PythonProgram_DAEs

The Python program includes two sources files (main.py & NSmodel.py) designed to do all the computations for the paper titled "DAEs-driven Dynamics and North-South Protection of IPRs" (by Hwan C. Lin). This paper now is titled "A Dynamic Modelling Approach to North-South Disparities in IPR Protection" and published in Oxford Economic Papers: https://doi.org/10.1093/oep/gpaf024. The main tasks of the Python program are to solve a North-South dynamical system of differential algebraic equations (DAEs) and compute intertemporal welfare effects. The Python program is coded using Anaconda Python 3.12.7. To run this Python program, one should save the two source files into the same folder of your computer. The file of main.py is the driver, while the file of NSmodel.py declares a Python class including class members and class functions. Specifically, the Python program accomplishes the following: Solve the North-South dynamical system of DAEs with the Python solver "scipy.integrate.solve_bvp" for a nonlinear stable manifold and the time paths of variables that evolve in transition to steady state; Compute steady state equlibirums for various scenarios; Compute intertemporal welfare effects for the North and South when Southern IPRs are tightened to match the Northern standard. Robustness checks on the coefficient of creative destruction. The Python program includes detailed remarks in order for the code to be reader-friendly. The two source files (main.py & NSmodel.py), which have been updated to reduce typographical errors in the code's remarks, are also available at Github: https://github.com/hwanclin/PythonProgram_DAEs

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-04-17
DOI
https://doi.org/10.5281/zenodo.15233607
Primary Topic
Traumatic Ocular and Foreign Body Injuries
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

PythonProgram_DAEs

Zenodo (CERN European Organization for Nuclear Research)
Traumatic Ocular and Foreign Body Injuries
article

PythonProgram_DAEs

article en

Abstract

The Python program includes two sources files (main.py & NSmodel.py) designed to do all the computations for the paper titled "DAEs-driven Dynamics and North-South Protection of IPRs" (by Hwan C. Lin). This paper now is titled "A Dynamic Modelling Approach to North-South Disparities in IPR Protection" and published in Oxford Economic Papers: https://doi.org/10.1093/oep/gpaf024. The main tasks of the Python program are to solve a North-South dynamical system of differential algebraic equations (DAEs) and compute intertemporal welfare effects. The Python program is coded using Anaconda Python 3.12.7. To run this Python program, one should save the two source files into the same folder of your computer. The file of main.py is the driver, while the file of NSmodel.py declares a Python class including class members and class functions. Specifically, the Python program accomplishes the following: Solve the North-South dynamical system of DAEs with the Python solver "scipy.integrate.solve_bvp" for a nonlinear stable manifold and the time paths of variables that evolve in transition to steady state; Compute steady state equlibirums for various scenarios; Compute intertemporal welfare effects for the North and South when Southern IPRs are tightened to match the Northern standard. Robustness checks on the coefficient of creative destruction. The Python program includes detailed remarks in order for the code to be reader-friendly. The two source files (main.py & NSmodel.py), which have been updated to reduce typographical errors in the code's remarks, are also available at Github: https://github.com/hwanclin/PythonProgram_DAEs

Zenodo (CERN European Organization for Nuclear Research)
Peace, Justice and strong institutions
Openalex Percentile: Top 40%
Traumatic Ocular and Foreign Body Injuries
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.