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1
Oliveri, Hadrien, and Alain Goriely. "Mathematical models of neuronal growth." Biomechanics and Modeling in Mechanobiology 21, no. 1 (January 7, 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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Tedeschi, Luís Orlindo, Danny Gene Fox, Roberto Daniel Sainz, Luís Gustavo Barioni, Sérgio Raposo de Medeiros, and Celso Boin. "Mathematical models in ruminant nutrition." Scientia Agricola 62, no. 1 (January 2005): 76–91. http://dx.doi.org/10.1590/s0103-90162005000100015.
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Mathematical models can be used to improve performance, reduce cost of production, and reduce nutrient excretion by accounting for more of the variation in predicting requirements and feed utilization in each unique production situation. Mathematical models can be classified into five or more categories based on their nature and behavior. Determining the appropriate level of aggregation of equations is a major problem in formulating models. The most critical step is to describe the purpose of the model and then to determine the appropriate mix of empirical and mechanistic representations of physiological functions, given development and evaluation dataset availability, inputs typically available and the benefits versus the risks of use associated with increased sensitivity. We discussed five major feeding systems used around the world. They share common concepts of energy and nutrient requirement and supply by feeds, but differ in structure and application of the concepts. Animal models are used for a variety of purposes, including the simple description of observations, prediction of responses to management, and explanation of biological mechanisms. Depending upon the objectives, a number of different approaches may be used, including classical algebraic equations, predictive empirical relationships, and dynamic, mechanistic models. The latter offer the best opportunity to make full use of the growing body of knowledge regarding animal biology. Continuing development of these types of models and computer technology and software for their implementation holds great promise for improvements in the effectiveness with which fundamental knowledge of animal function can be applied to improve animal agriculture and reduce its impact on the environment.
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Meena, Ayush, Tushar Sharma, Mohit Patodiya, and P. V. Ramana. "Chronology of Recycled Plastic Mathematical Models, Mechanical and Thermal Characterisation." Proceedings of the 12th Structural Engineering Convention, SEC 2022: Themes 1-2 1, no. 1 (December 19, 2022): 499–506. http://dx.doi.org/10.38208/acp.v1.540.
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Recycled plastic fibers restrict the characteristics of hardened concrete. They offer no considerable ductility after the initial fracture. Their capacity to prevent bleed and separation helps preserve the original water-cemetery ratio of the surface mortar, thereby enhancing the abrasion resistance. Recycled plastic fibers can be efficient in dispersing stresses and improving frost resistance. The spilling of concrete into the fire has also proven to reduce. Recycled plastic fibers enhance initial characteristics in sprayed concrete and decrease the shedding and rebound. The tiny recycled plastic fibers, which should have similar structural advantages to steel fibers, must be distinguished from giant synthetic fibers. PP is fully resistant to acid and alkaline circumstances and is not affected by acid/alkaline environments, including marine conditions. Chemically PP is non-absorbent, i.e., no moisture absorption and associated characteristic changes.
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Plotnitsky, Arkady. "The visualizable, the representable and the inconceivable: realist and non-realist mathematical models in physics and beyond." Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences 374, no. 2058 (January 13, 2016): 20150101. http://dx.doi.org/10.1098/rsta.2015.0101.
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The project of this article is twofold. First, it aims to offer a new perspective on, and a new argument concerning, realist and non-realist mathematical models, and differences and affinities between them, using physics as a paradigmatic field of mathematical modelling in science. Most of the article is devoted to this topic. Second, the article aims to explore the implications of this argument for mathematical modelling in other fields, in particular in cognitive psychology and economics.
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Shain, Kenneth H. "Mathematical Models of Cancer Evolution and Cure." Blood 126, no. 23 (December 3, 2015): SCI—55—SCI—55. http://dx.doi.org/10.1182/blood.v126.23.sci-55.sci-55.
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You cannot cure what you do not understand. So how can mathematical modeling address this pressing issue? The advances in therapeutic success in multiple myeloma over the last decades have hinged on an an army of researchers identifying a critical genetic, epigenetic and biochemical signaling factors within of MM cells as well as the tumor microenvironment (TME). Unfortunately, despite these large scale efforts we do not yet offer our patients curative intent therapy. The inability to provide curative therapy, especially in the setting of HRMM, is characterized by evolving resistance to lines of sequential therapy as a result of alternating clonal dynamics following the failure of initial therapy to eradicate minimal residual disease (MRD). Recent results underline the importance of tumor heterogeneity, in the form of pre-existing genotypically (and phenotypically) distinct sub-populations that translate to drug-resistant phenotypes leading to treatment failure. This phenomenon of “clonal tides”, has been well characterized using contemporary molecular techniques demonstrating that clonal evolution progresses by different evolutionary patterns across patients. Thus, resistance to therapy is a consequence of Darwinian dynamics- influenced by tumor heterogeneity, genomic instability, the TME (ecosystem), and selective pressures induced by therapy. Such evolutionary principles can be analyzed and exploited by mathematical models to personalize therapeutic options for patients with MM. Currently available clinical decision support tools and physician acumen are not able to account for the shear amount of information available. Mathematical models, however, provide a critical mechanism(s) to account of the large number of aspects to help predict and manage MM- accounting for what we do not know. Models can be designed with the specific intent of characterizing intra-tumoral heterogeneity, changing ecosystems, and clinical parameters over time to create patient-specific clinical predictions much like hurricane prediction models. This can only be achieved by creating mathematical models parameterized by longitudinal data of a number of parameters. The novel application of mathematical models based on Darwinian dynamics can be imputed with data to 1) predict progression events (risk of progression to from smoldering to active MM), 2) relapse, and 3) predictions of clinical response of MM patients for the optimizing therapeutics for cure or optimal control of MM; thus, providing invaluable clinical decision support tools. Disclosures: Shain: Celgene: Consultancy , Speakers Bureau ; Amgen/Onyx: Consultancy , Speakers Bureau ; Takeda: Consultancy , Speakers Bureau ; Signal Genetics: Consultancy , Research Funding.
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Mu, Lian Yun, and Yong Wei. "Evaluation on Effectiveness of Weapon Equipment Based on Grade Conversion Operations." Applied Mechanics and Materials 313-314 (March 2013): 733–36. http://dx.doi.org/10.4028/www.scientific.net/amm.313-314.733.
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Mathematical models and statistical models of effectiveness were set up during the technology preparation period. A model and flow was set up based on the system parameters and using regulation applying the theory of Monte-Carlo sampling, discrete event simulation and mathematical statistical. Results of its application show that the model can not only simulate effectiveness of equipment weapon, but also can analysis sensitivity, can offer auxiliary decision-making during the technology preparation period.
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Asadi, Houshyar, Shady Mohamed, Chee Peng Lim, Saeid Nahavandi, and Eugene Nalivaiko. "Semicircular canal modeling in human perception." Reviews in the Neurosciences 28, no. 5 (July 26, 2017): 537–49. http://dx.doi.org/10.1515/revneuro-2016-0058.
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AbstractThe human vestibular system is a sensory and equilibrium system that manages and controls the human sense of balance and movement. It is the main sensor humans use to perceive rotational and linear motions. Determining an accurate mathematical model of the human vestibular system is significant for research pertaining to motion perception, as the quality and effectiveness of the motion cueing algorithm (MCA) directly depends on the mathematical model used in its design. This paper describes the history and analyses the development process of mathematical semicircular canal models. The aim of this review is to determine the most consistent and reliable mathematical semicircular canal models that agree with experimental results and theoretical analyses, and offer reliable approximations for the semicircular canal functions based on the existing studies. Selecting and formulating accurate mathematical models of semicircular canals are essential for implementation into the MCA and for ensuring effective human motion perception modeling.
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Christianto, Victor, and Yunita Umniyati. "Remark on ‘The future of mathematical Cosmology” and “100 years of mathematical cosmology: Models, theories and problems, Part B” by S. Cotsakis and A.P. Yefremov." Journal of Cosmology, Filaments and Astrobiology 2, no. 1 (2022): 38–41. http://dx.doi.org/10.54216/jcfa.020105.
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In this review article, allow us to offer a few remark on “the future of mathematical cosmology” “100 years of mathematical cosmology: Models, theories and problems, Part B” by Cotsakis and Yefremov, which seems to us very interesting piece of review on progress on the last 3 or 4 decades in theoretical cosmology development. In particular, we would emphasize on testability of cosmology models, which seem to us this criterion can only be achieved via correspondence between condensed mattersuperfluiditylow temperature physics and cosmology (cf. for instance, Kibble Pickett, 2008).
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Ernst, Philip A., Marek Kimmel, Monika Kurpas, and Quan Zhou. "Heavy-tailed distributions in branching process models of secondary cancerous tumors." Advances in Applied Probability 50, A (December 2018): 99–114. http://dx.doi.org/10.1017/apr.2018.73.
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Abstract Recent progress in microdissection and in DNA sequencing has facilitated the subsampling of multi-focal cancers in organs such as the liver in several hundred spots, helping to determine the pattern of mutations in each of these spots. This has led to the construction of genealogies of the primary, secondary, tertiary, and so forth, foci of the tumor. These studies have led to diverse conclusions concerning the Darwinian (selective) or neutral evolution in cancer. Mathematical models of the development of multi-focal tumors have been devised to support these claims. We offer a model for the development of a multi-focal tumor: it is a mathematically rigorous refinement of a model of Ling et al. (2015). Guided by numerical studies and simulations, we show that the rigorous model, in the form of an infinite-type branching process, displays distributions of tumor size which have heavy tails and moments that become infinite in finite time. To demonstrate these points, we obtain bounds on the tails of the distributions of the process and an infinite series expansion for the first moments. In addition to its inherent mathematical interest, the model is corroborated by recent literature on apparent super-exponential growth in cancer metastases.
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Cortés Pellicer, Pascual, and Faustino Alarcón Valero. "Identification of reverse logistics decision types from mathematical models." Journal of Industrial Engineering and Management 11, no. 2 (April 6, 2018): 239. http://dx.doi.org/10.3926/jiem.2530.
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Purpose: The increase in social awareness, politics and environmental regulation, the scarcity of raw materials and the desired “green” image, are some of the reasons that lead companies to decide for implement processes of Reverse Logistics (RL). At the time when incorporate new RL processes as key business processes, new and important decisions need to be made. Identification and knowledge of these decisions, including the information available and the implications for the company or supply chain, will be fundamental for decision-makers to achieve the best results. In the present work, the main types of RL decisions are identified.Design/methodology/approach: This paper is based on the analysis of mathematical models designed as tools to aid decision making in the field of RL. Once the types of interest work to be analyzed are defined, those studies that really deal about the object of study are searched and analyzed. The decision variables that are taken at work are identified and grouped according to the type of decision and, finally, are showed the main types of decisions used in mathematical models developed in the field of RL. Findings: The principal conclusion of the research is that the most commonly addressed decisions with mathematical models in the field of RL are those related to the network’s configuration, followed by tactical/operative decisions such as the selections of product’s treatments to realize and the policy of returns or prices, among other decisions.Originality/value: The identification of the main decisions types of the reverse logistics will allow the managers of these processes to know and understand them better, while offer an integrated vision of them, favoring the achievement of better results.
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Clarke, David C., and Philip F. Skiba. "Rationale and resources for teaching the mathematical modeling of athletic training and performance." Advances in Physiology Education 37, no. 2 (June 2013): 134–52. http://dx.doi.org/10.1152/advan.00078.2011.
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A number of professions rely on exercise prescription to improve health or athletic performance, including coaching, fitness/personal training, rehabilitation, and exercise physiology. It is therefore advisable that the professionals involved learn the various tools available for designing effective training programs. Mathematical modeling of athletic training and performance, which we henceforth call “performance modeling,” is one such tool. Two models, the critical power (CP) model and the Banister impulse-response (IR) model, offer complementary information. The CP model describes the relationship between work rates and the durations for which an individual can sustain them during constant-work-rate or intermittent exercise. The IR model describes the dynamics by which an individual's performance capacity changes over time as a function of training. Both models elegantly abstract the underlying physiology, and both can accurately fit performance data, such that educating exercise practitioners in the science of performance modeling offers both pedagogical and practical benefits. In addition, performance modeling offers an avenue for introducing mathematical modeling skills to exercise physiology researchers. A principal limitation to the adoption of performance modeling is a lack of education. The goal of this report is therefore to encourage educators of exercise physiology practitioners and researchers to incorporate the science of performance modeling in their curricula and to serve as a resource to support this effort. The resources include a comprehensive review of the concepts associated with the development and use of the models, software to enable hands-on computer exercises, and strategies for teaching the models to different audiences.
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Sancho-Araiz, Aymara, Victor Mangas-Sanjuan, and Iñaki F. Trocóniz. "The Role of Mathematical Models in Immuno-Oncology: Challenges and Future Perspectives." Pharmaceutics 13, no. 7 (July 2, 2021): 1016. http://dx.doi.org/10.3390/pharmaceutics13071016.
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Immuno-oncology (IO) focuses on the ability of the immune system to detect and eliminate cancer cells. Since the approval of the first immune checkpoint inhibitor, immunotherapies have become a major player in oncology treatment and, in 2021, represented the highest number of approved drugs in the field. In spite of this, there is still a fraction of patients that do not respond to these therapies and develop resistance mechanisms. In this sense, mathematical models offer an opportunity to identify predictive biomarkers, optimal dosing schedules and rational combinations to maximize clinical response. This work aims to outline the main therapeutic targets in IO and to provide a description of the different mathematical approaches (top-down, middle-out, and bottom-up) integrating the cancer immunity cycle with immunotherapeutic agents in clinical scenarios. Among the different strategies, middle-out models, which combine both theoretical and evidence-based description of tumor growth and immunological cell-type dynamics, represent an optimal framework to evaluate new IO strategies.
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Minjarez-Sosa, Carlos Manuel, and Julio Waissman. "A Survey and Perspectives on Mathematical Models for Quantitative Precipitation Estimation Using Lightning." Advances in Meteorology 2017 (2017): 1–11. http://dx.doi.org/10.1155/2017/1351308.
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Lightning is one of the most spectacular phenomena in nature. It is produced when there is a breakdown in the resistance in the electric field between the ground and an electrically charged cloud. By simple observation, we observe that precipitation, especially the most intense, is often accompanied by lightning. Given this observation, lightning has been employed to estimate convective precipitation since 1969. In early studies, mathematical models were deduced to quantify this relationship and used to estimate precipitation. Currently, the use of several techniques to estimate precipitation is gaining momentum, and lightning is one of the novel techniques to complement the traditional techniques for Quantitative Precipitation Estimation. In this paper, the authors provide a survey of the mathematical methods employed to estimate precipitation through the use of cloud-to-ground lightning. We also offer a perspective on the future research to this end.
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Gürbüz, Ramazan, and Muammer Çalık. "INTERTWINING MATHEMATICAL MODELING WITH ENVIRONMENTAL ISSUES." Problems of Education in the 21st Century 79, no. 3 (June 10, 2021): 412–24. http://dx.doi.org/10.33225/pec/21.79.412.
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Since contemporary learning theories, strategies and models offer the interdisciplinary approach, educators need new pedagogical alternative ways to attain it in practicum. For this reason, the current research aimed to illustrate how to intertwine mathematical modeling with an environmental issue that recruits waste management (e.g., reuse-recycle-reduce) to live an environmentally friendly lifestyle. Through a case study research, 6 seventh-grade students (3 females and 3 males; aged 13-14) voluntarily participated in the research. The researchers videotaped and analyzed all interactive learning processes to elicit the students’ environmental dialogues. The results indicated that the interdisciplinary mathematical modeling afforded the students to acquire the targeted environmental concepts/issues and somewhat supported their arguments. Since the current research illustrates an alternative pedagogy to integrate science/environmental education into mathematics, it may be used to facilitate dissemination and applicability of the STEM education. Keywords: environmental issues, interdisciplinary approach, mathematical modeling
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Eliaš, Ján, and Cicely K. Macnamara. "Mathematical Modelling of p53 Signalling during DNA Damage Response: A Survey." International Journal of Molecular Sciences 22, no. 19 (September 30, 2021): 10590. http://dx.doi.org/10.3390/ijms221910590.
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No gene has garnered more interest than p53 since its discovery over 40 years ago. In the last two decades, thanks to seminal work from Uri Alon and Ghalit Lahav, p53 has defined a truly synergistic topic in the field of mathematical biology, with a rich body of research connecting mathematic endeavour with experimental design and data. In this review we survey and distill the extensive literature of mathematical models of p53. Specifically, we focus on models which seek to reproduce the oscillatory dynamics of p53 in response to DNA damage. We review the standard modelling approaches used in the field categorising them into three types: time delay models, spatial models and coupled negative-positive feedback models, providing sample model equations and simulation results which show clear oscillatory dynamics. We discuss the interplay between mathematics and biology and show how one informs the other; the deep connections between the two disciplines has helped to develop our understanding of this complex gene and paint a picture of its dynamical response. Although yet more is to be elucidated, we offer the current state-of-the-art understanding of p53 response to DNA damage.
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Wang, Li Hui, Xue Feng Wu, Jian Sun, and Yu Ping Lu. "Methods to Describe Optical Polarization State in Reflective Fiber Optic Current Sensor." Applied Mechanics and Materials 44-47 (December 2010): 2254–58. http://dx.doi.org/10.4028/www.scientific.net/amm.44-47.2254.
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Evolution process of optical polarization state in reflective fiber optic current sensor(R-FOCS) is complex, light wave travels from polarization maintaining (PM) fiber with linear polarization state, and light wave travels from sensing head with circular polarization state. Focused on characteristics of optical polarization state in R-FOCS, we analyze the characteristics of optical polarization state in R-FOCS, and demonstrate the methods to build optical polarization models by using Poincare sphere and Jones matrix respectively. Jones matrix provides a mathematically rigorous method of tracking optical polarization state, however, it often leads to a less intuitive description. Despite the mathematical complexity of some phenomena observed in R-FOCS, the Poincare sphere provides elegant and simple geometrical interpretations. The two methods are combined and offer both a mathematical representation and an intuitive interpretation of nonreciprocal polarization effects in R-FOCS.
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Almarri, B., and A. A. Azzam. "Energy Saving via a Minimal Structure." Mathematical Problems in Engineering 2022 (June 15, 2022): 1–6. http://dx.doi.org/10.1155/2022/5450344.
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Not only mathematical statistics, differential equations, and mathematical models were used to analyze and reduce data, but a rough set model is also employed in medical, engineering, and other fields to analyze and reduce them. The goal of this paper is to introduce a minimal structure concept to produce new rough set models and show that it is suitable for analyzing most real-life problems, reduction of attributes, and decision making. We examine the effectiveness of the following method in the problem of electric power generators and decision making. We also offer a comparison of our method and Pawlak’s method. Finally, the variable precision model improves the accuracy of decision making.
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Piskur, Pawel, Piotr Szymak, and Bartosz Larzewski. "Shipyard Crane Modeling Methods." Pedagogika-Pedagogy 93, no. 6s (August 31, 2021): 279–90. http://dx.doi.org/10.53656/ped21-6s.25shi.
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The article discusses various crane mathematical modelling and simulation methodologies. The purpose of this study is to assess the effect of wind force on the dynamic of shipyard cranes, particularly hook movements in the horizontal plane. Appropriate simulation models are required to offer a robust control strategy that allows the crane to be remotely operated in windy circumstances. As a result, mathematical models based on differential equations for varying numbers of independent variables are compared to object-oriented, physical modelling model based on Matlab Simscape Multibody. The assumptions are explored, as well as the effect of the number of independent variables on model correctness.
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Pilipenko, Aleksandr, and Sergei Petrov. "Computer Simulation and Modelling System of Non-Stationary Heat Exchange Processes." MATEC Web of Conferences 155 (2018): 01036. http://dx.doi.org/10.1051/matecconf/201815501036.
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This article suggests the solution to the up-to-date task of improving and increasing the energy efficiency of buildings and quality of functioning of systems, controlling boilers and heating devices, by using computer simulation and modelling of heat exchange processes of the building and operation of the heating systems. The authors present proven (checked) mathematical models, applicable for external protections, rooms, heaters, boilers, insulated and non-insulated piping. The authors offer an automated system of computer simulation and modelling, which not only allows us to solve mathematical models, but also to complement them with information from a real object and improve them by introducing corrective factors and coefficients.
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Ravand, Zahra Ghorbani, and Qi Xu. "Evaluation of Mathematical Models in Sustainable Supply Chain Management: Gap Analysis." International Business Research 14, no. 10 (August 31, 2021): 25. http://dx.doi.org/10.5539/ibr.v14n10p25.
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The main purpose of this paper is to present a comprehensive view of the application mathematical models in the designing and implementing SSCM beside to solving problems and making decision. The research questions are: what kind of mathematical models are used for designing and implementing sustainable supply chain management, how to use them, which industries implemented in, what modules of SSCM depth in and finally finding the gaps between the goals of Sustainable development and current researches and suggestions for further researches.
The methodology of the research is Systematic Literature review and evaluation peer review papers which are published in high ranking journals: First, we gather all papers through scientific data bases like Scopus, science direct, MDPI, Springer, Google Scholar. Then, screening papers based on the criteria such as object of paper, subject of paper, journals impact factor, peer review paper, and relative content of the papers. Finally, we selected 245 papers through three steps screening from 2806 papers that they have enough quality and relative to our research goals for context analysis.
For context analysis: First we categorize the information of the papers and draw the current situation of researches in the framework of our topic. Then, we evaluate and compare the goals of sustainability and current situation and find the gapes, then, offer suggestions required researches for pollutant industries such as Casting Industry, Heavy Industry, Coal Industry and so on. On the other hand, there are gaps in researches in some modules of SSCM such as packaging, designing products, etc.
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Li, Baojiu. "Approximation methods in modified gravity models." International Journal of Modern Physics D 27, no. 15 (November 2018): 1848004. http://dx.doi.org/10.1142/s0218271818480048.
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We review some of the commonly used approximation methods to predict large-scale structure formation in modified gravity (MG) models for the cosmic acceleration. These methods are developed to speed up the often slow [Formula: see text]-body simulations in these models, or directly make approximate predictions of relevant physical quantities. In both cases, they are orders of magnitude more efficient than full simulations, making it possible to explore and delineate the large cosmological parameter space. On the other hand, there is a wide variation of their accuracies and ranges of validity, and these are usually not known a priori and must be validated against simulations. Therefore, a combination of full simulations and approximation methods will offer both efficiency and reliability. The approximation methods are also important from a theoretical point of view, since they can often offer useful insight into the nonlinear physics in MG models and inspire new algorithms for simulations.
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Gentile, Nelida. "The Scope of the Construction of Experience in Empiricist Structuralism." Principia: an international journal of epistemology 21, no. 3 (May 7, 2018): 445–59. http://dx.doi.org/10.5007/1808-1711.2017v21n3p445.
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In his attempt to put forward an empiricist version of structuralism, van Fraassen develops an approach to scientific representation and models which has been the object of several critiques. Here we cover the “Loss of Reality Objection”, namely, that reality itself would play no role in science if science could only refer to mathematical models. We examine and dismiss the solution offered by van Fraassen. Finally, we offer an alternative solution path.
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Law, Helen. "Why do adolescent boys dominate advanced mathematics subjects in the final year of secondary school in Australia?" Australian Journal of Education 62, no. 2 (July 23, 2018): 169–91. http://dx.doi.org/10.1177/0004944118776458.
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In Australia, many students, especially girls, choose not to study advanced mathematics in Year 12 even though their schools offer relevant subjects. Previous studies have rarely examined, using nationally representative samples of Australian students, the extent to which teenage educational experiences and occupational expectations influence gender differences in later pursuits of advanced mathematics subjects. To fill this gap, I use multilevel logistic regression models to analyse the data from the 2003 cohort of the Longitudinal Survey of Australian Youth. My results show that students’ mathematics achievement, occupational expectations and self-assessed mathematical competence are crucial in explaining why boys are considerably more likely than girls to enrol in advanced mathematics subjects. The gender gap would decrease greatly if girls were as likely as boys to perform well in mathematics, to aspire to mathematically intensive careers and to have more confidence in their mathematical abilities when they were 15 years old.
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Plebankiewicz, Edyta. "MODELLING DECISION-MAKING PROCESSES IN BIDDING PROCEDURES WITH THE USE OF THE FUZZY SETS THEORY." International Journal of Strategic Property Management 18, no. 3 (September 18, 2014): 307–16. http://dx.doi.org/10.3846/1648715x.2014.943332.
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In the bidding procedure not only the contractor but also the construction owner make a number of vital decisions, the consequences of which are significant. The contractor has to decide whether to take part in a given bid and, having been accepted, he/she has to prepare a bidding offer. Its essential element is the mark-up introduced to the calculation of the bidding price. On the other hand, the investing construction owner has to decide which contractors are the closest to his/her requirements. The article presents mathematical models concerning the decisions made by the contractor and construction owner in the bidding procedure. All the models are based on the same simple mathematical apparatus using fuzzy sets.
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Rodiger, Tibor, Edgar Glavaš, and Ivan Kovač. "The first year of covid-19 in croatia - a mathematical model." Croatian Regional Development Journal 2, no. 2 (December 1, 2021): 32–44. http://dx.doi.org/10.2478/crdj-2021-0012.
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Abstract The new coronavirus has spread around the world at an unprecedented speed. Understanding patterns of disease spread is an important contribution to controlling any epidemic, and today’s mathematical methods offer a plethora of proven models to choose from. We provide a brief overview of epidemiological concepts, papers pertaining to mathematical modelling, and present a robust, simple mathematical model to model incidence of COVID-19 cases in Croatia during the first year of the disease. For our models, we chose logistic, Gumbel and Richards functions, with parameters generated using the Levenberg-Marquardt iterative method of nonlinear regression. In conclusion, all three models provided adequate estimation of incidence curve and final number of infected during the chosen time period, with relatively minor differences depending on chosen parameters of significance. The model using the logistic function proved to be the most applicable to available data. While no model can give the answers to ending the pandemic, this approach can provide a simple prognostic tool to evaluate interventions and estimate disease spread.
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Liu, Mao Fu, Xiong Hua Guo, and Hui Xian Han. "A Design-Analysis and Simulation Approach of Ball-End Cutter Based on OpenGL." Advanced Materials Research 139-141 (October 2010): 1281–84. http://dx.doi.org/10.4028/www.scientific.net/amr.139-141.1281.
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A design-analysis and simulation approach of complex ball-end cutter was proposed by using computer graphics and OpenGL control in this paper. The mathematical models of rake face and flank face of a complex ball-end cutter were built as the simulation condition. A computer-aided design and simulation processing system of complex tool was presented through pre-modeling OpenGL control. Some 3D simulation models of complex ball-end cutter including spiral cylinder, ball-head (including rake face, chip groove, first flank face and second flank face) and grinding wheel were created respectively. According to mathematical models and VC++ software platform, transformation and machining animation simulations of ball-end cutter were designed and realized visually using OpenGL control interface technique. The results of Three-dimensional design and simulation will offer sufficient theory foundation for virtually manufacturing ball-end cutter.
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Kosiret, Andri, Fariani Hermin Indiyah, and Dwi Antari Wijayanti. "The Use of Generative Learning Model in Improving Students’ Understanding of Mathematical Concepts of Al-Azhar 19 Islamic High School." International Journal of Progressive Mathematics Education 1, no. 1 (March 9, 2021): 16–26. http://dx.doi.org/10.22236/ijopme.v1i1.6593.
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Background. Distance learning during the COVID-19 pandemic has changed the landscape of mathematics learning as a whole. One of the mathematics learning models that offer new concepts in distance learning is generative learning model. The Aim of the Research. This study will evaluate the effectiveness of the implementation of generative learning models in improving students' mathematical understanding abilities. The appropriate research method to test the effectiveness is quasi-experimental design because the class being experimented with is not changed, so that it does not have much effect on overall learning stability. The research sample used cluster random sampling technique where class X MIPA 3 was the experimental class while class X MIPA 2 was the control class. The research instrument used was a test of students' ability to understand mathematical concepts in the material of Logarithmic Equations as many as seven essay questions. Conclusion. There is an effect (high) of the generative learning model on the ability to understand students' mathematical concepts applied to the distance learning system at Al-Azhar 19 Ciracas Islamic Senior High School logarithmic equation material with a significance level of α = 0.05. Contribution. This study offers a new concept for the application of distance learning mathematics by implementing a generative learning model which in this study has contributed positively to student understanding
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Bazargan, Massoud. "Airline maintenance strategies – in-house vs. outsourced – an optimization approach." Journal of Quality in Maintenance Engineering 22, no. 2 (May 9, 2016): 114–29. http://dx.doi.org/10.1108/jqme-08-2015-0038.
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Purpose – The purpose of this paper is to offer a new mathematical modeling approach to help airlines identify which types of heavy aircraft maintenance checks be performed in-house or outsourced. Design/methodology/approach – This study offers a mathematical model to minimize the total cost of heavy maintenance programs over a planning period subject to performing all maintenance programs on time and other side constraints. Findings – The results are very encouraging and somewhat counter-intuitive. The solutions recommend that more expensive and labor intensive checks be outsourced. A detailed analyses of the total maintenance cost breakdown is presented with implications and recommendation. Originality/value – To the best of the knowledge, the literature on quantitative models for airline in-house and outsourced maintenance checks is very limited. The author believes the model and airline cases presented in this paper can help airlines with their strategic maintenance strategies and will initiate further studies in this important area.
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Souza, Fernando, and Adolfo Maia Jr. "A Mathematical, Graphical and Visual Approach to Granular Synthesis Composition." Revista Vórtex 9, no. 2 (December 10, 2021): 1–27. http://dx.doi.org/10.33871/23179937.2021.9.2.4.
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We show a method for Granular Synthesis Composition based on a mathematical modeling for the musical gesture. Each gesture is drawn as a curve generated from a particular mathematical model (or function) and coded as a MATLAB script. The gestures can be deterministic through defining mathematical time functions, hand free drawn, or even randomly generated. This parametric information of gestures is interpreted through OSC messages by a granular synthesizer (Granular Streamer). The musical composition is then realized with the models (scripts) written in MATLAB and exported to a graphical score (Granular Score). The method is amenable to allow statistical analysis of the granular sound streams and the final music composition. We also offer a way to create granular streams based on correlated pair of grains parameters.
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Haurie, Caroline, David C. Dale, and Michael C. Mackey. "Cyclical Neutropenia and Other Periodic Hematological Disorders: A Review of Mechanisms and Mathematical Models." Blood 92, no. 8 (October 15, 1998): 2629–40. http://dx.doi.org/10.1182/blood.v92.8.2629.
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Abstract Although all blood cells are derived from hematopoietic stem cells, the regulation of this production system is only partially understood. Negative feedback control mediated by erythropoietin and thrombopoietin regulates erythrocyte and platelet production, respectively, but the regulation of leukocyte levels is less well understood. The local regulatory mechanisms within the hematopoietic stem cells are also not well characterized at this point. Because of their dynamic character, cyclical neutropenia and other periodic hematological disorders offer a rare opportunity to more fully understand the nature of these regulatory processes. We review the salient clinical and laboratory features of cyclical neutropenia (and the less common disorders periodic chronic myelogenous leukemia, periodic auto-immune hemolytic anemia, polycythemia vera, aplastic anemia, and cyclical thrombocytopenia) and the insight into these diseases afforded by mathematical modeling. We argue that the available evidence indicates that the locus of the defect in most of these dynamic diseases is at the stem cell level (auto-immune hemolytic anemia and cyclical thrombocytopenia seem to be the exceptions). Abnormal responses to growth factors or accelerated cell loss through apoptosis may play an important role in the genesis of these disorders. © 1998 by The American Society of Hematology.
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Haurie, Caroline, David C. Dale, and Michael C. Mackey. "Cyclical Neutropenia and Other Periodic Hematological Disorders: A Review of Mechanisms and Mathematical Models." Blood 92, no. 8 (October 15, 1998): 2629–40. http://dx.doi.org/10.1182/blood.v92.8.2629.420a35_2629_2640.
Full textAbstract:
Although all blood cells are derived from hematopoietic stem cells, the regulation of this production system is only partially understood. Negative feedback control mediated by erythropoietin and thrombopoietin regulates erythrocyte and platelet production, respectively, but the regulation of leukocyte levels is less well understood. The local regulatory mechanisms within the hematopoietic stem cells are also not well characterized at this point. Because of their dynamic character, cyclical neutropenia and other periodic hematological disorders offer a rare opportunity to more fully understand the nature of these regulatory processes. We review the salient clinical and laboratory features of cyclical neutropenia (and the less common disorders periodic chronic myelogenous leukemia, periodic auto-immune hemolytic anemia, polycythemia vera, aplastic anemia, and cyclical thrombocytopenia) and the insight into these diseases afforded by mathematical modeling. We argue that the available evidence indicates that the locus of the defect in most of these dynamic diseases is at the stem cell level (auto-immune hemolytic anemia and cyclical thrombocytopenia seem to be the exceptions). Abnormal responses to growth factors or accelerated cell loss through apoptosis may play an important role in the genesis of these disorders. © 1998 by The American Society of Hematology.
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Gogo, Kevin Otieno, Lawrence Nderu, and Makau Mutua. "Variances in knowledge-based interval type 2 Gaussian fuzzy on linear regression models." Journal of Intelligent & Fuzzy Systems 41, no. 1 (August 11, 2021): 1807–20. http://dx.doi.org/10.3233/jifs-210568.
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Fuzzy logic is a branch of artificial intelligence that has been used extensively in developing Fuzzy systems and models. These systems usually offer artificial intelligence based on the predictive mathematical models used; in this case linear regression mathematical model. Interval type 2 Gaussian fuzzy logic is a fuzzy logic that utilizes Gaussian upper membership function and the lower membership function, with a footprint of uncertainty in between the Gaussian membership functions. The artificial intelligence solutions predicted by these interval type 2 fuzzy systems depends on the training and the resultant linear regression mathematical model developed, which usually extract their training data from the expert knowledge stored in their knowledge bases. The variances in the expert knowledge stored in these knowledge-bases usually affect the overall accuracy of the linear regression predictive models of these systems, due to the variances in the training data. This research therefore establishes the extent that these variances in knowledge bases affect the predictive accuracy of these models, with a case study on knowledge bases used to predict learners’ knowledge level abilities. The calculated linear regression predictive models show that for every variance in the knowledge base, there occurs a change in linear regression predictive model with an intercept value factor commensurate to the variances and their respective weights in the knowledge bases.
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Ferreira, Jodavid A., Abraão D. C. Nascimento, and Alejandro C. Frery. "PolSAR Models with Multimodal Intensities." Remote Sensing 14, no. 20 (October 11, 2022): 5083. http://dx.doi.org/10.3390/rs14205083.
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Polarimetric synthetic aperture radar (PolSAR) systems are an important remote sensing tool. Such systems can provide high spacial resolution images, but they are contaminated by an interference pattern called multidimensional speckle. This fact requires that PolSAR images receive specialised treatment; particularly, tailored models which are close to PolSAR physical formation are sought. In this paper, we propose two new matrix models which arise from applying the stochastic summation approach to PolSAR, called compound truncated Poisson complex Wishart (CTPCW) and compound geometric complex Wishart (CGCW) distributions. These models offer the unique ability to express multimodal data. Some of their mathematical properties are derived and discussed—characteristic function and Mellin-kind log-cumulants (MLCs). Moreover, maximum likelihood (ML) estimation procedures via expectation maximisation algorithm for CTPCW and CGCW parameters are furnished as well as MLC-based goodness-of-fit graphical tools. Monte Carlo experiment results indicate ML estimates perform at what is asymptotically expected (small bias and mean square error) even for small sample sizes. Finally, our proposals are employed to describe actual PolSAR images, presenting evidence that they can outperform other well-known distributions, such as WmC, Gm0, and Km.
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Wu, Xinhe. "Boolean-Valued Models and Their Applications." Bulletin of Symbolic Logic 28, no. 4 (December 2022): 533. http://dx.doi.org/10.1017/bsl.2022.34.
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AbstractBoolean-valued models generalize classical two-valued models by allowing arbitrary complete Boolean algebras as value ranges. The goal of my dissertation is to study Boolean-valued models and explore their philosophical and mathematical applications.In Chapter 1, I build a robust theory of first-order Boolean-valued models that parallels the existing theory of two-valued models. I develop essential model-theoretic notions like “Boolean-valuation,” “diagram,” and “elementary diagram,” and prove a series of theorems on Boolean-valued models, including the (strengthened) Soundness and Completeness Theorem, the Löwenheim–Skolem Theorems, the Elementary Chain Theorem, and many more.Chapter 2 gives an example of a philosophical application of Boolean-valued models. I apply Boolean-valued models to the language of mereology to model indeterminacy in the parthood relation. I argue that Boolean-valued semantics is the best degree-theoretic semantics for the language of mereology. In particular, it trumps the well-known alternative—fuzzy-valued semantics. I also show that, contrary to what many have argued, indeterminacy in parthood entails neither indeterminacy in existence nor indeterminacy in identity, though being compatible with both.Chapter 3 (joint work with Bokai Yao) gives an example of a mathematical application of Boolean-valued models. Scott and Solovay famously used Boolean-valued models on set theory to obtain relative consistency results. In Chapter 3, I investigate two ways of extending the Scott–Solovay construction to set theory with urelements. I argue that the standard way of extending the construction faces a serious problem, and offer a new way that is free from the problem.Abstract prepared by Xinhe Wu.E-mail: xinhewu@mit.edu
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Rădulescu, G. M. T., A. T. G. Rădulescu, M. V. G. Rădulescu, and Sanda Naş. "Mathematical Modelling Of The Bridges Structural Monitoring I." Journal of Applied Engineering Sciences 5, no. 1 (May 1, 2015): 83–90. http://dx.doi.org/10.1515/jaes-2015-0011.
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Abstract Structural Health Monitoring is an extremely complex and relatively expensive activity, and the current offer of tools, methods and technologies is varied, which can lead to a virtually high number of structural monitoring systems that can be customized for each case. In time, the monitoring of bridges became the engine for the development of SHM tools, methods and technologies, or manager monitoring systems. The case study, in continuous quasi-static condition, was performed on Incheon Grand Bridge South Korea. Tracking the behaviour of an objective under the influence of sunshine is performed by VCE Vienna Consulting Engineers ZT GmbH. This paper presents the effect of sunshine on a steel structural element, the first lamella front North line, by comparing data pairs that reflect the cause: steel temperature and the effect: the movement of a sensor mounted on the structural element. The analysis was performed using several software dedicated to mathematical modelling, trying to establish different mathematical models that can be tested and validated.
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Cassani, Andrea, Alessandro Monteverde, and Marco Piumetti. "Belousov-Zhabotinsky type reactions: the non-linear behavior of chemical systems." Journal of Mathematical Chemistry 59, no. 3 (February 28, 2021): 792–826. http://dx.doi.org/10.1007/s10910-021-01223-9.
Full textAbstract:
AbstractChemical oscillators are open systems characterized by periodic variations of some reaction species concentration due to complex physico-chemical phenomena that may cause bistability, rise of limit cycle attractors, birth of spiral waves and Turing patterns and finally deterministic chaos. Specifically, the Belousov-Zhabotinsky reaction is a noteworthy example of non-linear behavior of chemical systems occurring in homogenous media. This reaction can take place in several variants and may offer an overview on chemical oscillators, owing to its simplicity of mathematical handling and several more complex deriving phenomena. This work provides an overview of Belousov-Zhabotinsky-type reactions, focusing on modeling under different operating conditions, from the most simple to the most widely applicable models presented during the years. In particular, the stability of simplified models as a function of bifurcation parameters is studied as causes of several complex behaviors. Rise of waves and fronts is mathematically explained as well as birth and evolution issues of the chaotic ODEs system describing the Györgyi-Field model of the Belousov-Zhabotinsky reaction. This review provides not only the general information about oscillatory reactions, but also provides the mathematical solutions in order to be used in future biochemical reactions and reactor designs.
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Suki, B., A. L. Barabasi, and K. R. Lutchen. "Lung tissue viscoelasticity: a mathematical framework and its molecular basis." Journal of Applied Physiology 76, no. 6 (June 1, 1994): 2749–59. http://dx.doi.org/10.1152/jappl.1994.76.6.2749.
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Recent studies indicated that lung tissue stress relaxation is well represented by a simple empirical equation involving a power law, t-beta (where t is time). Likewise, tissue impedance is well described by a model having a frequency-independent (constant) phase with impedance proportional to omega-alpha (where omega is angular frequency and alpha is a constant). These models provide superior descriptions over conventional spring-dashpot systems. Here we offer a mathematical framework and explore its mechanistic basis for using the power law relaxation function and constant-phase impedance. We show that replacing ordinary time derivatives with fractional time derivatives in the constitutive equation of conventional spring-dashpot systems naturally leads to power law relaxation function, the Fourier transform of which is the constant-phase impedance with alpha = 1 - beta. We further establish that fractional derivatives have a mechanistic basis with respect to the viscoelasticity of certain polymer systems. This mechanistic basis arises from molecular theories that take into account the complexity and statistical nature of the system at the molecular level. Moreover, because tissues are composed of long flexible biopolymers, we argue that these molecular theories may also apply for soft tissues. In our approach a key parameter is the exponent beta, which is shown to be directly related to dynamic processes at the tissue fiber and matrix level. By exploring statistical properties of various polymer systems, we offer a molecular basis for several salient features of the dynamic passive mechanical properties of soft tissues.
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Kimmel, M., and D. E. Axelrod. "Mathematical models of gene amplification with applications to cellular drug resistance and tumorigenicity." Genetics 125, no. 3 (July 1, 1990): 633–44. http://dx.doi.org/10.1093/genetics/125.3.633.
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Abstract An increased number of copies of specific genes may offer an advantage to cells when they grow in restrictive conditions such as in the presence of toxic drugs, or in a tumor. Three mathematical models of gene amplification and deamplification are proposed to describe the kinetics of unstable phenotypes of cells with amplified genes. The models differ in details but all assume probabilistic mechanisms of increase and decrease in gene copy number per cell (gene amplification/deamplification). Analysis of the models indicates that a stable distribution of numbers of copies of genes per cell, observed experimentally, exists only if the probability of deamplification exceeds the probability of amplification. The models are fitted to published data on the loss of methotrexate resistance in cultured cell lines, due to the loss of amplified dihydrofolate reductase gene. For two mouse cell lines unstably resistant to methotrexate the probabilities of amplification and deamplification of the dihydrofolate reductase gene on double minute chromosomes are estimated to be approximately 2% and 10%, respectively. These probabilities are much higher than widely presumed. The models explain the gradual disappearance of the resistant phenotype when selective pressure is withdrawn, by postulating that the rate of deamplification exceeds the rate of amplification. Thus it is not necessary to invoke a growth advantage of nonresistant cells which has been the standard explanation. For another analogous process, the loss of double minute chromosomes containing the myc oncogene from SEWA tumor cells, the growth advantage model does seem to be superior to the amplification and deamplification model. In a more theoretical section of the paper, it is demonstrated that gene amplification/deamplification can result in reduction to homozygosity, such as is observed in some tumors. Other applications are discussed.
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Tripp, D. E., J. H. Hemann, and J. P. Gyekenyesi. "A Review of Failure Models for Ceramic Matrix Composite Laminates Under Monotonic Loads." Journal of Engineering for Gas Turbines and Power 112, no. 4 (October 1, 1990): 492–501. http://dx.doi.org/10.1115/1.2906194.
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Ceramic matrix composites offer significant potential for improving the performance of turbine engines. In order to achieve their potential, however, improvements in design methodology are needed. In the past most components using structural ceramic matrix composites were designed by “trial and error” since the emphasis on feasibility demonstration minimized the development of mathematical models. To understand the key parameters controlling response and the mechanics of failure, the development of structural failure models is required. A review of short-term failure models with potential for ceramic matrix composite laminates under monotonic loads is presented. Phenomenological, semi-empirical, shear-lag, fracture mechanics, damage mechanics, and statistical models for the fast fracture analysis of continuous fiber unidirectional ceramic matrix composites under monotonic loads are surveyed.
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Hu, Liang Ming, Dan Ying Gao, Yi Zhi Li, and Shuai Qi Song. "Analysis of the Influence of Long Curing Age on the Compressive Strength of Plastic Concrete." Advanced Materials Research 382 (November 2011): 200–203. http://dx.doi.org/10.4028/www.scientific.net/amr.382.200.
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Plastic concrete is a composite material between the normal concrete and clay, with its characteristics of long curing age and slowed growth of strength. In this paper, the mathematical models of relationship between compressive strength (curing age of 540 days) and curing age (28 and 90 days) are established on the basis of multitudinous of tests. Comparing the value obtained by calculating model with experimental value, we find that they have well consistency. The establishment of these models provide the basis for making plastic concrete standard procedures and carrying out numerical analysis, and they also offer reference for engineering application of plastic concrete.
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PERLOVSKY, LEONID, and ROSS DEMING. "A MATHEMATICAL THEORY FOR LEARNING, AND ITS APPLICATION TO TIME-VARYING COMPUTED TOMOGRAPHY." New Mathematics and Natural Computation 01, no. 01 (March 2005): 147–71. http://dx.doi.org/10.1142/s1793005705000081.
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The brain has evolved to enable organisms to survive in a complicated and dynamic world. Its operation is based upon a priori models of the environment which are adapted, during learning, in response to new and changing stimuli. The same qualities that make biological learning mechanisms ideal for organisms make their underlying mathematical algorithms ideal for certain technological applications, especially those concerned with understanding the physical processes giving rise to complicated data sets. In this paper, we offer a mathematical model for the underlying mechanisms of biological learning, and we show how this mathematical approach to learning can yield a solution to the problem of imaging time-varying objects from X-ray computed tomographic (CT) data. This problem relates to several practical aspects of CT imaging including the correction of motion artifacts caused by patient movement or breathing.
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Průša, Vít, and K. R. Rajagopal. "Implicit Type Constitutive Relations for Elastic Solids and Their Use in the Development of Mathematical Models for Viscoelastic Fluids." Fluids 6, no. 3 (March 22, 2021): 131. http://dx.doi.org/10.3390/fluids6030131.
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Viscoelastic fluids are non-Newtonian fluids that exhibit both “viscous” and “elastic” characteristics in virtue of the mechanisms used to store energy and produce entropy. Usually, the energy storage properties of such fluids are modeled using the same concepts as in the classical theory of nonlinear solids. Recently, new models for elastic solids have been successfully developed by appealing to implicit constitutive relations, and these new models offer a different perspective to the old topic of the elastic response of materials. In particular, a sub-class of implicit constitutive relations, namely relations wherein the left Cauchy–Green tensor is expressed as a function of stress, is of interest. We show how to use this new perspective in the development of mathematical models for viscoelastic fluids, and we provide a discussion of the thermodynamic underpinnings of such models. We focus on the use of Gibbs free energy instead of Helmholtz free energy, and using the standard Giesekus/Oldroyd-B models, we show how the alternative approach works in the case of well-known models. The proposed approach is straightforward to generalize to more complex settings wherein the classical approach might be impractical or even inapplicable.
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Wutzler, T., and M. Reichstein. "Priming and substrate quality interactions in soil organic matter models." Biogeosciences Discussions 9, no. 12 (December 6, 2012): 17167–201. http://dx.doi.org/10.5194/bgd-9-17167-2012.
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Abstract. Interactions between different qualities of soil organic matter (SOM) affecting their turnover are rarely represented in models. In this study we propose three mathematical strategies at different levels of abstraction for representing those interactions. Implementing these strategies into the Introductory Carbon Balance Model (ICBM) and applying them to several scenarios of litter input show that the different levels of abstraction are applicable on different time scales. We present a simple one-parameter equation of substrate limitation applicable at decadal time scale that is straightforward to implement into other models of SOM dynamics. We show how substrate quality interactions can explain priming effects, acceleration of turnover times in FACE experiments, and the slowdown of decomposition in long-term bare fallow experiments as an effect of energy limitation of microbial biomass. The mechanisms of those interactions need to be further scrutinized empirically for a more complete understanding. Overall, substrate quality interactions offer a valuable way of understanding and quantitatively modelling SOM dynamics.
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Szász, Cs. "Intelligent building development and LabView-based modelling of a net zero-energy strategy." International Review of Applied Sciences and Engineering 5, no. 2 (December 1, 2014): 157–66. http://dx.doi.org/10.1556/irase.5.2014.2.8.
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The paper presents an intelligent building (IB) development strategy emphasizing the locally available non-polluting renewable energy resources utilization. Considering the immense complexity of the topic, the implementation strategy of the main energy-flow processes is unfolded, using the net zero-energy building concept (NZEB). Noticeably, in the first research steps the mathematical background of the considered NZEB strategy has been developed and presented. Then careful LabView software-based simulations prove that the adopted strategy is feasible for implementation. The result of the above mentioned research efforts is a set of powerful and versatile software toolkits well suitable to model and simulate complex heating, ventilation and air-conditioning processes and to perform energy balance performance evaluations. Besides the elaborated mathematical models, concrete software implementation examples and measurement data also is provided in the paper. Finally, the proposed original models offer a feasible solution for future developments and research in NZEB applications modelling and simulation purposes.
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Maldon, Benjamin, Ngamta Thamwattana, and Maureen Edwards. "Exploring Nonlinear Diffusion Equations for Modelling Dye-Sensitized Solar Cells." Entropy 22, no. 2 (February 21, 2020): 248. http://dx.doi.org/10.3390/e22020248.
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Dye-sensitized solar cells offer an alternative source for renewable energy by means of converting sunlight into electricity. While there are many studies concerning the development of DSSCs, comprehensive mathematical modelling of the devices is still lacking. Recent mathematical models are based on diffusion equations of electron density in the conduction band of the nano-porous semiconductor in dye-sensitized solar cells. Under linear diffusion and recombination, this paper provides analytical solutions to the diffusion equation. Further, Lie symmetry analysis is adopted in order to explore analytical solutions to physically relevant special cases of the nonlinear diffusion equations. While analytical solutions may not be possible, we provide numerical solutions, which are in good agreement with the results given in the literature.
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Spinozzi, Giulio, Valentina Tini, Alessio Ferrari, Ilaria Gionfriddo, Roberta Ranieri, Francesca Milano, Sara Pierangeli, et al. "SiCoDEA: A Simple, Fast and Complete App for Analyzing the Effect of Individual Drugs and Their Combinations." Biomolecules 12, no. 7 (June 28, 2022): 904. http://dx.doi.org/10.3390/biom12070904.
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The administration of combinations of drugs is a method widely used in the treatment of different pathologies as it can lead to an increase in the therapeutic effect and a reduction in the dose compared to the administration of single drugs. For these reasons, it is of interest to study combinations of drugs and to determine whether a specific combination has a synergistic, antagonistic or additive effect. Various mathematical models have been developed, which use different methods to evaluate the synergy of a combination of drugs. We have developed an open access and easy to use app that allows different models to be explored and the most fitting to be chosen for the specific experimental data: SiCoDEA (Single and Combined Drug Effect Analysis). Despite the existence of other tools for drug combination analysis, SiCoDEA remains the most complete and flexible since it offers options such as outlier removal or the ability to choose between different models for analysis. SiCoDEA is an easy to use tool for analyzing drug combination data and to have a view of the various steps and offer different results based on the model chosen.
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McHenry, Matthew J., Jacob L. Johansen, Alberto P. Soto, Brian A. Free, Derek A. Paley, and James C. Liao. "The pursuit strategy of predatory bluefish ( Pomatomus saltatrix )." Proceedings of the Royal Society B: Biological Sciences 286, no. 1897 (February 20, 2019): 20182934. http://dx.doi.org/10.1098/rspb.2018.2934.
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A predator’s ability to capture prey depends critically on how it coordinates its approach in response to a prey’s motion. Flying insects, bats and raptors are capable of capturing prey with a strategy known as parallel navigation, which allows a predator to move directly towards the anticipated point of interception. It is unclear if predators using other modes of locomotion are employing this strategy when pursuing evasive prey. Using kinematic measurements and mathematical modelling, we tested whether bluefish ( Pomatomus saltatrix ) pursue prey fish ( Fundulus heteroclitus ) with parallel navigation. We found that the directional changes of bluefish were not consistent with this strategy, but rather were predicted by a strategy known as deviated pursuit. Although deviated pursuit requires few sensory cues and relatively modest motor coordination, a comparison of mathematical models suggested negligible differences in path length from parallel navigation, largely owing to the acceleration exhibited by bluefish near the end of a pursuit. Therefore, the strategy of bluefish is unlike flying predators, but offers comparable performance with potentially more robust control that may be well suited to the visual system and habitat of fishes. These findings offer a foundation for understanding the sensing and locomotor control of predatory fishes.
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Abdulghafor, Rawad, and Sultan Almotairi. "A Fast Non-Linear Symmetry Approach for Guaranteed Consensus in Network of Multi-Agent Systems." Symmetry 12, no. 10 (October 15, 2020): 1692. http://dx.doi.org/10.3390/sym12101692.
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There has been tremendous work on multi-agent systems (MAS) in recent years. MAS consist of multiple autonomous agents that interact with each order to solve a complex problem. Several applications of MAS can be found in computer networks, smart grids, and the modeling of complex systems. Despite numerous benefits, a significant challenge for MAS is achieving a consensus among agents in a shared target task, which is difficult without applying certain mathematical equations. Non-linear models offer better possibility of resolving consensus for MAS; however, existing non-linear models are considerably complicated and present no guarantees for achieving consensus. This paper proposes a non-linear mathematical model of semi symmetry quadratic operator (SSQO) in order to resolve the issue of consensus in networks of MAS. The model is based on stochastic quadratic operator theory, with added new notations. An important feature for the proposed model is low complexity, fast consensus, and a guaranteed capability to reach a consensus. We present an evaluation of the proposed SSQO model and comparison with other existing models. We demonstrate that an average consensus can be achieved with our model in addition to the emulation effects for the MAS consensus.
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Heredia, Nathaly S., Karla Vizuete, Marco Flores-Calero, Katherine Pazmiño V., Fernanda Pilaquinga, Brajesh Kumar, and Alexis Debut. "Comparative statistical analysis of the release kinetics models for nanoprecipitated drug delivery systems based on poly(lactic-co-glycolic acid)." PLOS ONE 17, no. 3 (March 10, 2022): e0264825. http://dx.doi.org/10.1371/journal.pone.0264825.
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Poly(lactic-co-glycolic acid) is one of the most used polymers for drug delivery systems (DDSs). It shows excellent biocompatibility, biodegradability, and allows spatio-temporal control of the release of a drug by altering its chemistry. In spite of this, few formulations have reached the market. To characterize and optimize the drug release process, mathematical models offer a good alternative as they allow interpreting and predicting experimental findings, saving time and money. However, there is no general model that describes all types of drug release of polymeric DDSs. This study aims to perform a statistical comparison of several mathematical models commonly used in order to find which of them best describes the drug release profile from PLGA particles synthesized by nanoprecipitation method. For this purpose, 40 datasets extracted from scientific articles published since 2016 were collected. Each set was fitted by the models: order zero to fifth order polynomials, Korsmeyer-Peppas, Weibull and Hyperbolic Tangent Function. Some data sets had few observations that do not allow to apply statistic test, thus bootstrap resampling technique was performed. Statistic evidence showed that Hyperbolic Tangent Function model is the one that best fit most of the data.
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Berti, G., S. Giubbili, and E. Tognoni. "DISVAR93: A software package for determining systematic effects in X-ray powder diffractometry." Powder Diffraction 10, no. 2 (June 1995): 104–11. http://dx.doi.org/10.1017/s0885715600014457.
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DISVAR93 is a collection of programs devised to process XRPD patterns with the aim of determining the parameters of systematic instrumentation and sample effects. These effects have an influence on data uncertainty and also accuracy of the adopted models describing diffraction phenomena. Such modeling is carried out through the mathematical X-ray powder-diffraction theory, while parameter optimization is achieved by using the additive property of X2 and constraining the models to converge simultaneously to the same minimum in a restrained Hilbert's space. The package has been designed to allow both user interaction as well as automatic linking of programs managed by one main menu and offer several options to satisfy individual user requirements.