The Experts below are selected from a list of 107106 Experts worldwide ranked by ideXlab platform
Jasmina Panovskagriffiths - One of the best experts on this subject based on the ideXlab platform.
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can Mathematical Modelling solve the current covid 19 crisis
BMC Public Health, 2020Co-Authors: Jasmina PanovskagriffithsAbstract:Since COVID-19 transmission started in late January, Mathematical Modelling has been at the forefront of shaping the decisions around different non-pharmaceutical interventions to confine its’ spread in the UK and worldwide. This Editorial discusses the importance of Modelling in understanding Covid-19 spread, highlights different Modelling approaches and suggests that while Modelling is important, no one model can give all the answers.
Mohammad Kohandel - One of the best experts on this subject based on the ideXlab platform.
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Mathematical Modelling of phenotypic plasticity and conversion to a stem cell state under hypoxia
Scientific Reports, 2016Co-Authors: Andrew Dhawan, Seyed Ali Madani Tonekaboni, Joseph H Taube, Stephen Hu, Nathalie Sphyris, Sendurai A Mani, Mohammad KohandelAbstract:Hypoxia, or oxygen deficiency, is known to be associated with breast tumour progression, resistance to conventional therapies and poor clinical prognosis. The epithelial-mesenchymal transition (EMT) is a process that confers invasive and migratory capabilities as well as stem cell properties to carcinoma cells thus promoting metastatic progression. In this work, we examined the impact of hypoxia on EMT-associated cancer stem cell (CSC) properties, by culturing transformed human mammary epithelial cells under normoxic and hypoxic conditions, and applying in silico Mathematical Modelling to simulate the impact of hypoxia on the acquisition of CSC attributes and the transitions between differentiated and stem-like states. Our results indicate that both the heterogeneity and the plasticity of the transformed cell population are enhanced by exposure to hypoxia, resulting in a shift towards a more stem-like population with increased EMT features. Our findings are further reinforced by gene expression analyses demonstrating the upregulation of EMT-related genes, as well as genes associated with therapy resistance, in hypoxic cells compared to normoxic counterparts. In conclusion, we demonstrate that Mathematical Modelling can be used to simulate the role of hypoxia as a key contributor to the plasticity and heterogeneity of transformed human mammary epithelial cells.
Leon Danon - One of the best experts on this subject based on the ideXlab platform.
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Mathematical Modelling of infectious diseases
British Medical Bulletin, 2009Co-Authors: Matthew James Keeling, Leon DanonAbstract:Mathematical models allow us to extrapolate from current information about the state and progress of an outbreak, to predict the future and, most importantly, to quantify the uncertainty in these predictions. Here, we illustrate these principles in relation to the current H1N1 epidemic. Many sources of data are used in Mathematical Modelling, with some forms of model requiring vastly more data than others. However, a good estimation of the number of cases is vitally important. Mathematical models, and the statistical tools that underpin them, are now a fundamental element in planning control and mitigation measures against any future epidemic of an infectious disease. Well-parameterized Mathematical models allow us to test a variety of possible control strategies in computer simulations before applying them in reality. The interaction between modellers and public-health practitioners and the level of detail needed for models to be of use. The need for stronger statistical links between models and data. Greater appreciation by the medical community of the uses and limitations of models and a greater appreciation by modellers of the constraints on public-health resources.
Werner Blum - One of the best experts on this subject based on the ideXlab platform.
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crossing boundaries in Mathematical Modelling and applications educational research and practice
2017Co-Authors: Gloria Stillman, Werner Blum, Gabriele KaiserAbstract:This chapter gives an overview on the current state-of-the-art on the teaching and learning of Mathematical Modelling and applications and its contribution to educational research and practice which is reflected in the various contributions in this book. Several chapter authors use the opportunity to strengthen and build our research practices by reaching out to others in educational research, beyond the boundaries of our community, and those in fields other than education. By researchers recognising boundaries in applications and Modelling research that limit our vision and what we are currently able to do, a more entrepreneurial view of research groups could lead to the brokerage of knowledge in multidisciplinary or multi-community teams to work on some of the more perplexing research questions that have faced our research community. Fluid social alliances in research groups that coalesce and then disperse could result in a much wider dissemination of knowledge both to, and from, our community in the future.
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scaffolding Mathematical Modelling with a solution plan
Zdm, 2015Co-Authors: Stanislaw Schukajlow, Jana Kolter, Werner BlumAbstract:In the study presented in this paper, we examined the possibility to scaffold Mathematical Modelling with strategies. The strategies were prompted using an instrument called “solution plan” as a scaffold. The effects of this step by step instrument on Mathematical Modelling competency and on self-reported strategies were tested using nineth grade students (N = 91) at a German middle track school (Realschule) in a quasi-experimental design. Six classes were randomly assigned to the experimental group, in which students used the solution plan, or to the control group. The quantitative data analysis using ANOVAs reveals that (1) in the posttest the experimental group students reported more frequently about planning, rehearsal, elaboration and organizing strategies while solving Modelling problems than the control group; (2) the “solution plan” as a scaffold supports the development of students’ Modelling competency, including its sub-competencies. The students who used the solution plan outperformed the other students in solving Modelling problems concerning the topic “Pythagorean theorem”.
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quality teaching of Mathematical Modelling what do we know what can we do
2015Co-Authors: Werner BlumAbstract:The topic of this paper is Mathematical Modelling or—as it is often, more broadly, called—applications and Modelling. This has been an important topic in mathematics education during the last few decades, beginning with Pollak’s survey lecture (New Trends in Mathematics Teaching IV, Paris, pp. 232–248, 1979) at ICME-3, Karlsruhe 1976. By using the term “applications and Modelling”, both the products and the processes in the interplay between the real world and mathematics are addressed. In this paper, I will try to summarize some important aspects, in particular, concerning the teaching of applications and Modelling.
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Mathematical Modelling in teacher education experiences from a Modelling seminar
2010Co-Authors: Rita Borromeo Ferri, Werner BlumAbstract:Mathematical Modelling has recently become a compulsory part of the mathematics curriculum in Germany. Hence future teachers must have a strong background about different aspects of Modelling and also about appropriate methods how Modelling can be taught. That means that the content and the methodology of university courses on Modelling have to include all these aspects. In our paper, we will report on university seminars on Modelling for students in their fourth year of study. Among other things, the students had to write a “learning diary” over the whole semester. The results give interesting insights in students’ learning processes of Modelling, their progress and their problems during the semester and their considerations about teaching Modelling.
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Mathematical Modelling can it be taught and learnt
Journal of Mathematical Modelling and Application, 2009Co-Authors: Werner Blum, Rita Borromeo FerriAbstract:Mathematical Modelling ( the process of translating between the real world and mathematics in both directions ) is one of the topics in mathematics education that has been discussed and propagated most intensely during the last few decades. In classroom practice all over the world, however, Modelling still has a far less prominent role than is desirable. The main reason for this gap between the goals of the educational debate and everyday school practice is that Modelling is difficult both for students' and for teachers. In our paper, we will show examples of how students and teachers deal with demanding Modelling tasks. We will refer both to results from our own projects DISUM and COM² as well as to empirical findings from various other research studies. First, we will present some examples of students' difficulties with Modelling tasks and of students' specific Modelling routes when solving such tasks (also dependent on their Mathematical thinking styles), and try to explain these difficulties by the cognitive demands of these tasks. We will emphasise that Mathematical Modelling has to be learnt specifically by students, and that Modelling can indeed be learned if teaching obeys certain quality criteria, in particular maintaining a permanent balance between teacher's guidance and students' independence. We will then show some examples of how teachers have successfully realised this subtle balance, and we will present interesting differences between individual teachers ' handling of Modelling tasks. In the final part of our paper, we will draw some consequences from the reported empirical findings and formulate corresponding implications for teaching Mathematical Modelling. Eventually, we will present some encouraging results from a recent intervention study in the context of the DISUM project where it is demonstrated that appropriate learning environments may indeed lead to a higher and more enduring progress concerning students' Modelling competency.
Dipak Mazumdar - One of the best experts on this subject based on the ideXlab platform.
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The Physical and Mathematical Modelling of Gas Stirred Ladle SYstems
2014Co-Authors: Dipak Mazumdar, Roderick L. L. GuthrieAbstract:Considerable efforts have been madeduring the past two decadesto investigate gas injection operations in steelmaking ladles. Towards these, numerous physical and Mathematical model studies embodying aqueousas well as full sca[e systems have been reported. Onthe basis of an extensive literature search, a summary, discussion and analysis of these are now presented. For the sake of convenience and clarity of presentation, studies have been categorised into three major groups: (1 physical mode]]ing studies, (2) combined physica] and Mathematical Modelling studies and (3) Mathematical Modelling studies. In each of these categories, a great numberof publications on various phenomena,such as gas-liquid interactions, turbulent fluid flow, mixing, solid-Iiquid masstransfer, etc. have been reported. Accordingly, and as discussed in the text, considerable improvements have resulted in our understanding of the various gas injection induced phenomenain ladle metallurgy operations. Coupled with these, extensive Mathematical Modelling studies have also lead to a reasonably accurate framework for carrying out engineering design and process calculations. Nonetheless, someobscu~ities and uncertainties still remain and these are pointed out, together with those areas where further work is needed. KEYWORDS: overview; gas stirred ladles; fluid dynamics; heat transfer; masstransfer physical Modelling; Mathematical Modelling. 1
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the physical and Mathematical Modelling of continuous casting tundish systems
Isij International, 1999Co-Authors: Dipak Mazumdar, Roderick I. L. GuthrieAbstract:Considerable efforts have been made in academia and industry over the last two decades to fully exploit and enhance the metallurgical performance of continuous casting tundish systems. Towards these goals, numerous physical and Mathematical Modelling studies embodying both industrial and water model tundishes have been carried out and reported in the literature. Based on an extensive literature search, we now present a summary, discussion and analysis of these. For the sake of convenience and clarity of presentation, the studies have been categorised into three major groups: (1) physical Modelling (2) Mathematical Modelling and (3) combined physical and Mathematical Modelling. In each of these categories, a great number of publications on various aspects of tundish metallurgy, such as, Modelling criteria, turbulent fluid flow, residence time distributions (RTD), inclusion transport and separation, heat loss and temperature drop, grade transition and intermixing, etc. have been reported. These works have lead to considerable improvements in our understanding of the various transport processes (viz, RTD, inclusion float out, thermal energy transport, etc.) associated with tundish operations. Comprehensive and sufficiently reliable Mathematical models are also currently available and these also allow one to carry out full scale predictions and useful engineering design and process calculations. None the less, certain obscurities and uncertainties remain. These are reviewed together with suggestions of areas where further research is needed.
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the physical and Mathematical Modelling of gas stirred ladle systems
Isij International, 1995Co-Authors: Dipak Mazumdar, Roderick I. L. GuthrieAbstract:Considerable efforts have been made during the past two decades to investigate gas injection operations in steelmaking ladles. Towards these, numerous physical and Mathematical model studies embodying aqueous as well as full scale systems have been reported. On the basis of an extensive literature search, a summary, discussion and analysis of these are now presented. For the sake of convenience and clarity of presentation, studies have been categorised into three major groups: (1) physical Modelling studies, (2) combined physical and Mathematical Modelling studies and (3) Mathematical Modelling studies. In each of these categories, a great number of publications on various phenomena, such as gas-liquid interactions, turbulent fluid flow, mixing, solid-liquid mass transfer, etc. have been reported. Accordingly, and as discussed in the text, considerable improvements have resulted in our understanding of the various gas injection induced phenomena in ladle metallurgy operations. Coupled with these, extensive Mathematical Modelling studies have also lead to a reasonably accurate framework for carrying out engineering design and process calculations. Nonetheless, some obscurities and uncertainties still remain and these are pointed out, together with those areas where further work is needed.
