Monitoring pH and ORP in a SHARON reactor

This paper analyses the valuable information provided by the on-line measurements of pH and oxidation reduction potential (ORP) in a continuous single high ammonia removal over nitrite (SHARON) reactor. A laboratory-scale SHARON reactor equipped with pH, ORP, electric conductivity and dissolved oxygen (DO) probes has been operated for more than one year. Nitrogen removal over nitrite has been achieved by adding methanol at the beginning of anoxic stages. Time evolution of pH and ORP along each cycle allows identifying the decrease in nitritation rate when ammonia is consumed during the aerobic phase and the end of the denitrification process during the anoxic phase. Therefore, monitoring pH and ORP can be used to develop a real-time control system aimed at optimizing the length of both aerobic and anoxic stages. Real-time control of methanol addition can be carried out by using the information provided by these probes: excessive methanol addition in the anoxic stage is clearly detected in the ORP profile of the following aerobic phase, while a deficit of methanol is detected in both pH and ORP profiles of that anoxic phase. Moreover, other valuable information such as the amount of ammonia nitrified, failures in DO measurements, excessive stirring during the anoxic stage and methanol dosage in the aerobic phase was also provided by the pH and ORP profiles.     

“Area Without Numbers”: Using Touchscreen Dynamic Geometry to Reason About Shape

Abstract

In this article, we report on two lessons aimed at introducing junior high school students to the idea of shearing in a touchscreen dynamic geometry environment. By using shearing, we hoped to shift students’ attention away from a formula-driven, computational conception of area toward a more geometric one. We found that the students were able to solve several problems involving the comparison of polygons based on verbal and diagrammatic explanations. We describe the features of the touchscreen dynamic geometry technology that supported their learning, as well as the specific role that the teacher played in modeling students’ reasoning about area.     

Ferritin Protein Regulates the Degradation of Iron Oxide Nanoparticles

Proteins implicated in iron homeostasis are assumed to be also involved in the cellular processing of iron oxide nanoparticles. In this work, the role of an endogenous iron storage protein—namely the ferritin—is examined in the remediation and biodegradation of magnetic iron oxide nanoparticles. Previous in vivo studies suggest the intracellular transfer of the iron ions released during the degradation of nanoparticles to endogenous protein cages within lysosomal compartments. Here, the capacity of ferritin cages to accommodate and store the degradation products of nanoparticles is investigated in vitro in the physiological acidic environment of the lysosomes. Moreover, it is questioned whether ferritin proteins can play an active role in the degradation of the nanoparticles. The magnetic, colloidal, and structural follow‐up of iron oxide nanoparticles and proteins in lysosome‐like medium confirms the efficient remediation of potentially harmful iron ions generated by nanoparticles within ferritins. The presence of ferritins, however, delays the degradation of particles due to a complex colloidal behavior of the mixture in acidic medium. This study exemplifies the important implications of intracellular proteins in processes of degradation and metabolization of iron oxide nanoparticles.     

Surrogate modeling approximation using a mixture of experts based on EM joint estimation

An automatic method to combine several local surrogate models is presented. This method is intended to build accurate and smooth approximation of discontinuous functions that are to be used in structural optimization problems. It strongly relies on the Expectation−Maximization (EM) algorithm for Gaussian mixture models (GMM). To the end of regression, the inputs are clustered together with their output values by means of parameter estimation of the joint distribution. A local expert is then built (linear, quadratic, artificial neural network, moving least squares) on each cluster. Lastly, the local experts are combined using the Gaussian mixture model parameters found by the EM algorithm to obtain a global model. This method is tested over both mathematical test cases and an engineering optimization problem from aeronautics and is found to improve the accuracy of the approximation.     

Methodology for capturing and formalizing DFM Knowledge

Design for manufacturing (DFM) practices lead to more competitive products from the point of view of cost, development time and quality. However, the success of considering manufacturing issues during design process would be higher if manufacturing information was more readily available and designers needed less experience to select information relevant to DFM.     

Characterization of renal tumours based on Raman spectra classification

In this study, we propose to evaluate the potential of Raman spectroscopy (RS) to assess renal tumours at surgery. Different classes of Raman renal spectra acquired during a clinical protocol are discriminated using support vector machines classifiers. The influence on the classification scores of various preprocessing steps generally involved in RS are also investigated and evaluated in the particular context of renal tumour characterization. Encouraging results show the interest of RS to evaluate kidney cancer and suggest the potential of this technique as a surgical assistance during partial nephrectomy.     

Gambling versus Designing: Organizing for the Design of the Probability Space in the Energy Sector

The objective of this paper is to elucidate an organizational process for the design of generic technologies (GTs). While recognizing the success of GTs, the literature on innovation management generally describes their design according to evolutionary strategies featuring multiple and uncertain trials, resulting in the discovery of common features among multiple applications. This random walk depends on multiple market and technological uncertainties that are considered exogenous: as smart as he can be, the ‘gambler’ must play in a given probability space. However, what happens when the innovator is not a gambler but a designer, i.e., when the actor is able to establish new links between previously independent emerging markets and technologies? Formally speaking, the actor designs a new probability space. Building on a case study of two technological development programmes at the French Center for Atomic Energy, we present cases of GTs that correspond to this logic of designing the probability space, i.e. the logic of intentionally designing common features that bridge the gap between a priori heterogeneous applications and technologies. This study provides another example showing that the usual trial‐and‐learning strategy is not the only strategy to design GTs and that these technologies can be designed by intentionally building new interdependences between markets and technologies. Our main result is that building these interdependences requires organizational patterns that correspond to a ‘design of exploration’ phase in which multiple technology suppliers and application providers are involved in designing both the probability space itself and the instruments to explore and benefit from this new space.     

Building language resources for a Multi-Engine English-Filipino machine translation system

In this paper, we present the building of various language resources for a multi-engine bi-directional English-Filipino Machine Translation (MT) system. Since linguistics information on Philippine languages are available, but as of yet, the focus has been on theoretical linguistics and little is done on the computational aspects of these languages, attempts are reported here on the manual construction of these language resources such as the grammar, lexicon, morphological information, and the corpora which were literally built from almost non-existent digital forms. Due to the inherent difficulties of manual construction, we also discuss our experiments on various technologies for automatic extraction of these resources to handle the intricacies of the Filipino language, designed with the intention of using them for the MT system. To implement the different MT engines and to ensure the improvement of translation quality, other language tools (such as the morphological analyzer and generator, and the part of speech tagger) were developed.     

NodeTrix: a hybrid visualization of social networks

The need to visualize large social networks is growing as hardware capabilities make analyzing large networks feasible and many new data sets become available. Unfortunately, the visualizations in existing systems do not satisfactorily resolve the basic dilemma of being readable both for the global structure of the network and also for detailed analysis of local communities. To address this problem, we present NodeTrix, a hybrid representation for networks that combines the advantages of two traditional representations: node-link diagrams are used to show the global structure of a network, while arbitrary portions of the network can be shown as adjacency matrices to better support the analysis of communities. A key contribution is a set of interaction techniques. These allow analysts to create a NodeTrix visualization by dragging selections to and from node-link and matrix forms, and to flexibly manipulate the NodeTrix representation to explore the dataset and create meaningful summary visualizations of their findings. Finally, we present a case study applying NodeTrix to the analysis of the InfoVis 2004 coauthorship dataset to illustrate the capabilities of NodeTrix as both an exploration tool and an effective means of communicating results.