Coil‐Type Asymmetric Supercapacitor Electrical Cables

Cable‐shaped supercapacitors (SCs) have recently aroused significant attention due to their attractive properties such as small size, lightweight, and bendability. Current cable‐shaped SCs have symmetric device configuration. However, if an asymmetric design is used in cable‐shaped supercapacitors, they would become more attractive due to broader cell operation voltages, which results in higher energy densities. Here, a novel coil‐type asymmetric supercapacitor electrical cable (CASEC) is reported with enhanced cell operation voltage and extraordinary mechanical‐electrochemical stability. The CASECs show excellent charge–discharge profiles, extraordinary rate capability (95.4%), high energy density (0.85 mWh cm⁻³), remarkable flexibility and bendability, and superior bending cycle stability (≈93.0% after 4000 cycles at different bending states). In addition, the CASECs not only exhibit the capability to store energy but also to transmit electricity simultaneously and independently. The integrated electrical conduction and storage capability of CASECS offer many potential applications in solar energy storage and electronic gadgets.     

ProVoc: An app to train vocabulary depth in order to foster children's reading comprehension

Many studies have demonstrated the crucial role of vocabulary in predicting reading performance in general. More recent work has indicated that one particular facet of vocabulary (its depth) is more closely related to language comprehension, especially inferential comprehension. On this basis, we developed a training application to specifically improve vocabulary depth. The objective of this study was to test the effectiveness of a mobile application designed to improve vocabulary depth. The effectiveness of this training was examined on 3rd and 4th grade children's vocabulary (breadth and depth), decoding and comprehension performances. A randomized waiting-list control paradigm was used in which an experimental group first received the intervention during the first 4 weeks (between pretest and post-test1), thereafter, a waiting control group received the training for the next 4 weeks (between postest1 and posttest2). Results showed that the developed application led to significant improvements in terms of vocabulary depth performance, as well as a significant transfer effect to reading comprehension. However, we did not observe such a beneficial effect on either vocabulary breadth or written word identification. These results are discussed in terms of the links between vocabulary depth and comprehension, and the opportunities the app presents for remedying language comprehension deficits in children.     

Evaluation of the effect of processing on cocoa polyphenols: antiradical activity,anthocyanins and procyanidins profiling from raw beans to chocolate

The content and composition of anthocyanins and procyanidins in fermented cocoa beans (from different geographic origins: Ecuador, Cameroon, Ivory Coast, Ghana and Nigeria), roasted nibs, cocoa mass and chocolate were determined, beside the determination of the total antiradical capacity. Concerning geographic origin, cocoa beans and processed products from Ecuador showed the highest levels of anthocyanins, followed by Nigeria and Cameroon. Generally, as cocoa beans were further processed, the levels of anthocyanins and flavan‐3‐ols decreased. The largest observed losses of phenolics occurred during roasting. A progressive decreasing trend in polyphenol concentration was observed in the other processed samples as well. Despite the original content of polyphenols in raw cocoa beans, technological processes imply a significant impact on cocoa quality, confirming the need of specific optimisation to obtain high value chocolate.     

Effect of the cultivation mode on red pigments production from Monascus ruber

In submerged cultures performed in chemically defined fermentation medium containing glucose and glutamate, the growth and production of water‐soluble red pigments and citrinin by the filamentous fungus Monascus ruber were studied under various carbon/nitrogen (C/N) ratios. The specific production of the red pigments was optimal at a glucose/glutamate ratio of about 10 and then steadily decreased at higher C/N ratio. In contrast, the production of the mycotoxin increased with increased C/N with an optimum in the range of 30–45. In a fed‐batch mode, it was also found that the production of pigments was not favoured in fed‐batch mode by feeding the medium with glucose while keeping the C/N ratio lower than 10. This low production likely resulted from concurrent high accumulation of L‐malic acid that was reported to inhibit this production. In contrast, this mode of cultivation was rather favourable for the production of the mycotoxin.     

Single chamber Solid Oxide Fuel Cells selective electrodes: A real chance with brownmillerite-based nanocomposites

In this contribution brownmillerite-based nanocomposite cathode for Single-Chamber Solid Oxide Fuel Cells is developed. These cells can be very attractive especially for small and cheap devices because of the absence of seals. The efficiency of SC-SOFCs is strictly connected to the selectivity of anode and cathode, the bottleneck for this technology. The development of a cathode inert in fuel oxidation is particularly challenging. Our strategy is to start from a catalytically un-active support (CFA = Ca₂FeAl_0.95Mg_0.05O₅) and induce the formation of iron oxide based nanoparticles, expected to activate oxygen. Symmetric (CFA + FeO_x/CGO/CFA + FeO_x) and complete cells (CFA + FeO_x/CGO/Ni-CGO) are studied in air and methane/oxygen 2:1 mixture. The Area Specific Resistance of CFA + FeO_x is less than 1/3 that of CFA. The high selectivity allows to reach an efficiency of 25%; power still needs to be increased but we demonstrated the possibility to develop selective low cost electrodes. The effect of air, methane/oxygen exposure and the heat treatments were carefully investigated.     

A Lattice Approach to Image Segmentation

After a formal definition of segmentation as the largest partition of the space according to a criterion σ and a function f, the notion of a morphological connection is reminded. It is used as an input to a central theorem of the paper (Theorem 8), that identifies segmentation with the connections that are based on connective criteria. Just as connections, the segmentations can then be regrouped by suprema and infima. The generality of the theorem makes it valid for functions from any space to any other one. Two propositions make precise the AND and OR combinations of connective criteria. The soundness of the approach is demonstrated by listing a series of segmentation techniques. One considers first the cases when the segmentation under study does not involve initial seeds. Various modes of regularity are discussed, which all derive from Lipschitz functions. A second category of examples involves the presence of seeds around which the partition of the space is organized. An overall proposition shows that these examples are a matter for the central theorem. Watershed and jump connection based segmentations illustrate this type of situation. The third and last category of examples deals with cases when the segmentation occurs in an indirect space, such as an histogram, and is then projected back on the actual space under study. The relationships between filtering and segmentation are then investigated. A theoretical chapter introduces and studies the two notions of a pulse opening and of a connected operator. The conditions under which a family of pulse openings can yield a connected filter are clarified. The ability of segmentations to generate pyramids, or hierarchies, is analyzed. A distinction is made between weak hierarchies where the partitions increase when going up in the pyramid, and the strong hierarchies where the various levels are structured as semi-groups, and particularly as granulometric semi-groups. The last section is based on one example, and goes back over the controversy about “lattice” versus “functional” optimization. The problem is now tackled via a case of colour segmentation, where the saturation serves as a cursor between luminance and hue. The emphasis is put on the difficulty of grouping the various necessary optimizations into a single one.     

Automatic fog detection and estimation of visibility distance through use of an onboard camera

In this paper, we will present a technique for measuring visibility distances under foggy weather conditions using a camera mounted onboard a moving vehicle. Our research has focused in particular on the problem of detecting daytime fog and estimating visibility distances; thanks to these efforts, an original method has been developed, tested and patented. The approach consists of dynamically implementing Koschmieder's law. Our method enables computing the meteorological visibility distance, a measure defined by the International Commission on Illumination (CIE) as the distance beyond which a black object of an appropriate dimension is perceived with a contrast of less than 5%. Our proposed solution is an original one, featuring the advantage of utilizing a single camera and necessitating the presence of just the road and sky in the scene. As opposed to other methods that require the explicit extraction of the road, this method offers fewer constraints by virtue of being applicable with no more than the extraction of a homogeneous surface containing a portion of the road and sky within the image. This image preprocessing also serves to identify the level of compatibility of the processed image with the set of Koschmieder's model hypotheses. Nicolas Hautiére graduated from the École Nationale des Travaux Publics de l'État, France (2002). He received his M.S. and Ph.D. degree in computer vision, respectively, in 2002 and 2005 from Saint-Étienne University (France). From 2002, he is a researcher in the Laboratoire Central des Ponts et Chaussées (LCPC), Paris, France. His research interests include trafic engineering, computer vision, and pattern recognition. Jean-Philippe Tarel graduated from the École Nationale des Ponts et Chaussées, Paris, France (1991). He received his Ph.D. degree in Applied Mathematics from Paris IX-Dauphine University in 1996 and he was with the Institut National de Recherche en Informatique et Automatique (INRIA) from 1991 to 1996. From 1997 to 1998, he was a research associate at Brown University, USA. From 1999, he is a researcher in the Laboratoire Central des Ponts et Chaussées (LCPC), Paris, France, and from 2001 to 2003 in the INRIA. His research interests include computer vision, pattern recognition, and shape modeling. Jean Lavenant graduated from the École Nationale des Travaux Publics de l'État, Lyon, France (2001). He received the M.S. degree in Computer Vision from Jean Monnet university of Saint-Étienne in 2001. In 2001, he was a researcher in the Laboratoire Central des Ponts et Chaussées (LCPC). In 2002, he was a system engineer in Chicago (USA). He is currently an engineer for the french ministry of transports. Didier Aubert received the M.S. and Ph.D. degree, respectively, in 1985 and 1989 from the National Polytechnical Institut of Grenoble (INPG). From 1989--1990, he worked as a research scientist on the development of an automatic road following system for the NAVLAB at Carnegie Mellon University. From 1990–1994, he worked in the research department of a private company (ITMI). During this period he was the project leader of several projects dealing with computer vision. He is currently a researcher at INRETS since 1995 and works on Road traffic measurements, crowd monitoring, automated highway systems, and driving assistance systems for vehicles. He is an image processing expert for several companies, teaches at Universities (Paris VI, Paris XI, ENPC, ENST) and is at the editorial board of RTS (Research - Transport - Safety).