Are There Biomimetic Lessons from Genetic Regulatory Networks for Developing a Lunar Industrial Ecology?
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Glossary Glossary
Glossary Glossary Albedo A measure of an object’s reflectivity. A pure white reflecting surface has an albedo of 1.0 (100%). A pitch-black, nonreflecting surface has an albedo of 0.0. The Moon is a fairly dark object with a combined albedo of 0.07 (reflecting 7% of the sunlight that falls upon it). The albedo range of the lunar maria is between 0.05 and 0.08. The brighter highlands have an albedo range from 0.09 to 0.15. Anorthosite Rocks rich in the mineral feldspar, making up much of the Moon’s bright highland regions. Aperture The diameter of a telescope’s objective lens or primary mirror. Apogee The point in the Moon’s orbit where it is furthest from the Earth. At apogee, the Moon can reach a maximum distance of 406,700 km from the Earth. Apollo The manned lunar program of the United States. Between July 1969 and December 1972, six Apollo missions landed on the Moon, allowing a total of 12 astronauts to explore its surface. Asteroid A minor planet. A large solid body of rock in orbit around the Sun. Banded crater A crater that displays dusky linear tracts on its inner walls and/or floor. 250 Basalt A dark, fine-grained volcanic rock, low in silicon, with a low viscosity. Basaltic material fills many of the Moon’s major basins, especially on the near side. Glossary Basin A very large circular impact structure (usually comprising multiple concentric rings) that usually displays some degree of flooding with lava. The largest and most conspicuous lava- flooded basins on the Moon are found on the near side, and most are filled to their outer edges with mare basalts. -
Transformations of Lamarckism Vienna Series in Theoretical Biology Gerd B
Transformations of Lamarckism Vienna Series in Theoretical Biology Gerd B. M ü ller, G ü nter P. Wagner, and Werner Callebaut, editors The Evolution of Cognition , edited by Cecilia Heyes and Ludwig Huber, 2000 Origination of Organismal Form: Beyond the Gene in Development and Evolutionary Biology , edited by Gerd B. M ü ller and Stuart A. Newman, 2003 Environment, Development, and Evolution: Toward a Synthesis , edited by Brian K. Hall, Roy D. Pearson, and Gerd B. M ü ller, 2004 Evolution of Communication Systems: A Comparative Approach , edited by D. Kimbrough Oller and Ulrike Griebel, 2004 Modularity: Understanding the Development and Evolution of Natural Complex Systems , edited by Werner Callebaut and Diego Rasskin-Gutman, 2005 Compositional Evolution: The Impact of Sex, Symbiosis, and Modularity on the Gradualist Framework of Evolution , by Richard A. Watson, 2006 Biological Emergences: Evolution by Natural Experiment , by Robert G. B. Reid, 2007 Modeling Biology: Structure, Behaviors, Evolution , edited by Manfred D. Laubichler and Gerd B. M ü ller, 2007 Evolution of Communicative Flexibility: Complexity, Creativity, and Adaptability in Human and Animal Communication , edited by Kimbrough D. Oller and Ulrike Griebel, 2008 Functions in Biological and Artifi cial Worlds: Comparative Philosophical Perspectives , edited by Ulrich Krohs and Peter Kroes, 2009 Cognitive Biology: Evolutionary and Developmental Perspectives on Mind, Brain, and Behavior , edited by Luca Tommasi, Mary A. Peterson, and Lynn Nadel, 2009 Innovation in Cultural Systems: Contributions from Evolutionary Anthropology , edited by Michael J. O ’ Brien and Stephen J. Shennan, 2010 The Major Transitions in Evolution Revisited , edited by Brett Calcott and Kim Sterelny, 2011 Transformations of Lamarckism: From Subtle Fluids to Molecular Biology , edited by Snait B. -
Markov Model Checking of Probabilistic Boolean Networks Representations of Genes
Markov Model Checking of Probabilistic Boolean Networks Representations of Genes Marie Lluberes1, Jaime Seguel2 and Jaime Ramírez-Vick3 1, 2 Electrical and Computer Engineering Department, University of Puerto Rico, Mayagüez, Puerto Rico 3 General Engineering Department, University of Puerto Rico, Mayagüez, Puerto Rico or, on contrary, to prevent or to stop an undesirable Abstract - Our goal is to develop an algorithm for the behavior. This “guiding” of the network dynamics is automated study of the dynamics of Probabilistic Boolean referred to as intervention. The power to intervene with the Network (PBN) representation of genes. Model checking is network dynamics has a significant impact in diagnostics an automated method for the verification of properties on and drug design. systems. Continuous Stochastic Logic (CSL), an extension of Biological phenomena manifest in the continuous-time Computation Tree Logic (CTL), is a model-checking tool domain. But, in describing such phenomena we usually that can be used to specify measures for Continuous-time employ a binary language, for instance, expressed or not Markov Chains (CTMC). Thus, as PBNs can be analyzed in expressed; on or off; up or down regulated. Studies the context of Markov theory, the use of CSL as a method for conducted restricting genes expression to only two levels (0 model checking PBNs could be a powerful tool for the or 1) suggested that information retained by these when simulation of gene network dynamics. Particularly, we are binarized is meaningful to the extent that it is remains in a interested in the subject of intervention. This refers to the continuous domain [2]. -
Online Spectral Clustering on Network Streams Yi
Online Spectral Clustering on Network Streams By Yi Jia Submitted to the graduate degree program in Electrical Engineering and Computer Science and the Graduate Faculty of the University of Kansas in partial fulfillment of the requirements for the degree of Doctor of Philosophy Jun Huan, Chairperson Swapan Chakrabarti Committee members Jerzy Grzymala-Busse Bo Luo Alfred Tat-Kei Ho Date defended: The Dissertation Committee for Yi Jia certifies that this is the approved version of the following dissertation : Online Spectral Clustering on Network Streams Jun Huan, Chairperson Date approved: ii Abstract Graph is an extremely useful representation of a wide variety of practical systems in data analysis. Recently, with the fast accumulation of stream data from various type of networks, significant research interests have arisen on spectral clustering for network streams (or evolving networks). Compared with the general spectral clustering problem, the data analysis of this new type of problems may have additional requirements, such as short processing time, scalability in distributed computing environments, and temporal variation tracking. However, to design a spectral clustering method to satisfy these requirement cer- tainly presents non-trivial efforts. There are three major challenges for the new algorithm design. The first challenge is online clustering computation. Most of the existing spectral methods on evolving networks are off-line methods, using standard eigensystem solvers such as the Lanczos method. It needs to recompute solutions from scratch at each time point. The second challenge is the paralleliza- tion of algorithms. To parallelize such algorithms is non-trivial since standard eigen solvers are iterative algorithms and the number of iterations can not be pre- determined. -
Inference of a Probabilistic Boolean Network from a Single Observed Temporal Sequence
Hindawi Publishing Corporation EURASIP Journal on Bioinformatics and Systems Biology Volume 2007, Article ID 32454, 15 pages doi:10.1155/2007/32454 Research Article Inference of a Probabilistic Boolean Network from a Single Observed Temporal Sequence Stephen Marshall,1 Le Yu,1 Yufei Xiao,2 and Edward R. Dougherty2, 3, 4 1 Department of Electronic and Electrical Engineering, Faculty of Engineering, University of Strathclyde, Glasgow, G1 1XW, UK 2 Department of Electrical and Computer Engineering, Texas A&M University, College Station, TX 77843-3128, USA 3 Computational Biology Division, Translational Genomics Research Institute, Phoenix, AZ 85004, USA 4 Department of Pathology, University of Texas M. D. Anderson Cancer Center, Houston, TX 77030, USA Received 10 July 2006; Revised 29 January 2007; Accepted 26 February 2007 Recommended by Tatsuya Akutsu The inference of gene regulatory networks is a key issue for genomic signal processing. This paper addresses the inference of proba- bilistic Boolean networks (PBNs) from observed temporal sequences of network states. Since a PBN is composed of a finite number of Boolean networks, a basic observation is that the characteristics of a single Boolean network without perturbation may be de- termined by its pairwise transitions. Because the network function is fixed and there are no perturbations, a given state will always be followed by a unique state at the succeeding time point. Thus, a transition counting matrix compiled over a data sequence will be sparse and contain only one entry per line. If the network also has perturbations, with small perturbation probability, then the transition counting matrix would have some insignificant nonzero entries replacing some (or all) of the zeros. -
Dynamics of Information As Natural Computation
Information 2011, 2, 460-477; doi:10.3390/info2030460 OPEN ACCESS information ISSN 2078-2489 www.mdpi.com/journal/information Article Dynamics of Information as Natural Computation Gordana Dodig Crnkovic Mälardalen University, School of Innovation, Design and Engineering, Sweden; E-Mail: [email protected] Received: 30 May 2011; in revised form: 13 July 2011 / Accepted: 19 July 2011 / Published: 4 August 2011 Abstract: Processes considered rendering information dynamics have been studied, among others in: questions and answers, observations, communication, learning, belief revision, logical inference, game-theoretic interactions and computation. This article will put the computational approaches into a broader context of natural computation, where information dynamics is not only found in human communication and computational machinery but also in the entire nature. Information is understood as representing the world (reality as an informational web) for a cognizing agent, while information dynamics (information processing, computation) realizes physical laws through which all the changes of informational structures unfold. Computation as it appears in the natural world is more general than the human process of calculation modeled by the Turing machine. Natural computing is epitomized through the interactions of concurrent, in general asynchronous computational processes which are adequately represented by what Abramsky names “the second generation models of computation” [1] which we argue to be the most general representation of information dynamics. Keywords: philosophy of information; information semantics; information dynamics; natural computationalism; unified theories of information; info-computationalism 1. Introduction This paper has several aims. Firstly, it offers a computational interpretation of information dynamics of the info-computational universe [2,3]. -
The Life-Cycle of Operons
Lawrence Berkeley National Laboratory Lawrence Berkeley National Laboratory Title The Life-cycle of Operons Permalink https://escholarship.org/uc/item/0sx114h9 Authors Price, Morgan N. Arkin, Adam P. Alm, Eric J. Publication Date 2005-11-18 Peer reviewed eScholarship.org Powered by the California Digital Library University of California Title: The Life-cycle of Operons Authors: Morgan N. Price, Adam P. Arkin, and Eric J. Alm Author a±liation: Lawrence Berkeley Lab, Berkeley CA, USA and the Virtual Institute for Microbial Stress and Survival. A.P.A. is also a±liated with the Howard Hughes Medical Institute and the UC Berkeley Dept. of Bioengineering. Corresponding author: Eric Alm, [email protected], phone 510-486-6899, fax 510-486-6219, address Lawrence Berkeley National Lab, 1 Cyclotron Road, Mailstop 977-152, Berkeley, CA 94720 Abstract: Operons are a major feature of all prokaryotic genomes, but how and why operon structures vary is not well understood. To elucidate the life-cycle of operons, we compared gene order between Escherichia coli K12 and its relatives and identi¯ed the recently formed and destroyed operons in E. coli. This allowed us to determine how operons form, how they become closely spaced, and how they die. Our ¯ndings suggest that operon evolution is driven by selection on gene expression patterns. First, both operon creation and operon destruction lead to large changes in gene expression patterns. For example, the removal of lysA and ruvA from ancestral operons that contained essential genes allowed their expression to respond to lysine levels and DNA damage, respectively. Second, some operons have undergone accelerated evolution, with multiple new genes being added during a brief period. -
Boolean Network Control with Ideals
Portland State University PDXScholar Mathematics and Statistics Faculty Fariborz Maseeh Department of Mathematics Publications and Presentations and Statistics 1-2021 Boolean Network Control with Ideals Ian H. Dinwoodie Portland State University, [email protected] Follow this and additional works at: https://pdxscholar.library.pdx.edu/mth_fac Part of the Physical Sciences and Mathematics Commons Let us know how access to this document benefits ou.y Citation Details Dinwoodie, Ian H., "Boolean Network Control with Ideals" (2021). Mathematics and Statistics Faculty Publications and Presentations. 302. https://pdxscholar.library.pdx.edu/mth_fac/302 This Working Paper is brought to you for free and open access. It has been accepted for inclusion in Mathematics and Statistics Faculty Publications and Presentations by an authorized administrator of PDXScholar. Please contact us if we can make this document more accessible: [email protected]. Boolean Network Control with Ideals I H Dinwoodie Portland State University January 2021 Abstract A method is given for finding controls to transition an initial state x0 to a target set in deterministic or stochastic Boolean network control models. The algorithms use multivariate polynomial algebra. Examples illustrate the application. 1 Introduction A Boolean network is a dynamical system on d nodes (or coordinates) with binary node values, and with transition map F : {0, 1}d → {0, 1}d. The c coordinate maps F = (f1,...,fd) may use binary parameters u ∈ {0, 1} that can be adjusted or controlled at each step, so the image can be writ- ten F (x, u) and F takes {0, 1}d+c → {0, 1}d, usually written in logical nota- tion. -
Natural Computing Conclusion
Introduction Natural Computing Conclusion Natural Computing Dr Giuditta Franco Department of Computer Science, University of Verona, Italy [email protected] For the logistics of the course, please see the syllabus Dr Giuditta Franco Slides Natural Computing 2017 Introduction Natural Computing Natural Computing Conclusion Natural Computing Natural (complex) systems work as (biological) information elaboration systems, by sophisticated mechanisms of goal-oriented control, coordination, organization. Computational analysis (mat modeling) of life is important as observing birds for designing flying objects. "Informatics studies information and computation in natural and artificial systems” (School of Informatics, Univ. of Edinburgh) Computational processes observed in and inspired by nature. Ex. self-assembly, AIS, DNA computing Ex. Internet of things, logics, programming, artificial automata are not natural computing. Dr Giuditta Franco Slides Natural Computing 2017 Introduction Natural Computing Natural Computing Conclusion Bioinformatics versus Infobiotics Applying statistics, performing tools, high technology, large databases, to analyze bio-logical/medical data, solve problems, formalize/frame natural phenomena. Ex. search algorithms to recover genomic/proteomic data, to process them, catalogue and make them publically accessible, to infer models to simulate their dynamics. Identifying informational mechanisms underlying living systems, how they assembled and work, how biological information may be defined, processed, decoded. New -
A Computational Model Inspired by Gene Regulatory Networks
Rui Miguel Lourenço Lopes A Computational Model Inspired by Gene Regulatory Networks Doctoral thesis submitted to the Doctoral Program in Information Science and Technology, supervised by Full Professor Doutor Ernesto Jorge Fernandes Costa, and presented to the Department of Informatics Engineering of the Faculty of Sciences and Technology of the University of Coimbra. January 2015 A Computational Model Inspired by Gene Regulatory Networks A thesis submitted to the University of Coimbra in partial fulfillment of the requirements for the Doctoral Program in Information Science and Technology by Rui Miguel Lourenço Lopes [email protected] Department of Informatics Engineering Faculty of Sciences and Technology University of Coimbra Coimbra, January 2015 Financial support by Fundação para a Ciência e a Tecnologia, through the PhD grant SFRH/BD/69106/2010. A Computational Model Inspired by Gene Regulatory Networks ©2015 Rui L. Lopes ISBN 978-989-20-5460-5 Cover image: Composition of a Santa Fe trail program evolved by ReNCoDe overlaid on the ancestors, with a 3D model of the DNA crystal structure (by Paul Hakimata). This dissertation was prepared under the supervision of Ernesto J. F. Costa Full Professor of the Department of Informatics Engineering of the Faculty of Sciences and Tecnology of the University of Coimbra In loving memory of my father. Acknowledgements Thank you very much to Prof. Ernesto Costa, for his vision on research and education, for all the support and contributions to my ideas, and for the many life stories that always lighten the mood. Thank you also to Nuno Lourenço for the many discussions, shared books, and his constant helpfulness. -
Historical Painting Techniques, Materials, and Studio Practice
Historical Painting Techniques, Materials, and Studio Practice PUBLICATIONS COORDINATION: Dinah Berland EDITING & PRODUCTION COORDINATION: Corinne Lightweaver EDITORIAL CONSULTATION: Jo Hill COVER DESIGN: Jackie Gallagher-Lange PRODUCTION & PRINTING: Allen Press, Inc., Lawrence, Kansas SYMPOSIUM ORGANIZERS: Erma Hermens, Art History Institute of the University of Leiden Marja Peek, Central Research Laboratory for Objects of Art and Science, Amsterdam © 1995 by The J. Paul Getty Trust All rights reserved Printed in the United States of America ISBN 0-89236-322-3 The Getty Conservation Institute is committed to the preservation of cultural heritage worldwide. The Institute seeks to advance scientiRc knowledge and professional practice and to raise public awareness of conservation. Through research, training, documentation, exchange of information, and ReId projects, the Institute addresses issues related to the conservation of museum objects and archival collections, archaeological monuments and sites, and historic bUildings and cities. The Institute is an operating program of the J. Paul Getty Trust. COVER ILLUSTRATION Gherardo Cibo, "Colchico," folio 17r of Herbarium, ca. 1570. Courtesy of the British Library. FRONTISPIECE Detail from Jan Baptiste Collaert, Color Olivi, 1566-1628. After Johannes Stradanus. Courtesy of the Rijksmuseum-Stichting, Amsterdam. Library of Congress Cataloguing-in-Publication Data Historical painting techniques, materials, and studio practice : preprints of a symposium [held at] University of Leiden, the Netherlands, 26-29 June 1995/ edited by Arie Wallert, Erma Hermens, and Marja Peek. p. cm. Includes bibliographical references. ISBN 0-89236-322-3 (pbk.) 1. Painting-Techniques-Congresses. 2. Artists' materials- -Congresses. 3. Polychromy-Congresses. I. Wallert, Arie, 1950- II. Hermens, Erma, 1958- . III. Peek, Marja, 1961- ND1500.H57 1995 751' .09-dc20 95-9805 CIP Second printing 1996 iv Contents vii Foreword viii Preface 1 Leslie A. -
Glossary of Lunar Terminology
Glossary of Lunar Terminology albedo A measure of the reflectivity of the Moon's gabbro A coarse crystalline rock, often found in the visible surface. The Moon's albedo averages 0.07, which lunar highlands, containing plagioclase and pyroxene. means that its surface reflects, on average, 7% of the Anorthositic gabbros contain 65-78% calcium feldspar. light falling on it. gardening The process by which the Moon's surface is anorthosite A coarse-grained rock, largely composed of mixed with deeper layers, mainly as a result of meteor calcium feldspar, common on the Moon. itic bombardment. basalt A type of fine-grained volcanic rock containing ghost crater (ruined crater) The faint outline that remains the minerals pyroxene and plagioclase (calcium of a lunar crater that has been largely erased by some feldspar). Mare basalts are rich in iron and titanium, later action, usually lava flooding. while highland basalts are high in aluminum. glacis A gently sloping bank; an old term for the outer breccia A rock composed of a matrix oflarger, angular slope of a crater's walls. stony fragments and a finer, binding component. graben A sunken area between faults. caldera A type of volcanic crater formed primarily by a highlands The Moon's lighter-colored regions, which sinking of its floor rather than by the ejection of lava. are higher than their surroundings and thus not central peak A mountainous landform at or near the covered by dark lavas. Most highland features are the center of certain lunar craters, possibly formed by an rims or central peaks of impact sites.