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Each folder in this dataset refers to a specific publication and contains: 1) pdf files with an extended list of tables and images referred, but not included, in the main papers: 2) a compressed archive with the generated raw data. For more details, one can read the main articles referenced below.
Data Types:
  • Dataset
  • Document
  • File Set
Data Set from the Russian Federation Federal State Statistics Service - Росстат. Collected, translated into English language and published. Mortality in Russia by cause of death in 2018 (absolute numbers). Causes of death statistics are obtained from the inscriptions in medical death certificates filled in by a physician referring to disease, accident, homicide, suicide or any other external factor (injuries due to actions envisaged by the law, non-specified injuries, injuries caused by military actions) which led directly to death. Such inscriptions are used as a reason for classifying death causes in civil registration records of deaths. Some of the presented causes of death: Cause of death, Cholera, Typhoid fever, Paratyphoid, Salmonella infections, Shigellosis, Food poisoning, Intestinal infections, Tuberculosis, Plague, Anthrax, Brucellosis, Leprosy, Tetanus, Diphtheria, Whooping cough Scarlet fever, Meningococcal infection, Sepsis, Erysipelas, Other bacterial infections, Syphilis, Sexually transmitted infections, Typhus, Poliomyelitis, Rabies, Viral encephalitis, Measles, Hepatitis A, Human Immunodeficiency Virus (HIV) Disease, Other diseases caused by viruses, Malaria, Leishmaniasis, Trypanosomiasis, Schistosomiasis, Malignant, Leukemia, Neoplasms, Diabetes, Diseases of the endocrine system, eating disorders and metabolic disorders, Mental disorders, Parkinson's disease, Alzheimer's disease, Multiple sclerosis, Hypertension, myocardial infarction, Myocardial infarction, Stroke, Urolithiasis, Birth injury, Intrauterine hypoxia and asphyxia in childbirth, Suicides, Murder, Firearm Accident, Other accidents, Causes of death due to alcohol, Drug-related causes of death, All types of transport accidents And many more causes of death.
Data Types:
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This code source is a simulation of a hybrid high dimensional automated guided vehicle system design model in python. In fact, our approach aims to solve the problem of dimension growth in a convex 2D environment of an Automated Guided Vehicle System (AGVS), using a Deep reinforcement learning control system of kernels with low dimensions.
Data Types:
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  • File Set
By combining latitudinal gradient analysis with laboratory responses to temperature manipulation, we showed that ocean warming will increase the nitrogen demand of the globally distributed seagrass Z. marina and this demand may be met by an increasing uptake of organic nitrogen forms, highlighting that Z. marina will be winner under global change conditions of increased temperature and CO2.
Data Types:
  • Tabular Data
  • Dataset
The study investigates the adaptive capacity of urban dwellers in response to flooding, determines the factors influencing disaster preparedness among the residents; ascertains the disaster responses taken and identify opportunities for risk managing firms. The principal component analysis (PCA) and path analysis using the Khb method are employed in the analysis of primary data collected from the urban dwellers. The study reveals that majority of the residents had moderate to high perception of flood risk but were unprepared for flood disaster. It also reveals opportunity for risk managers to increase their market base but majority of the residents seem not willing to purchase insurance policy and this was attributed to either lack of awareness or unavailability of insurers in the communities. The variables used in the analysis are presented and described in the various sheets. Some of the variables are in ordinal measurements, others are in nominal or dummy categorisation.
Data Types:
  • Tabular Data
  • Dataset
These data compare the proteomes of budding yeast (Saccharomyces cerevisiae) treated with or without 80 micrograms/mL of the anticancer ruthenium complex KP1019. A full analysis of this dataset can be found in the corresponding manuscript "Proteomic analysis of the S. cerevisiae response to the anticancer ruthenium complex KP1019", which has been accepted for publication in the journal Metallomics. These data were gathered by LC-MS and show that KP1019 causes oxidative stress, DNA damage, and protetoxic stress.
Data Types:
  • Tabular Data
  • Dataset
Use investment criteria of business angels and venture capitalists to predict success of equity crowdfunding campaigns. Findings confirm that success of equity crowdfunding campaigns can be predicted from investment criteria of BA/VC. This would be explained partly by the professionalisation of equity crowdfunding.
Data Types:
  • Tabular Data
  • Dataset
Nairobi Securities Exchange All Stocks Prices 2007-2012 This historical data is valuable for machine learning algorithms that need data for training and testing. It was initially compiled as part of a project to apply Artificial Neural Networks (ANN) for next day stock price prediction, based on the prices of the previous five days. Use of ANN was to contrast to prevalent methods of stock market prediction such as technical, fundamental or time series analysis. This data was used for an initial research [1],[2] that tested an ANN for stock market prediction. This ANN model was of configuration - feedforward multi-layer perceptron (MLP) with error backpropagation, using sigmoid activation function, with network configuration 5:21:21:1. The data used in the research was for the 5-year period (2008 to 2012), with 80% of the data (4-year data) used for training and the balance 20% used for testing (last 1-year data). However, the full data that had been compiled, as presented here is the 6-year data for period 2007 to 2012. This 2007 to 2012 data for the Nairobi Securities Exchange (NSE) was scrapped from a public website that publishes daily stock prices and archives historical data [3]. The raw data was first exported to a spreadsheet then headers, footers and other unnecessary elements were removed. This data consists of daily stock prices for over 60 different stocks and market indices over a 12-month period in each year, for a total of 6-years. Each data row has the following 13 data columns (1) Date of trade (2) Code of the stock (3) Name of the stock (4) 12-month Low price (5) 12-month High price (6) Day's Low price (7) Day's High price (8) Day's Final Price (9) Previous traded price (10) Change in price by value (11) Change in price by % (12) Volume traded (13) Adjusted price, if any. The original data also had a column on the price direction, being an arrow graphic, showing Up, Down or Unchanged. This column was discarded from this final compilation. While the initial research only tested prediction based on adjusted final price for six stocks, the publishing of the full data now gives other researchers the opportunity to test any other of the more than 60 stocks and test any other hypothesis on this full data set. This data can also be used to reproduce and validate the initial research findings as already published. List of data files on this dataset: NSE_data_all_stocks_2007.csv NSE_data_all_stocks_2008.csv NSE_data_all_stocks_2009.csv NSE_data_all_stocks_2010.csv NSE_data_all_stocks_2011.csv NSE_data_all_stocks_2012.csv References: [1] Wanjawa, B. W. (2014). A Neural Network Model for Predicting Stock Market Prices at the Nairobi Securities Exchange (Dissertation, University of Nairobi). [2] Wanjawa, B. W., & Muchemi, L. (2014). ANN model to predict stock prices at stock exchange markets. arXiv preprint arXiv:1502.06434. [3] Synergy Systems Ltd. (2020). MyStocks. Retrieved March 9, 2020, from http://live.mystocks.co.ke/
Data Types:
  • Tabular Data
  • Dataset
Research data of "Characteristics of methane-air combustion with rotating gliding arc discharge plasma assistance"
Data Types:
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  • File Set
(1). Master data file (in Excel.xls format) in support of the paper by Pusiak, Auld and Godin (2020) in Animal Behaviour. Original raw data for mating preferences of individual focal male guppies tested in four independent experimental treatments. The data collected are organized into discrete columns (representing variables) in Sheet 1, and the definition of each column header title can be found in Sheet 2. (2) Data File (in Excel.xls format) in support of the paper by Pusiak, Auld and Godin (2020) in Animal Behaviour. Subset of original raw data on the mating preferences of individual focal male guppies for either Small or Large females in four independent experimental treatments. The data collected are organized into discrete columns (representing variables) in Sheet 1, and the definition of each column header title can be found in Sheet 2.
Data Types:
  • Tabular Data
  • Dataset
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