Filter Results
348105 results
data set for an online study exploring the role of the decoy effect in sustainable food choice
Data Types:
  • Software/Code
  • Dataset
The data source is a questionnaire survey conducted in July 2018. The survey was designed and administered to students from four junior middle schools at Midu County by “Peking University Caitong EconEdu for Kids”. This voluntary program aims to improve rural children’s financial literacy by offering free short-term financial education courses in rural schools. Located in the Dali Bai Autonomous Prefecture of Yunnan Province, Midu County is one of the nationally-designated poor counties, with the largest proportion of the poverty population in Dali and a high rate of migrant worker outflow. Many teenagers remain in rural regions while their parents leave to work in urban areas. Rural Midu has been experiencing high dropout rate during recent years and the teenager students who drop out of school usually go to work. Therefore, our sample students are representative of the population in question. The survey interviews 1737 students in total. This dataset contains a large range of data items relating to: (1) basic personal information and family background; (2) understanding of financial information on government subsidy policies in compulsory education; (3) financial knowledge measured by the understanding of compound interest, inflation and personal financing; (4) financial behavior in terms of budget planning and saving; (5) willingness to study, measured by self-assessed opportunity cost of attending school, expected future earnings and preference for savings for further education.
Data Types:
  • Software/Code
  • Dataset
This data set corresponds to the experimental data reported in the manuscript "E-DATA: a comprehensive field campaign to investigate evaporation enhanced by advection in the hyper-arid Altiplano" by Francisco Suárez, Felipe Lobos, Alberto de la Fuente, Jordi Vilà-Guerau de Arellano, Ana Prieto, Carolina Meruane and Oscar Hartogensis. The data are in matlab (*.mat) or ascii files (*.dat or *-csv). Each file has a description of the data (variables, units, etc.)
Data Types:
  • Software/Code
  • Tabular Data
  • Dataset
  • Document
Using the PiKh–model [1], a test data set for training the neural network is formed. The data for training is presented in the file (raw_data_table.csv). The architecture of the neural network can be arbitrary and is set by the settings file (experiment_plan.json). To build the architecture of a neural network, it is necessary to determine the names of the input nodes, the names of the output nodes and set the parameters for hidden layers and the output layer. Each output layer is characterized by a name and parameters that determine the number of nodes, the type of activation function, the optimization algorithm, and the method for distributing errors between nodes. The settings file allows you to set the number of epochs during the training of the neural network, the interval between epochs when the learning results are saved (the interval of data recording on the hard disk), the error value (MSE), and the value of the task stop time for cooling the processor. The values of the output streams for the output sections m=7.8 are presented in the file (epoch0000300000_R.xlsx) under the column names (7.outputA), (8.outputA). The values (7.outputA), (8.outputA) are defined for each row of the test data set for training the neural network.
Data Types:
  • Software/Code
  • Tabular Data
  • Dataset
  • Document
The objective of this dataset was to present the forage biomass production over time in different pasture management systems. We selected two farms located in the Western region of São Paulo State, Brazil. Pasture field data collection was carried out in two farms during three dates (June and November 2018 and March 2019) over two seasons (wet and dry). Samples were regularly taken through time to monitor forage biomass. These fields represent a wide variety of pasture management, as follow: Farm 1 (Santa Clara): i) traditional, low forage productivity, cattle rotation; ii) traditional, intermediate forage productivity, fertilized, cattle rotation; iii) intensified pasture, high forage productivity, reformed, cattle rotation. Farm 2 (Poderosa): i) traditional degraded*, recently reformed with millet + grass, cattle rotation; ii) traditional, low forage productivity, signs of degradation, fertilized, cattle rotation. *degraded was based on visual analysis of pasture area with sparse grass and exposed soil in some areas. With the support of NDVI images from the MODIS sensor, sample pixels were used to allocate the sample points. The areas of these pixels were divided into nine sampling points and in each of these points, the forage biomass was collected. Soil analyses were also carried out in two seasons (June 2018 and March 2019). The data files were organized in three folders. Each folder represents one field campaign. These folders have a shapefile of all the fields, the same file in kml extension (to open on Google Earth) and a zip file with photography of each field during the field campaign. The attribute table of the shapefile has a description of the fields and biomass. Excel files show the same information of the attribute table and a description of the items. A figure with the template of the biomass collection scheme is also available. Soil analyses are in the folders 'June 2018' and 'March 2019'. A more detailed description and discussion about these data and their association with soil chemical analysis were described in a scientific report (available by request). The biomass collection allowed the analysis of the forage production and better diagnoses about resource utilization strategies over the different pasture systems. This work was funded by the São Paulo Research Foundation (process numbers 2018/10770-1, 2017/06037-4, 2016/08741-8, 2017/08970-0, 2018/11052-5 and 2014/26767-9) as part of the Global Sustainable Bioenergy Initiative.
Data Types:
  • Software/Code
  • Geospatial Data
  • Tabular Data
  • Dataset
  • Document
  • File Set
A double-sided non-cooperative game with multiple firms and multiple customers based on supply function equilibrium model and demand response. Programs and data is contained in the Programs folder. Please execute loaddata.mat before executing any other programs. The data format and content is described in loaddata.mat
Data Types:
  • Software/Code
  • Dataset
Total RNA was purified from E. pacifica using with an RNeasy Lipid tissue mini kit. The library of E. pacifica for next generation sequencing was made using with a TruSeq RNA library prep kit v2 (Illumina). RNA purification and library preparation were performed according to the manufacturers’ instructions. The library was analyzed by Miseq using a Miseq reagent kit v3 (600 cycle) (Illumina). The fastaq data was assembled by Trinity.
Data Types:
  • Dataset
  • Text
The repository contains the ERP data for self-face, friend's face and other's face perception. Raw Data folder contain the EEG data in Brain Products format. Epoched Data folder contain processed EEG data in EEGLAB format. sLORETA files folder contain data of source mean amplitude within-cluster of significant correlations between ERP and heartbeat perception scores. Also, repository include subject description file with the antropometric and psychometric data.
Data Types:
  • Other
  • Software/Code
  • Tabular Data
  • Dataset
  • Text
Data contains all measured striae on slickensides in volcanic rocks within the Lutynia and Ladek Zdrój area catogorized to individual paleostress patterns. Dataset for SW Faultkin7 contains data for iwhole paleostress pattern, datasets for SW Rock2014 contains data for individual paleostress states.
Data Types:
  • Dataset
  • Text
This dataset contains cross-sectional and longitudinal tongue images and assessments obtained from 206 ALS patients and 104 age- and sex-matched controls that underwent high-resolution ultrasound (HRUS) and 3T MRI. In each image, the tongue is delineated in an additional region of interest (ROI) file provided for each of the coronal cross-sections acquired via HRUS and the midsagittal slices from the sagittal cerebral 3D-MPRAGE 3T MRI of the head. For these ROIs size and mean intensity markers are calculated. From the MRI images quantitative parameters for the shape and relative position of the tongue are derived. For each individual in the dataset these obtained markers are provided along with demographic and disease specific information in accompanying lists. The dataset can be combined with other data to increase statistical power or to extend the analysis with more advanced algorithms to implement and study additional markers for size, shape or texture of the tongue in ALS patients and controls.
Data Types:
  • Software/Code
  • Tabular Data
  • Dataset
  • File Set