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  • Data and R-code for the article "A modular, USB connected operant conditioning apparatus for fishes", which will be submitted to Behavioural Ecology and Sociobiology.
    Data Types:
    • Software/Code
    • Tabular Data
    • Dataset
  • Mimicry is ubiquitous in nature, yet understanding its origin and evolution is complicated by the scarcity of exceptional fossils that enable behavioural inferences about extinct animals. Here we report bizarre true bugs (Hemiptera) that closely resemble beetles (Coleoptera) from mid-Cretaceous amber. The unusual fossil bugs are described as Bersta vampirica gen. et sp. nov. and B. coleopteromorpha gen. et sp. nov., and are placed into a new family, Berstidae fam. nov. The specialised mouthparts of berstids indicate that they were predaceous on small arthropods. Their striking beetle-like appearance implies that they were either involved in defensive mimicry or mimicked beetles to attack unsuspecting prey. The latter represents the first case of aggressive mimicry in the invertebrate fossil record. This rare example of fossilised behaviour enriches our understanding of the palaeoecological associations and extinct behavioural strategies of Mesozoic insects.
    Data Types:
    • Other
    • Software/Code
    • Dataset
    • Document
    • Text
  • A dataset of high-speed video footage of mercury droplets settling through liquid media of which the viscosity is different, is presented. The video footage taken was at 4000 frames per second for mercury droplets at room temperature (25 °C) settling through either deionised water or silicone oil. The data set is useful for validation of computational models of a wide range of problems which include phase separation studies, settling behaviour as well as interfacial phenomena in liquid-liquid system.
    Data Types:
    • Other
    • Software/Code
    • Dataset
    • Document
  • This dataset includes the raw data (Dataset folder), processed dataset (newfeature.csv; after feature extraction), python code (code.py) of the diagnosis system developed using machine learning algorithms. In order to use different classifiers for the classification, use code.py file, where the bottom line has the different classifier performance commented statements. You may uncomment the statement associated with classifier you want to use to get the classification result.
    Data Types:
    • Software/Code
    • Tabular Data
    • Dataset
    • Text
  • The supplementary information includes the R scripts to run the validation study described in the main text, as well as the data files required to perfomr the validation. Validation script SI v2.R includes the code to run the validation models, kxv_glmer.R includes the code to perform a cross-validation evaluation of the models and is called for in the former (main) script. The Excel files are loaded within the script, and include respectively the GPS data of white-tailed eagles (GPS_RESULTSx.xls) and five sets of random points per GPS location (RANDOM_RESULTS_1-5.xls). HitraParametre.xlx presents the variables used in the updraft modelling (Table 1 of the main text). NyeTurbinerVerdier.xls is used in the validation R script to assess the location of wind turbines relative to updraft velocities. Both txt files (TERMISK, OROGRAFISK) give the actual updraft velocities across the island of Hitra and are used in the R script to prepare a histogram.
    Data Types:
    • Software/Code
    • Tabular Data
    • Dataset
    • Text
  • A companion code repository for the article, "Development and Validation of Prediction Model for Risk Reduction of Metabolic Syndrome by Body Weight Control: A Prospective Population-based Study". The database is available from the National Research Institute of Health of South Korea, but restrictions apply to the availability of these data, which were used under license for the current study and are not publicly available. Data are however available from the authors upon reasonable request and with permission of the National Research Institute of Health of South Korea. Further information is available at the KoGES website: https://www.cdc.go.kr/menu.es?mid=a50401010100
    Data Types:
    • Software/Code
    • Dataset
    • Document
  • Models as described in the manuscript "Using machine learning with target-specific feature sets for structure-property relationship modeling of octane numbers and octane sensitivity" (Preprint submitted to Fuel).
    Data Types:
    • Other
    • Software/Code
    • Tabular Data
    • Dataset
  • The data were the base for writing the manuscript
    Data Types:
    • Software/Code
    • Tabular Data
    • Dataset
  • This dataset was derived from a nationwide, anonymous, open Internet survey conducted amongst healthcare professionals in Denmark on the assessment and treatment of spatial neglect (SN). The objective was to describe knowledge and practices in the assessment and treatment of SN in current clinical practice across different healthcare sectors and professions. Data included the perceived prevalence of SN, assessment methods and observations, subtypes and differential diagnostics of SN as well as treatment methods, timing and sources of evidence. A total of 525 healthcare professionals participated in the survey. Open text comments has been redacted for anonymity.
    Data Types:
    • Software/Code
    • Dataset
  • For the full database, please visit: www.projectipad.org The 2011 accident at Japan’s Fukushima Daiichi Nuclear Power Plant released a considerable inventory of radioactive material into the local and global environments. While the vast majority of this contamination was in the form of gaseous and aerosol species, of which a large component was distributed out over the neighbouring Pacific Ocean (where is was subsequently deposited), a substantial portion of the radioactive release was in particulate form and was deposited across Fukushima Prefecture. To provide an underpinning understanding of the dynamics of this catastrophic accident, alongside assisting in the off-site remediation and eventual reactor decommissioning activities, the ‘International Particle Analysis Database’, or ‘IPAD’, was established to serve as an interactive repository for the continually expanding analysis dataset of the sub-mm ejecta particulate. In addition to a fully interrogatable database of analysis results for registered users (exploiting multiple search methods), the database also comprises an open-access front-end for members of the public to engage with the multi-national analysis activities by exploring a streamlined version of the data.
    Data Types:
    • Other
    • Software/Code
    • Image
    • Tabular Data
    • Dataset
    • Document
    • Text
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