Recent Additions: New and Updated Entries in the Past 60 Days
Displaying entries 46 through 60 of 130 found.
Stauffer, Dietrich, et al.
From Newton to Mandelbrot.
Senior theoretical physicists Stauffer, Eugene Stanley and Annick Lesne post the third edition since 1990 of a tutorial volume all about the natural persistence of self-similar fractal forms and movements from quantum mechanics, statistical physics, and broadly conceived dynamical systems
Thurner, Stefan, et al.
Introduction to the Theory of Complex Systems.
Introduction to the Theory of Complex Systems,
Senior Medical University of Vienna system physicists Stefan Thurner, Peter Klimek and Rudolf Hamel provide a wide-ranging technical survey to date which covers scaling, networks, evolutionary processes, self-organized criticality, non-equilibrium statistical mechanics, information theory, and future advances, see next quote.
The chapter is a mini outlook on the field. The classic achievenments in complexity science are mentioned, and we summarize how the new directions might open new doors into a twenty-first-century science of complex systems. We do that by clarifying the origin of scaling laws, in particular for driven non-equilibrium systems, deriving the statistics of driven systems, categorizing probabilistic complex systems into universality classes, by meaningful generalizations of statistical mechanics and information theory, and finally, by unifying approaches to evolution and co-evolution into a single mathematical framework. We comment on our view of the role of artificial intelligence and our opinion on the future of science of complex systems. (Future of Complex Systems Science excerpt)
Cosmic Code > Algorithms
The Principles of Informational Genomics.
Theoretical Computer Science.
The University of Verona computer scientist complements his chapter Decoding Genetic Information with G. Franco in Computational Matter (S. Stepney, 2017) about novel perspectives of genetic activity in terms of their algorithmic, semantic, linguistic qualities.
The present paper investigates the properties of genomes directly related with their long linear structure. A systematic approach is introduced that is based on an integration of string analysis and information theory, applied and verified on real genomes. New concepts and results are given in connection with genome empirical entropies (and related indexes), genome dictionaries and distributions, word elongations, informational divergences, genome assemblies, and genome segmentations.
Cosmic Code > Algorithms
The Beauty of Mathematics in Computer Science.
Boca Raton: CRC Press,
This popular text in Chinese by a Google Brain USA member (bio below) is here published in English. It’s main message is to show the deep affinities between algorithmic code, scriptural languages and innate mathematic principles
The book covers many topics including Natural language processing, Speech recognition and machine translation, Statistical language modeling, Quantitive measurement of information, Pagerank for web search, Matrix operation and document classification, Mathematical background of big data, and Neural networks and Google’s deep learning.
Cosmic Code > 2015 universal
Jun Wu was a research scientist who invented Google’s Chinese, Japanese, and Korean Web Search Algorithms. He wrote official blogs introducing Google technologies in simple languages for Chinese Internet users from 2006-2010. Wu received PhD in computer science from Johns Hopkins University and has been working on natural language processing for more than 20 years.
Horstmeyer, Leonhard, et al.
Network Topology near Criticality in Adaptive Epidemics.
Just as every other area from quantum to neural has become defined by the universally prevalent self-organized complex network systems, here LH and Stefan Thurner, Medical University of Vienna and Christian Kuehn, Technical University of Munich theorists describe how even human disease vectors among variegated populations similarly hold, as they mathematically must,Just as every other area from quantum to neural has become defined by the universally prevalent self-organized complex network systems, here LH and Stefan Thurner, Medical University of Vienna and Christian Kuehn, Technical University of Munich theorists describe how even human disease vectors among variegated populations similarly hold and exhibit, as they mathematically must, to predictable, critical principles.
We study structural changes of adaptive networks in the co-evolutionary susceptible-infected-susceptible (SIS) network model along its phase transition. We clarify to what extent these changes can be used as early-warning signs for the transition at the critical infection rate λc at which the network collapses and the system disintegrates. We analyze the interplay between topology and node-state dynamics near criticality. Several network measures exhibit clear maxima or minima close to the critical threshold that could potentially serve as early-warning signs. For the SI link density and triplet densities the maximum is found to originate from the co-existence of two power laws. (Abstract)
Cosmic Code > networks
Alves, Liuz, et al.
The Nested Structural Organization of the Worldwide Trade Multi-Layes Network.
Nature Scientific Reports.
As if a cerebral sapiensphere learning on her/his own, University of Sao Paulo, University of Catania, Italy, Imperial College London, Queen Mary University, London and University of Zaragosa, Spain systems theorists discern the active multiplex connectivities across the eastern and western continents and trader lands. As the quotes allude, once more nature’s independent, universally instantiated complex dynamics and geometries make an appearance.
Nestedness has traditionally been used to detect assembly patterns in meta-communities and networks of interacting species. Attempts have also been made to uncover nested structures in international trade as bipartite networks in which connections are between countries (exporters or importers) and industries. A bipartite representation of trade, however, neglects transactions between industries. To fully capture the organization of the global value chain, we draw on the World Input-Output Database and construct a multi-layer network in which the nodes are the countries, the layers are the industries, and links can be from sellers to buyers within and across industries. Drawing on null models that preserve the countries’ or layers’ distributions in the original multi-layer network, we uncover variations of country- and transaction-based nestedness over time. (Abstract)
Cosmic Code > networks
Our findings suggest that the nested structure of these matrices is similar to the one uncovered in ecological networks Finally, because multi-layer networks can be found across a variety of biological, technological and social systems, we discuss the implications that our proposed approach to measuring nestedness can have beyond trade, for a wide range of empirical domains. (2) Because a variety of empirical domains, from biological to technological and social ones, can be characterized as complex networks in which relationships have a multi-layer representation, our approach also has important implications beyond international trade, and can help gain a better understanding of their structural organization, stability, and growth mechanisms. (12)
Cinardi, Nicola, et al.
Quantum Statistics in Network Geometry with Fractional Flavor.
Systems physicists NC and Andrea Rapisarda, University of Catania, and Ginestra Bianconi, Queen Mary University of London continue to finely season nature’s true anatomy and physiology as it ever arrays in similar kinds from quantum to neuronal realms.
Growing network models have been shown to display emergent quantum statistics when nodes are associated to a fitness value describing the intrinsic ability of a node to acquire new links. Recently it has been shown that quantum statistics emerge also in a growing simplicial complex model called Network Geometry with Flavor which allow for the description of many-body interaction between the nodes. In this case the faces of the simplicial complex are naturally described by the Bose-Einstein, Boltzmann and Fermi-Dirac distribution depending on their dimension. We show that in this case the statistical properties of the faces of the simplicial complex are described by the Bose-Einstein or the Fermi-Dirac distribution only. (Abstract flavor)
Cosmic Code > networks
Harush, Uzi and Baruch Barzel.
Dynamic Patterns of Information Flow in Complex Networks.
We cite this entry by Bar-Ilan University, Israel mathematicians because after some 20 years of node/link multiplex network studies, the detection of common recurrences everywhere must imply “universal laws” in effect. The paper was cited by Paul Davies in The Demon in the Machine as proof that the generative “informative patterns” he and colleagues propose are indeed “coherent things with an independent existence.” (101)
Although networks are extensively used to visualize information flow in biological, social and technological systems, translating topology into dynamic flow continues to challenge us, as similar networks exhibit different flow patterns, driven by other interaction mechanisms. To uncover a network’s actual flow patterns, we use a perturbative formalism, tracking the contribution of all nodes/paths to the flow of information, exposing the rules that link structure and dynamic flow for a broad range of nonlinear systems. We find that the diversity of patterns can be mapped into a single universal function, characterizing the interplay between the system’s topology and its dynamics. (Abstract excerpt)
Cosmic Code > networks
Our results show that despite the diversity of potential interaction mechanisms, the patterns of information flow are governed by universal laws that can be directly linked to the system’s microscopic dynamics. (2) From neuronal signals to gene regulation, complex networks unction by enabling the flow of information between nodes. Understanding the rules that govern this flow is a crucial step toward establishing a theory of network dynamics. (10) In a broader perspective, our predicted universality indicates that the macroscopic flow patterns of complex systems are controlled by only a few relevant parameters of the system’s microscopic dynamics. (10)
Sreedharan, Jithin, et al.
Inferring Temporal Information from a Snapshot of a Dynamic Network.
Nature Scientific Reports.
Purdue University and University of Michigan (Abram Magner) computer researchers finesse nature’s pervasive webwork anatomy and physiology by showing that a small segment can serve in some way as an invariant capsule. The paper opens with the standard litany that the same such phenomena has been found in kind from cells to brains to economies (second quote). See also Network Archaeology by J. Young, et al at arXiv:1803.09191.
The problem of reverse-engineering the evolution of a dynamic network, known broadly as network archaeology, is of much importance in diverse applications. In an analysis of infection spread, it discerns the underlying spatial and temporal processes. For biomolecular interaction networks (e.g., protein interaction networks), it reveals early molecules that are implicated in diseases. In economic networks, it shows the flow of capital and associated actors. It can further help describe the structural and functional evolution of the human brain connectome. In this paper, we model, formulate, and analyze the arrival order of nodes in a dynamic network from a single snapshot. (Abstract)
Complex systems are comprised of interacting entities; e.g., cellular processes are comprised of interacting genes, proteins, and biomolecules; social systems, of individuals and organizations; and economic systems, of financial entities. These systems are modeled as networks, with nodes as entities and edges as their interactions. Typical systems continually evolve to optimize various criteria, including function (e.g., flow of information in social networks, evolution of brain connectomes to specialize function), structure (e.g., evolution of social network structures to minimize sociological stress while maximizing information flow), and survivability (e.g., redundant pathways in genic interactions as evidenced by synthetic lethality screens). (1)
CRISPR: A New Principle of Genome Engineering Linked to Conceptual Shifts in Evolutionary Biology.
Biology & Philosophy.
The National Center for Biotechnology Information, Bethesda biotheorist and author writes an invited paper for a special issue to broadly appreciate these multi-faceted genetic advances and abilities. In so doing, it is broached that biomolecular mechanisms for actual Lamarckian epigenetic effects seem to be evident. After an introduction Philosophy of CRISPR-Cas by Thomas Pradeau, the edition adds commentaries such as by Eva Jablonka who leavens with a “quasi” Lamarckian model. Other entries cite its potential for easy palliative editing, the specter of Jean Baptiste is opposed by Ford Dollitle, Emily Parke, Sam Woolley, et al. A balanced view may be Sophie Veigl’s paper A Use/Disuse Paradigm.
The CRISPR-Cas systems of bacterial and archaeal adaptive immunity have become a household name among biologists and the general public by the unprecedented success of new generation of genome editing tools utilizing Cas proteins. However, the fundamental biological features of CRISPR-Cas are of no lesser interest and have major impacts on our understanding of the evolution of antivirus defense, host-parasite coevolution, self versus non-self discrimination and mechanisms of adaptation. CRISPR-Cas systems present the best known case in point for Lamarckian evolution, i.e. generation of heritable, adaptive genomic changes in response to encounters with external factors, in this case, foreign nucleic acids.
CRISPR-Cas systems employ multiple mechanisms of self versus non-self discrimination but, as is the case with immune systems, are costly because autoimmunity cannot be eliminated completely. Analysis of the evolutionary connections of Cas proteins reveals multiple contributions of mobile genetic elements (MGE) to the origin of various components of CRISPR-Cas systems, The shared features of adaptive defense systems and MGE, namely the ability to recognize and cleave unique sites in genomes, make them ideal candidates for genome editing and engineering tools. (Abridged Abstract)
An Evo-Devo Perspective on Analogy in Biology.
In a special collection from the Second World Congress on Analogy at Adam Mickiewicz University, Poland in May 2017, the University of Padova senior biologist and author (search) describes new appreciations of life’s tendency to draw upon and repeat patterns and processes (aka homology, homoplasy, convergence, etc.) in creaturely kind across life’s evolution. As a result, this long, episodic emergence is increasingly becoming seen as a developmental gestation.
To explain the amazing morphological and biomechanical analogy between two distantly related vertebrates as a dolphin and a shark, framed only in terms of adaptation (i.e., Darwinian survival of the fittest) is far from satisfactory. The same is true of any other structurally similar, but phylogenetically unrelated organisms. An evolutionary argument does not say how the developmental processes of their ancestors could evolve so as to produce these phenotypes (the arrival of the fittest). To address the evolution of possible forms, we cannot ignore that these are products of development. This invites an integrated perspective, currently known as evolutionary developmental biology, or evo-devo. Paths through living forms are not satisfactorily explained in terms of geometrical transformations or the adaptive value of the phenotypes. The emergence of form is dependent on the intrinsic evolvability of developmental processes that translate the genotype into phenotypes. As a consequence, development makes analogous structures more likely to evolve than a purely adaptationist view would ever suggest. (Abstract)
Quickening Evolution > Systems Biology
This Special Issue follows the intention of the congress to promote interdisciplinary research, philosophical reflection, and discourse across multiple methodological perspectives about analogy. There are many definitions and conceptions of analogy, but it is always considered as a universal tool that enables us to discover, explore, compare, analyze, understand and illustrate similarities and differences. Formally speaking, analogy can be defined as a relation between relations; it is connected with proportions and remains pervasive in science, art and religion. If we agree that inter-cultural, inter-ideological and inter-religious dialogue is a crucial issue, the humanistic approach to analogy seems to be of the greatest importance. (Summary)
Ceska, Milan and David Safranek, eds.
Computational Methods in Systems Biology.
The Proceedings of the 16th International Conference on this title subject (CMSB) held in Brno, Czech Republic, in September. Some entries are Deep Abstractions of Chemical Reactions Networks, Synthesis for Vesicle Traffic Systems, and Experimental Biological Protocols with formal Semantics. May one then wonder, what grand phenomena, of we are as yet unawares, is our worldwise sapiensphere coming upon, trying to learn, provide a cosmic self-describe? What is going on, what language is natural genesis written in? Who are we phenomenal human beings to be able to do this, for what purpose? Does a universal procreation want us to intentionally take from here?
The 15 full and 7 short papers presented together with 5 invited talks were selected from 46 submissions. Topics of interest include formalisms for modeling biological processes; models and their biological applications; frameworks for model verification, validation, analysis, and simulation of biological systems; high-performance computational systems biology; parameter and model inference from experimental data; automated parameter and model synthesis; model integration and biological databases; multi-scale modeling and analysis methods; design, analysis, and verification methods for synthetic biology; methods for biomolecular computing and engineered molecular devices.
Quickening Evolution > Biosemiotics
Communication as the Main Characteristic of Life.
Vera Kolb, ed.
Handbook of Astrobiology, 2019.
The Austrian philosopher (search) continues his emphasis that cross-information and sign-sharing amongst and across all manner of fauna and flora from life’s cellular advent is a vital, definitive characteristic. The medium is the message from chemical and electro-sensory modes to gestures and grunts on to our loquacious language. The chapter courses through fungi, plants, genomes, bacteria, eukaryotes, viruses, insects, while finally reaching we peoples. Within this subject book, this essence of an animate semiotic ecosmos is suggested as a good guide for astrobiological surveys going forward.
Earth Life > Nest > Geological
Lofta, Nastaran, et al.
Centrality in Earthquake Multiplex Networks.
University of Zanjan, Iran and University of Sao Paulo physicists achieve a detailed global complex systems analysis of these spurious geological calamities. To reflect, out of this arduous planetary evolution and human history a collective, cumulative knowledge at last arises which then might be fed back to give better warnings, and maybe mitigate. What could its cosmic identity and purpose be?
Seismic time series has been mapped as a complex network, where a geographical region is divided into square cells that represent the nodes and connections are defined according to the sequence of earthquakes. In this paper, we map a seismic time series to a multiplex network, and characterize the evolution of the network structure in terms of the eigenvector centrality measure. We generalize previous works that considered the single layer representation of earthquake networks. Our results suggest that the multiplex representation captures better earthquake activity than methods based on single layer networks. We also verify that the regions with highest seismological activities in Iran and California can be identified from the network centrality analysis. The temporal modeling of seismic data provided here may open new possibilities for a better comprehension of the physics of earthquakes. (Abstract)
Earth Life > Nest > Life Origin
Quantitative Measurement of Heritability in the Pre-RNA World.
We cite this entry by a Nihon BioData Corp., Japan researcher, formerly at Kawasaki Medical University, as a 2019 example of how origin of life studies have moved beyond biomolecules (RNA) or metabolism alone to include the generative presence of nature’s universal independent generative propensities.
Before assembly with nucleotides, in the pre-RNA era, what system dominated heredity? Self-organized complex systems are hypothesized to be a primary factor of the origin of life and to dominate heritability, mediating the partitioning of an equal distribution of structures and molecules at cell division. The degree of strength of self-organization would correlate with heritability; self-organization is known to be a physical basis of hysteresis phenomena, and the degree of hysteresis is quantifiable. However, there is no argument corroborating the relationship between heritability and hysteresis. Here, we show that the degree of cellular hysteresis indicates its heritability and daughter equivalence at cell division. Our results demonstrate that self-organized complex systems contribute to heredity and are still important in mammalian cells. Discovering ancient and hidden heredity systems enables us to study our own origin, to predict cell features and to manage them in the bio-economy. (Abstract excerpt)