Recent Additions: New and Updated Entries in the Past 60 Days
Displaying entries 31 through 45 of 71 found.
Cosmic Code > nonlinear > Rosetta Cosmos
Classification of Literary Works: Fractality and Complexity of the Narrative, Essay, and Research Article.
We cite this entry by a National Polytechnic Institute, Mexico interdisciplinary theorist as another example of how even our written, textual reports and stories are similarly suffused by the same nonlinear intricate forms and net dynamics as all other phases. A further substantial depth is then noticed by affinities to mathematical physics.
Linguistic typological research using quantitative measures is a current research topic based on the complex network approach. This project aims at showing the node degree, betweenness, shortest path length, clustering coefficient, and nearest neighborhood degree, as well as the fractal dimension, the complexity of a given network, the Area Under Box-covering, and the Area Under the Robustness Curve. The literary works of Mexican writers were classified according to their genre. Almost 90% of the full word co-occurrence networks were classified as a fractal. Empirical evidence is presented also finds that lemmatisation of the original text is a renormalisation network process that preserves their fractal property and reveals stylistic attributes by genre. (Abstract)
Cosmic Code > nonlinear > 2015 universal
Berezutskii, Aleksandr, et al.
Probing Criticality in Quantum Spin Chains with Neural Networks.
Journal of Physics: Complexity.
We cite entry this by an international team based in Canada, Russia, and Hungary including Jacob Biamonte as an example of how even quantum phenomena can and does exhibit nature’s independent preference for this widely prevalent state of dynamic balance.
The numerical emulation of quantum systems often requires an exponential number of degrees of freedom which translates to a computational bottleneck. Methods of machine learning have been used in adjacent fields for effective feature extraction and high-dimensional datasets. Recent studies have revealed that neural networks are suitable for the determination of macroscopic phases of matter as well as efficient quantum state representation. In this work, we address phase transitions in quantum spin chains and show that even neural networks with no hidden layers can be effectively trained to distinguish between magnetically ordered and disordered phases. Our results extend to a wide class of interacting quantum many-body systems and illustrate the wide applicability of neural networks to many-body quantum physics. (Abstract excerpt)
Cosmic Code > nonlinear > 2015 universal
Chialvo, Dante, et al.
Controlling a Complex System near Its Critical Point via Temporal Correlations.
Nature Scientific Reports.
Argentine systems neuroscientists along with Dietmar Plenz, NIMH, USA press on with more reasons and evidence that animate phenomena of many kinds from proteins to neural nets does appear to seek and arrive at a best balance of openness to changing environs while sustaining an orderly consistency. So again we ask and wonder that as scientific studies continue to illume a common “sweet spot” between complementary opposites, however might this natural knowledge be applied to human political parties whence presently conserve and create modes are fatally locked in mutual battle?
Many complex systems exhibit large fluctuations both across space and over time. These activities have often been linked to some kind of critical phenomena, where it is well known that the emerging correlation functions in space and time are closely related to each other. Here we test whether time correlation properties allow systems exhibiting a phase transition to self-tune to their critical point. We describe results in three models: the 2D Ising ferromagnetic model, the 3D Vicsek flocking model and a small-world neuronal network model. We demonstrate that feedback from the autocorrelation function shifts the system towards its critical point. Our results rely on universal properties of critical systems and are expected to be relevant to a variety of other settings. (Abstract)
Cosmic Code > nonlinear > 2015 universal
The last decade has witnessed an escalating interest in complex biological phenomena at all levels including macroevolution, neuroscience at different scales, and molecular biology. The observed complexity in nature is often traced to critical phenomena because it resembles the complexity found for critical dynamics in models and theory. However such resemblances are not enough to attribute criticality as the mechanism behind all forms of natural complexity. Even though out of equilibrium generic scale invariance can arise without fine-tuning of control parameters, it is found that biological systems operate in special regions of control parameter space which are critical in the sense that they separate phases of different dynamical behavior. More specifically, it seems that many biological systems reach a “sweet spot” where they attain maximal sensitivity to changes in the environment, while maintaining internal order. (1)
Friston, Karl, et al.
Parcels and Particles: Markov Blankets in the Brain.
We cite this entry from researchers based at University College London Wellcome Centre along with a companion posting Is the Free-energy Principle a Formal Theory of Semantics? by Maxwell Ramstead, et al (2007.09291). While cast in technical jargon they emphasize an active complementarity of neuronal parts and modular wholes, aka reciprocal segregation and integration, or separate and come together dynamic phases. As these cerebral processes empower a predictive brain, they are seen to reside in a far-from-equilibrium, self-organized critical state.
Cosmic Code > nonlinear > 2015 universal
Goblot, Valentin, et al.
Emergence of Criticality through a Cascade of Delocalization Transitions in Quasiperiodic Chains.
We cite this entry by thirteen Université Paris-Saclay, CNRS and ETH Zurich nanotechnologists to report and convey that even nature’s complex materiality seems to adopt and exhibit this common dynamic duality of more or less orderly phases.
Conduction through materials crucially depends on how ordered the materials are. Periodically ordered systems exhibit extended Bloch waves that generate metallic bands, whereas disorder is known to limit conduction and localize the motion of particles in a medium. In this context, quasiperiodic systems, which are neither periodic nor disordered, demonstrate exotic conduction properties, self-similar wavefunctions and critical phenomena. Here, we explore the localization properties of waves in a novel family of quasiperiodic chains obtained when continuously interpolating between two paradigmatic limits: the Aubry–André model, and the Fibonacci chain, known for its critical nature. We discover that the Aubry–André model evolves into criticality through a cascade of band-selective localization/delocalization transitions that iteratively shape the self-similar critical wavefunctions of the Fibonacci chain. (Abstract excerpts)
Cosmic Code > nonlinear > 2015 universal
Hidalgo, Jorge, et al.
Information-based Fitness and the Emergence of Criticality in Living Systems.
Proceedings of the National Academy of Sciences.
We cite this entry by senior system theorists JH, Jacopo Grilli, Samir Suweis, Miguel Munoz, Jayanth Banavar and Amos Maritan (search each) as an early perception of life’s universal propensity to seek and reside at an optimum self-organized criticality. By 2020, a few years later, this section can now document its robust worldwide affirmation. In this time of great need, if we might mindfully allow and witness, here is a vital finding that a phenomenal nature prefers an active reciprocity of conserve/create, person/group and ever so on. Rather than totalitarian or anarchic extremes, me individual vs. We together politics, a salutary resolve going forward would be a middle way complementarity.
Recently, evidence has been mounting that biological systems might operate at the borderline between order and disorder, i.e., near a critical point. A general mathematical framework for understanding this common pattern, explaining the possible origin and role of criticality in living adaptive and evolutionary systems, is still missing. We rationalize this apparently ubiquitous criticality in terms of adaptive and evolutionary functional advantages. We provide an analytical framework, which demonstrates that the optimal response to broadly different changing environments occurs in systems organizing spontaneously—through adaptation or evolution—to the vicinity of a critical point. Furthermore, criticality turns out to be the evolutionary stable outcome of a community of individuals aimed at communicating with each other to create a collective entity. (Significance)
Cosmic Code > Genetic Info > Paleo/Cosmo
Frantz, Laurent, et al.
Animal Domestication in the Era of Ancient Genomics.
Nature Reviews Genetics.
Queen Mary University of London, Trinity College, Dublin, Oxford University, and University of Toulouse (Ludovic Orlando) paleogeneticists apply the latest advances in nucleotide recovery and sequencing ability to reconstruct, in this instance, the historic occasions by which many feral, native creatures were enjoined as beneficial hominid and human co-inhabitants. This long process, as readers know, led to much evolutionary modification, as cited and described in this paper.
The domestication of animals led to a major shift in human subsistence patterns from hunter–gatherers to a sedentary agricultural lifestyle. Over the past 15,000 years, the phenotype and genotype of multiple animal species, such as dogs, pigs, sheep, goats, cattle and horses, have been substantially altered during their adaptation to the human niche. Recent innovations such as improved ancient DNA extraction methods and next-generation sequencing, have enabled whole ancient genomes to be read. These genomes have helped reconstruct how animals entered into domestic relationships with humans and were subjected to selection pressures. Here, we discuss and update key concepts in animal domestication in light of these novel contributions. (Abstract)
Cosmic Code > Genetic Info > DNA word
Folding of a Peptide Continuum: Semiotic Approach to Protein Folding.
The Palacky University, Olomouc, CR linguist continues her studies of innate affinities across genetic, metabolic and onto communicative codes, which each seem to have a common textual nature. What then might be their phenomenal message as we first grade readers try to interpret, translate and understand?
In this paper I attempt to study the notion of “folding of a semiotic continuum” in a direction of a possible application to the biological processes (protein folding). The process of obtaining protein structures is compared to the folding of a semiotic continuum. Consequently, peptide chain is presented as a continuous line potential to be formed (folded) in order to create functional units. The functional units are protein structures having a certain usage in the cell or organism (semiotic agents). Moreover, protein folding is analyzed in terms of tension between syntax and semantics. (Abstract)
Cohen, Irun and Assaf Marron.
The Evolution of Universal Adaptations of Life is Driven by Universal Properties of Matter: Energy, Entropy and Interaction.
While the olden neoDarwinian version of selection alone persists, Weizmann Institute of Science, Israel biomathematicans (search IC) contribute to a revolutionary genesis synthesis by viewing life’s oriented emergence as a complex dynamical process which involves not only objects, be they genes or animals, but equally real cooperative relations between them. I log this in along with a brain research paper (Harang Ju) which emphasizes a similar emphasis of neural interactions, and a symbiosis report (F. Prosdocimi) as another example of this pervasive entity/group mutuality. As a result, in each and all cases a whole, composite genome, connectome and regnant organism in community is thus achieved.
The evolution of multicellular eukaryotes expresses two sorts of adaptations: local aspects like fur or feathers, which serve species in bioregions, and universal adaptations like microbiomes or sexual reproduction, which distinguish multicellularity in any environment. We reason that the mechanisms which drive them should be universal, and based on properties of matter and systems: energy, entropy, and interaction. Energy from the sun creates complex arrangements while metabolic networks channel it to form cooperative interactions. Entropy, a term for disorder, acts as a selective force.
Dynamic Interactions restrain entropy and enable survival and propagation of integrated living systems. The “unit” of evolution is not a discrete entity what evolves are related interactions at multiple scales. Our “survival-of-the-fitted” can explain universal adaptations, including microbiomes, reproduction, diversification, altruism, environmental niches and more. We propose ways to test our theories, and implications for the wellbeing of humans and the biosphere. (Abstract excerpts)
Cooperative interactions are pervasive and central to life: We define an interaction as a relationship between two or more entities involving a transfer or exchange of matter, information and/or energy. Interactions include both struggle and cooperation: in a struggle, the participants each strive to win and dominate the others – who become the losers. In a cooperative interaction, there are no losers; the participants each gain some benefit, or at the least suffer no loss. (5)
Biological Evolution is Coarsely Deterministic.
Journal of Big History.
This paper was presented by the veteran Howard University biologist at the Life in the Universe: Big History, SETI and the Future conference in Milan in July 2019. In essence, it continues his insightful views that “playing the tape over again” would necessarily lead to life’s development into human-like beings and cognitive capabilities because biochemical and thermal properties of the geobiosphere would again impel and channel it that way.
Starting with the origin of life, I argue that the general pattern of the tightly coupled evolution of biota and climate on Earth has been the very probable outcome from a relatively small number of possible histories at the macroscale, given the same initial conditions. Thus, the evolution of the biosphere self-selects a pattern of biotic evolution that is coarsely deterministic, with critical constraints likely including surface temperature as well as oxygen and carbon dioxide levels in the atmosphere. Environmental physics and chemistry drive the major events in biotic evolution, including photosynthesis and oxygenic photosynthesis, the emergence of new cell types (eucaryotes) from the merging of complementary metabolisms, multicellularity and even encephalization. (Abstract)
Quickening Evolution > major
Evolving a Major Transition in the Internet Age.
This 2020 posting by the veteran environmentalist and filmmaker in collaboration with the SUNY Binghamton evolutionary practitioner and author David Sloan Wilson is located on Wilson’s The Evolution Institute site. By way of text and a DSW interview, a project is scoped out is based upon a likely but rare perception that a further emergent stage of global proportions can be seen as much underway. By this extension, our anthropocene phase is composed of wholly interconnected information but beset by disjointed nations and societies. A vital need is to implement the “new ways to cooperate at higher levels of complexity” that usually distinguish and facilitate these transitions. To date, this is only concerted effort to carry forth life’s ascendant, quickening scale to its sustainable planetary fulfillment.
PROSOCIAL is a framework for improving the efficacy of groups that is being developed by the Evolution Institute. It is based on eight core design principles – originally derived by Elinor Ostrom for groups who manage natural resources – that are needed by most groups whose members must work together to achieve common goals: Strong group identity and understanding of purpose; Fair distribution of costs and benefits; Inclusive decision-making; Monitoring agreed-upon behaviors; Fast and fair conflict resolution; Appropriate relations with other groups. (Alan Honick website)
Quickening Evolution > Systems Biology
Gilpin, William, et al.
Learning Dynamics from Large Biological Data Sets: Machine Learning Meets Systems Biology.
Current Opinion in Systems Biology.
As is the current case for many scientific fields, Harvard and Dartmouth researchers scope out ways by which a suitable apply of AI deep neural net techniques can effectively interface with life studies so to enhance research methods and results.
In the past few decades, mathematical models based on dynamical systems theory have provided new insight into diverse biological systems. In this review, we ask whether the recent success of machine learning techniques for large-scale biological data analysis can provide a complementary, beneficial approach to traditional modeling. Recent applications of machine learning have been used to study biological dynamics in diverse systems from neuroscience to animal behavior. We propose several avenues for bridging dynamical systems theory with large-scale analysis enabled by machine learning. (Abstract excerpt)
Earth Life > Common Code
Taken together, these results introduce the question of whether universal mathematical constraints determine certain aspects of large biological systems whose interacting units spontaneously collapse onto a low-dimensional manifold. Has evolution driven complex biological networks toward these emergent motifs, and do they confer adaptive benefits such as stabilizing an ecosystem against an invasive predator, or suppressing unwanted fluctuations in a genetic circuit? We hope that further development of models at the intersection of machine learning and dynamical theory will provide unified insight into these questions. (6)
The Plant Body as a Network of Semi-Autonomous Agents.
Philosophical Transactions of the Royal Society B.
A Lorand Eotvos University, Budapest systems botanist shows how even life’s flora phase is distinguished and enabled by agent/link network modularities as they sense, process and convey vital information. See also Percolation Theory Suggests Some General Features Across Environmental Gradients by BO and Robert Juhasz at arXiv:1909.00585.
Plants can solve many difficult tasks while adjusting their growth and development to the environment. They can explore and exploit several resources, even when their distributions vary in space and time. Current research has found that the functional use of modular features enables the plant to adjust a flow of information and resources to ever changing conditions. Experiments have yielded many results about these processes but a theoretical model to encompass the high number of components and interactions has lagged behind. In this paper, I propose a framework on the basis of network theory, viewing the plant as a group of connected, semi-autonomous agents. I review some characteristic plant responses to the environment through changing the states of agents and/or links. (Abstract excerpt)
Earth Life > Nest > Geological
Cornacchia, Loreta, et al.
Self-Organization of River Vegetation Leads to Emergent Buffering of River Flows and Water Levels.
Proceedings of the Royal Society B.
As complexity studies of “tangled banks” continue to reveal inherent patterns and processes, Dutch and British geoecologists based at the Royal Netherlands Institute for Sea Research quantify how they riverine environs dynamically organize themselves so as to keep up with ever changing conditions.
Global climate change will impact hydrodynamic conditions in stream ecosystems but there is limited understanding of how they interact and change. By mathematical modelling of field data, we demonstrate that bio-physical feedback between plant growth and flow redistribution causes spatial self-organization of in-channel vegetation that buffers for changed hydrological conditions. The interplay of vegetation growth and hydrodynamics results in a separation of the stream into densely vegetated, low-flow zones divided by unvegetated channels of higher flow velocities. Our results provide important evidence of how plant-driven self-organization allows stream ecosystems to adapt to changing hydrological conditions, maintaining suitable hydrodynamic conditions to support high biodiversity. (Abstract excerpt)
Earth Life > Nest > Geological
Ferreira, Douglas, et al.
Long-range Correlation Studies in Deep Earthquakes Global Series.
Online August 27,
We highlight this entry by Instituto Federal do Rio de Janeiro seismologists because it not only considers a realm of internal quakes at depths of 50 miles, but proceeds to characterize them by way of multiplex network theories. As the second quote notes, the same dynamic scale-invariance found in every other realm is present in this basic geological domain. As alluded to here, a self-organized criticality can also be detected. And as I log in papers about neural and symbiotic phases, a 2020 perception of an independent mathematic source force which is in universal effect becomes strongly evident. For more see a 2016 book Methods of Statistical Physics Applied to Seismology from the Viewpoint of Complex Networks by this extended group, and earlier Self-Organized Criticality and Earthquakes at arXiv:0711.1750.
In the present paper we have conducted studies on seismological properties using worldwide data of deep earthquakes (70 km), considering events with magnitude greater than 4.5. We have addressed this new realm of seismic activity by a complex networks perspective which reveals scale-free and small-world features, strengthening the use of a time window model to construct epicenters. The results for deep events were further analyzed using Nonextensive Statistical Mechanics and corroborate with those found for the shallow quakes, since the connectivity distribution also follows a q-exponential distribution and the scaling behavior is present. Our findings thus reinforce correlations between earthquakes and the criticality of the seismological system. (Abstract)
Several phenomena in nature exhibit characteristics of complex systems such as nonlinear dynamics, fractal dimensions, power law distributions and long-range spatiotemporal memory, where the earthquakes being one example. Theories of complex systems have been applied to many different areas of knowledge for a long time, such aseconomics, computer science, mechanical engineering, biology and chemistry. In the last decades, works have used complex systems theories to perform studies on spatiotemporal properties of seismicity. In that sense, we can highlight the important approach of using complex networks concepts, which provides powerful procedures to analyse the interactions and correlations between elements of complex systems, giving efficient descriptions about the dynamics of such systems. (1)