Physics-based compact model for ultra-scaled FinFETs

A physical and explicit compact model for lightly doped FinFETs is presented. This design-oriented model is valid for a large range of silicon Fin widths and lengths, using only a very few number of model parameters. The quantum mechanical effects (QMEs), which are very significant for thin Fins below 15 nm, are included in the model as a correction to the surface potential. A physics-based approach is also followed to model short-channel effects (roll-off), drain-induced barrier lowering (DIBL), subthreshold slope degradation, drain saturation voltage, velocity saturation, channel length modulation and carrier mobility degradation. The quasi-static model is then developed and accurately accounts for small-geometry effects as well. This compact model is accurate in all regions of operation, from weak to strong inversion and from linear to saturation regions. It has been implemented in the high-level language Verilog-A and exhibits an excellent numerical efficiency. Finally, comparisons of the model with 3D numerical simulations show a very good agreement making this model well-suited for advanced circuit simulations.     

Effect of growth temperature on yeast lipid composition and alcoholic fermentation at low temperature

The loss of viability of wine yeast strains due to low-temperature fermentations could be overcome by increasing their stress tolerance and adaptability. Changes in membrane lipid composition are one of the first responses to cold stress. The aim of this study was to analyze the various adaptation mechanisms to low temperatures by comparing the better adapted Saccharomyces species. The viability, vitality, fermentation capacity, and lipid composition of different Saccharomyces species (S. cerevisiae, S. bayanus, S. uvarum, and a hybrid S. cerevisiae/S. uvarum) with different fermentative origins (wine, beer, and baker’s strains together with a laboratory strain) were compared after culturing at low (13 °C) and optimal (25 °C) temperatures. In spite of specific responses of the different strains/species, the results showed that at low temperature, the medium-chain fatty acid and the triacylglyceride content increased, whereas the phosphatidic acid content and the phosphatidylcholine/phosphatidylethanolamine ratio decreased. Only the laboratory strain was not able to ferment the sugars, and after growing at both temperatures, its lipid composition was very different from that of the other strains. The hybrid strain showed the highest sugar consumption at 13 °C and the best vitality whatever the preculture temperature used. The rest of the species needed a preadaptation at low temperature involving a change in their lipid composition to improve their fermentation rate at 13 °C.     

A comparison study of pattern recognition algorithms implemented on a microcontroller for use in an electronic tongue for monitoring drinking waters

A portable electronic tongue has been developed using an array of eighteen thick-film electrodes of different materials forming a multi-electrode array. A microcontroller is used to implement the pattern recognition. The classification of drinking waters is carried out by a Microchip PIC18F4550 micro-controller and is based on neural networks algorithms. These algorithm are initially trained with the multi-electrode array on a Personal Computer (PC) using several samples of waters (still, sparkling and tap) to obtain the optimum architecture of the networks. Once it is trained, the computed data are programmed into the microcontroller, which then gives the water classification directly for new unknown water samples. A comparative study between a Fuzzy ARTMAP, a Multi-Layer Feed-Forward network (MLFF) and a Linear Discriminant Analysis (LDA) has been done in order to obtain the best implementation on a microcontroller.     

The symmetry of partner modelling

Collaborative learning has often been associated with the construction of a shared understanding of the situation at hand. The psycholinguistics mechanisms at work while establishing common grounds are the object of scientific controversy. We postulate that collaborative tasks require some level of mutual modelling, i.e. that each partner needs some model of what the other partners know/want/intend at a given time. We use the term “some model” to stress the fact that this model is not necessarily detailed or complete, but that we acquire some representations of the persons we interact with. The question we address is: Does the quality of the partner model depend upon the modeler’s ability to represent his or her partner? Upon the modelee’s ability to make his state clear to the modeler? Or rather, upon the quality of their interactions? We address this question by comparing the respective accuracies of the models built by different team members. We report on 5 experiments on collaborative problem solving or collaborative learning that vary in terms of tasks (how important it is to build an accurate model) and settings (how difficult it is to build an accurate model). In 4 studies, the accuracy of the model that A built about B was correlated with the accuracy of the model that B built about A, which seems to imply that the quality of interactions matters more than individual abilities when building mutual models. However, these findings do not rule out the fact that individual abilities also contribute to the quality of modelling process.     

A cloud-based platform to ensure interoperability in aerospace industry

A new approach is proposed to address several key issues relating to interoperability for collaborative product development within networked organizations. The work innovatively combines (i) a two-phase semantic data mediation model to ensure interoperability, (ii) a cloud-based platform to enable complex collaboration scenarios and (iii) an implementation and the evaluation of the proposed approach in the aerospace industry. The latter demonstrates that data mediation delivered as a service drastically reduces cost and time needed for establishing and maintaining interoperability.     

Simulation of hydrogen diffusion affected by stress-strain heterogeneity in polycrystalline stainless steel

The effect of microstructure-induced strain-stress heterogeneity on the evolution of hydrogen distribution was studied on 316 L stainless steel. A crystal plasticity-transient hydrogen diffusion finite element analysis was developed. To reach the stress-strain heterogeneity, synthetic microstructures were computed under uniaxial loading. The results show that hydrostatic stress gradients is the main cause of the hydrogen redistribution and the strain rate has a crucial effect on the redistribution degree. Statistical analysis of H-segregation reveals clustering of H-enriched zones at the mesoscopic scale.     

Encapsulated Cellular Implants for Recombinant Protein Delivery and Therapeutic Modulation of the Immune System

Ex vivo gene therapy using retrievable encapsulated cellular implants is an effective strategy for the local and/or chronic delivery of therapeutic proteins. In particular, it is considered an innovative approach to modulate the activity of the immune system. Two recently proposed therapeutic schemes using genetically engineered encapsulated cells are discussed here: the chronic administration of monoclonal antibodies for passive immunization against neurodegenerative diseases and the local delivery of a cytokine as an adjuvant for anti-cancer vaccines.     

Antiproliferative,Antibacterial and Antifungal Activity of the Lichen Xanthoria parietina and Its Secondary Metabolite Parietin

Lichens are valuable natural resources used for centuries throughout the world as medicine, food, fodder, perfume, spices and dyes, as well as for other miscellaneous purposes. This study investigates the antiproliferative, antibacterial and antifungal activity of the acetone extract of the lichen Xanthoria parietina (Linnaeus) Theodor Fries and its major secondary metabolite, parietin. The extract and parietin were tested for antimicrobial activity against nine American Type Culture Collection standard and clinically isolated bacterial strains, and three fungal strains. Both showed strong antibacterial activity against all bacterial strains and matched clinical isolates, particularly against Staphylococcus aureus from standard and clinical sources. Among the fungi tested, Rhizoctonia solani was the most sensitive. The antiproliferative effects of the extract and parietin were also investigated in human breast cancer cells. The extract inhibited proliferation and induced apoptosis, both effects being accompanied by modulation of expression of cell cycle regulating genes such as p16, p27, cyclin D1 and cyclin A. It also mediated apoptosis by activating extrinsic and intrinsic cell death pathways, modulating Tumor Necrosis Factor-related apoptosis-inducing ligand (TRAIL) and B-cell lymphoma 2 (Bcl-2), and inducing Bcl-2-associated agonist of cell death (BAD) phosphorylation. Our results indicate that Xanthoria parietina is a major potential source of antimicrobial and anticancer substances.