A POEtic Architecture for Bio-Inspired Hardware

The implementation of bio-inspired systems in hardware has traditionally been more a matter of artistry than of method. The reasons are multiple, but one of the main problems has always been the lack of a universal platform, of a standardized architecture, and of a proper methodology for the implementation of such systems. The ideas presented in this article are the first results of a new research project, "Reconfigurable POEtic Tissue". The goal of the project is the development of a hardware platform capable of implementing systems inspired by all the three major axes (phylogenesis, ontogenesis, and epigenesis) of bio-inspiration in digital hardware. A novel cellular architecture, capable of exploiting the main features of the future POEtic tissue and compatible with a relatively automatic design methodology, is then presented

Verlatstraat te Antwerpen (gem. Antwerpen). Archeologische begeleiding.

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Ontogenetic Development and Fault Tolerance in the POEtic Tissue

In this article, we introduce the approach to the realization of ontogenetic development and fault tolerance that will be implemented in the POEtic tissue, a novel reconfigurable digital circuit dedicated to the realization of bio-inspired systems. The modelization in electronic hardware of the developmental process of multi-cellular biological organisms is an approach that could become extremely useful in the implementation of highly complex systems, where concepts such as self-organization and fault tolerance are key issues. The concepts presented in this article represent an attempt at finding a useful set of mechanisms to allow the implementation in digital hardware of a bio-inspired developmental process with a reasonable overhead

Robotic ubiquitous cognitive ecology for smart homes

Robotic ecologies are networks of heterogeneous robotic devices pervasively embedded in everyday environments, where they cooperate to perform complex tasks. While their potential makes them increasingly popular, one fundamental problem is how to make them both autonomous and adaptive, so as to reduce the amount of preparation, pre-programming and human supervision that they require in real world applications. The project RUBICON develops learning solutions which yield cheaper, adaptive and efficient coordination of robotic ecologies. The approach we pursue builds upon a unique combination of methods from cognitive robotics, machine learning, planning and agent- based control, and wireless sensor networks. This paper illustrates the innovations advanced by RUBICON in each of these fronts before describing how the resulting techniques have been integrated and applied to a smart home scenario. The resulting system is able to provide useful services and pro-actively assist the users in their activities. RUBICON learns through an incremental and progressive approach driven by the feed- back received from its own activities and from the user, while also self-organizing the manner in which it uses available sensors, actuators and other functional components in the process. This paper summarises some of the lessons learned by adopting such an approach and outlines promising directions for future work

Allergic sensitization: screening methods

Experimental in silico, in vitro, and rodent models for screening and predicting protein sensitizing potential are discussed, including whether there is evidence of new sensitizations and allergies since the introduction of genetically modified crops in 1996, the importance of linear versus conformational epitopes, and protein families that become allergens. Some common challenges for predicting protein sensitization are addressed: (a) exposure routes; (b) frequency and dose of exposure; (c) dose-response relationships; (d) role of digestion, food processing, and the food matrix; (e) role of infection; (f) role of the gut microbiota; (g) influence of the structure and physicochemical properties of the protein; and (h) the genetic background and physiology of consumers. The consensus view is that sensitization screening models are not yet validated to definitively predict the de novo sensitizing potential of a novel protein. However, they would be extremely useful in the discovery and research phases of understanding the mechanisms of food allergy development, and may prove fruitful to provide information regarding potential allergenicity risk assessment of future products on a case by case basis. These data and findings were presented at a 2012 international symposium in Prague organized by the Protein Allergenicity Technical Committee of the International Life Sciences Institute’s Health and Environmental Sciences Institute