Relevant bibliographies by topics / Molecular dynamics Mathematical models

Academic literature on the topic 'Molecular dynamics Mathematical models'

Author: Grafiati
Published: 4 June 2021
Last updated: 2 February 2022

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Journal articles on the topic "Molecular dynamics Mathematical models"

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Gruzdev, Roman, and Arkady Soloviev. "Polarizable Models in Molecular Dynamics." Solid State Phenomena 258 (December 2016): 202–5. http://dx.doi.org/10.4028/www.scientific.net/ssp.258.202.

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Current work is devoted to the problems of mathematical modeling of electrically polarized nanomaterials using LAMMPS software. There are next methods in this software for modeling of such kind: the fluctuating charge method; the adiabatic core-shell method; the thermalized Drude dipole method. This work provides information on advantages and disadvantages of each method; well-structured scripts for LAMMPS software. As our primary research is devoted to the crystalline elastic materials, much attention is given to the 1st and 2nd methods. Main purpose of research is to build models for zinc oxide (ZnO) for identification of elastic and piezoelectric constants and behavior of nanostructures in different fields. Results for analysis are given in figures and tables.
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SANCHEZ-OSORIO, ISMAEL, FERNANDO RAMOS, PEDRO MAYORGA, and EDGAR DANTAN. "FOUNDATIONS FOR MODELING THE DYNAMICS OF GENE REGULATORY NETWORKS: A MULTILEVEL-PERSPECTIVE REVIEW." Journal of Bioinformatics and Computational Biology 12, no. 01 (January 28, 2014): 1330003. http://dx.doi.org/10.1142/s0219720013300037.

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A promising alternative for unraveling the principles under which the dynamic interactions among genes lead to cellular phenotypes relies on mathematical and computational models at different levels of abstraction, from the molecular level of protein-DNA interactions to the system level of functional relationships among genes. This review article presents, under a bottom–up perspective, a hierarchy of approaches to modeling gene regulatory network dynamics, from microscopic descriptions at the single-molecule level in the spatial context of an individual cell to macroscopic models providing phenomenological descriptions at the population-average level. The reviewed modeling approaches include Molecular Dynamics, Particle-Based Brownian Dynamics, the Master Equation approach, Ordinary Differential Equations, and the Boolean logic abstraction. Each of these frameworks is motivated by a particular biological context and the nature of the insight being pursued. The setting of gene network dynamic models from such frameworks involves assumptions and mathematical artifacts often ignored by the non-specialist. This article aims at providing an entry point for biologists new to the field and computer scientists not acquainted with some recent biophysically-inspired models of gene regulation. The connections promoting intuition between different abstraction levels and the role that approximations play in the modeling process are highlighted throughout the paper.
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Curcio, Luciano, Laura D'Orsi, and Andrea De Gaetano. "Seven Mathematical Models of Hemorrhagic Shock." Computational and Mathematical Methods in Medicine 2021 (June 3, 2021): 1–34. http://dx.doi.org/10.1155/2021/6640638.

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Although mathematical modelling of pressure-flow dynamics in the cardiocirculatory system has a lengthy history, readily finding the appropriate model for the experimental situation at hand is often a challenge in and of itself. An ideal model would be relatively easy to use and reliable, besides being ethically acceptable. Furthermore, it would address the pathogenic features of the cardiovascular disease that one seeks to investigate. No universally valid model has been identified, even though a host of models have been developed. The object of this review is to describe several of the most relevant mathematical models of the cardiovascular system: the physiological features of circulatory dynamics are explained, and their mathematical formulations are compared. The focus is on the whole-body scale mathematical models that portray the subject’s responses to hypovolemic shock. The models contained in this review differ from one another, both in the mathematical methodology adopted and in the physiological or pathological aspects described. Each model, in fact, mimics different aspects of cardiocirculatory physiology and pathophysiology to varying degrees: some of these models are geared to better understand the mechanisms of vascular hemodynamics, whereas others focus more on disease states so as to develop therapeutic standards of care or to test novel approaches. We will elucidate key issues involved in the modeling of cardiovascular system and its control by reviewing seven of these models developed to address these specific purposes.
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Shain, Kenneth H. "Mathematical Models of Cancer Evolution and Cure." Blood 126, no. 23 (December 3, 2015): SCI—55—SCI—55. http://dx.doi.org/10.1182/blood.v126.23.sci-55.sci-55.

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You cannot cure what you do not understand. So how can mathematical modeling address this pressing issue? The advances in therapeutic success in multiple myeloma over the last decades have hinged on an an army of researchers identifying a critical genetic, epigenetic and biochemical signaling factors within of MM cells as well as the tumor microenvironment (TME). Unfortunately, despite these large scale efforts we do not yet offer our patients curative intent therapy. The inability to provide curative therapy, especially in the setting of HRMM, is characterized by evolving resistance to lines of sequential therapy as a result of alternating clonal dynamics following the failure of initial therapy to eradicate minimal residual disease (MRD). Recent results underline the importance of tumor heterogeneity, in the form of pre-existing genotypically (and phenotypically) distinct sub-populations that translate to drug-resistant phenotypes leading to treatment failure. This phenomenon of “clonal tides”, has been well characterized using contemporary molecular techniques demonstrating that clonal evolution progresses by different evolutionary patterns across patients. Thus, resistance to therapy is a consequence of Darwinian dynamics- influenced by tumor heterogeneity, genomic instability, the TME (ecosystem), and selective pressures induced by therapy. Such evolutionary principles can be analyzed and exploited by mathematical models to personalize therapeutic options for patients with MM. Currently available clinical decision support tools and physician acumen are not able to account for the shear amount of information available. Mathematical models, however, provide a critical mechanism(s) to account of the large number of aspects to help predict and manage MM- accounting for what we do not know. Models can be designed with the specific intent of characterizing intra-tumoral heterogeneity, changing ecosystems, and clinical parameters over time to create patient-specific clinical predictions much like hurricane prediction models. This can only be achieved by creating mathematical models parameterized by longitudinal data of a number of parameters. The novel application of mathematical models based on Darwinian dynamics can be imputed with data to 1) predict progression events (risk of progression to from smoldering to active MM), 2) relapse, and 3) predictions of clinical response of MM patients for the optimizing therapeutics for cure or optimal control of MM; thus, providing invaluable clinical decision support tools. Disclosures: Shain: Celgene: Consultancy , Speakers Bureau ; Amgen/Onyx: Consultancy , Speakers Bureau ; Takeda: Consultancy , Speakers Bureau ; Signal Genetics: Consultancy , Research Funding.
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Frisman, E. Ya, O. L. Zhdanova, M. P. Kulakov, G. P. Neverova, and O. L. Revutskaya. "Mathematical Modeling of Population Dynamics Based on Recurrent Equations: Results and Prospects. Part I." Biology Bulletin 48, no. 1 (January 2021): 1–15. http://dx.doi.org/10.1134/s1062359021010064.

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Abstract Approaches to modeling population dynamics using discrete-time models are described in this two-part review. The development of the scientific ideas of discrete time models, from the Malthus model to modern population models that take into account many factors affecting the structure and dynamics, is presented. The most important and interesting results of recurrent equation application to biological system analysis obtained by the authors are given. In the first part of this review, the population dynamic effects that result from density-dependent regulation of population, the age and sex structures, and the influence of external factors are considered.
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Neelagandan, Nagammal, Irene Lamberti, Hugo J. F. Carvalho, Cédric Gobet, and Felix Naef. "What determines eukaryotic translation elongation: recent molecular and quantitative analyses of protein synthesis." Open Biology 10, no. 12 (December 2020): 200292. http://dx.doi.org/10.1098/rsob.200292.

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Protein synthesis from mRNA is an energy-intensive and tightly controlled cellular process. Translation elongation is a well-coordinated, multifactorial step in translation that undergoes dynamic regulation owing to cellular state and environmental determinants. Recent studies involving genome-wide approaches have uncovered some crucial aspects of translation elongation including the mRNA itself and the nascent polypeptide chain. Additionally, these studies have fuelled quantitative and mathematical modelling of translation elongation. In this review, we provide a comprehensive overview of the key determinants of translation elongation. We discuss consequences of ribosome stalling or collision, and how the cells regulate translation in case of such events. Next, we review theoretical approaches and widely used mathematical models that have become an essential ingredient to interpret complex molecular datasets and study translation dynamics quantitatively. Finally, we review recent advances in live-cell reporter and related analysis techniques, to monitor the translation dynamics of single cells and single-mRNA molecules in real time.
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Erban, Radek. "From molecular dynamics to Brownian dynamics." Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences 470, no. 2167 (July 8, 2014): 20140036. http://dx.doi.org/10.1098/rspa.2014.0036.

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Three coarse-grained molecular dynamics (MD) models are investigated with the aim of developing and analysing multi-scale methods which use MD simulations in parts of the computational domain and (less detailed) Brownian dynamics (BD) simulations in the remainder of the domain. The first MD model is formulated in one spatial dimension. It is based on elastic collisions of heavy molecules (e.g. proteins) with light point particles (e.g. water molecules). Two three-dimensional MD models are then investigated. The obtained results are applied to a simplified model of protein binding to receptors on the cellular membrane. It is shown that modern BD simulators of intracellular processes can be used in the bulk and accurately coupled with a (more detailed) MD model of protein binding which is used close to the membrane.
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Carson, Ewart R. "The Role of Dynamic Mathematical Models." Alternatives to Laboratory Animals 13, no. 4 (June 1985): 295–98. http://dx.doi.org/10.1177/026119298501300407.

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Weron, Aleksander. "Mathematical Models for Dynamics of Molecular Processes in Living Biological Cells. A Single Particle Tracking Approach." Annales Mathematicae Silesianae 32, no. 1 (September 1, 2018): 5–41. http://dx.doi.org/10.1515/amsil-2017-0019.

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Abstract In this survey paper we present a systematic methodology of how to identify origins of fractional dynamics. We consider three models leading to it, namely fractional Brownian motion (FBM), fractional Lévy stable motion (FLSM) and autoregressive fractionally integrated moving average (ARFIMA) process. The discrete-time ARFIMA process is stationary, and when aggregated, in the limit, it converges to either FBM or FLSM. In this sense it generalizes both models. We discuss three experimental data sets related to some molecular biology problems described by single particle tracking. They are successfully resolved by means of the universal ARFIMA time series model with various noises. Even if the finer details of the estimation procedures are case specific, we hope that the suggested checklist will still have been of great use as a practical guide. In Appendices A-F we describe useful fractional dynamics identification and validation methods.
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Koelle, Katia, and David A. Rasmussen. "Rates of coalescence for common epidemiological models at equilibrium." Journal of The Royal Society Interface 9, no. 70 (September 14, 2011): 997–1007. http://dx.doi.org/10.1098/rsif.2011.0495.

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Coalescent theory provides a mathematical framework for quantitatively interpreting gene genealogies. With the increased availability of molecular sequence data, disease ecologists now regularly apply this body of theory to viral phylogenies, most commonly in attempts to reconstruct demographic histories of infected individuals and to estimate parameters such as the basic reproduction number. However, with few exceptions, the mathematical expressions at the core of coalescent theory have not been explicitly linked to the structure of epidemiological models, which are commonly used to mathematically describe the transmission dynamics of a pathogen. Here, we aim to make progress towards establishing this link by presenting a general approach for deriving a model's rate of coalescence under the assumption that the disease dynamics are at their endemic equilibrium. We apply this approach to four common families of epidemiological models: standard susceptible-infected-susceptible/susceptible-infected-recovered/susceptible-infected-recovered-susceptible models, models with individual heterogeneity in infectivity, models with an exposed but not yet infectious class and models with variable distributions of the infectious period. These results improve our understanding of how epidemiological processes shape viral genealogies, as well as how these processes affect levels of viral diversity and rates of genetic drift. Finally, we discuss how a subset of these coalescent rate expressions can be used for phylodynamic inference in non-equilibrium settings. For the ones that are limited to equilibrium conditions, we also discuss why this is the case. These results, therefore, point towards necessary future work while providing intuition on how epidemiological characteristics of the infection process impact gene genealogies.
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Dissertations / Theses on the topic "Molecular dynamics Mathematical models"

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Shepherd, Tricia D. "Models for chemical processes : activated dynamics across stochastic potentials." Diss., Georgia Institute of Technology, 2002. http://hdl.handle.net/1853/27062.

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Scholz, Timothy Theodore. "Density matrix theory of diatomic molecules." Title page, contents and summary only, 1989. http://web4.library.adelaide.edu.au/theses/09SM/09sms368.pdf.

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區逸賢 and Yat-yin Au. "Ab initio calculations: an extension of Sankey's method." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 1999. http://hub.hku.hk/bib/B31222195.

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Oguz, Cihan. "Control-oriented modeling of discrete configuration molecular scale processes applications in polymer synthesis and thin film growth /." Diss., Atlanta, Ga. : Georgia Institute of Technology, 2007. http://hdl.handle.net/1853/19867.

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Thesis (Ph.D)--Chemical Engineering, Georgia Institute of Technology, 2008.
Committee Chair: Gallivan, Martha A.; Committee Member: Hess, Dennis; Committee Member: Lee, Jay H.; Committee Member: Li, Mo; Committee Member: Ludovice, Pete.
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Quo, Chang Feng. "Reverse engineering homeostasis in molecular biological systems." Thesis, Georgia Institute of Technology, 2013. http://hdl.handle.net/1853/49144.

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This dissertation is an initial study of how modern engineering control may be applied to reverse engineer homeostasis in metabolic pathways using high-throughput biological data. This attempt to reconcile differences between engineering control and biological homeostasis from an interdisciplinary perspective is motivated not only by the observation that robust behavior in metabolic pathways resembles stabilized dynamics in controlled systems, but also by the challenges forewarned in achieving a true meeting of minds between engineers and biologists. To do this, a comparator model is developed and applied to model the effect of single-gene (SPT) overexpression on C16:0 sphingolipid de novo biosynthesis in vitro, specifically to simulate and predict potential homeostatic pathway interactions between the sphingolipid metabolites. Sphingolipid de novo biosynthesis is highly regulated because its pathway intermediates are highly bioactive. Alterations in sphingolipid synthesis, storage, and metabolism are implicated in human diseases. In addition, when variation in structure is considered, sphingolipids are one of the most diverse and complex families of biomolecules. To complete the modeling paradigm, wild type cells are defi ned as the reference that exhibits the "desired" pathway dynamics that the treated cells approach. Key model results show that the proposed modern engineering control approach using a comparator to reverse engineer homeostasis in metabolic systems is: (a) eff ective in capturing observed pathway dynamics from experimental data, with no signifi cant di fference in precision from existing models, (b) robust to potential errors in estimating state-space parameters as a result of sparse data, (c) generalizable to model other metabolic systems, as demonstrated by testing on a separate independent dataset, and (d) biologically relevant in terms of predicting steady-state feedback as a result of homeostasis that is verifi ed in literature and with additional independent data from drug dosage experiments.
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Moore, Matthew Richard. "New mathematical models for splash dynamics." Thesis, University of Oxford, 2014. http://ora.ox.ac.uk/objects/uuid:c94ff7f2-296a-4f13-b04b-e9696eda9047.

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In this thesis, we derive, extend and generalise various aspects of impact theory and splash dynamics. Our methods throughout will involve isolating small parameters in our models, which we can utilise using the language of matched asymptotics. In Chapter 1 we briefly motivate the field of impact theory and outline the structure of the thesis. In Chapter 2, we give a detailed review of classical small-deadrise water entry, Wagner theory, in both two and three dimensions, highlighting the key results that we will use in our extensions of the theory. We study oblique water entry in Chapter 3, in which we use a novel transformation to relate an oblique impact with its normal-impact counterpart. This allows us to derive a wide range of solutions to both two- and three-dimensional oblique impacts, as well as discuss the limitations and breakdown of Wagner theory. We return to vertical water-entry in Chapter 4, but introduce the air layer trapped between the impacting body and the liquid it is entering. We extend the classical theory to include this air layer and in the limit in which the density ratio between the air and liquid is sufficiently small, we derive the first-order correction to the Wagner solution due to the presence of the surrounding air. The model is presented in both two dimensions and axisymmetric geometries. In Chapter 5 we move away from Wagner theory and systematically derive a series of splash jet models in order to find possible mechanisms for phenomena seen in droplet impact and droplet spreading experiments. Our canonical model is a thin jet of liquid shot over a substrate with a thin air layer trapped between the jet and the substrate. We consider a variety of parameter regimes and investigate the stability of the jet in each regime. We then use this model as part of a growing-jet problem, in which we attempt to include effects due to the jet tip. In the final chapter we summarise the main results of the thesis and outline directions for future work.
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David, Laurent. "Modelisation des interactions electrostatiques des biomolecules en solution." Université Joseph Fourier (Grenoble), 1996. http://www.theses.fr/1996GRE10159.

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Les interactions electrostatiques jouent un role crucial dans la modelisation d'une macromolecule biologique, et particulierement dans la comprehension de l'effet du solvant sur le systeme considere. La resolution de l'equation lineaire de poisson-boltzmann (lpb) permet d'obtenir une representation de ces interactions. Plusieurs methodes resolvant cette equation (ou une approximation de cette equation) sont developpees dans le but d'etre utilisees en dynamique moleculaire. La premiere etude utilise la methode des differences finies pour discretiser le systeme et differents algorithmes mathematiques pour resoudre le systeme d'equations lineaires obtenu. Le temps de calcul reste superieur a celui d'une modelisation du solvant de facon explicite. Dans le but d'optimiser ce temps de calcul, une methode de resolution des equations aux derivees partielles, basee sur la fonctionnelle de l'energie et les fonctions de bases, est adaptee a la resolution de l'equation lpb. L'avantage majeur de cette methode est l'expression analytique du potentiel electrostatique, et par consequent de l'energie et des forces electrostatiques. L'effet du solvant peut aussi etre modelise en considerant les atomes comme des cavites dielectriques, et en exprimant le potentiel electrostatique a l'aide des multipoles. Les resultats obtenus sont tres interessants puisque le temps de calcul est nettement plus faible que pour la resolution de l'equation lpb. Cette methode est donc couplee a la dynamique moleculaire. Les methodes de representation du solvant, decrites precedemment, sont appliquees aux calculs de l'etat de protonation des residus ionisables des proteines. Les resultats obtenus sont en bon accord avec les donnees experimentales. Par ailleurs, trois dynamiques moleculaires sont realisees sur le complexe represseur 434/operateur or1 avec deux representations differentes du solvant et sur le complexe represseur 434/operateur or3 avec une representation implicite du solvant. Cette etude permet de mieux comprendre la specificite des interactions proteines/adn, ainsi que la qualite des differents modeles electrostatiques du solvant
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Stanek, Lucas James. "Deformation of a Graphene Sheet Driven by Lattice Mismatch with a Supporting Substrate." University of Akron / OhioLINK, 2018. http://rave.ohiolink.edu/etdc/view?acc_num=akron1493999094753307.

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Stekel, Dov Joseph. "Mathematical models of immune system and virus dynamics." Thesis, University of Oxford, 1997. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.364143.

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Werner, Benjamin [Verfasser]. "Mathematical models of cell population dynamics / Benjamin Werner." Lübeck : Zentrale Hochschulbibliothek Lübeck, 2014. http://d-nb.info/1052328598/34.

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Books on the topic "Molecular dynamics Mathematical models"

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Greenspan, Donald. Molecular cavity flow. Arlington: Dept. of Mathematics, University of Texas at Arlington, 1998.

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Greenspan, Donald. Molecular mechanics simulations of the three dimensional cavity problem. Arlington: Dept. of Mathematics, University of Texas at Arlington, 1999.

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Greenspan, Donald. A molecular mechanics type approach to turbulence. Arlington, Tex: Dept. of Mathematics, University of Texas at Arlington, 1997.

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From quantum to classical molecular dynamics: Reduced models and numerical analysis. Zürich, Switzerland: European Mathematical Society, 2008.

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Wang, Lichang. Molecular dynamics: Theoretical developments and applications in nanotechnology and energy. Croatia: InTech, 2012.

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Molecular gas dynamics and the direct simulation of gas flows. Oxford: Clarendon Press, 1994.

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Bird, G. A. Molecular gas dynamics and the direct simulation of gas flows. Oxford: Clarendon Press, 1998.

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Heyes, David M. The liquid state: Applications of molecular simulations. Chichester: Wiley, 1998.

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Fontaine-Vive, Fabien. From dynamics to structure and function of model bio-molecular systems. Amsterdam: IOS Press, 2007.

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Soleymani, Azita. Advanced topics in deformation and flow of dense gas-particle mixtures. Lappeenranta: Lappeenranta University of Technology, 2004.

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Book chapters on the topic "Molecular dynamics Mathematical models"

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Krause, Dorian, Konstantin Fackeldey, and Rolf Krause. "A Parallel Multiscale Simulation Toolbox for Coupling Molecular Dynamics and Finite Elements." In Singular Phenomena and Scaling in Mathematical Models, 327–46. Cham: Springer International Publishing, 2013. http://dx.doi.org/10.1007/978-3-319-00786-1_14.

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Tolstorukov, Michael Ye, and Konstantin M. Virnik. "Mathematical Model of the Nucleic Acids Conformational Transitions with Hysteresis over Hydration—Dehydration Cycle." In Computational Molecular Dynamics: Challenges, Methods, Ideas, 116–26. Berlin, Heidelberg: Springer Berlin Heidelberg, 1999. http://dx.doi.org/10.1007/978-3-642-58360-5_6.

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Mangiardi, Chris M., and R. Meyer. "Molecular-Dynamics Simulations Using Spatial Decomposition and Task-Based Parallelism." In Mathematical and Computational Approaches in Advancing Modern Science and Engineering, 133–40. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-30379-6_13.

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Kawano, Satoyuki, Tomoyuki Shiga, and Kazuhiro Nakahashi. "Mathematical Model of Interfacial Layer in Ultra-Fine Liquid Drop Based on Molecular Dynamics Simulation." In Micro Total Analysis Systems 2002, 85–87. Dordrecht: Springer Netherlands, 2002. http://dx.doi.org/10.1007/978-94-010-0295-0_28.

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Papulov, Yurii G., and Marina G. Vinogradova. "Relation of the Properties of Substances to Molecular Structure: Phenomenological Study of Substituted Methanes and Their Analogs." In Mathematical Models of Non-Linear Excitations, Transfer, Dynamics, and Control in Condensed Systems and Other Media, 399–408. Boston, MA: Springer US, 1999. http://dx.doi.org/10.1007/978-1-4615-4799-0_32.

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Varfolomeev, Sergey, Viktor Bykov, and Svetlana Tsybenova. "Kinetic modelling of processes in the cholinergic synapse. Mechanisms of functioning and control methods." In ORGANOPHOSPHORUS NEUROTOXINS, 127–39. ru: Publishing Center RIOR, 2020. http://dx.doi.org/10.29039/22_127-139.

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The kinetic model describing the dynamics of synaptic “discharge” taking into account the kinetics of the injection of the neurotransmitter into the synaptic cleft, the pH-dependence of catalytic activity of the enzyme and diffusion withdrawal of protons is proposed and studied. In the framework of the kinetic model, the functioning of the cholinergic synapse is considered. The results of mathematical modeling of changes in the level of acetylcholine, induced pH impulse, the influence of the frequency of impulse transfer and inhibition of acetylcholinesterase are presented. Physico-chemical explanation for a number of important physiological phenomena, such as neuromuscular paralysis, the molecular mechanism of neurological memory, actions of nerve poisons and toxins and Alzheimer’s disease is given.
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Varfolomeev, Sergey, Viktor Bykov, and Svetlana Tsybenova. "Kinetic modelling of processes in the cholinergic synapse. Mechanisms of functioning and control methods." In Organophosphorous Neurotoxins, 121–33. ru: Publishing Center RIOR, 2020. http://dx.doi.org/10.29039/chapter_5e4132b600e1c6.27895580.

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The kinetic model describing the dynamics of synaptic “discharge” taking into account the kinetics of the injection of the neurotransmitter into the synaptic cleft, the pH-dependence of catalytic activity of the enzyme and diffusion withdrawal of protons is proposed and studied. In the framework of the kinetic model, the functioning of the cholinergic synapse is considered. The results of mathematical modeling of changes in the level of acetylcholine, induced pH impulse, the influence of the frequency of impulse transfer and inhibition of acetylcholinesterase are presented. Physico-chemical explanation for a number of important physiological phenomena, such as neuromuscular paralysis, the molecular mechanism of neurological memory, actions of nerve poisons and toxins and Alzheimer’s disease is given.
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Michieletto, Davide. "Molecular Dynamics Models." In Springer Theses, 29–45. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-41042-5_3.

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Rubin, Andrew, and Galina Riznichenko. "Nonlinear Models of DNA Dynamics DNA dynamics." In Mathematical Biophysics, 117–38. Boston, MA: Springer US, 2013. http://dx.doi.org/10.1007/978-1-4614-8702-9_8.

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Caldwell, J., and Y. M. Ram. "Models in Dynamics and Vibration." In Mathematical Modelling, 67–141. Dordrecht: Springer Netherlands, 1999. http://dx.doi.org/10.1007/978-94-017-2201-8_3.

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Conference papers on the topic "Molecular dynamics Mathematical models"

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Pitskhelaury, S. S., K. A. Nekrasov, D. S. Borisenko, D. D. Seitov, and A. Ya Kupryazhkin. "Development of uranium nitride crystals mathematical model for molecular dynamics simulation." In THE 2ND INTERNATIONAL CONFERENCE ON PHYSICAL INSTRUMENTATION AND ADVANCED MATERIALS 2019. AIP Publishing, 2020. http://dx.doi.org/10.1063/5.0032828.

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Avakyan, L. A., A. S. Manukyan, E. V. Paramonova, A. S. Bogdan, G. S. Sukharina, E. G. Sharoyan, and L. A. Bugaev. "Reactive force-field molecular dynamic models of iron/oxide/carbon nanocomposites designed for magnetic hyperthermia." In Mathematical Biology and Bioinformatics. Pushchino: IMPB RAS - Branch of KIAM RAS, 2018. http://dx.doi.org/10.17537/icmbb18.42.

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Filippov, S. V. "Methods of working with dynamic molecular models, built in an environment of open 3D editor Blender." In Mathematical Biology and Bioinformatics. Pushchino: IMPB RAS - Branch of KIAM RAS, 2018. http://dx.doi.org/10.17537/icmbb18.62.

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Ryzhkov, Alexandr, and Yuriy Raikher. "Field-induced response of non-spherical magnetopolymersomes: Coarse-grained molecular dynamics model." In 29TH RUSSIAN CONFERENCE ON MATHEMATICAL MODELLING IN NATURAL SCIENCES. AIP Publishing, 2021. http://dx.doi.org/10.1063/5.0059529.

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Sazhin, S. S. "Droplet heating and evaporation: Hydrodynamic, kinetic and molecular dynamics models." In 11TH INTERNATIONAL CONFERENCE OF NUMERICAL ANALYSIS AND APPLIED MATHEMATICS 2013: ICNAAM 2013. AIP, 2013. http://dx.doi.org/10.1063/1.4825421.

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Filippov, S. V., and V. S. Sivozhelezov. "Method of constructing dynamic molecular models within the environment of the Blender open 3D platform exemplified by β2-adrenergic receptor." In Mathematical Biology and Bioinformatics. Pushchino: IMPB RAS - Branch of KIAM RAS, 2018. http://dx.doi.org/10.17537/icmbb18.23.

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Huzil, J. Torin, Siv Sivaloganathan, Mohammad Kohandel, Marianna Foldvari, Ilias Kotsireas, Roderick Melnik, and Brian West. "Modeling the Effects of Lipid Composition on Stratum Corneum Bilayers Using Molecular Dynamics Simulations." In ADVANCES IN MATHEMATICAL AND COMPUTATIONAL METHODS: ADDRESSING MODERN CHALLENGES OF SCIENCE, TECHNOLOGY, AND SOCIETY. AIP, 2011. http://dx.doi.org/10.1063/1.3663488.

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Grevtsev, Aleksandr, Karine Abgaryan, and Dmitriy Bajanov. "DEVELOPMENT OF A FUNCTIONAL BASED ON TERSOFF POTENTIAL TO MODEL THE PROPERTIES OF OXIDES." In Mathematical modeling in materials science of electronic component. LLC MAKS Press, 2020. http://dx.doi.org/10.29003/m1522.mmmsec-2020/71-74.

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Allam, Sushmita L., Jean-Marie C. Bouteiller, Renaud Greget, Serge Bischoff, Michel Baudry, and Theodore W. Berger. "EONS Synaptic Modeling Platform: Exploration of Mechanisms Regulating Information Processing in the CNS and Application to Drug Discovery." In ASME 2008 3rd Frontiers in Biomedical Devices Conference. ASMEDC, 2008. http://dx.doi.org/10.1115/biomed2008-38095.

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EONS modeling platform is a resourceful learning and research tool to study the mechanisms underlying the non-linear dynamics of synaptic transmission with the aid of mathematical models. Mathematical modeling of information processing in CNS pathways, in particular modeling of molecular events and synaptic dynamics, have not been extensively developed owing to the complex computations involved in integrating a multitude of parameters. In this paper, we discuss the development of a strategy to adapt the EONS synaptic modeling platform to a multi-node environment using a parallel computational framework to compute data intensive long simulations in a shorter time frame. We describe how this strategy can be applied to (i) determine the optimal values of the numerous parameters required for fitting experimental data, (ii) determine the impact of all parameters on various aspects of synaptic transmission (under normal conditions or conditions mimicking pathological conditions) and (iii) study the effects of exogenous molecules on both healthy and pathological synaptic models.
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Zucca, Alessandro, Daniele L. Marchisio, Antonello A. Barresi, and Giancarlo Baldi. "Mathematical Modelling of Particle Formation in Combustion Processes." In ASME 8th Biennial Conference on Engineering Systems Design and Analysis. ASMEDC, 2006. http://dx.doi.org/10.1115/esda2006-95407.

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In recent years the problem of studying particle formation and evolution in turbulent flames has become increasingly important, for both environmental and technological reasons. Information on particle size and morphology is often required, since these characteristics largely influence the effects of particulate matter on human health and global climate in the case of soot. A mathematical model able to describe the evolution of these particulate systems must solve the population balance equation within a Computational Fluid Dynamics (CFD) code that predicts the temperature, composition and velocity fields of the flame. In this work, the recently proposed Direct Quadrature Method of Moments (DQMOM) is applied to the study of soot formation in turbulent non-premixed flames. The model takes into account nucleation, molecular growth, oxidation and aggregation of soot particles; simplified kinetic rates are employed, while velocity and scalar fields are computed by simulations based on the solution of the Reynolds Averaged Navier Stokes (RANS) equations. Different population balance formulations are implemented and compared and results show that DQMOM is a suitable modelling tool; comparison of predictions with experimental data shows that the model accurately describes the morphological properties of soot aggregates.
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Reports on the topic "Molecular dynamics Mathematical models"

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Tucker-Blackmon, Angelicque. Engagement in Engineering Pathways “E-PATH” An Initiative to Retain Non-Traditional Students in Engineering Year Three Summative External Evaluation Report. Innovative Learning Center, LLC, July 2020. http://dx.doi.org/10.52012/tyob9090.

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The summative external evaluation report described the program's impact on faculty and students participating in recitation sessions and active teaching professional development sessions over two years. Student persistence and retention in engineering courses continue to be a challenge in undergraduate education, especially for students underrepresented in engineering disciplines. The program's goal was to use peer-facilitated instruction in core engineering courses known to have high attrition rates to retain underrepresented students, especially women, in engineering to diversify and broaden engineering participation. Knowledge generated around using peer-facilitated instruction at two-year colleges can improve underrepresented students' success and participation in engineering across a broad range of institutions. Students in the program participated in peer-facilitated recitation sessions linked to fundamental engineering courses, such as engineering analysis, statics, and dynamics. These courses have the highest failure rate among women and underrepresented minority students. As a mixed-methods evaluation study, student engagement was measured as students' comfort with asking questions, collaboration with peers, and applying mathematics concepts. SPSS was used to analyze pre-and post-surveys for statistical significance. Qualitative data were collected through classroom observations and focus group sessions with recitation leaders. Semi-structured interviews were conducted with faculty members and students to understand their experiences in the program. Findings revealed that women students had marginalization and intimidation perceptions primarily from courses with significantly more men than women. However, they shared numerous strategies that could support them towards success through the engineering pathway. Women and underrepresented students perceived that they did not have a network of peers and faculty as role models to identify within engineering disciplines. The recitation sessions had a positive social impact on Hispanic women. As opportunities to collaborate increased, Hispanic womens' social engagement was expected to increase. This social engagement level has already been predicted to increase women students' persistence and retention in engineering and result in them not leaving the engineering pathway. An analysis of quantitative survey data from students in the three engineering courses revealed a significant effect of race and ethnicity for comfort in asking questions in class, collaborating with peers outside the classroom, and applying mathematical concepts. Further examination of this effect for comfort with asking questions in class revealed that comfort asking questions was driven by one or two extreme post-test scores of Asian students. A follow-up ANOVA for this item revealed that Asian women reported feeling excluded in the classroom. However, it was difficult to determine whether these differences are stable given the small sample size for students identifying as Asian. Furthermore, gender differences were significant for comfort in communicating with professors and peers. Overall, women reported less comfort communicating with their professors than men. Results from student metrics will inform faculty professional development efforts to increase faculty support and maximize student engagement, persistence, and retention in engineering courses at community colleges. Summative results from this project could inform the national STEM community about recitation support to further improve undergraduate engineering learning and educational research.
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