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Littérature scientifique sur le sujet « Corporations – Growth – Mathematical models »

Auteur : Grafiati
Publié le 10 mars 2023

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Articles de revues sur le sujet "Corporations – Growth – Mathematical models"

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Sofiko Dzhvarsheishvili, Sofiko Dzhvarsheishvili. « Developing Tendencies of Foreign Direct Investments ». New Economist 16, no 03 (28 janvier 2022) : 41–47. http://dx.doi.org/10.36962/nec62-6303-042021-41.

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The formation process of foreign direct investment theories began in the second half of the twentieth century, it was period that the importance of foreign direct investment (FDI) in international capital movement increased, and this period was characterized by the rapid growth of multinational enterprises, which, in turn, is a major source of FDI. Scientific and technological progress has become the basis for decisions of transnational companies to invest capital in to different parts of the world and to coordinate and control its many branches from one country. During this period scientists actively began to develop theories and mathematical models of foreign direct investments, which meant studying the genesis of FDI, as well as analyzing their impact on the economy of both the host and the issuer countries. The analysis of foreign direct investment theories is closely related to the study of the activities of multinational corporations. Among them are some paradigms containing interesting discoveries that view the foreign direct investment as a contributing factor for the economic growth of the host country and its industrial development. In this article, the author consider the key theories and models of foreign direct investment: 1. The Product Life Cycle Theory, which is developed by Vernon; 2. Transnational companies and monopolistic computation theory, which is developed by Hymer; 3. Generalized theory of economic development, which is developed by Akamatsu; 4.The competitive advantage of nation’s theory, which is developed by Porter; 5.The eclectic paradigm and country's investment development theory, which is developed by Dunning; 6.Differential model of capital distribution between countries by Leontiev. The theories and models provide a basic range of motives of investors' behavior in the world market. It also makes it possible to analyze what impact foreign direct investment has on the economy of the recipient country and what forecast the recipient country's economy will have. Keywords: Globalization, Foreign Direct Investment, Economic Growth, Multinational Corporations, Analysis of Basic Theories and models;
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Du, Yuping, Rongping Kang et Yinbin Ke. « Understanding the growth models of Chinese multinational corporations ». International Journal of Chinese Culture and Management 1, no 4 (2008) : 451. http://dx.doi.org/10.1504/ijccm.2008.020010.

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Et.al, D. Priyadarshini. « A Novel Technique for IDS in Distributed Data Environment Using Merkel Based Security Mechanism for Secure User Allocation ». Turkish Journal of Computer and Mathematics Education (TURCOMAT) 12, no 3 (11 avril 2021) : 4284–97. http://dx.doi.org/10.17762/turcomat.v12i3.1720.

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Multiple corporations and people frequently launching their data in the cloud environment. With the huge growth of data mining and the cloud storage paradigm without checking protection policies and procedures that can pose a great risk to their sector. The data backup in the cloud storage would not only be problematic for the cloud user but also the Cloud Service Provider (CSP). The unencrypted handling of confidential data is likely to make access simpler for unauthorized individuals and also by the CSP. Normal encryption algorithms need more primitive computing, space and costs for storage. It is also of utmost importance to secure cloud data with limited measurement and storage capacity. Till now, different methods and frameworks to maintain a degree of protection that meets the requirements of modern life have been created. Within those systems, Intrusion Detection Systems (IDS) appear to find suspicious actions or events which are vulnerable to a system's proper activity. Today, because of the intermittent rise in network traffic, the IDS face problems for detecting attacks in broad streams of links. In existing the Two-Stage Ensemble Classifier for IDS (TSE-IDS) had been implemented. For detecting trends on big data, the irrelevant data characteristics appear to decrease both the velocity of attack detection and accuracy. The computing resource available for training and testing of the IDS models is also increased. We have put forward a novel strategy in this research paper to the above issues to improve the balance of the server load effectively with protected user allocation to a server, and thereby minimize resource complexity on the cloud data storage device, by integrating the Authentication based User-Allocation with Merkle based Hashing-Tree (AUA-MHT) technique. Through this, the authentication attack and flood attack are detected and restrict unauthorized users. By this proposed model the cloud server verifies, by resolving such attacks, that only approved users are accessing the cloud info. The proposed framework AUA-MHT performs better than the existing model TSE-IDS for parameters such as User Allocation Rate, Intrusion Detection Rate and Space Complexity
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Dolganova, Olga, et Valeriy Lokhov. « Mathematical models of growth deformation ». PNRPU Mechanics Bulletin 1 (30 mars 2014) : 126–41. http://dx.doi.org/10.15593/2224-9893/2014.1.06.

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Pavankumari, V. « Mathematical and Stochastic Growth Models ». International Journal for Research in Applied Science and Engineering Technology 9, no 11 (30 novembre 2021) : 1576–82. http://dx.doi.org/10.22214/ijraset.2021.39055.

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Abstract: Many statistical and mathematical models of growth are developed in the literature and effectively applied to various conditions in the existent world that involve many research problems in the different fields of applied statistics. Nevertheless, still, there is an equally large number of conditions, which have not yet been mathematically or statistically modeled, due to the complex situations or formed models are mathematically or statistically inflexible. The present study is based on mathematical and stochastic growth models. The specification of both the growth models is depicted. A detailed study of newly modified growth models is mentioned. This research will give substantial information on growth models, such as proposed modified exponential growth models and their specifications clearly motioned which gives scope for future research.
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Kumari, V. Pavan, Venkataramana Musala et M. Bhupathi Naidu. « Mathematical and Stochastic Growth Models ». International Journal for Research in Applied Science and Engineering Technology 10, no 5 (31 mai 2022) : 987–89. http://dx.doi.org/10.22214/ijraset.2022.42330.

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Abstract: Many statistical and mathematical models of growth are developed in the literature and effectively applied to various conditions in the existent world involves many research problems in the different fields of applied statistics. Nevertheless, still, there are an equally a large number of conditions, which have not yet been mathematically or statistically modeled, due to the complex situations or formed models are mathematically or statistically inflexible. The present study is based on mathematical and stochastic growth models. The specification of both the growth models is depicted. A details study of newly modified growth models are mentioned. This research will give substantial information on growth models, such as proposed modified exponential growth models and it’s specifications clearly motioned which gives scope for future research.
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Oliveri, Hadrien, et Alain Goriely. « Mathematical models of neuronal growth ». Biomechanics and Modeling in Mechanobiology 21, no 1 (7 janvier 2022) : 89–118. http://dx.doi.org/10.1007/s10237-021-01539-0.

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AbstractThe establishment of a functioning neuronal network is a crucial step in neural development. During this process, neurons extend neurites—axons and dendrites—to meet other neurons and interconnect. Therefore, these neurites need to migrate, grow, branch and find the correct path to their target by processing sensory cues from their environment. These processes rely on many coupled biophysical effects including elasticity, viscosity, growth, active forces, chemical signaling, adhesion and cellular transport. Mathematical models offer a direct way to test hypotheses and understand the underlying mechanisms responsible for neuron development. Here, we critically review the main models of neurite growth and morphogenesis from a mathematical viewpoint. We present different models for growth, guidance and morphogenesis, with a particular emphasis on mechanics and mechanisms, and on simple mathematical models that can be partially treated analytically.
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Leung, C. H. C. « Mathematical Models of Fire Growth ». Computer Journal 28, no 2 (1 février 1985) : 179–83. http://dx.doi.org/10.1093/comjnl/28.2.179.

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Dmitriev, V. I., E. S. Kurkina et O. E. Simakova. « Mathematical models of urban growth ». Computational Mathematics and Modeling 22, no 1 (janvier 2011) : 54–68. http://dx.doi.org/10.1007/s10598-011-9088-8.

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Suzuki, Takashi. « Mathematical models of tumor growth systems ». Mathematica Bohemica 137, no 2 (2012) : 201–18. http://dx.doi.org/10.21136/mb.2012.142866.

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Thèses sur le sujet "Corporations – Growth – Mathematical models"

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Mohd, Jaffar Mai. « Mathematical models of hyphal tip growth ». Thesis, University of Dundee, 2012. https://discovery.dundee.ac.uk/en/studentTheses/140f9a81-12ca-4337-a311-2f82441f1ea6.

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Filamentous fungi are important in an enormous variety of ways to our life, with examples ranging from bioremediation, through the food and drinks industry to human health. These organisms can form huge networks stretching metres and even kilometres. However, their mode of growth is by the extension of individual hyphal tips only a few microns in diameter. Tip growth is mediated by the incorporation of new wall building materials at the soft apex. Just how this process is controlled (in fungi and in cell elongation in other organisms) has been the subject of intense study over many years and has attracted considerable attention from mathematical modellers. In this thesis, we consider mathematical models of fungal tip growth that can be classified as either geometrical or biomechanical. In every model we examine, a 2-D axisymmetric semihemisphere-like curve represents half the medial section of fungal tip geometry. A geometrical model for the role of the Spitzenkorper in the tip growth was proposed by Bartnicki-Garcia et al (1989), where a number of problems with the mathematical derivation were pointed out by Koch (2001). A suggestion is given as an attempt to revise the derivation by introducing a relationship between arc length of a growing tip, deposition of wall-building materials and tip curvature. We also consider two types of geometrical models as proposed by Goriely et al (2005). The first type considers a relationship between the longitudinal curvature and the function used to model deposition of wall-building materials. For these types of models, a generalized formulae for the tip shape is introduced, which allows localization of deposition of wall-building materials to be examined. The second type considers a relationship between longitudinal and latitudinal curvatures and the function used to model deposition of wall-building materials. For these types of models, a new formulation of the function used to model deposition of wall-building materials is introduced. Finally, a biomechanical model as proposed by Goriely et al (2010). Varying arc length of the stretchable region on the tip suggests differences in geometry of tip shape and the effective pressure profile. The hypothesis of orthogonal growth is done by focusing only on the apex of a "germ tube". Following that, it suggests that material points on the tip appear to move in a direction perpendicular to the tip either when surface friction is increased or decreased.
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Al-Taie, Ali Hussein Shuaa. « Continuum models for fungal growth ». Thesis, University of Dundee, 2011. https://discovery.dundee.ac.uk/en/studentTheses/9b2c14ff-c012-4541-a6ea-3ab0fea38e50.

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Fungi generally exist as unicellular organisms (yeasts) or in a vegetative state in which a mycelium, i.e. an interconnected network of tubes (hyphae) is formed. The mycelium can operate over a very large range of scales (each hypha is only a few microns in diameter, yet mycelia can be kilometres across). Fungi are of fundamental importance to many natural processes: certain species have major roles in decomposition and nutrient cycling in the soil; some form vital links with plant roots allowing nutrient transfer. Other species are essential to industrial processes: citric acid production for use in soft drinks; brewing and baking; treatment of industrial effluent and ground toxins. Unfortunately, certain species can cause devastating damage to crops, serious disease in humans or can damage building materials. In this thesis we constructed new models for the development of fungal mycelia. At this scale, partial differential equations representing the interaction of biomass with the underlying substrate is the appropriate choice. Models are essentially based on those derived by Davidson and co workers (see e.g. Boswell et al.(2007)). These models are of a complex mathematical structure, comprising both parabolic and hyperbolic parts. Thus, their analytic and numerical properties are nontrivial. The objectives of this thesis are to: (i) obtain a solid understanding of the physiology of growth and function and the varying mathematical techniques used in model construction. (ii) revisit existing models to reinterpret the various model components in a simple form. (iii) construct models to compare the growth dynamics of different phenotype for new species to see if these "scale " appropriately.
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Robertson-Tessi, Mark. « Mathematical Models of Tumor Growth and Therapy ». Diss., The University of Arizona, 2010. http://hdl.handle.net/10150/194473.

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A number of mathematical models of cancer growth and treatment are presented. The most significant model presented is of the interactions between a growing tumor and the immune system. The equations and parameters of the model are based on experimental and clinical results from published studies. The model includes the primary cell populations involved in effector-T-cell-mediated tumor killing: regulatory T cells, helper T cells, and dendritic cells. A key feature is the inclusion of multiple mechanisms of immunosuppression through the main cytokines and growth factors mediating the interactions between the cell populations. Decreased access of effector cells to the tumor interior with increasing tumor size is accounted for.The model is applied to tumors of different growth rates and antigenicities to gauge the relative importance of the various immunosuppressive mechanisms in a tumor. The results suggest that there is an optimum antigenicity for maximal immune system effect. The immunosuppressive effects of further increases in antigenicity outweigh the increase in tumor cell control due to larger populations of tumor-killing effector T cells. The model is applied to situations involving cytoreductive treatment, specifically chemotherapy and a number of immunotherapies. The results how that for some types of tumors, the immune system is able to remove any tumor cells remaining after the therapy is finished. In other cases, the immune system acts to prolong remission periods. A number of immunotherapies are found to be ineffective at removing a tumor burden alone, but offer significant improvement on therapeutic outcome when used in combination with chemotherapy.Two simplified classes of cancer models are also presented. A model of cellular metabolism is formulated. The goal of the model is to understand the differences between normal cell and tumor cell metabolism. Several theories explaining the Crabtree Effect, hereby tumor cells reduce their aerobic respiration in the presence of glucose, have been put forth in the literature; the models test some of these theories, and examine their plausibility.A model of elastic tissue mechanics for a cylindrical tumor growing within a ductal membrane is used to determine the buildup of residual stress due to growth. These results can have possible implications for tumor growth rates and morphology.
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Jaroudi, Rym. « Inverse Mathematical Models for Brain Tumour Growth ». Licentiate thesis, Linköpings universitet, Tekniska fakulteten, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-141982.

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We study the following well-established model of reaction-diffusion type for brain tumour growth: This equation describes the change over time of the normalised tumour cell density u as a consequence of two biological phenomena: proliferation and diffusion. We discuss a mathematical method for the inverse problem of locating the brain tumour source (origin) based on the reaction-diffusion model. Our approach consists in recovering the initial spatial distribution of the tumour cells  starting from a later state , which can be given by a medical image. We use the nonlinear Landweber regularization method to solve the inverse problem as a sequence of well-posed forward problems. We give full 3-dimensional simulations of the tumour in time on two types of data, the 3d Shepp-Logan phantom and an MRI T1-weighted brain scan from the Internet Brain Segmentation Repository (IBSR). These simulations are obtained using standard finite difference discretisation of the space and time-derivatives, generating a simplistic approach that performs well. We also give a variational formulation for the model to open the possibility of alternative derivations and modifications of the model. Simulations with synthetic images show the accuracy of our approach for locating brain tumour sources.
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Wei, Yong, et 卫勇. « The real effects of S&P 500 Index additions : evidence from corporate investment ». Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2010. http://hub.hku.hk/bib/B4490681X.

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Moyen, Nathalie. « Financing investment with external funds ». Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1999. http://www.collectionscanada.ca/obj/s4/f2/dsk1/tape7/PQDD_0019/NQ46396.pdf.

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Hounslow, Michael John. « A discretized population balance for simultaneous nucleation, growth and aggregation / ». Title page, summary and table of contents only, 1990. http://web4.library.adelaide.edu.au/theses/09PH/09phh839.pdf.

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Browning, Alexander P. « Stochastic mathematical models of cell proliferation assays ». Thesis, Queensland University of Technology, 2017. https://eprints.qut.edu.au/110808/1/Alexander_Browning_Thesis.pdf.

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Cell proliferation assays are routinely used to study collective cell behaviour, and can be interpreted with mathematical models. In this thesis, we apply a computational Bayesian technique to calibrate stochastic discrete mathematical models of cell migration and cell proliferation in the context of a cell proliferation assay. Initially, we use a lattice-based model to explore the optimal duration of a cell proliferation assay. Next, we estimate the parameters in a lattice-free model using three independent experimental data sets. Our model is able to both describe and predict the evolution of the population and spatial structure in a cell proliferation assay.
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Vekstein, Daniel. « Dynamics of organizational growth in the international automobile industry ». Diss., The University of Arizona, 1993. http://hdl.handle.net/10150/186248.

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The phenomenon of organizational growth has traditionally been assumed to be indeterminate largely due to chance or accidents found in organizational worlds. This research takes up the causal processes underlying the growth (and decline) of virtually all world-class manufacturers in the international automobile industry from 1946 to 1989. Two models are developed as alternative explanations for the long-term trends observed in growth rates and their differences across firms. The models are estimated with a nonlinear method and tested through various empirical implications. The model that seems most consistent with the data shows unambiguously that they were not generated by a random or chance process but by underlying processes of collective learning, innovation, and outnovation in technologies and organizational routines. Firms that had generated different rates in these processes differed as hypothesized in their long-term growth performance. The dynamics of collective learning processes, as measured by the parameters of the model, largely explain the dynamics of organizational growth in the world automobile industry, hence, the dynamics of interorganizational competition. The results from tests of ecological hypotheses suggest that organizational ecology might benefit from the application of matrices of collective learning rates generated from interorganizational learning curves, particularly where ecology seeks to explain patterns of competition by organizational size. As shown, this research strategy is general and gauges directly interactions among organizations over long periods. It is also flexible in dealing with various levels of analysis in longitudinal and cross-sectional dimensions. As also shown, the collective learning theory, its model, and the ecology of interorganizational learning curves derived from them can help in evaluating empirically the competitive potential of firms by indicators of innovation and outnovation relative to other firms, patterns of competition (gauged by relative learning rates) among firms, and any changes of those patterns over time. Thus, the research strategy used here provides potentially useful causal analyses as well as meaningful measures on which different organizations can be compared, with each other and with themselves. These measures may also provide important benchmarks and diagnostics for strategic management.
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Stott, Emma Louise. « Solid tumour growth : a comparison of mathematical models and computer simulations ». Thesis, University of Bath, 1998. https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.285273.

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Livres sur le sujet "Corporations – Growth – Mathematical models"

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Berk, Jonathan B. Optimal investment, growth options, and security returns. Cambridge, MA : National Bureau of Economic Research, 1998.

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Lentz, Rasmus. An empirical model of growth through product innovation. Cambridge, Mass : National Bureau of Economic Research, 2005.

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Lentz, Rasmus. An empirical model of growth through product innovation. Bonn, Germany : IZA, 2005.

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Rossi-Hansberg, Esteban. Firm size dynamics in the aggregate economy. Cambridge, MA : National Bureau of Economic Research, 2005.

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Rossi-Hansberg, Esteban. Firm size dynamics in the aggregate economy. Cambridge, Mass : National Bureau of Economic Research, 2005.

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Sinn, Hans-Werner. The vanishing Harberger triangle. Cambridge, MA : National Bureau of Economic Research, 1990.

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Philippe, Aghion, et Durlauf Steven N, dir. Handbook of economic growth. Amsterdam : Elsevier, 2005.

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Chaubey, P. K. Growth models in Indian planning. Bombay : Himalaya Pub. House, 1989.

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1956-, Andersen Torben M., et Moene Karl Ove, dir. Endogenous growth. Oxford, UK : Blackwell Publishers, 1994.

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1956-, Andersen Torben M., et Moene Karl O, dir. Endogenous growth. Oxford : Blackwell, 1993.

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Chapitres de livres sur le sujet "Corporations – Growth – Mathematical models"

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Rubin, Andrew, et Galina Riznichenko. « Growth and Catalysis Models ». Dans Mathematical Biophysics, 3–24. Boston, MA : Springer US, 2013. http://dx.doi.org/10.1007/978-1-4614-8702-9_1.

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Gleißner, Winfried. « Growth Models in Comparison ». Dans Mathematical Modelling in Economics, 194–206. Berlin, Heidelberg : Springer Berlin Heidelberg, 1993. http://dx.doi.org/10.1007/978-3-642-78508-5_19.

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Nicola, PierCarlo. « Multisectoral Growth Models ». Dans Mainstream Mathematical Economics in the 20th Century, 325–50. Berlin, Heidelberg : Springer Berlin Heidelberg, 2000. http://dx.doi.org/10.1007/978-3-662-04238-0_23.

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Murray, James D. « Discrete Growth Models for Interacting Populations ». Dans Mathematical Biology, 95–108. Berlin, Heidelberg : Springer Berlin Heidelberg, 1989. http://dx.doi.org/10.1007/978-3-662-08539-4_4.

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Murray, James D. « Discrete Growth Models for Interacting Populations ». Dans Mathematical Biology, 95–108. Berlin, Heidelberg : Springer Berlin Heidelberg, 1993. http://dx.doi.org/10.1007/978-3-662-08542-4_4.

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Mickens, Ronald E. « Single Population Growth Models ». Dans Mathematical Modelling with Differential Equations, 71–90. Boca Raton : Chapman and Hall/CRC, 2022. http://dx.doi.org/10.1201/9781003178972-4.

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Zaslavski, Alexander J. « Models with Unbounded Endogenous Economic Growth ». Dans Monographs in Mathematical Economics, 351–70. Singapore : Springer Nature Singapore, 2022. http://dx.doi.org/10.1007/978-981-16-9298-7_10.

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Ranganathan, C. R. « Phase Dependent Population Growth Models ». Dans Lecture Notes in Economics and Mathematical Systems, 134–44. Berlin, Heidelberg : Springer Berlin Heidelberg, 1991. http://dx.doi.org/10.1007/978-3-642-58201-1_12.

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Smith, Robert W., et Christian Fleck. « Derivation and Use of Mathematical Models in Systems Biology ». Dans Pollen Tip Growth, 339–67. Cham : Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-56645-0_13.

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Biscoe, P. V., et V. B. A. Willington. « Crop Physiological Studies in Relation to Mathematical Models ». Dans Wheat Growth and Modelling, 257–69. Boston, MA : Springer US, 1985. http://dx.doi.org/10.1007/978-1-4899-3665-3_24.

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Actes de conférences sur le sujet "Corporations – Growth – Mathematical models"

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Sapi, Johanna, Daniel Andras Drexler et Levente Kovacs. « Comparison of mathematical tumor growth models ». Dans 2015 IEEE 13th International Symposium on Intelligent Systems and Informatics (SISY). IEEE, 2015. http://dx.doi.org/10.1109/sisy.2015.7325403.

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Silova, Elena, Irina Belova et Daria Bents. « Model of Growth of the Russian Corporations : Impaction of Institutional Factors ». Dans International Conference on Eurasian Economies. Eurasian Economists Association, 2014. http://dx.doi.org/10.36880/c05.00932.

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In modern conditions corporations are a core of economic system and many macroeconomic indicators depend on growth of corporations. Quality and intensity of growth of corporations depend on many factors, both internal, and external. Institutional factors, including efficiency of the contract relations, level of tax burden, quality of corporate institutes have huge impact on growth of corporations. The purpose of this work – to reveal factors of growth of the Russian corporations and to construct models of the Russian corporations’ growth in a branch section. In research the assessment influence of tax loading on efficiency of the contract relations and growth of the Russian corporations is carried out. The analysis of growth of the Russian corporations in various branches (oil and gas, metallurgy, power industry) is carried out and models of their growth taking into account such factors, as tax burden, level of dividend payments and level of compensation of the administrative personnel are constructed. The degree of tax burden to efficiency improvement of contractual relations in Russian corporations was analyzed. The growth rate of sales revenue was taken as an indicator of the corporation efficiency. The factors influencing the growth rate of sales revenue were analyzed, the basis for the analysis was Cobb-Douglas production function with some clarifications.
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SPOHN, HERBERT, PATRIK L. FERRARI et MICHAEL PRÄHOFER. « Stochastic growth in one dimension and Gaussian multi-matrix models ». Dans XIVth International Congress on Mathematical Physics. WORLD SCIENTIFIC, 2006. http://dx.doi.org/10.1142/9789812704016_0038.

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El-Kareh, Ardith W., et Timothy W. Secomb. « Abstract 102 : Mathematical models for growth of metastatic tumors ». Dans Proceedings : AACR 101st Annual Meeting 2010‐‐ Apr 17‐21, 2010 ; Washington, DC. American Association for Cancer Research, 2010. http://dx.doi.org/10.1158/1538-7445.am10-102.

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Korkmaz, Mehmet. « Partial sum approaches to mathematical parameters of some growth models ». Dans INTERNATIONAL CONFERENCE ON ADVANCES IN NATURAL AND APPLIED SCIENCES : ICANAS 2016. Author(s), 2016. http://dx.doi.org/10.1063/1.4945903.

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Zhang, Chao, Xiaoqian Jiang, Sheng Guo et Qixiang Li. « Abstract 4613 : Mathematical modeling of tumor growth in mouse models ». Dans Proceedings : AACR Annual Meeting 2019 ; March 29-April 3, 2019 ; Atlanta, GA. American Association for Cancer Research, 2019. http://dx.doi.org/10.1158/1538-7445.sabcs18-4613.

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Zhang, Chao, Xiaoqian Jiang, Sheng Guo et Qixiang Li. « Abstract 4613 : Mathematical modeling of tumor growth in mouse models ». Dans Proceedings : AACR Annual Meeting 2019 ; March 29-April 3, 2019 ; Atlanta, GA. American Association for Cancer Research, 2019. http://dx.doi.org/10.1158/1538-7445.am2019-4613.

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Aleixo, Sandra M., J. Leonel Rocha, Dinis D. Pestana, Alberto Cabada, Eduardo Liz et Juan J. Nieto. « Populational Growth Models Proportional to Beta Densities with Allee Effect ». Dans MATHEMATICAL MODELS IN ENGINEERING, BIOLOGY AND MEDICINE : International Conference on Boundary Value Problems : Mathematical Models in Engineering, Biology and Medicine. AIP, 2009. http://dx.doi.org/10.1063/1.3142952.

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Saribudak, Aydin, Emir Ganic, Jianmin Zou, Stephen Gundry et M. Umit Uyar. « Toward Genomic Based Personalized Mathematical Models for Breast Cancer Tumor Growth ». Dans 2014 IEEE International Conference on Bioinformatics and Bioengineering (BIBE). IEEE, 2014. http://dx.doi.org/10.1109/bibe.2014.50.

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Aygün, Ali, et Doğan Narinç. « Flexible and fixed mathematical models describing growth patterns of chukar partridges ». Dans INTERNATIONAL CONFERENCE ON ADVANCES IN NATURAL AND APPLIED SCIENCES : ICANAS 2016. Author(s), 2016. http://dx.doi.org/10.1063/1.4945840.

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Rapports d'organisations sur le sujet "Corporations – Growth – Mathematical models"

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Lieth, J. Heiner, Michael Raviv et David W. Burger. Effects of root zone temperature, oxygen concentration, and moisture content on actual vs. potential growth of greenhouse crops. United States Department of Agriculture, janvier 2006. http://dx.doi.org/10.32747/2006.7586547.bard.

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Résumé :
Soilless crop production in protected cultivation requires optimization of many environmental and plant variables. Variables of the root zone (rhizosphere) have always been difficult to characterize but have been studied extensively. In soilless production the opportunity exists to optimize these variables in relation to crop production. The project objectives were to model the relationship between biomass production and the rhizosphere variables: temperature, dissolved oxygen concentration and water availability by characterizing potential growth and how this translates to actual growth. As part of this we sought to improve of our understanding of root growth and rhizosphere processes by generating data on the effect of rhizosphere water status, temperature and dissolved oxygen on root growth, modeling potential and actual growth and by developing and calibrating models for various physical and chemical properties in soilless production systems. In particular we sought to use calorimetry to identify potential growth of the plants in relation to these rhizosphere variables. While we did experimental work on various crops, our main model system for the mathematical modeling work was greenhouse cut-flower rose production in soil-less cultivation. In support of this, our objective was the development of a Rose crop model. Specific to this project we sought to create submodels for the rhizosphere processes, integrate these into the rose crop simulation model which we had begun developing prior to the start of this project. We also sought to verify and validate any such models and where feasible create tools that growers could be used for production management. We made significant progress with regard to the use of microcalorimetry. At both locations (Israel and US) we demonstrated that specific growth rate for root and flower stem biomass production were sensitive to dissolved oxygen. Our work also identified that it is possible to identify optimal potential growth scenarios and that for greenhouse-grown rose the optimal root zone temperature for potential growth is around 17 C (substantially lower than is common in commercial greenhouses) while flower production growth potential was indifferent to a range as wide as 17-26C in the root zone. We had several set-backs that highlighted to us the fact that work needs to be done to identify when microcalorimetric research relates to instantaneous plant responses to the environment and when it relates to plant acclimation. One outcome of this research has been our determination that irrigation technology in soilless production systems needs to explicitly include optimization of oxygen in the root zone. Simply structuring the root zone to be “well aerated” is not the most optimal approach, but rather a minimum level. Our future work will focus on implementing direct control over dissolved oxygen in the root zone of soilless production systems.
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