cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.7864933
title: Newick Trees for EMERGE methanogen genome tree, and methylotrophic gene trees

description: Newick trees provided for phylogenomic and phylogenetic analyses from Ellenbogen <em>et al. </em>(in prep). The methanogen genome tree (gtdbtk.ar53.decorated.tree) was built using a GTDB-Tk v12.1.1 r207 run with the de novo workflow. All other trees are RAxML gene trees built using ProtPipeliner (https://github.com/TheWrightonLab/Protpipeliner/blob/master/protpipeliner.py) to confirm the functional identity of identified methylotrophic genes from methanogens and bacteria. The names of the Newick trees correspond to relevant gene groupings as discussed in the associated manuscript. DRAM v1.3.2 raw annotations files for Stordalen methanogen MAGs also included. FUNDING:<br> This research is a contribution of the EMERGE Biology Integration Institute, funded by the National Science Foundation, Biology Integration Institutes Program, Award # 2022070.<br> We thank the Swedish Polar Research Secretariat and SITES for the support of the work done at the Abisko Scientific Research Station. SITES is supported by the Swedish Research Council's grant 4.3-2021-00164.<br> This study was also funded by the Genomic Science Program of the United States Department of Energy Office of Biological and Environmental Research, grant #s DE-SC0010580 and DE-SC0016440.
DOI: 10.34740/kaggle/dsv/5530759
title: Mahanagar Yatayat Dataset
DOI: 10.5281/zenodo.7867102
title: ipaast-czo case study OptRX data: Montalcino (SI, Italy)

description: These data were collected as part of a case study for the ipaast project. The aim of the survey was to produce datasets interoperable for applications in archaeology and precision agriculture. The OptRx® Crop Sensors (AgLeader Technology, Ames, IO, USA) measure the reflectance in the 630–685 nm (red), 695–750 nm (RE red edge) and 760–850 nm (NIR—Near InfraRed) wavebands. Using those wavebands, NDVI and NDRE indexes are calculated. NDVI and NDRE are vegetative indexes obtained from the red, red-edge and NIR wavebands with formulas 1 and 2: NDVI = NIR−REDNIR+RED ; NDRE= NIR−RENIR+RE The two index values range from -1 (bare ground or water) to 1 (highly vigorous vegetation). To collect data, the sensor was mounted on a ground vehicle, a Kubota B2420 tractor. The sensor was paired with a GNNS receiver, GPS 6500 from AgLeader Technology (Ames, IO, USA). The instrumentation was coupled with the hardware and the rough book (Panasonic ToughPad FG-Z1, Panasonic Core. It was possible to install the sensor facing the ground using a metal bracket positioned on the front of the tractor. The sensor was positioned 1.15 m from the ground, emitting a rectangular footprint of 1.14 m in length and 20cm in width. The data were collected every 30 cm in alternate rows. 12 rows in total were analysed, covering a surface of 1.07 ha. Data were processed on QGIS. First, the data was interpolated with the Inverse Distance Weighting (IDW) function. The function was set up with a distance coefficient P of 4, with 40 rows and 98 columns. A Gaussian filter with a standard deviation value of 2 and a range of research of 3 was subsequently applied to create a representative raster.
DOI: 10.5281/zenodo.7867101
title: ipaast-czo case study OptRX data: Montalcino (SI, Italy)

description: These data were collected as part of a case study for the ipaast project. The aim of the survey was to produce datasets interoperable for applications in archaeology and precision agriculture. The OptRx® Crop Sensors (AgLeader Technology, Ames, IO, USA) measure the reflectance in the 630–685 nm (red), 695–750 nm (RE red edge) and 760–850 nm (NIR—Near InfraRed) wavebands. Using those wavebands, NDVI and NDRE indexes are calculated. NDVI and NDRE are vegetative indexes obtained from the red, red-edge and NIR wavebands with formulas 1 and 2: NDVI = NIR−REDNIR+RED ; NDRE= NIR−RENIR+RE The two index values range from -1 (bare ground or water) to 1 (highly vigorous vegetation). To collect data, the sensor was mounted on a ground vehicle, a Kubota B2420 tractor. The sensor was paired with a GNNS receiver, GPS 6500 from AgLeader Technology (Ames, IO, USA). The instrumentation was coupled with the hardware and the rough book (Panasonic ToughPad FG-Z1, Panasonic Core. It was possible to install the sensor facing the ground using a metal bracket positioned on the front of the tractor. The sensor was positioned 1.15 m from the ground, emitting a rectangular footprint of 1.14 m in length and 20cm in width. The data were collected every 30 cm in alternate rows. 12 rows in total were analysed, covering a surface of 1.07 ha. Data were processed on QGIS. First, the data was interpolated with the Inverse Distance Weighting (IDW) function. The function was set up with a distance coefficient P of 4, with 40 rows and 98 columns. A Gaussian filter with a standard deviation value of 2 and a range of research of 3 was subsequently applied to create a representative raster.
DOI: 10.5066/p9iiihqf
title: Measurements of velocity and bathymetry in the Ashtabula River near Ashtabula, Ohio, July 12&amp;amp;ndash;14, 2022

description: These data are depth-averaged velocities measured by an acoustic Doppler current profiler (ADCP), as well as continuous depth-averaged velocities from a stationary location measured with an acoustic Doppler velocity meter (ADVM). These data were collected from the July 12-14, 2022, survey of the Ashtabula River near Ashtabula, Ohio. The location of the ADCP data are from approximately 1,500 feet upstream from the Bridge Street bridge to 3,000 feet upstream from the Bridge Street bridge. The ADVM data are from approximately 41� 53' 46.4"N, 80� 47' 39.5"W. ADCP data were collected using an integrated global navigation satellite system (GNSS) smart antenna with submeter accuracy. The ADCP and GNSS antenna were mounted on a boat and collected data as the boat traversed the area along planned survey lines. These survey lines were chosen to measure velocities near engineered flow control structures (root wads/rock vanes/boulder clusters/sills). There was typically one reciprocal pair (two passes) of data collected per line, and survey lines were completed once in the morning and once in the afternoon to try to cover a range of flows. These data were collected to increase understanding of flow patterns around the engineered flow control structures.
DOI: 10.18112/openneuro.ds004557.v1.1.0
title: The role of superstition of cognitive control during neurofeedback training - part 2
DOI: 10.6084/m9.figshare.22701034
title: VC1_JansenPhageA

description: VC1_JansenPhageA
DOI: 10.6084/m9.figshare.22701034.v1
title: VC1_JansenPhageA

description: VC1_JansenPhageA
DOI: 10.5287/ora-mzzd1qykn
title: Mixed strain pathogen populations accelerate the evolution of antibiotic resistance in patients

description: This is the source data file for the manuscript "Mixed strain pathogen populations accelerate the evolution of antibiotic resistance in patients" accepted at Nature Communications.
DOI: 10.5281/zenodo.7867315
title: ipaast case study: Wiltshire yield and EM survey data

description: These data were collected by Soyl Ltd as part of a commercial agricultural soil survey. They were reprocessed by the University of Ghent ipaast team.
DOI: 10.5281/zenodo.7867314
title: ipaast case study: Wiltshire yield and EM survey data

description: These data were collected by Soyl Ltd as part of a commercial agricultural soil survey. They were reprocessed by the University of Ghent ipaast team.
DOI: 10.6084/m9.figshare.22700959.v1
title: Supplementary Table 2.xls

description: Bacterial genome used from Freilich dataset:<br> List of bacterial genomes information used to test the predictor
DOI: 10.6084/m9.figshare.22700959
title: Supplementary Table 2.xls

description: Bacterial genome used from Freilich dataset:<br> List of bacterial genomes information used to test the predictor
DOI: 10.5066/p99aeef4
title: Hydrogeologic Aquifer Test dataset, Lower Mississippi-Gulf Water Science Center, March 2022

description: Since the 1940's, commercial, academic and government hydrologist have used aquifer test to estimate the hydrogeologic properties near test wells. Results from these tests are recorded in various files, databases, reports and scientific publications. The LMG-Hydrogeologic Test dataset is an attempt to aggregate these dispersed hydrogeologic test results into a single dataset that is publicly available and in a machine readable format.
DOI: 10.6084/m9.figshare.22701115.v1
title: VC1_JansenPhageB

description: VC1_JansenPhageB
DOI: 10.6084/m9.figshare.22701115
title: VC1_JansenPhageB

description: VC1_JansenPhageB
DOI: 10.6084/m9.figshare.22701097
title: Supplementary Table 1.xls

description: Bacterial genomes for predictor: <br> List of bacterial genomes information used to create the predictor
DOI: 10.6084/m9.figshare.22701097.v1
title: Supplementary Table 1.xls

description: Bacterial genomes for predictor: <br> List of bacterial genomes information used to create the predictor
DOI: 10.6084/m9.figshare.22701133
title: VC1_JansenPhageC

description: VC1_JansenPhageC
DOI: 10.6084/m9.figshare.22701133.v1
title: VC1_JansenPhageC

description: VC1_JansenPhageC
DOI: 10.6084/m9.figshare.22701151
title: VC3_JansenPhageA

description: VC3_JansenPhageA
DOI: 10.6084/m9.figshare.22701151.v1
title: VC3_JansenPhageA

description: VC3_JansenPhageA
DOI: 10.57780/esa-tfnxgu7
title: ESA-MRG_Cilbo_Spectra_V1.0

description: This dataset contains the products of the research on meteor spectroscopy, conducted by the Meteor Research Group (MRG) at the European Space Research and Technology Centre (ESTEC).
DOI: 10.5281/zenodo.7868296
title: Master chart for the thesis

description: Master chart of the thesis containing responses to determine the four temperaments namely choleric, sanguine, melancholic and phlegmatic ,dominant in each patient.
DOI: 10.5281/zenodo.7868295
title: Master chart for the thesis

description: Master chart of the thesis containing responses to determine the four temperaments namely choleric, sanguine, melancholic and phlegmatic ,dominant in each patient.
DOI: 10.6084/m9.figshare.22701157
title: VC3_JansenPhageB

description: VC3_JansenPhageB
DOI: 10.6084/m9.figshare.22701157.v1
title: VC3_JansenPhageB

description: VC3_JansenPhageB
DOI: 10.6084/m9.figshare.22701163
title: VC3_JansenPhageC

description: VC3_JansenPhageC
DOI: 10.6084/m9.figshare.22701163.v1
title: VC3_JansenPhageC

description: VC3_JansenPhageC
DOI: 10.5519/qd.a5c85aqk
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (554 records)
DOI: 10.57780/esa-zxxl63l
title: 16969

description: This is a continuation of Program 16521 and is to be executed this cycle for internal CTE. There are two epochs of observations comma  one set in November-December 2022 and the other in May-June 2023.  The charge transfer efficiency (CTE) of the ACS CCD detectors declines as damage due to on-orbit radiation exposure accumulates. This degradation will be monitored twice a cycle to determine the useful lifetime of the CCDs (prior to 2015 comma  cycles were only monitored once a year). All the data for this program is internal (LED) only comma  so all of the exposures should be taken during Earth occultation time (but not during SAA passages). This program emulates the majority of the ACS pre-flight ground calibration and post-launch SMOV testing (program 8948) comma  so that results from each epoch can be directly compared.  Extended pixel edge response (EPER) data will be collected over a range of six signal levelsdoublePoint 182 comma  430 comma  1620 comma  3400 comma  7100 comma  and 42 comma 000 electrons. The data will be 0.5-sec darks post-flashed to the given levels. The post-flash LED will be used at low and high current comma  and readout will use gain 2 (CCDGAIN=2). Both parallel and serial CTE measurements can be made with the data. Both CCDAMP=AD and CCDAMP=BC will be monitored to test for CTE amplifier dependence. Shutter problems encountered during the first epoch of Program 15761 led to additional S-C exposures and containers being required to properly manage shutter behavior for EPER observations.
DOI: 10.5521/forestplots.net/2023_1
title: Data and R-code from 'Julia Valentim Tavares, Rafael S. Oliveira, Maurizio Mencuccini, [...] Oliver L. Phillips, Emanuel Gloor, David R. Galbraith. Basin-wide variation in tree hydraulic safety margins predicts the carbon balance of Amazon forests. Nature 2023. DOI 10.1038/s41586-023-05971-3'
DOI: 10.5281/zenodo.7861894
title: CHclim25 - maximum temperature (Tmax)

description: Maximum air temperature above 2m is derived from daily 1 km resolution gridded dataset from the Swiss federal agency for meteorology and climate (MeteoSwiss) using a downscaling procedure based on local regressions with a 25 m resolution elevation model. Monthly and yearly individual and current average (1981-2010) and future average (2020-2049, 2045-2074, and 2070-2099)<strong> </strong>geoTIFF layers can be downloaded from separate zip files. Future layers are based on the transient daily time series of gridded climate scenarios of temperature at 0.02°D (~2.2 km) provided by the CH2018 initiative. Anomalies between monthly temperature for 1981-2010 and monthly temperature for the future period at 2.2 km were downscaled at 25 m using bilinear interpolation. Anomalies were then added to 1981-2010 average monthly variables. We calculated future climatic layers for 4 GCMs (HADGEM, ECEARTH, MPIESM, and IPSL), 3 time slices (2020-2049, 2045-2074, and 2070-2099) and 3 representative concentration pathways (RCP 2.6, 4.5 and 8.5) The layer files are stored in compressed GeoTIFF format with the “deflate” algorithm with option “predictor2” from the GDAL. This format has a high compression ratio but allows direct import in most GIS softwares. All the maps are projected in the Swiss coordinate system CH 1903+ LV95 (epsg:2056) with a resolution of 25x25m using the extent of the digital height model DHM25 of the Swiss office for topography (swisstopo).
DOI: 10.5281/zenodo.7861893
title: CHclim25 - maximum temperature (Tmax)

description: Maximum air temperature above 2m is derived from daily 1 km resolution gridded dataset from the Swiss federal agency for meteorology and climate (MeteoSwiss) using a downscaling procedure based on local regressions with a 25 m resolution elevation model. Monthly and yearly individual and current average (1981-2010) and future average (2020-2049, 2045-2074, and 2070-2099)<strong> </strong>geoTIFF layers can be downloaded from separate zip files. Future layers are based on the transient daily time series of gridded climate scenarios of temperature at 0.02°D (~2.2 km) provided by the CH2018 initiative. Anomalies between monthly temperature for 1981-2010 and monthly temperature for the future period at 2.2 km were downscaled at 25 m using bilinear interpolation. Anomalies were then added to 1981-2010 average monthly variables. We calculated future climatic layers for 4 GCMs (HADGEM, ECEARTH, MPIESM, and IPSL), 3 time slices (2020-2049, 2045-2074, and 2070-2099) and 3 representative concentration pathways (RCP 2.6, 4.5 and 8.5) The layer files are stored in compressed GeoTIFF format with the “deflate” algorithm with option “predictor2” from the GDAL. This format has a high compression ratio but allows direct import in most GIS softwares. All the maps are projected in the Swiss coordinate system CH 1903+ LV95 (epsg:2056) with a resolution of 25x25m using the extent of the digital height model DHM25 of the Swiss office for topography (swisstopo).
DOI: 10.5281/zenodo.7857132
title: Dataset for manuscript "Thermal infrared dust optical depth and coarse-mode effective diameter over oceans retrieved from collocated MODIS and CALIOP observations"

description: This is the long-term satellite retrieval dataset of dust aerosol optical depth at 10 μm (DAOD<sub>10μm</sub>) and dust coarse mode effective diameter (D<sub>eff</sub>) based on collocated MODIS and CALIOP observations from July 2006 to August 2018. The full description is in the manuscript "<strong>Thermal infrared dust optical depth and coarse-mode effective diameter over oceans retrieved from collocated MODIS and CALIOP observations" </strong>by Zheng, Jianyu, et al. The readme file for the data is in "readme_dust_aod_size_product.txt". The variable list of Level-2 data is in "variable_list_L2.txt". The variable list of Level-3 data is in "variable_list_L3.txt".
description: {"references": ["Zheng, J., Zhang, Z., Yu, H., Garnier, A., Song, Q., Wang, C., Di Biagio, C., Kok, J. F., Derimian, Y., and Ryder, C.: Thermal infrared dust optical depth and coarse-mode effective diameter retrieved from collocated MODIS and CALIOP observations, EGUsphere [preprint], https://doi.org/10.5194/egusphere-2023-103, 2023."]}
DOI: 10.5281/zenodo.7857131
title: Dataset for manuscript "Thermal infrared dust optical depth and coarse-mode effective diameter over oceans retrieved from collocated MODIS and CALIOP observations"

description: This is the long-term satellite retrieval dataset of dust aerosol optical depth at 10 μm (DAOD<sub>10μm</sub>) and dust coarse mode effective diameter (D<sub>eff</sub>) based on collocated MODIS and CALIOP observations from July 2006 to August 2018. The full description is in the manuscript "<strong>Thermal infrared dust optical depth and coarse-mode effective diameter over oceans retrieved from collocated MODIS and CALIOP observations" </strong>by Zheng, Jianyu, et al. The readme file for the data is in "readme_dust_aod_size_product.txt". The variable list of Level-2 data is in "variable_list_L2.txt". The variable list of Level-3 data is in "variable_list_L3.txt".
description: {"references": ["Zheng, J., Zhang, Z., Yu, H., Garnier, A., Song, Q., Wang, C., Di Biagio, C., Kok, J. F., Derimian, Y., and Ryder, C.: Thermal infrared dust optical depth and coarse-mode effective diameter retrieved from collocated MODIS and CALIOP observations, EGUsphere [preprint], https://doi.org/10.5194/egusphere-2023-103, 2023."]}
DOI: 10.18112/openneuro.ds004556.v1.0.1
title: The role of superstition of cognitive control during neurofeedback training - part 1
DOI: 10.5517/ccdc.csd.cc2c5m5c
title: CCDC 2180142: Experimental Crystal Structure Determination

description: Related Article: Hai-Ling Wang, Qiu-Xiang Yu, Zhong-Hong Zhu, Xing-Lin Lu, Yun-Lan Li, Fu-Pei Liang, Hua-Hong Zou|2023|Inorg.Chem.|62|5863|doi:10.1021/acs.inorgchem.3c00743
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.6084/m9.figshare.22701130
title: data.xlsx

description: Market Survey Data for article <strong>FACTORS AFFECTING THE SATISFACTION OF CONSUMERS INVESTMENT PATTERN IN GOLD</strong>
DOI: 10.6084/m9.figshare.22701316
title: VC3_JansenPhageB

description: VC3_JansenPhageB
DOI: 10.6084/m9.figshare.22701316.v1
title: VC3_JansenPhageB

description: VC3_JansenPhageB
DOI: 10.34740/kaggle/dsv/5333807
title:  Synthetic Industrial Parts dataset (SIP-17)
DOI: 10.5281/zenodo.7868328
title: Smile aesthetics master chart for thesis

description: Master chart of the thesis containing responses about the percentage of kind of facial form, tooth shape and angulation of maxillary teeth w.r.t horizontal plane present in the four temperaments.
DOI: 10.5281/zenodo.7868327
title: Smile aesthetics master chart for thesis

description: Master chart of the thesis containing responses about the percentage of kind of facial form, tooth shape and angulation of maxillary teeth w.r.t horizontal plane present in the four temperaments.
DOI: 10.6084/m9.figshare.22701328
title: VC3_JansenPhageD

description: VC3_JansenPhageD
DOI: 10.6084/m9.figshare.22701328.v1
title: VC3_JansenPhageD

description: VC3_JansenPhageD
DOI: 10.6084/m9.figshare.22701331
title: VC3_JansenPhageE

description: VC3_JansenPhageE
DOI: 10.6084/m9.figshare.22701331.v1
title: VC3_JansenPhageE

description: VC3_JansenPhageE
DOI: 10.6084/m9.figshare.22701334
title: VC3_JansenPhageF

description: VC3_JansenPhageF
DOI: 10.6084/m9.figshare.22701334.v1
title: VC3_JansenPhageF

description: VC3_JansenPhageF
DOI: 10.6084/m9.figshare.22701340
title: VC3_JansenPhageG

description: VC3_JansenPhageG
DOI: 10.6084/m9.figshare.22701340.v1
title: VC3_JansenPhageG

description: VC3_JansenPhageG
DOI: 10.6084/m9.figshare.22701343
title: VC3_JansenPhageH

description: VC3_JansenPhageH
DOI: 10.6084/m9.figshare.22701343.v1
title: VC3_JansenPhageH

description: VC3_JansenPhageH
DOI: 10.6084/m9.figshare.22701349
title: VC3_JansenPhageI

description: VC3_JansenPhageI
DOI: 10.6084/m9.figshare.22701349.v1
title: VC3_JansenPhageI

description: VC3_JansenPhageI
DOI: 10.25345/c5tt4g378
title: MassIVE MSV000091800 - Silveira_CYP26B1_BioID_P124_6600
title: Dataset description This dataset consists of 8 raw MS files and associated peak lists and results files, acquired on AB Sciex TripleTOF 6600 mass spectrometer operated in Data Dependent Acquisition mode. Samples were generated by Ema Dreseris. BioID and Mass spectrometry acquisition was performed by Cassandra Wong. Analysis was performed by Cassandra Wong, Ema Dreseris, Anne-Claude Gingras and Eric Campos. The files are associated with a manuscript submitted for publication by Karina Silveria et al. The main goal of this paper was to investigate CYP26B1 pathogenic variants reported by two families. This dataset comprehensively maps the interactome of CYP26B1 and the associated pathogenic variants using proximity labeling and affinity purification. Peter Kannu is the corresponding author of the manuscript (kannu@ualberta.ca); Anne-Claude Gingras should be contacted for questions on this dataset (gingras@lunenfeld.ca) This submission is associated with 3 Supplementary Files (in addition to this README file) Table 1 describes the composition of this dataset Table 2 lists all the peptide identification evidence (as per iProphet) Table 3 lists the SAINTexpress interactions
DOI: 10.6084/m9.figshare.22701355
title: VC3_JansenPhageJ

description: VC3_JansenPhageJ
DOI: 10.6084/m9.figshare.22701325
title: SPSS statistics data file

description: data for <strong>BUYING BEHAVIOUR PERCEPTION OF CONSUMERS TOWARDS SAVING AND INVESTMENT IN GOLD article to for publishing in scopus indexed journal</strong>
DOI: 10.6084/m9.figshare.22701358
title: VC3_JansenPhageK

description: VC3_JansenPhageK
DOI: 10.6084/m9.figshare.22701358.v1
title: VC3_JansenPhageK

description: VC3_JansenPhageK
DOI: 10.6084/m9.figshare.22701361
title: VC3_JansenPhageL

description: VC3_JansenPhageL
DOI: 10.6084/m9.figshare.22701361.v1
title: VC3_JansenPhageL

description: VC3_JansenPhageL
DOI: 10.35078/rtnq7d
title: Replication Data for: Ficha epidemiológica de localidade: Distrito: Diamantina| Município: Jaboticatubas

description: Levantamento Triatomínico com operações de campo ocorridas em Minas Gerais pela Superintendência de Campanhas de Saúde Pública (SUCAM) e FUNASA (Fundação Nacional de Saúde), no período de 1979 a 1999, objetivando a busca da presença de vetores da doença de Chagas ou de vestígios dessa presença. A partir dela são orientadas as operações com inseticida (pt) Triatomine survey with field operations carried out in Minas Gerais by the Public Health Campaigns Superintendence (SUCAM) and FUNASA (National Health Foundation), from 1979 to 1999, aiming to search for the presence of Chagas disease vectors or traces of that presence. From it, operations with insecticide are guided (en) Encuesta de triatominos con operaciones de campo realizada en Minas Gerais por la Superintendencia de Campañas de Salud Pública (SUCAM) y FUNASA (Fundación Nacional de Salud), de 1979 a 1999, con el objetivo de buscar la presencia de vectores de la enfermedad de Chagas o rastros de esa presencia. Desde ella se orientan las operaciones con insecticida (es)
DOI: 10.6084/m9.figshare.22701367
title: VC4_HSPhageA

description: VC4_HSPhageA
DOI: 10.6084/m9.figshare.22701367.v1
title: VC4_HSPhageA

description: VC4_HSPhageA