Journal articles: 'Biological Mathematics'

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Doube, Michael. "Mathematics for Biological Scientists." Journal of Anatomy 216, no. 4 (April 2010): 542. http://dx.doi.org/10.1111/j.1469-7580.2009.01195.x.

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B. Khyade, Vitthalrao, and Hanumant V. Wanve. "Review on Use of Mathematics for Progression of Biological Sciences." International Academic Journal of Innovative Research 05, no. 01 (June 12, 2018): 301–38. http://dx.doi.org/10.9756/iajir/v5i1/1810004.

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Thompson, Paul. "Mathematics in the biological sciences." International Studies in the Philosophy of Science 6, no. 3 (January 1992): 241–48. http://dx.doi.org/10.1080/02698599208573434.

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BELLOMO, N., and F. BREZZI. "MATHEMATICS AND COMPLEXITY IN BIOLOGICAL SCIENCES." Mathematical Models and Methods in Applied Sciences 21, supp01 (April 2011): 819–24. http://dx.doi.org/10.1142/s0218202511005374.

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Karl, Lila. "DNA computing: Arrival of biological mathematics." Mathematical Intelligencer 19, no. 2 (March 1997): 9–22. http://dx.doi.org/10.1007/bf03024425.

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Penny, D. "Doom01: biological mathematics in evolutionary processes." Trends in Ecology & Evolution 16, no. 6 (June 1, 2001): 275–76. http://dx.doi.org/10.1016/s0169-5347(01)02166-8.

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Marland, Eric, Katrina M. Palmer, and René A. Salinas. "Biological Applications in the Mathematics Curriculum." PRIMUS 18, no. 1 (January 17, 2008): 85–100. http://dx.doi.org/10.1080/10511970701744984.

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Šorgo, Andrej. "Connecting Biology and Mathematics: First Prepare the Teachers." CBE—Life Sciences Education 9, no. 3 (September 2010): 196–200. http://dx.doi.org/10.1187/cbe.10-03-0014.

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Developing the connection between biology and mathematics is one of the most important ways to shift the paradigms of both established science disciplines. However, adding some mathematic content to biology or biology content to mathematics is not enough but must be accompanied by development of suitable pedagogical models. I propose a model of pedagogical mathematical biological content knowledge as a feasible starting point for connecting biology and mathematics in schools and universities. The process of connecting these disciplines should start as early as possible in the educational process, in order to produce prepared minds that will be able to combine both disciplines at graduate and postgraduate levels of study. Because teachers are a crucial factor in introducing innovations in education, the first step toward such a goal should be the education of prospective and practicing elementary and secondary school teachers.

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Durán, Pablo A., and Jill A. Marshall. "Mathematics for biological sciences undergraduates: a needs assessment." International Journal of Mathematical Education in Science and Technology 50, no. 6 (October 26, 2018): 807–24. http://dx.doi.org/10.1080/0020739x.2018.1537451.

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Naidoo, Jayaluxmi. "Integrating Indigenous Knowledge and Culturally based Activities in South African Mathematics Classrooms." African Journal of Teacher Education 10, no. 2 (December 11, 2021): 17–36. http://dx.doi.org/10.21083/ajote.v10i2.6686.

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Culturally based activities embedded within indigenous knowledge, in general, may be used to support the teaching of mathematics in multicultural classes. The article reflects on research that has been conducted with twenty-five post-graduate students studying Mathematics Education at one university in KwaZulu-Natal, South Africa. These post-graduate students were also practicing mathematics teachers at schools. The study explored the use of indigenous knowledge and culturally based activities by post-graduate students in schools while teaching mathematical concepts. The theory of Realistic Mathematics Education framed this qualitative, interpretive study which used a questionnaire, lesson observations and semi-structured interviews to generate data. Qualitative data were analysed inductively and thematically. The findings reveal that the participants needed to understand indigenous knowledge to integrate culturally based activities in mathematics lessons. Secondly, culturally based activities established on indigenous knowledge scaffolded mathematics lessons and promoted the understanding of mathematical concepts to make learning more meaningful and relevant. Thirdly, this study provides examples of good practice to support teachers in integrating classroom activities and activities outside the classroom, ensuring that mathematical concepts learned in classrooms are not done in isolation but take into account learners’ authentic experiences in various settings. Finally, by integrating indigenous knowledge and culturally based activities in the mathematics curriculum, learners interacted and engaged more freely within the educational context. Similar studies could be conducted at universities internationally. Implications for mathematics teachers, mathematics teacher educators and mathematics curriculum developers globally are discussed.

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Bianca, Carlo. "Mathematical and computational modeling of biological systems: advances and perspectives." AIMS Biophysics 8, no. 4 (2021): 318–21. http://dx.doi.org/10.3934/biophy.2021025.

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<abstract> <p>The recent developments in the fields of mathematics and computer sciences have allowed a more accurate description of the dynamics of some biological systems. On the one hand new mathematical frameworks have been proposed and employed in order to gain a complete description of a biological system thus requiring the definition of complicated mathematical structures; on the other hand computational models have been proposed in order to give both a numerical solution of a mathematical model and to derive computation models based on cellular automata and agents. Experimental methods are developed and employed for a quantitative validation of the modeling approaches. This editorial article introduces the topic of this special issue which is devoted to the recent advances and future perspectives of the mathematical and computational frameworks proposed in biosciences.</p> </abstract>

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Duncan, Sarah I., Pamela Bishop, and Suzanne Lenhart. "Preparing the “New” Biologist of the Future: Student Research at the Interface of Mathematics and Biology." CBE—Life Sciences Education 9, no. 3 (September 2010): 311–15. http://dx.doi.org/10.1187/cbe.10-03-0025.

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We describe a unique Research Experience for Undergraduates and Research Experience for Veterinary students summer program at the National Institute for Mathematical and Biological Synthesis on the campus of the University of Tennessee, Knoxville. The program focused on interdisciplinary research at the interface of biology and mathematics. Participants were selected to work on projects with a biology mentor and a mathematics mentor in an environment that promoted collaboration outside of the students' respective disciplines. There were four research projects with teams of four participants and two faculty mentors. The participants consisted of a mixture of 10 undergraduates in biology- and mathematics-related disciplines, four veterinary students, and two high-school teachers. The activities included lectures on both the biological and mathematical backgrounds of the projects, tutorials for software, and sessions on ethics, graduate school, and possible career paths for individuals interested in biology and mathematics. The program was designed to give students the ability to actively participate in the scientific research process by working on a project, writing up their results in a final report, and presenting their work orally. We report on the results of our evaluation surveys of the participants.

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Hailiang Zhang. "Estimates of the Solutions in Nonlinear Biological Mathematics Problems." International Journal of Advancements in Computing Technology 5, no. 3 (February 15, 2013): 472–80. http://dx.doi.org/10.4156/ijact.vol5.issue3.55.

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Garikipati, Krishna. "Perspectives on the mathematics of biological patterning and morphogenesis." Journal of the Mechanics and Physics of Solids 99 (February 2017): 192–210. http://dx.doi.org/10.1016/j.jmps.2016.11.013.

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Ghosh, Mini, Abid Ali Lashari, and Xue-Zhi Li. "Biological control of malaria: A mathematical model." Applied Mathematics and Computation 219, no. 15 (April 2013): 7923–39. http://dx.doi.org/10.1016/j.amc.2013.02.053.

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Winanda, Rara Sandhy, Akira Mikail, Defri Ahmad, Dina Agustina, and Rahmawati Rahmawati. "University Students' Procrastination: A Mathematical Model (Case Studies: Student in Mathematics Department Universitas Negeri Padang)." EKSAKTA: Berkala Ilmiah Bidang MIPA 23, no. 02 (June 30, 2022): 98–105. http://dx.doi.org/10.24036/eksakta/vol23-iss02/315.

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Mathematical modeling of procrastination was carried out on students in the Mathematics Department at Universitas Negeri Padang. Procrastination is the tendency to delay work and can be contagious among students. Mathematical modeling of procrastination aims to show the spread of procrastination among students. The SEIR compartment model was applied in this study. From a total of 1,154 population members, 93 samples were randomly selected and were given a questionnaire to estimate the parameter values in the model. A couple of steady states appear in the model. The free disease steady state has a biological meaning since all the variables are real, while the endemic steady state is surreal in biological terms. The number of its basic reproduction number, from which the parameter values are derived from the primary data, indicates stability analysis near the free disease steady states. The result shows that procrastination is spread among students in the population, with the number of Ro is 1,009.

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Ferreirós, José. "The Motives behind Cantor's Set Theory – Physical, Biological, and Philosophical Questions." Science in Context 17, no. 1-2 (June 2004): 49–83. http://dx.doi.org/10.1017/s0269889704000055.

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The celebrated “creation” of transfinite set theory by Georg Cantor has been studied in detail by historians of mathematics. However, it has generally been overlooked that his research program cannot be adequately explained as an outgrowth of the mainstream mathematics of his day. We review the main extra-mathematical motivations behind Cantor's very novel research, giving particular attention to a key contribution, the Grundlagen (Foundations of a general theory of sets) of 1883, where those motives are articulated in some detail. Evidence from other publications and correspondence is pulled out to provide clarification and a detailed interpretation of those ideas and their impact upon Cantor's research. Throughout the paper, a special effort is made to place Cantor's scientific undertakings within the context of developments in German science and philosophy at the time (philosophers such as Trendelenburg and Lotze, scientists like Weber, Riemann, Vogt, Haeckel), and to reflect on the German intellectual atmosphere during the nineteenth century.

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Barrett, A. N. "Mathematical modelling of biological systems by microcomputer." Mathematical Modelling 7, no. 9-12 (1986): 1601–11. http://dx.doi.org/10.1016/0270-0255(86)90092-8.

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Barnes, Jim. "Essential Biological Psychology." Psychology Teaching Review 23, no. 1 (2017): 85–86. http://dx.doi.org/10.53841/bpsptr.2017.23.1.85.

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Psychology is a valuable Science, Technology, Engineering, and Mathematics (STEM) discipline, but one which could do far more at communicating its value to the wider public. This paper discusses how popular initiatives, such as The University of Northampton’s STEM Champions programme, enhance psychology’s STEMmembership, while increasing public engagement and participation. These opportunities also enhance the psychology STEM student journey, by helping them to develop employability–related skills and allowing them to obtain valuable experience in theenvironments that they may later be working in.

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Anguelov, Roumen, and Armanda Bastos. "Can Mathematics be Biology’s next microscope in disease research at the interface?" BIOMATH 5, no. 2 (January 6, 2017): 1612237. http://dx.doi.org/10.11145/j.biomath.2016.12.237.

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In this paper we discuss how mathematics can be integrated into biological research as well as the benefits and challenges related to this process. The focus is on the research of diseases at the interface between wildlife, humans and livestock with some illustrative examples applications of mathematical models to disease research we have been personally involved with.

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MARTSENYUK, V., A. SVERSTIUK, O. BAGRIY-ZAYATS, A. PAVLYSHYN, and I. BOYMISTRUK. "MODELING OF PHYSICOCHEMICAL AND BIOLOGICAL PROCESSES DIFFERENTIAL EQUATIONS." Herald of Khmelnytskyi National University 301, no. 5 (October 2021): 177–87. http://dx.doi.org/10.31891/2307-5732-2021-301-5-177-187.

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The approaches to modeling of physicochemical and biological processes of differential equations are explained in the work. The law of radioactive decay, the law of absorption of ionizing radiation by the environment, the law of reproduction of bacteria, the law of dissolution of medicinal substance from a tablet, chemical reactions of the first and second order, mathematical model G.I. Marchuk are resulted, mathematical model of a cyber-physical immunosensory system on a hexagonal lattice using a system of delayed differential equations. The results of mathematical modeling in the form of the results of numerical modeling of the dynamic logic of the cyber-physical immunosensory system are presented. Phase planes, lattice images of the probability of antigen-antibody binding, images of fluorescent pixels, electrical signal from the transducer, which characterizes the number of fluorescent pixels, were obtained. In order to increase the student’s research interest in the study of natural sciences and improve the level of understanding of educational material in the disciplines “Biophysics with physical methods of analysis” and “Higher Mathematics” it is important to inform students about the latest discoveries in this field of knowledge, modern scientific mathematical and physical schools, because it is largely a motivating factor in the formation of future specialists in medicine, pharmacy, biology. Acquainting students with the current results of their own research allows them to be interested in the process of modeling medical and biological processes using differential equations, motivating them to their own research and development of various biosensor devices.

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Raïssi, Nadia, Mustapha Serhani, and Ezio Venturino. "Optimizing biological wastewater treatment." Ricerche di Matematica 69, no. 2 (March 6, 2020): 629–52. http://dx.doi.org/10.1007/s11587-020-00494-9.

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Hester, Susan, Sanlyn Buxner, Lisa Elfring, and Lisa Nagy. "Integrating Quantitative Thinking into an Introductory Biology Course Improves Students’ Mathematical Reasoning in Biological Contexts." CBE—Life Sciences Education 13, no. 1 (March 2014): 54–64. http://dx.doi.org/10.1187/cbe.13-07-0129.

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Recent calls for improving undergraduate biology education have emphasized the importance of students learning to apply quantitative skills to biological problems. Motivated by students’ apparent inability to transfer their existing quantitative skills to biological contexts, we designed and taught an introductory molecular and cell biology course in which we integrated application of prerequisite mathematical skills with biology content and reasoning throughout all aspects of the course. In this paper, we describe the principles of our course design and present illustrative examples of course materials integrating mathematics and biology. We also designed an outcome assessment made up of items testing students’ understanding of biology concepts and their ability to apply mathematical skills in biological contexts and administered it as a pre/postcourse test to students in the experimental section and other sections of the same course. Precourse results confirmed students’ inability to spontaneously transfer their prerequisite mathematics skills to biological problems. Pre/postcourse outcome assessment comparisons showed that, compared with students in other sections, students in the experimental section made greater gains on integrated math/biology items. They also made comparable gains on biology items, indicating that integrating quantitative skills into an introductory biology course does not have a deleterious effect on students’ biology learning.

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Langendorf, Ryan E. "Mathematics and Biology." American Biology Teacher 79, no. 6 (August 1, 2017): 500–501. http://dx.doi.org/10.1525/abt.2017.79.6.500b.

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Usher, David C., Tobin A. Driscoll, Prasad Dhurjati, John A. Pelesko, Louis F. Rossi, Gilberto Schleiniger, Kathleen Pusecker, and Harold B. White. "A Transformative Model for Undergraduate Quantitative Biology Education." CBE—Life Sciences Education 9, no. 3 (September 2010): 181–88. http://dx.doi.org/10.1187/cbe.10-03-0029.

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The BIO2010 report recommended that students in the life sciences receive a more rigorous education in mathematics and physical sciences. The University of Delaware approached this problem by (1) developing a bio-calculus section of a standard calculus course, (2) embedding quantitative activities into existing biology courses, and (3) creating a new interdisciplinary major, quantitative biology, designed for students interested in solving complex biological problems using advanced mathematical approaches. To develop the bio-calculus sections, the Department of Mathematical Sciences revised its three-semester calculus sequence to include differential equations in the first semester and, rather than using examples traditionally drawn from application domains that are most relevant to engineers, drew models and examples heavily from the life sciences. The curriculum of the B.S. degree in Quantitative Biology was designed to provide students with a solid foundation in biology, chemistry, and mathematics, with an emphasis on preparation for research careers in life sciences. Students in the program take core courses from biology, chemistry, and physics, though mathematics, as the cornerstone of all quantitative sciences, is given particular prominence. Seminars and a capstone course stress how the interplay of mathematics and biology can be used to explain complex biological systems. To initiate these academic changes required the identification of barriers and the implementation of solutions.

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Hirsch, Morris W. "Mathematics of Hebbian attractors." Behavioral and Brain Sciences 18, no. 4 (December 1995): 633–34. http://dx.doi.org/10.1017/s0140525x00040243.

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AbstractThe concept of an attractor in a mathematical dynamical system is reviewed. Emphasis is placed on the distinction between a cell assembly, the corresponding attractor, and the attractor dynamics. The biological significance of these entities is discussed, especially the question of whether the representation of the stimulus requires the full attractor dynamics, or merely the cell assembly as a set of reverberating neurons. Comparison is made to Freeman's study of dynamic patterns in olfaction.

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Castilho Piqueira, José Roberto. "A mathematical view of biological complexity." Communications in Nonlinear Science and Numerical Simulation 14, no. 6 (June 2009): 2581–86. http://dx.doi.org/10.1016/j.cnsns.2008.10.003.

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Stewart, Christie, Melissa M. Root, Taylor Koriakin, Dowon Choi, Sarah R. Luria, Melissa A. Bray, Kari Sassu, Cheryl Maykel, Patricia O’Rourke, and Troy Courville. "Biological Gender Differences in Students’ Errors on Mathematics Achievement Tests." Journal of Psychoeducational Assessment 35, no. 1-2 (September 23, 2016): 47–56. http://dx.doi.org/10.1177/0734282916669231.

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This study investigated developmental gender differences in mathematics achievement, using the child and adolescent portion (ages 6-19 years) of the Kaufman Test of Educational Achievement–Third Edition (KTEA-3). Participants were divided into two age categories: 6 to 11 and 12 to 19. Error categories within the Math Concepts & Applications and Math Computation subtests of the KTEA-3 were factor analyzed and revealed five error factors. Multiple ANOVA of the error factor scores showed that, across both age categories, female and male mean scores were not significantly different across four error factors: math calculation, geometric concepts, basic math concepts, and addition. They were significantly different on the complex math problems error factor, with males performing better at the p < .05 significance level for the 6 to 11 age group and at the p < .001 significance level for the 12 to 19 age group. Implications in light of gender stereotype threat are discussed.

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Leow, Melvin Khee-Shing. "Configuration of the hemoglobin oxygen dissociation curve demystified: a basic mathematical proof for medical and biological sciences undergraduates." Advances in Physiology Education 31, no. 2 (June 2007): 198–201. http://dx.doi.org/10.1152/advan.00012.2007.

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The oxygen dissociation curve (ODC) of hemoglobin (Hb) has been widely studied and mathematically described for nearly a century. Numerous mathematical models have been designed to predict with ever-increasing accuracy the behavior of oxygen transport by Hb in differing conditions of pH, carbon dioxide, temperature, Hb levels, and 2,3-diphosphoglycerate concentrations that enable their applications in various clinical situations. The modeling techniques employed in many existing models are notably borrowed from advanced and highly sophisticated mathematics that are likely to surpass the comprehensibility of many medical and bioscience students due to the high level of “mathematical maturity” required. It is, however, a worthy teaching point in physiology lectures to illustrate in simple mathematics the fundamental reason for the crucial sigmoidal configuration of the ODC such that the medical and bioscience undergraduates can readily appreciate it, which is the objective of this basic dissertation.

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Foss, Jeffrey. "Arithmetic and old lace." Behavioral and Brain Sciences 19, no. 2 (June 1996): 252–53. http://dx.doi.org/10.1017/s0140525x00042485.

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AbstractGeary's project faces the severe methodological difficulty of tracing the biological effects of gender on mathematical ability in a system that is massively open. Two methodological stratagems he uses are considered. The first is that pancultural sex differences are biological in nature, which is dubious in the domain of mathematics, since it is completely culture-bound. The second is that sociosexual differences are partly caused by biosexual differences, which renders his thesis unfalsifiable and empirically empty.

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Ramon Blanco, Sanchez. "The amazing systemic structure of Mathematics." Annals of Mathematics and Physics 5, no. 2 (July 19, 2022): 095–96. http://dx.doi.org/10.17352/amp.000045.

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Starting with the works of Ludwig von Bertalanffy, the general systems theory went from being applied to biological systems to identifying systemic structures in different natural, technological and social phenomena, even systemic structures are appreciated in different branches of science.

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Kolesov, A. Yu, N. Kh Rozov, and V. A. Sadovnichii. "On a Mathematical Model of Biological Self-Organization." Proceedings of the Steklov Institute of Mathematics 304, no. 1 (January 2019): 160–89. http://dx.doi.org/10.1134/s0081543819010127.

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De, A., K. Maity, and G. Panigrahi. "Fish and broiler optimal harvesting models in imprecise environment." International Journal of Biomathematics 10, no. 08 (October 31, 2017): 1750115. http://dx.doi.org/10.1142/s1793524517501157.

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In this paper, a two-species harvesting model has been considered and developed a solution procedure which is able to calculate the equilibrium points of the model where some biological parameters of the model are interval numbers. A parametric mathematical program is formulated to find the biological equilibrium of the model for different values of parameters. This interval-valued problem is converted into an equivalent crisp model using interval mathematics. The main advantage of the proposed procedure is that different characteristics of the model can be presented in a single framework. Analytically, the existence of steady state and stabilities are looked into. Using mathematical software, the model is illustrated and the results are obtained and presented in tabular and graphical forms.

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Ferrari, Pier Luigi. "Abstraction in mathematics." Philosophical Transactions of the Royal Society of London. Series B: Biological Sciences 358, no. 1435 (July 29, 2003): 1225–30. http://dx.doi.org/10.1098/rstb.2003.1316.

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Some current interpretations of abstraction in mathematical settings are examined from different perspectives, including history and learning. It is argued that abstraction is a complex concept and that it cannot be reduced to generalization or decontextualization only. In particular, the links between abstraction processes and the emergence of new objects are shown. The role that representations have in abstraction is discussed, taking into account both the historical and the educational perspectives. As languages play a major role in mathematics, some ideas from functional linguistics are applied to explain to what extent mathematical notations are to be considered abstract. Finally, abstraction is examined from the perspective of mathematics education, to show that the teaching ideas resulting from one–dimensional interpretations of abstraction have proved utterly unsuccessful.

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Lavrischeva, Ekaterina Mikhailovna, and Igor Borisovich Petrov. "Modeling Technical and Mathematical Tasks of Applied Knowledge Areas on Computers." Proceedings of the Institute for System Programming of the RAS 32, no. 6 (2020): 167–82. http://dx.doi.org/10.15514/ispras-2020-32(6)-13.

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The paper considers modeling of technical problems and problems of applied mathematics, their algorithms and programming. The characteristics of the numerical modeling of technical problems and applied mathematics are given: physical and technical experiments, energy, ballistic and seismic methods of I.V. Kurchatov, starting with mathematical methods of the 17-20th centuries, the first computers and computers. The analysis of the first technical problems and problems of applied mathematics, their modeling, algorithmization and programming using the A.A. Lyapunov graph-schematic language, address language and programming languages is given. Numerical methods are presented, implemented under the guidance of A.A. Dorodnitsyn, A.A. Samarsky, O.M. Belotserkovsky and other scientists on modern supercomputers. Examples of mathematical modeling of the biological problem of eye treatment and the subject of «Computational geometry» on the Internet are given.

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Bowyer, Jessica, and Ellie Darlington. "Mathematical struggles and ensuring success: post-compulsory mathematics as preparation for undergraduate bioscience." Journal of Biological Education 52, no. 1 (February 17, 2017): 54–65. http://dx.doi.org/10.1080/00219266.2017.1285803.

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Jordán, Ferenc, Anett Endrédi, Wei-chung Liu, and Domenico D’Alelio. "Aggregating a Plankton Food Web: Mathematical versus Biological Approaches." Mathematics 6, no. 12 (December 19, 2018): 336. http://dx.doi.org/10.3390/math6120336.

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Species are embedded in a web of intricate trophic interactions. Understanding the functional role of species in food webs is of fundamental interests. This is related to food web position, so positional similarity may provide information about functional overlap. Defining and quantifying similar trophic functioning can be addressed in different ways. We consider two approaches. One is of mathematical nature involving network analysis where unique species can be defined as those whose topological position is very different to others in the same food web. A species is unique if it has very different connection pattern compared to others. The second approach is of biological nature, based on trait-based aggregations. Unique species are not easy to aggregate with others because their traits are not in common with the ones of most others. Our goal here is to illustrate how mathematics can provide an alternative perspective on species aggregation, and how this is related to its biological counterpart. We illustrate these approaches using a toy food web and a real food web and demonstrate the sensitive relationships between those approaches. The trait-based aggregation focusing on the trait values of size (sv) can be best predicted by the mathematical aggregation algorithms.

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Molina-Cuasapaz, Gabriel, Sofía de Janon, Marco Larrea-Álvarez, Esteban Fernández-Moreira, Karen Loaiza, Miroslava Šefcová, David Ayala-Velasteguí, Karla Mena, Christian Vinueza Burgos, and David Ortega-Paredes. "An Online Pattern Recognition-Oriented Workshop to Promote Interest among Undergraduate Students in How Mathematical Principles Could Be Applied within Veterinary Science." Sustainability 14, no. 11 (June 1, 2022): 6768. http://dx.doi.org/10.3390/su14116768.

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Knowing the importance of mathematics and its relationship with veterinary medicine plays an important role for students. To promote interest in this relationship, we developed the workshop “Math in Nature” that utilizes the surrounding environment for stimulating pattern-recognition and observational skills. It consisted of four sections: A talk by a professional researcher, a question-and-answer section, a mathematical pattern identification session, and a discussion of the ideas proposed by students. The effectiveness of the program to raise interest in mathematics was evaluated using a questionnaire applied before and after the workshop. Following the course, a higher number of students agreed with the fact that biological phenomena can be explained and predicted by applying mathematics, and that it is possible to identify mathematical patterns in living beings. However, the students’ perspectives regarding the importance of mathematics in their careers, as well as their interest in deepening their mathematical knowledge, did not change. Arguably, “Math in Nature” could have exerted a positive effect on the students’ interest in mathematics. We thus recommend the application of similar workshops to improve interests and skills in relevant subjects among undergraduate students.

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Murray, J. D. "Vignettes from the field of mathematical biology: the application of mathematics to biology and medicine." Interface Focus 2, no. 4 (February 2012): 397–406. http://dx.doi.org/10.1098/rsfs.2011.0102.

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The application of mathematical models in biology and medicine has a long history. From the sparse number of papers in the first half of the twentieth century with a few scientists working in the field it has become vast with thousands of active researchers. We give a brief, and far from definitive history, of how some parts of the field have developed and how the type of research has changed. We describe in more detail just two examples of specific models which are directly related to real biological problems, namely animal coat patterns and the growth and image enhancement of glioblastoma brain tumours.

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El-Sharkasy, M. M. "Topological model for recombination of DNA and RNA." International Journal of Biomathematics 11, no. 08 (November 2018): 1850097. http://dx.doi.org/10.1142/s1793524518500973.

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The aim of this paper is to use topological concepts in the construction of flexible mathematical models in the field of biological mathematics. Also, we will build new topographic types to study recombination of deoxyribonucleic acid (DNA) and ribonucleic acid (RNA). Finally, we study the topographical properties of constructed operators and the associated topological spaces of DNA and RNA.

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Lake, Willem. "Success in Mathematics for All Students: A New Approach to High School Mathematics." Australian Educational and Developmental Psychologist 4, no. 2 (November 1987): 28–29. http://dx.doi.org/10.1017/s0816512200025670.

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While visiting Europe in 1986 I had the opportunity to observe an exciting educational experiment in Vienna. Dr. Guttmann, professor of biology and Dr. Vanecek, professor of psychology, worked together at the Boltzmann Institute for Learning Research to apply the latest psycho-biological findings to education. First they did this under laboratory conditions and later they proposed workable classroom procedures. In the laboratory they used “Cortical Evoked Potentials” to determine students’ activation levels and how they could alter these to improve their learning retention. From this they developed a model of classroom instruction.

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McCarthy, Maeve L., and K. Renee Fister. "BioMaPS: A Roadmap for Success." CBE—Life Sciences Education 9, no. 3 (September 2010): 175–80. http://dx.doi.org/10.1187/cbe.10-03-0023.

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The manuscript outlines the impact that our National Science Foundation Interdisciplinary Training for Undergraduates in Biological and Mathematical Sciences program, BioMaPS, has had on the students and faculty at Murray State University. This interdisciplinary program teams mathematics and biology undergraduate students with mathematics and biology faculty and has produced research insights and curriculum developments at the intersection of these two disciplines. The goals, structure, achievements, and curriculum initiatives are described in relation to the effects they have had to enhance the study of biomathematics.

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Khanna, D. R., R. Bhutiani, and Neetu Saxena. "An approach to mathematical models as a tool for water and air quality management." Journal of Applied and Natural Science 6, no. 1 (June 1, 2014): 304–14. http://dx.doi.org/10.31018/jans.v6i1.420.

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Interactions between mathematical and biological sciences have been increasing rapidly in recent years. The use of system analysis and mathematical model for formulation and solving the environmental pollution is of relatively recent vintage and has been used widely since last three decades. These models can be used to conduct numerical experiments, test hypothesis and help to understand the response of environmental pollution. A mathematical model acts as a bridge between study of mathematics and application of mathematics in environmentand other fields. Modeling is an abstraction of reality and its ultimate objective is to explore the complexity of functions and structure of the system under study. Today, a wide variety of models belonging to different nature and category are available to understand the processes of the environment around us. Various models such as WASP, CE-QUAL-ICM, QUAL W2, AQUATOX, QUAL2K, IITAQ, PEARL, GRAM, UGEM, and IITLT etc. related to water and air quality are developed so far along with their principles, intended use and applications. These models generally simulate the basic physical, chemical and biological processes. In the present study, an attempt has been made to evaluate the concept and utilization of mathematical models in air and water quality management.

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TIJSKENS, L. M. M., R. E. SCHOUTEN, T. UNUK, and M. SIMČIČ. "Green mathematics: Benefits of including biological variation in your data analysis." Acta agriculturae Slovenica 105, no. 1 (April 9, 2015): 157–64. http://dx.doi.org/10.14720/aas.2015.105.1.16.

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Jiang, Ying, C. K. Peng, and Yuesheng Xu. "Hierarchical entropy analysis for biological signals." Journal of Computational and Applied Mathematics 236, no. 5 (October 2011): 728–42. http://dx.doi.org/10.1016/j.cam.2011.06.007.

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Aikens, Melissa L., Carrie Diaz Eaton, and Hannah Callender Highlander. "The Case for Biocalculus: Improving Student Understanding of the Utility Value of Mathematics to Biology and Affect toward Mathematics." CBE—Life Sciences Education 20, no. 1 (March 2021): ar5. http://dx.doi.org/10.1187/cbe.20-06-0124.

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This study examines changes in life science students’ understanding of the utility of mathematics to biology, their interest in mathematics, and their overall attitudes toward mathematics after taking courses that integrate calculus into biological problems. Factors that contribute to improved attitudes toward mathematics are identified.

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Elser, James, John Nagy, and Yang Kuang. "Biological stoichiometry of tumor dynamics: Mathematical models and analysis." Discrete and Continuous Dynamical Systems - Series B 4, no. 1 (November 2003): 221–40. http://dx.doi.org/10.3934/dcdsb.2004.4.221.

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Jungck, John R., Holly Gaff, and Anton E. Weisstein. "Mathematical Manipulative Models: In Defense of “Beanbag Biology”." CBE—Life Sciences Education 9, no. 3 (September 2010): 201–11. http://dx.doi.org/10.1187/cbe.10-03-0040.

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Mathematical manipulative models have had a long history of influence in biological research and in secondary school education, but they are frequently neglected in undergraduate biology education. By linking mathematical manipulative models in a four-step process—1) use of physical manipulatives, 2) interactive exploration of computer simulations, 3) derivation of mathematical relationships from core principles, and 4) analysis of real data sets—we demonstrate a process that we have shared in biological faculty development workshops led by staff from the BioQUEST Curriculum Consortium over the past 24 yr. We built this approach based upon a broad survey of literature in mathematical educational research that has convincingly demonstrated the utility of multiple models that involve physical, kinesthetic learning to actual data and interactive simulations. Two projects that use this approach are introduced: The Biological Excel Simulations and Tools in Exploratory, Experiential Mathematics (ESTEEM) Project ( http://bioquest.org/esteem ) and Numerical Undergraduate Mathematical Biology Education (NUMB3R5 COUNT; http://bioquest.org/numberscount ). Examples here emphasize genetics, ecology, population biology, photosynthesis, cancer, and epidemiology. Mathematical manipulative models help learners break through prior fears to develop an appreciation for how mathematical reasoning informs problem solving, inference, and precise communication in biology and enhance the diversity of quantitative biology education.

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PAVELKO, VIKTORIYA. "MATHEMATICS IN NATURAL SCIENCES AND EDUCATION: THEORETICAL ASPECT." Scientific Issues of Ternopil Volodymyr Hnatiuk National Pedagogical University. Series: pedagogy 1, no. 2 (January 11, 2023): 106–13. http://dx.doi.org/10.25128/2415-3605.22.2.13.

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The need to modernize modern education in order to increase the level of students' interest in studying subjects, mathematical and natural sciences, was noted. The role of mathematics and natural sciences for the versatile development of the personality in general, their necessity from the first years of education is defined and integration as an important condition for unification and mutual use in the educational process of mathematical and natural knowledge. The relevance of the problem of using mathematics both in the learning process and for various areas of scientific knowledge is substantiated. The article describes general historical information about mathematics as a science and gives examples of the interpretation of its content by scientists of both the past and the present. The factors determining the importance of the role of mathematics are determined. Its general aspects are characterized from the point of view of mathematical language, its elements, namely, sign, symbol, model, mathematical modeling. The important role of the language of mathematics both in the cognitive activity of a person and in the research of natural sciences at various stages of their development is substantiated. As a result of the analysis of scientific and pedagogical literature and generalizations of the use of mathematical methods and tools, examples of the interpretation of the concept of "mathematization of scientific knowledge" are given. The main aspects of the mathematization of sciences and, in particular, its necessity in the formation and development of natural sciences are theoretically substantiated. The necessary conditions for the effectiveness of the application of the concepts and methods of mathematics and the strengthening of the mathematization of knowledge have been identified. Examples of the application of mathematical methods for such sciences as astronomy and chemistry are given. The need for mathematization in natural science is also mentioned in the context of biological sciences, and the stages of this process are characterized. The degree of reality of mathematical concepts and structures in natural science has been clarified; of mutual dependence, bilateral connection of mathematics and natural sciences are clarified. That is, that natural science is necessary for modern mathematics, just as it is necessary for it. The significance of mathematization in the integration of natural knowledge in today's conditions is indicated. The author also drew attention to the issue of mathematization of natural sciences in the context of the educational process, i.e., that for the subjects of the study, it involves the penetration of mathematics into natural science; on the problem of conditioning the integration of mathematics with science subjects. It was emphasized that science and mathematics education is gaining importance today and the need for active implementation of STEM education in the New Ukrainian School and, in particular, in the primary level.

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Tsidylo, I. M., L. O. Shevchyk, I. M. Hrod, H. V. Solonetska, and S. B. Shabaga. "A computer simulation of population reproduction rate on the basis of their mathematical models." Journal of Physics: Conference Series 2288, no. 1 (June 1, 2022): 012014. http://dx.doi.org/10.1088/1742-6596/2288/1/012014.

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Abstract The article deals with the adoption of computer modeling as one of the leading areas of introduction of modern information technology in the modernization of content, forms and methods of teaching. In order to implement interdisciplinary integrated learning, the possibilities of interdisciplinary integration of learning content have been identified, the practice of using software environments in the process of modeling biological problems based on mathematical models has been analyzed, the possibilities of implementing algorithms of mathematical models in computer modeling have been investigated. A set of research tasks in biology as a basis for the implementation of interdisciplinary integration: nature - mathematics -computer science has been introduced into the educational process. The mathematical models of Verhulst, Arim, Leslie and the exponential law of direct proportional dependence or proportional rate of reproduction depending on the number of individuals of a population were used to design computer models of reproduction of ecological processes. They were implemented using the computer mathematics system MathCad and using programming environments Python, C#, C++. The expediency of the proposed method of interdisciplinary integration of learning content has been justified through a developmental and productive integrated approach, the use of certain collective forms of activity, the practical orientation of professional training disciplines to form algorithmic competence of students as a basis for professional competence in computer modeling of mathematical models of biological processes.

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Journal articles on the topic 'Biological Mathematics'

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