Locations, trips, travel times, and travel distances for the simulation of an integrated item-sharing and crowdshipping platform in Atlanta, Georgia, US. Further information is provided in Description_of_files.html.
The data is test stress-strain data for cadaveric human supraspinatus tendon obtained in a uni-axial tensile test on MTS EM Tension testing equipment at University of South Africa's Biomechanics Research Laboratory. The equipment was operated in displacement mode on all the three tests at 0.1 s-1 of strain rate. The samples were not preconditioned. All columns are appropriately labelled to enable researchers to understand what each column represents. The test equipment did not have an environmental chamber at the time of the test so the samples were inevitably exposed to varying conditions before and during the test procedure.
This is a main processing MATLAB program file. It calculates the stress using nonlinear least squares curve fitting routine.
The function is called by the above file to fetch test data from the Excel file 'TestData.xlsx' and extracts only the section within the elastic region. There are three tests in the file and each test data is different in terms of the upper limit of the elastic region. The function calls each test data as specified in its argument.
This MATLAB function implements the Yeoh material model.
This MATLAB function implements the standard nonlinear solid model using the sigmoidal kernel function.
This a data about the corona virus COVID-19. It contains the actual reported data. Also, it includes the predicted COVID-19 data in the future based on a model developed to predict in the future. The model used will be published in one of the journals later and will be found on my profile with title "Optimistic Prediction Model For the COVID-19 Coronavirus Pandemic based on the Reported Data Analysis".
The daily folder contains the daily data. The predicted folder contains the predicted data for each country. The total cases folder contains the total cases for each country. he section folder contains a latex code for plotting the figures for each country. Also the source file from European Centre for Disease Prevention and Control is included. More updated files available in the website of European Centre for Disease Prevention and Control.
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 is a survey data collected in two rounds from the Kilosa district in the Morogoro region located in Eastern Tanzania, which is among the six biggest maize producing regions in Tanzania. Maize is the main food and income generating crop in Kilosa. The district is characterised by a semi-humid tropical climate. Its mean annual rainfall ranges between 800mm and 1400mm. The district receives long-term rainfall from March to early June and ‘short rains’ from November to January. The district experiences a long dry season between June and October. The temperature ranges from 18 to 30 degrees centigrade, depending on the altitude. These conditions offer a typical climate for maize production and a suitable case study area. Although Kilosa district has two rainy seasons, the pattern and amount of rainfall allow for only one harvest of the main staples per cropping season.
The survey sample consisted of 420 households in 21 villages in the Kilosa district. The sampling process involved two steps of random selection. First, a list of villages in Kilosa district which met two criteria: (1) maize is the main crop produced by the villagers and (2) maize is the main staple food in the village was obtained; and 21 villages were selected from the list. Second, 20 maize farming households from the household roster in the village office were randomly selected.
This is a database with the information on the conferimed cases and deaths, per million people in Colombia, from 20 March 2020 to 10 May 2020.
Sources of information to create the dataset:
1. INS (Instituto Nacional de Salud) National Health Institute
2. DANE (Departamento Administrativo Nacional de Estadistica) National Department of Statistics
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
This was a cross-sectional study made on a sample of 224 respondents, aged 18 - 67 years (M = 39.18, SD = 11.15). The other characteristics of the sample are presented in Appendix A. Data were collected through several online survey campaigns made on social media networks, in Romania. The subjects were told that their participation helps researchers to better understand the predictors of road accidents and received no financial compensation for their effort. In order to be eligible to participate in the study, participants had to own a valid driving license and regularly drive a vehicle.
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.