Reduced bio-efficacy of permethrin EC impregnated bednets against an Anopheles gambiae strain with oxidase-based pyrethroid tolerance

BACKGROUND: Insecticide-treated nets (ITNs) are an integral component of malaria control programmes in Africa. How much pyrethroid resistance in malaria vectors will impact on the efficacy of ITNs is controversial. The purpose of this study was to evaluate knockdown and killing effects of ITNs on a metabolic-based resistant or tolerant malaria vector strain. METHODS: Bio-efficacy of 500 mg/m(2 )permethrin EC treated bednets was assessed on the OCEAC laboratory (OC-Lab) strain of Anopheles gambiae s.s.. This strain is resistant to DDT and tolerant to pyrethroids, with elevated mixed function oxidases. The Kisumu reference susceptible strain of A. gambiae s.s. was used as control. Nets were impregnated in February 1998 and used by households of the Ebogo village. Then they were collected monthly over six months for Bio-assays (WHO cone test). Knockdown and mortality rates were compared between the OC-Lab and the Kisumu strains, by means of the Mantel-Haenszel chi-square test. RESULTS: During the whole trial, permethrin EC knockdown rates were impressive (mostly higher than 97%). No significant difference was observed between the two strains. However, the mortality rates were significantly decreased in the OC-Lab strain (40–80%) compared with that of the Kisumu strain (75–100%). The decrease of killing effect on the OC-Lab strain was attributed to permethrin EC tolerance, due to the high oxidase metabolic activity. CONCLUSION: These data suggested an impact of pyrethroid tolerance on the residual activity of ITNs. More attention should be given to early detection of resistance using biochemical or molecular assays for better resistance management

CAPRE: A New Methodology for Product Recommendation Based on Customer Actionability and Profitability

International audienceRecommender systems can apply knowledge discovery techniques to the problem of making product recommendations. This aims to establish a customer loyalty strategy and thus to optimize the customer life time value. In this paper we propose CAPRE, a data-mining based methodology for recommender systems based on the analysis of turnover for customers of specific products. Contrary to classical recommender systems, CAPRE does not aspire to predict a customer's behavior but to influence that behavior. By measuring the actionability and profitability of customers, we have the ability to focus on customers that can afford to spend larger sums of money in the target business. CAPRE aggregates rules to extract characteristic purchasing behaviors, and then analyzes the counter-examples to detect the most actionable and profitable customers. We measure the effectiveness of CAPRE by performing a cross-validation on the MovieLens benchmark. The methodology is applied to over 10,000 individual customers and 100,000 products for the customer relationship management of VM Matériaux company, thus assisting the salespersons' objective to increase the customer value

Semantics-based classification of rule interestingness measures

Assessing rules with interestingness measures is the cornerstone of successful applications of association rule discovery. However, as numerous measures may be found in the literature, choosing the measures to be applied for a given application is a difficult task. In this chapter, the authors present a novel and useful classification of interestingness measures according to three criteria: the subject, the scope, and the nature of the measure. These criteria seem essential to grasp the meaning of the measures, and therefore to help the user to choose the ones (s)he wants to apply. Moreover, the classification allows one to compare the rules to closely related concepts such as similarities, implications, and equivalences. Finally, the classification shows that some interesting combinations of the criteria are not satisfied by any index

Interactive visual exploration of association rules with rule-focusing methodology

International audienceOn account of the enormous amounts of rules that can be produced by data mining algorithms, knowledge post-processing is a difficult stage in an association rule discovery process. In order to find relevant knowledge for decision making, the user (a decision maker specialized in the data studied) needs to rummage through the rules. To assist him/her in this task, we here propose the rule-focusing methodology, an interactive methodology for the visual post-processing of association rules. It allows the user to explore large sets of rules freely by focusing his/her attention on limited subsets. This new approach relies on rule interestingness measures, on a visual representation, and on interactive navigation among the rules. We have implemented the rule-focusing methodology in a prototype system called ARVis. It exploits the user's focus to guide the generation of the rules by means of a specific constraint-based rule-mining algorithm

Post-Processing of Discovered Association Rules Using Ontologies

In Data Mining, the usefulness of association rules is strongly limited by the huge amount of delivered rules. In this paper we propose a new approach to prune and filter discovered rules. Using Domain Ontologies, we strengthen the integration of user knowledge in the post-processing task. Furthermore, an interactive and iterative framework is designed to assist the user along the analyzing task. On the one hand, we represent user domain knowledge using a Domain Ontology over database. On the other hand, a novel technique is suggested to prune and to filter discovered rules. The proposed framework was applied successfully over the client database provided by Nantes Habitat

Une méthodologie de recommandations produits fondée sur l'actionnabilité et l'intérêt économique des clients

National audienceDans un contexte économique difficile, la fidélisation des clients figure au premier rang des préoccupations des entreprises. En effet, selon le Gartner, fidéliser des clients existants coûterait beaucoup moins cher que prospecter de nouveaux clients. Pour y parvenir, les entreprises optimisent la marge et le cycle de vie des clients en développant une relation personnalisée aboutissant à demeilleures recommandations. Dans cet article, nous proposons une méthodologie pour les systèmes de recommandations fondée sur l'analyse des chiffres d'affaires des clients sur des familles de produits. Plus précisément, la méthodologie consiste à extraire des comportements de référence sous la forme de règles d'association et à en évaluer l'intérêt économique et l'actionnabilité. Les recommandations sont réalisées en ciblant les contre-exemples les plus actionnables sur les règles les plus rentables.Notreméthodologie est appliquée sur 12 000 clients et 100 000 produits de VMMatériaux afin d'orienter les commerciaux sur les possibilités d'accroissement de la valeur client

Découverte interactive de règles d'association via une interface visuelle

En nous appuyant sur des hypothèses majoritairement empruntées à des travaux sur les systèmes anthropocentrés d'aide à la décision, nous décrivons dans cet article un environnement interactif de fouille de règles d'association dans lequel l'utilisateur pilote le processus, en jouant le rôle d'une heuristique dans un environnement de recherche complexe. Afin de permettre à la fois une représentation visuelle accessible et une instanciation aisée des outils d'interactivité le modèle choisi est ici un graphe en niveaux - les niveaux étant associés aux cardinaux des sous-ensembles d'attributs des prémisses. Le processus a été déployé dans un logiciel prototype dont l'analyse des résultats ouvre de nouvelles perspectives sur l'analyse comportementale d'un utilisateur en situation de fouille

Proceedings of the 2nd international conference on insect pests in the urban environment

Larval susceptibility to organophosphates (OP), carbamates (CARB) and pyrethroids (PYR) was investigated in #Culex quinquefasciatus$ from Côte d'Ivoire and Burkina Faso. A total of 33 populations collected in 25 cities were tested. The resistance of these natural field populations was compared to a susceptible reference strain under the same conditions. In Côte d'Ivoire, populations showed a heterogeneous response to OP and CARB. A range of 40 %-98 % of larvae had a low resistance level to both chlorpyrifos (2-8x) and propoxur (1-4x). The remaining 2 % to 60 % of larvae displayed a high level of cross-resistance between chlorpyrifos (15-30x) and propoxur (>700x). Biochemical studies showed that low level resistance to OP was due to A2-B2 overproduced esterases and that cross-resistance to OP and CARB was conferred by an insensitive acetylcholinesterase (AChE). This AChE provided a lower resistance to temephos (10x). In Burkina Faso, populations were slightly resistant to OP (1-3x) and not to CARB. The esterases A2-B2 were only present at 50 % frequency. In contrast, PYR-resistance was similar between the two countries. All populations were resistant to either permethrin (20-80x) and deltamethrin (15-40x). Bioassays using piperonyl butoxide (PB) and biochemical studies showed that PYR-resistance involved increased metabolism by mixed function oxidases. Knowing that synergism of PB did not completely suppress resistance and that adults did not show a knockdown effect with high permethrin concentrations, it is likely that PYR-resistance was also due to a Kdr gene. (Résumé d'auteur

An Overview of Interaction Techniques and 3D Representations for Data Mining

International audienceAn Overview of Interaction Techniques and 3D Representations for Data Minin