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Статті в журналах з теми "Computational morphogenesi"

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Автор: Grafiati

Опубліковано: 14 березня 2023

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1

MACLENNAN, BRUCE J. "EMBODIED COMPUTATION: APPLYING THE PHYSICS OF COMPUTATION TO ARTIFICIAL MORPHOGENESIS." Parallel Processing Letters 22, no. 03 (July 8, 2012): 1240013. http://dx.doi.org/10.1142/s0129626412400130.

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Анотація:

We discuss the problem of assembling complex physical systems that are structured from the nanoscale up through the macroscale, and argue that embryological morphogenesis provides a good model of how this can be accomplished. Morphogenesis (whether natural or artificial) is an example of embodied computation, which exploits physical processes for computational ends, or performs computations for their physical effects. Examples of embodied computation in natural morphogenesis can be found at many levels, from allosteric proteins, which perform simple embodied computations, up through cells, which act to create tissues with specific patterns, compositions, and forms. We outline a notation for describing morphogenetic programs and illustrate its use with two examples: simple diffusion and the assembly of a simple spine with attachment points for legs. While much research remains to be done — at the simulation level before we attempt physical implementations — our results to date show how we may implement the fundamental processes of morphogenesis as a practical application of embodied computation at the nano- and microscale.

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2

Dodig-Crnkovic, Gordana. "Cognition as Morphological/Morphogenetic Embodied Computation In Vivo." Entropy 24, no. 11 (October 31, 2022): 1576. http://dx.doi.org/10.3390/e24111576.

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Cognition, historically considered uniquely human capacity, has been recently found to be the ability of all living organisms, from single cells and up. This study approaches cognition from an info-computational stance, in which structures in nature are seen as information, and processes (information dynamics) are seen as computation, from the perspective of a cognizing agent. Cognition is understood as a network of concurrent morphological/morphogenetic computations unfolding as a result of self-assembly, self-organization, and autopoiesis of physical, chemical, and biological agents. The present-day human-centric view of cognition still prevailing in major encyclopedias has a variety of open problems. This article considers recent research about morphological computation, morphogenesis, agency, basal cognition, extended evolutionary synthesis, free energy principle, cognition as Bayesian learning, active inference, and related topics, offering new theoretical and practical perspectives on problems inherent to the old computationalist cognitive models which were based on abstract symbol processing, and unaware of actual physical constraints and affordances of the embodiment of cognizing agents. A better understanding of cognition is centrally important for future artificial intelligence, robotics, medicine, and related fields.

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3

Ohmori, Hiroshi. "Computational Morphogenesis." International Journal of Space Structures 25, no. 2 (June 2010): 75–82. http://dx.doi.org/10.1260/0266-3511.25.2.75.

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4

Ohmori, Hiroshi. "Computational Morphogenesis." International Journal of Space Structures 26, no. 3 (September 2011): 269–76. http://dx.doi.org/10.1260/0266-3511.26.3.269.

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5

KOUMOUTSAKOS, PETROS, BASIL BAYATI, FLORIAN MILDE, and GERARDO TAURIELLO. "PARTICLE SIMULATIONS OF MORPHOGENESIS." Mathematical Models and Methods in Applied Sciences 21, supp01 (April 2011): 955–1006. http://dx.doi.org/10.1142/s021820251100543x.

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Анотація:

The simulation of the creation and evolution of biological forms requires the development of computational methods that are capable of resolving their hierarchical, spatial and temporal complexity. Computations based on interacting particles, provide a unique computational tool for discrete and continuous descriptions of morphogenesis of systems ranging from the molecular to the organismal level. The capabilities of particle methods hinge on the simplicity of their formulation which enables the formulation of a unifying computational framework encompassing deterministic and stochastic models. In this paper, we discuss recent advances in particle methods for the simulation of biological systems at the mesoscopic and the macroscale level. We present results from applications of particle methods including reaction–diffusion on deforming surfaces, deterministic and stochastic descriptions of tumor growth and angiogenesis and discuss successes and challenges of this approach.

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6

Pasquero, Claudia, and Marco Poletto. "Cities as biological computers." Architectural Research Quarterly 20, no. 1 (March 2016): 10–19. http://dx.doi.org/10.1017/s135913551600018x.

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In this paper the authors propose a conceptual model and a bio-computational design method to articulate the world's Urbansphere, suggesting new terms for its co-evolution with the Biosphere.The proposed model responds to principles of biological self-organisation, and operates by embedding a numerical/computational engine, a living Physarum polycephalum, onto a spatial/morphogenetic substratum, a Satellite driven informational territory. This integration is embodied in the Physarum Machine, a bio-digital design apparatus conceived by the authors and further developed within the Urban Morphogenesis Lab at the UCL in London.The use of specifically designed apparatus of material computation to demonstrate and solve problems of urban morphogenesis is not new and the authors refer to the work of German Architect Frei Otto and his theory for the occupation and connection of territories.This research leads to a notion of bio-city of the future where manmade infrastructures and non-human biological systems will constitute parts of a single biotechnological whole. To this respect it can be read as a manifesto for the extension of biotechnology to the scale of the Biosphere (biosphere geo-engineering) by expanding the scope and material articulation of global informational and energetic infrastructures (the internet of things and the internet of energy).In the tradition of design based research, the paper also suggests an application of the proposed model to a specific case study demonstrating its efficacy in the re-conceptualization of the post-industrial and ecologically depleted landscapes of eastern Arizona. In conclusion the experiment describes the potential of augmenting materiality through sensors and microprocessors so that it would become possible to harvest the computational power latent in micro-organisms like the slime mould.The dream outlined here is for an era where descriptive computation will be superseded by our capability to simulate and compute through the world that surrounds us.

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7

Fletcher, Alexander G., Fergus Cooper, and Ruth E. Baker. "Mechanocellular models of epithelial morphogenesis." Philosophical Transactions of the Royal Society B: Biological Sciences 372, no. 1720 (March 27, 2017): 20150519. http://dx.doi.org/10.1098/rstb.2015.0519.

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Embryonic epithelia achieve complex morphogenetic movements, including in-plane reshaping, bending and folding, through the coordinated action and rearrangement of individual cells. Technical advances in molecular and live-imaging studies of epithelial dynamics provide a very real opportunity to understand how cell-level processes facilitate these large-scale tissue rearrangements. However, the large datasets that we are now able to generate require careful interpretation. In combination with experimental approaches, computational modelling allows us to challenge and refine our current understanding of epithelial morphogenesis and to explore experimentally intractable questions. To this end, a variety of cell-based modelling approaches have been developed to describe cell–cell mechanical interactions, ranging from vertex and ‘finite-element’ models that approximate each cell geometrically by a polygon representing the cell's membrane, to immersed boundary and subcellular element models that allow for more arbitrary cell shapes. Here, we review how these models have been used to provide insights into epithelial morphogenesis and describe how such models could help future efforts to decipher the forces and mechanical and biochemical feedbacks that guide cell and tissue-level behaviour. In addition, we discuss current challenges associated with using computational models of morphogenetic processes in a quantitative and predictive way. This article is part of the themed issue ‘Systems morphodynamics: understanding the development of tissue hardware’.

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8

Riguidel, Michel. "Morphogenesis of the Zeta Function in the Critical Strip by Computational Approach." Mathematics 6, no. 12 (November 26, 2018): 285. http://dx.doi.org/10.3390/math6120285.

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This article proposes a morphogenesis interpretation of the zeta function by computational approach by relying on numerical approximation formulae between the terms and the partial sums of the series, divergent in the critical strip. The goal is to exhibit structuring properties of the partial sums of the raw series by highlighting their morphogenesis, thanks to the elementary functions constituting the terms of the real and imaginary parts of the series, namely the logarithmic, cosine, sine, and power functions. Two essential indices of these sums appear: the index of no return of the vagrancy and the index of smothering of the function before the resumption of amplification of its divergence when the index tends towards infinity. The method consists of calculating, displaying graphically in 2D and 3D, and correlating, according to the index, the angles, the terms and the partial sums, in three nested domains: the critical strip, the critical line, and the set of non-trivial zeros on this line. Characteristics and approximation formulae are thus identified for the three domains. These formulae make it possible to grasp the morphogenetic foundations of the Riemann hypothesis (RH) and sketch the architecture of a more formal proof.

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9

Rorot, Wiktor. "Counting with Cilia: The Role of Morphological Computation in Basal Cognition Research." Entropy 24, no. 11 (October 31, 2022): 1581. http://dx.doi.org/10.3390/e24111581.

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“Morphological computation” is an increasingly important concept in robotics, artificial intelligence, and philosophy of the mind. It is used to understand how the body contributes to cognition and control of behavior. Its understanding in terms of "offloading" computation from the brain to the body has been criticized as misleading, and it has been suggested that the use of the concept conflates three classes of distinct processes. In fact, these criticisms implicitly hang on accepting a semantic definition of what constitutes computation. Here, I argue that an alternative, mechanistic view on computation offers a significantly different understanding of what morphological computation is. These theoretical considerations are then used to analyze the existing research program in developmental biology, which understands morphogenesis, the process of development of shape in biological systems, as a computational process. This important line of research shows that cognition and intelligence can be found across all scales of life, as the proponents of the basal cognition research program propose. Hence, clarifying the connection between morphological computation and morphogenesis allows for strengthening the role of the former concept in this emerging research field.

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10

Dokmegang, Joel, Moi Hoon Yap, Liangxiu Han, Matteo Cavaliere, and René Doursat. "Computational modelling unveils how epiblast remodelling and positioning rely on trophectoderm morphogenesis during mouse implantation." PLOS ONE 16, no. 7 (July 28, 2021): e0254763. http://dx.doi.org/10.1371/journal.pone.0254763.

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Understanding the processes by which the mammalian embryo implants in the maternal uterus is a long-standing challenge in embryology. New insights into this morphogenetic event could be of great importance in helping, for example, to reduce human infertility. During implantation the blastocyst, composed of epiblast, trophectoderm and primitive endoderm, undergoes significant remodelling from an oval ball to an egg cylinder. A main feature of this transformation is symmetry breaking and reshaping of the epiblast into a “cup”. Based on previous studies, we hypothesise that this event is the result of mechanical constraints originating from the trophectoderm, which is also significantly transformed during this process. In order to investigate this hypothesis we propose MG# (MechanoGenetic Sharp), an original computational model of biomechanics able to reproduce key cell shape changes and tissue level behaviours in silico. With this model, we simulate epiblast and trophectoderm morphogenesis during implantation. First, our results uphold experimental findings that repulsion at the apical surface of the epiblast is essential to drive lumenogenesis. Then, we provide new theoretical evidence that trophectoderm morphogenesis indeed can dictate the cup shape of the epiblast and fosters its movement towards the uterine tissue. Our results offer novel mechanical insights into mouse peri-implantation and highlight the usefulness of agent-based modelling methods in the study of embryogenesis.

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11

Menges, Achim. "Performative morphology in architecture: Integrative design research by the Institute for computational design." SAJ - Serbian Architectural Journal 5, no. 2 (2013): 92–105. http://dx.doi.org/10.5937/saj1302092m.

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Анотація:

Computation, in its most basic meaning, refers to the processing of information. In this way, both machinic processes operating in the binary realm of the digital, as well as material processes operating in the complex domain of the physical can be considered computational. While there is a strong bias towards the former in contemporary design, sporadic investigations of the later have also occurred in architecture. What is more rarely explored, though, is the territory where machine computation and material computation potentially overlap, where they not simply co-exist but intensely interact in the design process. Such an integrative approach to machine and material computation forms a central part of the research pursued at the Institute for Computational Design at the University of Stuttgart. This paper will introduce the related design research through the presentation of three research projects. The first part of the paper focuses on the explanation of the theoretical framework of the Institute's approach to design computation, which finds its conceptual roots in the integrative processes of biological becoming rather than the striated processes of established technological production. It seeks to outline novel possibilities for a higher level of integration of form, information and performance in architecture through the possible synthesis of machine and material computation in morphogenetic design. The second part of the paper will provide specific examples of such a computational approach by introducing three related research areas. The possible integration of material behaviour as an active driver in computational design processes will be introduced through a first research project focusing on bending-active structures constructed from thin plywood lamellas. The second research project constitutes an example for the integration of materialization characteristics by encoding the possibilities and limits of robotic fabrication for modular wood shell structures in design computation. The third research project introduces the integration of material structure by embedding the complex reciprocities of form, material, structure and performance resulting from robotic carbon and glass fibre filament winding in a generative morphogenetic design process.

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12

NEAGU, ADRIAN, IOAN KOSZTIN, KAROLY JAKAB, BOGDAN BARZ, MONICA NEAGU, RICHARD JAMISON, and GABOR FORGACS. "COMPUTATIONAL MODELING OF TISSUE SELF-ASSEMBLY." Modern Physics Letters B 20, no. 20 (August 30, 2006): 1217–31. http://dx.doi.org/10.1142/s0217984906011724.

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As a theoretical framework for understanding the self-assembly of living cells into tissues, Steinberg proposed the differential adhesion hypothesis (DAH) according to which a specific cell type possesses a specific adhesion apparatus that combined with cell motility leads to cell assemblies of various cell types in the lowest adhesive energy state. Experimental and theoretical efforts of four decades turned the DAH into a fundamental principle of developmental biology that has been validated both in vitro and in vivo. Based on computational models of cell sorting, we have developed a DAH-based lattice model for tissues in interaction with their environment and simulated biological self-assembly using the Monte Carlo method. The present brief review highlights results on specific morphogenetic processes with relevance to tissue engineering applications. Our own work is presented on the background of several decades of theoretical efforts aimed to model morphogenesis in living tissues. Simulations of systems involving about 105 cells have been performed on high-end personal computers with CPU times of the order of days. Studied processes include cell sorting, cell sheet formation, and the development of endothelialized tubes from rings made of spheroids of two randomly intermixed cell types, when the medium in the interior of the tube was different from the external one. We conclude by noting that computer simulations based on mathematical models of living tissues yield useful guidelines for laboratory work and can catalyze the emergence of innovative technologies in tissue engineering.

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13

Varner, Victor D., and Celeste M. Nelson. "Computational models of airway branching morphogenesis." Seminars in Cell & Developmental Biology 67 (July 2017): 170–76. http://dx.doi.org/10.1016/j.semcdb.2016.06.003.

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14

Wyczalkowski, Matthew A., Zi Chen, Benjamen A. Filas, Victor D. Varner, and Larry A. Taber. "Computational models for mechanics of morphogenesis." Birth Defects Research Part C: Embryo Today: Reviews 96, no. 2 (June 2012): 132–52. http://dx.doi.org/10.1002/bdrc.21013.

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15

Misra, M., B. Audoly, and S. Y. Shvartsman. "Complex structures from patterned cell sheets." Philosophical Transactions of the Royal Society B: Biological Sciences 372, no. 1720 (March 27, 2017): 20150515. http://dx.doi.org/10.1098/rstb.2015.0515.

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The formation of three-dimensional structures from patterned epithelial sheets plays a key role in tissue morphogenesis. An important class of morphogenetic mechanisms relies on the spatio-temporal control of apical cell contractility, which can result in the localized bending of cell sheets and in-plane cell rearrangements. We have recently proposed a modified vertex model that can be used to systematically explore the connection between the two-dimensional patterns of cell properties and the emerging three-dimensional structures. Here we review the proposed modelling framework and illustrate it through the computational analysis of the vertex model that captures the salient features of the formation of the dorsal appendages during Drosophila oogenesis. This article is part of the themed issue ‘Systems morphodynamics: understanding the development of tissue hardware’.

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16

Sermeus, Yvenn, Jef Vangheel, Liesbet Geris, Bart Smeets, and Przemko Tylzanowski. "Mechanical Regulation of Limb Bud Formation." Cells 11, no. 3 (January 26, 2022): 420. http://dx.doi.org/10.3390/cells11030420.

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Early limb bud development has been of considerable interest for the study of embryological development and especially morphogenesis. The focus has long been on biochemical signalling and less on cell biomechanics and mechanobiology. However, their importance cannot be understated since tissue shape changes are ultimately controlled by active forces and bulk tissue rheological properties that in turn depend on cell–cell interactions as well as extracellular matrix composition. Moreover, the feedback between gene regulation and the biomechanical environment is still poorly understood. In recent years, novel experimental techniques and computational models have reinvigorated research on this biomechanical and mechanobiological side of embryological development. In this review, we consider three stages of early limb development, namely: outgrowth, elongation, and condensation. For each of these stages, we summarize basic biological regulation and examine the role of cellular and tissue mechanics in the morphogenetic process.

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17

Aage, Niels, Erik Andreassen, Boyan S. Lazarov, and Ole Sigmund. "Giga-voxel computational morphogenesis for structural design." Nature 550, no. 7674 (October 2017): 84–86. http://dx.doi.org/10.1038/nature23911.

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18

Igamberdiev, Abir U., Richard Gordon, Bradly Alicea, and Vladimir G. Cherdantsev. "Computational, theoretical, and experimental approaches to morphogenesis." Biosystems 173 (November 2018): 1–3. http://dx.doi.org/10.1016/j.biosystems.2018.09.018.

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19

Carrera-Pinzón, Andrés Felipe, Kalenia Márquez-Flórez, Reuben H. Kraft, Salah Ramtani, and Diego Alexander Garzón-Alvarado. "Computational model of a synovial joint morphogenesis." Biomechanics and Modeling in Mechanobiology 19, no. 5 (December 20, 2019): 1389–402. http://dx.doi.org/10.1007/s10237-019-01277-4.

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20

Choi, Habeun, Heng Chi, Kyoungsoo Park, and Glaucio H. Paulino. "Computational Morphogenesis: Morphologic constructions using polygonal discretizations." International Journal for Numerical Methods in Engineering 122, no. 1 (October 22, 2020): 25–52. http://dx.doi.org/10.1002/nme.6519.

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21

Lamport, Derek, Li Tan, Michael Held, and Marcia Kieliszewski. "The Role of the Primary Cell Wall in Plant Morphogenesis." International Journal of Molecular Sciences 19, no. 9 (September 9, 2018): 2674. http://dx.doi.org/10.3390/ijms19092674.

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Morphogenesis remains a riddle, wrapped in a mystery, inside an enigma. It remains a formidable problem viewed from many different perspectives of morphology, genetics, and computational modelling. We propose a biochemical reductionist approach that shows how both internal and external physical forces contribute to plant morphogenesis via mechanical stress–strain transduction from the primary cell wall tethered to the plasma membrane by a specific arabinogalactan protein (AGP). The resulting stress vector, with direction defined by Hechtian adhesion sites, has a magnitude of a few piconewtons amplified by a hypothetical Hechtian growth oscillator. This paradigm shift involves stress-activated plasma membrane Ca2+ channels and auxin-activated H+-ATPase. The proton pump dissociates periplasmic AGP-glycomodules that bind Ca2+. Thus, as the immediate source of cytosolic Ca2+, an AGP-Ca2+ capacitor directs the vectorial exocytosis of cell wall precursors and auxin efflux (PIN) proteins. In toto, these components comprise the Hechtian oscillator and also the gravisensor. Thus, interdependent auxin and Ca2+ morphogen gradients account for the predominance of AGPs. The size and location of a cell surface AGP-Ca2+ capacitor is essential to differentiation and explains AGP correlation with all stages of morphogenetic patterning from embryogenesis to root and shoot. Finally, the evolutionary origins of the Hechtian oscillator in the unicellular Chlorophycean algae reflect the ubiquitous role of chemiosmotic proton pumps that preceded DNA at the dawn of life.

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22

KUNDA, Masashi, Mikio KURITA, and Hiroshi OHMORI. "COMPUTATIONAL MORPHOGENESIS OF TRUSS STRUCTURES CONSIDERING HOMOLOGOUS DEFORMATION." Journal of Structural and Construction Engineering (Transactions of AIJ) 77, no. 676 (2012): 899–904. http://dx.doi.org/10.3130/aijs.77.899.

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23

MARUYAMA, Mizuki, Shinya MATSUMOTO, and Daiji FUJII. "COMPUTATIONAL MORPHOGENESIS OF BUILDING STRUCTURES USING IESO METHOD." Journal of Structural and Construction Engineering (Transactions of AIJ) 82, no. 739 (2017): 1383–89. http://dx.doi.org/10.3130/aijs.82.1383.

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24

NIIUCHI, Yohei, Shinya MATSUMOTO, and Daiji FUJII. "COMPUTATIONAL MORPHOGENESIS OF BUILDING STRUCTURES USING IESO METHOD." Journal of Structural and Construction Engineering (Transactions of AIJ) 82, no. 731 (2017): 97–103. http://dx.doi.org/10.3130/aijs.82.97.

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25

Siregar, Pridi, Nathalie Julen, Peter Hufnagl, and George L. Mutter. "Computational morphogenesis – Embryogenesis, cancer research and digital pathology." Biosystems 169-170 (July 2018): 40–54. http://dx.doi.org/10.1016/j.biosystems.2018.05.006.

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26

Fleming, A. "Leaf morphogenesis: A combined computational and molecular analysis." Comparative Biochemistry and Physiology Part A: Molecular & Integrative Physiology 150, no. 3 (July 2008): S142. http://dx.doi.org/10.1016/j.cbpa.2008.04.352.

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27

Ramasubramanian, Ashok, and Larry A. Taber. "Computational modeling of morphogenesis regulated by mechanical feedback." Biomechanics and Modeling in Mechanobiology 7, no. 2 (February 21, 2007): 77–91. http://dx.doi.org/10.1007/s10237-007-0077-y.

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28

Pavlova, Anna, Robert O. Stuart, Martin Pohl, and Sanjay K. Nigam. "Evolution of gene expression patterns in a model of branching morphogenesis." American Journal of Physiology-Renal Physiology 277, no. 4 (October 1, 1999): F650—F663. http://dx.doi.org/10.1152/ajprenal.1999.277.4.f650.

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Branching morphogenesis of the ureteric bud in response to unknown signals from the metanephric mesenchyme gives rise to the urinary collecting system and, via inductive signals from the ureteric bud, to recruitment of nephrons from undifferentiated mesenchyme. An established cell culture model for this process employs cells of ureteric bud origin (UB) cultured in extracellular matrix and stimulated with conditioned media (BSN-CM) from a metanephric mesenchymal cell line (H. Sakurai, E. J. Barros, T. Tsukamoto, J. Barasch, and S. K. Nigam. Proc. Natl. Acad. Sci. USA 94: 6279–6284, 1997.). In the presence of BSN-CM, the UB cells form branching tubular structures reminiscent of the branching ureteric bud. The pattern of gene regulation in this model of branching morphogenesis of the kidney collecting system was investigated using high-density cDNA arrays. Software and analytical methods were developed for the quantification and clustering of genes. With the use of a computational method termed “vector analysis,” genes were clustered according to the direction and magnitude of differential expression in n-dimensional log-space. Changes in gene expression in response to the BSN-CM consisted primarily of differential expression of transcription factors with previously described roles in morphogenesis, downregulation of pro-apoptotic genes accompanied by upregulation of anti-apoptotic genes, and upregulation of a small group of secreted products including growth factors, cytokines, and extracellular proteinases. Changes in expression are discussed in the context of a general model for epithelial branching morphogenesis. In addition, the cDNA arrays were used to survey expression of epithelial markers and secreted factors in UB and BSN cells, confirming the largely epithelial character of the former and largely mesenchymal character of the later. Specific morphologies (cellular processes, branching multicellular cords, etc.) were shown to correlate with the expression of different, but overlapping, genomic subsets, suggesting differences in morphogenetic mechanisms at these various steps in the evolution of branching tubules.

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29

KAMIMURA, Koichi, Masatoshi MANABE, Shinya MATSUMOTO, and Daiji FUJII. "COMPUTATIONAL MORPHOGENESIS OF CONTINUUM SHELL STRUCTURES USING IESO METHOD." Journal of Structural and Construction Engineering (Transactions of AIJ) 83, no. 745 (2018): 459–65. http://dx.doi.org/10.3130/aijs.83.459.

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30

Ma, Jiaming, Zi-Long Zhao, Sen Lin, and Yi Min Xie. "Topology of leaf veins: Experimental observation and computational morphogenesis." Journal of the Mechanical Behavior of Biomedical Materials 123 (November 2021): 104788. http://dx.doi.org/10.1016/j.jmbbm.2021.104788.

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31

OHMORI, Hiroshi, Hiroyuki FUTAI, Toshihiko IIJIMA, Atsushi MUTO, and Yasutoshi HASEGAWA. "STRUCTURAL DESIGN OF OFFICE BUILDING BY COMPUTATIONAL MORPHOGENESIS(Structures)." AIJ Journal of Technology and Design 10, no. 20 (2004): 77–82. http://dx.doi.org/10.3130/aijt.10.77.

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32

Liu, Min, Min Xing, Qingshan Yang, and Xinmin Yang. "Computational morphogenesis of free form shell structures by optimization." Procedia Engineering 31 (2012): 608–12. http://dx.doi.org/10.1016/j.proeng.2012.01.1074.

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33

FUJII, Daiji, Masatoshi MANABE, and Toyofumi TAKADA. "COMPUTATIONAL MORPHOGENESIS OF BUILDING STRUCTURE USING GROUND STRUCTURE APPROACH." Journal of Structural and Construction Engineering (Transactions of AIJ) 73, no. 633 (2008): 1967–73. http://dx.doi.org/10.3130/aijs.73.1967.

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34

FUJITA, Shinnosuke, Yoshihiro KANNO, and Makoto OHSAKI. "COMPUTATIONAL MORPHOGENESIS OF MINIMAL SURFACE REPRESENTED AS PARAMETRIC SURFACE." Journal of Structural and Construction Engineering (Transactions of AIJ) 82, no. 738 (2017): 1299–307. http://dx.doi.org/10.3130/aijs.82.1299.

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35

Kim, Sean H. J., Wei Yu, Keith Mostov, Michael A. Matthay, and C. Anthony Hunt. "A Computational Approach to Understand In Vitro Alveolar Morphogenesis." PLoS ONE 4, no. 3 (March 13, 2009): e4819. http://dx.doi.org/10.1371/journal.pone.0004819.

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36

Inoue, Yasuhiro, and Taiji Adachi. "OS1-1-3 Multiscale computational mechanobiology on tissue morphogenesis." Proceedings of the Symposium on Micro-Nano Science and Technology 2012.4 (2012): 123–24. http://dx.doi.org/10.1299/jsmemnm.2012.4.123.

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37

Roudavski, Stanislav. "Towards Morphogenesis in Architecture." International Journal of Architectural Computing 7, no. 3 (September 2009): 345–74. http://dx.doi.org/10.1260/147807709789621266.

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Анотація:

Procedural, parametric and generative computer-supported techniques in combination with mass customization and automated fabrication enable holistic manipulation in silico and the subsequent production of increasingly complex architectural arrangements. By automating parts of the design process, computers make it easier to develop designs through versioning and gradual adjustment. In recent architectural discourse, these approaches to designing have been described as morphogenesis. This paper invites further reflection on the possible meanings of this imported concept in the field of architectural designing. It contributes by comparing computational modelling of morphogenesis in plant science with techniques in architectural designing. Deriving examples from case-studies, the paper suggests potentials for collaboration and opportunities for bi-directional knowledge transfers.

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38

Li, Wenlong, Sedighe Keynia, Samuel A. Belteton, Faezeh Afshar-Hatam, Daniel B. Szymanski, and Joseph A. Turner. "Protocol for mapping the variability in cell wall mechanical bending behavior in living leaf pavement cells." Plant Physiology 188, no. 3 (December 15, 2021): 1435–49. http://dx.doi.org/10.1093/plphys/kiab588.

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Abstract Mechanical properties, size and geometry of cells, and internal turgor pressure greatly influence cell morphogenesis. Computational models of cell growth require values for wall elastic modulus and turgor pressure, but very few experiments have been designed to validate the results using measurements that deform the entire thickness of the cell wall. New wall material is synthesized at the inner surface of the cell such that full-thickness deformations are needed to quantify relevant changes associated with cell development. Here, we present an integrated, experimental–computational approach to analyze quantitatively the variation of elastic bending behavior in the primary cell wall of living Arabidopsis (Arabidopsis thaliana) pavement cells and to measure turgor pressure within cells under different osmotic conditions. This approach used laser scanning confocal microscopy to measure the 3D geometry of single pavement cells and indentation experiments to probe the local mechanical responses across the periclinal wall. The experimental results were matched iteratively using a finite element model of the experiment to determine the local mechanical properties and turgor pressure. The resulting modulus distribution along the periclinal wall was nonuniform across the leaf cells studied. These results were consistent with the characteristics of plant cell walls which have a heterogeneous organization. The results and model allowed the magnitude and orientation of cell wall stress to be predicted quantitatively. The methods also serve as a reference for future work to analyze the morphogenetic behaviors of plant cells in terms of the heterogeneity and anisotropy of cell walls.

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39

Holloway, David M., and Lionel G. Harrison. "Algal morphogenesis: modelling interspecific variation in Micrasterias with reaction–diffusion patterned catalysis of cell surface growth." Philosophical Transactions of the Royal Society of London. Series B: Biological Sciences 354, no. 1382 (February 28, 1999): 417–33. http://dx.doi.org/10.1098/rstb.1999.0395.

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Semi–cell morphogenesis in unicellular desmid algae of the genus Micrasterias generates a stellar shape by repeated dichotomous branching of growing tips of the cell surface. The numerous species of the genus display variations of the branching pattern that differ markedly in number of branchings, lobe width and lobe length. We have modelled this morphogenesis, following previous work by D. M. Harrison and M. Kolár (1988), on the assumptions that patterning occurs by chemical reaction–diffusion activity within the plasma membrane, leading to morphological expression by patterned catalysis of the extension of the cell surface. The latter has been simulated in simplified form by two–dimensional computations. Our results indicate that for generation of repeated branchings and for the control of diverse species–specific shapes, the loss of patterning activity and of rapid growth in regions separating the active growing tips is an essential feature. We believe this conclusion to be much more general than the specific details of our model. We discuss the limitations of the model especially in terms of what extra features might be addressed in three–dimensional computation.

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40

Du, XinXin, Miriam Osterfield, and Stanislav Y. Shvartsman. "Computational analysis of three-dimensional epithelial morphogenesis using vertex models." Physical Biology 11, no. 6 (November 20, 2014): 066007. http://dx.doi.org/10.1088/1478-3975/11/6/066007.

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41

Lee, Dongkyu, Soomi Shin, and Sungsoo Park. "Computational Morphogenesis Based Structural Design by Using Material Topology Optimization." Mechanics Based Design of Structures and Machines 35, no. 1 (February 21, 2007): 39–58. http://dx.doi.org/10.1080/15397730601180756.

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42

Bhatia, Neha, Adam Runions, and Miltos Tsiantis. "Leaf Shape Diversity: From Genetic Modules to Computational Models." Annual Review of Plant Biology 72, no. 1 (June 17, 2021): 325–56. http://dx.doi.org/10.1146/annurev-arplant-080720-101613.

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Plant leaves display considerable variation in shape. Here, we introduce key aspects of leaf development, focusing on the morphogenetic basis of leaf shape diversity. We discuss the importance of the genetic control of the amount, duration, and direction of cellular growth for the emergence of leaf form. We highlight how the combined use of live imaging and computational frameworks can help conceptualize how regulated cellular growth is translated into different leaf shapes. In particular, we focus on the morphogenetic differences between simple and complex leaves and how carnivorous plants form three-dimensional insect traps. We discuss how evolution has shaped leaf diversity in the case of complex leaves, by tinkering with organ-wide growth and local growth repression, and in carnivorous plants, by modifying the relative growth of the lower and upper sides of the leaf primordium to create insect-digesting traps.

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43

Wagner, Robert J., and Franck J. Vernerey. "Computational exploration of treadmilling and protrusion growth observed in fire ant rafts." PLOS Computational Biology 18, no. 2 (February 17, 2022): e1009869. http://dx.doi.org/10.1371/journal.pcbi.1009869.

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Collective living systems regularly achieve cooperative emergent functions that individual organisms could not accomplish alone. The rafts of fire ants (Solenopsis invicta) are often studied in this context for their ability to create aggregated structures comprised entirely of their own bodies, including tether-like protrusions that facilitate exploration of and escape from flooded environments. While similar protrusions are observed in cytoskeletons and cellular aggregates, they are generally dependent on morphogens or external gradients leaving the isolated role of local interactions poorly understood. Here we demonstrate through an ant-inspired, agent-based numerical model how protrusions in ant rafts may emerge spontaneously due to local interactions. The model is comprised of a condensed structural network of agents that represents the monolayer of interconnected worker ants, which floats on the water and gives ant rafts their form. Experimentally, this layer perpetually contracts, which we capture through the pairwise contraction of all neighboring structural agents at a strain rate of d˙. On top of the structural layer, we model a dispersed, on-lattice layer of motile agents that represents free ants, which walk on top of the floating network. Experimentally, these self-propelled free ants walk with some mean persistence length and speed that we capture through an ant-inspired phenomenological model. Local interactions occur between neighboring free ants within some radius of detection, R, and the persistence length of freely active agents is tuned through a noise parameter, η as introduced by the Vicsek model. Both R and η where fixed to match the experimental trajectories of free ants. Treadmilling of the raft occurs as agents transition between the structural and free layers in accordance with experimental observations. Ultimately, we demonstrate how phases of exploratory protrusion growth may be induced by increased ant activity as characterized by a dimensionless parameter, A. These results provide an example in which functional morphogenesis of a living system may emerge purely from local interactions at the constituent length scale, thereby providing a source of inspiration for the development of decentralized, autonomous active matter and swarm robotics.

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44

Lehnert, Fritz, and Stefan G. Mayr. "Nanoporous amorphous Ge–Si alloys – unraveling the physics behind ion beam induced morphogenesis." Physical Chemistry Chemical Physics 19, no. 34 (2017): 23461–70. http://dx.doi.org/10.1039/c7cp04855f.

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By employing a combined experimental-computational study, the atomic scale mechanisms for nanoporous morphogenesis due to exposure to energetic ions are unveiled. This opens avenues for generalizations and a design-by-understanding approach to synthesize tailored nanosponges.

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45

Menges, Achim. "Material Computation: Higher Integration in Morphogenetic Design." Architectural Design 82, no. 2 (March 2012): 14–21. http://dx.doi.org/10.1002/ad.1374.

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46

Pałubicki, Wojtek, Andrzej Kokosza, and Agata Burian. "Formal description of plant morphogenesis." Journal of Experimental Botany 70, no. 14 (July 1, 2019): 3601–13. http://dx.doi.org/10.1093/jxb/erz210.

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Abstract Plant morphogenesis may be characterized by complex feedback mechanisms between signals specifying growth and by the growth of the plant body itself. Comprehension of such feedback mechanisms is an ongoing research task and can be aided with formal descriptions of morphogenesis. In this review, we present a number of established mathematical paradigms that are useful to the formal representation of plant shape, and of biomechanical and biochemical signaling. Specifically, we discuss work from a range of research areas including plant biology, material sciences, fluid dynamics, and computer graphics. Treating plants as organized systems of information processing allows us to compare these different mathematical methods in terms of their expressive power of biological hypotheses. This is an attempt to bring together a large number of computational modeling concepts and make them accessible to the analytical as well as empirical student of plant morphogenesis.

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47

Sameshima, Yutaka, Masakazu TERAI, Tadashi SAITO, and Daiji FUJII. "STUDY ON COMPUTATIONAL MORPHOGENESIS OF UNREINFORCED CONCRETE SHELL USING IESO METHOD." Journal of Structural Engineering B 68B (2022): 127–34. http://dx.doi.org/10.3130/aijjse.68b.0_127.

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48

CUI, Changyu, Hiroshi OHMORI, and Mutsuro SASAKI. "COMPUTATIONAL MORPHOGENESIS BY EXTENDED ESO METHOD : Extension for three-dimensional structures." Journal of Structural and Construction Engineering (Transactions of AIJ) 69, no. 576 (2004): 79–86. http://dx.doi.org/10.3130/aijs.69.79_1.

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49

OHMORI, Hiroshi, Shogo WASEKURA, Hiroaki KAWAMURA, and Tatsushi ISHIYAMA. "COMPUTATIONAL MORPHOGENESIS OF FRAME STRUCTURES WITH UNCERTAINTIES BASED ON FUZZY THEORY." Journal of Structural and Construction Engineering (Transactions of AIJ) 69, no. 578 (2004): 83–90. http://dx.doi.org/10.3130/aijs.69.83.

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50

Siregar, Pridi, Nathalie Julen, Peter Hufnagl, and George Mutter. "A general framework dedicated to computational morphogenesis Part I – Constitutive equations." Biosystems 173 (November 2018): 298–313. http://dx.doi.org/10.1016/j.biosystems.2018.07.003.

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