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Journal articles on the topic 'Processes and Dynamics'

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Published: 10 March 2023

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1

Dew, Ryan, Asim Ansari, and Yang Li. "Modeling Dynamic Heterogeneity Using Gaussian Processes." Journal of Marketing Research 57, no. 1 (October 14, 2019): 55–77. http://dx.doi.org/10.1177/0022243719874047.

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Marketing research relies on individual-level estimates to understand the rich heterogeneity of consumers, firms, and products. While much of the literature focuses on capturing static cross-sectional heterogeneity, little research has been done on modeling dynamic heterogeneity, or the heterogeneous evolution of individual-level model parameters. In this work, the authors propose a novel framework for capturing the dynamics of heterogeneity, using individual-level, latent, Bayesian nonparametric Gaussian processes. Similar to standard heterogeneity specifications, this Gaussian process dynamic heterogeneity (GPDH) specification models individual-level parameters as flexible variations around population-level trends, allowing for sharing of statistical information both across individuals and within individuals over time. This hierarchical structure provides precise individual-level insights regarding parameter dynamics. The authors show that GPDH nests existing heterogeneity specifications and that not flexibly capturing individual-level dynamics may result in biased parameter estimates. Substantively, they apply GPDH to understand preference dynamics and to model the evolution of online reviews. Across both applications, they find robust evidence of dynamic heterogeneity and illustrate GPDH’s rich managerial insights, with implications for targeting, pricing, and market structure analysis.

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2

Martínez-Grau, Héctor, Reto Jagher, F. Xavier Oms, Joan Anton Barceló, Salvador Pardo-Gordó, and Ferran Antolín. "Global Processes, Regional Dynamics?" Documenta Praehistorica 47 (December 1, 2020): 170–91. http://dx.doi.org/10.4312/dp.47.10.

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The goal of this paper is to discuss the validity of radiocarbon dates as a source of knowledge for explaining social dynamics over a large region and a long period of time. We have carefully selected c. 1000 14C dates for the time interval 8000–4000 cal BC within the northwestern Mediterranean area (NE Iberian Peninsula, SE France, N Italy) and Switzerland. Using statistical analysis, we have modelled the summed probability distribution of those dates for each of the analysed ecoregion and discussed the rhythms of neolithisation in these regions and the probability of social contact between previous Mesolithic and new Neolithic populations.

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3

Fernández, J., A. Plastino, L. Diambra, and C. Mostaccio. "Dynamics of coevolutive processes." Physical Review E 57, no. 5 (May 1, 1998): 5897–903. http://dx.doi.org/10.1103/physreve.57.5897.

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4

Behringer, Hans, Ralf Eichhorn, and Stefan Wallin. "Dynamics of biomolecular processes." Physica Scripta 87, no. 5 (April 11, 2013): 058501. http://dx.doi.org/10.1088/0031-8949/87/05/058501.

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5

Weissman, Haim, and Shlomo Havlin. "Dynamics in multiplicative processes." Physical Review B 37, no. 10 (April 1, 1988): 5994–96. http://dx.doi.org/10.1103/physrevb.37.5994.

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6

Jung, W., K. Lee, and C. A. Morales. "Dynamics of G-processes." Stochastics and Dynamics 20, no. 01 (January 28, 2020): 2050037. http://dx.doi.org/10.1142/s0219493720500379.

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A G-process is briefly a process ([A. N. Carvalho, J. A. Langa and J. C. Robinson, Attractors for Infinite-Dimensional Non-Autonomous Dynamical Systems, Applied Mathematical Sciences, Vol. 182 (Springer, 2013)], [C. M. Dafermos, An invariance principle for compact processes, J. Differential Equations 9 (1971) 239–252], [P. E. Kloeden and M. Rasmussen, Nonautonomous Dynamical Systems, Mathematical Surveys and Monographs, Vol. 176 (Amer. Math. Soc., 2011)]) for which the role of evolution parameter is played by a general topological group [Formula: see text]. These processes are broad enough to include the [Formula: see text]-actions (characterized as autonomous [Formula: see text]-processes) and the two-parameter flows (where [Formula: see text]). We endow the space of [Formula: see text]-processes with a natural group structure. We introduce the notions of orbit, pseudo-orbit and shadowing property for [Formula: see text]-processes and analyze the relationship with the [Formula: see text]-processes group structure. We study the equicontinuous [Formula: see text]-processes and use it to construct nonautonomous [Formula: see text]-processes with the shadowing property. We study the global solutions of the [Formula: see text]-processes and the corresponding global shadowing property. We study the expansivity (global and pullback) of the [Formula: see text]-processes. We prove that there are nonautonomous expansive [Formula: see text]-processes and characterize the existence of expansive equicontinuous [Formula: see text]-processes. We define the topological stability for [Formula: see text]-processes and prove that every expansive [Formula: see text]-process with the shadowing property is topologically stable. Examples of nonautonomous topologically stable [Formula: see text]-processes are given.

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7

Krapivsky, P. L. "Dynamics of repulsion processes." Journal of Statistical Mechanics: Theory and Experiment 2013, no. 06 (June 20, 2013): P06012. http://dx.doi.org/10.1088/1742-5468/2013/06/p06012.

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8

Němcová, Ingeborg. "Dynamics of socio-economic processes." Acta Informatica Pragensia 2, no. 2 (December 31, 2013): 122–24. http://dx.doi.org/10.18267/j.aip.29.

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9

APOLLONI, ANDREA, and FLORIANA GARGIULO. "DIFFUSION PROCESSES THROUGH SOCIAL GROUPS' DYNAMICS." Advances in Complex Systems 14, no. 02 (April 2011): 151–67. http://dx.doi.org/10.1142/s0219525911003037.

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Axelrod's model describes the dissemination of a set of cultural traits in a society constituted by individual agents. In a social context, nevertheless, individual choices toward a specific attitude are also at the basis of the formation of communities, groups and parties. The membership in a group changes completely the behavior of single agents who start acting according to a social identity. Groups act and interact among them as single entities, but still conserve an internal dynamics. We show that, under certain conditions of social dynamics, the introduction of group dynamics in a cultural dissemination process avoids the flattening of the culture into a single entity and preserves the multiplicity of cultural attitudes. We also consider diffusion processes on this dynamical background, showing the conditions under which information as well as innovation can spread through the population in a scenario where the groups' choices determine the social structure.

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10

VINCENT, THOMAS L. "THE G-FUNCTION METHOD FOR ANALYZING DARWINIAN DYNAMICS." International Game Theory Review 06, no. 01 (March 2004): 69–90. http://dx.doi.org/10.1142/s0219198904000083.

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Darwinian dynamics refers to the dynamical processes underlying natural selection that drives evolution. We are interested in the evolution of strategies used by biological entities. There are two dynamical processes involved, population dynamics (relationship between population density and the agents affecting density) and strategy dynamics (relationship between strategy values and the agents affecting these values). Darwinian dynamics is a total dynamic obtained through the coupling of these two processes, the modeling of which, involves dynamical systems, optimization, stability, and game theory. Using a method called the G-function approach, we explore how an evolutionary process can take place in a set of differential equations, and we examine some interesting links between evolutionary stability and optimization as embodied in the ESS maximum principle. One of the interesting paradoxes is how a "hill-climbing" algorithm can end up at a stable local minimum and why this might have important implications in understanding speciation (the creation of new species from a homogeneous population). Finally, we will examine how these concepts are currently being applied to model the development of tumors in humans.

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11

Kondratenko, Leonid A., and Lubov I. Mironova. "Investigation of dynamics of roll forming processes." MATEC Web of Conferences 224 (2018): 01134. http://dx.doi.org/10.1051/matecconf/201822401134.

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This article contains the analysis of tube expander dynamics in complex interaction of structural elements of heat-exchange tubes attachment assembly in the process of roll-forming operation, description of dynamic process theoretical aspect. It is shown that torque variations lead to velocity fluctuations and influence the service life of operative parts of tube expander and quality of tube attachment assemblies.

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12

Vasconcelos, Vítor V., Simon A. Levin, and Flávio L. Pinheiro. "Consensus and polarization in competing complex contagion processes." Journal of The Royal Society Interface 16, no. 155 (June 2019): 20190196. http://dx.doi.org/10.1098/rsif.2019.0196.

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The rate of adoption of new information depends on reinforcement from multiple sources in a way that often cannot be described by simple contagion processes. In such cases, contagion is said to be complex. Complex contagion happens in the diffusion of human behaviours, innovations and knowledge. Based on that evidence, we propose a model that considers multiple, potentially asymmetric and competing contagion processes and analyse its respective population-wide dynamics, bringing together ideas from complex contagion, opinion dynamics, evolutionary game theory and language competition by shifting the focus from individuals to the properties of the diffusing processes. We show that our model spans a dynamical space in which the population exhibits patterns of consensus, dominance, and, importantly, different types of polarization, a more diverse dynamical environment that contrasts with single simple contagion processes. We show how these patterns emerge and how different population structures modify them through a natural development of spatial correlations: structured interactions increase the range of the dominance regime by reducing that of dynamic polarization, tight modular structures can generate structural polarization, depending on the interplay between fundamental properties of the processes and the modularity of the interaction network.

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13

Crutchfield, James P. "Dynamical embodiments of computation in cognitive processes." Behavioral and Brain Sciences 21, no. 5 (October 1998): 635. http://dx.doi.org/10.1017/s0140525x98291734.

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Dynamics is not enough for cognition, nor it is a substitute for information-processing aspects of brain behavior. Moreover, dynamics and computation are not at odds, but are quite compatible. They can be synthesized so that any dynamical system can be analyzed in terms of its intrinsic computational components.

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14

Fejgin, Naomi, and Ronit Hanegby. "Physical Educators’ Participation in Decision-Making Processes in Dynamic Schools." Journal of Teaching in Physical Education 18, no. 2 (January 1999): 141–58. http://dx.doi.org/10.1123/jtpe.18.2.141.

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Teacher participation in school decision-making processes is considered one of the major components of school dynamics. It is not known, however, whether all teachers participate in the process to the same extent. This study examines whether teacher participation is related to school dynamics and to subject matter taught. In a 3-step sequential model, the relative contribution of background variables, school measures, school dynamics, and subject matter taught to teacher participation was estimated. Findings showed that school dynamics had the strongest effect on teacher participation, but the effect was not the same for all teachers. Physical educators participated in school decision-making processes less than did other teachers. Physical educators in dynamic schools reported a higher degree of participation than physical educators in non-dynamic schools but a lower degree of participation compared to other teachers in dynamic schools.

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15

Jagers, Peter. "Branching Processes as Population Dynamics." Bernoulli 1, no. 1/2 (March 1995): 191. http://dx.doi.org/10.2307/3318688.

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16

Smith, Pamela K., Yidan Yin, Pamela K. Smith, Gabrielle Adams, Anurag Gupta, Nicholas Hays, M. Ena Inesi, et al. "Interpersonal Processes of Power Dynamics." Academy of Management Proceedings 2020, no. 1 (August 2020): 17588. http://dx.doi.org/10.5465/ambpp.2020.17588symposium.

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17

Wiggs, G. F. S. "Desert dune processes and dynamics." Progress in Physical Geography 25, no. 1 (March 1, 2001): 53–79. http://dx.doi.org/10.1191/030913301667883129.

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18

Peseckis, Frank E. "Statistical dynamics of stable processes." Physical Review A 36, no. 2 (July 1, 1987): 892–902. http://dx.doi.org/10.1103/physreva.36.892.

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19

Selim, H. M. "Soil Pollution: Processes and Dynamics." Soil Science 162, no. 12 (December 1997): 953–54. http://dx.doi.org/10.1097/00010694-199712000-00010.

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20

Loveland, P. "Soil pollution. Processes and dynamics." Geoderma 75, no. 1-2 (January 1997): 150–52. http://dx.doi.org/10.1016/s0016-7061(96)00082-1.

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21

Young, Scott. "Soil pollution, processes and dynamics." Environmental Pollution 94, no. 3 (1996): 363–64. http://dx.doi.org/10.1016/s0269-7491(97)84221-2.

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22

Brouwers, H. J. H. "Soil pollution, processes and dynamics." Journal of Hazardous Materials 54, no. 1-2 (June 1997): 137. http://dx.doi.org/10.1016/s0304-3894(97)89418-6.

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23

Velázquez-Quesada, Fernando R. "Reasoning Processes as Epistemic Dynamics." Axiomathes 25, no. 1 (October 30, 2014): 41–60. http://dx.doi.org/10.1007/s10516-014-9255-6.

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24

Volpi, G. G. "Elementary processes in chemical dynamics." Pure and Applied Chemistry 62, no. 9 (January 1, 1990): 1649–51. http://dx.doi.org/10.1351/pac199062091649.

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25

Balachandran, B. "Nonlinear dynamics of milling processes." Philosophical Transactions of the Royal Society of London. Series A: Mathematical, Physical and Engineering Sciences 359, no. 1781 (April 15, 2001): 793–819. http://dx.doi.org/10.1098/rsta.2000.0755.

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26

Комиссаров, G. Komissarov, Рубцова, and N. Rubtsova. "Chain processes in cognitive dynamics." Complexity. Mind. Postnonclassic 3, no. 1 (April 7, 2014): 70–78. http://dx.doi.org/10.12737/3399.

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The article discusses the construction of circuits only within random-access memory, additionally limited by attention. We propose a model explaining the features of the dynamics of solving problems on insight using N.N. Semenov’s theory of chain branching chemical reactions. When referring to long-term memory (and return from it with the result on the construction of a representation) the real average length of generalized mental chains can only increase, since it is known that the concepts and objects in it branched and associated with others. In circuit theory, the condition when values of average length chains go to infinity means nonstationary mode of reaction (chain explosion). Thus, in the present model this mode of sharp increase in the average length of the chains is the most favorable conditions for the building the representation – any circuit (with a length of no longer than d) we take to build from existing units operated with all its branches - it is taken in our attention and has no time to break off. These conditions are most favorable for the building and restructuring the representations, and there is the insight moment in our model. Well-known literature data on the experimental investigation of insight and creativity are in good agreement with the requirements of this model towards insight parameters.

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27

Wiggs, Giles F. S. "Desert dune processes and dynamics." Progress in Physical Geography: Earth and Environment 25, no. 1 (March 2001): 53–79. http://dx.doi.org/10.1177/030913330102500103.

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This article reviews the advances made and problems encountered in the measurement, modelling and understanding of desert dune dynamics and processes in the last two decades. The main findings of three methods of investigation are reviewed: field studies, wind tunnel studies and mathematical modelling. Whilst major advances in field techniques have allowed an appreciation of the aerodynamic nature of sand dunes, particular problems with field research are evident in the measurement of aeolian processes on dune surfaces. Specifically, it is shown that attempts to ascertain shear stresses on dune windward slopes in the field and relate changes in stress to sand transport rate and erosion/deposition measurements have generally failed. These difficulties have arisen because the non-log-linear nature of wind velocity profiles on dune surfaces as a result of windflow acceleration has made the calculation of surface shear stresses unviable. Significant advances have been achieved in wind tunnel modelling where high-frequency hot-wire anemometer measurements have enabled shear stress and turbulence characteristics to be determined, although problems have been encountered in choosing appropriate scaling parameters. Empirical field and wind tunnel data have allowed the calibration of mathematical models which are now at a stage where the flow field around dunes can be calculated. It is considered, however, that the emerging technique of modelling using complex systems theory may hold the key to constructing a reliable framework for future investigations. New complex systems models have emphasized the need to return to a larger-scale perspective where dunes are not considered as individual elements, but as an integral part of a dunefield where aeolian processes at the dune scale are not thought to be significant.

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28

Ejima, Toshiaki. "Dynamics of Stochastic Relaxation Processes." Systems and Computers in Japan 20, no. 3 (September 5, 2007): 68–77. http://dx.doi.org/10.1002/scj.4690200307.

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29

Hayes, Robert A., and John Ralston. "The dynamics of wetting processes." Colloids and Surfaces A: Physicochemical and Engineering Aspects 93 (December 1994): 15–23. http://dx.doi.org/10.1016/0927-7757(94)02934-2.

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30

Hansson, Lennart, and Heikki Henttonen. "Rodent dynamics as community processes." Trends in Ecology & Evolution 3, no. 8 (August 1988): 195–200. http://dx.doi.org/10.1016/0169-5347(88)90006-7.

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31

Kirkby, M. J., and L. J. Bracken. "Gully processes and gully dynamics." Earth Surface Processes and Landforms 34, no. 14 (November 30, 2009): 1841–51. http://dx.doi.org/10.1002/esp.1866.

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32

McKoy, Vincent, Diane Lynch, and Robert R. Lucchese. "Dynamics of molecular photoionization processes." International Journal of Quantum Chemistry 24, S17 (June 19, 2009): 89–100. http://dx.doi.org/10.1002/qua.560240810.

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33

Varona, Pablo, and Mikhail I. Rabinovich. "Hierarchical dynamics of informational patterns and decision-making." Proceedings of the Royal Society B: Biological Sciences 283, no. 1832 (June 15, 2016): 20160475. http://dx.doi.org/10.1098/rspb.2016.0475.

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Traditional studies on the interaction of cognitive functions in healthy and disordered brains have used the analyses of the connectivity of several specialized brain networks—the functional connectome. However, emerging evidence suggests that both brain networks and functional spontaneous brain-wide network communication are intrinsically dynamic. In the light of studies investigating the cooperation between different cognitive functions, we consider here the dynamics of hierarchical networks in cognitive space. We show, using an example of behavioural decision-making based on sequential episodic memory, how the description of metastable pattern dynamics underlying basic cognitive processes helps to understand and predict complex processes like sequential episodic memory recall and competition among decision strategies. The mathematical images of the discussed phenomena in the phase space of the corresponding cognitive model are hierarchical heteroclinic networks. One of the most important features of such networks is the robustness of their dynamics. Different kinds of instabilities of these dynamics can be related to ‘dynamical signatures’ of creativity and different psychiatric disorders. The suggested approach can also be useful for the understanding of the dynamical processes that are the basis of consciousness.

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34

Kuzenov, V. V., and S. V. Ryzhkov. "Mathematical Modeling of Plasma Dynamics for Processes in Capillary Discharges." Nelineinaya Dinamika 15, no. 4 (2019): 543–50. http://dx.doi.org/10.20537/nd190413.

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35

Cerdà, Artemi. "Post-fire dynamics of erosional processes under Mediterranean climatic conditions." Zeitschrift für Geomorphologie 42, no. 3 (October 1, 1998): 373–98. http://dx.doi.org/10.1127/zfg/42/1998/373.

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36

Khramchenkov, Maxim, and Eduard Khramchenkov. "Rheological aspects of underground fluid dynamics and mass exchange processes." Epitoanyag - Journal of Silicate Based and Composite Materials 68, no. 2 (2016): 34–38. http://dx.doi.org/10.14382/epitoanyag-jsbcm.2016.6.

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37

Lukyanov, G. "Studies of Dynamic Processes." Journal of Physics: Conference Series 2096, no. 1 (November 1, 2021): 012166. http://dx.doi.org/10.1088/1742-6596/2096/1/012166.

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Abstract The traditional approach to experimental data processing is based on the estimation of the averaged characteristics of the process, such as mean, variance, and range. However, a deeper processing with the identification of the features of the non-wicked dynamic behavior of the process allows us to see those features that are very important for a more complete understanding of its essence. The article provides examples of identifying the features of the dynamic behavior of processes in the atmosphere, studying the dynamics of heat and mass transfer when air moves in the upper respiratory tract of a person, and acoustic vibrations excited by a flame in the environment. Using the example of processing the time series of fluctuations in atmospheric air temperature, it is shown what unexpected information can be hidden in dynamic changes.

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38

WIESENFELD, J. M. "GAIN DYNAMICS AND ASSOCIATED NONLINEARITIES IN SEMICONDUCTOR OPTICAL AMPLIFIERS." International Journal of High Speed Electronics and Systems 07, no. 01 (March 1996): 179–222. http://dx.doi.org/10.1142/s0129156496000086.

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A rich variety of dynamical processes underlie the operation of active semiconductor light-emitting devices, such as semiconductor optical amplifiers. These processes include interband and intraband carrier dynamics. Interband processes comprise spontaneous recombination, both radiative and Auger, stimulated radiative recombination, and carrier transport. Intraband processes comprise carrier heating and cooling and spectral hole-burning, among others. The dynamical processes affect both the gain and refractive index of the semiconductor optical amplifier. In this article, these dynamic processes and their physical origins are reviewed. Under conditions of large, time-varying changes in carrier density or intraband carrier distribution, nonlinear gain and refraction becomes significant. For applications requiring linear amplification, such nonlinearities are deleterious. However, for many applications such nonlinearities can be the basis for useful device functions. In particular, the nonlinearities of cross-gain modulation, cross-phase modulation, and four-wave mixing in semiconductor optical amplifiers have been applied for the functions of wavelength conversion, optical time-demultiplexing, clock recovery, and trans-multiplexing. Such nonlinear devices based on semiconductor optical amplifiers and their effects on propagating optical signals are also reviewed.

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39

DENISENKO, IRINA YE. "DYNAMICS OF LANGUAGE PROCESSES IN BELGIUM." Cherepovets State University Bulletin 2, no. 101 (2021): 23–32. http://dx.doi.org/10.23859/1994-0637-2021-2-101-2.

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The article reveals the content of the terms “borrowing”, “belgicism”, “regionalism” in the framework of the comparative study of the Belgian version of the French language and the metropolitan French language. The research focuses on the regionalisms in the Belgian version of the French language, which, along with the standard Belgian French, constitute an important part of the vocabulary, have special features in terms of content or expression in comparison with lexis of the metropolitan French language. The author focuses on the contextual analysis of the lexis in the Belgian French and the standard French language in order to identify the lexical and semantic features and dynamics of linguistic processes in the territory of French-speaking Belgium. In the course of the study, dictionaries of regionalisms and belgicisms were used; the main research method is comparative.

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40

Munitsyna, M. A. "Transition Processes in Tippe-Top Dynamics." Mechanics of Solids 55, no. 8 (December 2020): 1178–84. http://dx.doi.org/10.3103/s0025654420080178.

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41

Kahn, E. Michael, I. Terry Sturke, and Janet Schaeffer. "Inpatient Group Processes Parallel Unit Dynamics." International Journal of Group Psychotherapy 42, no. 3 (July 1992): 407–18. http://dx.doi.org/10.1080/00207284.1992.11490708.

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Martinez-Valderrama, Jaime, Javier Ibáñez, Rolando Gartzia, and Francisco J. https://orcid.org/0000-0002-8165-8669. "System Dynamics for understanding desertification processes." Ecosistemas 30, no. 3 (December 24, 2021): 2191. http://dx.doi.org/10.7818/ecos.2191.

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La desertificación es un proceso complejo y contraintuitivo cuyo estudio demanda un enfoque multidisciplinar. Ello la convierte en un campo de investigación ideal sobre el que aplicar la Dinámica de Sistemas (DS). Se trata de una metodología de construcción de modelos dinámicos de simulación por ordenador que se concibe como herramienta de apoyo para el estudio y la gestión de problemas que, especialmente, muestren las características aludidas. Este artículo repasa los fundamentos de la metodología, muestra sus ventajas y desventajas, e ilustra su funcionamiento con un caso de estudio de desertificación. A través de este modelo, que describe un sistema de pastoreo en el que tanto la erosión como la invasión de matorrales son dos amenazas contrapuestas y latentes, se explican dos de las principales señas de identidad de la DS: la detección de bucles de realimentación y la implementación de multiplicadores. Mediante los primeros se trata de explicitar los mecanismos subyacentes al comportamiento del sistema y con los “multis” se demuestra la necesidad de considerar el comportamiento de un sistema en situaciones extremas, propias de problemas como la desertificación. El trabajo presenta, además, diversas maneras de utilizar un modelo DS. Más allá de la evolución temporal de las variables que forman parte del modelo, es posible acoplar distintos tipos de análisis que resultan muy útiles en el estudio y prevención de la desertificación, como es la estimación de riesgos de desertificación y los análisis de sensibilidad que permiten detectar los factores más determinantes de este problema.

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43

Caridade, P. J. S. B., J. Sabin, J. D. Garrido, and A. J. C. Varandas. "Dynamics of OH + O2vibrational relaxation processes." Phys. Chem. Chem. Phys. 4, no. 20 (2002): 4959–69. http://dx.doi.org/10.1039/b203101a.

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44

Abbott, Jason P., and Sophie Gregorios-Pippas. "Islamization in Malaysia: processes and dynamics." Contemporary Politics 16, no. 2 (May 21, 2010): 135–51. http://dx.doi.org/10.1080/13569771003783851.

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45

HAYAKAWA, HISAO. "FRACTIONAL DYNAMICS IN PHASE ORDERING PROCESSES." Fractals 01, no. 04 (December 1993): 947–53. http://dx.doi.org/10.1142/s0218348x93001003.

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The growth kinetics of a system with O(n) symmetric order parameter quenched into the ordered phase from the disordered phase, is considered based on the fractional dynamics model which is the time-dependent Ginzburg-Landau (TDGL) model with long-range interactions and locally non-conserved but globally conserved order parameter. A solution for the spatial correlation function in the spherical limit (n=∞) displays a multiscaling property. This multiscaling disappears in cases of large but finite n or pure non-conserved dynamics. It is found that the spatial correlation function in the fractional dynamics model is essentially the same as that in conventional conserved model for large n, while the growth exponent depends on the model.

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46

Philpott, D. R. "Vortex processes and Solid Body Dynamics." Proceedings of the Institution of Mechanical Engineers, Part G: Journal of Aerospace Engineering 211, no. 1 (January 1, 1997): 64–65. http://dx.doi.org/10.1177/095441009721100103.

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Khoromskaia, Diana, Rosemary J. Harris, and Stefan Grosskinsky. "Dynamics of non-Markovian exclusion processes." Journal of Statistical Mechanics: Theory and Experiment 2014, no. 12 (December 16, 2014): P12013. http://dx.doi.org/10.1088/1742-5468/2014/12/p12013.

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Bestehorn, Michael. "IMA8 – Interfacial Fluid Dynamics and Processes." European Physical Journal Special Topics 226, no. 6 (April 2017): 1151–53. http://dx.doi.org/10.1140/epjst/e2017-70057-9.

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Kitano, Hiromi, and Norio Ise. "Dynamics of association and recognition processes." Kobunshi 38, no. 8 (1989): 824–27. http://dx.doi.org/10.1295/kobunshi.38.824.

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Johansson, Börje. "Dynamics of Metropolitan processes and policies.Introduction." Scandinavian Housing and Planning Research 2, no. 3-4 (January 1985): 115–23. http://dx.doi.org/10.1080/02815738508730068.

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