Towards Understanding the Origin of Genetic Languages

Molecular biology is a nanotechnology that works--it has worked for billions of years and in an amazing variety of circumstances. At its core is a system for acquiring, processing and communicating information that is universal, from viruses and bacteria to human beings. Advances in genetics and experience in designing computers have taken us to a stage where we can understand the optimisation principles at the root of this system, from the availability of basic building blocks to the execution of tasks. The languages of DNA and proteins are argued to be the optimal solutions to the information processing tasks they carry out. The analysis also suggests simpler predecessors to these languages, and provides fascinating clues about their origin. Obviously, a comprehensive unraveling of the puzzle of life would have a lot to say about what we may design or convert ourselves into.Comment: (v1) 33 pages, contributed chapter to "Quantum Aspects of Life", edited by D. Abbott, P. Davies and A. Pati, (v2) published version with some editin

Customization principles of an aeronautics SLM environment and an illustration on aeronautics use cases: the doors management system and the flight control system

International audienceHaving efficient means to build an appropriate system engineering framework is a differentiating factor for the competitiveness of the European aeronautics industry. We present in this paper an approach and a set of concepts enabling the construction and customization of a system engineering environment. These customization principles, set up in the frame of the CESAR project, are driven by a multi-view model-based system development process and by a system data description. The flexibility and the benefits of this approach are demonstrated on two industrial cases: the doors management system and the flight control system

Emergence of Zipf's Law in the Evolution of Communication

Zipf's law seems to be ubiquitous in human languages and appears to be a universal property of complex communicating systems. Following the early proposal made by Zipf concerning the presence of a tension between the efforts of speaker and hearer in a communication system, we introduce evolution by means of a variational approach to the problem based on Kullback's Minimum Discrimination of Information Principle. Therefore, using a formalism fully embedded in the framework of information theory, we demonstrate that Zipf's law is the only expected outcome of an evolving, communicative system under a rigorous definition of the communicative tension described by Zipf.Comment: 7 pages, 2 figure

Carbon--The First Frontier of Information Processing

Information is often encoded as an aperiodic chain of building blocks. Modern digital computers use bits as the building blocks, but in general the choice of building blocks depends on the nature of the information to be encoded. What are the optimal building blocks to encode structural information? This can be analysed by substituting the operations of addition and multiplication of conventional arithmetic with translation and rotation. It is argued that at the molecular level, the best component for encoding discretised structural information is carbon. Living organisms discovered this billions of years ago, and used carbon as the back-bone for constructing proteins that function according to their structure. Structural analysis of polypeptide chains shows that an efficient and versatile structural language of 20 building blocks is needed to implement all the tasks carried out by proteins. Properties of amino acids indicate that the present triplet genetic code was preceded by a more primitive one, coding for 10 amino acids using two nucleotide bases.Comment: (v1) 9 pages, revtex. (v2) 10 pages. Several arguments expanded to make the article self-contained and to increase clarity. Applications pointed out. (v3) 11 pages. Published version. Well-known properties of proteins shifted to an appendix. Reformatted according to journal styl

Recovering Grammar Relationships for the Java Language Specification

Grammar convergence is a method that helps discovering relationships between different grammars of the same language or different language versions. The key element of the method is the operational, transformation-based representation of those relationships. Given input grammars for convergence, they are transformed until they are structurally equal. The transformations are composed from primitive operators; properties of these operators and the composed chains provide quantitative and qualitative insight into the relationships between the grammars at hand. We describe a refined method for grammar convergence, and we use it in a major study, where we recover the relationships between all the grammars that occur in the different versions of the Java Language Specification (JLS). The relationships are represented as grammar transformation chains that capture all accidental or intended differences between the JLS grammars. This method is mechanized and driven by nominal and structural differences between pairs of grammars that are subject to asymmetric, binary convergence steps. We present the underlying operator suite for grammar transformation in detail, and we illustrate the suite with many examples of transformations on the JLS grammars. We also describe the extraction effort, which was needed to make the JLS grammars amenable to automated processing. We include substantial metadata about the convergence process for the JLS so that the effort becomes reproducible and transparent

Programming as a mathematical activity

Programming in undergraduate mathematics is an opportunity to develop various mathematical skills. This paper outlines some topics covered in a second year, optional module ‘Programming with Mathematical Applications’ that develop mathematical thinking and involve mathematical activities, showing that practical programming can be taught to mathematicians as a mathematical skill

Think the image, don't make it! On algorithmic thinking, art education, and re-coding

In conceptual art, the idea is not only starting point and motivation for the material work, it is often considered the work itself. In algorithmic art, thinking the process of generating the image as one instance of an entire class of images becomes the decisive kernel of the creative work. This is so because the generative algorithm is the innovative component of the artist's work. We demonstrate this by critically looking at attempts to re-construct works of early computer art by the re-coding movement. Thinking images is not the same as thinking of images. For thinking images is the act of preparing precise descriptions that control the machinic materialization of images. This kind of activity is a case of algorithmic thinking which, in turn, has become an important general aspect of current society. Art education may play an important role in establishing concrete connections between open artistic and more confined technological ways of thinking when thinking pro-gresses algorithmically

The Noetic Prism

Definitions of ‘knowledge’ and its relationships with ‘data’ and ‘information’ are varied, inconsistent and often contradictory. In particular the traditional hierarchy of data-information-knowledge and its various revisions do not stand up to close scrutiny. We suggest that the problem lies in a flawed analysis that sees data, information and knowledge as separable concepts that are transformed into one another through processing. We propose instead that we can describe collectively all of the materials of computation as ‘noetica’, and that the terms data, information and knowledge can be reconceptualised as late-binding, purpose-determined aspects of the same body of material. Changes in complexity of noetica occur due to value-adding through the imposition of three different principles: increase in aggregation (granularity), increase in set relatedness (shape), and increase in contextualisation through the formation of networks (scope). We present a new model in which granularity, shape and scope are seen as the three vertices of a triangular prism, and show that all value-adding through computation can be seen as movement within the prism space. We show how the conceptual framework of the noetic prism provides a new and comprehensive analysis of the foundations of computing and information systems, and how it can provide a fresh analysis of many of the common problems in the management of intellectual resources