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this data set accompanies the study on the relationship between ICT and financial development. the variables involved in the study are mobile cellular subscription (lmcs), main telephone lines (lmtl), internet users (liu), and financial development (fd). The values in this dataset are the logarith transformation of their original values. the countries involves in the sample are grouped according to their nation income per capita.
Data Types:
  • Tabular Data
  • Dataset
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
This data set comprises of the underlying data used in Figures 2 (incident UV), 3 & 6 (Temperature, Chl-a and aCDOM), 4 (Kd), 5 (in situ UV exposure) and 7 (projected temperature and UV-B) of the publication entitled "Unraveling the Seasonality of UV Exposure in Reef Waters of a Rapidly Warming (Sub-)tropical Sea". Keywords: Red Sea, coral reefs, marine optics, ultraviolet radiation (UV), daily UV exposure, downwelling diffuse attenuation coefficient (Kd), chlorophyll-a, CDOM, temperature, seasonality, climate change
Data Types:
  • Tabular Data
  • Dataset
The empirical analysis explores annual panel data for 23 developed economies vis-à-vis 21 developing ones, over the period 2002-2017. For each country, we collect the US-denominated price levels of both conventional and Islamic equity market indices, as well as the levels of corruption. Stock market index series are retrieved from the MSCI Barra database, whereas country corruption risk ratings are sourced from the widely adopted International Country Risk Guide (ICRG), which is produced by the Political Risk Services (PRS) Group.
Data Types:
  • Tabular Data
  • Dataset
The original statistical data, lower level model and upper level model statistical data, and lower level model and upper level model bivariate correlation analysis results
Data Types:
  • Tabular Data
  • Dataset
Results from OLI Flowsheet modeling and DOW WAVE modeling of the baseline MVR and the advanced NR+RO+MVR designs
Data Types:
  • Tabular Data
  • Dataset
Geochemical data for mantle xenoliths hosted by Cenozoic basalts in northeastern China. The data include mineral and rock chemistry, in situ isotopic compositions of Sr in clinopyroxene and O in olivine.
Data Types:
  • Tabular Data
  • Dataset
Subclonal Mutation Selection in Mouse Lymphomagenesis Identifies Known Cancer Loci And Suggests Novel Candidates. - Supplementary figures and data
Data Types:
  • Tabular Data
  • Dataset
  • Document
These are the raw data sets for quantifying and analyzing the use of the word resilience in the context of western forest and fire management science between 1980 and 2016. The documents table (documents.csv) contains every document used in the analysis of the use of the word resilience in western forest and fire management science between 1980 and 2016 as well as counts of the words contained in thematic dictionaries used in the analysis. The instances table (instances.csv) contains every instance of the word resilience in these documents (documents.csv) and can be linked to the documents table using the "docid" field. The text field contains the 10-word context window used for structural topic modelling resilience.
Data Types:
  • Tabular Data
  • Dataset
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