Tweet Contextualization Based on Wikipedia and Dbpedia

National audienceBound to 140 characters, tweets are short and not written maintaining formal grammar and proper spelling. These spelling variations increase the likelihood of vocabulary mismatch and make them difficult to understand without context. This paper falls under the tweet contextualization task that aims at providing, automatically, a summary that explains a given tweet, allowing a reader to understand it. We propose different tweet expansion approaches based on Wikipeda and Dbpedia as external knowledge sources. These proposed approaches are divided into two steps. The first step consists in generating the candidate terms for a given tweet, while the second one consists in ranking and selecting these candidate terms using asimilarity measure. The effectiveness of our methods is proved through an experimental study conducted on the INEX 2014 collection

Disjonction symphysaire après un accouchement par voie basse dystocique: à propos d’un cas

La disjonction symphysaire est une affection rare, qui se définie par un élargissement au niveau de  l'articulation inter-symphysaire estimé supérieur à 10 mm. Cette affection nécessite une prise en charge spécialisée en cas de douleurs sévères et invalidantes. Nous rapportant le cas d'une patiente présentant des douleurs pelviennes intense avec impotence du MI gauche à J2 d'un accouchement dystocique, l'examen clinique a objectivé une douleur exquise à la palpation de la symphyse pubienne. Le diagnostic a été confirmé par une radiologie du bassin de face objectivant un élargissement de la symphyse pubienne de 15 mm, la prise en charge thérapeutique a consisté en une mise sous décharge et anticoagulation préventive avec un  traitement antalgique à base de paracétamol et AINS. L'évolution était favorable. A travers notre cas, nous insisterons sur les caractéristiques de cette pathologie notamment pronostic, ce qui permettra au praticien de comprendre l'intérêt du diagnostic et prise en charge précoce de cette entité qu'elle évoquer devant toute douleurs pelviennes survenant au cours de la grossesse ou en post partum.Key words: Disjonction symphysaire, accouchement dystocique, rupture uterin

Interactions entre virus géants, virophages et bactéries au sein de l'amibe : conséquences sur leur isolement

Les virus sont présents dans tous les écosystèmes, et sont les entités les plus abondantes dans le milieu marin. Bien que nous associons systématiquement virus aux maladies, la plupart d'entre eux coexistent cependant en équilibre avec leur hôte. Les virus sont associés à tous les règnes de la vie, même les virus qui affectent d'autres virus(virophages). La définition aujourd'hui d'un virus chez les virologues, c'est qu'un virus est un parasite génétique qui utilise des systèmes cellulaires pour sa propre réplication. Les hôtes les plus couramment utilisés par les virus que nous avons étudiés sont principalement des protozoaires. Ainsi, les Amoebozoa font l'objet de nombreuses études et sont utilisés pour isoler de nouvelles espèces intracellulaires( virus, bactéries). Ces espèces ont évolué de manière à résister aux effets consécutifs à la phagocytose ou à l'ingestion dans des vacuoles, et restent viable dans le cytoplasme de l'amibe, et ont le potentiel de se multiplier dans les parasites. Dans cette étude, nous avons dans un premier temps étudier les diverses interactions existantes entre virus Acanthamoeba polypaghaga Mimivirus(APMV) et des bactéries au sein de l'amibe. Pour cela, nous avons choisi un système original basé sur la co-culture de l'APMV, soit seul ou en combinaison avec deux autres microorganismes isolés individuellement à partir de l'amibe. Il s'agit d'une bactérie intracellulaire stricte(BABL1) et le virophage de APMV (Sputnik). Cela nous a permis de mettre en évidence, d'une part la capacité du virophage à moduler la virulence d'APMV tout en révélant, d'autre part, la bataille qui a eu lieu entre eux au cours de l'infection de l'hôte. dans un deuxième temps, nous avons examiné l'activité virucide des biocides couramment utilisés en pratique clinique pour la désinfection des équipements hospitaliers. APMV et Marseillevirus montrent une grande résitance aux biocides chimiques, en particulier l'alcool. Seule la température de 75°C et le glutaraldéhyde ont réussi à réduire les titres d'APMV et Marseillevirus à des niveaux indétectables. Après dessiccation ou exposition aux rayonnements ultraviolets, APMV et marseillevirus ont démontré leur stabilité durable. Précédent le pré-traitement des échantillons de l'environnement par l'éthanol à 70°C, a permis la disparition des contaminants bactériens sans réduire la charge virale, permettant leur isolement sur amibe, sans avoir besoin d'utiliser des antibiotiques, qui peuvent avoir un effet délétère su les amibes.In this study, we first examined the various interactions taking place between the virus Acanthamoeba polyphaga Mimivirus (APMV) and bacteria within the amoeba. We chose an original system based on a co-culture of APMV either alone or in combination with two other organisms isolated from amoeba, i.e a strict intracellular bacterium (BABL1) and the virophage of APMV (Sputnik). This allowed us to highlight, on the one hand, the possibility to modulate the virulence of APMV while revealing, on the other hand, the battle which occurs between them during the infection of the host. We then examined the virucidal activity of biocides commonly used in clinical practice for the disinfection of hospital equipment. APMV and Marseillevirus show high resistance to chemical biocides, especially to alcohol. Only a temperature of 75°C or glutaraldehyde were able to reduce APMV and Marseillevirus titres to undetectable levels. Whether dried or under ultraviolet, APMV and Marseillevirus demonstrated their lasting stability. Previous pre-treatment of environmental samples by ethanol 70° allowed disappearance of bacterial contaminating bacteria without reducing giant virus load allowing their isolation on amoeba without need the use of antibiotic that may have a deleterious effect on amoebae

Short Query Expansion for Microblog Retrieval

AbstractTwitter has emerged as the most popular among microblogging service providers. The content provided in Twitter is large, diverse, and huge in quantity. Given the increasing amount of information available through such microblogging sites, it would be interesting to be able to retrieve useful tweets in response to a given information need. However, Twitter's subscribers often have many difficulties dealing with its content. Especially in searching for tweets that satisfy their information needs. This problem becomes more complicated when the user-defined queries are short and precise. This paper deals with short and precise queries problem for micoblog retrieval. We expand short queries by semantically related terms extracted from Wikipedia, DBpedia and unstructured texts using textmining techniques. Experiments on TREC 2011 microblog collection show significant improvement in the retrieval performance

Exploring and Strengthening Energy Concepts through Computer Simulation in Educational Institutions

In a world increasingly dependent on energy, understanding its fundamental concepts becomes paramount. As we navigate complex global challenges related to sustainability and innovation, educating the younger generation about energy is crucial. Computer simulation learning has emerged as a pivotal tool in optimizing teaching methodologies, particularly when it comes to comprehending and mastering energy-related concepts. This innovative approach provides an immersive experience, allowing students to practically and interactively explore the intricate principles of energy. Focused on the industrial technology associated with energy, this study delves into the application of computer simulation to enhance the understanding of adolescents aged 13 to 16. A sample of students, spanning three classes, underwent electrical circuit manipulation tests utilizing simulation software. Analysis of the results, employing Pearson’s correlation coefficient, revealed a significant enhancement in the comprehension of energy concepts through simulation-based learning. By enabling students to visualize and experiment with various energy-related scenarios

PIGMMaLIOn: a Partial Incremental Gaussian Mixture Model with a Low I/O Design

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Adapting Gaussian Mixture Model Training to Embedded/Edge Devices: A Low I/O, Deadline-Aware and Energy Efficient Design

International audienceThis work focuses on the Gaussian Mixture Model (GMM), a machine learning model used for density estimation and cluster analysis in healthcare, networking, etc. The Expectation-Maximization (EM) algorithm is commonly used to train GMMs. One of the main challenges facing this algorithm when running on embedded systems is the crippling memory constraints. In fact, EM requires several scans of the dataset and we observed that when the dataset cannot fully reside in the main memory, its execution is dramatically slowed down by I/O movements. In this paper, we present an optimization of the EM algorithm for GMMs that reduces the number of I/O operations thanks to two main contributions: (1) A divide-and-conquer strategy that divides the dataset into chunks, learns the GMM separately on each chunk and combines the results incrementally. By doing so, we prevent data from being swapped several times during the learning process. (2) Restricting the training on a subset of data whose volume is inferred online using data properties while producing good accuracy. On average, our results show a 63% improvement in overall execution time with comparable accuracy. We also adapted GMM learning to run in a limited time budget while hitting a good trade-off between execution time and energy consumption. This solution succeeded in meeting the fixed deadline in 100% of the cases and in reducing the energy consumption by up to 68.77%

Wikipedia-based Semantic Approach for Tweet Contextualization

International audienceThe tweet contextualization task aims at providing an automatic readable summary explaining a given tweet. As tweets are very short documents, bound to 140 characters, and not always written maintaining proper spellings, there is indeed a need for such a task. This article describes a semantic tweet expansion approach for the tweet con-textualization task based on Wikipedia as an external knowledge source. This approach consists in two major phases, namely: the first is the generation of the candidate terms, from Wikipedia. While the second is the selection of the most-related terms. To achieve this latter, we propose a semantic relatedness measure based on the Explicit Semantic Analysis and association rules mining. The e↵ectiveness of our approach is proved through an experimental study conducted on the INEX 2014 collection. Our results have outperformed of the runs issued from INEX 2014

Wikipedia-based Semantic Approach for Tweet Contextualization

International audienceThe tweet contextualization task aims at providing an automatic readable summary explaining a given tweet. As tweets are very short documents, bound to 140 characters, and not always written maintaining proper spellings, there is indeed a need for such a task. This article describes a semantic tweet expansion approach for the tweet con-textualization task based on Wikipedia as an external knowledge source. This approach consists in two major phases, namely: the first is the generation of the candidate terms, from Wikipedia. While the second is the selection of the most-related terms. To achieve this latter, we propose a semantic relatedness measure based on the Explicit Semantic Analysis and association rules mining. The e↵ectiveness of our approach is proved through an experimental study conducted on the INEX 2014 collection. Our results have outperformed of the runs issued from INEX 2014

Statistical and Semantic Approaches for Tweet Contextualization

International audienceMicroblogging sites, like Twitter, have emerged as a popular platform for expressing opinions. Bound to 140 characters, Twitter's publications (tweets) are very short and not always written maintaining formal grammar and proper spelling. The spelling variations increase the likelihood of vocabulary mismatch and make the tweets dicult to understand without some kind of context. The task of tweet contextualization was organized around these issues. It aims to provide an automatic readable context explaining a given tweet, in order to help the reader understand this latter. In this paper, we describe statistical and semantic approaches for the tweet contextualization task. While the statistical one is based on association rules mining, the semantic one uses Wikipedia as an external knowledge source. The e↵ectiveness of our approaches is proved through an experimental study conducted on the INEX 2013 collection