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  • The current data of research "Peripheral members create and core members support: Role comparison of different positions in cooperation network during creative behaviour cooperation" The file included two parts: the data used to draw the figures and the raw data of the current analysis. The description of the raw data can be found in the "Description.txt" file in every folder.
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  • Research Hypothesis - That cannabis may predispose to COVID-19 viral infection due to its immunomodulatory, envorinmental contaminants, vaping and smoking inhalation actions. Data was analyzed by geospatial and causal inference techniques in R. Data was gathered from publicly available on line sources including: Data were downloaded from Publicly available datasets including: • US Census bureau 2019 • Five Year American Community Survey 2013-2018 • National Survey of Drug Use and Health (NSDUH) • NSDUH Resticted Use Data Analysis System (RDAS) • US Department of Transport International Flight Data • Worldometer Covid -19 Dataset Data were collected in the six domains of: • COVID numbers • Fights – numbers of flights and numbers of overseas destionations • Median household income • State ethnic composition • Population and population density • Drug use Inverse probability weights were constructed by inverse probability weighting conducted in package ipw in R. Geospatial weights were constructed in package spdep in R.
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  • The original, unprocessed data alongside the paper
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  • The data contains all the basic data of this study, including EIS, loading data, CT data.
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  • The advance of the agrarian frontier constitutes Nicaragua’s biggest environmental challenge as the major cause of complex processes of ecosystems degradation. I use the ESA-CCI land cover maps dataset and the UNCCD land cover classes (UNCCD-LC) to estimate its geospatial trend in terms of land cover changes at the country-level and the areas encompassing Bosawas and Río San Juan biosphere reserves from 1992 to 2015. The ESA-CCI land cover maps generated at 300 m spatial resolution on an annual basis from 1992 to 2015 in TIF format (raster layers) were collected from the official website of the ESA-CCI (https://www.esa-landcover-cci.org/). The coordinate reference system of the maps is a geographic coordinate system based on the World Geodetic System 84 (WGS84) reference ellipsoid. The processing of the geospatial data was carried out using QGIS. The 36 ESA-CCI land cover classes (ESA-CCI-LC) were re-classified to the 7 UNCCD-LC (i.e., tree-covered, grassland, cropland, wetland, artificial, other land, and water body). The global-level maps were clipped to the country-level (Nicaragua) using the vector layers in SHP format collected from the official website of GADM (https://gadm.org/), and at the biosphere reserve-level (Bosawas y Río San Juan) using the vector layers in SHP format collected from the official website of Protected Planet (https://www.protectedplanet.net/). A pixel count approach was used to estimate each UNCCD-LC area. STATA was used to calculate UNCCD-LC area estimates in squared kilometers, each pixel counting for 300 m x 300 m which is the ESA-CCI land cover maps spatial resolution. At the country-level, the analysis covered 124,552.2 km2. The total area might include land and water bodies. At the biosphere reserve-level, the analysis covered 19,548.2 km2 for Bosawas and 17,524.9 km2 for Río San Juan. In Basawas biosphere reserve, 41% (8,030.3 km2) of the total area belongs to core areas, whereas 69% (11,548.9 km2) to the buffer zone. In Río San Juan biosphere reserve, 48% (7,525.3 km2) of the total area belongs to core areas, whereas 52% (10,170.2 km2) to the buffer zone. The research finds that Nicaragua’s agrarian frontier has shown a remarkably strong advance during the last two decades, particularly from 1995 to 2007. The underlying land transition process has mainly implied the transformation of tree-covered into cropland or grassland areas. This process has also penetrated legally designated protected areas such as Bosawas and Río San Juan biosphere reserves.
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  • Icequakes, micro-seismicity caused by glacier deformation and motion, provide important information to study glacier dynamics and its responses to environmental changes at various temporal and spatial scales. In this study, we apply a multi-dimensional autoregressive maximum-likelihood algorithm to obtain 12 icequake templates on the Urumqi Glacier No. 1, China, and detect 65,363 icequakes through template matching. Centroid location of the 12 templates indicate that most icequakes are caused by surface crevasses inside the glacier, which are characterized by dominant surface waves. The icequakes show seasonal variation with more events in summer because of faster ice flow due to high temperature and precipitation. In winter, however, the icequakes, on par with those in summer, suggest considerable glacier growth in cold weather. Because of higher ice flow velocity due to low tide, the number of icequakes has two daily peaks which seems to negatively correlate with semi-diurnal solid tide.
    Data Types:
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  • This video dataset comprises (44) recordings of the human gait with (396) edited videos, there is also available a dataset of geometric features with (1431) files acquired from the video dataset that can be used for identifying people by human gait or for analyzing gait on various purposes. Each directory has the following structure: One directory with original videos of 44 people walking. Some parameters are, Video format AVI, stable background, resolution of 1280x700 p. Each video recording registers a person walking from left to right and back three times. One directory (Track A) with 44 edited videos with the first walking pass from left to right and back. A subdirectory (Sx_Track 1_Right) with 44 edited videos with the first walking pass from left to right. A subdirectory (Sx_Track 1_Left) with 44 edited videos with the first walking pass from right to left. This directory comprises 132 videos in total. One directory (Track B) with 44 edited videos with the second walking pass from left to right and back. A subdirectory (Sx_Track 1_Right) with 44 edited videos with the second walking pass from left to right. A subdirectory (Sx_Track 1_Left) with 44 edited videos with the second walking pass from right to left. This directory comprises 132 videos in total. One directory (Track C) with 44 edited videos with the third walking pass from left to right and back. A subdirectory (Sx_Track 1_Right) with 44 edited videos with the third walking pass from left to right. A subdirectory (Sx_Track 1_Left) with 44 edited videos with the third walking pass from right to left. This directory comprises 132 videos in total. One directory V-Geometric features with .dat files acquired from the video dataset with geometric features from the rectangle drawn over the silhouettes during a time. The geometric features were acquired with image processing techniques and are comprised of width, height, and area over time [1,2] nnW subdirectory: 477 .dat files with registered information about the behavior of the rectangle width during the gait record. nnH subdirectory: 477 .dat files with registered information about the behavior of the rectangle height during the gait record. nnA subdirectory: 477 .dat files with registered information about the behavior of the rectangle area during the gait record. References: [1] Senigagliesi, L.; Ciattaglia, G.; De Santis, A.; Gambi, E. People Walking Classification Using Automotive Radar. Electronics 2020, doi:10.3390/electronics9040588 [2] Kececi, Aybuke, Armağan Yildirak, Kaan Ozyazici, Gulsen Ayluctarhan, Onur Agbulut, and Ibrahim Zincir. 2020. Implementation of Machine Learning Algorithms for Gait Recognition. doi:10.1016/j.jestch.2020.01.005 [3] Figueiredo, Joana, Cristina P. Santos, and Juan C. Moreno. 2018. Automatic Recognition of Gait Patterns in Human Motor Disorders using Machine Learning: A Review. Vol. 53. doi: 10.1016/j.medengphy.2017.12.006
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  • This dataset is a geomorphic classification of the shelf features surrounding Lord Howe Island and Balls Pyramid. This dataset provides information on the size, extent and type of features which occur around the shelves, which can be used for a broad range of marine planning and research purposes. Shelves were classified into shelf region (inner, mid, outer) and geomorphic features. Features include an extensive submerged fossil reefs, ridges and patch reefs, sandy basins, paleochannels, modern fringing reef, shallow lagoon, shelf edge terraces and shelf break. Broad seafloor features were visually interpreted through digitisation in ArcGIS v10.1 using terminology consistent with international nomenclature and national standards. The classification of geomorphic features extends upon the interpretation of Balls Pyramid shelf undertaken by Linklater et al. (2015). Full description of methods is outlined in the following open-access publication, accessible by the following link: http://www.mdpi.com/2076-3263/8/1/11/htm
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  • This research aims to provide an understanding of how absorptive capacity occurs in startups, which maintains interorganizational relationships with large companies. The research used a qualitative multiple case study design and the investigation of seven startups constituted the study corpus. The data were analyzed using statistical analysis, content analysis, and business process analysis. In the study, the software Iramuteq (Interface of R pour les Analyzes Multidimensionnelles de Textes et de Questionnaires) was used as a tool to aid the qualitative analysis of textual data. In a complementary way, the SPSS Statistics 17 software was used to treat the survey data.
    Data Types:
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    • Document
    • Text
  • This data set contains the source files of the SeGa4Biz framework including metamodels, model instances, and transformation rules.
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