cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.14457/tu.the.2022.1686
title: The effects of collaborative CLIL teaching between an ESP teacher and pr professionals on the improvement of students’ content knowledge, specialized language, and awareness of professional culture

description: Despite the growing interest in the implementation of CLIL in various educational contexts, the majority of research has focused on the collaboration between language teachers and content teachers, and very little attention has been given to the PR ESP sector. Therefore, the present study aims to explore the effectiveness of a collaborative CLIL partnership between an ESP teacher and industry specialists outside of the classroom in an English for PR elective course at a public university in Thailand. To achieve this goal, a panel of subject matter experts in PR and related industries was involved in the design and development of the course. One PR expert also attended a class and shared with students her practical experience. The effectiveness of the collaborative CLIL teaching was then evaluated using pre- and post-testing of the students. In addition, the learning development of the students was observed and documented through learning logs. At the conclusion of the course, semi-structured interviews and student opinion evaluation questionnaire were conducted to gather feedback from the students. The findings of the study indicate that the collaborative CLIL teaching had positive outcomes for the students' PR content knowledge, specialized language, awareness of professional culture and motivation, as well as an increased sense of authenticity in the ESP classroom. The majority of students also expressed positive opinions about the course, with high marks given to the lesson plans, teaching methods and activities, evaluation, and special guest speaker. Most importantly, it was proven that the students' self-efficacy grew as a result of the collaborative CLIL teaching, thus filling a pedagogical PR research need and closing the gap between theory and practice. Given these results, it can be concluded that the collaborative CLIL partnership between an ESP teacher and industry specialists outside of the classroom can contribute to promoting self-efficacy of L2 students in the PR field. However, it is important to note that such integration should be conducted with careful planning to gain the greatest possible advantages. This study provides a valuable contribution to the growing body of research on CLIL and suggests that further exploration of the potential benefits of collaborative CLIL partnerships in ESP contexts is warranted.
DOI: 10.15468/dl.e8z45d
title: Occurrence Download

description: A dataset containing 12 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Glyptocephalus zachirus",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Year is greater than or equal to 1880",
 "Year is less than or equal to 1889"
 ]
}

 The dataset includes 12 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0040310-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.11075729
title: Replication Data for 'Room temperature observation of the anomalous in-plane Hall effect in a Weyl ferromagnet'

description: The zip file contains the raw data for Figs.1-5 of the main text. All data processing to obtain the final plots are described in the main text, Methods section, and Suppl. Materials. All other data that support the findings of this study are available from the corresponding authors upon request
description: Topologically nontrivial electronic states can lead to novel anomalous Hall effects, with room temperature manifestations promising for applications in magnetic sensing, spintronics, and energy harvesting. The anomalous in-plane Hall effect is expected in topological magnetic materials under an in-plane magnetic field, but its detection has been challenging due to strict symmetry requirements. Here, we combine molecular beam epitaxy of the kagome metal Fe$_3$Sn, electric Hall effect measurements, and theoretical calculations to propose and demonstrate that the kagome lattice motif combined with with spin-orbit coupling and canted ferromagnetism induces the anomalous in-plane Hall effect at room temperature via topological Weyl points. Additionally, we synthesize a topological thin-film heterostructure with Fe$_3$Sn and ferromagnetic CoFeB, showing enhanced anomalous in-plane Hall effect amplitude due to CoFeB's magnetic stray field. This work establishes a design framework for topological magnets and heterostructures aimed at discovering and controlling anomalous Hall effects for technological applications.
DOI: 10.5281/zenodo.11075730
title: Replication Data for 'Room temperature observation of the anomalous in-plane Hall effect in a Weyl ferromagnet'

description: The zip file contains the raw data for Figs.1-5 of the main text. All data processing to obtain the final plots are described in the main text, Methods section, and Suppl. Materials. All other data that support the findings of this study are available from the corresponding authors upon request
description: Topologically nontrivial electronic states can lead to novel anomalous Hall effects, with room temperature manifestations promising for applications in magnetic sensing, spintronics, and energy harvesting. The anomalous in-plane Hall effect is expected in topological magnetic materials under an in-plane magnetic field, but its detection has been challenging due to strict symmetry requirements. Here, we combine molecular beam epitaxy of the kagome metal Fe$_3$Sn, electric Hall effect measurements, and theoretical calculations to propose and demonstrate that the kagome lattice motif combined with with spin-orbit coupling and canted ferromagnetism induces the anomalous in-plane Hall effect at room temperature via topological Weyl points. Additionally, we synthesize a topological thin-film heterostructure with Fe$_3$Sn and ferromagnetic CoFeB, showing enhanced anomalous in-plane Hall effect amplitude due to CoFeB's magnetic stray field. This work establishes a design framework for topological magnets and heterostructures aimed at discovering and controlling anomalous Hall effects for technological applications.
DOI: 10.15468/dl.rchehu
title: Occurrence Download

description: A dataset containing 5 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Glyptocephalus zachirus",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Year is greater than or equal to 1890",
 "Year is less than or equal to 1899"
 ]
}

 The dataset includes 5 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0040311-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.13140/rg.2.2.15256.25604
title: RRR-CHALLENGE EPS005 - Data for Constructing Probability Distribution and Density Curves (GCG) GCG STEP 02 HISTOGRAM
DOI: 10.15468/dl.9dv6n9
title: Occurrence Download

description: A dataset containing 92 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Leptomastix dactylopii"
 ]
}

 The dataset includes 92 records from 13 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0040313-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.fq9zpa
title: Occurrence Download

description: A dataset containing 24 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Glyptocephalus zachirus",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Year is greater than or equal to 1900",
 "Year is less than or equal to 1909"
 ]
}

 The dataset includes 24 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0040314-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.25740/sb4q-wj06
title: 2011 Machine Learning Data Set for NASA's Solar Dynamics Observatory - Atmospheric Imaging Assembly

description: We present a curated dataset from the NASA Solar Dynamics Observatory (SDO) mission in a format suitable for machine learning research. Beginning from level 1 scientific products we have processed various instrumental corrections, downsampled to manageable spatial and temporal resolutions, and synchronized observations spatially and temporally. We anticipate this curated dataset will facilitate machine learning research in heliophysics and the physical sciences generally, increasing the scientific return of the SDO mission. This work is a deliverable of the 2018 NASA Frontier Development Lab program. This page includes data from 2011. Data from 2010 and 2012-2018 are also available. See links to related items elsewhere on this page.
DOI: 10.25740/1vyz-b592
title: 2012 Machine Learning Data Set for NASA's Solar Dynamics Observatory - Atmospheric Imaging Assembly

description: We present a curated dataset from the NASA Solar Dynamics Observatory (SDO) mission in a format suitable for machine learning research. Beginning from level 1 scientific products we have processed various instrumental corrections, downsampled to manageable spatial and temporal resolutions, and synchronized observations spatially and temporally. We anticipate this curated dataset will facilitate machine learning research in heliophysics and the physical sciences generally, increasing the scientific return of the SDO mission. This work is a deliverable of the 2018 NASA Frontier Development Lab program. This page includes data from 2012. Data from 2010, 2011, and 2013-2018 are also available. See links to related items elsewhere on this page.
DOI: 10.25740/2zme-3q44
title: 2013 Machine Learning Data Set for NASA's Solar Dynamics Observatory - Atmospheric Imaging Assembly

description: We present a curated dataset from the NASA Solar Dynamics Observatory (SDO) mission in a format suitable for machine learning research. Beginning from level 1 scientific products we have processed various instrumental corrections, downsampled to manageable spatial and temporal resolutions, and synchronized observations spatially and temporally. We anticipate this curated dataset will facilitate machine learning research in heliophysics and the physical sciences generally, increasing the scientific return of the SDO mission. This work is a deliverable of the 2018 NASA Frontier Development Lab program. This page includes data from 2013. Data from 2010-2012 and 2014-2018 are also available. See links to related items elsewhere on this page.
DOI: 10.15468/dl.axkad5
title: Occurrence Download

description: A dataset containing 3 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Glyptocephalus zachirus",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Year is greater than or equal to 1910",
 "Year is less than or equal to 1919"
 ]
}

 The dataset includes 3 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0040315-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.25740/3jhw-x180
title: 2014 Machine Learning Data Set for NASA's Solar Dynamics Observatory - Atmospheric Imaging Assembly

description: We present a curated dataset from the NASA Solar Dynamics Observatory (SDO) mission in a format suitable for machine learning research. Beginning from level 1 scientific products we have processed various instrumental corrections, downsampled to manageable spatial and temporal resolutions, and synchronized observations spatially and temporally. We anticipate this curated dataset will facilitate machine learning research in heliophysics and the physical sciences generally, increasing the scientific return of the SDO mission. This work is a deliverable of the 2018 NASA Frontier Development Lab program. This page includes data from 2014. Data from 2010-2013 and 2015-2018 are also available. See links to related items elsewhere on this page.
DOI: 10.25740/0fbp-re41
title: 2015 Machine Learning Data Set for NASA's Solar Dynamics Observatory - Atmospheric Imaging Assembly

description: We present a curated dataset from the NASA Solar Dynamics Observatory (SDO) mission in a format suitable for machine learning research. Beginning from level 1 scientific products we have processed various instrumental corrections, downsampled to manageable spatial and temporal resolutions, and synchronized observations spatially and temporally. We anticipate this curated dataset will facilitate machine learning research in heliophysics and the physical sciences generally, increasing the scientific return of the SDO mission. This work is a deliverable of the 2018 NASA Frontier Development Lab program. This page includes data from 2015. Data from 2010-2014 and 2016-2018 are also available. See links to related items elsewhere on this page.
DOI: 10.25740/64cr-bc95
title: 2016 Machine Learning Data Set for NASA's Solar Dynamics Observatory - Atmospheric Imaging Assembly

description: We present a curated dataset from the NASA Solar Dynamics Observatory (SDO) mission in a format suitable for machine learning research. Beginning from level 1 scientific products we have processed various instrumental corrections, downsampled to manageable spatial and temporal resolutions, and synchronized observations spatially and temporally. We anticipate this curated dataset will facilitate machine learning research in heliophysics and the physical sciences generally, increasing the scientific return of the SDO mission. This work is a deliverable of the 2018 NASA Frontier Development Lab program. This page includes data from 2016. Data from 2010-2015, 2017, and 2018 are also available. See links to related items elsewhere on this page.
DOI: 10.25740/c8bw-ar96
title: 2017 Machine Learning Data Set for NASA's Solar Dynamics Observatory - Atmospheric Imaging Assembly

description: We present a curated dataset from the NASA Solar Dynamics Observatory (SDO) mission in a format suitable for machine learning research. Beginning from level 1 scientific products we have processed various instrumental corrections, downsampled to manageable spatial and temporal resolutions, and synchronized observations spatially and temporally. We anticipate this curated dataset will facilitate machine learning research in heliophysics and the physical sciences generally, increasing the scientific return of the SDO mission. This work is a deliverable of the 2018 NASA Frontier Development Lab program. This page includes data from 2017. Data from 2010-2016 and 2018 are also available. See links to related items elsewhere on this page.
DOI: 10.25740/g12a-8515
title: Transient osmotic perturbation causes long-term alteration to the gut microbiota

description: "Osmotic diarrhea is a prevalent condition in humans caused by food intolerance, malabsorption, and widespread laxative use. Here, we assess the resilience of the gut ecosystem to osmotic perturbation at multiple length and time scales using mice as model hosts. Osmotic stress caused reproducible extinction of highly abundant taxa and expansion of less prevalent members in human and mouse microbiotas. Quantitative imaging revealed decimation of the mucus barrier during osmotic perturbation, followed by recovery. The immune system exhibited temporary changes in cytokine levels and a lasting IgG response against commensal bacteria. Increased osmolality prevented growth of commensal strains in vitro, revealing one mechanism contributing to extinction. Environmental availability of microbiota members mitigated extinction events, demonstrating how species reintroduction can impact community resilience. Our findings demonstrate that even mild osmotic diarrhea can cause lasting changes to the microbiota and host, and lay the foundation for interventions that increase system-wide resilience.The data presented here represents the 16S, transcriptomics and metagenomics sequencing files for the study and the associated metadata. Each file refers to a figure in the manuscript and is matched to its mapping file with the corresponding file name."
DOI: 10.25740/pknx-5s37
title: 2018 Machine Learning Data Set for NASA's Solar Dynamics Observatory - Atmospheric Imaging Assembly

description: We present a curated dataset from the NASA Solar Dynamics Observatory (SDO) mission in a format suitable for machine learning research. Beginning from level 1 scientific products we have processed various instrumental corrections, downsampled to manageable spatial and temporal resolutions, and synchronized observations spatially and temporally. We anticipate this curated dataset will facilitate machine learning research in heliophysics and the physical sciences generally, increasing the scientific return of the SDO mission. This work is a deliverable of the 2018 NASA Frontier Development Lab program. This page includes data from 2018. Data from 2010-2017 are also available. See links to related items elsewhere on this page.
DOI: 10.15468/dl.cyeap7
title: Occurrence Download

description: A dataset containing 4 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Glyptocephalus zachirus",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Year is greater than or equal to 1920",
 "Year is less than or equal to 1929"
 ]
}

 The dataset includes 4 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0040316-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.6084/m9.figshare.30643799
title: The Proteomics of EcN-OMV and OH2@EcN-OMV

description: The Proteomics of EcN-OMV and OH2@EcN-OMV
DOI: 10.6084/m9.figshare.30643799.v1
title: The Proteomics of EcN-OMV and OH2@EcN-OMV

description: The Proteomics of EcN-OMV and OH2@EcN-OMV
DOI: 10.15468/dl.8kgjgc
title: Occurrence Download

description: A dataset containing 90171 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Cynoglossum officinale",
 "HasCoordinate is true"
 ]
}

 The dataset includes 90171 records from 857 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0040301-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.6073/pasta/dcad0e155bc26fd1af3c44d461691420
title: Juvenile Salmonid Emigration Monitoring in the Stanislaus River at Caswell Memorial State Park, California, 2017-2025

description: Overview
 Operation of rotary screw traps on the lower Stanislaus River at Caswell Memorial State Park is part of the U.S Fish and Wildlife Service’s Anadromous Fish Restoration Program and Comprehensive Assessment and Monitoring Program under the National Marine Fisheries Service Reasonable and Prudent Alternatives actions and Central Valley Project Improvement Act. The primary objectives of the study are to collect data that can be used to estimate the passage of juvenile fall-run Chinook Salmon Oncorhynchus tshawytscha and to quantify the raw catch of steelhead Oncorhynchus mykiss. Secondary objectives of the trapping operations focus on collecting biological data on juvenile salmonids and gathering environmental data that will be used to develop models that correlate environmental parameters with salmonid size, temporal presence, abundance, and production.
 The data package contains seven datasets including: raw catch, trap operation, environmental, and trap efficiency data.
 
 
 Raw Catch – Chinook Dataset
 This dataset covers ALL Chinook Salmon captured by the rotary screw traps. This spreadsheet includes biological data on: 1) unmarked fall- and spring-run Chinook Salmon 2) recaptured marked fall-run (BBY OR "Pigment / Dye", Photonic Dye, Fin Clip, and VIE OR "Elastomer") Chinook Salmon utilized in trap efficiency trials.
 
 
 Raw Catch – Steelhead Dataset
 This dataset covers ALL steelhead captured by the rotary screw traps. All steelhead captured are unmarked and presumed to be natural origin steelhead.
 
 
 Raw Catch – ByCatch Dataset
 This dataset provides biological data on ALL catch (EXCLUDING Chinook Salmon or steelhead) captured by the rotary screw traps. All catch in this table is of natural origin.
 
 
 Trap Operations Dataset
 This dataset provides trap operation data for each trap visit. Specifically, it includes data on the visit type, trap functioning status, start and end sampling dates and times, total revolutions and instantaneous revolution speeds, livewell intake statuses, debris data, and whether the catch associated for this record will be include for juvenile production estimates.
 
 
 Environmentals Dataset
 This dataset covers environmental data collected at the rotary screw traps. This spreadsheet includes turbidity (nephelometric turbidity units), water velocity (meters per second), dissolved oxygen (milligrams per liter), and water depth (centimeters).
 
 
 Trap Efficiency Summary Dataset
 This dataset provides a summary of each trap efficiency trial conducted. It includes the release date and time, the length of the test, the number of marked fish released and recaptured, and whether the trial was included for juvenile production estimates.
 
 
 Trap Efficiency Release FL Dataset
 This dataset provides biological data on a subsample of released fish utilized in trap efficiency trials.
DOI: 10.5281/zenodo.17626131
title: PRISMA Materials Gamification and Metacognition Systematic Review

description: This record contains PRISMA 2020 materials used in the systematic review titled "Gamification and the Development of Metacognitive Processes: a Systematic Literature Review".

The dataset includes: 

The PRISMA 2020 Checklist

The PRISMA 2020 Flow Diagram 

The data extraction matrix

The materials support the reproducibility of the review and comply with F1000Research´s Open Data policy. All files are openly available under a CC0 1.0 Universal license.
DOI: 10.15468/dl.45f5km
title: Occurrence Download

description: A dataset containing 23 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Glyptocephalus zachirus",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Year is greater than or equal to 1930",
 "Year is less than or equal to 1939"
 ]
}

 The dataset includes 23 records from 7 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0040317-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.b5amq4
title: Occurrence Download

description: A dataset containing 242642 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Icterus gularis",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present"
 ]
}

 The dataset includes 242642 records from 85 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0040285-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.73caaa
title: Occurrence Download

description: A dataset containing 17119 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Gyps bengalensis"
 ]
}

 The dataset includes 17119 records from 24 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0040318-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.