cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.21508065.v2
title: Processed DRIVE data for running SLIdR

description: SLIdR (Synthetic Lethal Identification in R) is a statistical framework to identify synthetic lethality pairs from large scale screens across multiple cancer types. Here, we are sharing the processed Project DRIVE data along with mutation data for running SLIdR in the pan-cancer and cancer type-specific settings. The enclosed RData file contains two objects: <strong>all_data</strong> - List of 17 processed cancer type-specific data in SLIdR format. <strong>pc_data</strong> - Processed pan-cancer data in SLIdR format for running SLIdR in the pan-cancer setting.
DOI: 10.6084/m9.figshare.21508065
title: Processed DRIVE data for running SLIdR

description: SLIdR (Synthetic Lethal Identification in R) is a statistical framework to identify synthetic lethality pairs from large scale screens across multiple cancer types. Here, we are sharing the processed Project DRIVE data along with mutation data for running SLIdR in the pan-cancer and cancer type-specific settings. The enclosed RData file contains two objects: <strong>all_data</strong> - List of 17 processed cancer type-specific data in SLIdR format. <strong>pc_data</strong> - Processed pan-cancer data in SLIdR format for running SLIdR in the pan-cancer setting.
DOI: 10.6084/m9.figshare.21508065.v3
title: Processed DRIVE data for running SLIdR

description: SLIdR (Synthetic Lethal Identification in R) is a statistical framework to identify synthetic lethality pairs from large scale screens across multiple cancer types. Here, we are sharing the processed Project DRIVE data along with mutation data for running SLIdR in the pan-cancer and cancer type-specific settings. The enclosed RData file contains two objects: <strong>all_data</strong> - List of 17 processed cancer type-specific data in SLIdR format. <strong>pc_data</strong> - Processed pan-cancer data in SLIdR format for running SLIdR in the pan-cancer setting.
DOI: 10.6084/m9.figshare.21508062.v1
title: TamburelloLitt_DataTrackingTable_20210217_analysis.xlsx

description: A dataset synthesizing the identity, mechanisms of impact, mechanisms of spread, and magnitude of impacts across 784 unique pairs of invasive species and federally-listed species at risk in British Columbia, Canada, based on a systematic literature review of species at risk documentation.
DOI: 10.6084/m9.figshare.6187262
title: Raw Fear Surprise Data

description: As above - raw fear surprise task data set<br>
DOI: 10.6084/m9.figshare.6187262.v1
title: Raw Fear Surprise Data

description: As above - raw fear surprise task data set<br>
DOI: 10.5281/zenodo.7297064
title: PUDL Raw EIA Thermoelectric Cooling Water Data

description: US Energy Information Administration (EIA) thermoelectric cooling water dataset includes generator type and ID, boiler ID, fuel consumption, water source, discharge location, and more. Archived from https://www.eia.gov/electricity/data/water/ This archive contains raw input data for the Public Utility Data Liberation (PUDL) software developed by Catalyst Cooperative. It is organized into Frictionless Data Packages. For additional information about this data and PUDL, see the following resources: The PUDL Repository on GitHub PUDL Documentation Other Catalyst Cooperative data archives
DOI: 10.5281/zenodo.7297063
title: PUDL Raw EIA Thermoelectric Cooling Water Data

description: US Energy Information Administration (EIA) thermoelectric cooling water dataset includes generator type and ID, boiler ID, fuel consumption, water source, discharge location, and more. Archived from https://www.eia.gov/electricity/data/water/ This archive contains raw input data for the Public Utility Data Liberation (PUDL) software developed by Catalyst Cooperative. It is organized into Frictionless Data Packages. For additional information about this data and PUDL, see the following resources: The PUDL Repository on GitHub PUDL Documentation Other Catalyst Cooperative data archives
DOI: 10.3886/e133002v1-130420
title: COVID-19 Stress and Eating and Drinking Behaviors in the United States during the Early Stages of the Pandemic

description: https://osf.io/myfts/
DOI: 10.5281/zenodo.4578400
title: GROMACS input files

description: Input files for GROMACS with enforced rotation applied to the C-terminal amino acid of a peptide. See https://doi.org/10.12688/f1000research.28175.1 for more details.
DOI: 10.5281/zenodo.4578401
title: GROMACS input file

description: An example .tpr input file for GROMACS with enforced rotation applied to the C-terminal amino acid of a peptide. See https://doi.org/10.12688/f1000research.28175.1 for more details.
DOI: 10.5281/zenodo.4625519
title: GROMACS input files

description: Input files for GROMACS with enforced rotation applied to the C-terminal amino acid of a peptide. See https://doi.org/10.12688/f1000research.28175.1 for more details.
DOI: 10.5517/ccdc.csd.cc27mk5m
title: CCDC 2074370: Experimental Crystal Structure Determination

description: Related Article: Valiallah Hosseininasab, Ida M. DiMucci, Pokhraj Ghosh, Jeffery A. Bertke, Siddarth Chandrasekharan, Charles J. Titus, Dennis Nordlund, Jack H. Freed, Kyle M. Lancaster, Timothy H. Warren|2022|Nature Chemistry|14|1265|doi:10.1038/s41557-022-01025-9
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.cc27mk6n
title: CCDC 2074371: Experimental Crystal Structure Determination

description: Related Article: Valiallah Hosseininasab, Ida M. DiMucci, Pokhraj Ghosh, Jeffery A. Bertke, Siddarth Chandrasekharan, Charles J. Titus, Dennis Nordlund, Jack H. Freed, Kyle M. Lancaster, Timothy H. Warren|2022|Nature Chemistry|14|1265|doi:10.1038/s41557-022-01025-9
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: 10.4227/11/5587a862a9726
title: New global marine gravity model from CryoSat-2 and Jason-1
DOI: 10.4227/11/556fd561ea5e0
title: The tectonic fabric of the ocean basins
DOI: 10.4227/11/5587a8381832d
title: Global dynamic topography grids in mantle and plate reference frames
DOI: 10.4227/11/5587a83d726db
title: Global oceanic crustal age, basement temperature, paleo-heat flow, residual heat flow, and hydrothermal fluid flux data grids
DOI: 10.4227/11/5587a8423127e
title: The tectonic evolution of the Arctic since Pangea breakup
DOI: 10.4227/11/5587a846b5130
title: The tectonic fabric of the ocean basins
DOI: 10.4227/11/5587a84b4a543
title: Absolute plate motions since 130 Ma constrained by subduction zone kinematics
DOI: 10.4227/11/5587a84fea042
title: Australian palaeo-stress fields and tectonic reactivation over the past 100 Myr
DOI: 10.4227/11/5587a854928e1
title: Total Sediment Thickness of the World's Oceans and Marginal Seas, Version 2
DOI: 10.3886/e114877v1-130421
title: Replication data for: Does Federal Student Aid Raise Tuition? New Evidence on For-Profit Colleges

description: We provide the first comprehensive estimates of the size of the for-profit higher education sector and evaluate whether for-profits increase tuition in response to federal subsidies. By using state administrative data we include institutions that do not participate in federal student aid programs and are missed in official counts. Including these institutions doubles the number of for-profits and increases students by one-third compared with official counts. Aid-eligible institutions charge tuition for sub-baccalaureate (mainly certificate) programs that is about 78 percent higher than that charged by comparable programs in nonparticipating institutions, lending some credence to the "Bennett hypothesis" of federal aid capture.
DOI: 10.4227/11/5587a8676bb31
title: Palaeo-age, depth-to-basement and bathymetry data for the world's ocean basins
DOI: 10.4227/11/5587a86c0fdf1
title: A predictive model for opal exploration in Australia from a data mining approach
DOI: 10.4227/11/5587a870c2c55
title: Cretaceous palaeogeography of Eastern Australia
DOI: 10.4227/11/5587a87584bb2
title: A review of observations and models of dynamic topography - residual topography and dynamic topography grids
DOI: 10.4227/11/5587a87a1cda5
title: EMAG2: A 2–arc min resolution Earth Magnetic Anomaly Grid compiled from satellite, airborne, and marine magnetic measurements
DOI: 10.4227/11/5587a87ec4e5c
title: The breakup of East Gondwana: A best-fit tectonic model
DOI: 10.4227/11/5587a8835ab8c
title: Tectonic speed limits from plate kinematic reconstructions
DOI: 10.4227/11/5587a88805812
title: Age, spreading rates, and spreading asymmetry of the world's ocean crust
DOI: 10.4227/11/5587a88c8d6c9
title: An integrated Phanerozoic plate motion model with paleogeography and paleobiology data
DOI: 10.4227/11/5587a89122cf5
title: Testing absolute plate reference frames
DOI: 10.4227/11/5587a895ce418
title: Seafloor gravity roughness
DOI: 10.5281/zenodo.7275728
title: Melting and melt segregation processes controlling granitic melt composition

description: Granitic melt composition is controlled by melting reactions and modified by melt segregation process. This is a fundamental but unresolved issue for granite petrogenesis. To investigate the influence of these two processes on granitic melt compositions, we conducted systematic petrographic and geochemical analyses of melanosome and leucosome samples from the Jindong migmatite in the Indosinian orogen, South China. Petrographic observations and zircon U-Pb geochronology indicate that the Jindong migmatite was formed through water-fluxed melting of the Early Paleozoic gneissic granite (437±2 Ma) during the Triassic (238±1 Ma). The Jindong leucosomes can be divided into lenticular and net-structured types. They show increasing Rb with decreasing Ba and Sr, due to fractionation of K-feldspar and plagioclase during melt segregation. Nd isotope and Th, Y and REE contents of leucosomes reveal the complex behavior of phosphates during melting, recorded by the incongruent melting of apatite with precipitation of monazite and xenotime in the source. The leucosomes have similar Nd isotopic compositions with the source due to early dissolution of monazite. Continued dissolution of apatite caused saturation of monazite and decreased ε<sub>Nd</sub>(t) values of melts. This interplay also caused sharply reduction of Th, Y and REE contents in melts with increasing P<sub>2</sub>O<sub>5</sub>, when saturation of monazite and xenotime due to dissolution of apatite. Thus, dissolution of accessory phase in the source impacts fundamentally on REE geochemistry and Nd isotope of granites. Such patterns are reflected in granites worldwide, illustrating the strong controls of the melting and melt segregation processes on granitic melt compositions.
DOI: 10.5281/zenodo.3819617
title: Melting and melt segregation processes controlling granitic melt composition

description: Granitic melt composition is controlled by melting reactions and modified by melt segregation process. This is a fundamental but unresolved issue for granite petrogenesis. To investigate the influence of these two processes on granitic melt compositions, we conducted systematic petrographic and geochemical analyses of melanosome and leucosome samples from the Jindong migmatite in the Indosinian orogen, South China. Petrographic observations and zircon U-Pb geochronology indicate that the Jindong migmatite was formed through water-fluxed melting of the Early Paleozoic gneissic granite (437±2 Ma) during the Triassic (238±1 Ma). The Jindong leucosomes can be divided into lenticular and net-structured types. They show increasing Rb with decreasing Ba and Sr, due to fractionation of K-feldspar and plagioclase during melt segregation. Nd isotope and Th, Y and REE contents of leucosomes reveal the complex behavior of phosphates during melting, recorded by the incongruent melting of apatite with precipitation of monazite and xenotime in the source. The leucosomes have similar Nd isotopic compositions with the source due to early dissolution of monazite. Continued dissolution of apatite caused saturation of monazite and decreased ε<sub>Nd</sub>(t) values of melts. This interplay also caused sharply reduction of Th, Y and REE contents in melts with increasing P<sub>2</sub>O<sub>5</sub>, when saturation of monazite and xenotime due to dissolution of apatite. Thus, dissolution of accessory phase in the source impacts fundamentally on REE geochemistry and Nd isotope of granites. Such patterns are reflected in granites worldwide, illustrating the strong controls of the melting and melt segregation processes on granitic melt compositions.
DOI: 10.4227/11/5587a89aa4888
title: AgeGrid dataset: age, spreading rates and spreading asymmetry of the world's ocean crust
DOI: 10.4227/11/5587a89f4ee56
title: Evaluating global paleoshoreline models for the Cretaceous and Cenozoic
DOI: 10.3886/e157981v1-130422
title: The association between stigmatizing attitudes towards depression and help seeking attitudes in college students

description: Depression stigma has been considered a significant barrier to treatment and rehabilitation. This study aimed to understand the effects of gender, previous mental health care, and symptomatology on depression stigma and analyze the impact of depression stigma on help-seeking attitudes. A total of 969 students with a mean age of 18.87 (SD=1.49) were included in this study and completed the Depression Stigma Scale, the Attitude Toward Seeking Professional Psychological Help, the Patient Health Questionnaire-4 questionnaire, and a socio-demographic questionnaire. We analyzed data using SPSS 24.0, with a 95% confidence interval. Participants came from all University schools, and 64.6% were women. Personal stigma and help-seeking attitudes were affected by gender (β(male)=5.65, CI=4.07, 7.25) and previous access to mental healthcare services (β(previous help)=-4.35, CI=-5.89, -2.82). Perceived depression stigma was affected gender (β(male)=-2.67, CI=-5.00, -0.34) and symptomatology (β(no symptomatology)=-3.29, CI=-6.09, -0.49). Personal (r=-0.42, p&lt;0.01) and perceived (r=0.10, p&lt;0.01) depression stigma correlated with help-seeking attitudes, but we detected no direct symptomatology effect on help-seeking attitudes. Personal depression stigma significantly affected help-seeking attitudes (β=-0.15, CI=-0.17, -0.12). Promoting literacy may decrease personal depression stigma and increase professional help-seeking attitudes and behaviors.
DOI: 10.6084/m9.figshare.21505428
title: PaiNN dataset and model for LGPS

description: Can be used to run MD with the NeuralForceField repository. Units for the dataset are: kcal/mol for energy, kcal/mol-Å for forces, Å for units of length.
DOI: 10.6084/m9.figshare.21505605
title: NequIP dataset and model for LGPS

description: Can be used to run MD with the NequIP repository. Units for the dataset are: kcal/mol for energy, kcal/mol-Å for forces, Å for units of length.
DOI: 10.5281/zenodo.7297097
title: Materialidades por estructuras y sectores excavados en El Shincal de Quimivil

description: Base de datos con las materialidades recuperadas de excavaciones en las diferentes estructuras del sitio arqueológico El Shincal de Quimivil
DOI: 10.5281/zenodo.7297096
title: Materialidades por estructuras y sectores excavados en El Shincal de Quimivil

description: Base de datos con las materialidades recuperadas de excavaciones en las diferentes estructuras del sitio arqueológico El Shincal de Quimivil
DOI: 10.6084/m9.figshare.21508251
title: coarse-grained sentiment analysis.csv

description: This study selects the customer service conversation dataset from Jing Dong (JD)[1] to evaluate our proposed model. In the dataset, the number 0 represents the statement issued by the customer, the number 1 represents the statement issued by customer service and chatbots, and the "session-id" represents multi-turn sessions between the same customer service agents and customers. This paper selected about 10,000 dialogue texts for training, validation, and testing, including 5,068 sentences issued by customers and 4,942 sentences issued by customer service and chatbots.<br> [1] https://www.jd.com
DOI: 10.6084/m9.figshare.21508251.v1
title: coarse-grained sentiment analysis.csv

description: This study selects the customer service conversation dataset from Jing Dong (JD)[1] to evaluate our proposed model. In the dataset, the number 0 represents the statement issued by the customer, the number 1 represents the statement issued by customer service and chatbots, and the "session-id" represents multi-turn sessions between the same customer service agents and customers. This paper selected about 10,000 dialogue texts for training, validation, and testing, including 5,068 sentences issued by customers and 4,942 sentences issued by customer service and chatbots.<br> [1] https://www.jd.com
DOI: 10.34740/kaggle/dsv/4460825
title: BBC News
DOI: 10.34740/kaggle/dsv/4460858
title: OntoUML/UFO Catalog
DOI: 10.34740/kaggle/dsv/4460869
title: Polish-Ukrainian translations from Tatoeba
DOI: 10.21227/gs8y-xt20
title: CRAWDAD queensu/crowd_temperature

description: Outdoor temperature data collected by taxis in Rome, Italy.This dataset is to be used in conjunction with the roma/taxi dataset and provides the outdoor temperature of the areas in Rome where the taxis were located (289 taxicabs over 4 days).date/time of measurement start: 2012-08-15date/time of measurement end: 2014-02-04collection environment: We simulate taxicabs as if they were equipped with temperature sensors attached to their vehicles. The city of Rome is divided into 9 areas and temperate readings were gathered from a weather service, allowing us to simulate each taxicab sending its sensed temperature to a central server every 6 hours for each area.parent data name: roma/taxinote: The original dataset is the CRAWDAD roma/taxi dataset that comprises the position of each taxicab using GPS. This dataset adds the outdoor temperature of the areas that taxicabs visit during their services.Traceset temperatureSimulated outdoor temperature data collected by taxis in Rome, Italy.files:methodology: We generate a temperature value for every active taxicab by applying Gaussian distribution. To fill out the parameters of Gaussian function, we need to assign the mean mu; and standard deviation sigma; for every run. Therefore, we assign a ground truth temperature mu; for every period in every grid on every day. We use data from The Weather Network (http://www.theweathernetwork.com/) to assign the right ground truth to the right period and grid. For every taxicab, we assign a fixed error range sigma; that remains the same in all of its contributions. To do so, we randomly classify participant taxicabs into three classes. First class, called "honest", consists of taxicabs that usually sense accurate temperature within a 10% error range from the ground truth. The population of honest class is 145 taxicabs (50% of all participant taxicabs). Second class, called "dishonest", consists of taxicabs that usually sense inaccurate temperature within a 30% error range from the ground truth. The population of the dishonest class is 72 taxicabs (25%). Third class, called "misleading", consists of the rest of the participant taxicabs that is 72 (25%) that usually sense either accurate or inaccurate temperature. The data generator function makes a random decision of generating accurate or inaccurate temperature for each taxicab among the misleading class. The latter class plays a major role in the results of applying the data on a system, such as participants reputation system, since the accuracy of their contributions is not even. As a result, each taxicab has a sensed temperature contribution based on its fixed error range and the ground truth of the day, period and grid of its location.
DOI: 10.5281/zenodo.7266321
title: PERTEMUAN 9_ 07 NOVEMBER 2022_PENGENDALIAN BIAYA TENAGA KERJA, AKUNTANSI BIAYA _UNIVERSITAS GRESIK JAM 20.00-21.30

description: <strong>Capaian Pembelajan Mata Kuliah (CPMK)</strong> Setelah megikuti perkuliahan ini mahasiswa Mampu menghitung dan mengerjakan Pengendalian: Biaya Tenaga Kerja <strong>Indikator Pembelajaran</strong> 1. Karakteristik tenaga kerja 2. Pengendalian biaya tenaga kerja 3. Produktivitas tenaga kerja 4. Pengukuran produktivitas 5. Tuntutan mutu 6. Akunntansi biaya tenaga kerja 7. Rencana upah insentif 8. Kurva belajar 9. Latihan kasus <strong>Pengertian Tenaga Kerja</strong> Biaya tenaga kerja adalah jumlah upah dan gaji yang dibayarkan kepada para pekerja (labour cost). Biaya tenaga kerja adalah untuk pembayaran yang dinamakan “upah”. Beda halnya dengan Gaji. Jika gaji merupakan pembayaran kepada tenaga kerja atau karyawan yang didasarkan pada rentang waktu seperti gaji mingguan, bulanan dan lain sebagainya. Sedangkan, upah dibebankan melalui rekening biaya tenaga kerja langsung, dan gaji dibebankan melalui rekening biaya overhead pabrik.
description: PERTEMUAN 9_ 07 NOVEMBER 2022_PENGENDALIAN BIAYA TENAGA KERJA, AKUNTANSI BIAYA _UNIVERSITAS GRESIK JAM 20.00-21.30
DOI: 10.5281/zenodo.7266320
title: PERTEMUAN 9_ 07 NOVEMBER 2022_PENGENDALIAN BIAYA TENAGA KERJA, AKUNTANSI BIAYA _UNIVERSITAS GRESIK JAM 20.00-21.30

description: <strong>Capaian Pembelajan Mata Kuliah (CPMK)</strong> Setelah megikuti perkuliahan ini mahasiswa Mampu menghitung dan mengerjakan Pengendalian: Biaya Tenaga Kerja <strong>Indikator Pembelajaran</strong> 1. Karakteristik tenaga kerja 2. Pengendalian biaya tenaga kerja 3. Produktivitas tenaga kerja 4. Pengukuran produktivitas 5. Tuntutan mutu 6. Akunntansi biaya tenaga kerja 7. Rencana upah insentif 8. Kurva belajar 9. Latihan kasus <strong>Pengertian Tenaga Kerja</strong> Biaya tenaga kerja adalah jumlah upah dan gaji yang dibayarkan kepada para pekerja (labour cost). Biaya tenaga kerja adalah untuk pembayaran yang dinamakan “upah”. Beda halnya dengan Gaji. Jika gaji merupakan pembayaran kepada tenaga kerja atau karyawan yang didasarkan pada rentang waktu seperti gaji mingguan, bulanan dan lain sebagainya. Sedangkan, upah dibebankan melalui rekening biaya tenaga kerja langsung, dan gaji dibebankan melalui rekening biaya overhead pabrik.
description: PERTEMUAN 9_ 07 NOVEMBER 2022_PENGENDALIAN BIAYA TENAGA KERJA, AKUNTANSI BIAYA _UNIVERSITAS GRESIK JAM 20.00-21.30