cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.13369534
title: Datasæt & Bilag ifm. Speciale i Arkæologi, 2024

description: Datasæt & Bilag ifm. Speciale i Arkæologi, 2024.

Bilagene indeholder oplysninger vedrørende Hellekiste fra Langeland.
DOI: 10.15468/dl.q4d6g2
title: Occurrence Download

description: A dataset containing 29824 species occurrences available in GBIF matching the query:
{
 "and" : [
 {
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 }
 ]
 },
 "SpeciesKey is Leptinotarsa decemlineata (Say, 1824)",
 "Year is greater than or equal to 2004",
 "Year is less than or equal to 2023"
 ]
}

 The dataset includes 29824 records from 222 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0084107-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.21227/09en-qt48
title: 4- and 2- inch PM dataset and one 20_6 million LUT

description: The 4-inch and 2-inch dataset are generated using random mover poses with single square coils. The sample sizes are 8 million and 9.6 million for the 4-inch and 2-inch datasets, respectively. The input and label data are min-max normalized to range between zero and one. The 20.6 million dataset file is created using the same wrench model (GT model), which has infeasible mover poses. The infeasible mover poses are scruntinized for the 4-inch and 2-inch dataset to make sure the PM is above the top surface of the coil. The wrench results for the infeasible locations produced large results due to zero-divide-zero operation. The issue are fixed using another numerical method which is slower than the GT used in the study.
DOI: 10.6073/pasta/3fd0b125bc733bbb48dc98c34a4b535e
title: MCR LTER: Coral Reef: Modeling the effects of selectively fishing key functional groups of herbivores on coral resilience; data for Cook et al., 2023 Ecosphere

description: These data and code were generated in support of the manuscript: Cook DT, Schmitt RJ, Holbrook SJ, and HV Moeller, Ecosphere. 
 To investigate the impacts of selectively harvesting functional groups of herbivorous fishes on coral resilience, we used a dynamic model that is grounded by the coral reef system in Moorea, French Polynesia. Our model simulates the fraction of a reef occupied through time by classes of key benthic spaceholders (coral, two stages of macroalgae, and turf). Benthic and fishing dynamics are linked through the harvesting of two functional groups of herbivorous fishes. We utilize data collected on the abundance of fishes on the reef and in the catch in Moorea, French Polynesia to inform our model and to empirically explore patterns of fishing selectivity.
 These data and code were published in Ecosphere and were a part of the thesis of D. Cook (2023).
 This manuscript uses data collected by the U.S. National Science Foundation's (NSF) Moorea Coral Reef Long Term Ecological Research (MCR LTER) site under Grant No. OCE 2224354 (and earlier awards). Additional financial support to the MCR LTER site was provided through a generous gift from the Gordon and Betty Moore Foundation. Research was completed under permits issued by the French Polynesian Government (Délégation à la Recherche) and the Haut-commissariat de la République en Polynésie Francaise (DTRT) (Protocole d'Accueil 2005-2023).
DOI: 10.6073/pasta/c93d87c2000715eaa2f70d079965c6a5
title: Results of semantic queries for "carbon cycling" for datasets in the DataONE catalog

description: DataONE (https://www.dataone.org) is a federation of institutions involved with the
 earth and environmental sciences that share data through common cyberinfrastructure. In
 2016, the DataONE project carried out a quantification of the utility of semantic query, by
 measuring the precision and recall of relevant datasets available through that catalog.
 Precision is defined as the proportion of relevant data in the retrieved results, and recall
 is the proportion of relevant data retrieved, compared to all relevant data present in the
 repository (see Methods). 
 
 This dataset contains the queries and results of that study. Four data tables are
 included. First, a table of the 10 queries, which were formatted in several ways, including
 natural language and text strings (for plain text searches of various parts of metadata),
 and URIs for measurements in the EcoSystem Ontology (ECSO). A second table contains 994
 relevant datasets in the DataONE catalog, with a column for each of the ten queries and
 boolean value indicating whether the dataset is a match for that query. Two query results
 tables are included, for the raw and summarized results of the query tests. A fifth entity
 contains the zipped code (R language) used to perform the queries in the DataONE
 system.
 
 When run against approximately 1000 datasets (in October, 2016), results for the ten
 queries ranged from 0-50% (precision) and 0-100% (recall), indicating that traditional
 searches may sometimes be adequate to return all relevant data in a corpus, but results can
 be erratic and inconsistent, with potentially large returns of irrelevant data in the result
 set. When querying through semantic classes, precision and recall were much higher and more
 consistent (90-100% and 75-100%, respectively).
DOI: 10.17615/0k14-0s57
title: raw data for Cells

description: Data for Figures
DOI: 10.6073/pasta/6d421e346ebb9728ade7182c90d2d3ca
title: Prieta streams- Discharge and water level

description: This is a long-term monitoring of water discharge and water level at Prieta Stream. The monitoring point is located at Pool 0: which is the same location where we sample stream chemistry. Measurements are taken automatically with a pressure transducer: every 15 minutes. Measure are originally of pressure: which are translated to water level using the reference gauge. Using an equation provided by Dr. Fred Scatena: water level is converted into discharge. Stage height to discharge equation created by Fred N Scatena used from 2006 to 3-26-2013 10 AM: discharge (m3/sec) = 1.095 - 1.585 * stage + 0.578 * stage * stage Stage height to discharge equation created by William H McDowell and Jody Potter used from 3-26-2013 10:15 to present: discharge (m3/sec) = 0.0005*((stage)^8.8846)*35.314666
DOI: 10.6073/pasta/a2b8170a06c5d90978fd9b5225c50a64
title: StreamFRE: Downstream leaf litter exports in Prieta and lateral and vertical leaf litter inputs.
DOI: 10.6073/pasta/4aa99fc65d36596704f925cbb2e15434
title: StreamFRE: Pool area and depth in Prieta Streams

description: Measurements of pool depth in Prieta Stream, as part of the Stream Flow Reduction Experiment (StreamFRE). StreamFRE started in October 2016 with the goal of assessing the effects of droughts on stream ecosystems. The project is designed to assess the effect of flow reduction, the main effect of drought on streams. We collected pre-manipulation data from October 2016 to September 2017, when Hurricanes Irma and Maria hit Puerto Rico. Due to hurricane disturbances, the project became a hurricane impact assessment from September 2017 to early 2022, when the flow reduction is scheduled to start. Each month we measured pool depth by taking 5 random measurements through each of the pools. Values are recorded in cm and reported as average and variability in pool depth. Pool depths measures are collected the same day Decapod are sampled and pictures are taken to determine the pool surface area. 
 Pool depth:
 Each month we measured pool depth by taking 5 random measurements through each of the pools. Values are recorded in cm and reported as average and variability in pool depth. Pool depths measures are collected the same day Decapod are sampled and pictures are taken to determine the pool surface area.
DOI: 10.5281/zenodo.10614549
title: Code with Dataset
DOI: 10.5281/zenodo.10614550
title: Code with Dataset
DOI: 10.6073/pasta/fcbe4dccff85f650496f90bc2889dba7
title: StreamFRE-Shrimp assemblages in Prieta Stream
DOI: 10.6073/pasta/62d2f4bf0eb4753d5266d9c7764702a8
title: StreamFRE: Canopy cover over Prieta stream

description: Measurements of canopy cover over Prieta Stream, as part of the Stream Flow Reduction Experiment (StreamFRE). Background: StreamFRE started in October 2016 with the goal of assessing the effects of droughts on stream ecosystems. The project is designed to assess the effect of flow reduction, the main effect of droughts on streams. We collected pre-manipulation data from October 2016 to September 2017, when Hurricanes Irma and Maria hit Puerto Rico. The project became a hurricane impact assessment from September 2017 to early 2021, when the flow reduction is scheduled to start. Since pools and riffles are always the same, measurements allow to assess changes in canopy over time and in response to experimental and natural disturbances.
DOI: 10.6073/pasta/27b067eb7fcae65c8a4237a408f4d1c6
title: Groundwater, soil moisture and weather data in Brownsville forest, Nassawadox, VA, 2019-2021

description: This dataset includes groundwater, soil moisture and weather data collected in six study sites in the Brownsville forested area (VA). In particular, sites H5 and H7 characterize the high forest where healthy Pinus taeda dominate, sites L1 and L6 characterize the low forest, where barren or dead Pinus taeda are present and sites M1 and M2 characterize the medium forest, representing transition between high and low forest. Data collection, started in January 2019, is done for VCR-LTER and CCZN (Coastal Critical Zone Network) long term projects. CTD-Diver are used to measure groundwater pressure, specific conductance and temperature. They hang from a cable in six wells, one for each study site. Water pressure is compensated using barometric pressure data collected by the weather station nearby. Water levels are georeferenced to NAVD 88. One soil moisture sensor for each site is placed 7-10 cm below the ground surface to detect water content, specific conductance and temperature of the first soil layer. A weather station is installed in M1 to collect solar, wind, precipitation and atmospheric pressure data. 
 Groundwater and soil moisture are in VCR22344_1, weather data are in VCR22344_2, and locations of sites and instruments are in VCR22344_3.
 This material is based upon work supported by the National Science Foundation under Grant No. 2012322, Collaborative Research: Network Cluster: The Coastal Critical Zone: Processes that transform landscapes and fluxes between land and sea.
DOI: 10.6073/pasta/a7de61660e2fa73ce1899200cc64744b
title: Forest Transition Experiment - Vegetation Monitoring on a Coastal Virginia Forest, 2019-2022

description: This dataset contains data on vegetation (shrubs, trees, non-woody vegetation, seedlings and Phragmites occurrence in permanent plots at the Brownsville Forest near Nassawadox, VA.
DOI: 10.6073/pasta/859252320b7300eb78215663820f8466
title: Comparison of high-marsh and ghost-forest invertebrates in Virginia, 2020

description: This dataset includes data on two invertebrates (Orchestia grillus and Pardosa littoralis) found in a coastal marsh in Virginia, and in the associated "ghost forest." It includes information on the locations (Table 1); information on the composition of the habitat where they were found (Table 2); plant biomass, including detritus (Table 3); size of invertebrates (Table 4); Carbon, Nitrogen and Sulphur stable isotope levels in invertebrate tissues and food plants (Table 5); and macroinfauna (Table 6).
DOI: 10.6073/pasta/234adaf63d9de7601c0feb84271f0022
title: Invertebrates in a retreating coastal forest near Nassawadox, VA , 2019-2020

description: Sampling was conducted on the Eastern Shore of Virginia at Brownsville Preserve, part of the Virginia Coast Reserve LTER and adjacent to Upper Phillips Creek (37.463, -75.835). Plots were established in five zones along the forest-to-salt marsh gradient based on vegetation communities and seedling recruitment. The high forest (HF) is characterized by both coniferous and deciduous tree species, with maximum seedling recruitment. The mid forest (MF) contains primarily coniferous trees and shrubs and shows reduced seedling recruitment. The low forest (LF) canopy shows partial mortality due to salt stress and no tree recruitment; the understory contains primarily invasive (Phragmites australis) but also salt marsh (Spartina patens, Distichlis spicata) plant species. The transition zone (TZ) contains mostly dead mature trees, with its understory dominated by S. patens, D. spicata, and P. australis. The high marsh (HM) does not contain trees and is dominated by S. patens and D. spicata. 
 2019 data was collected September 16-18, 2019. 2020 data was collected September 8-9, 2020.
DOI: 10.5281/zenodo.10614535
title: DeepSLICEM: Clustering CryoEM particles using deep image and similarity graph representations: Experiment Data

description: Details of experiments are given in the paper, titled 'DeepSLICEM: Clustering CryoEM particles using deep image and similarity graph representations'.

Supporting code is available on GitHub at: https://github.com/marcottelab/2D_projection_clustering/

Details of the data are given below:

Folder CryoEM_data contains 6 datasets - one experimental, and 5 synthetic with 2D projection images of CryoEM particles, common-lines based similarity graph of the images, and ground truth clusters of the images corresponding to the same particles.

Folder DeepSLICEM_graph_node_embeddings contains graph node embeddings of the common-lines based similarity graph of the 2D projection images for each of the 6 datasets.

Folder DeepSLICEM_clustering_results contains algorithm predicted clusters of 2D projection images belonging to the same particles in each of the 6 datasets, along with the embeddings used for clustering, such as combined image and graph node embeddings.

Folder DeepSLICEM_siamese_neural_network_models contains models trained to obtain fine-tuned embeddings of 2D projection images based on similarity w.r.t the same particle's projections.
DOI: 10.5281/zenodo.10614536
title: DeepSLICEM: Clustering CryoEM particles using deep image and similarity graph representations: Experiment Data

description: Details of experiments are given in the paper, titled 'DeepSLICEM: Clustering CryoEM particles using deep image and similarity graph representations'.

Supporting code is available on GitHub at: https://github.com/marcottelab/2D_projection_clustering/

Details of the data are given below:

Folder CryoEM_data contains 6 datasets - one experimental, and 5 synthetic with 2D projection images of CryoEM particles, common-lines based similarity graph of the images, and ground truth clusters of the images corresponding to the same particles.

Folder DeepSLICEM_graph_node_embeddings contains graph node embeddings of the common-lines based similarity graph of the 2D projection images for each of the 6 datasets.

Folder DeepSLICEM_clustering_results contains algorithm predicted clusters of 2D projection images belonging to the same particles in each of the 6 datasets, along with the embeddings used for clustering, such as combined image and graph node embeddings.

Folder DeepSLICEM_siamese_neural_network_models contains models trained to obtain fine-tuned embeddings of 2D projection images based on similarity w.r.t the same particle's projections.
DOI: 10.5281/zenodo.10614581
title: Esophagogastroduodenoscopy Versus Thoracic Computed Tomography in Prediction of Caustic Stricture

description: The raw data, case record form, and participant information sheet of study "Esophagogastroduodenoscopy Versus Thoracic Computed Tomography in Prediction of Caustic Stricture".
DOI: 10.5281/zenodo.10614582
title: Esophagogastroduodenoscopy Versus Thoracic Computed Tomography in Prediction of Caustic Stricture

description: The raw data, case record form, and participant information sheet of study "Esophagogastroduodenoscopy Versus Thoracic Computed Tomography in Prediction of Caustic Stricture".
DOI: 10.15151/esrf-es-1413550204
title: ITABAG: 3D structures of macromolecules related to human health

description: The ITABAG includes structural biologists from Universities, the National Research Council and Hospital research centres in Italy. The laboratories take
advantage of single crystal and small angle X-ray diffraction methods to study the structure-function relationships in various macromolecules. A unifying factor for
the vast majority of the macromolecules under study is that they are related to human health, either directly, being human proteins involved in some disease, or
indirectly, as proteins expressed by human pathogens and validated as potential pharmacological targets. Other projects investigate basic chemical processes,
such as crystal growth, or aim at characterising macromolecules with potential biotechnological applications.
DOI: 10.15151/esrf-es-1432682476
title: IBS BAG

description: The IBS BAG includes in this proposal IBS teams and external groups from CEA-Cadarache (St Paul lez Durance) and IRBA (Brétigny-sur-Orge). We study structure-function relationships of proteins emphasizing in human health, biotechnology and methodology. Most of the projects are a continuation of the MX-2398 proposal and can be grouped into different topics as follows: host-pathogen interaction, new drug targets, fundamental cellular mechanisms, membrane proteins, biotechnological applications and methodology. Some of these projects use integrative approaches (X-ray crystallography, SAXS, NMR (and cryo-EM), together with other biophysical studies) with the aim to fully understand the complexity of the biological macromolecular systems on study.
DOI: 10.15151/esrf-es-1432598515
title: A microfocus / electrodynamic levitation study of a model system for respiratory aerosol droplets: effect of lung surfactant DPPC on salt b

description: We will study electrodynamically levitated droplets of a model respiratory aerosol containing the lung surfactant DPPC and salts, using microfocus SAXS/WAXS in a controlled humidity cell. We will explore the impact of the surfactant self-assembly on salt crystallisation as the droplets lose water and equilibrate with their environment. Our findings will help understand the effect of aerosol microenvironment on virus stability in exhaled droplets, which impacts on transmission of airborne diseases.
DOI: 10.15151/esrf-es-1432402110
title: Investigating Drug Encapsulation in Hierarchical Vaterite Particles Using Coherent X-ray Diffraction Imaging

description: Mineral particles are amongst the most commonly used drug delivery vehicles for cost-effective, biocompatible and biodegradable drug delivery solutions. The vaterite form of CaCO3 has emerged as an ideal system due to its structural versatility, biocompatibility, mechanical stability and pH responsive biodegradability. Depending on synthesis procedures and nature of the vaterite-drug pair, different modes of drug-mineral interactions might be considered, and the physical storage environment provided by the mesoporous vaterite host can result in significant variations in the loading capacity, release profile and preservation potential of the pharmaceutical agents. To achieve a comprehensive understanding of particle and drug interaction, the unique non-destructive 3D imaging of CXDI will be utilized. With an expected resolution of &lt; 20 nm the study will provide new understanding of how nano-sized grains of the bioactive components are located within the porous matrix of vaterite.
DOI: 10.15151/esrf-es-1432053649
title: In situ and operando coherent diffraction imaging of nanostructures during chemical reactions: towards atomic resolution and time-resolved e
DOI: 10.5281/zenodo.10614485
title: Supporting information to Fungal Community Diversity and Their Contribution to Nitrogen Cycling in In-Situ Aerated Landfills: Insights from Field and Laboratory Studies

description: Metagenomic sequencing data.
DOI: 10.5281/zenodo.10614486
title: Supporting information to Fungal Community Diversity and Their Contribution to Nitrogen Cycling in In-Situ Aerated Landfills: Insights from Field and Laboratory Studies

description: Metagenomic sequencing data.
DOI: 10.5517/ccdc.csd.cc275gsp
title: CCDC 2060842: Experimental Crystal Structure Determination

description: Related Article: Dmitry K. Sinitsa, Taisiya S. Sukhikh, Sergey N. Konchenko, Nikolay A. Pushkarevsky|2024|Organometallics|43|94|doi:10.1021/acs.organomet.3c00427
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: 10.5517/ccdc.csd.cc275gtq
title: CCDC 2060843: Experimental Crystal Structure Determination

description: Related Article: Dmitry K. Sinitsa, Taisiya S. Sukhikh, Sergey N. Konchenko, Nikolay A. Pushkarevsky|2024|Organometallics|43|94|doi:10.1021/acs.organomet.3c00427
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: 10.5517/ccdc.csd.cc275gvr
title: CCDC 2060844: Experimental Crystal Structure Determination

description: Related Article: Dmitry K. Sinitsa, Taisiya S. Sukhikh, Sergey N. Konchenko, Nikolay A. Pushkarevsky|2024|Organometallics|43|94|doi:10.1021/acs.organomet.3c00427
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: 10.5517/ccdc.csd.cc275gws
title: CCDC 2060845: Experimental Crystal Structure Determination

description: Related Article: Dmitry K. Sinitsa, Taisiya S. Sukhikh, Sergey N. Konchenko, Nikolay A. Pushkarevsky|2024|Organometallics|43|94|doi:10.1021/acs.organomet.3c00427
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: 10.5517/ccdc.csd.cc275gxt
title: CCDC 2060846: Experimental Crystal Structure Determination

description: Related Article: Dmitry K. Sinitsa, Taisiya S. Sukhikh, Sergey N. Konchenko, Nikolay A. Pushkarevsky|2024|Organometallics|43|94|doi:10.1021/acs.organomet.3c00427
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: 10.5517/ccdc.csd.cc275gyv
title: CCDC 2060847: Experimental Crystal Structure Determination

description: Related Article: Dmitry K. Sinitsa, Taisiya S. Sukhikh, Sergey N. Konchenko, Nikolay A. Pushkarevsky|2024|Organometallics|43|94|doi:10.1021/acs.organomet.3c00427
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.