Książki na temat „Kinetic data”

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1

Saenger, W., red. Spectroscopic and Kinetic Data. Physical Data I. Berlin/Heidelberg: Springer-Verlag, 1990. http://dx.doi.org/10.1007/b34251.

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2

Cornish-Bowden, Athel. Analysis of enzyme kinetic data. Oxford: Oxford University Press, 1995.

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3

Westley, Francis. Compilation of chemical Kinetic data for combustion chemistry. Washington: National Bureau of Standards, 1987.

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4

Westley, Francis. Compilation of chemical kinetic data for combustion chemistry. Gaithersburg, MD: U.S. Dept. of Commerce, National Bureau of Standards, 1987.

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5

Westley, Francis. Compilation of chemical kinetic data for combustion chemistry. Washington: U.S. Dept. of Commerce, National Bureau of Standards, 1987.

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6

F, Burgess D. R., i National Institute of Standards and Technology (U.S.), red. Thermochemical and chemical kinetic data for fluorinated hydrocarbons. Gaithersburg, MD: U.S. Dept. of Commerce, Technology Administration, National Institute of Standards and Technology, 1995.

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7

Westley, Francis. Compilation of chemical kinetic data for combustion chemistry. Gaithersburg, MD: U.S. Dept. of Commerce, National Bureau of Standards, 1987.

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8

F, Burgess D. R., i National Institute of Standards and Technology (U.S.), red. Thermochemical and chemical kinetic data for fluorinated hydrocarbons. Gaithersburg, MD: U.S. Dept. of Commerce, Technology Administration, National Institute of Standards and Technology, 1995.

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9

F, Burgess D. R., i National Institute of Standards and Technology (U.S.), red. Thermochemical and chemical kinetic data for fluorinated hydrocarbons. Gaithersburg, MD: U.S. Dept. of Commerce, Technology Administration, National Institute of Standards and Technology, 1995.

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10

United States. National Aeronautics and Space Administration., red. Calculation of kinetic rate constants from thermodynamic data. [Washington, DC]: National Aeronautics and Space Administration, 1995.

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11

Ward, Thomas E. Kinetic data extraction and analysis system for human gait. Dublin: University College Dublin, 1996.

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12

Sherlock, Elizabeth Jane. Evaluation of static and kinetic prediction test data and comparison with field monitoring data. Ottawa, ON: CANMET, 1995.

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13

J, Fuhrman S., Penko P. F i United States. National Aeronautics and Space Administration., red. Kinetic theory model predictions compared with low-thrust axisymmetric nozzle plume data. [Washington, DC: National Aeronautics and Space Administration, 1993.

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14

Skinner, F. Interpretation of ultimate biochemical oxygen demand data via kinetic curve extrapolation models. Vegreville, Alta: Environmental Technology Division, Alberta Environmental Centre, 1990.

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15

Paneth, Piotr, i Agnieszka Dybala-Defratyka. Kinetics and dynamics: From nano- to bio-scale. Dordrecht: Springer, 2010.

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16

Cobelli, Claudio. Tracer kinetics in biomedical research: From data to model. New York: Kluwer Academic/Plenum, 2000.

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17

C. C. J. M. Tiberius. Recursive data processing for kinematic GPS surveying. Delft: Nederlandse Commissie Voor Geodesie, 1998.

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18

B, DeMore W., NASA Panel for Data Evaluation. i Jet Propulsion Laboratory (U.S.), red. Chemical kinetics and photochemical data for use in stratospheric modeling. Pasadena, Calif: National Aeronautics and Space Administration, Jet Propulsion Laboratory, California Institute of Technology, 1992.

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19

S, Morozova N., Slobodi͡a︡n I. A i Fiziko-tekhnicheskiĭ institut im. A.F. Ioffe., red. Modelirovanie na ĖVM kinetiki defektov v kristallakh: Tematicheskiĭ sbornik. Leningrad: FTI, 1985.

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20

B, DeMore W., i Jet Propulsion Laboratory (U.S.), red. Chemical kinetics and photochemical data for use in stratospheric modeling: Evaluation number 11. Pasadena, Calif: National Aeronautics and Space Administration, Jet Propulsion Laboratory, California Institute of Technology, 1994.

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21

NATO Advanced Research Workshop on Supercomputer Algorithms for Reactivity, Dynamics, and Kinetics of Small Molecules (1988 Colombella, Italy). Supercomputer algorithms for reactivity, dynamics, and kinetics of small molecules. Dordrecht: Kluwer Academic Publishers, 1989.

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22

U.S. Nuclear Regulatory Commission. Office of Nuclear Regulatory Research. i Central Electricity Research Laboratories, red. Analysis of LOBI test BLO2 (three percent cold leg break) with RELAP5 code. Washington, DC: Office of Nuclear Regulatory Research, U.S. Nuclear Regulatory Commission, 1992.

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23

Prinz, Heino. Numerical methods for the life scientist: Binding and enzyme kinetics calculated with GNU Octave and MATLAB. Heidelberg: Springer, 2011.

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24

Radhakrishnan, Krishnan. LSENS: The NASA Lewis kinetics and sensitivity analysis code. [Washington, D.C: National Aeronautics and Space Administration, Scientific and Technical Information Program Office ; aHanover, Md., 2000.

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25

Gadek, I͡A. Proverka trekhmernoĭ neĭtronno-kineticheskoĭ programmy HEXDYN3D s pomoshchʹi͡u II. ėtapa ėksperimentov prostranstvenno zavisimoĭ kinetiki na reaktore LR-O: [otchet, Rzhezh, noi͡abrʹ, 1988 g.]. Rzhezh: Ústav jaderného v́yzkumu Řež, Informační středisko, 1988.

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26

A, Bittker David, i United States. National Aeronautics and Space Administration. Scientific and Technical Information Program., red. LSENS: A general chemical kinetics and sensitivity analysis code for homogeneous gas-phase reactions. [Washington, DC]: National Aeronautics and Space Administration, Office of Management, Scientific and Technical Information Program, 1994.

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27

U.S. Nuclear Regulatory Commission., red. Assessment of RELAP5/MOD 2, cycle 36, against FIX-II split break experiment no. 3051. Washington, D.C: U.S. Nuclear Regulatory Commission, 1986.

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28

Eriksson, J. Assessment of RELAP5/MOD 2, cycle 36, against FIX-II split break experiment no. 3027. Washington, D.C: U.S. Nuclear Regulatory Commission, 1986.

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29

Eriksson, J. Assessment of RELAP5/MOD 2, cycle 36, against FIX-II split break experiment no. 3027. Washington, D.C: U.S. Nuclear Regulatory Commission, 1986.

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30

Rosdahl, Ö. Assessment of RELAP5/MOD 2 against critical flow data from Marviken tests JIT 11 and CFT 21. Washington, D.C: U.S. Nuclear Regulatory Commission, 1986.

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31

Rosdahl, Ö. Assessment of RELAP5/MOD 2 against critical flow data from Marviken tests JIT 11 and CFT 21. Washington, D.C: U.S. Nuclear Regulatory Commission, 1986.

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32

Rosdahl, Ö. Assessment of RELAP5/MOD 2 against critical flow data from Marviken tests JIT 11 and CFT 21. Washington, D.C: U.S. Nuclear Regulatory Commission, 1986.

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33

Aerojet TechSystems Company (U.S.) i George C. Marshall Space Flight Center., red. Carbon deposition model for oxygen-hydrocarbon combustion: Task VI, data analysis and formulation of an empirical model. Sacramento, Calif: Aerojet Techsystems Co., 1990.

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34

United States. National Aeronautics and Space Administration., red. Methodology issues concerning the accuracy of kinematic data collection and analysis using the Ariel performance analysis system. [Washington, DC: National Aeronautics and Space Administration, 1992.

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35

Rosdahl, Ö. Assessment of RELAP5/MOD 2 against Marviken jet impingement test 11 level swell. Washington, D.C: U.S. Nuclear Regulatory Commission, Office of Nuclear Regulatory Research, 1986.

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36

Rosdahl, Ö. Assessment of RELAP5/MOD 2 against Marviken jet impingement test 11 level swell. Washington, D.C: U.S. Nuclear Regulatory Commission, Office of Nuclear Regulatory Research, 1986.

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37

Nikravesh, Parviz E. Computer-aided analysis of mechanical systems. Englewood Cliffs: Prentice-Hall, 1988.

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38

Brady, Nicholas William. Investigation of Lithium Ion Battery Electrodes: Using Mathematical Models Augmented with Data Science to Understand Surface Layer Formation, Mass Transport, Electrochemical Kinetics, and Chemical Phase Change. [New York, N.Y.?]: [publisher not identified], 2019.

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39

Leonovich, Sergey, Evgeniy Shalyy, Elena Polonina, Elena Sadovskaya, Lev Kim i Valentin Dorkin. Durability of port reinforced concrete structures (Far East and Sakhalin). ru: INFRA-M Academic Publishing LLC., 2021. http://dx.doi.org/10.12737/1816638.

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Streszczenie:
Section I of the monograph is devoted to an urgent problem - forecasting the durability of port reinforced concrete structures, the destruction of which is associated with corrosion of steel reinforcement caused by chloride aggression and carbonation of concrete. The analysis of models for calculating the service life of structures and experimental data is carried out, the life cycles for the main degradation processes in concrete and reinforcement, the periods of initiation and propagation of corrosion are considered, the influence of environmental factors (temperature, humidity) and the quality of concrete (In/C, cement consumption, diffusion coefficient) on the kinetics of chloride penetration and the movement of the carbonation front is taken into account. Probabilistic models of basic variables are considered, the limiting states of port reinforced concrete structures for the durability of reinforced concrete structures based on the reliability coefficient for service life are formulated. Sections II and III describe modern methods of restoration and restoration of reinforced concrete port structures subjected to corrosion destruction using nanofibrobeton. The concept of multilevel reinforcement has been implemented. Methods of experimental fracture mechanics were used to evaluate the joint work of exploited concrete and reinforcement nanofibre concrete. It is intended for scientific and engineering staff of universities, research and design organizations.
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40

Korn, Granino A. Interactive dynamic-system simulation. Wyd. 2. Boca Raton, FL: CRC Press, 2011.

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41

Swinbourne, E. S. Analysis of Kinetic Data. Springer, 2012.

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42

Swinbourne, E. S. Analysis of Kinetic Data. Springer, 2013.

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43

Chappell, Michael, Bradley MacIntosh i Thomas Okell. Kinetic Modeling. Oxford University Press, 2017. http://dx.doi.org/10.1093/oso/9780198793816.003.0004.

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The quantification of perfusion from arterial spin labeling (ASL) perfusion MRI data relies upon the principles of tracer kinetics. This chapter first outlines the simplest form of a tracer kinetic model that can be applied to ASL data, before exploring variations on this model that can be applied to extract other hemodynamic information such as arterial transit time. Finally, the chapter examines how tracer kinetic models are used with data to estimate perfusion parameters, including the use of model fitting and Bayesian inference.
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44

Calculation of kinetic rate constants from thermodynamic data. [Washington, DC]: National Aeronautics and Space Administration, 1995.

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45

Simplified half-life methods for the analysis of kinetic data. [Moffett Field, Calif.?]: Research Institute for Advanced Computer Science, NASA Ames Research Center, 1988.

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46

Simplified half-life methods for the analysis of kinetic data. [Moffett Field, Calif.?]: Research Institute for Advanced Computer Science, NASA Ames Research Center, 1988.

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47

Chung, Hyung-Keun. Microcomputer-based fluorometric kinetic determination of ascorbic acid and flow injection analysis methods for interference correction and kinetic determinations based on the peak profile. 1989.

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48

Chung, Hyung-Keun. Microcomputer-based fluorometric kinetic determination of ascorbic acid and flow injection analysis methods for interference correction and kinetic determinations based on the peak profile. 1989.

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49

Endrenyi, Laszlo. Kinetic Data Analysis: Design and Analysis of Enzyme and Pharmacokinetic Experiments. Springer, 2011.

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50

Henderson, Daniel A., R. J. Boys, Carole J. Proctor i Darren J. Wilkinson. Linking systems biology models to data: A stochastic kinetic model of p53 oscillations. Redaktorzy Anthony O'Hagan i Mike West. Oxford University Press, 2018. http://dx.doi.org/10.1093/oxfordhb/9780198703174.013.7.

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This article discusses the use of a stochastic kinetic model to study protein level oscillations in single living cancer cells, using the p53 and Mdm2 proteins as examples. It describes the refinement of a dynamic stochastic process model of the cellular response to DNA damage and compares this model to time course data on the levels of p53 and Mdm2. The article first provides a biological background on p53 and Mdm2 before explaining how the stochastic kinetic model is constructed. It then introduces the stochastic kinetic model and links it to the data and goes on to apply sophisticated MCMC methods to compute posterior distributions. The results demonstrate that it is possible to develop computationally intensive Markov chain Monte Carlo (MCMC) methods for conducting a Bayesian analysis of an intra-cellular stochastic systems biology model using single-cell time course data.
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