cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.21153868
title: Rawdata for insect DNA metabarcoding sequences in citrus in China

description: DNA metabarcoding is rapidly emerging as a cost-effective approach for large-scale biodiversity assessment and pest monitoring. The current study employed metabarcoding to assess insect diversity in citrus orchards in Ganzhou city, Jiangxi, China during 2018-2019. Insects were sampled using single Malaise traps deployed in three citrus orchards producing a total of 43 pooled monthly collections (samples). These bulk samples were metabarcoded, and sequences were curated and analyzed using two cloud-based data storage and analytical platforms, the Barcode of Life Data System (BOLD) and Multiplex Barcode Research And Visualization Environment (mBRAVE). These platforms assigned the sequences to 2,141 Barcode Index Numbers (BINs), a species proxy. Only 63% of the BINs were shared among the three sampling sites while BIN sharing between any two sites did not exceed 75%. Comparison of these records against all those on BOLD made it possible to identify 40% of the BINs to a species, 57% to a genus, 97% to a family, and 99% to an order. Species which received a species match on BOLD were placed in one of four categories based on this assignment: pest, parasitoid, predator, or pollinator. As this study provides the first baseline data on insect biodiversity in Chinese citrus plantations, it is a valuable resource for research in a broad range of areas such as pest management and monitoring beneficial insects in citrus gardens.DNA metabarcoding is rapidly emerging as a cost-effective approach for large-scale biodiversity assessment and pest monitoring. The current study employed metabarcoding to assess insect diversity in citrus orchards in Ganzhou city, Jiangxi, China during 2018-2019. Insects were sampled using single Malaise traps deployed in three citrus orchards producing a total of 43 pooled monthly collections (samples). These bulk samples were metabarcoded, and sequences were curated and analyzed using two cloud-based data storage and analytical platforms, the Barcode of Life Data System (BOLD) and Multiplex Barcode Research And Visualization Environment (mBRAVE). These platforms assigned the sequences to 2,141 Barcode Index Numbers (BINs), a species proxy. Only 63% of the BINs were shared among the three sampling sites while BIN sharing between any two sites did not exceed 75%. Comparison of these records against all those on BOLD made it possible to identify 40% of the BINs to a species, 57% to a genus, 97% to a family, and 99% to an order. Species which received a species match on BOLD were placed in one of four categories based on this assignment: pest, parasitoid, predator, or pollinator. As this study provides the first baseline data on insect biodiversity in Chinese citrus plantations, it is a valuable resource for research in a broad range of areas such as pest management and monitoring beneficial insects in citrus gardens.
DOI: 10.25919/0qcy-ck83
title: Parkes observations for project P1173 semester 2022OCTS_02

description: Spider pulsar systems are compact binary pulsars with low-mass companions in tight orbits, where the primary pulsar is ablating the secondary through the output of high-energy radiation and pulsar wind due to proximity. These systems present an interesting opportunity to probe the mechanisms related to the destruction of these low-mass bodies in the radio regime, as debris surrounding the ablated secondary companion causes the pulsar emission to propagate and scatter as it moves through it, along our line of sight - revealing details of the complex, turbulent structure of this region. Recent studies have shown that the eclipsing region can cause pulsar signals to scatter, revealing small-scale structure of the turbulent field, as well as a strong variation in the pulsar’s polarsiation, rotation measure and dispersion measure. Under this proposal, we wish to study two known spider pulsars for their full orbit with the Parkes UWL capability – which has not been achieved by any other telescope. This will give us the opportunity to analyse he eclipsing effects of these systems.
DOI: 10.5281/zenodo.6526191
title: Understanding Security Issues in the NFT Ecosystem

description: The dataset used in the ACM CCS 2022 paper titled "Understanding Security Issues in the NFT Ecosystem". It contains the following items. The asset (e.g., collection name, asset URI, metadata URI, etc.) and event (e.g., mint, buy, sell, auction creation, placing of a bid, acceptance of a bid, transfer, etc.) data collected from the top 8 NFT marketplaces (OpenSea, Axie, CryptoPunks, Rarible, Superrare, Sorare, Foundation, and Nifty) are stored in their respective databases. Since the OpenSea dataset contains events for the same set of assets, crawled three times, with a three-month interval between two subsequent crawls: in June 2021, September 2021, and finally in December 2021, therefore respective asset tables are appropriately timestamped. The `coins` database contains the Historical prices of the cryptocoins as provided by CoinGecko. The `stats` database contains the availability of the source code of the token contracts in Etherscan. <strong>Usage</strong> Download all the parts of the dataset zip. Combine them into one single zip file. The MD5 hash of the resulting `nft-marketplaces.zip` would be `2e27cd3a319d0fb187a1a51589156e96`. <pre><code class="language-bash">cat nft-marketplaces.zip.part* &gt; nft-marketplaces.zip</code></pre> Extract the zip file containing the database dumps. <pre><code class="language-bash">unzip nft-marketplaces.zip</code></pre> Restore databases to a PostgreSQL instance: <pre><code class="language-bash">pg_restore -U $DB_USER -h $DB_HOST -v -Fc -Fd -C -d postgres -j $CONCURRENCY $DB_DIR &gt; $LOG_DIR/pg_$DB.log 2&gt;&1</code></pre> Substitute variables with appropriate values. $DB_DIR is the directory containing the database backup files. $LOG_DIR is the directory containing the restoration logs. <strong>Citation</strong> If you use this dataset, please cite our ACM CCS '22 paper. <pre><code>@inproceedings{nft-study, author = {Dipanjan Das and Priyanka Bose and Nicola Ruaro and Christopher Kruegel and Giovanni Vigna}, booktitle = {Proceedings of the ACM Conference on Computer and Communications Security (CCS)}, title = {Understanding Security Issues in the NFT Ecosystem}, year = {2022} }</code></pre>
DOI: 10.5281/zenodo.6526192
title: Understanding Security Issues in the NFT Ecosystem

description: The dataset used in the ACM CCS 2022 paper titled "Understanding Security Issues in the NFT Ecosystem". It contains the following items. The asset (e.g., collection name, asset URI, metadata URI, etc.) and event (e.g., mint, buy, sell, auction creation, placing of a bid, acceptance of a bid, transfer, etc.) data collected from the top 8 NFT marketplaces (OpenSea, Axie, CryptoPunks, Rarible, Superrare, Sorare, Foundation, and Nifty) are stored in their respective databases. Since the OpenSea dataset contains events for the same set of assets, crawled three times, with a three-month interval between two subsequent crawls: in June 2021, September 2021, and finally in December 2021, therefore respective asset tables are appropriately timestamped. The `coins` database contains the Historical prices of the cryptocoins as provided by CoinGecko. The `stats` database contains the availability of the source code of the token contracts in Etherscan. <strong>Usage</strong> Download all the parts of the dataset zip. Combine them into one single zip file. The MD5 hash of the resulting `nft-marketplaces.zip` would be `2e27cd3a319d0fb187a1a51589156e96`. <pre><code class="language-bash">cat nft-marketplaces.zip.part* &gt; nft-marketplaces.zip</code></pre> Extract the zip file containing the database dumps. <pre><code class="language-bash">unzip nft-marketplaces.zip</code></pre> Restore databases to a PostgreSQL instance: <pre><code class="language-bash">pg_restore -U $DB_USER -h $DB_HOST -v -Fc -Fd -C -d postgres -j $CONCURRENCY $DB_DIR &gt; $LOG_DIR/pg_$DB.log 2&gt;&1</code></pre> Substitute variables with appropriate values. $DB_DIR is the directory containing the database backup files. $LOG_DIR is the directory containing the restoration logs. <strong>Citation</strong> If you use this dataset, please cite our ACM CCS '22 paper. <pre><code>@inproceedings{nft-study, author = {Dipanjan Das and Priyanka Bose and Nicola Ruaro and Christopher Kruegel and Giovanni Vigna}, booktitle = {Proceedings of the ACM Conference on Computer and Communications Security (CCS)}, title = {Understanding Security Issues in the NFT Ecosystem}, year = {2022} }</code></pre>
DOI: 10.6073/pasta/216bc17b3e9a24994119d4ff3039e6a1
title: Survey of pond habitats and aquatic diversity of Madison, Wisconsin from May to Aug 2019 and 2020 Data Set

description: 1) Urbanization may lead to changes in local richness (alpha diversity) or in community composition (beta diversity), although the direction of change can be challenging to predict. For instance, introduced species may offset the loss of native specialist taxa, leading to no change in alpha diversity in urban areas, but decreased beta diversity (i.e., more homogenous community structure). Alternatively, because urban areas can have low connectivity and high environmental heterogeneity between sites, they may support distinct communities from one another over small geographic distances. 2) Wetlands and ponds provide critical ecosystem services and support diverse communities, making them important systems in which to understand consequences of urbanization. To determine how urban development shapes pond community structure, we surveyed 68 ponds around Madison, Wisconsin, USA, which were classified as urban, greenspace, or rural based on surrounding land use. We evaluated the influence of local abiotic factors, presence of nonnative fishes, and landscape characteristics on alpha diversity of aquatic plants, macroinvertebrates, and vertebrates. We also analyzed whether surrounding land cover was associated with changes in community composition and/or the presence of specific taxa. 3) We found a 23% decrease in mean richness (alpha diversity) from rural to urban pond sites, and a 15% decrease in richness from rural to urban greenspace pond sites. Among landscape factors, observed pond richness was negatively correlated with adjacent developed land and mowed lawns, as well as greater distances to other waterbodies. Among pond level factors, habitat complexity was associated with increased richness, while the presence of invasive fish was associated with decreased richness. 4) Beta diversity was relatively high for all ponds due to turnover in composition between sites. Urban ponds supported more introduced species, lacked a subset of native species found in rural ponds, and had slightly higher beta diversity than greenspace and rural ponds. 5) Synthesis and Applications: Integrating ponds into connected greenspaces comprised of native vegetation (rather than mowed grass), preventing nonnative fish introductions, and promoting habitat complexity may mitigate negative effects of urbanization on aquatic richness. The high beta diversity of distinct pond communities emphasizes their importance to biodiversity support in urban environments, despite being small in size and rarely incorporated into urban conservation planning.
DOI: 10.5281/zenodo.7507032
title: JF ligand file test upload

description: JF ligand inventory test upload
DOI: 10.5281/zenodo.7507033
title: JF ligand file test upload

description: JF ligand inventory test upload
DOI: 10.15132/10000189
title: Leptin-based hexamers facilitate memory and prevent amyloid-driven AMPA receptor internalisation and neuronal degeneration

description: Datasets in support of the paper Leptin-based hexamers facilitate memory and prevent amyloid-driven AMPA receptor internalisation and neuronal degeneration
DOI: 10.18742/18166406
title: GWAS Summary statistics - HIV-1 acquisition meta-analysis - Duarte et al. 2022

description: <strong>Transcriptome-wide association study of HIV-1 acquisition identifies </strong><em><strong>HERC1</strong></em><strong> as a susceptibility gene </strong> <br> <strong>Abstract: </strong>The host genetic factors conferring protection against HIV-1 acquisition, particularly those regulated by common genetic variants, remain elusive. Here, we performed the largest genome-wide association meta-analysis of HIV-1 acquisition, which included 7,303 HIV-1-positive individuals and 587,343 population controls. We identified 25 independent genetic loci with suggestive association, of which one was genome-wide significant within the major histocompatibility complex (MHC) locus. After exclusion of the MHC signal, linkage disequilibrium score regression analyses revealed a SNP heritability of 21%, and genetic correlations with behavioral factors. A transcriptome-wide association study identified 15 susceptibility genes, including <em>HERC1</em>, <em>UEVLD, </em>and<em> HIST1H4K</em>. Convergent evidence from conditional analyses and fine-mapping identified <em>HERC1</em> downregulation in immune cells as a robust mechanism associated with HIV-1 acquisition. Functional studies on <em>HERC1</em> and other identified candidates, as well as larger genetic studies, have the potential to further our understanding of the host mechanisms associated with protection against HIV-1. <br> <strong>Content: </strong>The file in this repository contains GWAS summary statistics for the HIV-1 meta-analysis and a read me file describing the column labels. Studies included in the meta-analysis (see URLs under "References"): 1) McLaren P.J. et al. (2013). Association Study of Common Genetic Variants and HIV-1 Acquisition in 6,300 Infected Cases and 7,200 Controls. PLOS Pathogens 9, e1003515. 10.1371/journal.ppat.1003515. 2) Johnson E.O. et al. (2015). Novel Genetic Locus Implicated for HIV-1 Acquisition with Putative Regulatory Links to HIV Replication and Infectivity: A Genome-Wide Association Study. PLOS ONE 10, e0118149. 10.1371/journal.pone.0118149. 3) Ben Neale’s group’s UKBB results (data release 3, trait ID 20002_1439 HIV/AIDS). 4) FinnGen (data release 5, trait ID AB1_HIV). <br> <strong>Related content:</strong> Code used in manuscript has also been deposited in Figshare, DOI: 10.18742/20343219. <br> <strong>Disclaimer: </strong>If you choose to download and analyse these data, you acknowledge that: - These data are provided on an “as-is” basis, and no warranty is provided as to their performance or fitness for any purpose - You and your collaborators are in compliance with all applicable local/state/national/international laws or regulations and institutional policies regarding human subjects and genetics research - You will cite Duarte et al. 2022 in any communications or publications arising directly or indirectly from these data - All data here are released for the benefit of the wider biomedical community for use in the investigation of the genetics of susceptibility to infectious agents and wider genetics research.
DOI: 10.18742/18166406.v1
title: GWAS Summary statistics - HIV-1 acquisition meta-analysis - Duarte et al. 2022

description: <strong>Transcriptome-wide association study of HIV-1 acquisition identifies </strong><em><strong>HERC1</strong></em><strong> as a susceptibility gene </strong> <br> <strong>Abstract: </strong>The host genetic factors conferring protection against HIV-1 acquisition, particularly those regulated by common genetic variants, remain elusive. Here, we performed the largest genome-wide association meta-analysis of HIV-1 acquisition, which included 7,303 HIV-1-positive individuals and 587,343 population controls. We identified 25 independent genetic loci with suggestive association, of which one was genome-wide significant within the major histocompatibility complex (MHC) locus. After exclusion of the MHC signal, linkage disequilibrium score regression analyses revealed a SNP heritability of 21%, and genetic correlations with behavioral factors. A transcriptome-wide association study identified 15 susceptibility genes, including <em>HERC1</em>, <em>UEVLD, </em>and<em> HIST1H4K</em>. Convergent evidence from conditional analyses and fine-mapping identified <em>HERC1</em> downregulation in immune cells as a robust mechanism associated with HIV-1 acquisition. Functional studies on <em>HERC1</em> and other identified candidates, as well as larger genetic studies, have the potential to further our understanding of the host mechanisms associated with protection against HIV-1. <br> <strong>Content: </strong>The file in this repository contains GWAS summary statistics for the HIV-1 meta-analysis and a read me file describing the column labels. Studies included in the meta-analysis (see URLs under "References"): 1) McLaren P.J. et al. (2013). Association Study of Common Genetic Variants and HIV-1 Acquisition in 6,300 Infected Cases and 7,200 Controls. PLOS Pathogens 9, e1003515. 10.1371/journal.ppat.1003515. 2) Johnson E.O. et al. (2015). Novel Genetic Locus Implicated for HIV-1 Acquisition with Putative Regulatory Links to HIV Replication and Infectivity: A Genome-Wide Association Study. PLOS ONE 10, e0118149. 10.1371/journal.pone.0118149. 3) Ben Neale’s group’s UKBB results (data release 3, trait ID 20002_1439 HIV/AIDS). 4) FinnGen (data release 5, trait ID AB1_HIV). <br> <strong>Related content:</strong> Code used in manuscript has also been deposited in Figshare, DOI: 10.18742/20343219. <br> <strong>Disclaimer: </strong>If you choose to download and analyse these data, you acknowledge that: - These data are provided on an “as-is” basis, and no warranty is provided as to their performance or fitness for any purpose - You and your collaborators are in compliance with all applicable local/state/national/international laws or regulations and institutional policies regarding human subjects and genetics research - You will cite Duarte et al. 2022 in any communications or publications arising directly or indirectly from these data - All data here are released for the benefit of the wider biomedical community for use in the investigation of the genetics of susceptibility to infectious agents and wider genetics research.
DOI: 10.5281/zenodo.7006309
title: Radar and ground-level measurements collected during the POPE 2020 campaign at Princess Elisabeth Antarctica

description: This repository contain the datasets of radar and ground-level measurements collected in the vicinity of the Belgian research base Princess Elisabeth Antarctica (PEA). The measurement campaign has been conducted by the Environmental Remote Sensing Laboratory (LTE) of the Scole Polytechnique Fédérale de Lausanne (EPFL), with the logistical support of the International Polar Foundation (IPF). The datasets and their processing are described in the article “Radar and ground-level measurements of clouds and precipitation collected during the POPE 2020 campaign at Princess Elisabeth Antarctica”, by Alfonso Ferrone and Alexis Berne, submitted to Earth System Science Data in July 2022. <br> <br> <strong>Content</strong><br> The datasets have been divided into compressed archives. Each of them contains a series of data files, all saved in NetCDF4 format.<br> The content of each archives is listed below. - <em>WProf.zip</em><br> This archive contains the radar variables collected by the W-band Doppler profiling cloud radar (WProf) deployed at PEA.<br> The liquid water path and integrated water vapor (retrieved thanks to the 89 GHz radiometer included in the instrument) has also been included in the files. - <em>MXPol_PPI.zip</em><br> This archive contains the polarimetric radar variables collected by the X-band Doppler dual-polarization scanning weather radar (MXPol) during the nearly-vertical PPI scans. - <em>MXPol_sector_scans_2019.zip</em><br> This archive contains the polarimetric radar variables collected by MXPol during the sector scans (PPI scans limited to a sector of the full azimuth circle) scans performed in December 2019. Sector scans collected in the following months have been stored separately, due to a limitation on the maximum number of files in input to the creation of the zip archive. - <em>MXPol_sector_scans_2020.zip</em><br> This archive contains the polarimetric radar variables collected by MXPol during the sector scans scans performed in January and February 2020. - <em>MXPol_hydrometeor_types.zip</em><br> This archive contains the polarimetric radar variables collected by MXPol during the RHI scans. The files also contain information on the proportion of hydrometeor classes and the dominant hydrometeor type computed from the measurements of MXPol. - <em>MRR_PRO_06.zip, MRR_PRO_22.zip, and MRR_PRO_23.zip</em><br> The three archives contain the radar variables collected by the K-band Doppler profiling radars (MRR-PRO) deployed in a transect across the mountain range south of PEA. - <em>aws_radiometers.zip</em><br> This archive contains the measurements collected by the Automated Weather Station (AWS) installed alongside each of the three MRR-PRO. The data from the two radiometers deployed at the MRR-PRO 06 site have also been included in the archive.
DOI: 10.57745/makcos
title: AP_FAIR_results_01_10_2021.xlsx

description: :unav
DOI: 10.6084/m9.figshare.21822111
title: Data Manufacturing

description: Data on local agricultural machinery manufacturers in Africa
DOI: 10.5281/zenodo.7504042
title: Grid-to-Grid daily simulated soil moisture 1964-2018, at selected UK Soil Moisture Databank sites.

description: This dataset contains Grid-to-Grid (G2G) daily simulated soil moisture time-series at selected UK Soil Moisture Databank (UKSMD) sites. It was created to facilitate an evaluation of G2G simulated soil moisture against the UKSMD neutron probe soil moisture observations (Bell et al., 2022). G2G (Bell et al., 2009) is a national-scale gridded hydrological model, which has been widely applied to simulate river flows and more recently soil moisture. Here, the model was run at 1km resolution from 01/01/1964 - 16/12/2019 across Great Britain. Simulated soil moisture time-series are provided for the 1km grid-cells closest to selected UKSMD site locations. The G2G simulates vertically-integrated soil moisture in units of mm/m. For further explanation of G2G soil moisture, please see Kay et al., 2022 (https://iopscience.iop.org/article/10.1088/1748-9326/ac7a4e). The data is provided as two plain text files: 1) g2g_soilmoist_1964_2018.txt contains the simulated soil moisture values. The first three columns specify the simulation date (day, month, year). Subsequent columns are soil moisture (mm/m) time-series at each site, with the UKSMD site ID given as column headers. 2) site_locations.csv contains the locations of the UKSMD sites. In some cases there were multiple tubes with slightly different locations within a larger site, and here we are providing the location of the specific tube used. Columns specify: SITE_NAME (the site ID), TUBE_NAME (the tube number), EASTING and NORTHING (easting and northing in British National Grid). The site ID and tube names used in this document are consistent with the UKSMD documentation. References: Bell, V. A., Kay, A. L., Jones, R. G., Moore, R. J., & Reynard, N. S. (2009). Use of soil data in a grid-based hydrological model to estimate spatial variation in changing flood risk across the UK. Journal of Hydrology, 377(3-4), 335-350. Bell, V.A.; Davies, H.N.; Fry, M.; Zhang, T.; Murphy, H.; Hitt, O.; Hewitt, E.J.; Chapman, R.; Black, K.B. (2022). Collated neutron probe measurements and derived soil moisture data, UK, 1966-2013. NERC EDS Environmental Information Data Centre. https://doi.org/10.5285/450bb14b-c711-47af-8792-f9bd88482cd4 Kay, A. L., Lane, R. A., & Bell, V. A. (2022). Grid-based simulation of soil moisture in the UK: future changes in extremes and wetting and drying dates. Environmental Research Letters, 17(7), 074029.