"The Analysis tools of three-dimensional weather radar data: ANT3D was originally developed at the National Research Institute for Earth Science and Disaster prevention (NIED) to retrieve three-dimensional precipitation and wind fields of convective storms. The source codes were written by FORTRAN. In 2013, Kagoshima University made a significant revision of ANT3D to analyze volcanic eruption clouds. The main revisions were improvements of the temporal and spatial interpolation of radar data and the estimation of advection vector which is necessary for the temporal interpolation." (From Maki and Kobori, 2020)
Two programs ʹANT3D_GUIʹ and ʹCAPPI viewerʹ are available here.
These programs are still under development.
Maki, M., Kobori, T., 2020. Construction of Three-Dimensional Weather Radar Data of Volcanic Eruption Clouds. MethodsX. (submitted)
We used pooled CRISPR/Cas9 screens in the human RPE1-hTERT p53-/- cell line against 27 genotoxic agents. The Dataset herein make the primary data available. The files are:
* Additional genes of interest (discussion and data relating to TMEM2, ESD, USP37, PHF12, BTAF1 and DRAP1)
* Supplementary Raw Data: Data used to make all the graphs in the manuscript
* Folder "CRISPR screen readcount files". Readcounts for the screens undertaken as part of this study.
* Folder "Raw images for immunoblots": uncropped images for all the blots in the manuscript
* Folder: "Additional QC analyses of CRISPR screens": Additional analyses that measure the quality of the screens using Presion-Recall curves of essential genes and an estimate of genes that scored as hits due to batch effects.
* Folder "Data_Analysis_Code" R markdown file along with data files
* File: "Additional Genes of Interests" contains a short discussion of genes we found noteworthy after analysis of our screen data.
Version 2 note: this version differs from Version 1 by a single file (FDRPos_31screens.csv) which has a tab error fixed.
The presented cross-sectional dataset can be employed to analyze the governmental, trade, and competitiveness relationships of official COVID-19 reports. It contains 18 COVID-19 variables generated based on the official reports of 138 countries, as well as an additional 2203 governance, trade, and competitiveness indicators from the World Bank Group GovData360 and TCdata360 platforms in a preprocessed form. The current version was compiled on July 7, 2020.
Please cite as:
• Kurbucz, M. T. (2020). A Joint Dataset of Official COVID-19 Reports and the Governance, Trade and Competitiveness Indicators of World Bank Group Platforms. Data in Brief, 105881.
• Data generation (data_generation. Rmd): Datasets were generated with this R Notebook. It can be used to update datasets and customize the data generation process.
• Country data (country_data.txt): Country data.
• Metadata (metadata.txt): The metadata of selected GovData360 and TCdata360 indicators.
• Joint dataset (joint_dataset.txt): The joint dataset of COVID-19 variables and preprocessed GovData360 and TCdata360 indicators.
• Correlation matrix (correlation_matrix.txt): The Kendall rank correlation matrix of the joint dataset.
Raw data of figures and tables:
• Raw data of Fig. 2 (raw_data_fig2.txt): The raw data of Fig. 2.
• Raw data of Fig. 3 (raw_data_fig3.txt): The raw data of Fig. 3.
• Raw data of Table 1 (raw_data_table1.txt): The raw data of Table 1.
• Raw data of Table 2 (raw_data_table2.txt): The raw data of Table 2.
• Raw data of Table 3 (raw_data_table3.txt): The raw data of Table 3.
The MATLAB program solve_morphology3.m takes in embryo transfer information including age at oocyte retrieval, number of embryos of each embryo quality grouping, and number of live births that resulted. The program uses linear algebra to solve for the best fit live birth rates for embryos in each quality group and age using moving centered age groups centered on the age of interest. The analysis is performed for moving centered age groups of 1, 3, 5, 7, and 9 years. The program can analyze any number of embryo quality groupings (such as good/fair/poor or excellent/good/fair/poor or others). A description of the program including required inputs and outputs is included in the comments section at the beginning of the code.
In this dataset, we use the theory of auction between relay nodes of Delay/disruption-tolerant Networks (DTNs) to motivate them to collaborate in forwarding messages. Based on the second-price sealed-bid auction mechanism, the node that does not cooperate in forwarding messages fails to acquire utility. In this way, if the node itself intends to send a message to another node, it will not be able to do so due to a lack of budget. Thus, the selfish behavior of the node causes the node to be harmed.
The data set is from a series of two eye tracking experiments testing the role of statistical learning induced by frequency manipulation of salient distractor trials on its the suppression during active visual search. Salient distractor present trials could make up for 20%, 50% and 80% of total trials, along with salient distractor absent trials, in each block. We expected RTs, dwell time, and saccade latency and percentage of saccades to indicate suppression of salient distractor and that it would vary across blocks. The trial reports were used for reaction time and accuracy analysis, the fixation report for dwell time analysis and percent of fixations, and the saccade report for first saccade latency and proportion analysis. The experiment has a distractor (present vs absent) and block (20,50,80) within-subjects design. The raw data files as well as R codes for linear mixed model analysis are available here.
We found better suppression in the 20 and 80 block compared to the 50 block.