APP MTH 7088 - Applied Mathematics Topic F
North Terrace Campus - Semester 2 - 2016
The course information on this page is being finalised for 2016. Please check again before classes commence.
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General Course Information
Course Details
Course Code APP MTH 7088 Course Applied Mathematics Topic F Coordinating Unit Mathematical Sciences Term Semester 2 Level Postgraduate Coursework Location/s North Terrace Campus Units 3 Available for Study Abroad and Exchange Y Assessment Ongoing assessment 30%, Exam 70% Course Staff
Course Coordinator: Dr David Green
Course Timetable
The full timetable of all activities for this course can be accessed from Course Planner.
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Learning Outcomes
Course Learning Outcomes
In 2015, the topic of this course is Applied Methods in Biology and Engineering.
Syllabus
The goal for this class is for students to develop a fundamental understanding of how mathematics is applied as a tool to aid in studying complex systems in biological and engineering sciences. We will thoroughly investigate case studies in several fields including: Neuron Action Potential Propagation, Cardiac dynamics, Tumor/cancer growth and Pattern formation. Graded work will include a mix of theoretical and computational homework, culminating in a final exam.
Practically speaking, this class is designed for advanced undergraduate, honours, MPhil and beginning PhD students in the mathematical, physical, and biological sciences with a solid mathematical background, i.e., Linear Algebra and Differential Equations. The course prerequisite (which can be waived with instructor approval) is Modelling with Ordinary Differential Equations (APP MTH 3021) and may be taken simultaneously with this course. Also note that familiarity with MATLAB or other programming language is assumed (prerequisites include classes which use MATLAB). The list of mathematical tools and methods that we will learn in this course include:
1) Matched asymptotics, multi-scale modeling: This method will be taught via Michaelis-Menton kinetics, Fitzhugh-Nagumo and Hodgkin-Huxley models.
2) Solving moving boundary problems, traveling wave solutions: This method will be introduced while solving advection-diffusion-reaction equations for tumor growth, pattern formation and the Fisher’s equation.
Learning Outcomes
On successful completion of this course, students will be able to:
1) understand modelling of chemical reactions involving multiple time-scales
2) develop regular as well as singular perturbation formulation for these models
3) understand the concept of non-dimensionalization which distinguishes various time-scales
4) analyse theory of motion, directed motion or taxis, diffusion, steady-state solutions
5) develop and solve traveling wave solutions to reaction-diffusion systems, Fisher’s equation
6) understand pattern formation, Turing instabilities and bifurcations
7) analyse pattern activation and inhibition coupled with biological motionUniversity Graduate Attributes
No information currently available.
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Learning Resources
Required Resources
None.Recommended Resources
Books
[1] James Keener and James Sneyd, Mathematical Physiology I: Cellular Physiology, 2nd edition, Springer, 2009.
[2] N. Britton, Essential Mathematical Biology, Springer, 2005.
[3] L. Edelstein-Keshet, Mathematical models in biology, SIAM, 2005.
[4] J. D. Murray, Mathematical Biology, Springer-Verlag, New York, 2nd edition, 1993.Online Learning
MyUni will be used to provide electronic resources, such as lecture notes, assignment papers, sample solutions, discussion boards, etc. It is recommended that the students make appropriate use of these resources.
See https://myuni.adelaide.edu.au/webapps/login/ -
Learning & Teaching Activities
Learning & Teaching Modes
The lecturer guides the students through the course material in 30 lectures. Students are expected to engage with the material in the lectures. Interaction with the lecturer and discussion of any difficulties that arise during the lecture is encouraged. Fortnightly homework assignments help students strengthen their understanding of the theory and their skills in applying it, and allow them to gauge their progress.Workload
The information below is provided as a guide to assist students in engaging appropriately with the course requirements.
The information below is provided as a guide to assist students in engaging appropriately with the course requirements.
Lectures (x30) = 90 workload hours
Assignments (x6) = 60 workload hours
Test = 6 workload hours
Total = 156 workload hoursLearning Activities Summary
1) Introduction to biochemical kinetics
2) Non-dimentionalization, time-scale analysis, regular and singular perturbation, matched asymptotics
3) Theory of motion, directed motion, diffusion
4) Traveling wave solution, Fisher's equation
5) Pattern formation, Turing instability
6) Solutions at steady-state for non-linear PDEsSpecific Course Requirements
Course prerequisite: Modelling with Ordinary Differential Equations (APP MTH 3021). -
Assessment
The University's policy on Assessment for Coursework Programs is based on the following four principles:
- Assessment must encourage and reinforce learning.
- Assessment must enable robust and fair judgements about student performance.
- Assessment practices must be fair and equitable to students and give them the opportunity to demonstrate what they have learned.
- Assessment must maintain academic standards.
Assessment Summary
Assessment: Assignments
Due: Even weeks
Weighting: 30%
Learning outcomes: All
Assessment: Examination
Due: Examination period
Weighting: 70%
Learning outcomes: AllAssessment Related Requirements
An aggregate score of 50% is required to pass the course.Assessment Detail
There will be a total of 6 homework assignments, distributed during each even week of the semester and due at the end of the following week. Each will cover material from the lectures, and in addition, will sometimes go beyond that so that students may have to undertake some additional research. The 6 assignments will constitute 30% of the final grade.Submission
Homework assignments must either be given to the lecturer in person or left in the box outside the lecturer's office by the given due time. Failure to meet the deadline without reasonable and verifiable excuse may result in a significant penalty for that assignment.Course Grading
Grades for your performance in this course will be awarded in accordance with the following scheme:
M10 (Coursework Mark Scheme) Grade Mark Description FNS Fail No Submission F 1-49 Fail P 50-64 Pass C 65-74 Credit D 75-84 Distinction HD 85-100 High Distinction CN Continuing NFE No Formal Examination RP Result Pending Further details of the grades/results can be obtained from Examinations.
Grade Descriptors are available which provide a general guide to the standard of work that is expected at each grade level. More information at Assessment for Coursework Programs.
Final results for this course will be made available through Access Adelaide.
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Student Feedback
The University places a high priority on approaches to learning and teaching that enhance the student experience. Feedback is sought from students in a variety of ways including on-going engagement with staff, the use of online discussion boards and the use of Student Experience of Learning and Teaching (SELT) surveys as well as GOS surveys and Program reviews.
SELTs are an important source of information to inform individual teaching practice, decisions about teaching duties, and course and program curriculum design. They enable the University to assess how effectively its learning environments and teaching practices facilitate student engagement and learning outcomes. Under the current SELT Policy (http://www.adelaide.edu.au/policies/101/) course SELTs are mandated and must be conducted at the conclusion of each term/semester/trimester for every course offering. Feedback on issues raised through course SELT surveys is made available to enrolled students through various resources (e.g. MyUni). In addition aggregated course SELT data is available.
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Policies & Guidelines
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- Student Experience of Learning and Teaching Policy
- Student Grievance Resolution Process
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