The aim of this study was to develop a realistic network model to predict qualitatively the relationship between lockdown duration and coverage in controlling the progression of the incidence curve of an epidemic with the characteristics of COVID-19 in a closed and non-immune population.
Effects of lockdown time and rate on the progression of an epidemic incidence curve in a virtual closed population of 10 thousand subjects. Predictor variables were R0 values established in the most recent literature (2.7 and 5.7), without lockdown and with coverages of 25%, 50%, and 90% for 21, 35, 70, and 140 days in 13 different scenarios for each R0, where individuals remained infected and transmitters for 14 days. We estimated model validity by applying an exponential model on the incidence curve with no lockdown, with growth rate coefficient observed in realistic scenarios. Pairwise comparisons were performed using Wilcoxon test with Bonferroni correction between peak amplitude, peak latency, and total number of cases for each R0 used.
For R0=5.7, the flattening of the curve occurs only with long lockdown periods (70 and 140 days) with a 90% coverage. For R0=2.7, coverages of 25 and 50% also result in curve flattening and reduction of total cases, provided they occur for a long period (70 days or more). Short and soft lockdowns had no relevant effect on incidence or casuistry.
These data corroborate the importance of lockdown duration regardless of virus transmission.
This dataset includes four bioinformatic pipelines to analyze data generated through 3' RACE-seq or TAIL-seq experiments in Arabidopsis thaliana or in Nicotiana benthamiana. These pipelines allow measuring the mRNA poly(A) tail length and detecting other 3’ untemplated nucleotides. This dataset contains all scripts and files that are required for the analyses, including all homemade python and bash scripts.
This case represents part of the European high voltage transmission network. It contains 1,354 buses, 260 generators, 1,991 branches and it operates at 380kV and 220kV. The data stems from the Pan European Grid Advanced Simulation and State Estimation (PEGASE) project. The PEGASE original data was obtained from Matpower (Which is also included here). The case has been modified to incorporate an HVDC Link and a MTDC grid. Two files contain the modified data, one in excel and one in AIMMS.dat
Here are the data and the codes used in Hiramoto&Cline (2020). Imaris image data, Matlab code, and data in mat or fig (with metadata) files are provided. These Matlab codes require a statistic toolbox.
The data validates several results published in the study titled "A comparative study of the effect of random and preferred crystallographic orientations on dynamic recrystallization behavior using a cellular automata model" in Materials Today: Communications (https://doi.org/10.1016/j.mtcomm.2020.101200). The description of the files is:
1. Orientation files.zip has the orientation files to reproduce Fig. 15 onwards in the manuscript.
2. The excel file is the misorientation data for Fig. 11 in the manuscript.
3. The remaining two .txt files are for reproducing Fig. 4 in the manuscript.