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Journal articles on the topic 'Freshwater microbiology mathematical models'

Author: Grafiati

Published: 4 June 2021

Last updated: 1 February 2022

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1

Chiyaka, Edward T., Gesham Magombedze, and Lawrence Mutimbu. "Modelling within Host Parasite Dynamics of Schistosomiasis." Computational and Mathematical Methods in Medicine 11, no. 3 (2010): 255–80. http://dx.doi.org/10.1080/17486701003614336.

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Schistosomiasis infection is characterized by the presence of adult worms in the portal and mesenteric veins of humans as part of a complex migratory cycle initiated by cutaneous penetration of the cercariae shed by infected freshwater snails. The drug praziquantel is not always effective in the treatment against schistosomiasis at larvae stage. However, our simulations show that it is effective against mature worms and eggs. As a result, the study and understanding of immunological responses is key in understanding parasite dynamics. We therefore introduce quantitative interpretations of huma

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2

Stelling, Jörg. "Mathematical models in microbial systems biology." Current Opinion in Microbiology 7, no. 5 (2004): 513–18. http://dx.doi.org/10.1016/j.mib.2004.08.004.

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3

Costanza, Robert, and Fred H. Sklar. "Articulation, accuracy and effectiveness of mathematical models: A review of freshwater wetland applications." Ecological Modelling 27, no. 1-2 (1985): 45–68. http://dx.doi.org/10.1016/0304-3800(85)90024-9.

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4

Tom, Eric, and Kevin A. Schulman. "Mathematical Models in Decision Analysis." Infection Control and Hospital Epidemiology 18, no. 1 (1997): 65–73. http://dx.doi.org/10.2307/30141966.

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5

Tom, Eric, and Kevin A. Schulman. "Mathematical Models in Decision Analysis." Infection Control and Hospital Epidemiology 18, no. 1 (1997): 65–73. http://dx.doi.org/10.1086/647503.

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6

Li, Hao, Guozhong Xie, and Alan S. Edmondson. "Review of Secondary Mathematical Models of Predictive Microbiology." Journal of Food Products Marketing 14, no. 2 (2008): 57–74. http://dx.doi.org/10.1080/10454440801918283.

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7

Grassly, Nicholas C., and Christophe Fraser. "Mathematical models of infectious disease transmission." Nature Reviews Microbiology 6, no. 6 (2008): 477–87. http://dx.doi.org/10.1038/nrmicro1845.

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8

Schneider, B., and G. I. Marchuk. "Mathematical Models in Immunology." Biometrics 42, no. 4 (1986): 1003. http://dx.doi.org/10.2307/2530721.

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9

Bao, Weijun, Songming Zhu, Shuirong Guo, et al. "Particle size distribution mathematical models and properties of suspended solids in a typical freshwater pond." Environmental Pollution 241 (October 2018): 164–71. http://dx.doi.org/10.1016/j.envpol.2018.05.063.

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10

Shang, Qian Ming. "Modeling and Simulation of Freshwater Generator Subsystem of Low Speed Engine Room Simulator Based on Visual." Advanced Materials Research 557-559 (July 2012): 2324–28. http://dx.doi.org/10.4028/www.scientific.net/amr.557-559.2324.

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3d models of the equipments of freshwater generator system are built according to the real ship. In support of a simulative sustainable system, a real-time variable database and mathematical models of the subsystem are set up. Then the precision of the models are proved to meet the demands by comparing the simulation results with the practical situation. The interfaces are available by making use of VC++6.0. Finally, the data connections between the math models and interfaces are established by means of the technology of network communications. The purpose of developing this simulation system

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11

Li, Hao, Guozhong Xie, and Alan Edmondson. "Evolution and limitations of primary mathematical models in predictive microbiology." British Food Journal 109, no. 8 (2007): 608–26. http://dx.doi.org/10.1108/00070700710772408.

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12

Black, F. L., and B. Singer. "Elaboration Versus Simplification in Refining Mathematical Models of Infectious Disease." Annual Review of Microbiology 41, no. 1 (1987): 677–701. http://dx.doi.org/10.1146/annurev.mi.41.100187.003333.

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13

Hunt, C. Anthony, Glen E. P. Ropella, Sunwoo Park, and Jesse Engelberg. "Dichotomies between computational and mathematical models." Nature Biotechnology 26, no. 7 (2008): 737–38. http://dx.doi.org/10.1038/nbt0708-737.

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14

Assab, Rania, Narimane Nekkab, Pascal Crépey, et al. "Mathematical models of infection transmission in healthcare settings." Current Opinion in Infectious Diseases 30, no. 4 (2017): 410–18. http://dx.doi.org/10.1097/qco.0000000000000390.

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15

López, S., M. Prieto, J. Dijkstra, M. S. Dhanoa, and J. France. "Statistical evaluation of mathematical models for microbial growth." International Journal of Food Microbiology 96, no. 3 (2004): 289–300. http://dx.doi.org/10.1016/j.ijfoodmicro.2004.03.026.

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16

Nokes, D. J., and R. M. Anderson. "Application of mathematical models to the design of immunization strategies." Reviews in Medical Microbiology 4, no. 1 (1993): 1–7. http://dx.doi.org/10.1097/00013542-199301000-00001.

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17

Lopatin, A. A., E. V. Kuklev, V. A. Safronov, A. S. Razdorsky, L. V. Samoilova, and V. P. Toporkov. "Verification of Mathematical Models of Plague." Problems of Particularly Dangerous Infections, no. 3(113) (June 20, 2012): 26–28. http://dx.doi.org/10.21055/0370-1069-2012-3-26-28.

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Mathematic modeling and prognostication of infectious diseases epidemic process is a promising trend of epidemiologic investigations. The complex of mathematic models (SEIRF type) of plague epidemic process was developed for this purpose by the Russian Research Anti-Plague Institute “Microbe” and laboratory of epidemiologic cybernetics of N.F.Gamaleya Institute for Epidemiology and Microbiology. The data on the plague outbreak in 1945 in the rural settlement Avan’ (Aral region of Kzyl-Orda district of Kazakh SSR) were used to test working efficiency of this complex. The data analysis permitted

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18

Navarro, Antonio R. "Effects of furfural on ethanol fermentation bySaccharomyces cerevisiae: Mathematical models." Current Microbiology 29, no. 2 (1994): 87–90. http://dx.doi.org/10.1007/bf01575753.

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19

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

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20

WALLS, ISABEL, VIRGINIA N. SCOTT, and DANE T. BERNARD. "Validation of Predictive Mathematical Models Describing Growth of Staphylococcus aureus." Journal of Food Protection 59, no. 1 (1996): 11–15. http://dx.doi.org/10.4315/0362-028x-59.1.11.

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An investigation was performed on the growth of Staphylococcus aureus in a commercially available, sterile, homogeneous food at 12°C with 1.2 and 5.9% NaCl; at 25°C with 10.4% NaCl; and at 20 and 35°C with 1.2, 5.3, 12.5, and 15.8% NaCl; over a pH range of 5.5 to 7.5. Growth data were fitted to the Gompertz equation and the resulting growth kinetics were compared with predictions from the Pathogen Modeling Program (PMP) and Food MicroModel (FMM). For the PMP, predicted lag-phase durations varied from 0.5 to 130 h longer than the observed values. In general, close agreement with growth rates wa

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21

Mayank, Rahul, Amrita Ranjan, and Vijayanand S. Moholkar. "Mathematical models of ABE fermentation: review and analysis." Critical Reviews in Biotechnology 33, no. 4 (2012): 419–47. http://dx.doi.org/10.3109/07388551.2012.726208.

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22

Fowler, A. C. "Mathematical Models in the Applied Sciences." Biometrics 54, no. 4 (1998): 1684. http://dx.doi.org/10.2307/2533707.

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23

Drancourt, M., and D. Raoult. "Value of mathematical models for epidemics: the plague paradigm." Clinical Microbiology and Infection 25, no. 1 (2019): 120. http://dx.doi.org/10.1016/j.cmi.2018.08.014.

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24

WALLS, ISABEL, and VIRGINIA N. SCOTT. "Validation of Predictive Mathematical Models Describing the Growth of Listeria monocytogenes." Journal of Food Protection 60, no. 9 (1997): 1142–45. http://dx.doi.org/10.4315/0362-028x-60.9.1142.

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Growth of Listeria monocytogenes and Listeria innocua in commercially available sterile homogeneous foods was investigated at different temperatures, pH values, and NaCl concentrations. Growth data were fitted to the Gompertz equation and the resulting growth kinetics were compared with predictions from the Pathogen Modeling Program and Food MicroModel. In general, good agreement was obtained when comparing growth rates and generation times for both models. Differences were observed when comparing lag phases, which ranged from 117 h shorter to 4.9 h longer than predicted for L. monocytogenes.

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25

Bouzouf, Boutaina, and Zhi Chen. "A comparison of finite volume method and sharp model for two dimensional saltwater intrusion modeling." Canadian Journal of Civil Engineering 41, no. 3 (2014): 191–96. http://dx.doi.org/10.1139/cjce-2013-0265.

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Seawater intrusion in coastal aquifers is a 3-D phenomenon. However, 3-D regional aquifer models are often limited by insufficient geological and hydrological data, the large horizontal to vertical scales ratio, and by numerical constraints. A mathematical formulation and numerical implementation of the model for saltwater intrusion problems are presented in this paper. The mathematical model is based on assumption of two-phase flow between saltwater and freshwater and Dupuit approximation. Finite volume method is used as the numerical method in non-structured grids to have flexibility upon co

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26

Policastro, Grazia, Vincenzo Luongo, Luigi Frunzo, and Massimiliano Fabbricino. "A comprehensive review of mathematical models of photo fermentation." Critical Reviews in Biotechnology 41, no. 4 (2021): 628–48. http://dx.doi.org/10.1080/07388551.2021.1873241.

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27

Michelson, Seth. "Multidrug restistance and its reversal: mathematical models." Computational and Mathematical Methods in Medicine 2, no. 1 (1999): 103–15. http://dx.doi.org/10.1080/10273669908833032.

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28

Moser, A., B. Mayr, W. Jury, W. Steiner, and P. Horvat. "Mathematical models for mixing in deep jet bioreactors: analysis." Bioprocess Engineering 7, no. 4 (1991): 171–76. http://dx.doi.org/10.1007/bf00387413.

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29

Puskas, James, Edward McBean, and Nicholas Kouwen. "Behaviour and transport of oil under smooth ice." Canadian Journal of Civil Engineering 14, no. 4 (1987): 510–18. http://dx.doi.org/10.1139/l87-075.

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Mathematical and physical models are used in studying transport of oil slicks beneath ice in the presence of an ambient water current. The mathematical expressions for the relevant forces are developed by utililizing basic boundary layer theory and considering the physical properties of the oils and are verified from the laboratory experiments. Three different crude oils are utilized beneath freshwater ice under various flow conditions in the experiments.The transport of oil slicks oriented longitudinally to the direction of the water flow are modelled by the summation of the shear force at th

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30

Britton, N. F. "Review: Mathematical Models in Biology: An Introduction." Mathematical Medicine and Biology: A Journal of the IMA 22, no. 3 (2005): 289–90. http://dx.doi.org/10.1093/imammb/dqi008.

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31

Zhou, Zhifang, Boran Zhang, Qiaona Guo, and Shumei Zhu. "Experimental and Numerical Studies on the Vertical Flow of Variable Density Fluid in Different Directions." Geofluids 2019 (April 24, 2019): 1–15. http://dx.doi.org/10.1155/2019/2175983.

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Injecting freshwater and pumping salt water are effective methods to restore the salt water in a coastal area. Based on a one-dimensional vertical experiment, the variable density flow is simulated under the condition of different injection directions and injection rates of fresh water. A one-dimensional mathematical model of variable density flow and solute transport is established. The mathematical models are solved using the implicit difference method. Fortran code is developed to simulate and verify the vertical flow of variable density flow in different directions. Through both numerical

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32

Vilyunov, Sergey D. "Study of the contribution of horizontal stability in the probability model of the “hostpathogen” interaction system on the basis of millet varieties susceptible to smut." Agrarian science, no. 11-12 (January 20, 2021): 97–100. http://dx.doi.org/10.32634/0869-8155-2020-343-11-97-100.

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Digital control of breeding process, creation of mathematical models of living objects and management of plant life cycle is an urgent problem of modern times. Сreation of technologies that ensure implementation of the concept of advanced digital "smart" agriculture is impossible without basic mathematical models of "mass interactions" of natural living objects. This primarily affects the spread of certain diseases in populations. In the plant world, such a convenient model object is the well-studied "host-pathogen" system by the example of the interaction of millet and its smut disease. At pr

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33

Curto, Raul, Eberhard O. Voit, Albert Sorribas, and Marta Cascante. "Mathematical models of purine metabolism in man." Mathematical Biosciences 151, no. 1 (1998): 1–49. http://dx.doi.org/10.1016/s0025-5564(98)10001-9.

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34

Amuzescu, Bogdan, Razvan Airini, Florin Bogdan Epureanu, Stefan A. Mann, Thomas Knott, and Beatrice Mihaela Radu. "Evolution of mathematical models of cardiomyocyte electrophysiology." Mathematical Biosciences 334 (April 2021): 108567. http://dx.doi.org/10.1016/j.mbs.2021.108567.

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35

Gutarowska, B., and Z. Żakowska. "Mathematical models of mycelium growth and ergosterol synthesis in stationary mould culture." Letters in Applied Microbiology 48, no. 5 (2009): 605–10. http://dx.doi.org/10.1111/j.1472-765x.2009.02577.x.

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36

Weeks, Stephen C., Thomas F. Sanderson, Sadie K. Reed, et al. "Ancient androdioecy in the freshwater crustacean Eulimnadia." Proceedings of the Royal Society B: Biological Sciences 273, no. 1587 (2005): 725–34. http://dx.doi.org/10.1098/rspb.2005.3370.

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Among the variety of reproductive mechanisms exhibited by living systems, one permutation—androdioecy (mixtures of males and hermaphrodites)—is distinguished by its rarity. Models of mating system evolution predict that androdioecy should be a brief stage between hermaphroditism and dioecy (separate males and females), or vice versa. Herein we report evidence of widespread and ancient androdioecy in crustaceans in the genus Eulimnadia , based on observations of over 33 000 shrimp from 36 locations from every continent except Antarctica. Using phylogenetic, biogeographical and palaeontological

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37

CASTILLEJO-RODRÍGUEZ, A. M., R. M. GARCÍA GIMENO, G. ZURERA COSANO, E. BARCO ALCALÁ, and M. R. RODRÍGUEZ PÉREZ. "Assessment of Mathematical Models for Predicting Staphylococcus aureus Growth in Cooked Meat Products." Journal of Food Protection 65, no. 4 (2002): 659–65. http://dx.doi.org/10.4315/0362-028x-65.4.659.

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The growth of Staphylococcus aureus in commercially available vacuum-packaged cooked ham, turkey breast meat, and chicken breast meat stored at 2.3, 6.5, 10, 13.5, and 17.7°C was studied. Growth rates observed in these food products were compared with those predicted on the basis of various growth models found in the literature and with those generated by the Pathogen Modeling Program and the Food MicroModel software using graphical and mathematical analysis for performance evaluation. In general, the models studied overestimated the growth of S. aureus. The Dengremont and Membré model most cl

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38

Zhani, Khalifa, and Khaled Ali Abuhasel. "Modeling, Simulation, and Optimization of a Solar-Based System of Desalination Using Humidification and Dehumidification." Applied Sciences 10, no. 10 (2020): 3361. http://dx.doi.org/10.3390/app10103361.

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Solar desalination systems are characterized by low freshwater production compared with the usual techniques of mineral and salt removal from water. The usual methods include, but are not limited to, multi-stage flash distillation, multiple-effect distillation, vapor-compression desalination, and reverse osmosis. Solar desalination requires various modifications to make it more productive than the usual methods. The method is suitable for energy and environmental protection, making it the most effective system. The adjustments involve using the humidification and dehumidification principle (HD

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39

Vila, X., C. A. Abella, J. B. Figueras, and J. P. Hurley. "Vertical models of phototrophic bacterial distribution in the metalimnetic microbial communities of several freshwater North-American kettle lakes." FEMS Microbiology Ecology 25, no. 3 (1998): 287–99. http://dx.doi.org/10.1111/j.1574-6941.1998.tb00481.x.

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40

Nicolaï, Bart M., Jan F. Van Impe, Peter A. Vanrolleghem, and Joos Vandewalle. "Evaluation of two unstructured mathematical models for the penicillin G fedbatch fermentation." Antonie van Leeuwenhoek 62, no. 4 (1992): 273–83. http://dx.doi.org/10.1007/bf00572595.

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41

Pruitt, Kenneth M., and David N. Kamau. "Mathematical models of bacterial growth, inhibition and death under combined stress conditions." Journal of Industrial Microbiology 12, no. 3-5 (1993): 221–31. http://dx.doi.org/10.1007/bf01584194.

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42

Yue, Li Hong, and Yi Peng Yang. "Study on Light Intensity Attenuation Characteristics of Chlorella Sp. Culture and the Growth of Chlorella Sp. with the Gradient Light Illuminate Culture." Applied Mechanics and Materials 675-677 (October 2014): 86–89. http://dx.doi.org/10.4028/www.scientific.net/amm.675-677.86.

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Based on the photoautotrophic characteristics of the freshwater microalage, light intensity attenuation characteristics in the cell culture system for Chlorella sp. were studied. Micralgae was cultured with a constant and the gradient light illuminate culture conditions, the cell growth of Microlagae was detected respectively, By means of regression analysis, mathematical models of illuminance intensity attenuation are gotten under different culture conditions. Results show algae cell density under gradient light culture conditions is higher than constant light, so the gradient light is more s

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43

Adkison, Milo D. "Models of the effects of marine-derived nutrients on salmon (Oncorhynchus spp.) population dynamics." Canadian Journal of Fisheries and Aquatic Sciences 67, no. 1 (2010): 5–15. http://dx.doi.org/10.1139/f09-161.

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Pacific salmon ( Oncorhynchus spp.) populations transfer large quantities of nutrients from their marine to their freshwater habitats. These nutrients have been shown to affect salmon populations in fresh water, including increasing basal food resources and elevating juvenile salmon growth rates and condition. The broader effects on recruitment and commercial harvests, however, are not clear. I developed and explored mathematical models of the effects of these nutrients on stock–recruitment relationships and used these models to investigate management implications. Populations strongly depende

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44

Layton, Anita T. "His and her mathematical models of physiological systems." Mathematical Biosciences 338 (August 2021): 108642. http://dx.doi.org/10.1016/j.mbs.2021.108642.

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45

Li, Songjun, Pingchu Chen, Wuke Li, Xiao Hao, and Guangfu Yang. "Establishing Mathematical and Physical Models for the Adsorption of Biomacromolecules." Applied Biochemistry and Biotechnology 134, no. 2 (2006): 165–78. http://dx.doi.org/10.1385/abab:134:2:165.

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46

Schwippel, J., and J. Votruba. "Identification of mathematical models of complex cultures of microorganisms in continuous cultivation—Numerical approach." Folia Microbiologica 37, no. 6 (1992): 427–32. http://dx.doi.org/10.1007/bf02899901.

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47

SCHAFFNER, DONALD W. "Utilization of Mathematical Models To Manage Risk of Holding Cold Food without Temperature Control." Journal of Food Protection 76, no. 6 (2013): 1085–94. http://dx.doi.org/10.4315/0362-028x.jfp-12-424.

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This document describes the development of a tool to manage the risk of the transportation of cold food without temperature control. The tool uses predictions from ComBase predictor and builds on the 2009 U.S. Food and Drug Administration Model Food Code and supporting scientific data in the Food Code annex. I selected Salmonella spp. and Listeria monocytogenes as the organisms for risk management. Salmonella spp. were selected because they are associated with a wide variety of foods and grow rapidly at temperatures &gt;17°C. L. monocytogenes was selected because it is frequently present i

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48

Moser, A., B. Mayr, W. Jury, W. Steiner, and P. Horvat. "Mathematical models for mixing in deep-jet bioreactors: Calculation of parameters." Bioprocess Engineering 7, no. 4 (1991): 177–82. http://dx.doi.org/10.1007/bf00387414.

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49

Meyerhoff, J., and K. H. Bellgardt. "Two mathematical models for the development of a single microbial pellet." Bioprocess Engineering 12, no. 6 (1995): 315–22. http://dx.doi.org/10.1007/bf00369508.

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50

Maini, Philip K. "Using mathematical models to help understand biological pattern formation." Comptes Rendus Biologies 327, no. 3 (2004): 225–34. http://dx.doi.org/10.1016/j.crvi.2003.05.006.

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