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Journal articles on the topic 'Dynamic'

Author: Grafiati

Published: 4 June 2021

Last updated: 16 November 2024

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1

f, f. "Designing for Dynamics in Dynamic Narrative Inquiry." Asian Qualitative Inquiry Association 2, no. 2 (December 31, 2023): 77–94. http://dx.doi.org/10.56428/aqij.2023.2.2.77.

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This article addresses the question “How is dynamic narrative inquiry dynamic?” To do that, I present principles of dynamic narrative inquiry, with a focus on the active authoring of meaning in research interactions as in everyday life. Drawing on prior examples of activity-meaning system research designs and dynamic narrative analyses, I illustrate how this authoring process involves creative use of language and literary forms to express and transform interactive meaning with diverse others and one’s self. A goal of the article is to increase researchers’ sensitivity to the fact that paying attention to how everyone communicates offers major and otherwise overlooked insights into what everyone is saying about the issue of interest.

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2

Williams, Robley C., Michael Caplow, and J. Richard McIntosh. "Cytoskeleton: Dynamic microtubule dynamics." Nature 324, no. 6093 (November 1986): 106–7. http://dx.doi.org/10.1038/324106a0.

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3

Raza, Md Shamim, Nitesh Kumar, and Sourav Poddar. "Combustor Characteristics under Dynamic Condition during Fuel – Air Mixingusing Computational Fluid Dynamics." Journal of Advances in Mechanical Engineering and Science 1, no. 1 (August 8, 2015): 20–33. http://dx.doi.org/10.18831/james.in/2015011003.

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4

STRADTMANN, Hinnerk. "1D14 Examples for European assessment of vehicle's dynamic running behaviour(Vehicles-Dynamics)." Proceedings of International Symposium on Seed-up and Service Technology for Railway and Maglev Systems : STECH 2015 (2015): _1D14–1_—_1D14–12_. http://dx.doi.org/10.1299/jsmestech.2015._1d14-1_.

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5

Agnew, Thelma. "Dynamic teams and team dynamics." Nursing Management 12, no. 1 (April 2005): 7. http://dx.doi.org/10.7748/nm.12.1.7.s10.

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6

Travers, Andrew. "Dynamic DNA Underpins Chromosome Dynamics." Biophysical Journal 105, no. 10 (November 2013): 2235–37. http://dx.doi.org/10.1016/j.bpj.2013.10.011.

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7

Curtis-Jones, Alison. "Dynamic dichotomies: How can the body be a dynamic archive?" Dance, Movement & Spiritualities 10, no. 1 (October 1, 2023): 99–124. http://dx.doi.org/10.1386/dmas_00049_1.

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This article discusses the complexities around movement dynamics and how the term ‘dynamic archive’ is understood in dance. Drawing from Andre Lepecki’s ‘The body as archive’ (2010), Rudolf Laban and F. C. Lawrence’s Effort theory (1947) and a choreological perspective to investigate the complexities of dynamics as an embodied phenomenon, I discuss the body as a dynamic archive of embodied experience. This article provides debate about how dynamics are learnt and recalled for the purposes of re-staging and how movement dynamics are stored by the dancer as a dynamic archive.

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Han, Yueying, Yi Cao, and Hai Lei. "Dynamic Covalent Hydrogels: Strong yet Dynamic." Gels 8, no. 9 (September 10, 2022): 577. http://dx.doi.org/10.3390/gels8090577.

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Hydrogels are crosslinked polymer networks with time-dependent mechanical response. The overall mechanical properties are correlated with the dynamics of the crosslinks. Generally, hydrogels crosslinked by permanent chemical crosslinks are strong but static, while hydrogels crosslinked by physical interactions are weak but dynamic. It is highly desirable to create synthetic hydrogels that possess strong mechanical stability yet remain dynamic for various applications, such as drug delivery cargos, tissue engineering scaffolds, and shape-memory materials. Recently, with the introduction of dynamic covalent chemistry, the seemingly conflicting mechanical properties, i.e., stability and dynamics, have been successfully combined in the same hydrogels. Dynamic covalent bonds are mechanically stable yet still capable of exchanging, dissociating, or switching in response to external stimuli, empowering the hydrogels with self-healing properties, injectability and suitability for postprocessing and additive manufacturing. Here in this review, we first summarize the common dynamic covalent bonds used in hydrogel networks based on various chemical reaction mechanisms and the mechanical strength of these bonds at the single molecule level. Next, we discuss how dynamic covalent chemistry makes hydrogel materials more dynamic from the materials perspective. Furthermore, we highlight the challenges and future perspectives of dynamic covalent hydrogels.

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9

Feng, Zengming, Fuliang Suo, and Yabing Cheng. "58793 MESHING MECHANISM AND DYNAMIC ANALYSIS OF NEW SILENT CHAIN(Dynamics of Machine Components)." Proceedings of the Asian Conference on Multibody Dynamics 2010.5 (2010): _58793–1_—_58793–5_. http://dx.doi.org/10.1299/jsmeacmd.2010.5._58793-1_.

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10

Cho, J. I., J. Y. Kim, and T. W. Park. "62931 DYNAMIC ANALYSIS ON THE NEXT GENERATION HIGH-SPEED RAILWAY VEHICLE(Railroad System Dynamics)." Proceedings of the Asian Conference on Multibody Dynamics 2010.5 (2010): _62931–1_—_62931–6_. http://dx.doi.org/10.1299/jsmeacmd.2010.5._62931-1_.

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11

Dassi, Erik, and Alessandro Quattrone. "DynaMIT: the dynamic motif integration toolkit." Nucleic Acids Research 44, no. 10 (February 18, 2016): 4988. http://dx.doi.org/10.1093/nar/gkw119.

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12

Dassi, Erik, and Alessandro Quattrone. "DynaMIT: the dynamic motif integration toolkit." Nucleic Acids Research 44, no. 1 (August 7, 2015): e2-e2. http://dx.doi.org/10.1093/nar/gkv807.

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13

Srinivasan, S. G., I. Ashok, Hannes Jônsson, Gretchen Kalonji, and John Zahorjan. "Dynamic-domain-decomposition parallel molecular dynamics." Computer Physics Communications 102, no. 1-3 (May 1997): 44–58. http://dx.doi.org/10.1016/s0010-4655(97)00016-7.

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14

Paolini, Gaia V. "Dynamic approach to nonequilibrium molecular dynamics." Nuclear Physics B - Proceedings Supplements 5, no. 1 (September 1988): 272–77. http://dx.doi.org/10.1016/0920-5632(88)90054-0.

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15

VAN DER MAAREL, EDDY. "Vegetation dynamics and dynamic vegetation science*." Acta Botanica Neerlandica 45, no. 4 (December 1996): 421–42. http://dx.doi.org/10.1111/j.1438-8677.1996.tb00804.x.

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16

Nguyen, T. T. B., and J. J. Fredberg. "Strange Dynamics of a Dynamic Cytoskeleton." Proceedings of the American Thoracic Society 5, no. 1 (January 1, 2008): 58–61. http://dx.doi.org/10.1513/pats.200705-055vs.

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17

Zhou, S. J., P. S. Lomdahl, R. Thomson, and B. L. Holian. "Dynamic Crack Processes via Molecular Dynamics." Physical Review Letters 76, no. 13 (March 25, 1996): 2318–21. http://dx.doi.org/10.1103/physrevlett.76.2318.

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18

Lane, Stuart. "The Dynamics of Dynamic River Channels." Geography 80, no. 2 (April 1995): 147–62. http://dx.doi.org/10.1080/20436564.1995.12452485.

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19

Sun, Ao, and Ting Qiang Yao. "Modeling and Analysis of Planar Multibody System Containing Deep Groove Ball Bearing with Slider-Crank Mechanism." Advanced Materials Research 753-755 (August 2013): 918–23. http://dx.doi.org/10.4028/www.scientific.net/amr.753-755.918.

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With the rotating machinery system developing toward high speed, high precision, and high reliability direction, ball bearing dynamic performance have a critical impact to dynamics characteristics of support system. Based on multibody dynamics theory and contact dynamics method,and considering the ball and ring raceway 3 d dynamic contact relationship, using ADAMS dynamics analysis software to establish the multibody dynamics model of crank slider mechanism containing ball bearing dynamic contact relationship.The simulation analysis of the dynamic performance of the ball bearing and the crank slider mechanism dynamics response, and the influence of dynamic performance for considering ball bearing rotating mechanical system dynamics analysis provides a reference method.The simulation analysts the influence of dynamic performance of the ball bearing to the crank slider mechanism dynamics response. It provides a reference method for rotating mechanical system dynamics analysis considering the dynamic performance of the ball bearing.

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20

Heitmann, Stewart, and Michael Breakspear. "Putting the “dynamic” back into dynamic functional connectivity." Network Neuroscience 2, no. 2 (June 2018): 150–74. http://dx.doi.org/10.1162/netn_a_00041.

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The study of fluctuations in time-resolved functional connectivity is a topic of substantial current interest. As the term “dynamic functional connectivity” implies, such fluctuations are believed to arise from dynamics in the neuronal systems generating these signals. While considerable activity currently attends to methodological and statistical issues regarding dynamic functional connectivity, less attention has been paid toward its candidate causes. Here, we review candidate scenarios for dynamic (functional) connectivity that arise in dynamical systems with two or more subsystems; generalized synchronization, itinerancy (a form of metastability), and multistability. Each of these scenarios arises under different configurations of local dynamics and intersystem coupling: We show how they generate time series data with nonlinear and/or nonstationary multivariate statistics. The key issue is that time series generated by coupled nonlinear systems contain a richer temporal structure than matched multivariate (linear) stochastic processes. In turn, this temporal structure yields many of the phenomena proposed as important to large-scale communication and computation in the brain, such as phase-amplitude coupling, complexity, and flexibility. The code for simulating these dynamics is available in a freeware software platform, the Brain Dynamics Toolbox.

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21

Avkiran, Necmi Kemal, and Alan McCrystal. "DYNAMIC NETWORK RANGE-ADJUSTED MEASURE VS. DYNAMIC NETWORK SLACKS-BASED MEASURE." Journal of the Operations Research Society of Japan 57, no. 1 (2014): 1–14. http://dx.doi.org/10.15807/jorsj.57.1.

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22

Vukobratović, Miomir, Veljko Potkonjak, and Aleksandar Rodić. "Contribution to the dynamic study of humanoid robots interacting with dynamic environment." Robotica 22, no. 4 (August 2004): 439–47. http://dx.doi.org/10.1017/s0263574704000207.

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The questions when and why one needs to use mathematical models, and especially the models of dynamics, represent still an unresolved issue. A general answer would be that dynamic modelling is needed as a tool when designing structure of the system and its control unit. In this case we talk about simulation. The other application is in on-line control of the system – the so-called dynamic control. While in simulation one generally uses the best available model, the control can be based on a reduced dynamics, depending on a particular task. The aim of this paper was to highlight the problems important for the dynamics of humanoids and their dynamic environment.

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23

Liu, Fu Rong, Shuang Qing Tang, and Cong Ping Chen. "Dynamic Thrust Allocation of Dynamic Positioning Vessel Based on Model Predictive Control." Advanced Materials Research 1049-1050 (October 2014): 996–99. http://dx.doi.org/10.4028/www.scientific.net/amr.1049-1050.996.

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The dynamic positioning (DP) vessel maintains its position and heading by active thrusters. For safety reasons, DP vessels are typically designed with redundancy thrusters more than needed for motion control. Optimization theories are useful in finding thrust allocation solutions that minimize fuel consumption and reduce “wear and tear” on a thruster. But several challenges exist such as uncertain thruster model, thruster dynamics characters and the individual limitations of the thrusters. In this paper, a dynamic thrust allocation scheme is presented based on model predictive control (MPC) that directly takes thrusters with dynamics characters and various constraints into account. It is shown in simulations that the MPC dynamic thrust allocation scheme performs better in comparison with an existing static allocation method. Its main advantage is the ability to handle thruster dynamics characters and various constraints.

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24

Galizia, Roberto, and Petri T. Piiroinen. "Regions of Reduced Dynamics in Dynamic Networks." International Journal of Bifurcation and Chaos 31, no. 06 (May 2021): 2150080. http://dx.doi.org/10.1142/s0218127421500802.

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We consider complex networks where the dynamics of each interacting agent is given by a nonlinear vector field and the connections between the agents are defined according to the topology of undirected simple graphs. The aim of the work is to explore whether the asymptotic dynamic behavior of the entire network can be fully determined from the knowledge of the dynamic properties of the underlying constituent agents. While the complexity that arises by connecting many nonlinear systems hinders us to analytically determine general solutions, we show that there are conditions under which the dynamical properties of the constituent agents are equivalent to the dynamical properties of the entire network. This feature, which depends on the nature and structure of both the agents and connections, leads us to define the concept of regions of reduced dynamics, which are subsets of the parameter space where the asymptotic solutions of a network behave equivalently to the limit sets of the constituent agents. On one hand, we discuss the existence of regions of reduced dynamics, which can be proven in the case of diffusive networks of identical agents with all-to-all topologies and conjectured for other topologies. On the other hand, using three examples, we show how to locate regions of reduced dynamics in parameter space. In simple cases, this can be done analytically through bifurcation analysis and in other cases we exploit numerical continuation methods.

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25

Kuivaniemi, Teemu, Antti Mäntylä, Ilkka Väisänen, Antti Korpela, and Tero Frondelius. "Dynamic Gear Wheel Simulations using Multibody Dynamics." Rakenteiden Mekaniikka 50, no. 3 (August 21, 2017): 287–91. http://dx.doi.org/10.23998/rm.64944.

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Simulation of the gear train is an important part of the dynamic simulation of the power train of a medium speed diesel engine. In this paper, the advantages of dynamic gear wheel simulation as a part of the flexible multibody simulation of a complete power train are described. The simulation is performed using AVL EXCITE Power Unit.

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26

Reufer, Mathias, Vincent A. Martinez, Peter Schurtenberger, and Wilson C. K. Poon. "Differential Dynamic Microscopy for Anisotropic Colloidal Dynamics." Langmuir 28, no. 10 (February 29, 2012): 4618–24. http://dx.doi.org/10.1021/la204904a.

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27

Franklin, J., and S. Doniach. "Dynamic bond constraints in protein Langevin dynamics." Journal of Chemical Physics 124, no. 15 (April 21, 2006): 154901. http://dx.doi.org/10.1063/1.2178325.

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28

Bolesta, Alexey. "Calculation of Dynamic Hardness by Molecular Dynamics." EPJ Web of Conferences 221 (2019): 01005. http://dx.doi.org/10.1051/epjconf/201922101005.

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Based on the molecular-dynamic simulation of the impact of a solid ball on the surface of polycrystalline copper, a method for calculating the dynamic hardness of nanocrystalline materials is proposed. It is proposed to carry out the calculation of hardness by dividing the impact work by the squeezed volume. It is shown that this expression of dynamic hardness is consistent with Meyer hardness in the case of quasistatic indentation. As a result of this simulation, it is shown that under conditions when the diameter of the impactor decreases and approaches the crystal lattice constant of the target, the dynamic hardness increases. Also, in the calculations, the impactor density varied approximately twice, which was equal to the density of steel and the density of tungsten carbide. For a striker diameter of 5 nm, dynamic hardness increases with the speed of the striker and does not depend on its density.

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29

Wang, Shengfeng, Xin Feng, Ye Wu, and Jinhua Xiao. "Double dynamic scaling in human communication dynamics." Physica A: Statistical Mechanics and its Applications 473 (May 2017): 313–18. http://dx.doi.org/10.1016/j.physa.2017.01.010.

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30

Gupta, Pramod, and Naresh K. Sinha. "Modeling Robot Dynamics Using Dynamic Neural Networks." IFAC Proceedings Volumes 30, no. 11 (July 1997): 755–59. http://dx.doi.org/10.1016/s1474-6670(17)42936-3.

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31

Christensen, Claire, István Albert, Bryan Grenfell, and Réka Albert. "Disease dynamics in a dynamic social network." Physica A: Statistical Mechanics and its Applications 389, no. 13 (July 2010): 2663–74. http://dx.doi.org/10.1016/j.physa.2010.02.034.

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32

Moser, Irene, and Raymond Chiong. "Dynamic function optimisation with hybridised extremal dynamics." Memetic Computing 2, no. 2 (December 19, 2009): 137–48. http://dx.doi.org/10.1007/s12293-009-0027-6.

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33

Schlenker, Philippe. "Anti-dynamics: presupposition projection without dynamic semantics." Journal of Logic, Language and Information 16, no. 3 (February 8, 2007): 325–56. http://dx.doi.org/10.1007/s10849-006-9034-x.

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34

Gumbsch, P., S. J. Zhou, and B. L. Holian. "Molecular dynamics investigation of dynamic crack stability." Physical Review B 55, no. 6 (February 1, 1997): 3445–55. http://dx.doi.org/10.1103/physrevb.55.3445.

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35

Baden-Fuller, Charles, and David J. Teece. "Market sensing, dynamic capability, and competitive dynamics." Industrial Marketing Management 89 (August 2020): 105–6. http://dx.doi.org/10.1016/j.indmarman.2019.11.008.

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36

Storti, Mario A., Norberto M. Nigro, Rodrigo R. Paz, and Lisandro D. Dalcín. "Dynamic boundary conditions in computational fluid dynamics." Computer Methods in Applied Mechanics and Engineering 197, no. 13-16 (February 2008): 1219–32. http://dx.doi.org/10.1016/j.cma.2007.10.014.

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37

Umarovna, Muzaffarova Mokhinur Umarovna*. "About the Dynamics of a Dynamic System." Irish Interdisciplinary Journal of Science & Research 07, no. 04 (2023): 77–86. http://dx.doi.org/10.46759/iijsr.2023.7410.

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38

Bai, Zhengfeng, and Zhiyuan Ning. "Dynamic Responses of the Planetary Gear Mechanism Considering Dynamic Wear Effects." Lubricants 11, no. 6 (June 9, 2023): 255. http://dx.doi.org/10.3390/lubricants11060255.

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Gear wear is unavoidable and results in vibrations and decreased performance in a planetary gear system. In this work, the wear phenomenon of the gear teeth surface and the dynamic responses of the planetary gear mechanism are investigated through a computational methodology. Dynamic responses are presented by considering the dynamic wear effects. First, the model of the planetary gear mechanism dynamics is established by considering the nonlinear stiffness and friction of gear surfaces. The dynamic wear model of the gear is then established based on Archard’s wear model. Further, the coupling between the dynamics and wear characteristics of the planetary gear mechanism is presented by considering the dynamic wear effects. Finally, a numerical investigation is conducted. The simulation results reveal severe wear between the sun and planet gears. The wear depth and meshing vibration responses exhibit prominent nonlinear characteristics. The low-order resonance of the meshing frequency becomes more marked as the mesh times and wear increase.

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39

Sun, Zejun, Jinfang Sheng, Bin Wang, Aman Ullah, and FaizaRiaz Khawaja. "Identifying Communities in Dynamic Networks Using Information Dynamics." Entropy 22, no. 4 (April 9, 2020): 425. http://dx.doi.org/10.3390/e22040425.

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Identifying communities in dynamic networks is essential for exploring the latent network structures, understanding network functions, predicting network evolution, and discovering abnormal network events. Many dynamic community detection methods have been proposed from different viewpoints. However, identifying the community structure in dynamic networks is very challenging due to the difficulty of parameter tuning, high time complexity and detection accuracy decreasing as time slices increase. In this paper, we present a dynamic community detection framework based on information dynamics and develop a dynamic community detection algorithm called DCDID (dynamic community detection based on information dynamics), which uses a batch processing technique to incrementally uncover communities in dynamic networks. DCDID employs the information dynamics model to simulate the exchange of information among nodes and aims to improve the efficiency of community detection by filtering out the unchanged subgraph. To illustrate the effectiveness of DCDID, we extensively test it on synthetic and real-world dynamic networks, and the results demonstrate that the DCDID algorithm is superior to the representative methods in relation to the quality of dynamic community detection.

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40

Yuan, Zhe, Fei Fan, and Xiaotian Bai. "Nonlinear dynamics analysis of a gear system considering tooth contact temperature and dynamic wear." Advances in Mechanical Engineering 14, no. 9 (September 2022): 168781322211210. http://dx.doi.org/10.1177/16878132221121056.

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Increased temperature and surface wear of high-speed and heavy-load gears are inevitable. Thermal deformation and surface wear modify the position of the action line of the tooth surface and thus influence the dynamic characteristics of the gear mesh. In this study, the elastic modulus and tooth profile thermal deformation were calculated when the tooth contact temperature (TCT) increased. A dynamic wear calculation method was used to combine the dynamic mesh force and dynamic wear coefficient caused by the dynamic mesh force obtained in the nonlinear dynamics model with the quasi-static wear model to obtain the cumulative wear depth. The changed elastic modulus, the tooth profile thermal deformation and the wear depth are considered when calculating the mesh stiffness using the energy method. A nonlinear dynamics model was established by considering the effects of TCT and dynamic wear on the internal dynamic excitation of the gear transmission system. The effects of internal excitation variations such as mesh stiffness, STE and backlash on gear dynamics are analyzed, and the study showed their complex effects on gear dynamics. Comparing the bifurcation diagrams with or without considering TCT and dynamic wear reveals that the system enters chaos earlier after considering TCT and dynamic wear.

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41

Cheng, Jun, Shusheng Bi, Chang Yuan, Lin Chen, Yueri Cai, and Yanbin Yao. "A Graph Theory-Based Method for Dynamic Modeling and Parameter Identification of 6-DOF Industrial Robots." Applied Sciences 11, no. 22 (November 19, 2021): 10988. http://dx.doi.org/10.3390/app112210988.

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At present, the absolute positioning accuracy and control accuracy of industrial serial robots need to be improved to meet the accuracy requirements of precision manufacturing and precise control. An accurate dynamic model is an important theoretical basis for solving this problem, and precise dynamic parameters are the prerequisite for precise control. The research of dynamics and parameter identification can greatly promote the application of robots in the field of precision manufacturing and automation. In this paper, we study the dynamical modeling and dynamic parameter identification of an industrial robot system with six rotational DOF (6R robot system) and propose a new method for identifying dynamic parameters. Our aim is to provide an accurate mathematical description of the dynamics of the 6R robot and to accurately identify its dynamic parameters. First, we establish an unconstrained dynamic model for the 6R robot system and rewrite it to obtain the dynamic parameter identification model. Second, we establish the constraint equations of the 6R robot system. Finally, we establish the dynamic model of the constrained 6R robot system. Through the ADAMS simulation experiment, we verify the correctness and accuracy of the dynamic model. The experiments prove that the result of parameter identification has extremely high accuracy and the dynamic model can accurately describe the 6R robot system mathematically. The dynamic modeling method proposed in this paper can be used as the theoretical basis for the study of 6R robot system dynamics and the study of dynamics-based control theory.

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42

Park, Dongil, and Doohyung Kim. "Vibration Analysis of the Flexible Beam Using Dynamic Solver K_Sim." Journal of Advance Research in Mechanical & Civil Engineering (ISSN: 2208-2379) 2, no. 12 (December 31, 2015): 01–06. http://dx.doi.org/10.53555/nnmce.v2i12.324.

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We developed the dynamic solver including the pre-processor with GUI, kinematic/dynamic solver and the post-processor. This can support to analyze the flexible body dynamics as well as the rigid body dynamics. Because almost robot system has the multi bodies including some flexible bodies, multi flexible body dynamics is very important. In the paper, we carried out the vibration analysis of the flexible beam using the developed dynamic solver K_Sim and compared it to the commercial multi flexible body dynamic solver.

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43

Mitchell, Koritha. "Dynamic People, Dynamic Archives." Callaloo 38, no. 3 (2015): 538–43. http://dx.doi.org/10.1353/cal.2015.0075.

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44

Szelągowski, Marek. "The consequences of dynamic BPM." e-mentor 2014, no. 56 (4) (October 24, 2014): 61–68. http://dx.doi.org/10.15219/em56.1126.

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45

Huang, Yicong, and Zhuliang Yu. "Representation Learning for Dynamic Functional Connectivities via Variational Dynamic Graph Latent Variable Models." Entropy 24, no. 2 (January 19, 2022): 152. http://dx.doi.org/10.3390/e24020152.

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Latent variable models (LVMs) for neural population spikes have revealed informative low-dimensional dynamics about the neural data and have become powerful tools for analyzing and interpreting neural activity. However, these approaches are unable to determine the neurophysiological meaning of the inferred latent dynamics. On the other hand, emerging evidence suggests that dynamic functional connectivities (DFC) may be responsible for neural activity patterns underlying cognition or behavior. We are interested in studying how DFC are associated with the low-dimensional structure of neural activities. Most existing LVMs are based on a point process and fail to model evolving relationships. In this work, we introduce a dynamic graph as the latent variable and develop a Variational Dynamic Graph Latent Variable Model (VDGLVM), a representation learning model based on the variational information bottleneck framework. VDGLVM utilizes a graph generative model and a graph neural network to capture dynamic communication between nodes that one has no access to from the observed data. The proposed computational model provides guaranteed behavior-decoding performance and improves LVMs by associating the inferred latent dynamics with probable DFC.

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46

Gilkerson, Robert. "A Disturbance in the Force: Cellular Stress Sensing by the Mitochondrial Network." Antioxidants 7, no. 10 (September 22, 2018): 126. http://dx.doi.org/10.3390/antiox7100126.

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As a highly dynamic organellar network, mitochondria are maintained as an organellar network by delicately balancing fission and fusion pathways. This homeostatic balance of organellar dynamics is increasingly revealed to play an integral role in sensing cellular stress stimuli. Mitochondrial fission/fusion balance is highly sensitive to perturbations such as loss of bioenergetic function, oxidative stress, and other stimuli, with mechanistic contribution to subsequent cell-wide cascades including inflammation, autophagy, and apoptosis. The overlapping activity with m-AAA protease 1 (OMA1) metallopeptidase, a stress-sensitive modulator of mitochondrial fusion, and dynamin-related protein 1 (DRP1), a regulator of mitochondrial fission, are key factors that shape mitochondrial dynamics in response to various stimuli. As such, OMA1 and DRP1 are critical factors that mediate mitochondrial roles in cellular stress-response signaling. Here, we explore the current understanding and emerging questions in the role of mitochondrial dynamics in sensing cellular stress as a dynamic, responsive organellar network.

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47

Forrest, David V. "Elements of Dynamics VI: The Dynamic Unconscious and Unconscious Dynamics." Journal of the American Academy of Psychoanalysis and Dynamic Psychiatry 33, no. 3 (September 2005): 547–60. http://dx.doi.org/10.1521/jaap.2005.33.3.547.

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48

Davtyan, Aram, Gregory A. Voth, and Hans C. Andersen. "Dynamic force matching: Construction of dynamic coarse-grained models with realistic short time dynamics and accurate long time dynamics." Journal of Chemical Physics 145, no. 22 (December 14, 2016): 224107. http://dx.doi.org/10.1063/1.4971430.

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49

Базаров, С. М. "Introduction to chronodynamics." Известия СПбЛТА, no. 233 (December 29, 2020): 259–70. http://dx.doi.org/10.21266/2079-4304.2020.233.259-270.

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В динамике решаются задачи движения тел в координатной системе отсчета динамический параметр-время (пространство): динамические параметры (сила, импульс, энергия, механический момент) функциональны по отношению к независимым координатам времени (пространства). Как правило, эти функции непрерывны (кусочно непрерывны), поэтому с позиции теории обратных функций им можно построить в соответствие обратные функции: функциональность времени (пространства) от динамических параметров как независимых. Для монотонных функций эти отображения (образ-прообраз) взаимно однозначные. Произведение динамического параметра на координату времени (пространства) является потенциалом, это произведение образа и прообраза. Потенциалу можно поставить в соответствие полный дифференциал. Аналитическое исследование полного дифференциала потенциала в координатной системе динамические параметры-время (пространство) раскрывает картину появления функционального времени (пространства) и функциональных динамических параметров, сопряженных координатному времени (пространству) и динамическим параметрам. В результате этого вырисовываются элементы основ хронодинамики, сопряженно дополняющие динамику до потенциальной динамики. При потенциальном построении динамики функциональность динамических параметров от времени (пространства), раскрываемая законами сохранения в динамике, дополняется функциональностью времени (пространства) от динамических параметров: сколько динамических параметров, соответственно столько функциональных времен (пространств) и функциональных параметров. В обобщенной потенциальной динамике динамическим параметрам и времени (пространству) в динамике ставится в соответствие потенциальные динамические параметры и потенциальные времена (пространства). В результате исследования получено: при гиперболической зависимости динамических параметров от времени (пространства) соответствующие им потенциальные динамические параметры и потенциальные времена (пространства) равны нулю. В этих случаях динамика и хронодинамика становятся взаимными антидинамиками. Исследование потенциальных параметров открывает динамический код связности динамических параметров. In dynamics, the problems of motion of bodies in the coordinate reference system dynamic parameter-time (space) are solved: dynamic parameters (force, momentum, energy, mechanical moment) are functional with respect to independent coordinates of time (space). As a rule, these functions are continuous (piecewise continuous), so from the position of the torus of inverse functions, they can be constructed in accordance with inverse functions: the functionality of time (space) from dynamic parameters, as independent. For monotone functions, these mappings (image-prototype) are one-to-one. The product of a dynamic parameter on the coordinate of time (space) is a potential, it is the product of an image and a prototype, the Potential can be matched with a complete differential. The analytical study of the full potential differential in the coordinate system dynamic parameters-time (space) reveals the picture of the appearance of functional time (space) and functional dynamic parameters conjugated to coordinate time (space) and dynamic parameters. As a result, elements of the basics of chronodynamics are drawn, which complement the dynamics to the potential dynamics. In the potential construction of dynamics, the functionality of dynamic parameters from time (space), revealed by the laws of conservation in dynamics, is supplemented by the functionality of time (space) from dynamic parameters: how many dynamic parameters, respectively, as many functional times (spaces) and functional parameters. In generalized potential dynamics, the dynamic parameters and time (space) in dynamics are matched to the potential dynamic parameters and potential times (space). As a result of the study, it is obtained that if the dynamic parameters are hyperbolically dependent on time (space), the corresponding potential dynamic parameters and potential times (space) are equal to zero. In these cases, dynamics and chronodynamics become mutual anti-dynamics. Investigation of potential parameters opens the dynamic code of connectivity of dynamic parameters.

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Базаров, С. М. "Introduction to chronodynamics." Известия СПбЛТА, no. 233 (December 29, 2020): 259–70. http://dx.doi.org/10.21266/2079-4304.2020.233.259-270.

Full text

Abstract:

В динамике решаются задачи движения тел в координатной системе отсчета динамический параметр-время (пространство): динамические параметры (сила, импульс, энергия, механический момент) функциональны по отношению к независимым координатам времени (пространства). Как правило, эти функции непрерывны (кусочно непрерывны), поэтому с позиции теории обратных функций им можно построить в соответствие обратные функции: функциональность времени (пространства) от динамических параметров как независимых. Для монотонных функций эти отображения (образ-прообраз) взаимно однозначные. Произведение динамического параметра на координату времени (пространства) является потенциалом, это произведение образа и прообраза. Потенциалу можно поставить в соответствие полный дифференциал. Аналитическое исследование полного дифференциала потенциала в координатной системе динамические параметры-время (пространство) раскрывает картину появления функционального времени (пространства) и функциональных динамических параметров, сопряженных координатному времени (пространству) и динамическим параметрам. В результате этого вырисовываются элементы основ хронодинамики, сопряженно дополняющие динамику до потенциальной динамики. При потенциальном построении динамики функциональность динамических параметров от времени (пространства), раскрываемая законами сохранения в динамике, дополняется функциональностью времени (пространства) от динамических параметров: сколько динамических параметров, соответственно столько функциональных времен (пространств) и функциональных параметров. В обобщенной потенциальной динамике динамическим параметрам и времени (пространству) в динамике ставится в соответствие потенциальные динамические параметры и потенциальные времена (пространства). В результате исследования получено: при гиперболической зависимости динамических параметров от времени (пространства) соответствующие им потенциальные динамические параметры и потенциальные времена (пространства) равны нулю. В этих случаях динамика и хронодинамика становятся взаимными антидинамиками. Исследование потенциальных параметров открывает динамический код связности динамических параметров. In dynamics, the problems of motion of bodies in the coordinate reference system dynamic parameter-time (space) are solved: dynamic parameters (force, momentum, energy, mechanical moment) are functional with respect to independent coordinates of time (space). As a rule, these functions are continuous (piecewise continuous), so from the position of the torus of inverse functions, they can be constructed in accordance with inverse functions: the functionality of time (space) from dynamic parameters, as independent. For monotone functions, these mappings (image-prototype) are one-to-one. The product of a dynamic parameter on the coordinate of time (space) is a potential, it is the product of an image and a prototype, the Potential can be matched with a complete differential. The analytical study of the full potential differential in the coordinate system dynamic parameters-time (space) reveals the picture of the appearance of functional time (space) and functional dynamic parameters conjugated to coordinate time (space) and dynamic parameters. As a result, elements of the basics of chronodynamics are drawn, which complement the dynamics to the potential dynamics. In the potential construction of dynamics, the functionality of dynamic parameters from time (space), revealed by the laws of conservation in dynamics, is supplemented by the functionality of time (space) from dynamic parameters: how many dynamic parameters, respectively, as many functional times (spaces) and functional parameters. In generalized potential dynamics, the dynamic parameters and time (space) in dynamics are matched to the potential dynamic parameters and potential times (space). As a result of the study, it is obtained that if the dynamic parameters are hyperbolically dependent on time (space), the corresponding potential dynamic parameters and potential times (space) are equal to zero. In these cases, dynamics and chronodynamics become mutual anti-dynamics. Investigation of potential parameters opens the dynamic code of connectivity of dynamic parameters.

APA, Harvard, Vancouver, ISO, and other styles

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