cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5066/f7qz298v
title: Examination of contaminant exposure and reproduction of ospreys (Pandion haliaetus) nesting in Delaware Bay and River in 2015

description: Reproductive Data for All Nests Monitored; Data for Mayfield Analysis; Eggshell thickness, nestling morphological measurements, nestling plasma stable isotopes, and nestling red blood cell oxidative DNA damage; Egg organochlorine pesticide, total PCB, flame retardants, and PCB toxic equivalent concentrations; Fish capture by osprey; Fish pools and size for contaminant analysis; Fish organochlorine pesticide, total PCB and flame retardants concentrations; Data for estimation of DDE and total PCB biomagnification from fish to osprey eggs
DOI: 10.14469/hpc/4152
title: HDA-2+4 mechanism, TS1, trans + HCl, p=Me -1308.176539

description: Gaussian Calculation
DOI: 10.18739/a20c5v
title: Hydroxyl (OH) airglow image data, Alaska, November 13, 2011
DOI: 10.18739/a20c67
title: Hydroxyl (OH) airglow image data, Alaska, December 18, 2011
DOI: 10.18739/a20z97
title: Hydroxyl (OH) airglow image data, Alaska, December 3, 2011
DOI: 10.18739/a22c6v
title: Hydroxyl (OH) airglow image data, Alaska, November 30, 2011
DOI: 10.18739/a23p34
title: Hydroxyl (OH) airglow image data, Alaska, December 17, 2011
DOI: 10.18739/a2558g
title: Hydroxyl (OH) airglow image data, Alaska, December 4, 2011
DOI: 10.18739/a2628r
title: Hydroxyl (OH) airglow image data, Alaska, November 29, 2011
DOI: 10.18739/a27583
title: Hydroxyl (OH) airglow image data, Alaska, December 16, 2011
DOI: 10.18739/a29c61
title: Hydroxyl (OH) airglow image data, Alaska, November 28, 2011
DOI: 10.18739/a2bk4n
title: Hydroxyl (OH) airglow image data, Alaska, November 26, 2011
DOI: 10.18739/a2cp3m
title: Hydroxyl (OH) airglow image data, Alaska, December 15, 2011
DOI: 10.18739/a2f57k
title: Hydroxyl (OH) airglow image data, Alaska, November 27, 2011
DOI: 10.18739/a2fw1j
title: Hydroxyl (OH) airglow image data, Alaska, November 25, 2011
DOI: 10.18739/a2gp25
title: Hydroxyl (OH) airglow image data, Alaska, December 13, 2011
DOI: 10.18739/a2kp3g
title: Hydroxyl (OH) airglow image data, Alaska, November 24, 2011
DOI: 10.18739/a2mc6t
title: Hydroxyl (OH) airglow image data, Alaska, December 11, 2011
DOI: 10.18739/a2mk44
title: Hydroxyl (OH) airglow image data, Alaska, November 8, 2011
DOI: 10.18739/a2q873
title: Hydroxyl (OH) airglow image data, Alaska, November 23, 2011
DOI: 10.18739/a2r58r
title: Hydroxyl (OH) airglow image data, Alaska, December 12, 2011
DOI: 10.18739/a2tw0k
title: Hydroxyl (OH) airglow image data, Alaska, November 14, 2011
DOI: 10.18739/a2tw1z
title: Hydroxyl (OH) airglow image data, Alaska, December 19, 2011
DOI: 10.18739/a2w580
title: Hydroxyl (OH) airglow image data, Alaska, December 10, 2011
DOI: 10.20350/digitalcsic/8538
title: Assessment of the National Park network of mainland Spain by the Insecurity Index of vertebrate species

description: Data set of the above mentioned paper. Distribution of 37 vertebrate species and values of environmental variables in each 10 km x 10 km UTM cell of mainland Spain. Codes for the species and for the variables are detailed in Table 1 and Table S1 of the paper, respectively. IDcuad and UTM10 are numerical and text identifiers of the cells. NP details if the cell overlaps with a National Park. Proportion_NP is the proportion of the cell covered by National Parks.
description: Distribution of 37 vertebrate species and values of environmental variables in each 10 km x 10 km UTM cell of mainland Spain.
DOI: 10.21239/v94x60
title: FOTOGRAFIAS: MADS 646/2017 MONITOREO CALIDAD DE AGUAS TOMA MUESTRAS MARINAS
DOI: 10.21239/v98m7h
title: FOTOGRAFIAS: MADS 646/2017 MONITOREO CALIDAD DE AGUAS LABORATORIO- OSTRAS
DOI: 10.21239/v9dd9f
title: FOTOGRAFIAS: MADS 646/2017 MONITOREO CALIDAD DE AGUAS SALIDA DE CAMPO
DOI: 10.21239/v9j43n
title: FOTOGRAFIAS: MADS 646/2017 MONITOREO CALIDAD DE AGUAS CANAL DIQUE - CARTAGENA
DOI: 10.21239/v9nx58
title: FOTOGRAFIAS: MADS 646/2017 MONITOREO CALIDAD AMBIENTAL SALIDA DE CAMPO PLANTA ALCALIS - CARTAGENA
DOI: 10.5063/f1000081
title: Carbon and nitrogen storage in the topsoils of Inceptisols and Mollisols under native sage scrub and non-native grasslands in southern California

description: In southern California, native California sage scrub is increasingly being converted to non-native grasslands, a process known as type conversion. Here we present data that was used to test if type conversion influences C and N storage in surface soil (A horizon). To better understand the factors influencing regional nutrient storage, we examined total C and total N concentration (%) and quantity (g/m2), key soil properties, and microbial abundances and assemblages in sage scrub and non-native grassland habitats at three sites. The three sites were along a coast to inland gradient spanning both Los Angeles and San Bernardino counties. The coastal site was in the Santa Monica Mountains while the most interior site was in the Crafton Hills Conservancy, 155 km east. An intermediate site was the Robert J. Bernard Biological Field Station, located 101 km east of the Santa Monica Mountains and 55 km west of Crafton Hills. To compare total C and N, soil properties, and microbial abundances, we collected soil from six sampling locations in both habitat types at each site in the spring of 2016 (March 25 through April 1). At each sampling location, we collected five different types of soil samples. First, we collected an intact soil clod from the mineral soil surface (immediately below the O horizon) to determine bulk density using a modified version of the clod method—a measure of soil density that excludes rock fragments &gt; 2 mm diameter (description of the method is attached). Second, we gathered ~30 ml of loose soil from the top ~10 cm of the soil profile (all within the A horizon) for analyses of percent C and N using an Elementar vario MICRO cube elemental analyzer (Elementar Mt. Laurel, New Jersey). Third, we collected ~250 mL of soil from the A horizon at each sampling location to send to Earthfort Laboratories (Corvallis, Oregon) to determine total and active bacteria and fungi. Total bacteria and fungi (µg/g) were determined through direct enumeration using microscopy. Bacteria were identified using the fluorescein isothiocyante method. Total fungal biomass was determined by converting width and length measurements. Active bacteria and fungi (µg/g) were quantified using direct microscopy after staining samples with fluorescein diacetate, which binds and fluoresces to metabolically active bacteria and fungi. Fourth, a composite soil sample comprised of soil from all six sampling locations within each habitat at each site was sent to the UC Davis Analytical Laboratory to determine organic matter content, CEC, pH, and soil texture. The final type of sample was 20 mL of loose soil from each sampling location for 16S and ITS amplicon metagenomics analysis, which involves the direct sequencing of the microbiomes in an environmental sample. Molecular data can be found on GenBank.
DOI: 10.18739/a2387h
title: Hydroxyl (OH) airglow image data, Alaska, December 25, 2011
DOI: 10.18739/a2657d
title: Hydroxyl (OH) airglow image data, Alaska, December 24, 2011
DOI: 10.18739/a28c5b
title: Hydroxyl (OH) airglow image data, Alaska, December 31, 2011
DOI: 10.18739/a2bs2z
title: Hydroxyl (OH) airglow image data, Alaska, December 23, 2011
DOI: 10.18739/a2f58z
title: Hydroxyl (OH) airglow image data, Alaska, December 30, 2011
DOI: 10.18739/a2gp3j
title: Hydroxyl (OH) airglow image data, Alaska, December 22, 2011
DOI: 10.18739/a2jg5v
title: Hydroxyl (OH) airglow image data, Alaska, December 29, 2011
DOI: 10.18739/a2kc6h
title: Hydroxyl (OH) airglow image data, Alaska, December 21, 2011
DOI: 10.18739/a2nk4f
title: Hydroxyl (OH) airglow image data, Alaska, December 28, 2011
DOI: 10.18739/a2q58f
title: Hydroxyl (OH) airglow image data, Alaska, December 20, 2011
DOI: 10.18739/a2sc6c
title: Hydroxyl (OH) airglow image data, Alaska, December 27, 2011
DOI: 10.18739/a2z29z
title: Hydroxyl (OH) airglow image data, Alaska, December 26, 2011
DOI: 10.5281/zenodo.1240488
title: Lithosphere removal (delamination) following continental collision: shape and complexity of observables predicted from 3D numerical models

description: Upload contains most essential data files from the manuscript. The raw data amount to several TB and cannot be uploaded. <strong>1 Model data</strong> <em>1.1 Models covered</em> Relatively frequent output is available for the reference model (<em>R</em> in paper, see Table S2), prefixed <em>dp10</em>. Limited output is uploaded for models with geometric variations (<em>OSM -&gt; dp19, TSM-&gt;dp26</em>). <em>1.2 Types of data</em> Most files are visualisation files (ending *.<em>vtr</em>). These are intended for loading into the visualisation software Paraview. Files starting with <em>comp_</em> contain the lithological composition field; other visualisation files hold the fields of selected physical parameters. Note that as of the design of the study, the maximum file size allowed for loading into Paraview is ca. 2 GB. This limits the number of fields available according to model size - larger models (geometrical variations) hold therefore less fields. Binary files with ending *.<em>prn</em> are saved model states, from which programs can be rerun. Time information mapping step numbers to years is provided in <em>times...txt</em>. <strong>2 Software for reproduction</strong> The numerical code is not in the public domain, and its use is restricted. A pre-compiled binary is provided and allows reproduction of the main/reference model. We present the input files; however, these cannot be changed freely (equivalent to software distribution), and changes will lead to termination of the program. <em>2.1 Requirements, preparation and use</em> The code is compiled on CentOS with gcc 4.8.2. There is no library dependency, apart from the intrinsic OpenMP and glibc (&gt;= 2.17). The following requirements <em>must</em> be satisfied in order to run it: Linux OS (tested on CentOS and Fedora) &gt; 160 GB shared memory The following provisions are recommended: 16 cores high bandwidth storage storage space <em>O</em>(TB) To prepare, simply unzip the provided snapshot <em>clsd_reproduce_gcc_CentOS.zip</em> in an appropriate directory (cluster). The input file <em>init.t3c</em> sets the initial conditions; the input file <em>mode.t3c </em>controls solver and file output. <em>file.t3c</em> is the pointer to the last output step; if a model snapshot is available as binary dump (*.prn file), setting the pointer to its number allows restarting. For normal usage, create initial condition with executable <em>in3mg</em>, and subsequently run <em>i3mg</em>. This will create snapshots and *.vtr visualisation files. High-performance computing facilities, runtime (months), proper software environment, and training in use of the code, or in the use of the visualisation software, are not provided.
DOI: 10.5281/zenodo.1240489
title: Lithosphere removal (delamination) following continental collision: shape and complexity of observables predicted from 3D numerical models

description: Upload contains most essential data files from the manuscript. The raw data amount to several TB and cannot be uploaded. <strong>1 Model data</strong> <em>1.1 Models covered</em> Relatively frequent output is available for the reference model (<em>R</em> in paper, see Table S2), prefixed <em>dp10</em>. Limited output is uploaded for models with geometric variations (<em>OSM -&gt; dp19, TSM-&gt;dp26</em>). <em>1.2 Types of data</em> Most files are visualisation files (ending *.<em>vtr</em>). These are intended for loading into the visualisation software Paraview. Files starting with <em>comp_</em> contain the lithological composition field; other visualisation files hold the fields of selected physical parameters. Note that as of the design of the study, the maximum file size allowed for loading into Paraview is ca. 2 GB. This limits the number of fields available according to model size - larger models (geometrical variations) hold therefore less fields. Binary files with ending *.<em>prn</em> are saved model states, from which programs can be rerun. Time information mapping step numbers to years is provided in <em>times...txt</em>. <strong>2 Software for reproduction</strong> The numerical code is not in the public domain, and its use is restricted. A pre-compiled binary is provided and allows reproduction of the main/reference model. We present the input files; however, these cannot be changed freely (equivalent to software distribution), and changes will lead to termination of the program. <em>2.1 Requirements, preparation and use</em> The code is compiled on CentOS with gcc 4.8.2. There is no library dependency, apart from the intrinsic OpenMP and glibc (&gt;= 2.17). The following requirements <em>must</em> be satisfied in order to run it: Linux OS (tested on CentOS and Fedora) &gt; 160 GB shared memory The following provisions are recommended: 16 cores high bandwidth storage storage space <em>O</em>(TB) To prepare, simply unzip the provided snapshot <em>clsd_reproduce_gcc_CentOS.zip</em> in an appropriate directory (cluster). The input file <em>init.t3c</em> sets the initial conditions; the input file <em>mode.t3c </em>controls solver and file output. <em>file.t3c</em> is the pointer to the last output step; if a model snapshot is available as binary dump (*.prn file), setting the pointer to its number allows restarting. For normal usage, create initial condition with executable <em>in3mg</em>, and subsequently run <em>i3mg</em>. This will create snapshots and *.vtr visualisation files. High-performance computing facilities, runtime (months), proper software environment, and training in use of the code, or in the use of the visualisation software, are not provided.
DOI: 10.18141/1436857
title: Computed Tomography Scanning and Geophysical Measurements of the Marcellus Formation from the Nathan Goff #55 Well

description: UCR TRS
DOI: 10.18141/1436877
title: Computed Tomography Scanning and Geophysical Measurements of the Marcellus Formation from the Dunham Pad A 4H Well

description: UCR TRS
DOI: 10.18739/a2057cr7b
title: BeringFall2013_video_BeringFlight
DOI: 10.18739/a2154dn7k
title: Active Layer ARCSS grid Atqasuk, Alaska 2014
DOI: 10.18739/a23x83k1s
title: BeringFall2013_laser_BeringFlight
DOI: 10.18739/a24x54g11
title: Bering2011_laser_Flight1
DOI: 10.18739/a26294
title: Hydroxyl (OH) airglow image data, Alaska, December 2, 2011
DOI: 10.18739/a28c6q
title: Arctic Chamber Metadata, 2000-2018
DOI: 10.18739/a2cc0ts6h
title: BeringFall2012_video_BeringFlight
DOI: 10.18739/a2h41jm08
title: Active Layer ARCSS grid Atqasuk, Alaska 2015
DOI: 10.18739/a2mw28d43
title: BeringFall2012_laser_BeringFlight
DOI: 10.18739/a2q00p
title: Arctic Ocean Acidification-Bering Strait Time Series
DOI: 10.18739/a2rn30687
title: Bering2011_video_Flight1
DOI: 10.18739/a2v579
title: Arctic Ocean Acidification-Bering Strait Time Series
DOI: 10.18739/a2v58p
title: Bering2011_laser_Flight2
DOI: 10.18739/a2vd6p42c
title: BeringSummer2012_laser_BeringFlight
DOI: 10.5063/f189141h
title: Areas of occupancy (AOO) and fractal dimensions of Finnish butterflies

description: This dataset comprises the areas of occupancy (AOO) of Finnish butterflies (n = 97) across three spatial scales (10 km, 50 km, 100 km) as well as values of the fractal dimension (D) calculated by using scale-area curves fitted for each butterfly species across the three spatial scales mentioned above. The dataset also includes values of the range shift observed in Finnish butterflies between 1992-96 and 2000-04, classification of butterfly species according to their distributional pattern and long-term population trend and main breeding habitat of the butterfly species. The dataset represents the main data used in the paper by PÃ¶yry et al. (2018) in Diversity and Distributions.
DOI: 10.5063/f1d21vrf
title: Areas of occupancy (AOO) and fractal dimensions of Finnish butterflies

description: This dataset comprises the areas of occupancy (AOO) of Finnish butterflies (n = 97) across three spatial scales (10 km, 50 km, 100 km) as well as values of the fractal dimension (D) calculated by using scale-area curves fitted for each butterfly species across the three spatial scales mentioned above. The dataset also includes values of the range shift observed in Finnish butterflies between 1992-96 and 2000-04, classification of butterfly species according to their distributional pattern and long-term population trend and main breeding habitat of the butterfly species. The dataset represents the main data used in the paper by PÃ¶yry et al. (2018) in Diversity and Distributions.
DOI: 10.14469/hpc/4154
title: HDA-2+4 mechanism, Reactant, p=Me -847.328552

description: Gaussian Calculation
DOI: 10.14469/hpc/4153
title: HDA-2+4 mechanism, Reactant, trans + HCl, p=Me -1308.192300

description: Gaussian Calculation
DOI: 10.14469/hpc/4156
title: HDA-2+4 mechanism,TS2, cis + HCl, p=OMe, IRC

description: Gaussian 16 calculation
DOI: 10.14469/hpc/4157
title: HDA-2+4 mechanism,TS2, cis + HCl, p=OMe, IRC

description: Gaussian 16 calculation
DOI: 10.14469/hpc/4158
title: HDA-2+4 mechanism,TS2, cis + HCl, p=OMe, IRC

description: Gaussian 16 calculation
DOI: 10.14469/hpc/4162
title: HDA-2+4 mechanism,TS2, cis + HCl, p=OMe IRC

description: Gaussian Calculation
DOI: 10.14469/hpc/4163
title: HDA-2+4 mechanism, TS2, trans + HCl, p=Me -1308.176306

description: Gaussian Calculation
DOI: 10.14469/hpc/4164
title: HDA-2+4 mechanism, TS2, trans + HCl, p=NH2 + H2O, Def2-TZVPPD -1400.715725

description: Gaussian Calculation
DOI: 10.5281/zenodo.781806
title: Occurrence data on Pyrrolizidine Alkaloids (PAs) in food

description: The dataset contains data on the occurrence of Pyrrolizidine Alkaloids (PAs) in food products of plant origin, in particular herbal teas and food supplements from different geographic regions in Europe. A total of 359 samples were collected in years 2014 and 2015 and analysed for the presence of 28 PAs. Samples were collected in supermarkets, retail shops and for a small proportion via internet. The samples comprised 168 teas (including black, green, rooibos, chamomile, peppermint and mixed herbal tea) and 191 food supplements. The analytical method for determination of 1,2-unsaturated PAs is based on liquid chromatography combined with tandem mass spectrometry (LC-MS/MS), which complies with the requirements as described by the Commission regulation No. 401/2006. The updates in version 2 mainly refer to the analytical methods and the limits of quantification reported for the analysis of pyrrolizidine alkaloids in different food samples, and to some plant extracts for which wrong levels of pyrrolizidine alkaloids were reported by a data provider.
description: EU; XLSX; data.collection@efsa.europa.eu
DOI: 10.18739/a26q1sg5v
title: Active Layer ARCSS grid Barrow, Alaska 2014
DOI: 10.18739/a2bg2h890
title: Siberian boreal forest energy balance (ViPER project), Cherskiy, Sakha Republic, Russia, 2016 - 2017
DOI: 10.18739/a2kw57h4v
title: Yukon-Kuskokwim Delta fire: soil and permafrost carbon, nitrogen, horizons, and ice structure, Alaska, 2016
DOI: 10.18739/a2qn5z98m
title: BeringSummer2012_video_BeringFlight
DOI: 10.18739/a2z60c16t
title: Active Layer ARCSS grid Barrow, Alaska 2014
DOI: 10.18739/a22z12p13
title: Active Layer ARCSS grid Barrow, Alaska 2014
DOI: 10.18739/a2f76663h
title: Active Layer NIMS Barrow, Alaska 2014
DOI: 10.18739/a2td9n724
title: Active Layer ARCSS grid Barrow, Alaska 2015
DOI: 10.5281/zenodo.1245180
title: TUT Urban Acoustic Scenes 2018, Leaderboard dataset

description: TUT Urban Acoustic Scenes 2018, Leaderboard dataset consists of 10-seconds audio segments from 10 acoustic scenes: Airport - <em>airport</em> Indoor shopping mall - <em>shopping_mall</em> Metro station - <em>metro_station</em> Pedestrian street - <em>street_pedestrian</em> Public square - <em>public_square</em> Street with medium level of traffic - <em>street_traffic</em> Travelling by a tram - <em>tram</em> Travelling by a bus - <em>bus</em> Travelling by an underground metro - <em>metro</em> Urban park - <em>park</em>
DOI: 10.5281/zenodo.1245181
title: TUT Urban Acoustic Scenes 2018, Leaderboard dataset

description: TUT Urban Acoustic Scenes 2018, Leaderboard dataset consists of 10-seconds audio segments from 10 acoustic scenes: Airport - <em>airport</em> Indoor shopping mall - <em>shopping_mall</em> Metro station - <em>metro_station</em> Pedestrian street - <em>street_pedestrian</em> Public square - <em>public_square</em> Street with medium level of traffic - <em>street_traffic</em> Travelling by a tram - <em>tram</em> Travelling by a bus - <em>bus</em> Travelling by an underground metro - <em>metro</em> Urban park - <em>park</em>
DOI: 10.5281/zenodo.1245183
title: TUT Urban Acoustic Scenes 2018 Mobile, Leaderboard dataset

description: TUT Urban Acoustic Scenes 2018 Mobile, Leaderboard dataset consists of 10-seconds audio segments from 10 acoustic scenes: Airport - <em>airport</em> Indoor shopping mall - <em>shopping_mall</em> Metro station - <em>metro_station</em> Pedestrian street - <em>street_pedestrian</em> Public square - <em>public_square</em> Street with medium level of traffic - <em>street_traffic</em> Travelling by a tram - <em>tram</em> Travelling by a bus - <em>bus</em> Travelling by an underground metro - <em>metro</em> Urban park - <em>park</em>
DOI: 10.5281/zenodo.1245184
title: TUT Urban Acoustic Scenes 2018 Mobile, Leaderboard dataset

description: TUT Urban Acoustic Scenes 2018 Mobile, Leaderboard dataset consists of 10-seconds audio segments from 10 acoustic scenes: Airport - <em>airport</em> Indoor shopping mall - <em>shopping_mall</em> Metro station - <em>metro_station</em> Pedestrian street - <em>street_pedestrian</em> Public square - <em>public_square</em> Street with medium level of traffic - <em>street_traffic</em> Travelling by a tram - <em>tram</em> Travelling by a bus - <em>bus</em> Travelling by an underground metro - <em>metro</em> Urban park - <em>park</em>
DOI: 10.4119/unibi/2919795
title: Supplementary Data for the Paper entitled ''An Analytical Study of Time of Flight Error Estimation in Two-Way Ranging Methods''

description: The contents of this publication are intended for providing additional supplementary materials, i.e. proofs of formula derivations, presented in our paper entitled "An Analytical Study of Time of Flight Error Estimation in Two-Way Ranging Methods". The mentioned paper was submitted to ``Ninth International Conference on Indoor Positioning and Indoor Navigation (IPIN) 2018}'', which will be held in Nantes, France on September 24-27, 2018.
DOI: 10.4225/08/5afaa66cbee44
title: 9s climatology for continental Australia 2036-2065: CAN ESM 2 rcp 4.5 : Summary variables with elevation and radiative adjustment

description: A suite of 9s resolution climate surfaces for the Australian continent, with adjustment for the radiative effects of terrain. This collection represents a 30 year average centred on 2050 for the CAN ESM2 circulation model under RCP 4.5. Projected future climates were generated by applying within-model changes (e.g. CAN ESM2 2036-2065 –CAN ESM2 (1976-2005) calculated at the native general circulation model grid resolution to these current surfaces, using ANUCLIM 6.1 prior to radiative adjustment. Precipitation, temperature, evaporation and water balance data are presented as annual means or totals and maximum and minimum monthly values. Data are provided as zipped ESRI float grids: Binary float grids (*.flt) with associated ESRI header files (*.hdr) and projection files (*.prj). After extracting from the zip archive, these files can be imported into most GIS software packages, and can be used as other binary file formats by substituting the appropriate header file. Additionally a short methods summary is provided in the file 9sClimateMethodsSummary.pdf for further information, including a nomenclature for files.