cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.21227/xtq1-f705
title: Training Neural Networks for Loss Allocation in Power System

description: Power transmission system losses can typically represent from five to tenpercent of the total generation, a quantity worth millions ofdollars per year.The purpose of loss allocation in the context of pooldispatch is to assign to each individual generation and load theresponsibility of paying for part of the system transmissionlosses.Since the system losses arenon-separable, non-linear functions of the real powergeneration and loads, the allocation of transmission loss is achallenging and contentious issue in a fully deregulatedsystem. Loss allocation is a procedure for subdividing thesystem transmission losses into fractions, the cost of whichthen becomes the responsibilities of individual users of thepower system (Gencos, Discos, and Marketers). Loss allocationdoes not affect generation level or power flows; however, itmodifies the distribution of revenues and payments at thenetwork buses among suppliers and consumers.This dataset presents the data used in the paper titled "ANN Based Z-Bus Loss Allocation for PoolDispatch in Deregulated Power System" and also the data for the practical IEEE 30 bus system.Dataset 1 (fivebus.csv)FIve bus test system used in the paperDataset 2 (book30.csv)IEEE 30 bus system
DOI: 10.21227/p0b7-3566
title: Training Neural Networks for Loss Allocation in Power System

description: Power transmission system losses can typically represent from five to tenpercent of the total generation, a quantity worth millions ofdollars per year.The purpose of loss allocation in the context of pooldispatch is to assign to each individual generation and load theresponsibility of paying for part of the system transmissionlosses.Since the system losses arenon-separable, non-linear functions of the real powergeneration and loads, the allocation of transmission loss is achallenging and contentious issue in a fully deregulatedsystem. Loss allocation is a procedure for subdividing thesystem transmission losses into fractions, the cost of whichthen becomes the responsibilities of individual users of thepower system (Gencos, Discos, and Marketers). Loss allocationdoes not affect generation level or power flows; however, itmodifies the distribution of revenues and payments at thenetwork buses among suppliers and consumers.This dataset presents the data used in the paper titled "ANN Based Z-Bus Loss Allocation for PoolDispatch in Deregulated Power System" and also the data for the practical IEEE 30 bus system.Dataset 1 (fivebus.csv)FIve bus test system used in the paperDataset 2 (book30.csv)IEEE 30 bus system
DOI: 10.5281/zenodo.3855034
title: ADCP data of ice-covered and open-channel (macro-turbulent) flow, Pulmanki River, 2016-2020

description: README of ADCP_data_Lotsari_et_al_Water_opened.zip <br> The ADCP data was the basis of the following paper:<br> Macro-turbulent flow and its impacts on sediment transport potential of a subarctic river during ice-covered and open-channel conditions <br> Eliisa Lotsari (1, 2), Michael Dietze (3), Maria Kämäri (4), Petteri Alho (2,5), Elina Kasvi (6,2) 1 Department of Geographical and Historical Studies, University of Eastern Finland, Yliopistokatu 2, P.O. Box 111, FI-80101, Joensuu, Finland. eliisa.lotsari@uef.fi<br> 2 Department of Geography and Geology, University of Turku, FI-20014 Turun yliopisto, Turku, Finland.<br> 3 Section 4.6 Geomorphology, German Research Centre for Geosciences GFZ Potsdam, D-14473 Potsdam, Germany. mdietze@gfz-potsdam.de<br> 4 Finnish Environment Institute, Latokartanonkaari 11, FI-00790 Helsinki, Finland. maria.kamari@ymparisto.fi<br> 5 Finnish Geospatial Research Institute, National Land Survey of Finland, Geodeetinrinne 2, FI-02430, Masala, Finland. mipeal@utu.fi<br> 6 Turku University of Applied Sciences, Joukahaisenkatu 3, FI-20520, Turku, Finland. elina.kasvi@turkuamk.fi (Note: During the time of data gathering, Maria Kämäri worked at the University of Eastern Finland, and Elina Kasvi at the University of Turku) The data set has been measured with Sontek M9 or S5 sensors, depending on the time step (Table 1). Table 1. The measurement times, their acronyms (applied in the above mentioned publication)<br> and applied sensors. In the acronyms of the measurement times W=winter low flow period, S=spring<br> (snow-melt flood period), A=autumn low flow period. These information are presented also<br> in the Table 1 of the above-mentioned publication.<br> Date Acronym Sensor<br> 17.2.2016 W2016 M9<br> 25.5.2016 S2016 S5 <br> 10.9.2016 A2016 M9<br> 16.2.2017 W2017 M9 <br> 31.5.2017 S2017 M9 <br> 9.9.2017 A2017 M9 <br> 9.2.2018 W2018 M9 <br> 23.5.2018 S2018 S5 <br> 8.9.2018 A2018 S5 <br> 8.2.2019 W2019 M9 <br> 21.5.2019 S2019 M9 <br> 6.2.2020 W2020 M9 RiverSurveyor Live software, and its most recent version, was used each time.<br> The measurements have been done at Pulmanki River (69°55'59.09" N; 28° 2'34.32" E), Northern Finland, during 2016 - 2020. <br> The data is in directories of corresponding measurement times. The measurement<br> locations cs1, cs2, cs3, cs4, csA, csB and csC can be found in the paper (Figs. 1 and 2). <br> The data is in raw Matlab file format, as exported from the RiverSurveyor Live software.<br> The coordinate system is ENU. When used, the referencing to the paper and DOI ( 10.5281/zenodo.3855035 ) are required.
DOI: 10.5281/zenodo.3855035
title: ADCP data of ice-covered and open-channel (macro-turbulent) flow, Pulmanki River, 2016-2020

description: README of ADCP_data_Lotsari_et_al_Water_opened.zip <br> The ADCP data was the basis of the following paper:<br> Macro-turbulent flow and its impacts on sediment transport potential of a subarctic river during ice-covered and open-channel conditions <br> Eliisa Lotsari (1, 2), Michael Dietze (3), Maria Kämäri (4), Petteri Alho (2,5), Elina Kasvi (6,2) 1 Department of Geographical and Historical Studies, University of Eastern Finland, Yliopistokatu 2, P.O. Box 111, FI-80101, Joensuu, Finland. eliisa.lotsari@uef.fi<br> 2 Department of Geography and Geology, University of Turku, FI-20014 Turun yliopisto, Turku, Finland.<br> 3 Section 4.6 Geomorphology, German Research Centre for Geosciences GFZ Potsdam, D-14473 Potsdam, Germany. mdietze@gfz-potsdam.de<br> 4 Finnish Environment Institute, Latokartanonkaari 11, FI-00790 Helsinki, Finland. maria.kamari@ymparisto.fi<br> 5 Finnish Geospatial Research Institute, National Land Survey of Finland, Geodeetinrinne 2, FI-02430, Masala, Finland. mipeal@utu.fi<br> 6 Turku University of Applied Sciences, Joukahaisenkatu 3, FI-20520, Turku, Finland. elina.kasvi@turkuamk.fi (Note: During the time of data gathering, Maria Kämäri worked at the University of Eastern Finland, and Elina Kasvi at the University of Turku) The data set has been measured with Sontek M9 or S5 sensors, depending on the time step (Table 1). Table 1. The measurement times, their acronyms (applied in the above mentioned publication)<br> and applied sensors. In the acronyms of the measurement times W=winter low flow period, S=spring<br> (snow-melt flood period), A=autumn low flow period. These information are presented also<br> in the Table 1 of the above-mentioned publication.<br> Date Acronym Sensor<br> 17.2.2016 W2016 M9<br> 25.5.2016 S2016 S5 <br> 10.9.2016 A2016 M9<br> 16.2.2017 W2017 M9 <br> 31.5.2017 S2017 M9 <br> 9.9.2017 A2017 M9 <br> 9.2.2018 W2018 M9 <br> 23.5.2018 S2018 S5 <br> 8.9.2018 A2018 S5 <br> 8.2.2019 W2019 M9 <br> 21.5.2019 S2019 M9 <br> 6.2.2020 W2020 M9 RiverSurveyor Live software, and its most recent version, was used each time.<br> The measurements have been done at Pulmanki River (69°55'59.09" N; 28° 2'34.32" E), Northern Finland, during 2016 - 2020. <br> The data is in directories of corresponding measurement times. The measurement<br> locations cs1, cs2, cs3, cs4, csA, csB and csC can be found in the paper (Figs. 1 and 2). <br> The data is in raw Matlab file format, as exported from the RiverSurveyor Live software.<br> The coordinate system is ENU. When used, the referencing to the paper and DOI ( 10.5281/zenodo.3855035 ) are required.
DOI: 10.21227/r0r9-5d46
title: Mold Materials for an Artificial Pancreas Phantom

description: This data set contains all relevant 3D mold files for modeling a pancreatic phantom described in the publication (currently under review):Benjamin Eigl et al.: A Multimodal Pancreas Phantom for Computer-Assisted Surgery Training.
DOI: 10.25919/5ed01ad86abd4
title: Parkes observations for project P1021 semester 2020APRS_01

description: We propose to continue our observations of PSR J1653-45, a 951-ms pulsar in a long, 1.5-yr orbit. Binary pulsars are valuable objects of scientific study, allowing for a wide range of applications, including tests of gravity, probes of the neutron star equation of state, and fossil records of stellar evolution. Long spin-period pulsars in binary systems are generally much rarer than faster-spinning `recycled’ pulsars, and represent an under-explored region of pulsar binary evolution. In addition to its long orbital period, PSR J1653-45 also experiences extended eclipses, lasting up to half of the orbital period and whose nature is not well understood. These eclipses have also prevented the determination of an orbital or phase-connected timing solution, both vital steps in allowing for the continued study of this system. We propose a targeted, high-cadence observing campaign designed to monitor this pulsar as it transitions out of its eclipsing state. The campaign has the twin goals of both monitoring how the eclipse affects the pulsar’s emission properties, thereby revealed more about the nature of the eclipses themselves, and of extracting as much information regarding the pulsar’s orbit during its least-explored regions, thereby constrained and hopefully solving the pulsar’s orbit and ideally leading to the development of a timing solution. In both instances, we hope to gain a greater understanding of this pulsar’s properties and how it fits into this under-explored class of unrecycled pulsar binaries.
DOI: 10.25345/c5gh7p
title: MassIVE MSV000085493 - A preliminary DDA study of human plasma exosomes 05/28/2020
title: This is a preliminary DDA study of human plasma exosomes.
DOI: 10.5281/zenodo.3862957
title: edxia examples

description: edxia is a plugin for glue. <strong>Description of the samples</strong> <em> OPC</em> A CEM I sample, with w/c=0.4, cured 28d. Field of view: 280 μm by 210 μm<br> Resolution: 1024 x 768 <em>LC3</em> A blended sample made from CEM I cement (53%) with limestone (15%), calcined clay (30%) and Gypsum (2%), with w/c=0.4, cured 28d. Field of view: 280 μm by 210 μm<br> Resolution: 1024 x 768
DOI: 10.5281/zenodo.3862958
title: edxia examples

description: edxia is a plugin for glue. <strong>Description of the samples</strong> <em> OPC</em> A CEM I sample, with w/c=0.4, cured 28d. Field of view: 280 μm by 210 μm<br> Resolution: 1024 x 768 <em>LC3</em> A blended sample made from CEM I cement (53%) with limestone (15%), calcined clay (30%) and Gypsum (2%), with w/c=0.4, cured 28d. Field of view: 280 μm by 210 μm<br> Resolution: 1024 x 768
DOI: 10.5258/soton/d1385
title: Dataset for: Effect of spanwise domain size on direct numerical simulations of airfoil noise during flow separation and stall

description: Dataset supporting: Turner, J.M. and Kim, J.W. (2020) Effect of spanwise domain size on direct numerical simulations of airfoil noise during flow separation and stall. Physics of Fluids.
DOI: 10.5281/zenodo.3708081
title: Consensus QSAR models estimating acute aquatic toxicity for three trophic levels organisms: Algae, Daphnia and Fish

description: We report new consensus models estimating acute toxicity for algae, daphnia and fish endpoints. We assembled a large collection of 3680 public unique compounds annotated by, at least, one experimental value for the given endpoint. Support Vector Machine models were internally and externally validated following the OECD principles. Reasonable predictive performances were achieved (RMSE<sub>ext</sub> = 0.56 – 0.78) which are in line with those of state-of-the-art models. The known structural alerts are compared with analysis of the atomic contributions to these models obtained using the ISIDA/<em>ColorAtom</em> utility. A benchmarking against existing tools has been carried out on a set of compounds considered more representative and relevant for the chemical space of the current chemical industry. Our model scored one of the best accuracies and data coverage. Nevertheless, industrial data performances were noticeably lower than those on public data, indicating that existing models fail to meet the industrial needs. Thus, final models were updated with the inclusion of new industrial compounds, extending applicability domain and relevance for application in an industrial context. Generate models and collected public data are made freely available. <strong>Available fields in the SDF file:</strong> SMILES_Canonical: canonical SMILES code DB: source of the data, "Litterature set" means that the data is originated from an article (see the companion article of the dataset for details). endpoint: organism for which endpoint is available CASRN: CAS registration number 98-81-7 pEC50 - DAPHNIA: Daphnia, mortality, which is evaluated by the immobilization of the invertebrate is recorded at 48 hours and expressed as the log median effective concentration (pEC50) mg/L - DAPHNIA: Daphnia, mortality, which is evaluated by the immobilization of the invertebrate is recorded at 48 hours and expressed as the median effective concentration (EC50) pLC50 - FISH: Fish, the log median lethal concentration measured at 96 hours is considered (pLC50) mg/L - FISH: Fish, the log median lethal concentration measured at 96 hours is considered (LC50) pEC50 - ALGA: Algae, the purpose is to determine the substance’s growth inhibition effect, expressed as the log median effective concentration (pEC50) measured at 72 hours mg/L - ALGA: Algae, the purpose is to determine the substance’s growth inhibition effect, expressed as the median effective concentration (EC50) measured at 72 hours
DOI: 10.5281/zenodo.3708082
title: Consensus QSAR models estimating acute aquatic toxicity for three trophic levels organisms: Algae, Daphnia and Fish

description: We report new consensus models estimating acute toxicity for algae, daphnia and fish endpoints. We assembled a large collection of 3680 public unique compounds annotated by, at least, one experimental value for the given endpoint. Support Vector Machine models were internally and externally validated following the OECD principles. Reasonable predictive performances were achieved (RMSE<sub>ext</sub> = 0.56 – 0.78) which are in line with those of state-of-the-art models. The known structural alerts are compared with analysis of the atomic contributions to these models obtained using the ISIDA/<em>ColorAtom</em> utility. A benchmarking against existing tools has been carried out on a set of compounds considered more representative and relevant for the chemical space of the current chemical industry. Our model scored one of the best accuracies and data coverage. Nevertheless, industrial data performances were noticeably lower than those on public data, indicating that existing models fail to meet the industrial needs. Thus, final models were updated with the inclusion of new industrial compounds, extending applicability domain and relevance for application in an industrial context. Generate models and collected public data are made freely available. <strong>Available fields in the SDF file:</strong> SMILES_Canonical: canonical SMILES code DB: source of the data, "Litterature set" means that the data is originated from an article (see the companion article of the dataset for details). endpoint: organism for which endpoint is available CASRN: CAS registration number 98-81-7 pEC50 - DAPHNIA: Daphnia, mortality, which is evaluated by the immobilization of the invertebrate is recorded at 48 hours and expressed as the log median effective concentration (pEC50) mg/L - DAPHNIA: Daphnia, mortality, which is evaluated by the immobilization of the invertebrate is recorded at 48 hours and expressed as the median effective concentration (EC50) pLC50 - FISH: Fish, the log median lethal concentration measured at 96 hours is considered (pLC50) mg/L - FISH: Fish, the log median lethal concentration measured at 96 hours is considered (LC50) pEC50 - ALGA: Algae, the purpose is to determine the substance’s growth inhibition effect, expressed as the log median effective concentration (pEC50) measured at 72 hours mg/L - ALGA: Algae, the purpose is to determine the substance’s growth inhibition effect, expressed as the median effective concentration (EC50) measured at 72 hours
DOI: 10.21227/aavy-jc50
title: Training Neural Networks for Loss Allocation in Power System

description: Power transmission system losses can typically represent from five to tenpercent of the total generation, a quantity worth millions ofdollars per year.The purpose of loss allocation in the context of pooldispatch is to assign to each individual generation and load theresponsibility of paying for part of the system transmissionlosses.Since the system losses arenon-separable, non-linear functions of the real powergeneration and loads, the allocation of transmission loss is achallenging and contentious issue in a fully deregulatedsystem. Loss allocation is a procedure for subdividing thesystem transmission losses into fractions, the cost of whichthen becomes the responsibilities of individual users of thepower system (Gencos, Discos, and Marketers). Loss allocationdoes not affect generation level or power flows; however, itmodifies the distribution of revenues and payments at thenetwork buses among suppliers and consumers.This dataset presents the data used in the paper titled "ANN Based Z-Bus Loss Allocation for PoolDispatch in Deregulated Power System" and also the data for the practical IEEE 30 bus system.Dataset 1 (fivebus.csv)FIve bus test system used in the paperDataset 2 (book30.csv)IEEE 30 bus system
DOI: 10.6073/pasta/05fc7a39ea8d01784a64fe7c8b6c4bee
title: IEP Zooplankton Study

description: The Zooplankton Study was implemented in 1972 to assess fish food resources in the upper San Francisco Estuary (SFE). Mandated by the State Water Resources Control Board's Water Right Decision D-1641, the study is conducted jointly by the California Department of Fish and Wildlife and the California Department of Water Resources under the guidance and management of the Interagency Ecological Program. For nearly 5 decades, this study has monitored the zooplankton community in the region, tracking abundance trends and distributional patterns, detecting and monitoring introduced species, and documenting changes in community composition. The Zooplankton Study operates three gear types to sample macro, meso, and micro-zooplankton across the upper SFE on a monthly basis.
DOI: 10.17632/zts3zb53cx.2
title: Data for: The role of dyadic social capital in enhancing collaborative knowledge creation

description: The data are extracted from co-publication information across top cited institutions in the field of engineering categorized by the Essential Science Indicators (ESI) over the 2006-2016 period.
DOI: 10.6073/pasta/26d2d882293a0017e8144d172e8e4954
title: Water column and sediment porewater nutrient concentrations from lagoon, river, and ocean sites along the Alaska Beaufort Sea coast, 2018-ongoing

description: Several water types (lagoon, river, ocean) and surface sediment porewater from the coastal Beaufort Sea system are sampled seasonally to investigate temporal and spatial shifts in nutrient dynamics. Surface and bottom water samples, and surface sediment samples are collected during full ice cover (April), ice break-up (mid-June to early July), and open water (late July and August) periods, and analyzed for ammonia, nitrate + nitrite, orthophosphate, and silicate concentrations.
DOI: 10.25387/g3.10307972
title: Supplemental Material for Huda et al., 2020

description: This file contains Supplemental Tables and Figures for the manuscript entitled “Dissecting the Genetic Architecture of Cystatin C in Diversity Outbred Mice” by Huda et al.
DOI: 10.25387/g3.10307972.v1
title: Supplemental Material for Huda et al., 2020

description: This file contains Supplemental Tables and Figures for the manuscript entitled “Dissecting the Genetic Architecture of Cystatin C in Diversity Outbred Mice” by Huda et al.
DOI: 10.21227/9vpy-8658
title: Ferroelectric_NegCap_Hybrid_MEMS_SPICE_Model_2020

description: The SPICE model of a ferroelectric negative capacitance - electrostatic MEMS hybrid actuator is presented. The model is validated for static pull-in and release characteristics. The simulation results are in agreement with the analytical predictions available in the literature. The model could be used for investigating the static, dynamic and load-line analysis of the hybrid actuator. The SPICE model being circuit compatible could be used along with other standard device models to evaluate various CMOS-MEMS hybrdi circuits.
DOI: 10.21227/s7sg-2a16
title: Ferroelectric_NegCap_Hybrid_MEMS_SPICE_Model_2020

description: The SPICE model of a ferroelectric negative capacitance - electrostatic MEMS hybrid actuator is presented. The model is validated for static pull-in and release characteristics. The simulation results are in agreement with the analytical predictions available in the literature. The model could be used for investigating the static, dynamic and load-line analysis of the hybrid actuator. The SPICE model being circuit compatible could be used along with other standard device models to evaluate various CMOS-MEMS hybrdi circuits.
DOI: 10.21949/1518702
title: Work Zone Data Exchange (WZDx) Feed Registry
DOI: 10.21949/1518703
title: Maricopa County Regional Work Zone Data Exchange (WZDx) Feed Data Sample
DOI: 10.25592/uhhfdm.999
title: 3D Model of a Hammer

description: 3D Model of a hammer
DOI: 10.25919/5ed021f15d9a5
title: Parkes observations for project P1062 semester 2020APRS_01

description: We propose to monitor the potential repeating FRBs in the Southern Sky with luminosity di- chotomy criterion. With a success of luminosity-guided detection of a repeating source by FAST, we can continue to search for more repeaters hidden in current FRB sample according to luminosity dichotomy. Specifically, we select FRB 171020 and FRB 180923 as the targets of proposed obser- vations, which are located in the repeater population in the luminosity function. We demonstrate that the observing with 20 hours for each source is optimistic using Parkes ultra-wide-bandwidth receiver (UWL), if there are repeaters among them.
DOI: 10.21227/vedr-dq64
title: Ferroelectric_NegCap_Hybrid_MEMS_SPICE_Model_2020

description: The SPICE model of a ferroelectric negative capacitance - electrostatic MEMS hybrid actuator is presented. The model is validated for static pull-in and release characteristics. The simulation results are in agreement with the analytical predictions available in the literature. The model could be used for investigating the static, dynamic and load-line analysis of the hybrid actuator. The SPICE model being circuit compatible could be used along with other standard device models to evaluate various CMOS-MEMS hybrid circuits.
DOI: 10.25592/uhhfdm.1000
title: 3D Model of Palmea Raphia-spec

description: 3D Model of Palmea Raphia-spec
DOI: 10.25592/uhhfdm.1001
title: 3D Model of an Eye Mirror medical device - part Mirror

description: 3D Model of an Eye Mirror medical device - part Mirror
DOI: 10.25592/uhhfdm.1002
title: 3D Model of a plaster cast of Pancraticians

description: 3D Model of a plaster cast of Pancraticians