(logo) Natural Genesis (logo text)
A Sourcebook for the Worldwide Discovery of a Creative Organic Universe
Table of Contents
Introduction
Genesis Vision
Learning Planet
Organic Universe
Earth Life Emerge
Genesis Future
Glossary
Recent Additions
Search
Submit

Recent Additions: New and Updated Entries in the Past 60 Days
Displaying entries 61 through 75 of 139 found.


Cosmomics: A Genomic Source Code in Procreative Effect

Cosmic Code > 2015 universal

Calim, Ali, et al. Chimera States in Hybrid Coupled Neuron Populations. arXiv:2003.01854. Zonguldak Bulent Ecevit University, Turkey, Istanbul Technical University, and University of Granada, Spain biomedical engineers report a sophisticated technical finesse of this common preference for an optimum dual dance in our cerebral cognition.

Chimera state is a recently discovered dynamical system behavior which has attracted an increasing interest, and which is characterized by the coexistence of synchronization and desynchronization within a population of identical dynamical elements. This interesting phenomenon has been studied in a wide range of natural and artificial systems, as well as in neuron populations. (15)

Cosmic Code > 2015 universal

Ganaie, Mudasir, et al. Identification of Chimera using Machine Learning. arXiv:2001.08985. We cite this entry by Indian Institute of Technology complexity scientists as an example of how new AI techniques with their basis in cerebral cognition can now reveal the propensity of all manner of natural systems to be attracted to and perform best at an active poise of a more or less orderly balance. A notable feature is that any instance can be seen to exist in both states at the same moment.

Coupled dynamics on network models have provided much insight into complex spatiotemporal patterns from many large-scale real-world complex systems. Chimera, a state of coexistence of incoherence and coherence, is one such pattern which has drawn attention due to its common presence, especially in neuroscience. We describe an approach to characterize chimeras using machine learning techniques, namely random forest, oblique random forests via multi-surface proximal support vector machines. We demonstrate high accuracy in identifying the coherent/incoherent chimera states from given spatial profiles. (Abstract excerpt)

Cosmic Code > 2015 universal

Helmrich, Stephan, et al. Signatures of Self-Organized Criticality in an Ultracold Atomic Gas. Nature. 577/481, 2020. In a paper appropriately published in the first month of this binocular year, University of Heidelberg, Cal Tech, and University of Koln physicists contribute to the ubiquitous occurrence of self-similar, critically poised states everywhere. The subject case here is elemental gases where such exemplary features appear even at these frigid, quantum extremes. See also Singular Charge Fluctuations at a Magnetic Quantum Critical Point and Quantum Spin Liquids in Science for January 17, 2020. Two decades into the 21st century, a Worldwide Discovery of a Organic, Procreative UniVerse does seem well underway, if we might be of a mind to ask and see.

Self organisation provides an elegant explanation for how complex structures emerge and persist throughout nature with remarkably similar scale-invariant properties. While this can be captured by simple models, the connection to real-world systems is difficult to test. Here we identify three key signatures of self-organised criticality in the dynamics of a dissipative gas of ultracold atoms and provide a first characterisation of its universal properties. We show that population decay drives the system to a stationary state that is independent of the initial conditions and exhibits scale invariance and a strong response to perturbations. This establishes a practical platform for investigating self-organisation phenomena and non-equilibrium universality with much experimental access to the microscopic details of the system. (Abstract)

Cosmic Code > 2015 universal

Lugo, Haydee, et al. Chimera and Anticoordination States in Learning Dynamics. arXiv:1812.05603. We cite this entry by Spanish economists because they go on to suggest ways that this recently realized tendency of physical, electronic and neural systems to become poised between more or less order could be similarly evident in personal and social activities. Its early on, but we add that by perceptive extensions like this, its traditional version best known as yin/yang dynamics can at last gain a modern, 21st century scientific confirmation.

In many real-life situations, individuals are motivated to achieve both social acceptance or approval and strategic objectives of coordination. Since these modes may take place in different environments, a two-layer network works well for its analysis. From an evolutionary approach, we focus on asymptotic solutions for all-to-all interactions across and inside the layers and for initial distributions of strategies. We report the existence of chimera states in which two collective states coexist in the same network. We trace back the emergence of chimera states and global anticoordination states to the agents inertia against social pressure. (Abstract excerpt)

The coexistence of coherent and incoherent states has received much attention as an intriguing manifestation of collective behaviour. This interesting behaviour was first observed by Kuramoto et al. and then named it as chimera state. Although the literature about chimera states started with the study of interacting populations of oscillators in dynamical systems, it has been dizzily expanded to many fields in physics, chemistry, biology, etc. Also in social systems, situations of two interacting populations in which one exhibits a coherent or synchronized behaviour while the other is incoherent or desynchronized are commonly observed. This phenomena has also been addressed from the conceptual framework of chimera states. (1)

In the context of coordination in social systems, our contribution brings a more realistic insight about the consequences of a collective behavior that makes a distinction between social and strategic objectives. This collective behavior may lead herding societies to chimera states and skeptical societies to polarized states of anti-coordination. (12)

Cosmic Code > 2015 universal

Schlapfer, Markus, et al. The Hidden Universality of Movement in Cities. arXiv:2002.06070. Santa Fe Institute, MIT, ETH Zurich, and University of Copenhagen theorists including Geoffrey West consider urban intensities such as social media, innovation, productivity, epidemics and much more across four continents. As this project to treat cities as complex fractal systems reaches two decades, it is now possible to robustly confirm the presence of common mathematic spatial patterns and temporal dynamics. Once more this year, an unseen generative invariance every case and place becomes quite apparent. As other planners variously perceive, our larger and smaller human habitations gain a predictability and preference which can be availed for betterment. See also The Spectral Dimension of Human Mobility by this group at 2002.06740.

The interaction of all mobile species within an environment hinges on their movement patterns. In human society, where the prevalent form of cohabitation is in cities, the dynamic and diverse movement of people affects every aspect of socio-economic life and the evolution of urban infrastructure, productivity, innovation and technology. However, the laws that govern the variation of population flows to specific locations have remained elusive. Here we show that behind their apparent complexity a simple universal scaling relation drives the flow of individual based on both frequency of visitation and distance travelled. We demonstrate that population flows obey this theoretical prediction in all tested areas across the globe, ranging from Europe and America to Asia and Africa, regardless of the geographies, cultures or levels of development. (Abstract excerpt)

Cosmic Code > 2015 universal

Shmulevich, Ilya, et al. Eukaryotic Cells are Dynamically Ordered or Critical but Not Chaotic. Proceedings of the National Academy of Sciences. 102/13439, 2005. We cite this entry with Stuart Kauffman as a coauthor as an early notice of the tendency for gene regulatory networks to arrive and perform at this critical cusp between stability and openness. The many 2018 – 2020 entries herein and throughout which robustly quantify this common state give proof to its prescience.

Cosmic Code > 2015 universal

Stanoev, Angel, et al. Organization at Criticality Enables Processing of Time-Varying Signals by Receptor Networks. Molecular Systems Biology. 16/2, 2020. As we cite many papers about self-organized criticalities in neural systems, here MPI Molecular Physiology cell biologists report the presence of nature’s optimum biochemical balance has similarly been found in cellular information processing. Circa 2020, increasingly across in every realm, a common, independent generative pattern seems to be in exemplary evidence.

How cells utilize surface receptors for chemoreception is an open issue spanning physics and biology. For example, the dynamical mechanism for processing time‐varying signals is still unclear. Using a dynamical formalism to describe criticality in non‐equilibrium systems, we propose a generic principle for temporal information processing through phase space trajectories with transient memory. In contrast to short‐term memory, dynamic memory generated via a “ghost” attractor enables signal integrations and interprets complex temporal growth factor signals. We propose how recycling provides self‐organized maintenance of the critical receptor concentration at the plasma membrane through a fluctuation‐sensing mechanism. Processing of non‐stationary signals, a feature previously attributed only to neural networks, thus uniquely emerges for receptor networks organized at criticality. (Abstract excerpt)

Cosmic Code > 2015 universal

Villani, Marco, et al. Dynamic Criticality in Gene Regulatory Networks. Complexity. October, 2018. University of Modena theorists, along with coauthor Stuart Kauffman, show how his original prescience (search Bornholdt) that living systems reside at an dynamic edge between order and chaos is currently being robustly verified, as this section reports. While other studies in neuroscience (see VI. G. 2) also confirm, here this optimum state is found to hold for genomes. Search Villani for much more about this long foreseen, often elusive, historic discovery of one uniVerse to human epitome creative code.

Cosmic Code > 2015 universal

Villani, Marco, et al. Evolving Always-Critical Networks. Life. 10/3, 2020. In this year of binocular clarity, systems physicists MV and Roberto Serra, University of Modena, and Salvatore Magri and Andrea Roli, University of Bologna, along with colleagues can well describe an optimum condition of self-organized criticality that active systems seek and prefer to reside at. As this section reports, some two decades of global research have now settled upon this vital iconic “criticality principle” from brains to genomes to quantum phases. The occasion at last achieves a resolve and proof that a reciprocal mutuality between apart/together, conserve/create, and so on is nature’s best beneficial balance (except politics which blindly pit one complement vs. the other). See also Dynamical Criticality: Overview and Open Questions by this team (Andrea Roli, et al) in the Journal of Systems Science and Complexity (31/647, 2018).

Living beings share several common features at the molecular level, but there are as yet few large-scale “operating rules” for all organisms. An interesting candidate is the “criticality” principle, which claims that biological evolution favors those regimes that are intermediaries between ordered and disordered states, “at the edge of chaos”. The reasons why this should be the case are discussed such as gene regulatory networks (GRN) which do in fact reside at the critical boundaries. In order to explore an “always-critical” state, we resort to simulated evolution via genetic algorithms which show that new individuals do indeed develop critical GRNs. (Abstract excerpt)

Therefore, critical states are in between ordered and disordered ones. The criticality principle states that these states are at an advantage with respect either to chaotic states, since they are more stable and controllable, or to ordered states, since they can better change in response to different conditions, without being stuck in the same state. If this is indeed the case, evolution should have modified the parameters in such a way that living beings are found near critical states—a statement that is, in principle, amenable to experimental verification. (2)

Let us revisit now the CP that has been introduced and discussed in Section 1, which claims that some dynamical states are advantaged with respect to other states, and that evolution drives living beings towards these “critical” states, which are neither fully ordered nor fully disordered. (13)

Systems that exhibit complex behaviours are often found in a dynamical condition which is poised between order and disorder. This observation is the essence of the criticality hypothesis, which states that such an active balance can attain the highest level of computational capabilities and an optimal trade-off between robustness and flexibility. Recent results in cellular and evolutionary biology, neuroscience and computer science have heightened interest in a preferred criticality state as a candidate general law in adaptive complex systems. (Roli, et al Abstract)

Cosmic Code > 2015 universal

Zur Bonsen, Alexander, et al. Chimera States in Networks of Logistic Maps with Hierarchical Connectivities. arXiv:1711.03287. Technical University of Berlin system physicists including Anna Zakharova and Eckehard Scholl go on to describe fractal self-similar bifurcations which these node/link scalar topologies seem to be attracted to.

Cosmic Code > networks

Nature Network Collection. www.nature.com/collections/adajhgjece. A new collection series from across the many premier Nature publishing group journals. Some typical entries are The Multilayer Nature of Ecological Networks, Network Neuroscience, and Spatial Scaling of Species Interaction Networks.

Network science is now a mature research field, whose growth was catalysed by the introduction of the ‘small world’ network model in 1998. Networks give mathematical descriptions of systems containing containing many interacting components, including power grids, neuronal networks and ecosystems. This collection brings together selected research, comments and review articles on how networks are structured (Layers & structure); how networks can describe healthy and disordered systems (Brain & disorders); how dynamics unfold on networks (Dynamics & spread); and community structures and resilience in networks (Community & resilience).

Cosmic Code > networks

Boguna, Marian, et al. Network Geometry. arXiv:2001.03241. Six senior complexity scientists including Dmitri Krioukov and Shlomo Havlin offer a January 2020 posting which couldl be a bidecadal capsule of how much studies of nature’s innate node/link multiplex anatomy and physiology has been found in vivifying evidence from physical depths and galactic clusters and to evolutionary bodies, brains, groupings and onto economies and cultures. This entry describes how “fractal self-similarities, diffusion dynamics, and functional modularity” have been found from a chemical-space renormalization to cellular communities across life’s biota, as shown in intricate displays. Into the 2010s, an increasing implication is the presence of an independent, mathematic source in exemplary manifestation at each and every scale and instance. See also Geometric Origins of Self-Similarity in the Evolution of Real Networks by this group at 1912.00704 and Scale-free Networks Revealed from Finite-size Scaling at 1805.09512.

Networks are natural geometric objects. Yet the discrete metric structure of shortest path lengths in a network is not the only reservoir of geometric distances. Other forms of network-related topologies are continuous latent spaces underlying many networks, and the effective geometry induced by dynamical processes. A growing amount of evidence shows that the three approaches are well related. Network geometry is thus quite efficient in discovering hidden symmetries, such as scale-invariance, and other fundamental physical and mathematical properties, along with a variety of applications from the understanding how the brain works to routings in the Internet. Here, we review theoretical and practical developments in network geometry in the last two decades, and offer perspectives on future research for this novel complexity frontier. (Abstract)

Cosmic Code > networks

Chavalarias, David. From Inert Matter to the Global Society: Life as Multi-level Networks of Processes. Philosophical Transactions of the Royal Society B. February, 2020. In this Unifying the Essential Concepts of Biological Networks issue, a Parisian cognitive scientist (bio below) illumes a cosmic to congress synthesis due to the generative activity of self-organization, autopoiesis, biocatalysis, recurrent scales, and more. This view leads a “triple closure” (see Abstract) made up of member components, active relations, and an integral unity. Life’s evolutionary basis and intent is then seen as a constant fulfillment of this iconic, triune whole. A consequentl rise of cerebral cognition, collective intelligence, and cultural learning can also be observed. As this universe to human course proceeds, our global phase is seen to be emerging into a “humanity-organism.” In closing, it is noted that this worldwide advance must not be left to chance, rather a common, informed, popular, concerted effort is imperative to bring to fruition.

A billion years have passed since the first life forms appeared. Since then, life has continued to form complex associations between emergent levels of interconnection. Advances in molecular chemistry and theoretical biology based on a systems view can now conceptualize life’s origins and complexity from three notions of closure: processes, autocatalysis and constraints. This integral paradigm can then trace the physical levels of the organization of matter from physics to biology and society without resorting to reductionism. The phenomenon of life thus becomes a contingent complexification until life emerges as a network of auto-catalytic process networks, organized in a multi-level manner. A living systems approach inevitably reflects on cognition; and on the deep changes that affects humanity by way of our cultural evolution. (Abstract Excerpt)

Humanity, by becoming an ‘organism’, is becoming de facto mortal. Cultural evolution as we used to think of it, is over. It will become more similar to a process of adaptation and learning at the level of humanity that can lead to its disappearance at any time. The new humanity – organism is alone on its evolutionary path and we can ask ourselves if we can afford to have it guided by random trials and errors. The kinds of collective cognition and behaviours that humanity will adopt in this new phase of its existence will determine its chances of survival in the future. (9)

David Chavalarias is the director of the Complex Systems Institute of Paris and Vice-President of the Complex Systems Society. He holds a PhD from the Ecole Polytechnique in cognitive sciences and attended the Ecole Normale Supérieure de Cachan in Mathematics and Computer Sciences. Currently permanent researcher at the National Center for Scientific Research (CNRS) in France, he studies the social and cognitive dynamics, both. His interdisciplinary research includes: quantitative epistemology, information visualization, modelling of the cultural dynamics, socio-semantic networks modelling, scientific discovery processes and cognitive economics.

Cosmic Code > networks

Filan, Daniel, et al. Neural Networks are Surprisingly Modular. arXiv:2003.04881. UC Berkeley and Boston University computer engineers find a way to emphasize and increase the practical presence of these local, clustered concentrations of specific cognitive functions in net topologies, just as biological systems draw upon nested modularities for their development and sustenance. Once again, the tacit assumption is a ready transferability of this independent, iconic source as manifest in connectomic and genomic phenomena.

The learned weights of a neural network are often considered devoid of scrutable internal structure. In order to discern structure in these weights, we introduce a measurable notion of modularity for multi-layer perceptrons (MLPs), and investigate their modular structure as trained on datasets of small images. A "module" as we conceive, is a set of neurons with strong internal connectivity but weak external connectivity. We find that MLPs that undergo training and weight pruning are significantly more modular than random networks. (Abstract excerpt)

Cosmic Code > networks

Kitsak, Maksim. Latent Geometry for Complementary Driven Networks. arXiv:2003.06665. A Northeastern University, Network Science Institute physicist elucidates another innate proclivity that networlds everywhere commonly appear to possess. As the abstract notes, reciprocal forms and/or actions seem to be drawn together so as to conceive a beneficial, more effective whole.

Networks of interdisciplinary teams, biological interactions as well as food webs are examples of networks that are shaped by complementarity principles: connections in these networks are preferentially established between nodes with complementary properties. We propose a geometric framework for this property by first noting that traditional methods which embed networks into latent metric spaces are not applicable. We then consider a cross-geometric representation which (i) follows naturally from the complementarity rule, (ii) is consistent with the metric property of the latent space, (iii) reproduces structural properties of real complementarity-driven networks and (iv) allows for prediction of missing links with accuracy surpassing similarity-based methods. (Abstract excerpt)

Previous   1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10  Next