cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.21258/1424586
title: Schweizerisches Landesforstinventar - Ergebnistabelle Nr. 892004
DOI: 10.21258/1423792
title: Schweizerisches Landesforstinventar - Ergebnistabelle Nr. 891745
DOI: 10.21258/1383891
title: Schweizerisches Landesforstinventar - Ergebnistabelle Nr. 899663
DOI: 10.21258/1384158
title: Schweizerisches Landesforstinventar - Ergebnistabelle Nr. 898780
DOI: 10.21258/1423852
title: Schweizerisches Landesforstinventar - Ergebnistabelle Nr. 891665
DOI: 10.21258/1383858
title: Schweizerisches Landesforstinventar - Ergebnistabelle Nr. 899305
DOI: 10.21258/1384255
title: Schweizerisches Landesforstinventar - Ergebnistabelle Nr. 897387
DOI: 10.21258/1423840
title: Schweizerisches Landesforstinventar - Ergebnistabelle Nr. 891681
DOI: 10.21258/1425591
title: Schweizerisches Landesforstinventar - Ergebnistabelle Nr. 891878
DOI: 10.21258/1413094
title: Schweizerisches Landesforstinventar - Ergebnistabelle Nr. 897834
DOI: 10.21258/1384194
title: Schweizerisches Landesforstinventar - Ergebnistabelle Nr. 898904
DOI: 10.21258/1384240
title: Schweizerisches Landesforstinventar - Ergebnistabelle Nr. 899104
DOI: 10.21258/1384138
title: Schweizerisches Landesforstinventar - Ergebnistabelle Nr. 898678
DOI: 10.21258/1421863
title: Schweizerisches Landesforstinventar - Ergebnistabelle Nr. 892959
DOI: 10.21258/1431618
title: Schweizerisches Landesforstinventar - Ergebnistabelle Nr. 902167
DOI: 10.5281/zenodo.4307700
title: Data and code for comparison of different machine learning methods and dimensionality reduction for classification astrocytoma and glioblastoma tissues by mass spectra

description: This upload contains all replication material for "Comparison of different machine learning methods and dimensionality reduction for classification astrocytoma and glioblastoma tissues by mass spectra" (forthcoming). <strong>Authors:</strong> E.S. Zhvansky, A.A. Sorokin, V.A. Shurkhay, V.A. Eliferov, D.S. Bormotov, D.G. Ivanov, D.S. Zavorotnyuk, A.A. Potapov. <strong>Code and data are located within data_and_code.zip.</strong> Code is written in Python 3.7.7 using Jupyter Notebook, MATLAB R2019b, and Python 3.5.2. Please find the readme.txt for code using and the code to replicate the main findings of the paper described below: venn_diagramm.py for Venn diagram figures. SSM.m for SSM calculation and visualization. DR_ML.ipynb for dimensionality reduction and machine learning algorithms comparing on the datasets.
DOI: 10.5441/001/1.4q2t4fn8/1
title: Feral horse (Equus ferus caballus) Wyoming_Colorado USA

description: Hennig JD, Scasta JD, Pratt AC, Wanner CP, Beck JL. 2022. Habitat selection and space use overlap between feral horses, pronghorn, and greater sage-grouse in cold arid steppe. J Wildlife Manage. e22329. doi:10.1002/jwmg.22329
description: Populations of feral horses (Equus ferus caballus) in the western United States have increased during the past decade, consequently affecting co-occurring wildlife habitat. Feral horses may influence 2 native wildlife species, greater sage-grouse (Centrocercus urophasianus; sage-grouse) and pronghorn (Antilocapra americana) through mechanisms of habitat alteration and competition. Wyoming, USA, contains the largest populations of pronghorn and sage-grouse of any state and also has the highest degree of range overlap between feral horses and these species. Consequently, the effects that horses may have on pronghorn and sage-grouse populations in Wyoming have implications at local, state, and population-wide levels. Managers need information concerning habitat selection and space use overlap among these species to develop appropriate management strategies; yet this information is absent for most feral horse management areas. To address this knowledge need, we attached global positioning system (GPS) transmitters to horses, pronghorn, and sage-grouse within the greater Bureau of Land Management–Adobe Town Herd Management Area in southern Wyoming and northern Colorado, USA, between 2017 and 2021 to evaluate habitat selection and space use of all species during 3 biologically relevant seasons: spring (Apr–Jun; sage-grouse breeding, nesting, and early-brood rearing; pronghorn late gestation and early parturition), summer (Jul–Oct; sage-grouse summer and late-brood rearing; pronghorn late parturition and breeding), and winter (Nov–Mar; non-breeding season). Feral horses selected flatter slopes and shorter mean shrub height across all seasons and were closer to water in spring and summer. Pronghorn habitat selection was similar to horses, but they also avoided oil and gas well pads year-round. During spring, sage-grouse selected greater herbaceous cover, flatter slopes, and areas farther from well pads. In summer, sage-grouse selected greater mean shrub height, flatter slopes, and were closer to water. In winter, sage-grouse selected flatter slopes and areas with greater vegetation production during the preceding summer. Our results indicate strong year-round overlap in space use between horses and pronghorn, whereas overlap between horses and sage-grouse is greatest during the summer in this region. Consequently, managers should recognize the potential for horses to influence habitat quality of pronghorn and sage-grouse in the region.
DOI: 10.5441/001/1.4q2t4fn8/2
title: Feral horse (Equus ferus caballus) Wyoming_Colorado USA-reference-data

description: Hennig JD, Scasta JD, Pratt AC, Wanner CP, Beck JL. 2022. Habitat selection and space use overlap between feral horses, pronghorn, and greater sage-grouse in cold arid steppe. J Wildlife Manage. e22329. doi:10.1002/jwmg.22329
description: Populations of feral horses (Equus ferus caballus) in the western United States have increased during the past decade, consequently affecting co-occurring wildlife habitat. Feral horses may influence 2 native wildlife species, greater sage-grouse (Centrocercus urophasianus; sage-grouse) and pronghorn (Antilocapra americana) through mechanisms of habitat alteration and competition. Wyoming, USA, contains the largest populations of pronghorn and sage-grouse of any state and also has the highest degree of range overlap between feral horses and these species. Consequently, the effects that horses may have on pronghorn and sage-grouse populations in Wyoming have implications at local, state, and population-wide levels. Managers need information concerning habitat selection and space use overlap among these species to develop appropriate management strategies; yet this information is absent for most feral horse management areas. To address this knowledge need, we attached global positioning system (GPS) transmitters to horses, pronghorn, and sage-grouse within the greater Bureau of Land Management–Adobe Town Herd Management Area in southern Wyoming and northern Colorado, USA, between 2017 and 2021 to evaluate habitat selection and space use of all species during 3 biologically relevant seasons: spring (Apr–Jun; sage-grouse breeding, nesting, and early-brood rearing; pronghorn late gestation and early parturition), summer (Jul–Oct; sage-grouse summer and late-brood rearing; pronghorn late parturition and breeding), and winter (Nov–Mar; non-breeding season). Feral horses selected flatter slopes and shorter mean shrub height across all seasons and were closer to water in spring and summer. Pronghorn habitat selection was similar to horses, but they also avoided oil and gas well pads year-round. During spring, sage-grouse selected greater herbaceous cover, flatter slopes, and areas farther from well pads. In summer, sage-grouse selected greater mean shrub height, flatter slopes, and were closer to water. In winter, sage-grouse selected flatter slopes and areas with greater vegetation production during the preceding summer. Our results indicate strong year-round overlap in space use between horses and pronghorn, whereas overlap between horses and sage-grouse is greatest during the summer in this region. Consequently, managers should recognize the potential for horses to influence habitat quality of pronghorn and sage-grouse in the region.
DOI: 10.5441/001/1.74pf3n2p/1
title: Pronghorn (Antilocapra americana) Wyoming_Colorado USA

description: Hennig JD, Scasta JD, Pratt AC, Wanner CP, Beck JL. 2022. Habitat selection and space use overlap between feral horses, pronghorn, and greater sage-grouse in cold arid steppe. J Wildlife Manage. e22329. doi:10.1002/jwmg.22329
description: Populations of feral horses (Equus ferus caballus) in the western United States have increased during the past decade, consequently affecting co-occurring wildlife habitat. Feral horses may influence 2 native wildlife species, greater sage-grouse (Centrocercus urophasianus; sage-grouse) and pronghorn (Antilocapra americana) through mechanisms of habitat alteration and competition. Wyoming, USA, contains the largest populations of pronghorn and sage-grouse of any state and also has the highest degree of range overlap between feral horses and these species. Consequently, the effects that horses may have on pronghorn and sage-grouse populations in Wyoming have implications at local, state, and population-wide levels. Managers need information concerning habitat selection and space use overlap among these species to develop appropriate management strategies; yet this information is absent for most feral horse management areas. To address this knowledge need, we attached global positioning system (GPS) transmitters to horses, pronghorn, and sage-grouse within the greater Bureau of Land Management–Adobe Town Herd Management Area in southern Wyoming and northern Colorado, USA, between 2017 and 2021 to evaluate habitat selection and space use of all species during 3 biologically relevant seasons: spring (Apr–Jun; sage-grouse breeding, nesting, and early-brood rearing; pronghorn late gestation and early parturition), summer (Jul–Oct; sage-grouse summer and late-brood rearing; pronghorn late parturition and breeding), and winter (Nov–Mar; non-breeding season). Feral horses selected flatter slopes and shorter mean shrub height across all seasons and were closer to water in spring and summer. Pronghorn habitat selection was similar to horses, but they also avoided oil and gas well pads year-round. During spring, sage-grouse selected greater herbaceous cover, flatter slopes, and areas farther from well pads. In summer, sage-grouse selected greater mean shrub height, flatter slopes, and were closer to water. In winter, sage-grouse selected flatter slopes and areas with greater vegetation production during the preceding summer. Our results indicate strong year-round overlap in space use between horses and pronghorn, whereas overlap between horses and sage-grouse is greatest during the summer in this region. Consequently, managers should recognize the potential for horses to influence habitat quality of pronghorn and sage-grouse in the region.
DOI: 10.5441/001/1.74pf3n2p/2
title: Pronghorn (Antilocapra americana) Wyoming_Colorado USA-reference-data

description: Hennig JD, Scasta JD, Pratt AC, Wanner CP, Beck JL. 2022. Habitat selection and space use overlap between feral horses, pronghorn, and greater sage-grouse in cold arid steppe. J Wildlife Manage. e22329. doi:10.1002/jwmg.22329
description: Populations of feral horses (Equus ferus caballus) in the western United States have increased during the past decade, consequently affecting co-occurring wildlife habitat. Feral horses may influence 2 native wildlife species, greater sage-grouse (Centrocercus urophasianus; sage-grouse) and pronghorn (Antilocapra americana) through mechanisms of habitat alteration and competition. Wyoming, USA, contains the largest populations of pronghorn and sage-grouse of any state and also has the highest degree of range overlap between feral horses and these species. Consequently, the effects that horses may have on pronghorn and sage-grouse populations in Wyoming have implications at local, state, and population-wide levels. Managers need information concerning habitat selection and space use overlap among these species to develop appropriate management strategies; yet this information is absent for most feral horse management areas. To address this knowledge need, we attached global positioning system (GPS) transmitters to horses, pronghorn, and sage-grouse within the greater Bureau of Land Management–Adobe Town Herd Management Area in southern Wyoming and northern Colorado, USA, between 2017 and 2021 to evaluate habitat selection and space use of all species during 3 biologically relevant seasons: spring (Apr–Jun; sage-grouse breeding, nesting, and early-brood rearing; pronghorn late gestation and early parturition), summer (Jul–Oct; sage-grouse summer and late-brood rearing; pronghorn late parturition and breeding), and winter (Nov–Mar; non-breeding season). Feral horses selected flatter slopes and shorter mean shrub height across all seasons and were closer to water in spring and summer. Pronghorn habitat selection was similar to horses, but they also avoided oil and gas well pads year-round. During spring, sage-grouse selected greater herbaceous cover, flatter slopes, and areas farther from well pads. In summer, sage-grouse selected greater mean shrub height, flatter slopes, and were closer to water. In winter, sage-grouse selected flatter slopes and areas with greater vegetation production during the preceding summer. Our results indicate strong year-round overlap in space use between horses and pronghorn, whereas overlap between horses and sage-grouse is greatest during the summer in this region. Consequently, managers should recognize the potential for horses to influence habitat quality of pronghorn and sage-grouse in the region.
DOI: 10.5517/ccdc.csd.cc2c98nm
title: CCDC 2183660: Experimental Crystal Structure Determination

description: Related Article: Bo Zhang, Ya-Ning Wang, Jun Li, Xiao-Chen Ren, Yan Yang, Xin-Ru Yang|2022|Cryst.Growth Des.|22|7434|doi:10.1021/acs.cgd.2c01007
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.cc2c98pn
title: CCDC 2183661: Experimental Crystal Structure Determination

description: Related Article: Bo Zhang, Ya-Ning Wang, Jun Li, Xiao-Chen Ren, Yan Yang, Xin-Ru Yang|2022|Cryst.Growth Des.|22|7434|doi:10.1021/acs.cgd.2c01007
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: 10.5281/zenodo.7130000
title: A supramolecular cucurbit[8]uril-based rotaxane chemosensor for the optical tryptophan detection in human serum and urine

description: Dataset of the publication data. Raw and analyzed data included in each excel file.
DOI: 10.5281/zenodo.7130001
title: A supramolecular cucurbit[8]uril-based rotaxane chemosensor for the optical tryptophan detection in human serum and urine

description: Dataset of the publication data. Raw and analyzed data included in each excel file.
DOI: 10.34943/327d6a68-4aa5-46e3-9d82-e2f437e7335e
title: Douglas Channel Hydrophone Deployed 2022-07-14

description: The Ocean Sonics icListen AF Hydrophone 2534 was deployed on 2022-07-14 at Douglas Channel. Douglas Channel is one of the principal inlets of the British Columbia coast. This device is a Hydrophone. Hydrophones are devices containing transducers that convert underwater sound waves into electrical signals. They are acoustic instruments that can process data while they are being collected to produce calibrated waveform data. Hydrophones are typically used to study vocalizations of marine mammals, ship traffic and ambient noise. It was deployed on a fixed platform. Data from this deployment were archived and made available through Ocean Networks Canada's Oceans 3.0 digital infrastructure, with quality assurance and derived data products following established practices.
DOI: 10.5281/zenodo.7434544
title: Heuristics for SoS Design

description: Heuristics for SoS Design
DOI: 10.5281/zenodo.7434543
title: Heuristics for SoS Design

description: Heuristics for SoS Design
DOI: 10.5281/zenodo.7434542
title: Euterpe Mendelssohn Wagner research dataset

description: This dataset contains repertory data from the Euterpe concerto in Leipzig, but only works of Mendelssohn and Wagner. The timeframe is from 1832 until 1886.
DOI: 10.5281/zenodo.7434541
title: Euterpe Mendelssohn Wagner research dataset

description: This dataset contains repertory data from the Euterpe concerto in Leipzig, but only works of Mendelssohn and Wagner. The timeframe is from 1832 until 1886.
DOI: 10.5441/001/1.vd88t77s
title: Data from: Kiawah and Seabrook islands are a critical site for the rufa Red Knot (Calidris canutus rufa)

description: Pelton MM, Padula SR, Garcia-Walther J, Andrews M, Mercer R, Porter R, Sanders F, Thibault J, Senner NR, Linscott JA. 2022. Kiawah and Seabrook islands are a critical site for the rufa Red Knot (Calidris canutus rufa). Wader Study. 129(2):105-118. doi:10.18194/ws.00277
description: The rufa Red Knot Calidris canutus rufa is a migratory shorebird that performs one of the longest known migrations among birds and has experienced a population decline of over 85% in recent decades. During migration, rufa Red Knots rest and refuel at stopover sites along the Atlantic Coast of the USA, including Kiawah and Seabrook islands in South Carolina. We document the importance of Kiawah and Seabrook islands forknots during their spring migration using on-the-ground surveys between 19 February and 20 May 2021 to record the occurrence and proportion of individually marked knots, as well as geolocators deployed on knots captured in the area. Using a superpopulation model, we estimated a minimum passage population of 17,247 knots (95% CI: 13,548–22,099; ~41% of the total rufa knot population) and an average stopover duration of 47 days (95% CI: 40.1–54.8). Our geolocator results showed that knots using Kiawah and Seabrook islands can bypass Delaware Bay and fly directly to the Canadian Arctic. Finally, our geolocators, combined with resighting data from across the Atlantic Flyway, indicate that a large network of more than 70 coastal sites concentrated largely in the southeastern USA provide stopover and overwintering habitat for the knots we observed on Kiawah and Seabrook islands. These findings show that Kiawah and Seabrook islands should be recognized as critical sites in the knot network and, therefore, a conservation priority. The threats facing these sites, such as prey depletion, anthropogenic disturbance, and sea level rise, require immediate attention.
DOI: 10.5441/001/1.vd88t77s/1
title: Migration of red knots on Kiawah-Seabrook Island

description: Pelton MM, Padula SR, Garcia-Walther J, Andrews M, Mercer R, Porter R, Sanders F, Thibault J, Senner NR, Linscott JA. 2022. Kiawah and Seabrook islands are a critical site for the rufa Red Knot (Calidris canutus rufa). Wader Study. 129(2):105-118. doi:10.18194/ws.00277
description: The rufa Red Knot Calidris canutus rufa is a migratory shorebird that performs one of the longest known migrations among birds and has experienced a population decline of over 85% in recent decades. During migration, rufa Red Knots rest and refuel at stopover sites along the Atlantic Coast of the USA, including Kiawah and Seabrook islands in South Carolina. We document the importance of Kiawah and Seabrook islands forknots during their spring migration using on-the-ground surveys between 19 February and 20 May 2021 to record the occurrence and proportion of individually marked knots, as well as geolocators deployed on knots captured in the area. Using a superpopulation model, we estimated a minimum passage population of 17,247 knots (95% CI: 13,548–22,099; ~41% of the total rufa knot population) and an average stopover duration of 47 days (95% CI: 40.1–54.8). Our geolocator results showed that knots using Kiawah and Seabrook islands can bypass Delaware Bay and fly directly to the Canadian Arctic. Finally, our geolocators, combined with resighting data from across the Atlantic Flyway, indicate that a large network of more than 70 coastal sites concentrated largely in the southeastern USA provide stopover and overwintering habitat for the knots we observed on Kiawah and Seabrook islands. These findings show that Kiawah and Seabrook islands should be recognized as critical sites in the knot network and, therefore, a conservation priority. The threats facing these sites, such as prey depletion, anthropogenic disturbance, and sea level rise, require immediate attention.
DOI: 10.5441/001/1.vd88t77s/2
title: Migration of red knots on Kiawah-Seabrook Island-reference-data

description: Pelton MM, Padula SR, Garcia-Walther J, Andrews M, Mercer R, Porter R, Sanders F, Thibault J, Senner NR, Linscott JA. 2022. Kiawah and Seabrook islands are a critical site for the rufa Red Knot (Calidris canutus rufa). Wader Study. 129(2):105-118. doi:10.18194/ws.00277
description: The rufa Red Knot Calidris canutus rufa is a migratory shorebird that performs one of the longest known migrations among birds and has experienced a population decline of over 85% in recent decades. During migration, rufa Red Knots rest and refuel at stopover sites along the Atlantic Coast of the USA, including Kiawah and Seabrook islands in South Carolina. We document the importance of Kiawah and Seabrook islands forknots during their spring migration using on-the-ground surveys between 19 February and 20 May 2021 to record the occurrence and proportion of individually marked knots, as well as geolocators deployed on knots captured in the area. Using a superpopulation model, we estimated a minimum passage population of 17,247 knots (95% CI: 13,548–22,099; ~41% of the total rufa knot population) and an average stopover duration of 47 days (95% CI: 40.1–54.8). Our geolocator results showed that knots using Kiawah and Seabrook islands can bypass Delaware Bay and fly directly to the Canadian Arctic. Finally, our geolocators, combined with resighting data from across the Atlantic Flyway, indicate that a large network of more than 70 coastal sites concentrated largely in the southeastern USA provide stopover and overwintering habitat for the knots we observed on Kiawah and Seabrook islands. These findings show that Kiawah and Seabrook islands should be recognized as critical sites in the knot network and, therefore, a conservation priority. The threats facing these sites, such as prey depletion, anthropogenic disturbance, and sea level rise, require immediate attention.
DOI: 10.17909/yrww-m237
title: HR 8799 sortof
DOI: 10.6084/m9.figshare.21719879
title: Synthetic Data for Article: Alleviating Housing Market Shocks in Real-Time: an Agent-Based Reinforcement Learning Approach.

description: There are two sets of data in this repository, these are: <br> Model Validation Python_Base_100Runs.csv Netlogo_Base_100Runs.csv Python_Ratefall_100Runs.csv Netlogo_Ratefall_100Runs.csv Article Experiment Outputs LTV_80_Ratefall_NORL.csv LTV_100_Ratefall_NORL.csv LTV_80_Ratefall_Shock_Training_RL.csv LTV_100_Ratefall_Shock_Training_RL.csv The model validation datasets compare identical experiments conducted on two different programming frameworks and quantified the similarities between the two model architectures. These results are referenced in the paper in section titled: Quantifying model similarities (validation) <br> The artical experiment outputs compare base case conditions (no reinforcement learning) and reinforcement learning decisions and the housing market reactions to RL agent involvement. Generally, the RL agent adjusts the interest rates to stabilise the housing market indicators. <br> These datasets are purely experimental and will accompany the article mentioned earlier. <br>