Mathematical and computational modeling of flexoelectricity

2021 ◽  
Vol 130 (23) ◽  
pp. 231102
Author(s):  
D. Codony ◽  
A. Mocci ◽  
J. Barceló-Mercader ◽  
I. Arias
Keyword(s):  
Computational Modeling ◽  
Mathematical And Computational Modeling

Mathematical and computational modeling of nano-engineered drug delivery systems

2019 ◽  
Vol 307 ◽  
pp. 150-165 ◽  
Author(s):  
Milad Shamsi ◽  
Amir Mohammadi ◽  
Mohammad K.D. Manshadi ◽  
Amir Sanati-Nezhad
Keyword(s):  
Drug Delivery ◽  
Computational Modeling ◽  
Drug Delivery Systems ◽  
Delivery Systems ◽  
Mathematical And Computational Modeling

scholarly journals Preface for the Special Issue on Dynamical Models of Biology and Medicine

2019 ◽  
Vol 9 (11) ◽  
pp. 2380
Author(s):  
Yang Kuang ◽  
Meng Fan ◽  
Shengqiang Liu ◽  
Wanbiao Ma
Keyword(s):  
Computational Modeling ◽  
Medical Research ◽  
Rapid Growth ◽  
Special Issue ◽  
Dynamical Models ◽  
Modeling Approaches ◽  
Mathematical And Computational Modeling

Mathematical and computational modeling approaches in biological and medical research are experiencing rapid growth globally [...]

Mathematical and Computational Modeling in Clinical Psychology

2015 ◽  
Author(s):  
Richard W. J. Neufeld
Keyword(s):  
Computational Modeling ◽  
Clinical Science ◽  
Significant Information ◽  
Clinically Significant ◽  
Neuro Imaging ◽  
Basic Ideas ◽  
Specific Disorders ◽  
Methodological Considerations ◽  
Model Features ◽  
Mathematical And Computational Modeling

This chapter begins with an introduction to the basic ideas behind clinical mathematical and computational modeling. In general, models of normal cognitive-behavioral functioning are titrated to accommodate performance deviations accompanying psychopathology; model features remaining intact indicate functions that are spared; those that are perturbed are triaged as signifying functions that are disorder affected. Distinctions and interrelations among forms of modeling in clinical science and assessment are stipulated, with an emphasis on analytical, mathematical modeling. Preliminary conceptual and methodological considerations are presented. Concrete examples illustrate the benefits of modeling as applied to specific disorders. Emphasis in each case is on clinically significant information uniquely yielded by the modeling enterprise. Implications for the functional side of clinical functional neuro-imaging are detailed. Challenges to modeling in the domain of clinical science and assessment are described, as are tendered solutions. The chapter ends with a description of continuing challenges and future opportunities.

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