Filter Results
2644783 results
COVID-19 reported cases and deaths through 3/31/2020 world wide, excluding China and South Korea
Data Types:
• Dataset
• Text
This data set contains the following data files: - biomat-conductivity.csv: Measured hydraulic conductivities of the soil and biomat - biomat-growth.csv: Time for sensor positions (within upper 5 cm) to reach a 2.5% increase in VWC for each site and treatment - biomat-parameters.csv: Parameters for biomat growth models - effluent-data.csv: Effluent pollutant concentrations - hydrus-parameters.csv: Parameters used in HYDRUS modeling - met-data.csv: Meteorological data - sensor-control.csv: VWC observations for control sensors installed outside the soil treatment unit - sensor-meta.csv: Meta data for sensor locations - site-meta.csv: Meta data for the research sites - vwc-predrought.csv: VWC changes before the onset of the summer 2018 drought - vwc-postdrought.csv: VWC changes during the summer 2018 drought A detailed description of the content of each data file is given in the codebook provided with this dataset.
Data Types:
• Tabular Data
• Dataset
• Text
The archive contains original SEM images, XRD files,charge densification data, thermal conductivity experiments.
Data Types:
• Dataset
• File Set
The descriptive data presented in this article is used to measure the level of student’s satisfaction with university facilities which are provided by the university as well as the government. This study involved 280 respondents comprising diploma, bachelor degree and post graduate student at Malaysian Public University. An open-ended question with 10 Likert Scale was distributed to respondents to identify the level of student’s satisfaction with the facilities provided by the university. The one to 10 scale measurements starting with one is Strongly Dissatisfied to 10 is Strongly Satisfied has been used to measure the level of student’s satisfaction towards 14 facilities at the university.
Data Types:
• Tabular Data
• Dataset
• Document
• Text
Explanation and description of the microscopic data of mice tissue histology under concern by the Editor's of Plos One
Data Types:
• Dataset
• Document
• File Set
This dataset contains the primary data used in: "Multi-epoch X-ray burst modelling: MCMC with large grids of 1D simulations", Johnston et al. (2020). In this work, we interpolated and sampled a grid of 3840 KEPLER burst models using Markov Chain Monte Carlo (MCMC) methods to produce posterior distributions for the system parameters of the "Clocked Burster", GS 1826-238. Provided here is the full burst model grid and the raw MCMC sample chains. More details on the files, and how to load them, are provided in README.md
Data Types:
• Software/Code
• Dataset
• Text
• File Set
In this repository we make available two datasets of research on soccer analysis data. - baseNormalizada - is a dataset that joins real data of soccer players transfers with athletes abilities gathered from the eletronic soccer game FIFA. - Network_dataset - is a dataset that gatheres all major soccer transfers that occured on the soccer world between 1990 - 2017. For both datasets we make available the crawler for future updates.
Data Types:
• Dataset
• Text
Dataset for the paper entitled "Real-time command strategies for microgrids based on the Contract Collaboration Problem". You are free to use the instances in the zip file, if you cite the following work: @article{Levorato2020, author = {Levorato, M. and Figueiredo, R. and Frota, Y. and Jouglet, A. and Savourey, D.}, journal = {To be published}, title = {{Real-time command strategies for microgrids based on the Contract Collaboration Problem}}, year = {2020} } Instances description ================================= 1) full_intances: the 3 microgrid instances used in the main experiments: - A_instance2_1NDU_Cons : the *Cons* microgrid instance, with only the consumer uncertain system; - A_instance2_1NDU_Prod : the *Prod* microgrid instance, with only the producer uncertain system; - A_instance2 : the *Prod\&Cons* microgrid instance, with both uncertain systems (producer and consumer). For each instance, there are 3 files, each one for a group of randomly generated scenarios: - _1000s_skewed-left.txt : left-skewed beta distribution with parameters $\alpha=5,\beta=2$; - _1000s_skewed-right.txt : right-skewed beta distribution with parameters $\alpha=2,\beta=5$; - _1000s_uniform.txt: uniform distribution. The randomly-generated scenario values are located in the end of each file. 2) toy_sensitivity: reduces microgrid instances used in the sensitivity tests. Each file corresponds to a specific combination of model cost parameters, and the filename follows this mask: OC_Ct__DS_ST_NDU__.txt The parameters OC_cost, DS_cost, ST_cost follow the values listed in Table VI of the aforementioned paper. (caption: Energy cost parameters in sensitivity analysis). can be one of the 3 distributions used in the work (skewed-left, skewed-right or uniform). The used was 'default'. The used was 'default'. Again, the randomly-generated scenario values are located in the end of each file.
Data Types:
• Dataset
• Text
• File Set
Aedes mosquitoes are one of the mosquito genus a large impact on humans that it is the main vector of deadly infectious diseases such as microcephaly. Aedes koreicus is a mosquito, endemic to east Asia, including Korea, Japan and China. According to the available research about its native range, Ae. koreicus is able to tolerate winter temperatures lower than Ae. Albopictus and Ae. japonicus. Therefore, this species has rapidly expanded outside its native range and invaded Europe.
Data Types:
• Dataset
• File Set
Mitogenome sequences assembled using raw data for two Malaysian Hippocampus kuda (HK1 and HK2). Genomic DNA was extracted using Qiagen Blood and Tissue Kit (Qiagen, Valencia, CA) following the manufacturer’s instructions. All libraries were prepared using BEST protocol as described in Mak et al., (2017) and were sequenced on an BGISEQ-500 platform (100PE). Raw sequence reads were assembled into individual mitogenome sequence using the MITOBIM v1.8 (reference genome assembly) pipelines. Mitogenome mapping quality was assessed using PALEOMIX and further annotated using MitoAnnotator and GB2sequin annotation web application. The mitogenome data is available in Genbank with the accession numbers MT221436 and MT221436.
Data Types:
• Dataset
• Text
3