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Abdelhamid I.,Center Hospitalier National | Lasram K.,Institute Pasteur Of Tunis | Meiloud G.,British Petroleum | Ben Halim N.,Institute Pasteur Of Tunis | And 4 more authors.
Primary Care Diabetes | Year: 2014

Aims Many genetic association studies reported the contribution of KCNJ11 gene to type 2 diabetes susceptibility in different populations. We aimed to evaluate the association between E23K variant of KCNJ11 and type 2 diabetes in the Mauritanian population. Materials and methods We performed a case-control association study including 135 type 2 diabetes Mauritanian patients and 135 controls. Genotyping for the E23K variant was performed using a TaqMan allelic discrimination assay. Results We found significant association between KCNJ11 E23K variant and type 2 diabetes (Global model, OR = 2.08, 95% CI = 1.09-3.97, p = 0.026). In the Moor ethnic group, E23K was also associated with type 2 diabetes in the general model (OR = 2.08, 95% CI = 1.09-3.97, p = 0.026) and under the dominant model (OR = 2.49, 95% CI = 1.12-5.55, p = 0.026). In the Mauritanians of African descent, KK genotype was not found. Besides, E23K variant was not associated with type 2 diabetes (OR = 0.69, 95% CI = 0.04-11.32, p = 0.793). Conclusions Our results revealed the risk of type 2 diabetes conferred by KCNJ11 E23K gene variant in the Mauritanian population. © 2013 Primary Care Diabetes Europe. Source


Paeth H.,University of Wurzburg | Hall N.M.,Toulouse 1 University Capitole | Gaertner M.A.,University of Castilla - La Mancha | Alonso M.D.,University of Castilla - La Mancha | And 13 more authors.
Atmospheric Science Letters | Year: 2011

We review the recent progress in dynamical and statistical downscaling approaches for west African precipitation and perform a regional climate model (RCM) intercomparison using the novel multi-model RCM data set from the Ensembles-based Predictions of Climate Changes and Their Impacts (ENSEMBLES) and African Monsoon Multidisciplinary Analyses (AMMA) projects. Present RCMs have distinct systematic errors in terms of west African precipitation varying in amplitude and pattern across models. This is also reflected in a relatively large spread in projected future precipitation trends. Altogether, the ENSEMBLES RCMs indicate a prevailing drying tendency in sub-Saharan Africa. Statistical post-processing of simulated precipitation is a promising tool to reduce systematic model errors before application in impact studies. Copyright © 2011 Royal Meteorological Society. Source


Diallo O.,University of Beira Interior | Rodrigues J.J.P.C.,University of Beira Interior | Sene M.,Ucad | Lloret J.,Polytechnic University of Valencia
Journal of Network and Computer Applications | Year: 2014

Wireless sensor networks (WSNs) have been the focus of many research works. Nowadays, because of the time-critical tasks of several WSN applications, one of the new challenges faced by WSNs is handling real-time storage and querying the data they process. This is the real-time database management on WSN and it deals with time-constrained data, time-constrained transactions, and limited resources of wireless sensors. Developing, testing, and debugging this kind of complex system are time-consuming and hard work. The deployment is also generally very costly in both time and money. Therefore in this context, the use of a simulator for a validation phase before implementation and deploying is proved to be very useful. The aim of this paper is to describe the different specificities of real-time databases on WSN and to present a model for a simulation framework of the real-time databases management on WSN that uses a distributed approach. Then, the model of the simulator is described and developed in Java and a case study with some results demonstrates the validity of the structural model. © 2013 Elsevier Ltd. Source


Diallo O.,University of Beira Interior | Rodrigues J.J.P.C.,University of Beira Interior | Sene M.,Ucad | Niu J.,Beihang University
Information Sciences | Year: 2014

Wireless body area networks (WBANs) have received a lot of attention from both academia and industry due to the increasing need of ubiquitous computing for eHealth applications, the continuous advances in miniaturization of electronic devices, and the ultra-low-power wireless technologies. In these networks, various sensors are attached either on clothes, on human body or even implanted under the skin for real-time health monitoring of patients in order to improve their independent daily lives. The energy constraints of sensors, the vital and large amount of data collected by WBAN nodes require powerful and secure storage, and a query processing mechanism that takes into account both real-time and energy constraints. This paper addresses these challenges and proposes a new architecture that combines a cloud-based WBANs with statistical modeling techniques in order to provide a secure storage infrastructure and optimize the real-time user query processing in terms of energy minimization and query latency. Such statistical model provides good approximate answers to queries with a given probabilistic confidence. Furthermore, the combination of the model with the cloud-based WBAN allows performing a query processing algorithm that uses the error tolerance and the probabilistic confidence interval as query execution criterions. The performance analysis and the experiments based on both real and synthetic data sets demonstrate that the new architecture and its underlying proposed algorithm optimize the real-time query processing to achieve minimal energy consumption and query latency, and provide secure and powerful storage infrastructure. © 2014 Elsevier Inc. All rights reserved. Source


Diallo O.,University of Beira Interior | Rodrigues J.J.P.C.,University of Beira Interior | Rodrigues J.J.P.C.,Saint Petersburg State University of Information Technologies, Mechanics and Optics | Sene M.,Ucad | Lloret J.,Polytechnic University of Valencia
IEEE Transactions on Parallel and Distributed Systems | Year: 2015

In sensor networks, the large amount of data generated by sensors greatly influences the lifetime of the network. To manage this amount of sensed data in an energy-efficient way, new methods of storage and data query are needed. In this way, the distributed database approach for sensor networks is proved as one of the most energy-efficient data storage and query techniques. This paper surveys the state of the art of the techniques used to manage data and queries in wireless sensor networks based on the distributed paradigm. A classification of these techniques is also proposed. The goal of this work is not only to present how data and query management techniques have advanced nowadays, but also show their benefits and drawbacks, and to identify open issues providing guidelines for further contributions in this type of distributed architectures. © 1990-2012 IEEE. Source

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