BiNem® manufacturing process for mass production

Abstract— As the need for high‐resolution ultra‐low‐power bistable displays grows, it is important to rapidly implement the mass‐production manufacturing of BiNem® LCDs. The cost‐effective approach for BiNem® manufacturing is based on using STN manufacturing process technologies since BiNem® and STN displays have a similar internal structure. The key differences between BiNem® and STN displays from a manufacturing point of view will be discussed. We show that industrial STN manufacturing equipment can be used to produce BiNem® LCDs at competitive costs. Reflective e‐book display modules with VGA resolution are produced in the pilot‐production series.     

GEAMAS: A Generic Architecture for Agent-Oriented Simulations of Complex Processes

This paper's object is to present the results of the GEAMAS project which aims at modeling and simulating natural complex systems. GEAMAS is a generic architecture of agents used to study the behavior emergence in such systems. It is a multiagent program meant to develop simulation applications. Modeling complex systems requires to reduce, to organize the system complexity and to describe suitable components. Complexity of the system can then be tackled with an agent-oriented approach, where interactions lead to a global behavior. This approach helps in understanding how non-determinist behavior can emerge from interactions between agents, which is near of self-organized criticality used to explain natural phenomena. In the Applied Artificial Intelligence context, this paper presents an agent software architecture using a model of agent. This architecture is composed of three abstract levels over which the complexity is distributed and reduced. The architecture is implemented in ReActalk, an open agent-oriented development tool, which was developed on top of Smalltalk-80. To illustrate our purpose and to validate the architecture, a simulation program to help in predicting volcanic eruptions was investigated. This program was run over a period of one year and has given many satisfying results unattainable up to there with more classical approaches.     

Quantitative x-ray microanalysis of spherical inclusions embedded in a matrix using a SEM and Monte Carlo simulations

The current schemes of quantification of x-ray microanalysis in the SEM [ZAF and σ(ρZ) methods] are valid for specimens of homogeneous composition. The determination of the chemical composition of small inclusions using these techniques is impossible because the volume of x-ray emission is not of homogeneous composition. A scheme of quantification to determine the composition of small inclusions embedded in a matrix has been developed using Monte Carlo simulations. This scheme is similar to that developed by Kyser and Murata (1974) for the quantification of thin foils deposited on a substrate using x-ray microanalysis in the SEM.     

A transformation-based approach to context-aware modelling

Context-aware computing is a paradigm for governing the numerous mobile devices surrounding us. In this computing paradigm, software applications continuously and dynamically adapt to different “contexts” implying different software configurations of such devices. Unfortunately, modelling a context-aware application (CAA) for all possible contexts is only feasible in the simplest of cases. Hence, tool support verifying certain properties is required. In this article, we introduce the CAA model, in which context adaptations are specified explicitly as model transformations. By mapping this model to graphs and graph transformations, we can exploit graph transformation techniques such as critical pair analysis to find contexts for which the resulting application model is ambiguous. We validate our approach by means of an example of a mobile city guide, demonstrating that we can identify subtle context interactions that might go unnoticed otherwise.     

Soft Matter Technology at KIT: Chemical Perspective from Nanoarchitectures to Microstructures

Bioinspiration has emerged as an important design principle in the rapidly growing field of materials science and especially its subarea, soft matter science. For example, biological cells form hierarchically organized tissues that not only are optimized and designed for durability, but also have to adapt to their external environment, undergo self‐repair, and perform many highly complex functions. Being able to create artificial soft materials that mimic those highly complex functions will enable future materials applications. Herein, soft matter technologies that are used to realize bioinspired material structures are described, and potential pathways to integrate these into a comprehensive soft matter research environment are addressed. Solutions become available because soft matter technologies are benefitting from the synergies between organic synthesis, polymer chemistry, and materials science.     

Effect of different cranberry extracts and juices during cranberry juice processing on the antiproliferative activity against two colon cancer cell lines

The effect of cranberry extracts and juices during cranberry juice processing on the antiproliferative properties against colon cancer cells was investigated. Two colon cancer cell lines HT-29 and LS-513 were treated with different concentrations of cranberry phenolic extracts from fruits, puree, depectinised puree and pomace and different concentration of three juices (raw, filtered and concentrated juices). The phenolic extracts consisted of water-soluble phenolic compounds, apolar phenolic compounds and anthocyanins. These phenolic extracts and juices were tested against two cell lines at pH 2.5 (natural juice pH) and at pH 7.0 (physiological pH). All cranberry extracts and juices could inhibit the growth of both cell lines with the IC₅₀ values (the concentration of phenolic content required to inhibit 50% the growth of cancer cells) varied from 3.8 to 179.2 μg gallic acid equivalent/ml. It was found that three types of extracts from fruit at pH 7.0 were the most effective at inhibiting the growth of HT-29 cell line. Extracts containing anthocyanins from fruit and from pomace were the most and the least efficient, respectively, in inhibiting the growth of both cancer cell lines. Further, three juices at natural pH (pH 2.5) were more effective at inhibiting the growth of two cell lines as compared to juices at pH 7.0. Concentrated juice at both pH values was the most effective at growth inhibition of two cancer cell lines compared to two other juices.