Comparison of selected mathematical functions for the analysis of growth behavior of items and physical interpretation of Avrami-Weibull function
Abstract
AbstractEmpirical data of sigmoidal-shaped y(t) growth behavior of different types of items, such as papers and citations earned by individual and all successively published papers of selected top-cited authors, germination of tomato seeds and three different bacteria, are analyzed and compared by Avrami-Weibull, Verhulst (logistic) and Gompertz functions. It was found that: (1) Avrami-Weibull function describes different types of the data better than Gompertz and Verhulst funtions, and (2), in comparison with Verhulst and Gompertz functions, Avrami-Weibull function, expressed in the form: y(t)/ymax = 1-exp[(t/Θ)q] (where ymax is the maximum value of y(t) when t→∞, and Θ and q are constants), is equally very versatile in explaining the generation rate dy(t)/dt of items in terms of its parameters Θ and q. Using the basic concepts involved in the derivation of Avrami-Weibull function for overall crystallization from melt and supersaturated solution, the growth behavior of cumulative number y(t) of items produced at time t by individual (simple) sources and collectives or groups of simple sources (i.e. complex or composite sources) is presented. Comparison of the process of receiving of citations by papers with the processes of occurrence of chemical reactions and crystallization of solid phases from melts and supersaturated solutions shows that this process is similar to that of overall crystallization of solid phases from melts and solutions. Analysis of growth of citations using Avrami-Weibull function to individual papers published by different authors shows that 1 < q < 4 for most cases. This suggests that the process of citations to individual articles is mainly determined by progressive nucleation mode involving both diffusion and integration of published knowledge.
Supporting Agencies
Keywords:
Avrami-Weibull function; Gompertz and Verhulst functions; Growth behavior of items; Citation analysisReferences
D.D.S. Price, Little Science, Big Science. Columbia Uni-versity Press, New York & London, 1963.
DOI: https://doi.org/10.7312/pric91844
Google Scholar
L. Egghe, I.K. Ravichandra Rao, Classification of growth models based on growth rates and its applications, Scientometrics 25 (1992) 5-46.
DOI: https://doi.org/10.1007/BF02016845
Google Scholar
B.M., Gupta, L. Sharma, C.R. Karisiddappa, Modeling the growth of papers in a scientific speciality, Scientometrics 33(2), (1995) 187-201.
DOI: https://doi.org/10.1007/BF02020568
Google Scholar
B.M., Gupta, S. Kumar, S.L. Sangam, C.R. Karisiddappa, Modeling the growth of social science literature, Scientometrics 53(1), (2002) 161-164.
DOI: https://doi.org/10.1023/A:1014844222898
Google Scholar
I.K. Ravichandra Rao, D. Srivastava, Growth of journals, articles and authors in malaria research, Journal of Informetrics 4(1), (2010) 249-256.
DOI: https://doi.org/10.1016/j.joi.2009.12.003
Google Scholar
C.-Y. Wong, K.-L. Goh, Growth behavior of publications and patents: A comparative study on selected Asian economies, Journal of Informetrics 4(2), (2010) 460-474.
DOI: https://doi.org/10.1016/j.joi.2010.04.002
Google Scholar
K. Sangwal, Progressive nucleation mechanism and its application to the growth of journals, articles and authors in scientific fields, Journal of Informetrics 5(4), (2011) 529-536.
DOI: https://doi.org/10.1016/j.joi.2011.04.005
Google Scholar
K. Sangwal, Application of progressive nucleation mechanism for the citation behavior of individual papers of different authors,. Scientometrics 92(2), (2012) 643-655.
DOI: https://doi.org/10.1007/s11192-011-0564-x
Google Scholar
Q.L. Burrell, The nth-citation distribution and obsoles-cence, Scientometrics 53(3), (2002) 309-323.
DOI: https://doi.org/10.1023/A:1014816911511
Google Scholar
Q.L. Burrell, Hirsch’s h-index: A stochastic model, Jour-nal of Informetrics 1(1), (2007) 16-25.
DOI: https://doi.org/10.1016/j.joi.2006.07.001
Google Scholar
Q.L. Burrell, On the h-index, the size of the Hirsch core and Jin’s A-index, Journal of Informetrics 1(2), (2007) 170-177.
DOI: https://doi.org/10.1016/j.joi.2007.01.003
Google Scholar
Q.L. Burrell, The individual author’s publicationcitation process: theory and practice, Scientometrics 98(1), (2014) 725-742.
DOI: https://doi.org/10.1007/s11192-013-1018-4
Google Scholar
W. Glänzel, On the possibility and reliability of predictions based on stochastic citation processes, Scientometrics 40(3), (1997) 481-492.
DOI: https://doi.org/10.1007/BF02459295
Google Scholar
W. Glänzel, A. Schubert, Predictive aspects of a stochastic model for citation processes, Information Processing and Management 31(1), (1995) 69-80.
DOI: https://doi.org/10.1016/0306-4573(95)80007-G
Google Scholar
X. Zheng, Predicting publication productivity for re-searchers: A piecewise Poisson model, Journal of Informetrics 14(3), (2020) 101065.
DOI: https://doi.org/10.1016/j.joi.2020.101065
Google Scholar
S.Nadarajan, S. Kotz, Models for citation behavior, Scientometrics 72(2), (2007) 291-305.
DOI: https://doi.org/10.1007/s11192-007-1717-9
Google Scholar
M.V. Simkin, V.P. Roychowdhury, A mathematical theory of citing, Journal of American Society for Infor-mation Science and Technology 58(11), (2007) 1661-1673.
DOI: https://doi.org/10.1002/asi.20653
Google Scholar
J.E. Hirsch, An index to quantify an individual’s scientific research output, Proceedings of the National Academy of Sciences of the USA 102(46), (2005), 16569-16572.
DOI: https://doi.org/10.1073/pnas.0507655102
Google Scholar
A. Fernandez, C. Salmeron, P.S. Fernandez, A. Martinez, Application of a frequency distribution model to describe the thermal inactivation of two strains of Becillus cereus, Trends in Food Science and Technology 10(4-5), (1999) 158-162.
DOI: https://doi.org/10.1016/S0924-2244(99)00037-0
Google Scholar
J.-C. Augustin, A. Brouillaud-Delattre, L. Rosso, V. Carlier, Significance of Inoculum size in the lag time of Listeria monocytogenes, Applied and Environmental Mi-crobiology 66(4), (2000) 1706-1710.
DOI: https://doi.org/10.1128/AEM.66.4.1706-1710.2000
Google Scholar
M. Valero, S. Leontidis, P.S. Fernandez, A. Martinez, M.C. Salmeron, Growth of Bacillus cereus in natural and acidified carrot substrates over the temperature range 5-30oC, Food Microbiology 17(6), (2000) 605-612.
DOI: https://doi.org/10.1006/fmic.2000.0352
Google Scholar
H. Fujizawa, A. Kai, S. Morozumi, A new logistic model for bacterial growth, Journal of the Food Hygienic Society of Japan 44(3), (2003) 155-160.
DOI: https://doi.org/10.3358/shokueishi.44.155
Google Scholar
H. Fujizawa, A. Kai, S. Morozumi, A new logistic model for Escherichia coli growth at constant and dynamic tem-peratures. Food Microbiology 21(5), (2004) 501-509.
DOI: https://doi.org/10.1016/j.fm.2004.01.007
Google Scholar
M.G. Corradini, M. Peleg, A Weibullian model for microbial injury and mortality, International Journal of Food Microbiology 119(3), (2007) 319-328.
DOI: https://doi.org/10.1016/j.ijfoodmicro.2007.08.035
Google Scholar
M. Peleg, M.G. Corradini, M.D. Normand, The logistic (Verhulst) model for sigmoidal microbial growth curves revisited, Food Research International, 40(7), (2007) 808-818.
DOI: https://doi.org/10.1016/j.foodres.2007.01.012
Google Scholar
G.T., Yates, T. Smotzer, On the phase lag and initial decline of microbial growth curves, Journal of Theoretical Biology 244(3), (2007) 511-517.
DOI: https://doi.org/10.1016/j.jtbi.2006.08.017
Google Scholar
G.M.F., Aragao, M.G., Corradini, M.D., Nonmand, M. Peleg, Evaluation of the Weibull and log normal distribu-tion functions as survival models of Escherichia coli under isothermal and non-isothermal conditions, International Journal of Food Microbiology 119(3), (2007) 243-257.
DOI: https://doi.org/10.1016/j.ijfoodmicro.2007.08.004
Google Scholar
M.Y. Li, X.M. Sun, G.M. Zhao, X.Q. Huang, J.W. Zhang, W. Tian, Q.H. Zhang, Comparison of mathemati-cal models of lactic acid bacteria growth in vacuum-packaged raw beef stored at different temperatures, Jour-nal of Food Science 78(4), (2012) M600-M604.
DOI: https://doi.org/10.1111/j.1750-3841.2012.02995.x
Google Scholar
J. Kowalik, A. Lobacz, Development of a predictive model for describing the growth of Yersinia enterocolitica in Camembert-type cheese, International Journal of Food Science and Technology 50(3), (2015) 811-818.
DOI: https://doi.org/10.1111/ijfs.12715
Google Scholar
A. Lobacz, J. Kowalik, A predictive model for Listeria monocytogenes in UHT diary products with various fat content during storage, Journal of Food Safety 35(1), (2015) 119-277.
DOI: https://doi.org/10.1111/jfs.12163
Google Scholar
S. Sakanoue, Extended logistic model for growth of single-species population, Ecological Modelling 205(1-2), (2007) 159-168.
DOI: https://doi.org/10.1016/j.ecolmodel.2007.02.013
Google Scholar
H. Krug, G. Taubert, Practical use of the logistic law in experimental tumor-growth, Archiv für Geschwulstforsch 55(4), (1985) 235-244.
Google Scholar
U. Foryś, A. Marciniak-Czochra, Logistic equations in tumour growth modelling, International Journal of Ap-plied Mathematical Computation Science 13(3), (2003) 317-325.
Google Scholar
B. Gładyszewska, Ocena wpływu przedsiewnej laserowej biostymulacji nasion pomidorów na proces ich kiełkowania (Evaluation of presowing laser biostymulation of tomato seeds on the process of their germination), PhD thesis, Agriculture Academy, Lublin (1998).
Google Scholar
W. Kloek, P. Walstra, T. van Vliet. Crystallization kinetics of fully hydrogenated palm oil in sunflower oil mixtures, Journal of American Oil Chemistry Society 77(4), (2000) 389-398.
DOI: https://doi.org/10.1007/s11746-000-0063-z
Google Scholar
S. Padar, S.A.K. Jeelani, E.J. Windhab, Crystallization kinetics of cocoa fat systems: Experiments and modeling, Journal of American Oil Chemists’ Society 85(12), (2009) 1115-1126.
DOI: https://doi.org/10.1007/s11746-008-1312-0
Google Scholar
K. Sangwal, K. Sato, Nucleation and crystallization kinet-ics of fats. In: A.G. Marangoni (Editor), Structure-function analysis of edible fats, AOCS Press, Urbana, 2012, Chapter 2, pp. 25-78.
Google Scholar
L.M. Cunha, F.A.R. Oliveira, J.C. Oliveira, Optimal experimental design for estimating the kinetic parameters of processes described by the Weibull probability distri-bution function, Journal of Food Engineering 37(1), (1998) 175-191.
DOI: https://doi.org/10.1016/S0260-8774(98)00085-5
Google Scholar
K. Sangwal, Growth dynamics of citations of cumulative papers of individual authors according to progressive nu-cleation mechanism: concept of citation acceleration, In-formation Processing and Management 49(4), (2013) 757-772.
DOI: https://doi.org/10.1016/j.ipm.2013.01.003
Google Scholar
K. Sangwal, On the growth dynamics of citations of articles by some Nobel Prize winners, Journal of Informetrics 9 (2015) 466-476.
DOI: https://doi.org/10.1016/j.joi.2015.03.004
Google Scholar
M.F. Brilhante, M.I. Gomes, D. Pestana, Extensions of Verhulst model in population dynamics and extremes. Chaotic Modeling and Simulation (CMSIM), Issue 4, (2012) 575-591.
Google Scholar
T. Chatterjee, B.K. Chatterjee, D. Majumdar, P. Chakrabarti, Antibacterial effect of silver nanoparticles and the modeling of bacterial growth kinetics using a modified Gompertz model, Biochimica et Biophysica Acta 185(2), (2015) 299-306.
DOI: https://doi.org/10.1016/j.bbagen.2014.10.022
Google Scholar
A. El-Gohary, A. Alshamrani, A.N. Al-Otaibi, The gen-eralized Gompertz distribution, Applied Mathematical Modelling 37(1), (2013) 13-24.
DOI: https://doi.org/10.1016/j.apm.2011.05.017
Google Scholar
A.A. Jafari, A. Tahmasebi, M. Alizadeh, The beta-Gompertz distribution, Revista Colombiana de Estadistica, 37(1), (2014) 139-156.
DOI: https://doi.org/10.15446/rce.v37n1.44363
Google Scholar
K.Y. Chuang, Y.S. Ho, Bibliometric profile of top-cited single-author articles in the Science Citation Index Ex-panded, Journal of Informetrics 8 (2014) 951-962.
DOI: https://doi.org/10.1016/j.joi.2014.09.008
Google Scholar
G. Leubner-Metzger, Functions and regulation of -1,3-glucanases during seed germination, dormancy release and after-ripening, Seed Science Research 13(1), (2003) 17–34.
DOI: https://doi.org/10.1079/SSR2002121
Google Scholar
K. Weitbrecht, K, Müller, G. Leubner-Metzger, First off the mark: Early seed germination, Journal of Experimental Botany 62(10), (2011) 3289–3309.
DOI: https://doi.org/10.1093/jxb/err030
Google Scholar
M.A. Lopez-Manchado, J. Biagiotti, L. Torre, J.M. Kenny, Effects of reinforcing fibers on the crystallzation of polypropylene, Polymer Engineering Science 40(10), (2000) 2194-2204.
DOI: https://doi.org/10.1002/pen.11351
Google Scholar
D.F. Eggers, N.W. Gregory, G.D. Halsey, & B.S. Rabinovitch, Physical Chemistry. Wiley, New York, 1964.
Google Scholar
J.W. Atkinson, An Introduction to Motivation. Van Nostrand, Princeton, 1964.
Google Scholar
P. Vinkler, A quasi-quantitative citation model, Scientometrics 12 (1987) 47–72.
DOI: https://doi.org/10.1007/BF02016689
Google Scholar
P. Vinkler, Comparative investigation of frequency and strength of motives towards referencing: The reference threshold model, Scientometrics 43(1) (1998) 107-127.
DOI: https://doi.org/10.1007/BF02458400
Google Scholar
K. Sangwal, Progressive nucleation mechanism for the growth behavior of items and its application to cumulative papers and citations of individual authors, Scientometrics 92(2), (2012) 575-591.
DOI: https://doi.org/10.1007/s11192-011-0610-8
Google Scholar
K. Sangwal, Czochralski method of crystal growth in the scientific literature: An informetric study, Acta Physica Polonica B 124(2), (2013) 173-180.
DOI: https://doi.org/10.12693/APhysPolA.124.173
Google Scholar
W. Weibull, A statistical distribution function of wide applicability, Journal of Applied Mechanics 18(3), (1951) 293–297.
DOI: https://doi.org/10.1115/1.4010337
Google Scholar
Y.X. Liu, R. Rousseau, Citation analysis and the devel-opment of science: A case study using articles by some Nobel Prize winners, Journal of American Society for In-formation Science and Technogy 65(2), (2014) 281-289.
DOI: https://doi.org/10.1002/asi.22978
Google Scholar
K. Sangwal, On the growth of citations of publication output of individual authors, Journal of Informetrics 5(4), (2011) 554-564.
DOI: https://doi.org/10.1016/j.joi.2011.04.007
Google Scholar
K. Sangwal, On the growth behavior of yearly citations of cumulative papers of individual authors, Journal of Scientometric Research 2(1), (2013) 30-36.
DOI: https://doi.org/10.4103/2320-0057.115878
Google Scholar
Y.-S. Ho, M. Kahn, A bibliometric study of highly cited reviews in the Science Citation Index ExpandedTM, Jour-nal of American Society for Information Science and Technology 65(2), (2014) 372-385.
DOI: https://doi.org/10.1002/asi.22974
Google Scholar
E.S. Aversa, Citation patterns of highly cited papers and their relationship to literature aging: A study of the work-ing literature, Scientometrics 7(3-6), (1985) 383-389.
DOI: https://doi.org/10.1007/BF02017156
Google Scholar
A. Avramescu, Actuality and obsolescence of scientific literature, Journal of American Society for Information Science 30(4), (1979) 296-303.
DOI: https://doi.org/10.1002/asi.4630300509
Google Scholar
L. Egghe, On the influence of growth on obsolescence, Scientometrics, 27(2), (1993) 195-214.
DOI: https://doi.org/10.1007/BF02016550
Google Scholar
L. Egghe, I.K. Ravichandra Rao, R. Rousseau, On the influence of production on utilization functions: Obsoles-cence or increased use? Scientometrics 34(2), (1995) 285-315.
DOI: https://doi.org/10.1007/BF02020425
Google Scholar
U. Gupta, Obsolescence of physics literature: Exponential decrease of the density of citations to Physical Review articles with age, Journal of American Society for Infor-mation Science 41(4), (1990) 282-287.
DOI: https://doi.org/10.1002/(SICI)1097-4571(199006)41:4<282::AID-ASI7>3.0.CO;2-1
Google Scholar
A.L. Horvat, Handbook of Electrolyte Solutions: Physical Properties, Estimation and Correlation Methods. Ellis Horwood, Chichester (1985).
Google Scholar
D. Kashchiev, Nucleation: Basic Theory with Applica-tions. Butterworth-Heinemann. Oxford, 2000.
DOI: https://doi.org/10.1016/B978-075064682-6/50012-3
Google Scholar
J.W. Mullin, Crystallization, 4th Edition. Butterworth-Heinemann, Oxford, 2001.
DOI: https://doi.org/10.1016/B978-075064833-2/50009-7
Google Scholar
A.G. Marangoni, On the use and misuse of the Avrami equation in the characterization of the kinetics of fat crys-tallization, Journal of American Oil Chemists’ Society 75(10), (1998) 1465-1467.
DOI: https://doi.org/10.1007/s11746-998-0203-8
Google Scholar
S. Bonzi, H.W. Snyder, Motivations for citation: A com-parison of self citation and citation to others. Scientometrics 21 (1991) 245–254.
DOI: https://doi.org/10.1007/BF02017571
Google Scholar
M.H.C. Ho, J.S. Liu, The motivations for knowledge transfer across borders: the diffusion of data envelopment analysis (DEA) methodology, Scientometrics 94 (2013) 397–421 .
DOI: https://doi.org/10.1007/s11192-012-0705-x
Google Scholar
D. Lyu, X. Ruan, J. Xie, Y. Cheng, The classification of citing motivations: a meta-synthesis, Scientometrics 126 (2021) 3243–3264.
DOI: https://doi.org/10.1007/s11192-021-03908-z
Google Scholar
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