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Готові списки джерел за темами / Evolution of developmental systems

Добірка наукової літератури з теми "Evolution of developmental systems"

Автор: Grafiati

Опубліковано: 10 грудня 2022

Оновлено: 19 лютого 2023

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Статті в журналах з теми "Evolution of developmental systems"

1

SHIGENO, SHUICHI. "I-5. Nervous systems and developmental evolution." NIPPON SUISAN GAKKAISHI 80, no. 2 (2014): 246. http://dx.doi.org/10.2331/suisan.80.246.

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2

Rushton, J. Philippe. "The ontogeny of information: Developmental systems and evolution." Personality and Individual Differences 8, no. 4 (1987): 597. http://dx.doi.org/10.1016/0191-8869(87)90230-3.

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3

Wereha, Tyler J., and Timothy P. Racine. "A systems view on revenge and forgiveness systems." Behavioral and Brain Sciences 36, no. 1 (December 5, 2012): 39. http://dx.doi.org/10.1017/s0140525x12000611.

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AbstractApplying a non-developmental evolutionary metatheory to understanding the evolution of psychological capacities leads to the creation of models that mischaracterize developmental processes, misattribute genes as the source of developmental information, and ignore the myriad developmental and contextual factors involved in human decision-making. Using an evolutionary systems perspective, we argue that revenge and forgiveness cannot be understood apart from the development of foundational human psychological capacities and the contexts under which they develop.

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4

Dickins, Benjamin J. A. "Book Review: Cycles of Contingency: Developmental Systems and Evolution." Evolutionary Psychology 1, no. 1 (January 1, 2003): 147470490300100. http://dx.doi.org/10.1177/147470490300100107.

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5

Downes, Stephen M. "The Ontogeny of Information: Developmental Systems and Evolution (review)." Perspectives in Biology and Medicine 44, no. 3 (2001): 464–69. http://dx.doi.org/10.1353/pbm.2001.0046.

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6

Hackett-Jones, Emily, Andrew White, and Christina A. Cobbold. "The evolution of developmental timing in natural enemy systems." Journal of Theoretical Biology 275, no. 1 (April 2011): 1–11. http://dx.doi.org/10.1016/j.jtbi.2010.12.040.

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7

Griesemer, James, Matthew H. Haber, Grant Yamashita, and Lisa Gannett. "Critical Notice: Cycles of Contingency – Developmental Systems and Evolution." Biology & Philosophy 20, no. 2-3 (March 2005): 517–44. http://dx.doi.org/10.1007/s10539-004-0836-4.

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8

Finlay, Barbara L., Richard B. Darlington, and Nicholas Nicastro. "Developmental structure in brain evolution." Behavioral and Brain Sciences 24, no. 2 (April 2001): 263–78. http://dx.doi.org/10.1017/s0140525x01003958.

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How does evolution grow bigger brains? It has been widely assumed that growth of individual structures and functional systems in response to niche-specific cognitive challenges is the most plausible mechanism for brain expansion in mammals. Comparison of multiple regressions on allometric data for 131 mammalian species, however, suggests that for 9 of 11 brain structures taxonomic and body size factors are less important than covariance of these major structures with each other. Which structure grows biggest is largely predicted by a conserved order of neurogenesis that can be derived from the basic axial structure of the developing brain. This conserved order of neurogenesis predicts the relative scaling not only of gross brain regions like the isocortex or mesencephalon, but also the level of detail of individual thalamic nuclei. Special selection of particular areas for specific functions does occur, but it is a minor factor compared to the large-scale covariance of the whole brain. The idea that enlarged isocortex could be a “spandrel,” a by-product of structural constraints later adapted for various behaviors, contrasts with approaches to selection of particular brain regions for cognitively advanced uses, as is commonly assumed in the case of hominid brain evolution.

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9

Petrinovich, Lewis. "The Ontogeny of Information. Developmental Systems and Evolution. Susan Oyama." Quarterly Review of Biology 62, no. 2 (June 1987): 227–28. http://dx.doi.org/10.1086/415506.

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10

Cauret, Caroline M. S., Marie-Theres Gansauge, Andrew S. Tupper, Benjamin L. S. Furman, Martin Knytl, Xue-Ying Song, Eli Greenbaum, Matthias Meyer, and Ben J. Evans. "Developmental Systems Drift and the Drivers of Sex Chromosome Evolution." Molecular Biology and Evolution 37, no. 3 (November 11, 2019): 799–810. http://dx.doi.org/10.1093/molbev/msz268.

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Abstract Phenotypic invariance—the outcome of purifying selection—is a hallmark of biological importance. However, invariant phenotypes might be controlled by diverged genetic systems in different species. Here, we explore how an important and invariant phenotype—the development of sexually differentiated individuals—is controlled in over two dozen species in the frog family Pipidae. We uncovered evidence in different species for 1) an ancestral W chromosome that is not found in many females and is found in some males, 2) independent losses and 3) autosomal segregation of this W chromosome, 4) changes in male versus female heterogamy, and 5) substantial variation among species in recombination suppression on sex chromosomes. We further provide evidence of, and evolutionary context for, the origins of at least seven distinct systems for regulating sex determination among three closely related genera. These systems are distinct in their genomic locations, evolutionary origins, and/or male versus female heterogamy. Our findings demonstrate that the developmental control of sexual differentiation changed via loss, sidelining, and empowerment of a mechanistically influential gene, and offer insights into novel factors that impinge on the diverse evolutionary fates of sex chromosomes.

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Дисертації з теми "Evolution of developmental systems"

1

Maitland, Kathleen M. "Information systems evolution." Thesis, Open University, 2003. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.289003.

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2

Ryan, Patricia A. "A general model for structural processing in cultural and developmental systems." Virtual Press, 1998. http://liblink.bsu.edu/uhtbin/catkey/1115764.

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Anthropology, and other disciplines have searched for isomorphic principles and rules operating in information systems. This thesis locates and describes this deep structure applicable to all information systems. It presents a model for information flow as a set of ordering principles revealing universal patterns inherent in nature, a set of transformation rules functioning to increase organization and complexity, and a structure for this activity. The model is isomorphic: it demonstrates similar operational behavior in different systems. Major features of the model include polarity, emergent or transformational phenomena, self-organization, and a trajectory traveling through a hierarchical structure representing the flow of information. Polar opposition is the primary functional mechanism, and has two critical roles. It initiates and maintains the trajectory through time and stabilizes the system by representing existence in time. The author applies the model to consciousness, neurogenesis, ontogeny, social behavior, mythology, rites of passage, and other systems.
Department of Anthropology

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3

Nnatuanya, Ifechukwu. "Evolution of living information systems development." Thesis, Brunel University, 2005. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.412796.

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4

Maad, Johanne. "Selection and Floral Evolution in Platanthera bifolia and P. chlorantha (Orchidaceae)." Doctoral thesis, Uppsala : Acta Universitatis Upsaliensis : Univ.-bibl. [distributör], 2002. http://publications.uu.se/theses/91-554-5226-4/.

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5

Marques, Pita Manuel Arturo. "Aitana : a developmental cognitive artifact to explore the evolution of conceptual representations of cellular automata-based complex systems." Thesis, University of Edinburgh, 2006. http://hdl.handle.net/1842/24904.

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This thesis explores cognitive mechanisms that process models of complex systems – represented in their implicit form – in order to produce explicit redescriptions, which reveal knowledge about these models that is not accessible on the implicit level. The aim of this exploration is to support new ways of conceptualising the phenomenon of emergence, the main characterising feature of complex systems in general. The main problem tackled in this thesis concerns the development of representations that support new forms of model conceptualisation. Specifically, the thesis focuses on producing primordial explicit representations (where primordial means that they are not the composition of lower level explicit forms) directly from the implicit levels of knowledge, with the latter being represented in terms of Cellular Automata (CA) rules. Three hypotheses concerning the capabilities of CA redescription mechanisms are tested. The hypotheses state that such mechanisms are able (1) to capture the whole (or most significant) extent of the input implicit representation, (2) to produce redescriptions that are more compact (in terms of dimensionality) than the input representation and (3) to allow (or to provide substrate to allow) the derivation of “knowledge” about what has been learnt – the knowledge that is implicit in the low level representational forms acquired through learning. The hypotheses are tested by means of Aitana – a prototype developed specifically for this purpose. This developmental cognitive artifact is capable of learning implicit models of Cellular Automata that achieve certain pre-specified emergent behaviours, using Genetic Algorithms as its learning mechanism. Once acquired, implicit representations are processed, in order to produce explicit representations. The mechanisms for redescribing CA rules are based on the study of their endogenous spatial properties. In particular, two redescription transducers or modules are implemented in Aitana and explored through a set of case-studies. Aitana’s artificial cognitive development confirms the three hypotheses of this thesis.

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6

Hudson, Corey M. "Informatic approaches to evolutionary systems biology." Thesis, University of Missouri - Columbia, 2014. http://pqdtopen.proquest.com/#viewpdf?dispub=3577951.

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The sheer complexity of evolutionary systems biology requires us to develop more sophisticated tools for analysis, as well as more probing and biologically relevant representations of the data. My research has focused on three aspects of evolutionary systems biology. I ask whether a gene’s position in the human metabolic network affects the degree to which natural selection prunes variation in that gene. Using a novel orthology inference tool that uses both sequence similarity and gene synteny, I inferred orthologous groups of genes for the full genomes of 8 mammals. With these orthologs, I estimated the selective constraint (the ratio of non-synonymous to synonymous nucleotide substitutions) on 1190 (or 80.2%) of the genes in the metabolic network using a maximum likelihood model of codon evolution and compared this value to the betweenness centrality of each enzyme (a measure of that enzyme’s relative global position in the network). Second, I have focused on the evolution of metabolic systems in the presence of gene and genome duplication. I show that increases in a particular gene’s copy number are correlated with limiting metabolic flux in the reaction associated with that gene. Finally, I have investigated the proliferative cell programs present in 6 different cancers (breast, colorectal, gastrointestinal, lung, oral squamous and prostate cancers). I found an overabundance of genes that share expression between cancer and embryonic tissue and that these genes form modular units within regulatory, proteininteraction, and metabolic networks. This despite the fact that these genes, as well as the proteins they encode and reactions they catalyze show little overlap among cancers, suggesting parallel independent reversion to an embryonic pattern of gene expression.

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7

Alhaj, Hussen Kutaiba. "Developmental architecture of human lymphopoiesis." Thesis, Sorbonne Paris Cité, 2016. http://www.theses.fr/2016USPCC308.

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Selon le modèle standard de l'hématopoïèse, la différenciation des cellules souches hématopoïétiques est un processus graduel de type arborescent. La première séparation a lieu au niveau de cellules multipotentes qui se scindent en progéniteurs lymphoïdes et myéloïdes communs. Bien que l'architecture de l'hématopoïèse humaine reste encore mal connue, de nombreux travaux suggèrent qu'elle ne suit pas le modèle standard. À ce jour encore, la question de l'existence d'un équivalent humain du CLP murin, n'a pas été tranchée. L'étude de l'hématopoïèse humaine soulève des problèmes méthodologiques. Ceci est lié au difficile accès au; prélèvements de moelle primaire et les études sur le sang placentaire ne reflètent pas complétement le développement médullaire. Dans ce travail, nous avons utilisé un modèle in vivo d'hématopoïèse foetale humaine chez la souris NSG par xénogreffe de progéniteurs du sang placentaire. La caractérisation faite sur les populations générées dans la moelle osseuse de souris a révélé que ce modèle reproduit l'hématopoïèse foetale humaine. Nous montrons que la lymphopoïèse foetale humaine présente une organisation originale caractérisée par une duplication des axes développementaux. Nos travaux mettent en évidence l'émergence indépendante de deux type de progéniteurs lymphoïdes à partir d'un intermédiaire multipotent: une population ancestrale CD127+générant principalement des lymphocytes B folliculaires, ainsi que des cellules ILC3 ; une population CD127- générant des lymphocytes T, des lymphocytes B de la zone marginale, et des cellules NK/ILC1. Ces résultats montrent que l'hématopoïèse humaine ne suit pas le modèle standard établi chez la souris
The standard model of hematopoiesis proposes that hematopoietic differentiation is a stepwise bifurcation process. The first separation downstream of hematopoietic stem cells will segregate mutipotent progenitors into common lymphoid and myeloid progenitors. In human many evidences support the idea that human hematopoietic organization doesn't follow the classical model, but the question was not concluded and need for further investigation. Due to limited access to primary bone marrow samples and lack of appropriate in vivo model human studies face many difficulties. In this work, we used a xenogeneic model of human fetal hematopoiesis in immune-deficient mice to dissect the early stages of lymphoid development. This model relies on the injection of UCB CD34+ cells into NSG mice. Flow cytometry analysis and gene expression profiling of humanized mice BM populations revealed that this model faithfully reproduces human fetal hematopoiesis. Combining in vitro differentiation assays to molecular studies and genetic approaches, we show that fetal human lymphopoiesis displays a dual organization, split into an ancestral CD127+ CLP-like population devoid o myeloid potential that differentiate preferentially into follicular B cells and ILC3s, and into a previously undescribed CD127- population mainly dedicated to the generation of T, marginal zone B, NK, and ILC1s We also provide evidence that Early Lymphoid Progenitors emerge independently from multipotent developmental intermediates referred to as lympho-mono'dendritic progenitors. These results confirm that human hematopoiesis doesn't follow the standard model of hematopoietic differentiation established in the mouse

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8

Monzón, Sandoval Jimena. "Networks and the evolution of complex phenotypes in mammalian systems." Thesis, University of Bath, 2016. https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.683544.

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During early development of the nervous system, gene expression patterns are known to vary widely depending on the specific developmental trajectories of different structures. Observable changes in gene expression profiles throughout development are determined by an underlying network of precise regulatory interactions between individual genes. Elucidating the organizing principles that shape this gene regulatory network is one of the central goals of developmental biology. Whether the developmental programme is the result of a dynamic driven by a fixed architecture of regulatory interactions, or alternatively, the result of waves of regulatory reorganization is not known. Here we contrast these two alternative models by examining existing expression data derived from the developing human brain in prenatal and postnatal stages. We reveal a sharp change in gene expression profiles at birth across brain areas. This sharp division between foetal and postnatal profiles is not the result of sudden changes in level of expression of existing gene networks. Instead we demonstrate that the perinatal transition is marked by the widespread regulatory rearrangement within and across existing gene clusters, leading to the emergence of new functional groups. This rearrangement is itself organized into discrete blocks of genes, each associated with a particular set of biological functions. Our results provide evidence of an acute modular reorganization of the regulatory architecture of the brain transcriptome occurring at birth, reflecting the reassembly of new functional associations required for the normal transition from prenatal to postnatal brain development.

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9

Anderson, Ingrid Anna. "The role of developmental constraint in mating-system evolution in Leavenworthia a quantitative genetic analysis /." [Bloomington, Ind.] : Indiana University, 2005. http://wwwlib.umi.com/dissertations/fullcit/3204293.

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Thesis (Ph.D.)--Indiana University, Dept. of Biology, 2005.
Source: Dissertation Abstracts International, Volume: 67-01, Section: B, page: 0033. Adviser: Lynda F. Delph. "Title from dissertation home page (viewed Feb. 9, 2007)."

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10

Mainville, Sebastien. "The International System and Its Environment: Modern Evolutionary, Physiological and Developmental Perspectives on Change in World Politics." The Ohio State University, 2016. http://rave.ohiolink.edu/etdc/view?acc_num=osu1468866930.

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Книги з теми "Evolution of developmental systems"

1

Susan, Oyama, Griffiths Paul E, and Gray Russell D, eds. Cycles of contingency: Developmental systems and evolution. Cambridge, Mass: MIT Press, 2001.

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2

The ontogeny of information: Developmental systems and evolution. Cambridge: Cambridge University Press, 1994.

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3

Oyama, Susan. The ontogeny of information: Developmental systems and evolution. Cambridge: Cambridge University Press, 1985.

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4

Jože, Župančić, and International Conference on Information Systems Development (7th : 1998 : Bled, Slovenia), eds. Evolution and challenges in system development. New York: Plenum Press, 1999.

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5

Krogstie, John. Model-Based Development and Evolution of Information Systems. London: Springer London, 2012. http://dx.doi.org/10.1007/978-1-4471-2936-3.

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6

Kappeler, Peter M. Lemur Social Systems and Their Ecological Basis. Boston, MA: Springer US, 1993.

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7

1936-, Ebeling Werner, ed. Evolution of complex systems: Self-organization, entropy, and development. Dordrecht, Holland: Kluwer Academic Publishers, 1989.

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8

Rasskin-Gutman, Diego, and Werner Callebaut. Modularity: Understanding the development and evolution of natural complex systems. Cambridge, Mass: MIT Press, 2005.

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9

service), SpringerLink (Online, ed. Model-Based Development and Evolution of Information Systems: A Quality Approach. London: Springer London, 2012.

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10

International Conference on Systems Research, Informatics and Cybernetics (15th 2003 Baden-Baden, Germany). Sociocybernetics and human development: Impact of knowledge advancement on human evolution ... Windsor, Ont: International Institute for Advanced Studies in Systems Research and Cybernetics, 2003.

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Частини книг з теми "Evolution of developmental systems"

1

Last, Cadell. "Deep Future: Evolutionary Developmental Pathways." In World-Systems Evolution and Global Futures, 189–211. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-46966-5_10.

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2

Rust, Alistair G., Rod Adams, Stella George, and Hamid Bolouri. "Towards Computational Neural Systems through Developmental Evolution." In Emergent Neural Computational Architectures Based on Neuroscience, 188–202. Berlin, Heidelberg: Springer Berlin Heidelberg, 2001. http://dx.doi.org/10.1007/3-540-44597-8_14.

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3

Richardson, Ken. "Evolution of Development." In The Evolution of Intelligent Systems, 69–89. London: Palgrave Macmillan UK, 2010. http://dx.doi.org/10.1057/9780230299245_5.

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4

Solodovnikova, Darja. "Metadata to Support Data Warehouse Evolution." In Information Systems Development, 627–35. Boston, MA: Springer US, 2009. http://dx.doi.org/10.1007/b137171_65.

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Solodovnikova, Darja, and Laila Niedrite. "Evolution-Oriented User-Centric Data Warehouse." In Information Systems Development, 721–34. New York, NY: Springer New York, 2011. http://dx.doi.org/10.1007/978-1-4419-9790-6_58.

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Sosis, Richard. "The Building Blocks of Religious Systems: Approaching Religion as a Complex Adaptive System." In Evolution, Development and Complexity, 421–49. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-00075-2_19.

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Heinrich, L. J., G. Pomberger, and I. Häntschel. "Information Systems Diagnosis." In Evolution and Challenges in System Development, 187–97. Boston, MA: Springer US, 1999. http://dx.doi.org/10.1007/978-1-4615-4851-5_18.

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Sayama, Hiroki. "Complexity, Development, and Evolution in Morphogenetic Collective Systems." In Evolution, Development and Complexity, 293–305. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-00075-2_11.

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Sommer, Ralf J. "Evolution of Regulatory Networks: Nematode Vulva Induction as an Example of Developmental Systems Drift." In Evolutionary Systems Biology, 79–91. New York, NY: Springer New York, 2012. http://dx.doi.org/10.1007/978-1-4614-3567-9_4.

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Boukachour, Hadhoum, Stéphane Allorge, Franck Lesage, and Alain Cardon. "Information and Communication Systems." In Evolution and Challenges in System Development, 353–60. Boston, MA: Springer US, 1999. http://dx.doi.org/10.1007/978-1-4615-4851-5_32.

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Тези доповідей конференцій з теми "Evolution of developmental systems"

1

Schramm, Lisa, Yaochu Jin, and Bernhard Sendhoff. "Quantitative analysis of redundancy in evolution of developmental systems." In 2012 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology (CIBCB). IEEE, 2012. http://dx.doi.org/10.1109/cibcb.2012.6217212.

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2

Shayani, Hooman, Peter J. Bentley, and Andy M. Tyrrell. "A Multi-cellular Developmental Representation for Evolution of Adaptive Spiking Neural Microcircuits in an FPGA." In 2009 NASA/ESA Conference on Adaptive Hardware and Systems (AHS). IEEE, 2009. http://dx.doi.org/10.1109/ahs.2009.39.

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Homes, J. E. "A development of reference models for computer systems." In 1988 Computer Standards Evolution: Impact and Imperatives. IEEE, 1988. http://dx.doi.org/10.1109/cstand.1988.4765.

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Amosova, Nataliya A., and Mikhail Yu Sanakoev. "Deposit Insurance Systems: Evolution, Risks, Development Trends." In The 3rd International Conference on Economy, Management and Entrepreneurship (ICOEME 2020). Paris, France: Atlantis Press, 2020. http://dx.doi.org/10.2991/aebmr.k.200908.001.

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Bresfelean, Vasile. "ENTERPRISE RESOURCE PLANNING SYSTEMS - EVOLUTION AND DEVELOPMENT." In 5th SGEM International Multidisciplinary Scientific Conferences on SOCIAL SCIENCES and ARTS SGEM2018. STEF92 Technology, 2018. http://dx.doi.org/10.5593/sgemsocial2018/1.5/s05.040.

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"ONTOLOGIES AND COMMUNITIES CO-EVOLUTION IN INFORMATION SYSTEMS." In International Conference on Knowledge Engineering and Ontology Development. SciTePress - Science and and Technology Publications, 2010. http://dx.doi.org/10.5220/0003106404530458.

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"Modifying Neuro Evolution For Mobile Robotic Behavior Development." In The First International Workshop on Multi-Agent Robotic Systems. SciTePress - Science and and Technology Publications, 2005. http://dx.doi.org/10.5220/0001192901550164.

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Morar, S. "Evolution of communication based train control worldwide." In IET Professional Development Course on Railway Signalling and Control Systems (RSCS 2010). IET, 2010. http://dx.doi.org/10.1049/ic.2010.0106.

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Morar, S. "Evolution of communication based train control worldwide." In IET Professional Development Course on Railway Signalling and Control Systems (RSCS 2012). IET, 2012. http://dx.doi.org/10.1049/ic.2012.0054.

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10

Lapin, Nikolay I. "REGIONAL INNOVATION SYSTEMS – A WAY OF SELF-DEVELOPMENT OF THE RUSSIAN REGIONS." In Problems of sociocultural evolution of Russia and its regions. Tula State Lev Tolstoy Pedagogical University, 2018. http://dx.doi.org/10.22405/978-5-6041453-4-0-2018-7-19.

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Звіти організацій з теми "Evolution of developmental systems"

1

Shrestha, S. Evolution of Mountain Farming Systems: Sustainable Development Policy Implications. International Workshop Report. Kathmandu, Nepal: International Centre for Integrated Mountain Development (ICIMOD), 1995. http://dx.doi.org/10.53055/icimod.193.

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2

Shrestha, S. Evolution of Mountain Farming Systems: Sustainable Development Policy Implications. International Workshop Report. Kathmandu, Nepal: International Centre for Integrated Mountain Development (ICIMOD), 1995. http://dx.doi.org/10.53055/icimod.193.

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3

Keen, C. E., K. Dickie, L. T. Dafoe, T. Funck, J. K. Welford, S A Dehler, U. Gregersen, and K J DesRoches. Rifting and evolution of the Labrador-Baffin Seaway. Natural Resources Canada/CMSS/Information Management, 2022. http://dx.doi.org/10.4095/321854.

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Анотація:

The evolution of the 2000 km long Mesozoic rift system underlying the Labrador-Baffin Seaway is described, with emphasis on results from geophysical data sets, which provide the timing, sediment thickness, and crustal structure of the system. The data sets include seismic reflection and refraction, gravity, and magnetic data, with additional constraints provided by near-surface geology and well data. Many features that characterize rift systems globally are displayed, including: wide and narrow rift zones; magma-rich and magma-poor margin segments; exhumation of continental mantle in distal, magma-poor zones; and occurrences of thick basalts, associated with the development of seaward-dipping reflectors, and magmatic underplating. The magma-rich regions were affected by Paleogene volcanism, perhaps associated with a hotspot or plume. Plate reconstructions help elucidate the plate tectonic history and modes of rifting in the region; however, many questions remain unanswered with respect to this rift system.

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4

Previtali, Marco, Matteo Ciantia, Saverio Spadea, Riccardo Castellanza, and Giovanni Crosta. Development of a macro-element model for rockfall steel wires using. University of Dundee, December 2021. http://dx.doi.org/10.20933/100001232.

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This paper aims to present a few aspects of the development of a plastic-hardening macro-element model for steel wires in flexible protection systems. First, the material behaviour is obtained using uniaxial tensile tests. Successively, the evolution of the elastic and plastic domain is obtained using a combination of physical tests, analytical models, and numerical simulations. Finally, the results obtained with the macro-element model are compared to those obtained using other approaches found in literature.

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5

Harn, M., V. Berzins, W. Kemple, and Luqi. Evolution of C4I Systems. Fort Belvoir, VA: Defense Technical Information Center, June 1999. http://dx.doi.org/10.21236/ada467887.

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6

Cook, Stephen, and Loyd Hook. Developmental Pillars of Increased Autonomy for Aircraft Systems. ASTM International, January 2020. http://dx.doi.org/10.1520/tr2-eb.

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Increased automation for aircraft systems holds the promise to increase safety, precision, and availability for manned and unmanned aircraft. Specifically, established aviation segments, such as general aviation and light sport, could utilize increased automation to make significant progress towards solving safety and piloting difficulties that have plagued them for some time. Further, many emerging market segments, such as urban air mobility and small unmanned (e.g., small parcel delivery with drones) have a strong financial incentive to develop increased automation to relieve the pilot workload, and/or replace in-the-loop pilots for most situations. Before these advances can safely be made, automation technology must be shown to be reliable, available, accurate, and correct within acceptable limits based on the level of risk these functions may create. However since inclusion of these types of systems is largely unprecedented at this level of aviation, what constitutes these required traits (and at what level they must be proven to) requires development as well. Progress in this domain will likely be captured and disseminated in the form of best practices and technical standards created with collaboration from regulatory and industry groups. This work intends to inform those standards producers, along with the system designers, with the goal of facilitating growth in aviation systems toward safe, methodical, and robust inclusion of these new technologies. Produced by members of the manned and unmanned small aircraft community, represented by ASTM task group AC 377, this work strives to suggest and describe certain fundamental principles, or “pillars”, of complex aviation systems development, which are applicable to the design and architectural development of increased automation for aviation systems.

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7

Carney, David, David Fisher, and Patrick Place. Topics in Interoperability: System-of-Systems Evolution. Fort Belvoir, VA: Defense Technical Information Center, March 2005. http://dx.doi.org/10.21236/ada441303.

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8

Lehoczky, J., P. Feiler, B. Krogh, T. Marz, and R. Rajkumar. Incremental Software Evolution for Real-Time Systems (INSERT). Fort Belvoir, VA: Defense Technical Information Center, January 2001. http://dx.doi.org/10.21236/ada400815.

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9

Enke, Benjamin. Kinship, Cooperation, and the Evolution of Moral Systems. Cambridge, MA: National Bureau of Economic Research, June 2017. http://dx.doi.org/10.3386/w23499.

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10

Mailloux, Robert J. Wideband Subarray Systems: Evolution of a Research Area. Fort Belvoir, VA: Defense Technical Information Center, November 1998. http://dx.doi.org/10.21236/ada408872.

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