Extraction and Analysis of Dynamic Conversational Networks from TV Series

Identifying and characterizing the dynamics of modern tv series subplots is an open problem. One way is to study the underlying social network of interactions between the characters. Standard dynamic network extraction methods rely on temporal integration, either over the whole considered period, or as a sequence of several time-slices. However, they turn out to be inappropriate in the case of tv series, because the scenes shown onscreen alternatively focus on parallel storylines, and do not necessarily respect a traditional chronology. In this article, we introduce Narrative Smoothing, a novel network extraction method taking advantage of the plot properties to solve some of their limitations. We apply our method to a corpus of 3 popular series, and compare it to both standard approaches. Narrative smoothing leads to more relevant observations when it comes to the characterization of the protagonists and their relationships, confirming its appropriateness to model the intertwined storylines constituting the plots.Comment: arXiv admin note: substantial text overlap with arXiv:1602.0781

A Machine Learning Model on Virtual University of Senegal's Educational Data Based on Lambda Architecture

Nowadays, a new form of learning has emerged in higher education. This is e-Learning. Lessons are taught on a Learning Content Management Systems (LCMS). These platforms generate a large variety of data at very high speed. This massive data comes from the interactions between the system and the users and between the users themselves (Learners, Tutors, Teachers, administrative Agents). Since 2013, UVS (Virtual University of Senegal), a digital university that offers distance learning through Moodle and Blackboard Collaborate platforms, has emerged. In terms of statistics, it has 29340 students, more than 400 active Tutors and 1000 courses. As a result, a large volume of data is generated on its learning platforms. In this article, we have set up an architecture allowing us to execute all types of queries on all data from platforms (historical data and real-time data) in order to set up intelligent systems capable of improving learning in this university. We then set up a machine learning model as a use case which is based on multiple regression in order to predict the most influential learning objects on the learners' final mark according to his learning activities

Solving a Berth Assignment Problem

The Berth Allocation Problem (BAP) is the problem of allocating berthing spaces and scheduling container vessels on these spaces so as to minimize total weighted time. We study a version of BAP in which containers are moved between vessels and berth space is abundant. Thus, the problem reduces to optimally assign vessels to berths. We call it the Berth Assignment Problem (BASP). We formulate it as a non standard Quadratic Assignment Problem, and we show that BASP is NP-Hard. The formulation is simplified, linearized, and valid inequalities are found. Numerical results are shown

A Quadratic Model and A Heuristic for Sizing an Hybrid Renewable Energy System

Collaboration avec le laboratoire GREAH de l'université du HavreInternational audienceAn Hybrid Renewable Energy System (HRES) may be defined as a system in which various renewable energy components (solar panels, wind turbines,...,batteries) are interconnected in such a way to satisfy, at any time, a demand of electrical energy. Since electrical power supplied by each component (taking independently) depends on different environment conditions (sun, wind), and since the demand fluctuates, the objective of such system is to be able to produce energy at any time by optimally exploiting favourable weather 2 conditions for each component, and to stock available energy (for latter use in non favourable conditions) of surproduction periods. The induced problem is to compute the optimal number of each component, minimizing installation and maintenance costs. We propose an integer quadratic programming model to solve this problem. The model is linearized and solved with a heuristic scheme. Numerical results, based on data obtained on a site in Dakar (Senegal) in which the system has to be installed, are provided

Inflammatory breast cancer: features and outcomes in a breast unit in Dakar, Senegal

Background: The aim of this study was to determine clinical features and outcomes of patients with inflammatory breast cancer (IBC) treated in our breast unit.Methods: This study was performed at Gynaecologic and Obstetric Clinic of Dakar Teaching Hospital, in which a breast unit was created since 2007. All women with diagnosis of inflammatory breast cancer in our Breast Unit between January 2010 and December 2013 were included in this study. The diagnosis of IBC was made clinically using the American Joint Committee on Cancer (AJCC) and confirmed histologically. The follow-up cut-off for this data set was December 31st, 2014. All analyses for this study were performed using SPSS software (version 20.0).Results: Between 2010 and 2013, 22 women with breast cancer who met eligibility criteria were included out of 161 patients followed for breast cancer leading to a frequency of 13.6%. The median age at diagnosis was 43.4 years (26-79 years). Mean time to diagnosis was 4 months. The mean time to recurrence was 11.2 months. This recurrence was observed in 45.5% of cases. The median overall survival was 13.3 months (CI 95% 8.576-18.526), the survival rate was 31.8%.Conclusions: This series shows a high frequency of inflammatory breast cancer. These tumours are very aggressive with a very poor prognosis

A hospital based case control study of female breast cancer risk factors in a Sub-Saharan African country

Background: Breast cancer is the most common cancer diagnosed in women worldwide with over 1.3 million new cases per year. There is a wide variation in the geographical burden of the disease with the highest incidences seen in the developed regions of the world and the lowest incidences observed in the least developed regions. The objective of this study was to understand further the risks for breast cancer in Senegalese population which can then inform public health strategies to try and reduce the burden of breast cancer.Methods: This matched case control study was conducted in 2015 in Aristide Le Dantec Teaching Hospital in Dakar. All women with pathologically confirmed primary breast cancer were considered as cases. For each case, 2 age-matched women were recruited. We collected and compared demographic factors, family history of breast cancer, socioeconomic variables, reproductive variables (age at menarche, age at first pregnancy and first live birth, parity, menopausal status, duration of breastfeeding), and exogenous hormone use up to 6 months. Odds ratios from univariate logistic regression were used to estimate the relative risk of breast cancer associated with the various factors, and their predictive effects.Results: In all, 212 women with breast cancer who were diagnosed as having breast cancer and 424 control women were involved in the study. The mean±SD age of cases and controls was 43.37±11.94 years (range 18-83 years) and 42.04±11.08 years (range 18-84 years), respectively. There were no significant differences between cases and controls with regards to marital status, parity, age at menarche, past oral contraceptive use, age at first last full-term pregnancy and history of breastfeeding. Breast cancer risk was significantly greater in women with a family history of the disease (OR 2.12, 95% confidence interval [CI] 1.35-3.31). A significant increase in breast cancer was observed among illiterate women compared to educated women (OR 1.27, CI 1.02-1.58), in premenopausal women and those without occupation.Conclusions: In this study, reproductive factors as early menarche or menopausal status were not associative to the risk of breast cancer and the early age at diagnosis and the positive history of breast cancer suggest a genetic pattern of this disease in Senegalese woman. But this fact is difficult to confirm for financial reasons

Evaluation de l’activité antioxydante des extraits des feuilles de Aphania senegalensis (Sapindaceae) et de Saba senegalensis (Apocynaceae)

Les plantes traditionnelles présentent généralement de nombreuses propriétés thérapeutiques. L’objectif de la présente étude consistait à évaluer l’activité antioxydante des extraits des feuilles de Aphania senegalensis et de Saba senegalensis par spectrophotométrie moléculaire au moyen des méthodes de piégeage des radicaux libres 2,2-diphényl-1-picryl-hydrazyle (DPPH•) et acide 2,2’-azino-bis-(3-éthylbenzothiazoline-6- sulfonique) (ABTS+•). Une extraction éthanolique des feuilles de ces deux plantes a été effectuée au Soxhlet. Les deux extraits secs, redissouts dans de l’eau, ont été fractionnés en utilisant successivement l’hexane, le dichlorométhane et l’acétate d’éthyle. Les propriétés antioxydantes des extraits et celles de leurs différentes fractions ont été évaluées à différentes concentrations : 5, 10, 25 et 150 μg/ml. Les pourcentages d’inhibition (PI) expriment l’effet antioxydant mesuré. Une activité de piégeage des deux radicaux libres a été associée aux deux extraits et à l’ensemble des fractions. Pour les tests d’inhibition de l’absorbance du radical DPPH•, les PI ont varié de (22,20±0,03)% à (91,30±0,08)%. Avec le radical ABTS+•, les PI ont varié de (54,37±0,02)% à (99,13±0,01)%. Les extraits éthanoliques des feuilles de Aphania senegalensis et de Saba senegalensis et leurs différentes fractions présentent ainsi un pouvoir antioxydant.© 2015 International Formulae Group. All rights reserved.Mots clés: Plante médicinale, ABTS (2,2’-azino-bis(3-ethylbenzothiazoline-6 sulfonic acid)), DPPH (2,2- diphényl-1-picryl-hydrazyle), spectrophotométrie moléculaireEnglish Title: Antioxidant activity of leaves extracts of Aphania senegalensis (Sapindaceae) and Saba senegalensis (Apocynaceae)English AbstractSeveral therapeutic properties are often associated with traditional plants. The antioxidant properties of Aphania senegalensis and Saba senegalensis leaf extracts were evaluated by molecular spectrophotometry and using two radical scavenging methods: 2,2-diphenyl-1-picrylhydrazyl (DPPH) assay and 2,2’-azino bis(3- ethylbenzothiazoline-6-sulfonic acid) (ABTS) assay. The leaves of each plant were extracted with ethanol  using a Soxhlet extractor apparatus. The two dry ethanolic extracts were dissolved in water then fractionated using successively hexane, dichloromethane and ethyl acetate. The antioxidant activities of the extracts and their different fractions were determined at various concentrations: 5, 10, 25 and 150 μg/ml. The antioxidant capacity was expressed as percent inhibition (PI). The extracts and their different fractions scavenged DPPH• and ABTS+• free radicals. The DPPH assay showed PI varying from 22.20±0.03% to 91.30±0.08%. With the ABTS+• radical, the PI varied from 54.37±0.02% to 99.13±0.01%. The ethanolic extracts of Aphania senegalensis and Saba senegalensis as well as their fractions showed antioxidant capacities.© 2015 International Formulae Group. All rights reserved.Keywords: Medicinal plant, ABTS (2,2’-azino-bis(3-ethylbenzothiazoline-6 sulfonic acid)), DPPH (2,2-diphenyl-1-picrylhydrazyl), molecular spectrophotometr