Assessment of heavy metals in Hibiscus sabdariffa calyces and Moringa oleifera leaves collected from different areas in Tanzania

Medicinal plants are known in prevention and curing of diseases. Contamination of medicinal plants by heavy metals is one of the factors affecting quality of medicinal products from medicinal plants. Heavy metals may enter the edible and medicinal plants through contaminated environment such as water bodies, air or soil.  Hibiscus sabdariffa calyces and Moringa oleifera leaves are used in Tanzania as nutritional and disease-remedial herbal drinks. This study assessed heavy metal contamination of Hibiscus sabdariffa calyces and Moringa oleifera leaves collected from Dodoma region (Vikonje, Msanga, Nzuguni A and Nzuguni B village), Pwani region (Kongowe and Chalinze village) and Shinyanga region (Mwime village). Lead, arsenic, chromium, cadmium and mercury were analyzed by Atomic Absorption Spectrometry. Microsoft excel 2010 software were used to analyze the means of heavy metal concentrations. Levels of chromium in the calyces and leaves of H. sabdariffa and M. oleifera ranged between 0.029-0.221 ppm and 0.019-0.088 ppm respectively while Arsenic was 0.096-0.204 ppm and 0.096-0.219 ppm, respectively. Mercury and Lead were found only in leaves of M. oleifera, mercury was between 0.017 ppm and 0.042 ppm and lead was 0.056 ppm. Cadmium was not detected in all plant materials. The concentrations of heavy metals in the selected samples were statistically significant at (P˂0.05). M. oleifera leaves and H. sabdariffa calyces, collected from different regions, had the low levels of heavy metals than recommended limits provided by the Tanzania Medicine and Medical Devices Authority (TMDA) and WHO

Management Of Infection By The Zika Virus

A panel of national experts was convened by the Brazilian Infectious Diseases Society in order to organize the national recommendations for the management of zika virus infection. The focus of this document is the diagnosis, both clinical and laboratorial, and appropriate treatment of the diverse manifestations of this infection, ranging from acute mild disease to Guillain-Barre syndrome and also microcephaly and congenital malformations.1

Management of infection by the Zika virus

A panel of national experts was convened by the Brazilian Infectious Diseases Society in order to organize the national recommendations for the management of zika virus infection. The focus of this document is the diagnosis, both clinical and laboratorial, and appropriate treatment of the diverse manifestations of this infection, ranging from acute mild disease to Guillain-Barré syndrome and also microcephaly and congenital malformations.1

Hierarchical Approach for Driver Disturbance Rejection in an Electric Vehicle: The CRONE Approach

This study deals with the control chassis dynamics of a light electric vehicle. In the frame of Global Chassis Control, it proposes a hierarchical control approach focuses on compensating the chassis dynamics against driver disturbances. It is based on a supervisory structure consists of two main levels, a global controller for regulating chassis variables and a local controller to each suspension system. Both controllers are designed using a fractional-order robust controller, namely CRONE controller, to provide an optimized solution for the performance-robustness tradeoff. The main objective is to improve ride comfort for passengers while respecting road holding and handling criteria. In contrast to other studies, random road disturbances are considered to investigate the limits of the proposed approach. Analysis in frequency and time domain has been done to evaluate the performance and robustness of the designed controller. Simulation results based on a full nonlinear 14 degree of freedom vehicle model show that the proposed strategy can effectively improve the ride quality in the field of interest where a significant performance in driver disturbance rejection is reported

Sur le problème de la pré-image en reconnaissance des formes avec contraintes de non-négativité

International audienceCet article traite le problème de la pré-image en méthodes à noyau pour la reconnaissance des formes. Il s'agit d'un passage obligé pour les applications dont le résultat du traitement doit pouvoir s'exprimer dans le même espace que les observations et non dans un espace fonctionnel difficile à appréhender. C'est le cas par exemple pour le débruitage de données au moyen de l'Analyse en Composantes Principales à noyau. On montre que le problème de la pré-image se prête à une résolution par des méthodes de descente. On profite alors de cette opportunité pour montrer qu'il est possible d'imposer des contraintes à la pré-image, telle que la non-négativité du résultat comme on peut la rencontrer en traitement d'images par exemple. Les algorithmes proposés sont illustrés sur le débruitage non-linéaire d'images et les performances atteintes montrent la pertinence de notre approch

Kernel autoregressive models using Yule-Walker equations

International audienceThis paper proposes nonlinear autoregressive (AR) models for time series, within the framework of kernel machines. Two models are investigated. In the first proposed model, the AR model is defined on the mapped samples in the feature space. In order to predict a future sample, this formulation requires to solve a pre-image problem to get back to the input space. We derive an iterative technique to provide a fine-tuned solution to this problem. The second model bypasses the pre-image problem, by defining the AR model with an hybrid model, as a tradeoff considering the computational time and the precision, by comparing it to the iterative, fine-tuned, model. By considering the stationarity assumption, we derive the corresponding Yule–Walker equations for each model, and show the ease of solving these problems. The relevance of the proposed models is studied on several time series, and compared with other well-known models in terms of accuracy and computational complexity

Etude de l'influence des incertitudes sur le comportement d'un système dynamique non entier de première espèce

Le sujet de cette thèse concerne l'étude de l'influence des incertitudes paramétriques et structurelles sur le comportement d un SDNE de 1ière espèce défini par l association d une fractance et d un élément I (au sens bond-graph), et ce quel que soit le domaine de la Physique. Le mémoire de thèse comporte deux parties. La première, composée de trois chapitres, présente un caractère théorique et méthodologique, elle s inscrit dans le cadre de la théorie des systèmes. La seconde comporte deux chapitres qui présentent un caractère applicatif, l objectif étant d illustrer dans les domaines de la mécanique et de l électronique la démarche présentée dans la première partie.The objective of this thesis is to study the effects of the parametric and structural uncertainties on the behavior of the 1st order fractional dynamic systems. Such systems are defined by the alliance of a fractance and an inductance and can be applied in any physical domain.So, this thesis is divided into two parts. The first part regroups the first three chapters and presents a theoretical and methodological approach for this study whereas the second part contains the remaining two chapters. These chapters represent the applications of the previously shown theory in the mechanical domain (hydropneumatic suspension) and in the electrical domain.BORDEAUX1-Bib.electronique (335229901) / SudocSudocFranceF

A Comparative Study Of Pre-Image Techniques: The Kernel Autoregressive Case

International audienceThe autoregressive (AR) model is one of the most used techniques for time series analysis, applied to study stationary as well as non-stationary processes. However, being a linear technique, it is not adapted for nonlinear systems. Recently, we introduced the kernel AR model, a straightforward extension of the AR model to the nonlinear case. It is based on the concept of kernel machines, where data are nonlinearly mapped from the input space to a feature space. The AR model can thus be applied on the mapped data. Nevertheless, in order to predict future samples, one needs to go back to the input space, by solving the pre-image problem. The prediction performance highly depends on the considered pre-image technique. In this paper, a comparative study of several state-of-the-art pre-image techniques is conducted for the kernel AR model, investigating the prediction error with the optimal model parameters, as well as the computational complexity. The conformal map approach presents results as good as the well known fixed-point iterative method, with less computational time. This is shown on unidimensional and multidimensional chaotic time series

Effect of fractional order damping control on braking performance for electric vehicles

International audienc