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12 results for “Legacy datasets”
Dataset: Sentiment Analysis annotation of News headlines covering the Olympic legacy of Rio 2016 and London 2012 published by the Brazilian and British online media
<p>Dataset of 464 news headlines with sentiment manually annotated by a domain expert using the labels positive, negative and neutral. Data contains URLs for news articles published between 2004-2020 by the British and Brazilian media in English and Brazilian Portuguese covering the Olympic legacies of London 2012 and Rio 2016. Articles were collected from the news outlets’ websites using Google search engine.</p> <p>News outlets:</p> <ul> <li>The Guardian</li> <li>Daily Mail</li> <li>Globo</li> <li>Estadao</li> </ul>
Dataset: Legacy Housing Corporation (LEGH) Stock Performance
This dataset provides historical stock market performance data for specific companies. It enables users to analyze and understand the past trends and fluctuations in stock prices over time. This information can be utilized for various purposes such as investment analysis, financial research, and market trend forecasting.
Dataset to Schiedung et al (2023): Soil carbon losses due to priming moderated by adaptation and legacy effects
<p>Data set to: Schiedung et al. (2023) Soil carbon losses due to priming moderated by adaptation and legacy effects, Nature Geoscience</p> <p>All file informations are presented in 0_Read_me_description.csv</p> <p>All .csv files are separated by ",". All .xlsx files contain the isotopic excess calculations condcuted in Microsoft Excel (Version 2301 Build 16.0.16026.20002).</p> <p>This repository contains all data of the soils and sites, incubation and fractionation presented in the above mentioned publication.</p> <p>For further questions and requests contact Marcus Schiedung (marcusschiedung@gmail.com)</p>
Dataset of concentrations of legacy persistent organic pollutants in fishes and human of the European Arctic Russia
<p>The dataset presented in this Data descriptor supports “Persistent organic pollutants (POPs) in fish consumed by the indigenous peoples from Nenets Autonomous Okrug” (Lakhmanov et al., 2020).</p>
Dataset for: Exploring the legacy effect of biochar application on soil nitrous oxide emissions
<p><span>This dataset contains data for exploring the legacy effects of biochar addition on soil nitrous oxide emissions and their effects on functional gene abundance associated with soil nitrogen cycling. The dataset contains two data files, one is a data table on the impact of biochar application on soil nitrous oxide emissions, which contains the coordinates of the study site, climate, basic physical and chemical properties of the soil, biochar characteristics and study duration, crop type and management. The other is the data table on the effect of biochar application on the abundance of functional genes related to soil nitrogen cycling, which contains information such as test site coordinates, climate, biochar characteristics, crop type and management. This data can be referenced and reused without any legal or ethical considerations</span>.</p>
Dataset associated with the manuscript: Soil management legacy interacts with wheat genotype to determine access to organic N in a dryland system
<p>Organic nutrient management through the application of compost and/or cover crops provides mineralizable sources of nutrients for plants while often building soil organic matter (SOM) and various aspects of soil health. Variability in nutrient acquisition strategies between crop genotypes may confer advantages under different soil health contexts and could be important for crop selection and breeding, but crop response under field conditions remains unexplored. We investigated the ability of different genotypes of winter wheat (<em>Triticum aestivum</em> L.) to access nitrogen (N) from newly added cover crop residues in two soils with contrasting levels of SOM and biological activity. We planted three previously characterized wheat genotypes in a long-term dryland compost amendment field trial: 1) Byrd (modern, deep roots, low exudation), 2) Cheyenne (historic, drought susceptible, intermediate exudation), and 3) Snowmass (modern, drought-susceptible, high exudation). <sup>15</sup>N-labelled cover crop residue was added to each plot and traced into wheat tissue. In the low SOM soil, the high exudate genotype Snowmass and historic genotype Cheyenne took up the most residue-derived N (6.4-8.1 kg N ha<sup>-1</sup>) compared to the low-exudate genotype Byrd (4.4 kg N ha<sup>-1</sup>), suggesting a strong exudate effect in the more carbon-limited soil. However, the low-exudate, deep rooted genotype, Byrd, took up the most residue N in the high SOM soils (4.6 kg N ha<sup>-1 </sup>vs. 2.8 and 3.3 hg N ha<sup>-1</sup> for Cheyenne and Snowmass, respectively), which indicated higher native N cycling activities and great importance of drought resistance. Enzyme activity, inorganic N, and microbial communities were not influenced by genotype, though did show strong effects of compost application legacy. Our results show that belowground allocation strategies that favor microbial stimulation may be less successful under water limitation, especially when high SOM can support mineralization of residue N without added investment in root inputs. Increased soil health through SOM-building management likely enhances nutrient cycling, and may better support root strategies that invest less in microbial stimulation in favor of other limiting resources.</p>
The legacy of one hundred years of climate change for organic carbon stocks in global agricultural topsoils - full dataset
<p>This zip folder contains a txt and a shp file with predicted soil organic carbon stocks for a total of 931149 points on agricultural land across the globe at three different timepoints. The initial value (2018) for the scenarios c (constant carbon input) and v (variable carbon input) was derived from the FAO GSP Global SOC map published in 2018. the values in 1969 and 1919 are the results of backwards modelling with RothC model to estimate past climate change effects on SOC stocks. Details can be found in the publication " The legacy of one hundred years of climate change for organic carbon stocks in global agricultural topsoils" as published in Scientific Reports.</p>
Dataset associated with the manuscript: Soil management legacy interacts with wheat genotype to determine access to organic N in a dryland system
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Dataset for: Exploring the legacy effect of biochar application on soil nitrous oxide emissions
Open the record for dataset details and reuse information.
Dataset for: A Lingering Legacy of Leaded Gasoline in Southeast Asia
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ArchiWood: dataset of legacy documents about wood anatomical, morphological, and architectural traits for plant species in Madagascar
<p><strong>Abstract</strong></p> <p>Digitization of a part of CIRAD's' xylotheque, one of the most important collections of tropical timber in the world, now allows researchers, experts in the field, trainers and archaeologists to have a new source of homogenized information. This corpus constitutes a unique database on the botanical characteristics of many species of Madagascar and could feed the research in both ecological and systematic fields by the possibility to define traits and criteria usable for example in phylogeny or functional ecology.</p> <p>The island of Madagascar presents a remarkable floristic diversity, with a very high rate of endemism, making it a permanent laboratory for the study of the mechanisms governing evolution.</p> <p>The digitization project was conducted in close coordination with other projects currently underway involving the same partners. 995 species are concerned by the ArchiWood project: 3 planes of anatomical sections for each species, associated with a total of 100 field notebooks (architectural sketches) and 20,000 slides.</p> <p><strong>Contents</strong></p> <p>This dataset is composed of digitized legacy documents, all related to Madagascar biodiversity:</p> <ul> <li>More than 2,300 illustrations and notes taken from field notebooks</li> <li>More than 1,200 anatomical cuts</li> <li>More than 70 photographs of plants and landscapes</li> </ul> <p><strong>Methods</strong></p> <p><em>Digitization of anatomical cuts</em><br> For each species, there are 3 anatomical cuts associated with the 3 planes of symmetry of the material: radial, tangential and longitudinal. Each cut was scanned using an Olympus DP71 digital camera fitted on an Olympus BX60 microscope. The shooting software that drives the camera is Archimed from Microvision Instruments. The image format is 24 bits colored TIFF. Each image is 1600 x 1200 pixels for 3 different magnifications of the microscope: x40 (overview of the cut), x200 (main features anatomical from IAWA), x400 (highlighting fine lines such as punctuations).</p> <p><em>Digitization of sketches (from field notebooks) </em><br> The digitized information in the field notebooks is made up of architectural sketches (with descriptive notes). The slides include additional remarkable visual information of field sketches (flowers, fruits, overview, geographical implantation conditions…). The sketches were scanned using a resolution of 300 dpi, 24 bits colors in JPEG format.</p> <p><em>Digitization of photographs (24 x 36 mm)</em><br> The photographs were scanned at 600 dpi, 24 bits colors in JPEG format.</p> <p><strong>File management and data quality control</strong></p> <p>Controlling images and adding metadata operations were carried out by the researchers concerned in their field of activity (anatomy, botany, architecture). The homogenization and final harmonization of the metadata and data was carried out by the data manager.<br> </p>
LEGACY DATASET: Reconstructed global long-term contiguous solar-induced fluorescence (LCSIF), MODIS period (2001-2021)
<p><strong>This is a legacy version of the dataset and is no longer recommended for use. Please access the latest version of LCSIF and LCREF with the following links:</strong></p> <ul> <li>LCSIF-AVHRR v3.1 (1982-2000): <a href="https://doi.org/10.5281/zenodo.13922371" target="_blank" rel="noopener">10.5281/zenodo.13922371</a></li> <li>LCSIF-AVHRR v3.1 (2001-2022): <a href="https://doi.org/10.5281/zenodo.13922367" target="_blank" rel="noopener">10.5281/zenodo.13922367</a></li> <li>LCSIF-MODIS v3.1 (2001-2022): <a href="https://doi.org/10.5281/zenodo.13922379" target="_blank" rel="noopener">10.5281/zenodo.13922379</a></li> <li>LCREF-AVHRR v3.1 (1982-2022): <a href="https://doi.org/10.5281/zenodo.11905960" target="_blank" rel="noopener">10.5281/zenodo.11905960</a></li> <li>LCREF-MODIS v3.1 (2001-2022): <a href="https://doi.org/10.5281/zenodo.11657459" target="_blank" rel="noopener">10.5281/zenodo.11657459</a></li> </ul> <p>Thanks a lot. Please feel free to reach out to Jianing Fang (<a href="mailto:jf3423@columbia.edu">jf3423@columbia.edu</a>) if you have any questions.</p>
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International Brain Laboratory public data
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OpenNeuro
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