ASU Scholarship Showcase
- 2 College of Liberal Arts and Sciences
- 2 Kuang, Yang
- 2 School of Mathematical and Statistical Sciences
- 1 Allali, Karam
- 1 Baez, Javier
- 1 Cheng, Kewei
- 1 Danane, Jaouad
- 1 Ira A. Fulton Schools of Engineering
- 1 Li, Hao
- 1 Lin, Fan
- 1 Liu, Zhijian
- 1 School of Computing, Informatics and Decision Systems Engineering
- 1 Tang, Xindong
- 1 Wang, Run
- 3 English
- 3 Text
- 3 Public
A modified mathematical model describing the human immunodeficiency virus (HIV) pathogenesis with cytotoxic T-lymphocytes (CTL) and infected cells in eclipse phase is presented and studied in this paper. The model under consideration also includes a saturated rate describing viral infection. First, the positivity and boundedness of solutions for nonnegative initial data are proved. Next, the global stability of the disease free steady state and the endemic steady states are established depending on the basic reproduction number R[subscript 0] and the CTL immune response reproduction number R[subscript CTL]. Moreover, numerical simulations are performed in order to show the numerical stability for ...
- Allali, Karam, Danane, Jaouad, Kuang, Yang, et al.
- Created Date
1,1,1,2,3,3,3-Heptafluoropropane (R227ea) is a good refrigerant that reduces greenhouse effects and ozone depletion. In practical applications, we usually have to know the compressed liquid densities at different temperatures and pressures. However, the measurement requires a series of complex apparatus and operations, wasting too much manpower and resources. To solve these problems, here, Song and Mason equation, support vector machine (SVM), and artificial neural networks (ANNs) were used to develop theoretical and machine learning models, respectively, in order to predict the compressed liquid densities of R227ea with only the inputs of temperatures and pressures. Results show that compared with the Song ...
- Li, Hao, Tang, Xindong, Wang, Run, et al.
- Created Date
Predicting the timing of a castrate resistant prostate cancer is critical to lowering medical costs and improving the quality of life of advanced prostate cancer patients. We formulate, compare and analyze two mathematical models that aim to forecast future levels of prostate-specific antigen (PSA). We accomplish these tasks by employing clinical data of locally advanced prostate cancer patients undergoing androgen deprivation therapy (ADT). While these models are simplifications of a previously published model, they fit data with similar accuracy and improve forecasting results. Both models describe the progression of androgen resistance. Although Model 1 is simpler than the more realistic ...
- Baez, Javier, Kuang, Yang, College of Liberal Arts and Sciences, et al.
- Created Date
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