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A Sourcebook for the Worldwide Discovery of a Creative Organic Universe
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Recent Additions: New and Updated Entries in the Past 60 Days
Displaying entries 46 through 60 of 107 found.


Ecosmos: A Revolutionary Fertile, Habitable, Solar-Bioplanet, Incubator Lifescape

Animate Cosmos > Self-Selection

Ostrander, Chadlin, et al. Onset of coupled atmosphere–ocean oxygenation 2.3 billion years ago.. Nature. June 1, 2024. Seven geophysicists at the University of Utah and the Woods Hole Oceanographic Institution can now achieve a more detailed quantification of this crucial passage to a stable atmosphere with a vital 21% oxygen and 79% nitrogen composition. As a result, we gain more prior evidence of how chancy the occasion of Earth life’s evolutionary emergence to a worldwide intelligence has actually been. And just now a natural genesis by virtue of all this knowledge we peoples must to unite and select our own fittest success. See also Life on the Edge: The Cambrian Marine Realm and Oxygenation by Sara Pruss1, and Benjamin Gill in Annual Review of Earth and Planetary Sciences (Vol. 52, 2024).

The initial rise of molecular oxygen after the Archaean–Proterozoic transition 2.5 bya was more complex than the single step-change once envisioned. Sulfur mass-independent fractionation records suggest that the rise of atmospheric O2 was oscillatory, with multiple returns to an anoxic state until perhaps 2.2 bya. Yet few constraints exist for contemporaneous marine dynamics, precluding a holistic understanding of planetary oxygenation. Here we report thallium (Tl) isotope ratio and redox-sensitive element data for marine shales from the Transvaal Supergroup, South Africa. Our data connect atmospheric O2 dynamics on early Earth with the marine realm, marking an important turning point in Earth’s redox history away from heterogeneous and highly localized ‘oasis’-style oxygenation. (Excerpt)

Animate Cosmos > Self-Selection

Stern, Robert and Taras Gerya. The importance of continents, oceans and plate tectonics for the evolution of complex life: implications for finding e. Nature Scientific Reports. 14/8552, 2024. A UT Dallas Earth system scientist and an ETU Zurich geochemist make a latest strong case that our past billion years of drifting surface forms with a general land/sea ratio of 30/70 ratio is especially conducive for a life’s developmental emergence and also seems to be a rarest habitable planet occasion.

Within astronomical and biological parameters, the Drake Equation predicts that there should be many exoplanets in our galaxy with active communicative civilizations (ACCs). This optimism, however, is not supported by evidence, often referred to as the Fermi Paradox. Here, we elaborate on the importance of planetary tectonics for biological evolution by adding two additional terms to the Drake Equation: foc (the fraction of habitable exoplanets with continents and oceans) and fpt (the fraction of habitable exoplanets with continents and oceans that have had plate tectonics operating for at least 0.5 Ga). We propose that an absence of ACCs reflects the scarcity of continents and oceans on exoplanets with primitive life. (Excerpt)

Ecosmomics: Independent, UniVersal, Complex Network Systems and a Genetic Code-Script Source

Cosmic Code

Ball, Philip. The New Math of How Large-Scale Order Emerges. Quanta. June 10, 2024. The polymath British science writer provides an update survey as complexity theorists get closer to explaining how many local interactive entities (neurons, birds, people) can give rise to predictable global formations. The current work of Jim Critchfield, Fernando Rosas, Anil Seth (search each) and others is profiled with an especial notice of Software in the natural world by F. Rosas, et al (arXiv:2402.09090). See also Dynamical independence: Discovering emergent macroscopic processes in complex dynamical systems by L Barnett and A. Seth in Phys. Rev. E (108/014304, 2023) and Evolving reservoir computers reveals bidirectional coupling between predictive power and emergent dynamics by Hanna Tolle, et al at arXiv:2406.19201.

Rosas’ framework could help complex systems researchers see when they can and can’t hope to develop predictive coarse-grained models. When a system meets the key requirement of being computationally closed, “you don’t lose any faithfulness by simulating the upper levels and neglecting the lower levels,” he said. But ultimately Rosas hopes an approach like his might answer some deep questions about the structure of the universe — why, for example, life seems to exist only at scales intermediate between the atomic and the galactic. (PB)

Cosmic Code > nonlinear > networks

Baptista, Anthony, et al. Mining higher-order triadic interactions. arXiv:2404.14997. Into this year, Queen Mary University of London, Alan Turing Institute, Central European University, Vienna, University of Southampton, UK, and Potsdam Institute for Climate Impact Research system theorists including Ginestra Bianconi, and Jurgen Kurths exemplify how vast and richly adorned nature’s network anatomy and physiology really is by still finding further multiplex dimensions.

Complex systems often present higher-order interactions which require us to go beyond their description in terms of pairwise networks. Triadic interactions are a fundamental type of higher-order interaction that occurs when one node regulates the interaction between two other nodes. Triadic interactions are a fundamental type of higher-order networks, found in a large variety of biological systems from neuron-glia to gene-regulation and ecosystems. In this article, a theoretical principle is used to model and mine this triune phase from node metadata, which is applied to Acute Myeloid Leukemia. Our work reveals higher-order properties which to advance our understanding of complex systems ranging from biology to the climate. (Excerpt)

Cosmic Code > nonlinear > networks

gallo, Luca, et al. Gallo, Luca, et al. Higher-order correlations reveal complex memory in temporal hypergraphs. Nature Communications. 15/4754, 2024. Central European University, Vienna and Queen Mary University, London theorists including Vito Latora and Federico Battiston continue to explicate the many structural, informative, knowledgeable qualities of nature’s brain-like anatomy and physiology.

Many real-world complex systems are characterized by interactions in groups that change in time. Current temporal network approaches, however, are unable to describe group dynamics based on pairwise interactions only. Here, we introduce a framework for higher-order correlations to characterize their temporal organization. We use a model of temporal hypergraphs with non-Markovian group interactions, which reveals complex memory as a fundamental mechanism underlying the emerging pattern in the data. (Excerpt)
In conclusion, our work sheds light on the multifaceted nature of memory that emerges at different scales in real-world interacting systems. Beyond the scope of network science, we hope that our framework can open new avenues to reveal the higher-order dynamics of coherent structures in a variety of physical systems, from multi-fragmentation in nuclear physics to vortex-vortex interaction in the atmosphere or other fluid dynamical systems. (4)

Cosmic Code > nonlinear > networks

Pal, Kumar Palash, et al. Pal, Kumar Palash, et al. Global synchronizatin in generalized multilayer higher-order networks. arXiv:2406.03771. Indian Statistical Institute, Kolkata and University of Maribor, Slovenia system physicists including Matjaz Perc and Dibakar Ghosh continue to trace multiplex features and benefits of nature’s essential organismic anatomy and physiology as it becomes evident and suffuses from physical to societal interactive vitalities.

Networks incorporating higher-order interactions introduce novel dynamics into various processes such as synchronization. Here, we investigate these coordinations in multilayer networks beyond pairwise connections, both within and across layers. We demonstrate the existence of a stable global synchronous state resembling a master stability function. Our findings are supported by simulations using Hindmarsh-Rose neuronal and Rössler oscillators which illustrate how synchronization is facilitated by multiplex forms, over scenarios involving interactions within single layers. (Excerpt)

The study of complex networks has emerged as a prominent area of research. This interest growing arises from their capacity to model interconnected dynamical systems across many fields, such as physics, biology, ecology, social sciences, and engineering [1–3]. These networks are comprised of nodes, representing entities or elements, and links, representing connections or pairwise interactions between them. Many real-world systems can be conceptualized as multilayer networks include transportation networks [6], neuronal networks in the brain [7, 8], and various types of social networks [9]. A multilayer network consists of individual networks, each with its set of nodes and links (referred to as intralayer links), interconnected through interlayer links. The representation of multilayer networks hinges on a fundamental assumption: the complex connections among individuals within and across layers are comprehensively elucidated through pairwise links.

Cosmic Code > nonlinear > Rosetta Cosmos

Fortnow, Lance. Computation Is All Around Us and You Can See It if You Try. Quanta. June 12, 2024. The dean of the College of Computing at the Illinois Institute of Technology reflects on years of wondering how to experience and explain an extant, active reality that well seems as the result of a separate domain of immaterial, software-like, informational, maybe linguistic codings.

Do we have a way to manage this randomness and complexity? The recent progress we have seen in AI gives us a glimpse into what it would mean to do just that. Information can be split into a structured part and a random part. Take English for example. There is an underlying complex structure that describes the language, and the sentences that society has produced over time are, in effect, a random sampling from that structure. Recent advances in machine learning have allowed us to take these random samples and recover much of the orderly basics that inform.

I’ve been very lucky. I could build a research career around the machines that encompass the way I feel the world. Whether you hear the music, the algebra, computation, biology, magic, art, or some other way of understanding the world, listen to it. Who knows what secrets you may learn?

Cosmic Code > nonlinear > 2015 universal

Ansell, Helen and Istvan Kovacs. Unveiling universal aspects of the cellular anatomy of the brain. Communications Physics. 7/184, 2024. . Northwestern University systems neuroscientists describe the latest neuroimaging insight findings which add strong support to a definitive self-organized, critically poised, invariance. They next view the relative neural architecture of other mammals and onto insects to observe the same definitive patterns and processes.

Recent cellular volumetric brain reconstructions have revealed even higher levels of anatomic complexity. But which aspects to focus on when by way of computational models remains a challenge. Our own work has now been able to perceive an intricate brain anatomy satisfies universal scaling laws to an extent as to reveal a structural criticality. To illustrate, we estimated critical exponents in human, mouse and fruit fly brains and show they are consistent between these organisms. Such universal quantities are robust to many microscopic details of the cellular structures of individual brains. This is a key step towards generative computational approaches and toward which sense one animal may be akin to another. (Abstract)

In regard, neuronal complexity can be described through its fractal dimension which exemplifies a scale invariance, or self-similarity which occurs in the structure and function of the cerebral cortex, human connectome, and synaptic network of multiple organisms. We next propose that statistical physics can provide a further guide to discern cellular complexity. An analysis of cell size, as well as pairwise and higher-order correlations, can then signify collective phenomena close to criticality. We estimate a set of exponents from for each subject organism and find critical scaling relations, again indicating that brains reside in the vicinity of criticality. (1,2)

Cosmic Code > nonlinear > 2015 universal

Cai, Chao-Ran, et al. Epidemic criticality in temporal networks. Physics Reviews Research. 6/L022017 April, 2024. Northwest University, China, Shaanxi Key Laboratory for Physics Frontiers, Xi’an, China and Aalto University, Espoo, Finland (Petter Holme) theorists discern the deep presence of self-organized critical transitions even in public phenomena such as disease vectors amongst diverse, many body populations.

Analytical studies of network epidemiology often focus on the extreme situations where the timescales of network dynamics are well separated (longer or shorter) from that of propagation. In realistic scenarios, however, these timescales could be similar, which has profound implications for modeling. Combining Monte Carlo simulations and mean-field theory, we analyze the behavior of susceptible-infected epidemics in the vicinity of the critical threshold of temporal networks. Dynamic correlations from being close to infected nodes increases the likelihood of infection and drive the state in the opposite direction. (Excerpt)

Cosmic Code > nonlinear > Common Code

Lynn, Christopher, et al. Heavy-tailed neuronal connectivity arises from Hebbian self-organization. Nature Physics. January 2024, . Into this year, CCNY, Princeton and University of Chicago neuroscientists are able to report a constant cerebral topology which appears constant across mammalian species. As a result their next insight is to attribute this genomic commonality to the presence of universal, independent self-organizing forces.

The connections in networks of neurons are heavy-tailed, with a small number of connected more strongly. However, it remains unclear whether these patterns emerge from underlying mechanisms. Here we propose a minimal model of synaptic self-organization wherein links are pruned and synaptic strength rearranges by a mixture of preferential and random dynamics. Under these generic rules, networks evolve to produce connectivities that are scale-free with a power-law exponent. We confirm these predictions in the connectomes of several animals, suggesting that this cerebral phenomena may arise from general principles of network self-organization rather than mechanisms specific to individual species or systems.
Together, the results and models developed here demonstrate how two fundamental features of connectomes—heavy–tailed connectivity and clustering—can arise from simple network dynamics, providing a framework for future investigations into the self–organization of neuronal connectivity. (13)

Cosmic Code > Genetic Info

Ken, Megan, et al. RNA conformational propensities determine cellular activity. Nature. 617/835, 2023. We post this entry by Duke University School of Medicine, Johns Hopkins University, Gladstone Institute of Virology, San Francisco, Stanford University, and Columbia University (Hashim Al-Hashimi) bioresearchers for itself and to record its constant citation of “propensities” to necessarily enact vital nucleotide biomolecular metabolic processes. In regard, such a perception can move beyond abstract “mechanisms” to a deeper sense of an innately organic procreativity.

Cellular processes are due to interactions between biomolecules and intermolecular contacts, which if disrupted, alter cell physiologies. As a result, binding affinity and cellular activity crucially depend both on the strength of the contacts and on the inherent propensities to form binding-competent conformational states. Here we altered the propensities for forming the protein-bound conformation of HIV-1 TAR RNA and the extent of HIV-1 Tat-dependent transactivation in cells. Our results establish the role of ensemble-based conformational propensities in cellular activity. (Excerpt)

Cosmic Code > Genetic Info

Liu, Shuming, et al. From Nucleosomes to Compartments: Physicochemical Interactions Underlying Chromatin Organization. Annual Review of Biophysics.. Volume 53, 2024. MIT system biologists add a latest chapter about life’s serial metabolic developments which can be traced to informative and topological genomic expressions. See also The Geometry of Chromatin by Subhash Kak at arXiv:2402.09408.

Chromatin organization plays a critical role in cellular function by regulating access to genetic information. However, its folding is hard to analyze due to a complex, multiscale nature. Advances have been made in vitro systems, individual nucleosomes, and the role of physicochemical forces in stabilization. But the resemblance between in vitro and in vivo chromatin conformations and internucleosomal interactions are subjects of debate. This article reviews experimental and computational studies which highlight intrinsic interactions between nucleosomes and their roles in chromatin folding. (Abstract).

Chromatin is a complex of DNA and protein found in eukaryotic cells.[1] The primary function is to package long DNA molecules into compact, denser structures. A nucleosome is a section of DNA that is wrapped around a core of proteins.

Cosmic Code > Genetic Info > Paleo/Cosmo

Mazzucato, Camilla et al.. "A network of mutualities of being": socio-material archaeological networks and biological ties at Çatalhöyük.. arXiv:2406.19149.. University of Copenhagen and Middle East Technical University, Ankara paleogeneticists add a further dimension to retrospective studies with regard to social and cultural aspects by an ability to identify relative interactivities.

Recent advances in archaeogenomics have the potential to further our understanding of past social dynamics at a range of scales. In this paper we propose a Network Science framework to study and integrate genomic data and material culture about biological relatedness and social organization at the Neolithic site of Çatalhöyük. Methodologically, we propose the use of network variances to investigate the concentration of biological relatedness and material culture within neighborhood dwellings. This approach allowed us to observe how material culture similarity between residences gives valuable information on relationships between individuals and how biogenetic ties concentrate at specific localities.

Cosmic Code > Genetic Info > DNA word

Fang, Jing-Kai, et al. Divide-and-Conquer Quantum Algorithm for Hybrid de novo Genome Assembly of Short and Long Reads. PRX Life. 2/023006, 2024. We note this contribution by BGI Research, Shenzhen, China computational geneticists as a frontier instance of how genetic studies are being taken to a new dimension by virtue of quantum capabilities. The evidential result implies that life’s implicate genomic proscription can gain an affinity with this fundamental physical ground.

Researchers have begun to apply quantum computing in genome assembly implementation, but the issue of repetitive sequences remains unresolved. Here, we propose a hybrid assembly quantum algorithm using short reads and long reads which utilizes divide-and-conquer strategies to approximate the ground state of a larger Hamiltonian while conserving quantum resources. The convergence speed is improved via the problem-inspired Ansatz based on the known information. In addition, we verify that entanglement within quantum circuits may accelerate the assembly path optimization. (Excerpt)

Cosmic Code > Genetic Info > DNA word

Hwang, Yunha, et al. Genomic language model predicts protein co-regulation and function. Nature Communications.. 15/2880, 2024. We enter this work by Cornell, Harvard, Johns Hopkins, and MIT biologists including Sergey Ovchinnikov as another literate version of the textual affinity of nucleotides and narratives. See also ProteinEngine: Empower LLM with Domain Knowledge for Protein Engineering at arXiv:2405.06658.


Deciphering the relationship between a gene and its genomic context is vital to understand and modify biological systems. Machine learning can study the sequence-structure-function paradigm but higher order genomic information remains elusive. Evolutionary processes dictate genomic contexts in which a gene occurs across phylogenetic distances, and these emergent patterns can be leveraged to uncover functional relationships. Here, we train a genomic language model (gLM) on metagenomic scaffolds to uncover regulatory relationships between genes. Our findings illustrate that gLM’s deep learning of metagenomes is an effective approach to encode the semantics and syntax of genes and uncover complex relationships in a genomic region. (Abstract)

The unprecedented amount and diversity of metagenomic data presents opportunities to learn hidden patterns and structures of biological systems. With larger amounts of data, these models can disentangle the complexity of organismal genomes and their encoded functions. The work presented here validates the concept of genomic language modeling. Our implementation of the masked genomic language modeling illustrates the feasibility of training such a model, and provides evidence that biologically meaningful information is being captured in learned contextualized embeddings. (9)

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