Thesis Speciation in Digital Organisms
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The Pandemic Exposes Human Nature: 10 Evolutionary Insights PERSPECTIVE Benjamin M
PERSPECTIVE The pandemic exposes human nature: 10 evolutionary insights PERSPECTIVE Benjamin M. Seitza,1, Athena Aktipisb, David M. Bussc, Joe Alcockd, Paul Bloome, Michele Gelfandf, Sam Harrisg, Debra Liebermanh, Barbara N. Horowitzi,j, Steven Pinkerk, David Sloan Wilsonl, and Martie G. Haseltona,1 Edited by Michael S. Gazzaniga, University of California, Santa Barbara, CA, and approved September 16, 2020 (received for review June 9, 2020) Humans and viruses have been coevolving for millennia. Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2, the virus that causes COVID-19) has been particularly successful in evading our evolved defenses. The outcome has been tragic—across the globe, millions have been sickened and hundreds of thousands have died. Moreover, the quarantine has radically changed the structure of our lives, with devastating social and economic consequences that are likely to unfold for years. An evolutionary per- spective can help us understand the progression and consequences of the pandemic. Here, a diverse group of scientists, with expertise from evolutionary medicine to cultural evolution, provide insights about the pandemic and its aftermath. At the most granular level, we consider how viruses might affect social behavior, and how quarantine, ironically, could make us susceptible to other maladies, due to a lack of microbial exposure. At the psychological level, we describe the ways in which the pandemic can affect mating behavior, cooperation (or the lack thereof), and gender norms, and how we can use disgust to better activate native “behavioral immunity” to combat disease spread. At the cultural level, we describe shifting cultural norms and how we might harness them to better combat disease and the negative social consequences of the pandemic. -
Natural Selection Plays an Important Role in Shaping the Codon Usage of Structural Genes of the Viruses Belonging to the Coronaviridae Family
viruses Article Natural Selection Plays an Important Role in Shaping the Codon Usage of Structural Genes of the Viruses Belonging to the Coronaviridae Family Dimpal A. Nyayanit 1,†, Pragya D. Yadav 1,† , Rutuja Kharde 1 and Sarah Cherian 2,* 1 Maximum Containment Facility, ICMR-National Institute of Virology, Sus Road, Pashan, Pune 411021, India; [email protected] (D.A.N.); [email protected] (P.D.Y.); [email protected] (R.K.) 2 Bioinformatics Group, ICMR-National Institute of Virology, Pune 411001, India * Correspondence: [email protected] or [email protected]; Tel.: +91-20-260061213 † These authors equally contributed to this work. Abstract: Viruses belonging to the Coronaviridae family have a single-stranded positive-sense RNA with a poly-A tail. The genome has a length of ~29.9 kbps, which encodes for genes that are essential for cell survival and replication. Different evolutionary constraints constantly influence the codon usage bias (CUB) of different genes. A virus optimizes its codon usage to fit the host environment on which it savors. This study is a comprehensive analysis of the CUB for the different genes encoded by viruses of the Coronaviridae family. Different methods including relative synonymous codon usage (RSCU), an Effective number of codons (ENc), parity plot 2, and Neutrality plot, were adopted to analyze the factors responsible for the genetic evolution of the Coronaviridae family. Base composition and RSCU analyses demonstrated the presence of A-ended and U-ended codons being preferred in the 3rd codon position and are suggestive of mutational selection. The lesser ENc value for the spike ‘S’ gene suggests a higher bias in the codon usage of this gene compared to the other structural Citation: Nyayanit, D.A.; Yadav, P.D.; genes. -
Guiding Organic Management in a Service-Oriented Real-Time Middleware Architecture
Guiding Organic Management in a Service-Oriented Real-Time Middleware Architecture Manuel Nickschas and Uwe Brinkschulte Institute for Computer Science University of Frankfurt, Germany {nickschas, brinks}@es.cs.uni-frankfurt.de Abstract. To cope with the ever increasing complexity of today's com- puting systems, the concepts of organic and autonomic computing have been devised. Organic or autonomic systems are characterized by so- called self-X properties such as self-conguration and self-optimization. This approach is particularly interesting in the domain of distributed, embedded, real-time systems. We have already proposed a service-ori- ented middleware architecture for such systems that uses multi-agent principles for implementing the organic management. However, organic management needs some guidance in order to take dependencies between services into account as well as the current hardware conguration and other application-specic knowledge. It is important to allow the appli- cation developer or system designer to specify such information without having to modify the middleware. In this paper, we propose a generic mechanism based on capabilities that allows describing such dependen- cies and domain knowledge, which can be combined with an agent-based approach to organic management in order to realize self-X properties. We also describe how to make use of this approach for integrating the middleware's organic management with node-local organic management. 1 Introduction Distributed, embedded systems are rapidly advancing in all areas of our lives, forming increasingly complex networks that are increasingly hard to handle for both system developers and maintainers. In order to cope with this explosion of complexity, also commonly referred to as the Software Crisis [1], the concepts of Autonomic [2,3] and Organic [4,5,6] Computing have been devised. -
Organic Computing Doctoral Dissertation Colloquium 2018 B
13 13 S. Tomforde | B. Sick (Eds.) Organic Computing Doctoral Dissertation Colloquium 2018 Organic Computing B. Sick (Eds.) B. | S. Tomforde S. Tomforde ISBN 978-3-7376-0696-7 9 783737 606967 V`:%$V$VGVJ 0QJ `Q`8 `8 V`J.:`R 1H@5 J10V`1 ? :VC Organic Computing Doctoral Dissertation Colloquium 2018 S. Tomforde, B. Sick (Editors) !! ! "#$%&'&$'$(&)(#(&$* + "#$%&'&$'$(&)(#$&,*&+ - .! ! /)!/#0// 12#$%'$'$()(#$, 23 & ! )))0&,)(#$' '0)/#5 6 7851 999!& ! kassel university press 7 6 Preface The Organic Computing Doctoral Dissertation Colloquium (OC-DDC) series is part of the Organic Computing initiative [9, 10] which is steered by a Special Interest Group of the German Society of Computer Science (Gesellschaft fur¨ Informatik e.V.). It provides an environment for PhD students who have their research focus within the broader Organic Computing (OC) community to discuss their PhD project and current trends in the corresponding research areas. This includes, for instance, research in the context of Autonomic Computing [7], ProActive Computing [11], Complex Adaptive Systems [8], Self-Organisation [2], and related topics. The main goal of the colloquium is to foster excellence in OC-related research by providing feedback and advice that are particularly relevant to the students’ studies and ca- reer development. Thereby, participants are involved in all stages of the colloquium organisation and the review process to gain experience. The OC-DDC 2018 took place in -
Evolutionary Pressure in Lexicase Selection Jared M
When Specialists Transition to Generalists: Evolutionary Pressure in Lexicase Selection Jared M. Moore1 and Adam Stanton2 1School of Computing and Information Systems, Grand Valley State University, Allendale, MI, USA 2School of Computing and Mathematics, Keele University, Keele, ST5 5BG, UK [email protected], [email protected] Abstract Downloaded from http://direct.mit.edu/isal/proceedings-pdf/isal2020/32/719/1908636/isal_a_00254.pdf by guest on 02 October 2021 Generalized behavior is a long standing goal for evolution- ary robotics. Behaviors for a given task should be robust to perturbation and capable of operating across a variety of envi- ronments. We have previously shown that Lexicase selection evolves high-performing individuals in a semi-generalized wall crossing task–i.e., where the task is broadly the same, but there is variation between individual instances. Further Figure 1: The wall crossing task examined in this study orig- work has identified effective parameter values for Lexicase inally introduced in Stanton and Channon (2013). The ani- selection in this domain but other factors affecting and ex- plaining performance remain to be identified. In this paper, mat must cross a wall of varying height to reach the target we expand our prior investigations, examining populations cube. over evolutionary time exploring other factors that might lead wall-crossing task (Moore and Stanton, 2018). Two key to generalized behavior. Results show that genomic clusters factors contributing to the success of Lexicase were iden- do not correspond to performance, indicating that clusters of specialists do not form within the population. While early tified. First, effective Lexicase parameter configurations ex- individuals gain a foothold in the selection process by spe- perience an increasing frequency of tiebreaks. -
Teaching and Learning with Digital Evolution: Factors Influencing Implementation and Student Outcomes
TEACHING AND LEARNING WITH DIGITAL EVOLUTION: FACTORS INFLUENCING IMPLEMENTATION AND STUDENT OUTCOMES By Amy M Lark A DISSERTATION Submitted to Michigan State University in partial fulfillment of the requirements for the degree of Curriculum, Instruction, and Teacher Education – Doctor of Philosophy 2014 ABSTRACT TEACHING AND LEARNING WITH DIGITAL EVOLUTION: FACTORS INFLUENCING IMPLEMENTATION AND STUDENT OUTCOMES By Amy M Lark Science literacy for all Americans has been the rallying cry of science education in the United States for decades. Regardless, Americans continue to fall short when it comes to keeping pace with other developed nations on international science education assessments. To combat this problem, recent national reforms have reinvigorated the discussion of what and how we should teach science, advocating for the integration of disciplinary core ideas, crosscutting concepts, and science practices. In the biological sciences, teaching the core idea of evolution in ways consistent with reforms is fraught with challenges. Not only is it difficult to observe biological evolution in action, it is nearly impossible to engage students in authentic science practices in the context of evolution. One way to overcome these challenges is through the use of evolving populations of digital organisms. Avida-ED is digital evolution software for education that allows for the integration of science practice and content related to evolution. The purpose of this study was to investigate the effects of Avida-ED on teaching and learning evolution and the nature of science. To accomplish this I conducted a nationwide, multiple-case study, documenting how instructors at various institutions were using Avida-ED in their classrooms, factors influencing implementation decisions, and effects on student outcomes. -
Network Complexity of Foodwebs
Network Complexity of Foodwebs Russell Standish School of Mathematics and Statistics, University of New South Wales Abstract Complexity as Information The notion of using information content as a complexity In previous work, I have developed an information theoretic measure is fairly simple. In most cases, there is an ob- complexity measure of networks. When applied to several vious prefix-free representation language within which de- real world food webs, there is a distinct difference in com- plexity between the real food web, and randomised control scriptions of the objects of interest can be encoded. There networks obtained by shuffling the network links. One hy- is also a classifier of descriptions that can determine if two pothesis is that this complexity surplus represents informa- descriptions correspond to the same object. This classifier is tion captured by the evolutionary process that generated the commonly called the observer, denoted O(x). network. To compute the complexity of some object x, count the In this paper, I test this idea by applying the same complex- number of equivalent descriptions ω(ℓ, x) of length ℓ that ity measure to several well-known artificial life models that map to the object x under the agreed classifier. Then the exhibit ecological networks: Tierra, EcoLab and Webworld. Contrary to what was found in real networks, the artificial life complexity of x is given in the limit as ℓ → ∞: generated foodwebs had little information difference between C(x) = lim ℓ log N − log ω(ℓ, x) (1) itself and randomly shuffled versions. ℓ→∞ where N is the size of the alphabet used for the representa- Introduction tion language. -
Evolutionary Rate Covariation in Meiotic Proteins Results from Fluctuating Evolutionary Pressure in Yeasts and Mammals
Genetics: Advance Online Publication, published on November 26, 2012 as 10.1534/genetics.112.145979 Clark 1 Evolutionary rate covariation in meiotic proteins results from fluctuating evolutionary pressure in yeasts and mammals Nathan L. Clark*, Eric Alani§, and Charles F. Aquadro§ * Department of Computational and Systems Biology University of Pittsburgh Pittsburgh, Pennsylvania 15260, USA § Department of Molecular Biology and Genetics Cornell University Ithaca, New York 14853, USA Running head: Rate covariation in meiotic proteins Key words: coevolution, correlated evolution, evolutionary rate, meiosis, mismatch repair Corresponding Author: Nathan L. Clark 3501 Fifth Avenue Biomedical Science Tower 3 Suite 3083 Dept. of Computational and Systems Biology University of Pittsburgh Pittsburgh, PA 15260 phone: (412) 648-7785 fax: (412) 648-3163 email: [email protected] Copyright 2012. Clark 2 ABSTRACT Evolutionary rates of functionally related proteins tend to change in parallel over evolutionary time. Such evolutionary rate covariation (ERC) is a sequence-based signature of coevolution and a potentially useful signature to infer functional relationships between proteins. One major hypothesis to explain ERC is that fluctuations in evolutionary pressure acting on entire pathways cause parallel rate changes for functionally related proteins. To explore this hypothesis we analyzed ERC within DNA mismatch repair (MMR) and meiosis proteins over phylogenies of 18 yeast species and 22 mammalian species. We identified a strong signature of ERC between eight yeast proteins involved in meiotic crossing over, which seems to have resulted from relaxation of constraint specifically in Candida glabrata. These and other meiotic proteins in C. glabrata showed marked rate acceleration, likely due to its apparently clonal reproductive strategy and the resulting infrequent use of meiotic proteins. -
Evolving Quorum Sensing in Digital Organisms
Evolving Quorum Sensing in Digital Organisms Benjamin E. Beckmann and Phillip K. McKinley Department of Computer Science and Engineering 3115 Engineering Building Michigan State University East Lansing, Michigan 48824 {beckma24,mckinley}@cse.msu.edu ABSTRACT 1. INTRODUCTION For centuries it was thought that bacteria live asocial lives. The human body is made up of 1013 human cells. Yet, However, recent discoveries show many species of bacteria this number is an order of magnitude smaller than the num- communicate in order to perform tasks previously thought ber a bacterial cells living within the gastrointestinal tract to be limited to multicellular organisms. Central to this ca- of a single adult [4]. Although it was previously assumed pability is quorum sensing, whereby organisms detect cell that bacteria and other microorganisms rarely interact [24], density and use this information to trigger group behav- in 1979 Nealson and Hastings found evidence that bacterial iors. Quorum sensing is used by bacteria in the formation communities of Vibrio fischeri and Vibrio harveyi were able of biofilms, secretion of digestive enzymes and, in the case to perform a coordinated behavioral change, namely emit- of pathogenic bacteria, release of toxins or other virulence ting light, when the cell density rose above a certain thresh- factors. Indeed, methods to disrupt quorum sensing are cur- old [20]. This type of density-based behavioral change is rently being investigated as possible treatments for numer- called quorum sensing [27]. In quorum sensing (QS), con- ous diseases, including cystic fibrosis, epidemic cholera, and tinual secretion and detection of chemicals provide a way methicillin-resistant Staphylococcus aureus. -
Fire As an Evolutionary Pressure Shaping Plant Traits
Opinion Fire as an evolutionary pressure shaping plant traits Jon E. Keeley1,2, Juli G. Pausas3, Philip W. Rundel2, William J. Bond4 and Ross A. Bradstock5 1 US Geological Survey, Sequoia-Kings Canyon Field Station, Three Rivers, CA 93271, USA 2 Department of Ecology and Evolutionary Biology, University of California, Los Angeles, CA 90095, USA 3 Centro de Investigaciones sobre Desertificacio´n of the Spanish National Research Council (CIDE - CSIC), IVIA campus, 46113 Montcada, Valencia, Spain 4 Botany Department, University of Cape Town, Private Bag, Rondebosch 7701, South Africa 5 Centre for Environmental Risk Management of Bushfires, University of Wollongong, Wollongong, NSW 2522, Australia Traits, such as resprouting, serotiny and germination by parent adaptive value in fire-prone environments and the heat and smoke, are adaptive in fire-prone environ- extent to which we can demonstrate that they are adapta- ments. However, plants are not adapted to fire per se tions to fire. We also address the question of what fire- but to fire regimes. Species can be threatened when adaptive traits and fire adaptations can tell us about fire humans alter the regime, often by increasing or decreas- management. ing fire frequency. Fire-adaptive traits are potentially the result of different evolutionary pathways. Distinguishing Adaptive traits between traits that are adaptations originating in re- Adaptive traits are those that provide a fitness advantage sponse to fire or exaptations originating in response in a given environment. There are many plant traits that to other factors might not always be possible. However, are of adaptive value in the face of recurrent fire and these fire has been a factor throughout the history of land- vary markedly with fire regime. -
Digital Irreducible Complexity: a Survey of Irreducible Complexity in Computer Simulations
Critical Focus Digital Irreducible Complexity: A Survey of Irreducible Complexity in Computer Simulations Winston Ewert* Biologic Institute, Redmond, Washington, USA Abstract Irreducible complexity is a concept developed by Michael Behe to describe certain biological systems. Behe claims that irreducible complexity poses a challenge to Darwinian evolution. Irreducibly complex systems, he argues, are highly unlikely to evolve because they have no direct series of selectable intermediates. Various computer models have been published that attempt to demonstrate the evolution of irreducibly complex systems and thus falsify this claim. How- ever, closer inspection of these models shows that they fail to meet the definition of irreducible complexity in a num- ber of ways. In this paper we demonstrate how these models fail. In addition, we present another designed digital sys- tem that does exhibit designed irreducible complexity, but that has not been shown to be able to evolve. Taken together, these examples indicate that Behe’s concept of irreducible complexity has not been falsified by computer models. Cite as: Ewert W (2014) Digital irreducible complexity: A survey of irreducible complexity in computer simulations. BIO-Complexity 2014 (1):1–10. doi:10.5048/BIO-C.2014.1. Editor: Ola Hössjer Received: November 16, 2013; Accepted: February 18, 2014; Published: April 5, 2014 Copyright: © 2014 Ewert. This open-access article is published under the terms of the Creative Commons Attribution License, which permits free distribution and reuse in derivative works provided the original author(s) and source are credited. Notes: A Critique of this paper, when available, will be assigned doi:10.5048/BIO-C.2014.1.c. -
Applying Evolutionary Computation to Mitigate Uncertainty in Dynamically-Adaptive, High-Assurance Middleware
J Internet Serv Appl (2012) 3:51–58 DOI 10.1007/s13174-011-0049-4 SI: FOME - THE FUTURE OF MIDDLEWARE Applying evolutionary computation to mitigate uncertainty in dynamically-adaptive, high-assurance middleware Philip K. McKinley · Betty H.C. Cheng · Andres J. Ramirez · Adam C. Jensen Received: 31 October 2011 / Accepted: 12 November 2011 / Published online: 3 December 2011 © The Brazilian Computer Society 2011 Abstract In this paper, we explore the integration of evolu- systems need to perform complex, distributed tasks despite tionary computation into the development and run-time sup- lossy wireless communication, limited resources, and uncer- port of dynamically-adaptable, high-assurance middleware. tainty in sensing the environment. However, even systems The open-ended nature of the evolutionary process has been that operate entirely within cyberspace need to account for shown to discover novel solutions to complex engineering changing network and load conditions, component failures, problems. In the case of high-assurance adaptive software, and exposure to a wide variety of cyber attacks. however, this search capability must be coupled with rigor- A dynamically adaptive system (DAS) monitors itself and ous development tools and run-time support to ensure that its execution environment at run time. This monitoring en- the resulting systems behave in accordance with require- ables a DAS not only to detect conditions warranting a re- ments. Early investigations are reviewed, and several chal- configuration, but also to determine when and how to safely lenging problems and possible research directions are dis- reconfigure itself in order to deliver acceptable behavior be- cussed. fore, during, and after adaptation [2].