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Hamilton NP, Burton PJ. Wildfire disturbance reveals evidence of ecosystem resilience and precariousness in a forest–grassland mosaic. Ecosphere 2023. [DOI: 10.1002/ecs2.4460] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/22/2023] Open
Affiliation(s)
- Nicholas P. Hamilton
- Ministry of Forests, Range Branch Prince George British Columbia Canada
- Natural Resources and Environmental Studies Program University of Northern British Columbia Prince George British Columbia Canada
| | - Philip J. Burton
- Department of Ecosystem Science and Management University of Northern British Columbia Terrace British Columbia Canada
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Hopkins JR, Huffman JM, Jones NJ, Platt WJ, Sikes BA. Pyrophilic Plants Respond to Postfire Soil Conditions in a Frequently Burned Longleaf Pine Savanna. Am Nat 2023; 201:389-403. [PMID: 36848518 DOI: 10.1086/722569] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/04/2022]
Abstract
AbstractFire-plant feedbacks engineer recurrent fires in pyrophilic ecosystems like savannas. The mechanisms sustaining these feedbacks may be related to plant adaptations that trigger rapid responses to fire's effects on soil. Plants adapted for high fire frequencies should quickly regrow, flower, and produce seeds that mature rapidly and disperse postfire. We hypothesized that the offspring of such plants would germinate and grow rapidly, responding to fire-generated changes in soil nutrients and biota. We conducted an experiment using longleaf pine savanna plants that were paired on the basis of differences in reproduction and survival under annual ("more" pyrophilic) versus less frequent ("less" pyrophilic) fire regimes. Seeds were planted in different soil inoculations from experimental fires of varying severity. The more pyrophilic species displayed high germination rates followed by species-specific rapid growth responses to soil location and fire severity effects on soils. In contrast, the less pyrophilic species had lower germination rates that were not responsive to soil treatments. This suggests that rapid germination and growth constitute adaptations to frequent fires and that plants respond differently to fire severity effects on soil abiotic factors and microbes. Furthermore, variable plant responses to postfire soils may influence plant community diversity and fire-fuel feedbacks in pyrophilic ecosystems.
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Lucia U, Deisboeck TS, Ponzetto A, Grisolia G. A Thermodynamic Approach to the Metaboloepigenetics of Cancer. Int J Mol Sci 2023; 24:ijms24043337. [PMID: 36834748 PMCID: PMC9960652 DOI: 10.3390/ijms24043337] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/18/2023] [Revised: 02/03/2023] [Accepted: 02/03/2023] [Indexed: 02/11/2023] Open
Abstract
We present a novel thermodynamic approach to the epigenomics of cancer metabolism. Here, any change in a cancer cell's membrane electric potential is completely irreversible, and as such, cells must consume metabolites to reverse the potential whenever required to maintain cell activity, a process driven by ion fluxes. Moreover, the link between cell proliferation and the membrane's electric potential is for the first time analytically proven using a thermodynamic approach, highlighting how its control is related to inflow and outflow of ions; consequently, a close interaction between environment and cell activity emerges. Lastly, we illustrate the concept by evaluating the Fe2+-flux in the presence of carcinogenesis-promoting mutations of the TET1/2/3 gene family.
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Affiliation(s)
- Umberto Lucia
- Dipartimento Energia “Galileo Ferraris”, Politecnico di Torino, Corso Duca degli Abruzzi 24, 10129 Torino, Italy
- Correspondence: (U.L.); (G.G.); Tel.: +39-011-090-4558 (U.L.)
| | - Thomas S. Deisboeck
- Department of Radiology, Harvard-MIT Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Charlestown, Boston, MA 02129, USA
| | - Antonio Ponzetto
- Department of Medical Sciences, University of Torino, Corso A.M. Dogliotti 14, 10126 Torino, Italy
| | - Giulia Grisolia
- Dipartimento Energia “Galileo Ferraris”, Politecnico di Torino, Corso Duca degli Abruzzi 24, 10129 Torino, Italy
- Dipartimento Scienza Applicata e Tecnologia, Politecnico di Torino, Corso Duca degli Abruzzi 24, 10129 Torino, Italy
- Correspondence: (U.L.); (G.G.); Tel.: +39-011-090-4558 (U.L.)
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Gentili PL, Stano P. Monitoring the advancements in the technology of artificial cells by determining their complexity degree: Hints from complex systems descriptors. Front Bioeng Biotechnol 2023; 11:1132546. [PMID: 36815888 PMCID: PMC9928734 DOI: 10.3389/fbioe.2023.1132546] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/27/2022] [Accepted: 01/18/2023] [Indexed: 02/04/2023] Open
Affiliation(s)
- Pier Luigi Gentili
- Dipartimento di Chimica, Biologia e Biotecnologie, Università degli Studi di Perugia, Perugia, Italy,*Correspondence: Pier Luigi Gentili, ; Pasquale Stano,
| | - Pasquale Stano
- Department of Biological and Environmental Sciences and Technologies (DiSTeBA), University of Salento, Ecotekne, Lecce, Italy,*Correspondence: Pier Luigi Gentili, ; Pasquale Stano,
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Medhin LB, Beasley AB, Warburton L, Amanuel B, Gray ES. Extracellular vesicles as a liquid biopsy for melanoma: Are we there yet? Semin Cancer Biol 2023; 89:92-98. [PMID: 36706847 DOI: 10.1016/j.semcancer.2023.01.008] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2022] [Revised: 01/10/2023] [Accepted: 01/23/2023] [Indexed: 01/26/2023]
Abstract
Melanoma is the most aggressive form of skin cancer owing to its high propensity to metastasise in distant organs and develop resistance to treatment. The scarce treatment options available for melanoma underscore the need for biomarkers to guide treatment decisions. In this context, an attractive alternative to overcome the limitations of repeated tissue sampling is the analysis of peripheral blood samples, referred to as 'liquid biopsy'. In particular, the analysis of extracellular vesicles (EVs) has emerged as a promising candidate due to their role in orchestrating cancer dissemination, immune modulation, and drug resistance. As we gain insights into the role of EVs in cancer and melanoma their potential for clinical use is becoming apparent. Herein, we critically summarise the current evidence supporting EVs as biomarkers for melanoma diagnosis, prognostication, therapy response prediction, and drug resistance. EVs are proposed as a candidate biomarker for predicting therapeutic response to immune checkpoint inhibition. However, to realise the potential of EV analysis for clinical decision-making strong clinical validation is required, underscoring the need for further research in this area.
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Affiliation(s)
- Lidia B Medhin
- Centre for Precision Health, Edith Cowan University, Joondalup WA 6027, Australia; School of Medical and Health Sciences, Edith Cowan University, Joondalup WA 6027, Australia
| | - Aaron B Beasley
- Centre for Precision Health, Edith Cowan University, Joondalup WA 6027, Australia; School of Medical and Health Sciences, Edith Cowan University, Joondalup WA 6027, Australia
| | - Lydia Warburton
- Centre for Precision Health, Edith Cowan University, Joondalup WA 6027, Australia; School of Medical and Health Sciences, Edith Cowan University, Joondalup WA 6027, Australia; Department of Medical Oncology, Fiona Stanley Hospital, Murdoch, Australia
| | - Benhur Amanuel
- School of Medical and Health Sciences, Edith Cowan University, Joondalup WA 6027, Australia; Department of Anatomical Pathology PathWest, QEII Medical Centre, Nedlands WA 6009, Australia
| | - Elin S Gray
- Centre for Precision Health, Edith Cowan University, Joondalup WA 6027, Australia; School of Medical and Health Sciences, Edith Cowan University, Joondalup WA 6027, Australia.
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Ahmad RA, Imron MA, Ramadona AL, Lathifah N, Azzahra F, Widyastuti K, Fuad A. Modeling social interaction and metapopulation mobility of the COVID-19 pandemic in main cities of highly populated Java Island, Indonesia: An agent-based modeling approach. Front Ecol Evol 2023. [DOI: 10.3389/fevo.2022.958651] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/21/2023] Open
Abstract
IntroductionCoronavirus transmission is strongly influenced by human mobilities and interactions within and between different geographical regions. Human mobility within and between cities is motivated by several factors, including employment, cultural-driven, holidays, and daily routines.MethodWe developed a sustained metapopulation (SAMPAN) model, an agent-based model (ABM) for simulating the effect of individual mobility and interaction behavior on the spreading of COVID-19 viruses across main cities on Java Island, Indonesia. The model considers social classes and social mixing affecting the mobility and interaction behavior within a sub-population of a city in the early pandemic. Travelers’ behavior represents the mobility among cities from central cities to other cities and commuting behavior from the surrounding area of each city.ResultsLocal sensitivity analysis using one factor at a time was performed to test the SAMPAN model, and we have identified critical parameters for the model. While validation was carried out for the Jakarta area, we are confident in implementing the model for a larger area with the concept of metapopulation dynamics. We included the area of Bogor, Depok, Bekasi, Bandung, Semarang, Surakarta, Yogyakarta, Surabaya, and Malang cities which have important roles in the COVID-19 pandemic spreading on this island.DiscussionOur SAMPAN model can simulate various waves during the first year of the pandemic caused by various phenomena of large social mobilities and interactions, particularly during religious occasions and long holidays.
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Beer RD, Di Paolo EA. The theoretical foundations of enaction: Precariousness. Biosystems 2023; 223:104823. [PMID: 36574923 DOI: 10.1016/j.biosystems.2022.104823] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2022] [Revised: 11/28/2022] [Accepted: 12/14/2022] [Indexed: 12/25/2022]
Abstract
Enaction is an increasingly influential approach to cognition that grew out of Maturana and Varela's earlier work on autopoiesis and the biology of cognition. As with any relatively new scientific discipline, the enactive approach would benefit greatly from a careful analysis of its theoretical foundations. Here we initiate such an analysis for one of the core concepts of enaction, precariousness. Specifically, we consider three types of fragility: systemic, processual and thermodynamic. Using a glider in the Game of Life as a toy model, we illustrate each of these fragilities and examine the relationships between them. We also argue that each type of fragility is characterized by which aspects of a system are hardwired into its definition from the outset and which aspects are emergent and hence vulnerable to disintegration without ongoing maintenance.
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Affiliation(s)
- Randall D Beer
- Cognitive Science Program, Luddy School of Informatics, Computing and Engineering, Indiana University, USA.
| | - Ezequiel A Di Paolo
- Ikerbasque, Basque Foundation for Science, Bizkaia, Spain; IAS-Research Center for Life, Mind and Society, University of the Basque Country, Donostia, Spain; Department of Informatics, University of Sussex, Brighton, UK
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Stano P, Damiano L. Synthetic cell research: Is technical progress leaving theoretical and epistemological investigations one step behind? Front Robot AI 2023; 10:1143196. [PMID: 37033673 PMCID: PMC10076886 DOI: 10.3389/frobt.2023.1143196] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2023] [Accepted: 03/06/2023] [Indexed: 04/11/2023] Open
Abstract
Advancements in the research on so-called "synthetic (artificial) cells" have been mainly characterized by an important acceleration in all sorts of experimental approaches, providing a growing amount of knowledge and techniques that will shape future successful developments. Synthetic cell technology, indeed, shows potential in driving a revolution in science and technology. On the other hand, theoretical and epistemological investigations related to what synthetic cells "are," how they behave, and what their role is in generating knowledge have not received sufficient attention. Open questions about these less explored subjects range from the analysis of the organizational theories applied to synthetic cells to the study of the "relevance" of synthetic cells as scientific tools to investigate life and cognition; and from the recognition and the cultural reappraisal of cybernetic inheritance in synthetic biology to the need for developing concepts on synthetic cells and to the exploration, in a novel perspective, of information theories, complexity, and artificial intelligence applied in this novel field. In these contributions, we will briefly sketch some crucial aspects related to the aforementioned issues, based on our ongoing studies. An important take-home message will result: together with their impactful experimental results and potential applications, synthetic cells can play a major role in the exploration of theoretical questions as well.
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Affiliation(s)
- Pasquale Stano
- Department of Biological and Environmental Sciences and Technologies (DiSTeBA), University of Salento, Lecce, Italy
- *Correspondence: Pasquale Stano, Luisa Damiano,
| | - Luisa Damiano
- RG-ESA (Research Group on the Epistemology of the Sciences of the Artificial), Libera Università di Lingue e Comunicazione (IULM), Milan, Italy
- *Correspondence: Pasquale Stano, Luisa Damiano,
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Côté J, Kourtis S. Qubit vitrification and entanglement criticality on a quantum simulator. Nat Commun 2022; 13:7395. [DOI: 10.1038/s41467-022-34982-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2022] [Accepted: 11/11/2022] [Indexed: 12/03/2022] Open
Abstract
AbstractMany elusive quantum phenomena emerge from a quantum system interacting with its classical environment. Quantum simulators enable us to program this interaction by using measurement operations. Measurements generally remove part of the entanglement built between the qubits in a simulator. While in simple cases entanglement may disappear at a constant rate as we measure qubits one by one, the evolution of entanglement under measurements for a given class of quantum states is generally unknown. We show that consecutive measurements of qubits in a simulator can lead to criticality, separating two phases of entanglement. Using up to 48 qubits, we prepare an entangled superposition of ground states to a classical spin model. Progressively measuring the qubits drives the simulator through an observable vitrification point and into a spin glass phase of entanglement. Our findings suggest coupling to a classical environment may drive critical phenomena in more general quantum states.
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Stano P. A four-track perspective for bottom-up synthetic cells. Front Bioeng Biotechnol 2022; 10:1029446. [PMID: 36246382 PMCID: PMC9563707 DOI: 10.3389/fbioe.2022.1029446] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/27/2022] [Accepted: 09/13/2022] [Indexed: 11/29/2022] Open
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Deshmukh J, Srinivasa S. Computational Transcendence: Responsibility and agency. Front Robot AI 2022; 9:977303. [PMID: 36226256 PMCID: PMC9548871 DOI: 10.3389/frobt.2022.977303] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2022] [Accepted: 08/18/2022] [Indexed: 11/13/2022] Open
Abstract
Emergence of responsible behavior is explored in non-cooperative games involving autonomous agents. Rather than imposing constraints or external reinforcements, agents are endowed with an elastic “sense of self” or an elastic identity that they curate based on rational considerations. This approach is called “computational transcendence (CT).” We show that agents using this model make choices for collective welfare instead of individual benefit. First, relevance of this model in game theoretic contexts like Prisoners’ dilemma and collusion is presented. Next, a generic multi-agent framework for simulating dilemmas around responsible agency is also proposed. CT implemented on this framework, is shown to be versatile in acting responsibly to different kinds of circumstances–including modifying their strategy based on their interaction with other agents in the system as well as interacting with adversaries that are rational maximizers, and who have a rationale to exploit responsible behavior from other agents. CT is also shown to outperform reciprocity as a strategy for responsible autonomy. Thus, we present CT as a framework for building autonomous agents which can intrinsically act responsibly in multi-agent systems. The core model for computational ethics presented in this paper can potentially be adapted to the needs of applications in areas like supply chains, traffic management, and autonomous vehicles. This paper hopes to motivate further research on responsible AI, by exploring computational modeling of this elusive concept called the “sense of self” that is a central element of existential inquiry in humans.
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Kawai T, Gunji YP. How do soldier crabs behave when seeing vibrating robots? Biosystems 2022. [DOI: 10.1016/j.biosystems.2022.104776] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2021] [Revised: 09/01/2022] [Accepted: 09/01/2022] [Indexed: 11/16/2022]
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Hsu S, Massolo FIS, Schaposnik LP. A Physarum-inspired approach to the Euclidean Steiner tree problem. Sci Rep 2022; 12:14536. [PMID: 36008426 PMCID: PMC9411548 DOI: 10.1038/s41598-022-18316-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2021] [Accepted: 08/09/2022] [Indexed: 11/09/2022] Open
Abstract
This paper presents a novel biologically-inspired explore-and-fuse approach to solving a large array of problems. The inspiration comes from Physarum, a unicellular slime mold capable of solving the traveling salesman and Steiner tree problems. Besides exhibiting individual intelligence, Physarum can also share information with other Physarum organisms through fusion. These characteristics of Physarum imply that spawning many such organisms we can explore the problem space in parallel, each individual gathering information and forming partial solutions pertaining to a local region of the problem space. When the organisms meet, they fuse and share information, eventually forming one organism which has a global view of the problem and can apply its intelligence to find an overall solution to the problem. This approach can be seen as a "softer" method of divide and conquer. We demonstrate this novel approach, developing the Physarum Steiner Algorithm which is capable of finding feasible solutions to the Euclidean Steiner tree problem. This algorithm is of particular interest due to its resemblance to Physarum polycephalum, ability to leverage parallel processing, avoid obstacles, and operate on various shapes and topological surfaces including the rectilinear grid.
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Affiliation(s)
- Sheryl Hsu
- Valley Christian High School, San Jose, USA
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Lu Y, Bai E, Jiang X, Wu Y. High-Speed Privacy Amplification Algorithm Using Cellular Automate in Quantum Key Distribution. Electronics 2022; 11:2426. [DOI: 10.3390/electronics11152426] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
Privacy amplification is an important step in the post-processing of quantum communication, which plays an indispensable role in the security of quantum key distribution systems. In this paper, we propose a Cellular Automata-based privacy amplification algorithm, which improves the speed of key distribution. The proposed algorithm is characterized by block iteration to generate secure key of arbitrary length. The core of the algorithm in this paper is to use the property that Cellular Automata can generate multiple new associated random sequences at the same time to carry out bit operations for multiple negotiation keys in the meantime and calculate in turn, so as to quickly realize the compression of negotiation keys. By analyzing the final key, the proposed algorithm has the advantages of fast key generation speed and high real-time performance. At the same time, the results of the NIST randomness test and avalanche test show that the algorithm has good randomness performance.
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Abstract
Cancers are complex adaptive diseases regulated by the nonlinear feedback systems between genetic instabilities, environmental signals, cellular protein flows, and gene regulatory networks. Understanding the cybernetics of cancer requires the integration of information dynamics across multidimensional spatiotemporal scales, including genetic, transcriptional, metabolic, proteomic, epigenetic, and multi-cellular networks. However, the time-series analysis of these complex networks remains vastly absent in cancer research. With longitudinal screening and time-series analysis of cellular dynamics, universally observed causal patterns pertaining to dynamical systems, may self-organize in the signaling or gene expression state-space of cancer triggering processes. A class of these patterns, strange attractors, may be mathematical biomarkers of cancer progression. The emergence of intracellular chaos and chaotic cell population dynamics remains a new paradigm in systems medicine. As such, chaotic and complex dynamics are discussed as mathematical hallmarks of cancer cell fate dynamics herein. Given the assumption that time-resolved single-cell datasets are made available, a survey of interdisciplinary tools and algorithms from complexity theory, are hereby reviewed to investigate critical phenomena and chaotic dynamics in cancer ecosystems. To conclude, the perspective cultivates an intuition for computational systems oncology in terms of nonlinear dynamics, information theory, inverse problems, and complexity. We highlight the limitations we see in the area of statistical machine learning but the opportunity at combining it with the symbolic computational power offered by the mathematical tools explored.
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Affiliation(s)
| | - Hector Zenil
- Machine Learning Group, Department of Chemical Engineering and Biotechnology, The University of Cambridge, Cambridge, United Kingdom
- The Alan Turing Institute, British Library, London, United Kingdom
- Oxford Immune Algorithmics, Reading, United Kingdom
- Algorithmic Dynamics Lab, Karolinska Institute, Stockholm, Sweden
- Algorithmic Nature Group, LABORES, Paris, France
- *Correspondence: Hector Zenil,
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Stano P. Exploring Information and Communication Theories for Synthetic Cell Research. Front Bioeng Biotechnol 2022; 10:927156. [PMID: 35910013 PMCID: PMC9334554 DOI: 10.3389/fbioe.2022.927156] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/23/2022] [Accepted: 06/24/2022] [Indexed: 01/17/2023] Open
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Ghosh OM, Good BH. Emergent evolutionary forces in spatial models of luminal growth and their application to the human gut microbiota. Proc Natl Acad Sci U S A 2022; 119:e2114931119. [PMID: 35787046 DOI: 10.1073/pnas.2114931119] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/07/2023] Open
Abstract
The genetic composition of the gut microbiota is constantly reshaped by ecological and evolutionary forces. These strain-level dynamics are challenging to understand because they depend on complex spatial growth processes that take place within a host. Here we introduce a population genetic framework to predict how stochastic evolutionary forces emerge from simple models of microbial growth in spatially extended environments like the intestinal lumen. Our framework shows how fluid flow and longitudinal variation in growth rate combine to shape the frequencies of genetic variants in simulated fecal samples, yielding analytical expressions for the effective generation times, selection coefficients, and rates of genetic drift. We find that over longer timescales, the emergent evolutionary dynamics can often be captured by well-mixed models that lack explicit spatial structure, even when there is substantial spatial variation in species-level composition. By applying these results to the human colon, we find that continuous fluid flow and simple forms of wall growth alone are unlikely to create sufficient bottlenecks to allow large fluctuations in mutant frequencies within a host. We also find that the effective generation times may be significantly shorter than expected from traditional average growth rate estimates. Our results provide a starting point for quantifying genetic turnover in spatially extended settings like the gut microbiota and may be relevant for other microbial ecosystems where unidirectional fluid flow plays an important role.
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Abd Latiff FN, Mior Othman WA. Implementation of synchronization of multi-fractional-order of chaotic neural networks with a variety of multi-time-delays: Studying the effect of double encryption for text encryption. PLoS One 2022; 17:e0270402. [PMID: 35776758 PMCID: PMC9249245 DOI: 10.1371/journal.pone.0270402] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2022] [Accepted: 06/09/2022] [Indexed: 11/28/2022] Open
Abstract
This research proposes the idea of double encryption, which is the combination of chaos synchronization of non-identical multi-fractional-order neural networks with multi-time-delays (FONNSMD) and symmetric encryption. Symmetric encryption is well known to be outstanding in speed and accuracy but less effective. Therefore, to increase the strength of data protection effectively, we combine both methods where the secret keys are generated from the third part of the neural network systems (NNS) and used only once to encrypt and decrypt the message. In addition, a fractional-order Lyapunov direct function (FOLDF) is designed and implemented in sliding mode control systems (SMCS) to maintain the convergence of approximated synchronization errors. Finally, three examples are carried out to confirm the theoretical analysis and find which synchronization is achieved. Then the result is combined with symmetric encryption to increase the security of secure communication, and a numerical simulation verifies the method’s accuracy.
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Affiliation(s)
- Fatin Nabila Abd Latiff
- Institute of Mathematical Sciences, Faculty of Science, Universiti Malaya, Kuala Lumpur, Malaysia
| | - Wan Ainun Mior Othman
- Institute of Mathematical Sciences, Faculty of Science, Universiti Malaya, Kuala Lumpur, Malaysia
- * E-mail:
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Abstract
Multicellular life forms have evolved many times on our planet, suggesting that this is a common evolutionary innovation. Multiple advantages have been proposed for the emergence of multicellularity (MC). In this paper, we address the problem of how the first precondition for MC, namely 'stay together', might have occurred under spatially limited resources exploited by a population of unicellular agents. Using a minimal model of evolved cell-cell adhesion among growing and dividing cells that exploit a localized resource with a given size, we show that a transition occurs at a critical resource size separating a phase of evolved multicellular aggregates from a phase where unicellularity (UC) is favoured. The two phases are separated by an intermediate domain where both UC and MC can be selected by evolution. This model provides a minimal approach to the early stages that were required to transition from individuality to cohesive groups of cells associated with a physical cooperative effect: when resources are present only in a localized portion of the habitat, MC is a desirable property as it helps cells to keep close to the available local nutrients.
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Affiliation(s)
- Adriano Bonforti
- ICREA-Complex Systems Lab, UPF-PRBB, Dr. Aiguader 80, 08003 Barcelona, Spain.,Institut de Biologia Evolutiva, CSIC-UPF, Passeig Maritim de la Barceloneta 37, 08003 Barcelona, Spain
| | - Ricard Solé
- ICREA-Complex Systems Lab, UPF-PRBB, Dr. Aiguader 80, 08003 Barcelona, Spain.,Institut de Biologia Evolutiva, CSIC-UPF, Passeig Maritim de la Barceloneta 37, 08003 Barcelona, Spain.,Santa Fe Institute, 1399 Hyde Park Road, Santa Fe, NM 87501, USA
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20
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Abstract
Temporal networks and network-structured systems are gaining ground in daily life. Such net-works are Vehicular Ad-hoc NETworks (VANET) and Mobile Ad-hoc NETworks (MANET), in fact, Industry 4.0 requires similar local networks. During mathematical model-based analysis of real temporal systems, it is vital to determine the existence and frequency of accessibility between components. Graph theory is a well-known mathematical tool used for studying accessibility of network components. In previous publications, the author proposed an easy-usable algorithm for determining the existence of interconnection between system-components. The Monte-Carlo Simulation can model the temporality of systems. The aim of this paper is to propose a Monte-Carlo Simulation-based method that estimates symmetry or asymmetry and the frequency of accessibilities between the components of temporal network-structured systems.
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Lam TM, Wang Z, Vaartjes I, Karssenberg D, Ettema D, Helbich M, Timmermans EJ, Frank LD, den Braver NR, Wagtendonk AJ, Beulens JWJ, Lakerveld J. Development of an objectively measured walkability index for the Netherlands. Int J Behav Nutr Phys Act 2022; 19:50. [PMID: 35501815 PMCID: PMC9063284 DOI: 10.1186/s12966-022-01270-8] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2021] [Accepted: 03/10/2022] [Indexed: 12/03/2022] Open
Abstract
Background Walkability indices have been developed and linked to behavioural and health outcomes elsewhere in the world, but not comprehensively for Europe. We aimed to 1) develop a theory-based and evidence-informed Dutch walkability index, 2) examine its cross-sectional associations with total and purpose-specific walking behaviours of adults across socioeconomic (SES) and urbanisation strata, 3) explore which walkability components drive these associations. Methods Components of the index included: population density, retail and service density, land use mix, street connectivity, green space, sidewalk density and public transport density. Each of the seven components was calculated for three Euclidean buffers: 150 m, 500 m and 1000 m around every 6-digit postal code location and for every administrative neighbourhood in GIS. Componential z-scores were averaged, and final indices normalized between 0 and 100. Data on self-reported demographic characteristics and walking behaviours of 16,055 adult respondents (aged 18–65) were extracted from the Dutch National Travel Survey 2017. Using Tobit regression modelling adjusted for individual- and household-level confounders, we assessed the associations between walkability and minutes walking in total, for non-discretionary and discretionary purposes. By assessing the attenuation in associations between partial indices and walking outcomes, we identified which of the seven components drive these associations. We also tested for effect modification by urbanization degree, SES, age and sex. Results In fully adjusted models, a 10% increase in walkability was associated with a maximum increase of 8.5 min of total walking per day (95%CI: 7.1–9.9). This association was consistent across buffer sizes and purposes of walking. Public transport density was driving the index’s association with walking outcomes. Stratified results showed that associations with minutes of non-discretionary walking were stronger in rural compared to very urban areas, in neighbourhoods with low SES compared to high SES, and in middle-aged (36–49 years) compared to young (18–35 years old) and older adults (50–65 years old). Conclusions The walkability index was cross-sectionally associated with Dutch adult’s walking behaviours, indicating its validity for further use in research. Supplementary Information The online version contains supplementary material available at 10.1186/s12966-022-01270-8.
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Affiliation(s)
- Thao Minh Lam
- Amsterdam UMC, Vrije Universiteit Amsterdam, Department of Epidemiology and Data Science, Amsterdam Public Health research institute, Boelelaan 1089a, 1081HV, Amsterdam, Netherlands. .,Upstream Team, Vrije Universiteit, Amsterdam, Netherlands.
| | - Zhiyong Wang
- Department of Human Geography and Spatial Planning, Faculty of Geosciences, Utrecht University, Princetonlaan 8a, 3584, Utrecht, CB, Netherlands
| | - Ilonca Vaartjes
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, Netherlands.,Global Geo Health Data Center, University Medical Center Utrecht & Utrecht University, Utrecht, Netherlands
| | - Derek Karssenberg
- Global Geo Health Data Center, University Medical Center Utrecht & Utrecht University, Utrecht, Netherlands.,Department of Physical Geography, Utrecht University, Princetonlaan 8a, 3584, Utrecht, CB, Netherlands
| | - Dick Ettema
- Department of Human Geography and Spatial Planning, Faculty of Geosciences, Utrecht University, Princetonlaan 8a, 3584, Utrecht, CB, Netherlands
| | - Marco Helbich
- Department of Human Geography and Spatial Planning, Faculty of Geosciences, Utrecht University, Princetonlaan 8a, 3584, Utrecht, CB, Netherlands
| | - Erik J Timmermans
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, Netherlands
| | - Lawrence D Frank
- Department of Urban Studies and Planning, UC San Diego, La Jolla, San Diego, USA.,Urban Design 4 Health, Inc, Rochester, NY, USA
| | - Nicolette R den Braver
- Amsterdam UMC, Vrije Universiteit Amsterdam, Department of Epidemiology and Data Science, Amsterdam Public Health research institute, Boelelaan 1089a, 1081HV, Amsterdam, Netherlands.,Upstream Team, Vrije Universiteit, Amsterdam, Netherlands
| | - Alfred J Wagtendonk
- Amsterdam UMC, Vrije Universiteit Amsterdam, Department of Epidemiology and Data Science, Amsterdam Public Health research institute, Boelelaan 1089a, 1081HV, Amsterdam, Netherlands.,Upstream Team, Vrije Universiteit, Amsterdam, Netherlands
| | - Joline W J Beulens
- Amsterdam UMC, Vrije Universiteit Amsterdam, Department of Epidemiology and Data Science, Amsterdam Public Health research institute, Boelelaan 1089a, 1081HV, Amsterdam, Netherlands.,Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, Netherlands.,Upstream Team, Vrije Universiteit, Amsterdam, Netherlands
| | - Jeroen Lakerveld
- Amsterdam UMC, Vrije Universiteit Amsterdam, Department of Epidemiology and Data Science, Amsterdam Public Health research institute, Boelelaan 1089a, 1081HV, Amsterdam, Netherlands.,Upstream Team, Vrije Universiteit, Amsterdam, Netherlands
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22
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Shoemaker WR, Polezhaeva E, Givens KB, Lennon JT. Seed banks alter the molecular evolutionary dynamics of Bacillus subtilis. Genetics 2022; 221:6576633. [PMID: 35511143 PMCID: PMC9157070 DOI: 10.1093/genetics/iyac071] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/14/2022] [Accepted: 04/23/2022] [Indexed: 11/14/2022] Open
Abstract
Fluctuations in the availability of resources constrain the growth and reproduction of individuals, which subsequently affects the evolution of their respective populations. Many organisms contend with such fluctuations by entering a reversible state of reduced metabolic activity, a phenomenon known as dormancy. This pool of dormant individuals (i.e. a seed bank) does not reproduce and is expected to act as an evolutionary buffer, though it is difficult to observe this effect directly over an extended evolutionary timescale. Through genetic manipulation, we analyze the molecular evolutionary dynamics of Bacillus subtilis populations in the presence and absence of a seed bank over 700 days. The ability of these bacteria to enter a dormant state increased the accumulation of genetic diversity over time and altered the trajectory of mutations, findings that were recapitulated using simulations based on a mathematical model of evolutionary dynamics. While the ability to form a seed bank did not alter the degree of negative selection, we found that it consistently altered the direction of molecular evolution across genes. Together, these results show that the ability to form a seed bank can affect the direction and rate of molecular evolution over an extended evolutionary timescale.
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Affiliation(s)
| | | | | | - Jay T Lennon
- Department of Biology, Indiana University, Bloomington, IN, 47405, USA
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23
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Idrais J, El Abassi R, El Moudene Y, Sabour A. Characterizing community behavior in OSNs: Modeling and forecasting activity on Facebook using the SARIMA model. IFS 2022. [DOI: 10.3233/jifs-213391] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
Online social networks (OSNs) occupy an important part in users’ daily life as they maintain the flow of interaction and information exchange on all local, national, and global scales.This work develops a time series model of interactions on Facebook using the SARIMA (seasonal autoregressive integrated moving average) time series modeling technique based on empiricism with the theoretical model of regular user behavior. A case study of the Moroccan community, which has a high rate of interactions, is carried out to test the conformity of the model with the measurements. The results show that the SARIMA model is better suited to modeling the flow of interactions. The application of the SNR method on the signal energies has allowed to measure the usage damping in the users. The multitude of applied approaches have allowed to extract some main characteristics of this large and complex network.
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Affiliation(s)
- Jaafar Idrais
- IMI Laboratory, Faculty of Sciences, Ibn Zohr University, Agadir, Morocco
| | - Rida El Abassi
- IMI Laboratory, Faculty of Sciences, Ibn Zohr University, Agadir, Morocco
| | - Yassine El Moudene
- IMI Laboratory, Faculty of Sciences, Ibn Zohr University, Agadir, Morocco
| | - Abderrahim Sabour
- Department of Computer Science High School of Technology, Ibn Zohr University, Agadir, Morocco
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24
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Lombardo G, Pellegrino M, Tomaiuolo M, Cagnoni S, Mordonini M, Giacobini M, Poggi A. Fine-Grained Agent-Based Modeling to Predict Covid-19 Spreading and Effect of Policies in Large-Scale Scenarios. IEEE J Biomed Health Inform 2022; 26:2052-2062. [PMID: 35298388 DOI: 10.1109/jbhi.2022.3160243] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
Abstract
Modeling and forecasting the spread of COVID-19 remains an open problem for several reasons. One of these concerns the difficulty to model a complex system at a high resolution (fine-grained) level at which the spread can be simulated by taking into account individual features such as the social structure, the effects of the governments' policies, age sensitivity to Covid-19, mask-wearing habits and geographical distribution of susceptible people. Agent-based modeling usually needs to find an optimal trade-off between the resolution of the simulation and the population size. Indeed, modeling single individuals usually leads to simulations of smaller populations or the use of meta-populations. In this article, we propose a solution to efficiently model the Covid-19 spread in Lombardy, the most populated Italian region with about ten million people. In particular, the model described in this paper is, to the best of our knowledge, the first attempt in literature to model a large population at the single-individual level. To achieve this goal, we propose a framework that implements: i.~a scale-free model of the social contacts combining a sociability rate, demographic information, and geographical assumptions; ii.~a multi-agent system relying on the actor model and the High-Performance Computing technology to efficiently implement ten million concurrent agents. We simulated the epidemic scenario from January to April 2020 and from August to December 2020, modeling the government's lockdown policies and people's mask-wearing habits. The social modeling approach we propose could be rapidly adapted for modeling future epidemics at their early stage in scenarios where little prior knowledge is available.
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25
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Pellegrino M, Lombardo G, Cagnoni S, Poggi A. High-Performance Computing and ABMS for High-Resolution COVID-19 Spreading Simulation. Future Internet 2022; 14:83. [DOI: 10.3390/fi14030083] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/04/2023] Open
Abstract
This paper presents an approach for the modeling and the simulation of the spreading of COVID-19 based on agent-based modeling and simulation (ABMS). Our goal is not only to support large-scale simulations but also to increase the simulation resolution. Moreover, we do not assume an underlying network of contacts, and the person-to-person contacts responsible for the spreading are modeled as a function of the geographical distance among the individuals. In particular, we defined a commuting mechanism combining radiation-based and gravity-based models and we exploited the commuting properties at different resolution levels (municipalities and provinces). Finally, we exploited the high-performance computing (HPC) facilities to simulate millions of concurrent agents, each mapping the individual’s behavior. To do such simulations, we developed a spreading simulator and validated it through the simulation of the spreading in two of the most populated Italian regions: Lombardy and Emilia-Romagna. Our main achievement consists of the effective modeling of 10 million of concurrent agents, each one mapping an individual behavior with a high-resolution in terms of social contacts, mobility and contribution to the virus spreading. Moreover, we analyzed the forecasting ability of our framework to predict the number of infections being initialized with only a few days of real data. We validated our model with the statistical data coming from the serological analysis conducted in Lombardy, and our model makes a smaller error than other state of the art models with a final root mean squared error equal to 56,009 simulating the entire first pandemic wave in spring 2020. On the other hand, for the Emilia-Romagna region, we simulated the second pandemic wave during autumn 2020, and we reached a final RMSE equal to 10,730.11.
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26
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Abstract
The causal set program and the Wolfram physics project leave open the problem of how a graph that is a (3+1)-dimensional Minkowski spacetime according to its simple geodesic distances could be generated solely from simple deterministic rules. This paper provides a solution by describing simple rules that characterize discrete Lorentz boosts between 4D lattice graphs, which combine further to form Wigner rotations that produce isotropy and lead to the emergence of the continuous Lorentz group and the (3+1)-dimensional Minkowski spacetime. On such graphs, the speed of light, the proper time interval, as well as the proper length are all shown to be highly accurate.
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27
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Collera JA. Bubbling, Bistable Limit Cycles and Quasi-Periodic Oscillations in Queues with Delayed Information. Symmetry (Basel) 2022; 14:376. [DOI: 10.3390/sym14020376] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/04/2023] Open
Abstract
We consider a model describing the length of two queues that incorporates customer choice behavior based on delayed queue length information. The symmetric case, where the values of the time-delay parameter in each queue are the same, was recently studied. It was shown that under some conditions, the stable equilibrium solution becomes unstable as the common time delay passes a threshold value. This one-time stability switch occurs only at a symmetry-breaking Hopf bifurcation where a family of stable asynchronous limit-cycle solutions arise. In this paper, we examine the non-symmetric case, wherein the values of the time-delay parameter in each queue are different. We show that, in contrast to the symmetric case, the non-symmetric case allows bubbling, multiple stability switches and coexistence of distinct families of stable limit cycles. An investigation of the dynamical behavior of the non-symmetric system in a neighborhood of a double-Hopf bifurcation using numerical continuation explains the occurrence of the bistable limit cycles. Quasi-periodic oscillations were also observed due to the presence of torus bifurcations near the double-Hopf bifurcation. These identifications of the underlying mechanisms that cause unwanted oscillations in the system give a better understanding of the effects of providing delayed information and consequently help in better management of queues.
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28
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Uthamacumaran A, Elouatik S, Abdouh M, Berteau-Rainville M, Gao ZH, Arena G. Machine learning characterization of cancer patients-derived extracellular vesicles using vibrational spectroscopies: results from a pilot study. APPL INTELL 2022. [DOI: 10.1007/s10489-022-03203-1] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
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29
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Krivorotko OI, Kabanikhin SI, Sosnovskaya MI, Andornaya DV. Sensitivity and identifiability analysis of COVID-19 pandemic models. Vavilovskii Zhurnal Genet Selektsii 2022; 25:82-91. [PMID: 35083396 PMCID: PMC8696171 DOI: 10.18699/vj21.010] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/25/2020] [Revised: 12/17/2020] [Accepted: 12/18/2020] [Indexed: 12/02/2022] Open
Abstract
The paper presents the results of sensitivity-based identifiability analysis of the COVID-19 pandemic
spread models in the Novosibirsk region using the systems of differential equations and mass balance law. The
algorithm is built on the sensitivity matrix analysis using the methods of differential and linear algebra. It allows
one to determine the parameters that are the least and most sensitive to data changes to build a regularization for solving an identification problem of the most accurate pandemic spread scenarios in the region. The
performed analysis has demonstrated that the virus contagiousness is identifiable from the number of daily
confirmed, critical and recovery cases. On the other hand, the predicted proportion of the admitted patients
who require a ventilator and the mortality rate are determined much less consistently. It has been shown that
building a more realistic forecast requires adding additional information about the process such as the number
of daily hospital admissions. In our study, the problems of parameter identification using additional information about the number of daily confirmed, critical and mortality cases in the region were reduced to minimizing
the corresponding misfit functions. The minimization problem was solved through the differential evolution
method that is widely applied for stochastic global optimization. It has been demonstrated that a more general
COVID-19 spread compartmental model consisting of seven ordinary differential equations describes the main
trend of the spread and is sensitive to the peaks of confirmed cases but does not qualitatively describe small
statistical datasets such as the number of daily critical cases or mortality that can lead to errors in forecasting.
A more detailed agent-oriented model has been able to capture statistical data with additional noise to build
scenarios of COVID-19 spread in the region.
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Affiliation(s)
- O I Krivorotko
- Institute of Computational Mathematics and Mathematical Geophysics of Siberian Branch of the Russian Academy of Sciences, Novosibirsk, Russia Novosibirsk State University, Novosibirsk, Russia
| | - S I Kabanikhin
- Institute of Computational Mathematics and Mathematical Geophysics of Siberian Branch of the Russian Academy of Sciences, Novosibirsk, Russia Novosibirsk State University, Novosibirsk, Russia
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30
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Abstract
The statistical associations between mutations, collectively known as linkage disequilibrium, encode important information about the evolutionary forces acting within a population. Yet in contrast to single-site analogues like the site frequency spectrum, our theoretical understanding of linkage disequilibrium remains limited. In particular, little is currently known about how mutations with different ages and fitness costs contribute to expected patterns of linkage disequilibrium, even in simple settings where recombination and genetic drift are the major evolutionary forces. Here, I introduce a forward-time framework for predicting linkage disequilibrium between pairs of neutral and deleterious mutations as a function of their present-day frequencies. I show that the dynamics of linkage disequilibrium become much simpler in the limit that mutations are rare, where they admit a simple heuristic picture based on the trajectories of the underlying lineages. I use this approach to derive analytical expressions for a family of frequency-weighted linkage disequilibrium statistics as a function of the recombination rate, the frequency scale, and the additive and epistatic fitness costs of the mutations. I find that the frequency scale can have a dramatic impact on the shapes of the resulting linkage disequilibrium curves, reflecting the broad range of time scales over which these correlations arise. I also show that the differences between neutral and deleterious linkage disequilibrium are not purely driven by differences in their mutation frequencies and can instead display qualitative features that are reminiscent of epistasis. I conclude by discussing the implications of these results for recent linkage disequilibrium measurements in bacteria. This forward-time approach may provide a useful framework for predicting linkage disequilibrium across a range of evolutionary scenarios.
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Affiliation(s)
- Benjamin H Good
- Department of Applied Physics, Stanford University, Stanford, CA 94305, USA,Corresponding author: Department of Applied Physics, Stanford University, Clark Center, 318 Campus Drive, Stanford, CA 94305, USA.
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32
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Gros C. Emotions as Abstract Evaluation Criteria in Biological and Artificial Intelligences. Front Comput Neurosci 2022; 15:726247. [PMID: 34970130 PMCID: PMC8712665 DOI: 10.3389/fncom.2021.726247] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2021] [Accepted: 11/22/2021] [Indexed: 11/13/2022] Open
Abstract
Biological as well as advanced artificial intelligences (AIs) need to decide which goals to pursue. We review nature's solution to the time allocation problem, which is based on a continuously readjusted categorical weighting mechanism we experience introspectively as emotions. One observes phylogenetically that the available number of emotional states increases hand in hand with the cognitive capabilities of animals and that raising levels of intelligence entail ever larger sets of behavioral options. Our ability to experience a multitude of potentially conflicting feelings is in this view not a leftover of a more primitive heritage, but a generic mechanism for attributing values to behavioral options that can not be specified at birth. In this view, emotions are essential for understanding the mind. For concreteness, we propose and discuss a framework which mimics emotions on a functional level. Based on time allocation via emotional stationarity (TAES), emotions are implemented as abstract criteria, such as satisfaction, challenge and boredom, which serve to evaluate activities that have been carried out. The resulting timeline of experienced emotions is compared with the “character” of the agent, which is defined in terms of a preferred distribution of emotional states. The long-term goal of the agent, to align experience with character, is achieved by optimizing the frequency for selecting individual tasks. Upon optimization, the statistics of emotion experience becomes stationary.
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Affiliation(s)
- Claudius Gros
- Institute for Theoretical Physics, Goethe University Frankfurt am Main, Frankfurt, Germany
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33
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Maserat E. Integration of Artificial Intelligence and CRISPR/Cas9 System for Vaccine Design. Cancer Inform 2022; 21:11769351221140102. [DOI: 10.1177/11769351221140102] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/03/2022] [Accepted: 10/28/2022] [Indexed: 11/28/2022] Open
Abstract
The CRISPR/Cas9 system offers a new approach to genome editing and cancer treatment. This approach is able to detect drug targets and genomic analysis of cancer. The use of artificial intelligence (AI) capacity to edit genomes through CRISPR/Cas9 enables modification of gene mutations, molecular simulation. AI approaches include knowledge discovery approaches, antigen and epitope prediction approaches, and agent based-model approaches. These methods in combination with CRISPR/Cas9 can be used in vaccine design.
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Affiliation(s)
- Elham Maserat
- Department of Medical Informatics, Faculty of Medical Sciences, Tarbiat Modares University, Tehran, Iran
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34
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Gravner J, Liu X. One-dimensional cellular automata with random rules: longest temporal period of a periodic solution. ELECTRON J PROBAB 2022. [DOI: 10.1214/22-ejp744] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/19/2022]
Affiliation(s)
- Janko Gravner
- Department of Mathematics. University of California, Davis
| | - Xiaochen Liu
- Department of Mathematics. University of California, Davis
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35
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Amir Siddique M, Wang Y, Xu N, Ullah N, Zeng P. The Spatiotemporal Implications of Urbanization for Urban Heat Islands in Beijing: A Predictive Approach Based on CA–Markov Modeling (2004–2050). Remote Sensing 2021; 13:4697. [DOI: 10.3390/rs13224697] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
The rapid increase in infrastructural development in populated areas has had numerous adverse impacts. The rise in land surface temperature (LST) and its associated damage to urban ecological systems result from urban development. Understanding the current and future LST phenomenon and its relationship to landscape composition and land use/cover (LUC) changes is critical to developing policies to mitigate the disastrous impacts of urban heat islands (UHIs) on urban ecosystems. Using remote sensing and GIS data, this study assessed the multi-scale relationship of LUCC and LST of the cosmopolitan exponentially growing area of Beijing, China. We investigated the impacts of LUC on LST in urban agglomeration for a time series (2004–2019) of Landsat data using Classification and Regression Trees (CART) and a single channel algorithm (SCA), respectively. We built a CA–Markov model to forecast future (2025 and 2050) LUCC and LST spatial patterns. Our results indicate that the cumulative changes in an urban area (UA) increased by about 908.15 km2 (5%), and 11% of vegetation area (VA) decreased from 2004 to 2019. The correlation coefficient of LUCC including vegetation, water bodies, and built-up areas with LST had values of r = −0.155 (p > 0.419), −0.809 (p = 0.000), and 0.526 (p = 0.003), respectively. The results surrounding future forecasts revealed an estimated 2309.55 km2 (14%) decrease in vegetation (urban and forest), while an expansion of 1194.78 km2 (8%) was predicted for a built-up area from 2019 to 2050. This decrease in vegetation cover and expansion of settlements would likely cause a rise of about ~5.74 °C to ~9.66 °C in temperature. These findings strongly support the hypothesis that LST is directly related to the vegetation index. In conclusion, the estimated overall increase of 7.5 °C in LST was predicted from 2019–2050, which is alarming for the urban community’s environmental health. The present results provide insight into sustainable environmental development through effective urban planning of Beijing and other urban hotspots.
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Albantakis L. Quantifying the Autonomy of Structurally Diverse Automata: A Comparison of Candidate Measures. Entropy (Basel) 2021; 23:e23111415. [PMID: 34828113 PMCID: PMC8624265 DOI: 10.3390/e23111415] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/15/2021] [Revised: 10/16/2021] [Accepted: 10/26/2021] [Indexed: 11/16/2022]
Abstract
Should the internal structure of a system matter when it comes to autonomy? While there is still no consensus on a rigorous, quantifiable definition of autonomy, multiple candidate measures and related quantities have been proposed across various disciplines, including graph-theory, information-theory, and complex system science. Here, I review and compare a range of measures related to autonomy and intelligent behavior. To that end, I analyzed the structural, information-theoretical, causal, and dynamical properties of simple artificial agents evolved to solve a spatial navigation task, with or without a need for associative memory. By contrast to standard artificial neural networks with fixed architectures and node functions, here, independent evolution simulations produced successful agents with diverse neural architectures and functions. This makes it possible to distinguish quantities that characterize task demands and input-output behavior, from those that capture intrinsic differences between substrates, which may help to determine more stringent requisites for autonomous behavior and the means to measure it.
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Affiliation(s)
- Larissa Albantakis
- Department of Psychiatry, University of Wisconsin-Madison, Madison, WI 53719, USA
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37
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Aldhyani THH, Alkahtani H. A Bidirectional Long Short-Term Memory Model Algorithm for Predicting COVID-19 in Gulf Countries. Life (Basel) 2021; 11:1118. [PMID: 34832994 DOI: 10.3390/life11111118] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/23/2021] [Revised: 09/17/2021] [Accepted: 10/19/2021] [Indexed: 12/14/2022] Open
Abstract
Accurate prediction models have become the first goal for aiding pandemic-related decisions. Modeling and predicting the number of new active cases and deaths are important steps for anticipating and controlling COVID-19 outbreaks. The aim of this research was to develop an accurate prediction system for the COVID-19 pandemic that can predict the numbers of active cases and deaths in the Gulf countries of Saudi Arabia, Oman, the United Arab Emirates (UAE), Kuwait, Bahrain, and Qatar. The novelty of the proposed approach is that it uses an advanced prediction model—the bidirectional long short-term memory (Bi-LSTM) network deep learning model. The datasets were collected from an available repository containing updated registered cases of COVID-19 and showing the global numbers of active COVID-19 cases and deaths. Statistical analyses (e.g., mean square error, root mean square error, mean absolute error, and Spearman’s correlation coefficient) were employed to evaluate the results of the adopted Bi-LSTM model. The Bi-LSTM results based on the correlation metric gave predicted confirmed COVID-19 cases of 99.67%, 99.34%, 99.94%, 99.64%, 98.95%, and 99.91% for Saudi Arabia, Oman, the UAE, Kuwait, Bahrain, and Qatar, respectively, while testing the Bi-LSTM model for predicting COVID-19 mortality gave accuracies of 99.87%, 97.09%, 99.53%, 98.71%, 95.62%, and 99%, respectively. The Bi-LSTM model showed significant results using the correlation metric. Overall, the Bi-LSTM model demonstrated significant success in predicting COVID-19. The Bi-LSTM-based deep learning network achieves optimal prediction results and is effective and robust for predicting the numbers of active cases and deaths from COVID-19 in the studied Gulf countries.
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38
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Gunji YP, Uragami D. Computational Power of Asynchronously Tuned Automata Enhancing the Unfolded Edge of Chaos. Entropy (Basel) 2021; 23:e23111376. [PMID: 34828074 PMCID: PMC8622964 DOI: 10.3390/e23111376] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/09/2021] [Revised: 10/15/2021] [Accepted: 10/18/2021] [Indexed: 01/27/2023]
Abstract
Asynchronously tuned elementary cellular automata (AT-ECA) are described with respect to the relationship between active and passive updating, and that spells out the relationship between synchronous and asynchronous updating. Mutual tuning between synchronous and asynchronous updating can be interpreted as the model for dissipative structure, and that can reveal the critical property in the phase transition from order to chaos. Since asynchronous tuning easily makes behavior at the edge of chaos, the property of AT-ECA is called the unfolded edge of chaos. The computational power of AT-ECA is evaluated by the quantitative measure of computational universality and efficiency. It shows that the computational efficiency of AT-ECA is much higher than that of synchronous ECA and asynchronous ECA.
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Affiliation(s)
- Yukio-Pegio Gunji
- Department of Intermedia, Art and Science, School of Fundamental Science and Technology, Waseda University, 3-4-1, Ohkubo, Shinjuku, Tokyo 169-8555, Japan
- Correspondence: ; Tel.: +81-(0)3-5286-2904
| | - Daisuke Uragami
- Department of Mathematical Engineering, College of Industrial Technology, Nihon University, 1-2-1, Izumi-cho, Narashino 275-8575, Japan;
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Damiano L, Stano P. A Wetware Embodied AI? Towards an Autopoietic Organizational Approach Grounded in Synthetic Biology. Front Bioeng Biotechnol 2021; 9:724023. [PMID: 34631678 PMCID: PMC8495316 DOI: 10.3389/fbioe.2021.724023] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/11/2021] [Accepted: 09/10/2021] [Indexed: 11/13/2022] Open
Affiliation(s)
- Luisa Damiano
- RG-ESA (Research Group on the Epistemology of the Sciences of the Artificial), Libera Università di Lingue e Comunicazione (IULM), Milan, Italy
| | - Pasquale Stano
- Department of Biological and Environmental Sciences and Technologies (DiSTeBA), University of Salento, Lecce, Italy
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Valle MA, Lavín JF, Magner NS. Equity Market Description under High and Low Volatility Regimes Using Maximum Entropy Pairwise Distribution. Entropy (Basel) 2021; 23:1307. [PMID: 34682031 DOI: 10.3390/e23101307] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/12/2021] [Revised: 09/29/2021] [Accepted: 10/01/2021] [Indexed: 11/17/2022]
Abstract
The financial market is a complex system in which the assets influence each other, causing, among other factors, price interactions and co-movement of returns. Using the Maximum Entropy Principle approach, we analyze the interactions between a selected set of stock assets and equity indices under different high and low return volatility episodes at the 2008 Subprime Crisis and the 2020 COVID-19 outbreak. We carry out an inference process to identify the interactions, in which we implement the a pairwise Ising distribution model describing the first and second moments of the distribution of the discretized returns of each asset. Our results indicate that second-order interactions explain more than 80% of the entropy in the system during the Subprime Crisis and slightly higher than 50% during the COVID-19 outbreak independently of the period of high or low volatility analyzed. The evidence shows that during these periods, slight changes in the second-order interactions are enough to induce large changes in assets correlations but the proportion of positive and negative interactions remains virtually unchanged. Although some interactions change signs, the proportion of these changes are the same period to period, which keeps the system in a ferromagnetic state. These results are similar even when analyzing triadic structures in the signed network of couplings.
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Lobo JL, Del Ser J, Osaba E, Bifet A, Herrera F. CURIE: a cellular automaton for concept drift detection. Data Min Knowl Discov 2021. [DOI: 10.1007/s10618-021-00776-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/20/2022]
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Reijnen F, Leliveld E, van de Mortel-fronczak J, van Dinther J, Rooda J, Fokkink W. Synthesized fault-tolerant supervisory controllers, with an application to a rotating bridge. COMPUT IND 2021; 130:103473. [DOI: 10.1016/j.compind.2021.103473] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
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43
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Rigakis M, Trachanatzi D, Marinaki M, Marinakis Y. Tourist group itinerary design: When the firefly algorithm meets the n-person Battle of Sexes. Knowl Based Syst 2021; 228:107257. [DOI: 10.1016/j.knosys.2021.107257] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/20/2023]
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Abstract
The investigation of thermalization in isolated quantum many-body systems has a long history, dating back to the time of developing statistical mechanics. Most quantum many-body systems in nature are considered to thermalize, while some never achieve thermal equilibrium. The central problem is to clarify whether a given system thermalizes, which has been addressed previously, but not resolved. Here, we show that this problem is undecidable. The resulting undecidability even applies when the system is restricted to one-dimensional shift-invariant systems with nearest-neighbour interaction, and the initial state is a fixed product state. We construct a family of Hamiltonians encoding dynamics of a reversible universal Turing machine, where the fate of a relaxation process changes considerably depending on whether the Turing machine halts. Our result indicates that there is no general theorem, algorithm, or systematic procedure determining the presence or absence of thermalization in any given Hamiltonian. The question whether a given isolated quantum many-body system would thermalize has currently no general answer. Here, Shiraishi and Matsumoto demonstrate the computational universality of thermalization phenomena already for simplified 1D systems, thus proving that the thermalization problem is undecidable.
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Affiliation(s)
- Naoto Shiraishi
- Department of Physics, Gakushuin Univerisity, Toshima-ku, Tokyo, Japan.
| | - Keiji Matsumoto
- Quantum Computation Group, National Institute of Informatics, Chiyoda-ku, Tokyo, Japan.
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Dehshibi MM, Chiolerio A, Nikolaidou A, Mayne R, Gandia A, Ashtari-Majlan M, Adamatzky A. Stimulating Fungi Pleurotus ostreatus with Hydrocortisone. ACS Biomater Sci Eng 2021; 7:3718-3726. [PMID: 34309374 DOI: 10.1021/acsbiomaterials.1c00752] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
Fungi cells can sense extracellular signals via reception, transduction, and response mechanisms, allowing them to communicate with their host and adapt to their environment. They feature effective regulatory protein expressions that enhance and regulate their response and adaptation to various triggers such as stress, hormones, physical stimuli such as light, and host factors. In our recent studies, we have shown that Pleurotus oyster fungi generate electrical potential impulses in the form of spike events in response to their exposure to environmental, mechanical, and chemical triggers, suggesting that the nature of stimuli may be deduced from the fungal electrical responses. In this study, we explored the communication protocols of fungi as reporters of human chemical secretions such as hormones, addressing whether fungi can sense human signals. We exposed Pleurotus oyster fungi to hydrocortisone, which was directly applied to the surface of a fungal-colonized hemp shavings substrate, and recorded the electrical activity of the fungi. Hydrocortisone is a medicinal hormone replacement that is similar to the natural stress hormone cortisol. Changes in cortisol levels released by the body indicate the presence of disease and can have a detrimental effect on physiological process regulation. The response of fungi to hydrocortisone was also explored further using X-rays to reveal changes in the fungi tissue, where receiving hydrocortisone by the substrate can inhibit the flow of calcium and, as a result, reduce its physiological changes. This research could open the way for future studies on adaptive fungal wearables capable of detecting human physiological states and biosensors built of living fungi.
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Affiliation(s)
| | - Alessandro Chiolerio
- Unconventional Computing Laboratory, UWE, Bristol, U.K.,Center for Sustainable Future Technologies, Istituto Italiano di Tecnologia, Torino, Italy
| | - Anna Nikolaidou
- Unconventional Computing Laboratory, UWE, Bristol, U.K.,Department of Architecture, UWE, Bristol, U.K
| | - Richard Mayne
- Unconventional Computing Laboratory, UWE, Bristol, U.K
| | - Antoni Gandia
- Institute for Plant Molecular and Cell Biology, CSIC-UPV, Valencia, Spain.,Mogu S.r.l., Inarzo, Italy
| | - Mona Ashtari-Majlan
- Department of Computer Science, Universitat Oberta de Catalunya, Barcelona, Spain
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Großmann G, Backenköhler M, Wolf V. Heterogeneity matters: Contact structure and individual variation shape epidemic dynamics. PLoS One 2021; 16:e0250050. [PMID: 34283842 PMCID: PMC8291658 DOI: 10.1371/journal.pone.0250050] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2021] [Accepted: 07/05/2021] [Indexed: 12/17/2022] Open
Abstract
In the recent COVID-19 pandemic, mathematical modeling constitutes an important tool to evaluate the prospective effectiveness of non-pharmaceutical interventions (NPIs) and to guide policy-making. Most research is, however, centered around characterizing the epidemic based on point estimates like the average infectiousness or the average number of contacts. In this work, we use stochastic simulations to investigate the consequences of a population's heterogeneity regarding connectivity and individual viral load levels. Therefore, we translate a COVID-19 ODE model to a stochastic multi-agent system. We use contact networks to model complex interaction structures and a probabilistic infection rate to model individual viral load variation. We observe a large dependency of the dispersion and dynamical evolution on the population's heterogeneity that is not adequately captured by point estimates, for instance, used in ODE models. In particular, models that assume the same clinical and transmission parameters may lead to different conclusions, depending on different types of heterogeneity in the population. For instance, the existence of hubs in the contact network leads to an initial increase of dispersion and the effective reproduction number, but to a lower herd immunity threshold (HIT) compared to homogeneous populations or a population where the heterogeneity stems solely from individual infectivity variations.
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Affiliation(s)
- Gerrit Großmann
- Saarland Informatics Campus, Saarland University, Saarbrücken, Germany
| | | | - Verena Wolf
- Saarland Informatics Campus, Saarland University, Saarbrücken, Germany
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Li Z. Financial market volatility based on complex network and fuzzy logic theory. IFS 2021. [DOI: 10.3233/jifs-219084] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
Volatility is an inherent attribute of the financial market, which is usually expressed as the degree of volatility of financial asset prices. The volatility of the financial market means that there is uncertainty or risk in the market. This paper mainly studies financial market fluctuations based on complex networks and fuzzy logic theory. This article first systematically organizes and summarizes the theoretical construction of complex networks and fuzzy logic. In terms of complex networks, the definition of complex networks, the theory of commonly used functions (classical models of complex networks) and the solving methods are sorted out. In the construction of fuzzy logic theory, starting with quantifiable financial market volatility indicators, the construction models of realized volatility and implied volatility are discussed, and complex network models of implied volatility and model-free models are discussed. The theoretical construction methods were compared and analyzed. Finally, it summarizes the theoretical construction methods of implied volatility index and points out the advantages of model-free implied volatility as a market volatility and risk measurement index, which contains more effective future risk information and is based on implied volatility. The empirical research on indexes and complex network models has laid a theoretical foundation. Experimental data shows that the bond market and the foreign exchange market have the largest fluctuations in the correlation coefficient, reaching 0.35; followed by the stock market and the bond market, which is about 0.17; the stock market and foreign exchange market with the smallest fluctuations are about 0.08. The experimental results show that the financial market volatility research data based on complex networks and fuzzy logic theory is more accurate.
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Ohzawa Y, Gunji Y. Logic Gates Formed by Perturbations in an Asynchronous Game of Life. Symmetry (Basel) 2021; 13:907. [DOI: 10.3390/sym13050907] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022] Open
Abstract
The game of life (GL), a type of two-dimensional cellular automaton, has been the subject of many studies because of its simple mechanism and complex behavior. In particular, the construction of logic circuits using the GL has helped to extend the concept of computation. Conventional logic circuits assume deterministic transitions due to the synchronicity of the classic GL. However, they are fragile to noise and cannot maintain the expected behavior in an environment with noise. In this study, a probabilistic logic gate model was constructed using perturbations in an asynchronous game of life (AGL). Since our asynchronous automaton had no heterogeneity in either the horizontal or vertical directions, it was symmetrical with respect to spatial structure. On the other hand, the construction of the logical gate was implemented to contain heterogeneity in the horizontal or vertical directions, which could allow an AND gate and an OR gate in a single system. It was based on the phase transition between connected and unconnected phases, which is newly discovered in this study. In the model, perturbations symmetrically entail operations successful and unsuccessful, and this symmetrical double action is given not to interfere with established operations but to make operations possible. Therefore, this model had a different meaning from logic gates that exclude perturbations or use them externally. The idea of this perturbation is analogous to the inherent noise that destroys and generates structures in biological swarms.
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Japyassú HF, Neco LC, Nunes-Neto N. Minimal Organizational Requirements for the Ascription of Animal Personality to Social Groups. Front Psychol 2021; 11:601937. [PMID: 33995158 PMCID: PMC8116521 DOI: 10.3389/fpsyg.2020.601937] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2020] [Accepted: 11/24/2020] [Indexed: 11/13/2022] Open
Abstract
Recently, psychological phenomena have been expanded to new domains, crisscrossing boundaries of organizational levels, with the emergence of areas such as social personality and ecosystem learning. In this contribution, we analyze the ascription of an individual-based concept (personality) to the social level. Although justified boundary crossings can boost new approaches and applications, the indiscriminate misuse of concepts refrains the growth of scientific areas. The concept of social personality is based mainly on the detection of repeated group differences across a population, in a direct transposition of personality concepts from the individual to the social level. We show that this direct transposition is problematic for avowing the nonsensical ascription of personality even to simple electronic devices. To go beyond a metaphoric use of social personality, we apply the organizational approach to a review of social insect communication networks. Our conceptual analysis shows that socially self-organized systems, such as isolated ant trails and bee's recruitment groups, are too simple to have social personality. The situation is more nuanced when measuring the collective choice between nest sites or foraging patches: some species show positive and negative feedbacks between two or more self-organized social structures so that these co-dependent structures are inter-related by second-order, social information systems, complying with a formal requirement for having social personality: the social closure of constraints. Other requirements include the decoupling between individual and social dynamics, and the self-regulation of collective decision processes. Social personality results to be sometimes a metaphorical transposition of a psychological concept to a social phenomenon. The application of this organizational approach to cases of learning ecosystems, or evolutionary learning, could help to ground theoretically the ascription of psychological properties to levels of analysis beyond the individual, up to meta-populations or ecological communities.
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Affiliation(s)
- Hilton F Japyassú
- National Institute of Science and Technology in Interdisciplinary and Transdisciplinary Studies in Ecology and Evolution (INCT IN-TREE), Federal University of Bahia, Salvador, Brazil.,Biology Institute, Federal University of Bahia, Salvador, Brazil
| | - Lucia C Neco
- School of Humanities, University of Western Australia, Perth, WA, Australia
| | - Nei Nunes-Neto
- National Institute of Science and Technology in Interdisciplinary and Transdisciplinary Studies in Ecology and Evolution (INCT IN-TREE), Federal University of Bahia, Salvador, Brazil.,Faculty of Biological and Environmental Sciences, Federal University of Grande Dourados, Dourados, Brazil
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50
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Tadić B, Melnik R. Microscopic dynamics modeling unravels the role of asymptomatic virus carriers in SARS-CoV-2 epidemics at the interplay between biological and social factors. Comput Biol Med 2021; 133:104422. [PMID: 33930762 PMCID: PMC8078086 DOI: 10.1016/j.compbiomed.2021.104422] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2021] [Revised: 04/16/2021] [Accepted: 04/17/2021] [Indexed: 12/25/2022]
Abstract
The recent experience of SARS-CoV-2 epidemics spreading revealed the importance of passive forms of infection transmissions. Apart from the virus survival outside the host, the latent infection transmissions caused by asymptomatic and presymptomatic hosts represent major challenges for controlling the epidemics. In this regard, social mixing and various biological factors play their subtle, but often critical, role. For example, a life-threatening condition may result in the infection contracted from an asymptomatic virus carrier. Here, we use a new recently developed microscopic agent-based modelling framework to shed light on the role of asymptomatic hosts and unravel the interplay between the biological and social factors of these nonlinear stochastic processes at high temporal resolution. The model accounts for each human actor's susceptibility and the virus survival time, as well as traceability along the infection path. These properties enable an efficient dissection of the infection events caused by asymptomatic carriers from those which involve symptomatic hosts before they develop symptoms and become removed to a controlled environment. Consequently, we assess how their relative proportions in the overall infection curve vary with changing model parameters. Our results reveal that these proportions largely depend on biological factors in the process, specifically, the virus transmissibility and the critical threshold for developing symptoms, which can be affected by the virus pathogenicity. Meanwhile, social participation activity is crucial for the overall infection level, further modulated by the virus transmissibility.
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Affiliation(s)
- Bosiljka Tadić
- Department of Theoretical Physics, Jožef Stefan Institute, Jamova 39, Ljubljana, Slovenia; Complexity Science Hub, Josefstaedter Strasse 39, Vienna, Austria.
| | - Roderick Melnik
- MS2Discovery Interdisciplinary Research Institute, M2NeT Laboratory and Department of Mathematics, Wilfrid Laurier University, Waterloo, ON, Canada; BCAM - Basque Center for Applied Mathematics, Alameda de Mazarredo 14, E-48009, Bilbao, Spain
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