The system is able to categorize any given set of images based on the visual appearance of the images. Images that have similar image regions are grouped together in the same category. Thus, for example, images which contain cars are assigned to the same cluster. The unsupervised visual object categorization system can be used in many situations, e.g., in an Internet search engine. The system can categorize images for a user, and the user can then easily find a specific type of image.

Overvoltage Mitigation Techniques in Wind Power Generators

Advancements in power electronic semiconductor switching devices have lead to significantly faster switching times. In motor and generator applications, the fast switching times of pulse width modulated (PWM) inverters lead to overvoltages caused by voltage reflections with shorter and shorter cables. These excessive overvoltages may lead to a failure of the electrical machine in a matter of months. In this thesis, the causes behind the overvoltage phenomenon as well as its different mitigation techniques are studied. The most suitable techniques for mitigating the overvoltage phenomenon in wind power generator applications are chosen based on both simulations and actual measurements performed on a prototype. An RC filter at the terminals of the electrical machine and an inverter output filter designed to reduce the rise and fall times of voltage pulses are presented as a solution to the overvoltage problem. The performance and losses of both filter types are analysed.