Bioreactor scale-up often pose a serious issue during the industrial development of a bioprocess considering the numerous physical and biological phenomena occurring in the reacting volume. The basic principles of scale-up coming from the traditional chemical and process engineering approaches will be first reviewed and will be then compared to a new one involving recent development at the level of microbial strain manipulation. This "physiological" approach of scale-up involves directly a biological component of the system (by comparison with the traditional approach for scaling-up involving physical parameters indirectly linked to the physiological phenomena occurring in the bioreactor), i.e. the synthesis of a reporter fluorescent protein when microbial cells are exposed to stress. It will be shown how this principle can be used for a better understanding of the relationship between bioreactor hydrodynamics and microbial stress.

Le présent travail fait appel à une approche de classification basée sur un réseau de neurones artificiels de type carte auto-organisatrice SOM (Self Organizing Maps). Cet algorithme a été utilisé pour mieux discriminer les individus (points de mesures) en mettant en évidence les relations non linéaires impossibles à obtenir avec les méthodes classiques d'ordination. Ainsi, à partir d'un apprentissage non supervisé d'un réseau de neurones artificiels, cet algorithme recherche itérativement des similarités parmi les données observées et les représente sur une carte de sortie (carte de Kohonen). Dans cette étude, 88 échantillons de sédiments de surface ont été prélevés au niveau de 22 stations, pendant les quatre saisons de l'année agricole 2010-2011, au niveau de la retenue du barrage Sidi Chahed (région Fès-Meknès). Chaque échantillon est représenté par 14 paramètres physico-chimiques. La couche d'entrée de la carte SOM est constituée des valeurs normalisées des 88 échantillons. La sortie est représentée par une carte de deux dimensions. Les résultats obtenus présentent globalement de légères variations spatio-temporelles des paramètres physico-chimiques qui seraient en relation avec la nature des formations géologiques, l'activité anthropique et en particulier une forte activité agricole avoisinante. Mots clés— Retenue de barrage Sidi Chahed, Paramètres physico-chimiques, sédiments superficiels, Carte auto-organisatrice (SOM), SOM-HC. Abstract— The present work appeals to a classification approach based on a network of artificial neurons of type Self-Organizing map SOM. This algorithm has been used to better discriminate individuals (measuring points) by highlighting nonlinear relationships unobtainable with classic methods of ordination. Thus, from an unsupervised learning of an artificial neural network, this algorithm searches iteratively for similarities among the observed data and represents them on a map output (Kohonen map). In this study, 88 surface sediment samples were collected at 22 stations, during the four seasons of the agricultural year 2010-2011, at the retaining of Sidi Chahed Dam (region Fez-Meknes). Each sample is represented by 14 physicochemical parameters. The SOM map input layer consists of normalized values of the 88 samples. The output is represented by a two-dimensional map.The results obtained overall present slight spatial and temporal deviation of physicochemical parameters that would be related to the nature of the geological formations, anthropogenic activity and particularly a strong adjacent agricultural activity Keywords— Retaining of Sidi Chahed Dam, physicochemical parameters, surficial sediments, self-organizing map (SOM) , SOM-HC

—In the present work, emulsion liquid membrane (ELM) technique was applied for the extraction of cadmium(II) present in aqueous samples. Aliquat 336 (Chloride tri-N-octylmethylammonium) was used as carrier to extract cadmium(II). The main objective of this work is to investigate the influence of various parameters affected the ELM formation and its stability and testing the performance of the prepared ELM on removal of cadmium by using synthetic solution with different concentrations. Experiments were conducted to optimize pH of the feed solution and it was found that cadmium(II) can be extracted at pH 6.5. The influence of the carrier concentration and treat ratio on the extraction process was investigated. The obtained results showed that the optimal values are respectively 3% (Aliquat 336) and a ratio (feed: emulsion) equal to 1:1.