Resources for Educators
1. Inverted-classroom teaching modules to educate MATLAB in chemical process control
USA students are falling behind their peers in other countries as shown in this news. The aim of our study is to develop innovative teaching modules to facilitate students' learning in the field of process modeling and control. In particular, we implemented the core techniques of process modeling and control in MATLAB/Simulink, which offers user-friendly interface and which makes solving math problems like kids playing Lego. Three teaching modules are developed, including 11 examples and 13 videos that deal with solving ODE models, performing Laplace transform, and designing PID controllers. Our teaching modules have been published in Paper "X. Li, Z. Huang. An Inverted Classroom Approach to Educate MATLAB in Chemical Process Control, Education for Chemical Engineers, 19, 1-12, 2017. " These materials are only allowed for academic purpose, NOT for commercial usage. Questions are welcomed to send to Dr. Huang (zuyi.huang@villanova.edu), but they are not guaranteed for prompt response due to Dr.Huang’s work commitment.
1) Paper "X. Li, Z. Huang. An Inverted Classroom Approach to Educate MATLAB in Chemical Process Control, Education for Chemical Engineers, 19, 1-12, 2017"
2) Videos for Example 1 include Part 1, Part 2, and Part 3.
3) Videos can be downloaded for Example 2, Example 3, Example 4, Example 5, Example 6, Example 7, Example 8, and Example 9.
4) Videos can be downloaded for Example 10 and Example 11.
5) The handout of all MATLAB modules can be found in this link.
2. MATLAB training videos for Engineering students
Dr. Sergey Nersesov and Dr. Huang developed 17 videos that covered basic MATLAB skills for solving typical problems in engineering (mainly mechanical engineering and chemical engineering). The handouts maybe available upon request. YouTube videos for these 17 MATLAB modules can be found in the following links:
Module 01 Introduction of MATLAB
Module 02 Data format (MATLAB)
Module 03 Data display multiple curves (MATLAB)
Module 04 Data iterative processing function (MATLAB)
Module 05 Interpolation and Curve Fitting (MATLAB)
Module 06 Basics of Statistics （MATLAB）
Module 07 Basics of Linear Algebra (MATLAB)
Module 08 Systems of Linear Algebraic Equations (MATLAB)
Module 09 Systems of Nonlinear Algebraic Equation (MATLAB)
Module 10 Symbolic Integration & Differentiation (MATLAB)
Module 11 Solving ODE in MATLAB and plotting phase diagram
Module 12 Introduction of Simulink and solving ODE models (MATLAB)
Module 13 Solving Linear ODE via Laplace Tranform (MATLAB)
Module 14 Transfer Function and System Response (MATLAB)
Module 15 - Control System Design - Root locus and PID controllers (MATLAB)
Module 16 Animation (MATLAB)
Module 17 Solving Partial Differential Equations (MATLAB)
2. A MATLAB based teaching module for solving and analyzing biological ODE models (Systems Biology)
Dr. Huang is enthusiastic in educating students with practical modeling skills that can be implemented in MATLAB. He is developing innovative teaching strategies (such as flipped-classroom) to enhance students’ enthusiasm in learning process simulation and control techniques.
The MATLAB based teaching module for solving and analyzing ODE models was presented in the paper: K. Lee, N. Comolli, W.J. Kelly, Z. Huang. MATLAB Based Teaching Modules in Biochemical Engineering. Chemical Engineering Education, in press, 2015.The ODE model as well as the MATLAB programs can be found in this document.
3. A video to introduce Cell Metabolism recorded by Dr. Huang
https://www.youtube.com/watch?v=NvBVffHNL7A
4. MATLAB Programs for Signaling Pathway
4.1 The IL-6 ~ IL-10 signaling model
The MATLAB model was presented in the paper " C. Moya*, Z. Huang*, P. Cheng, A. Jayaraman, and J. Hahn. Investigation of IL-6 and IL-10 Signaling in Steatosis via Mathematical Modeling. IET Systems Biology, 5, No. 1, pp. 15-26, 2011 (*equal contribution)". Please read the appendix of this paper for the detail of the ODE model and parameters. The inputs of the model are the concentrations of IL-6 and IL-10, while the outputs the model include the concentrations of transcription factors nuclear STAT3 dimer and C/EBPβ.
The MATLAB program can be downloaded here. Please run the Main function to run the simulation. Please cite our paper if you use our model/program.
4.2 The TNF-α ~ NFκB signaling model
This is the model that was presented in our paper Z. Huang, F. Senocak, A. Jayaraman, and J. Hahn. Integrated Modeling and Experimental Approach for Determining Transcription Factor Profiles from Fluorescent Reporter Data. BMC Systems Biology 2:64 (2008).The input of the model is the concentrations of TNF-α, while the output the model include the concentrations of transcription factor NFκB.
The MATLAB program can be downloaded here. Please run the Main function to run the simulation. Please cite our paper if you use our model/program.
4.3 Fluorescent image analysis program
The image algorithm was presented in our paper Z. Huang, F. Senocak, A. Jayaraman, and J. Hahn. Integrated Modeling and Experimental Approach for Determining Transcription Factor Profiles from Fluorescent Reporter Data. BMC Systems Biology 2:64 (2008). It can identifty fluorescent cell regions from fluorescent images.
The The MATLAB program can be downloaded here (200M). Please read the readme document herebefore downloading and running the program. Please cite our paper if you use our model/program.