cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.25416/ntr.24236200
title: ELDeR slidedeck

description: The Edinburgh Learning Design Roadmap (ELDeR), created in 2016, is a practical, team-based approach to learning design, based on the University of Northampton’s CAIeRO approach. ELDeR also incorporates elements of other learning design tools and approaches, including the Open University’s Curriculum Feature cards, the University of Ulster’s Viewpoints toolkit, and University College London’s ABC method.<br> These open resources can be used to facilitate collaborative workshops, which will enable academic teams to develop a detailed blueprint of their learning design, together with a comprehensive action plan.<br> The student learning experience is at the heart of ELDeR. Student feedback and assessment literacies are given top priority, and a shared vision of the programme is developed between team members. By considering what students should be able to do by the end of the programme, and how they will know that they are getting there, a foundation is set for authentic assessment that aligns with learning outcomes.The principles behind ELDeR It is efficient: the initial investment of time developing a robust design means less ad hoc adjustment later. It is a creative, supportive and collaborative process: tackling problems together results in better solutions and strengthens the team. It is a safe space: everyone’s input is valued, and there are no silly questions. It is an invaluable staff development tool: in particular, it supports and builds the confidence of staff who are new to teaching. It is invaluable for programme directors: it provides an overview of the programme so that gaps and duplications can be identified and addressed.
DOI: 10.25416/ntr.24236200.v1
title: ELDeR slidedeck

description: The Edinburgh Learning Design Roadmap (ELDeR), created in 2016, is a practical, team-based approach to learning design, based on the University of Northampton’s CAIeRO approach. ELDeR also incorporates elements of other learning design tools and approaches, including the Open University’s Curriculum Feature cards, the University of Ulster’s Viewpoints toolkit, and University College London’s ABC method.<br> These open resources can be used to facilitate collaborative workshops, which will enable academic teams to develop a detailed blueprint of their learning design, together with a comprehensive action plan.<br> The student learning experience is at the heart of ELDeR. Student feedback and assessment literacies are given top priority, and a shared vision of the programme is developed between team members. By considering what students should be able to do by the end of the programme, and how they will know that they are getting there, a foundation is set for authentic assessment that aligns with learning outcomes.The principles behind ELDeR It is efficient: the initial investment of time developing a robust design means less ad hoc adjustment later. It is a creative, supportive and collaborative process: tackling problems together results in better solutions and strengthens the team. It is a safe space: everyone’s input is valued, and there are no silly questions. It is an invaluable staff development tool: in particular, it supports and builds the confidence of staff who are new to teaching. It is invaluable for programme directors: it provides an overview of the programme so that gaps and duplications can be identified and addressed.
DOI: 10.21223/e95zj1/qnwjyv
title: 03_Material_list.txt

description: :unav
DOI: 10.21223/e95zj1/xf9nj9
title: 01_Fieldbook_TVIT200609_LAVICT_Inmadure_.txt

description: :unav
DOI: 10.21223/e95zj1/nafygg
title: TCAR200609_LAVICT_Inmadure.xls

description: :unav
DOI: 10.21223/e95zj1/vkka3n
title: 02_Fieldbook_TCAR200609_LAVICT_Inmadure_.txt

description: :unav
DOI: 10.5281/zenodo.8401277
title: JusBrasilRec: A large-scale dataset of user sessions for recommendations on the legal domain

description: <strong>JusBrasilRec: A large-scale dataset of user sessions for recommendations on the legal domain</strong> The proliferation of legal documents in various formats and their dispersion across multiple courts present a significant challenge for users seeking precise matches to their information requirements. Despite notable advancements in legal information retrieval systems, research into legal recommender systems remains limited. A plausible factor contributing to this scarcity could be the absence of extensive publicly accessible datasets or benchmarks. Jusbrasil (https://www.jusbrasil.com.br) is known as the largest legal search portal in Brazil. It provides an online environment where users can find the legal documents that best match their information needs. With millions of user interactions to billions of documents containing different artifacts related to law in Brazil, Jusbrasil appears as a large-scale test bed for advancing research on the still scarce area of legal recommender systems. Therefore, we collected and made available the <strong>JusBrasilRec</strong>, a dataset containing user sessions from Jusbrasil for recommendations on the legal domain. Additionally, we also computed and made available a TF-IDF matrix from the textual content of the documents in Jusbrasil. The following files are available for download from JusBrasilRec: <strong>jusbrasilrec_dataset.zip:</strong> a compacted file containing the user sessions; <strong>jusbrasilrec_tfidf_matrix.zip:</strong> a compacted file containing the TF-IDF matrix; <strong>readme.txt:</strong> a text file explaining the content and format of the previous files. <strong>How to cite the dataset:</strong> Marcos Aurélio Domingues, Edleno Silva de Moura, Leandro Balby Marinho and Altigran da Silva. A Large Scale Benchmark for Session-based Recommendations on the Legal Domain. Artificial Intelligence and Law. 2023.
DOI: 10.5281/zenodo.8401278
title: JusBrasilRec: A large-scale dataset of user sessions for recommendations on the legal domain

description: <strong>JusBrasilRec: A large-scale dataset of user sessions for recommendations on the legal domain</strong> The proliferation of legal documents in various formats and their dispersion across multiple courts present a significant challenge for users seeking precise matches to their information requirements. Despite notable advancements in legal information retrieval systems, research into legal recommender systems remains limited. A plausible factor contributing to this scarcity could be the absence of extensive publicly accessible datasets or benchmarks. Jusbrasil (https://www.jusbrasil.com.br) is known as the largest legal search portal in Brazil. It provides an online environment where users can find the legal documents that best match their information needs. With millions of user interactions to billions of documents containing different artifacts related to law in Brazil, Jusbrasil appears as a large-scale test bed for advancing research on the still scarce area of legal recommender systems. Therefore, we collected and made available the <strong>JusBrasilRec</strong>, a dataset containing user sessions from Jusbrasil for recommendations on the legal domain. Additionally, we also computed and made available a TF-IDF matrix from the textual content of the documents in Jusbrasil. The following files are available for download from JusBrasilRec: <strong>jusbrasilrec_dataset.zip:</strong> a compacted file containing the user sessions; <strong>jusbrasilrec_tfidf_matrix.zip:</strong> a compacted file containing the TF-IDF matrix; <strong>readme.txt:</strong> a text file explaining the content and format of the previous files. <strong>How to cite the dataset:</strong> Marcos Aurélio Domingues, Edleno Silva de Moura, Leandro Balby Marinho and Altigran da Silva. A Large Scale Benchmark for Session-based Recommendations on the Legal Domain. Artificial Intelligence and Law. 2023.
DOI: 10.21223/e95zj1/lwaynn
title: 04_Datadictionary.txt

description: :unav
DOI: 10.21223/e95zj1/qswoag
title: TVIT200609_LAVICT_Inmadure.xls

description: :unav
DOI: 10.21223/e95zj1
title: Dataset for: Nutritional Analysis of native potato in Huancayo - Junin, 2006

description: A study of vitamin C and carotenoid compounds was carried out on six varieties of native potatoes using a Completely Randomized Design (CRD). This assessment was conducted with planted materials in the Junin region during the year 2006.
DOI: 10.5519/qd.fhwcnhth
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (1279 records)
DOI: 10.5066/p9ywr2y2
title: Basin characteristics data for the Washington, D.C. StreamStats application

description: This data was created to support the Washington D.C. StreamStats project funded by the Washington D.C. Department of Energy and Environment (DOEE). The data release contains high-resolution (1-meter) land cover data layers for Washington D.C. and its tributaries that represent canopy cover, canopy cover with building and road coverage removed (?pervious canopy?), impervious cover, slope (in units of percent rise), and 30-year normal annual precipitation (1991-2020). The data are hosted online as a component of the USGS StreamStats web application (https://streamstats.usgs.gov), where users can interact with a map of Washington D.C.?s stormwater pipe system and delineate drainage basins that account for pipe flow. For drainage basins delineated in Washington D.C., the user can choose to produce a report of basin characteristic statistics. The contents of this data release includes the following GeoTiffs: ?tc_all.tif: 1-meter tree canopy layer derived from the Chesapeake Bay Program?s (CBP) Chesapeake Bay Land Use and Land Cover (LULC) Database 2022 Edition for 2017 (CBP, 2023). ?tc_p.tif: 1-meter ?pervious? tree canopy layer that represents canopy with canopy over buildings and impervious extents removed. This data is derived from the Chesapeake Bay Program?s Chesapeake Bay Land Use and Land Cover (LULC) Database 2022 Edition for 2017 (CBP,2023). ?imperv.tif: 1-meter impervious surface layer derived from the Chesapeake Bay Program?s Chesapeake Bay Land Use and Land Cover (LULC) Database 2022 Edition for 2017 (CBP, 2023). ?precip.tif: 800-meter resolution 30-year normal (1991-2020) annual precipitation collected from the PRISM Climate Group at Oregon State University (PRISM CG, 2022). ?slp_pctr.tif: 1-meter resolution slope layer in units of percent rise derived from 2018 LiDAR digitial elevation models (DEMs) for Washington D.C. and its tributaries (6 HUC-12 watersheds: NW Branch Anacostia, Lower Rock Creek, Nichols Run Potomac River, Lower Anacostia River, Pimmit Run- Potomac River, and Fourmile Run- Potomac River; Katoski and others, 2023) References: Chesapeake Bay Program, 2023, Chesapeake Bay Land Use and Land Cover (LULC) Database 2022 Edition: U.S. Geological Survey data release, https://doi.org/10.5066/P981GV1L. Katoski, M.P., Steeves, P.A., Onyullo, G.E., 2023, Digital elevation model and derivative datasets to support the integration of stormwater drainage into the Washington, D.C. Stormwater StreamStats application: U.S. Geological Survey data release, https://doi.org/10.5066/P9AJLI3I. PRISM Climate Group, Oregon State University, 2022, United States Annual 30-year Normal Precipitation, 1991-2020 (800m; BIL), https://prism.oregonstate.edu.
DOI: 10.3886/4gcq-vy88
title: Liberia Compact - Mt. Coffee and Capacity Building and Sector Reform: Final Analysis Report
DOI: 10.5519/qd.hsrgr55v
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (246 records)
DOI: 10.5281/zenodo.8403868
title: Cook_Tree

description: Network representation of a tree
DOI: 10.5281/zenodo.8403869
title: Cook_Tree

description: Network representation of a tree
DOI: 10.5281/zenodo.8403848
title: Cook_GasometerPforzheim

description: The Gasometer Pforzheim
DOI: 10.5281/zenodo.8403849
title: Cook_GasometerPforzheim

description: The Gasometer Pforzheim
DOI: 10.5281/zenodo.8403840
title: Cook_AlamilloBridge

description: The Alamillo Bridge
DOI: 10.5281/zenodo.8403841
title: Cook_AlamilloBridge

description: The Alamillo Bridge
DOI: 10.5281/zenodo.8403830
title: Cook_BorisovArena

description: The Borisov Arena
DOI: 10.5281/zenodo.8403831
title: Cook_BorisovArena

description: The Borisov Arena
DOI: 10.5281/zenodo.8000167
title: Data for "Why are Mountaintops Cold? The Transition of Surface Lapse Rate on Dry Planets"

description: Edited by Bowen Fan on 06/02/2023 0. This Dataset is for the paper “Why are Mountaintops Cold? The Transition of Surface Lapse Rate on Dry Planets”. 1. data_Fig1.mat: data for figure 1<br> Lon: longitude<br> Lat: latitude<br> Ts: surface temperature (unit in K) as a function of longitude, latitude, and case. <br> Z: surface elevation (unit in meter) as a function of longitude latitude, and case. <br> A: surface lapse rate (unit in %) for the cases in figure 1c<br> A1, A2, A3, A4, A5, A6: surface lapse rate (unit in %) for the cases in figure 1d<br> B1, B2, B3, B4, B5, B6: surface lapse rate (unit in %) for the cases in figure 1e 2. data_Fig2.mat: data for figure 2<br> GSW: net solar heating (unit in W/m2) as a function of longitude, latitude, and case. <br> GLW: atmospheric heating (unit in W/m2) as a function of longitude, latitude, and case.<br> TSK: surface emission (unit in W/m2) as a function of longitude, latitude, and case.<br> HFX: sensible cooling (unit in W/m2) as a function of longitude, latitude, and case. 3. data_Fig3.mat: data for figure 3<br> LWS_diff: the absolute value of the difference of surface emission between highland and lowland <br> LWA_diff: the absolute value of the difference of atmospheric emission between highland and lowland <br> SH_diff: the absolute value of the difference of sensible heat flux between highland and lowland 4. data_Fig4.mat: data for figure 4<br> 4a. Cases with varied greenhouse forcing<br> SW_G LWA_G LWS_G SH_G: surface energy budgets from the GCM. The dimensions are location (1 for highland, 2 for lowland) and case.<br> LWA1_G, LWS1_G, SH1_G: surface energy budgets from the highland part of two-column model<br> LWA4_G, LWS4_G, SH4_G: surface energy budgets from the lowland part of two-column model<br> 4b. Cases with varied surface pressure<br> SW_A LWA_A LWS_A SH_A: surface energy budgets from the GCM. The dimensions are location (1 for highland, 2 for lowland) and case.<br> LWA1_A, LWS1_A, SH1_A: surface energy budgets from the highland part of two-column model<br> LWA4_A, LWS4_A, SH4_A: surface energy budgets from the lowland part of two-column model
DOI: 10.5281/zenodo.8404015
title: GE Discovery TOF MI PET NEMA IQ projector benchmark listmode data

description: ## LIST0000.BLF listmode file from GE Discvoery MI PET/CT containing all acquired emission events (HDF5)<br> of a single bed position NEMA IQ phantom acq. ## corrections.h5 file containing all quantitative corrections estimate using GE's duetto tool box (HDF5) - correction_lists/sens -&gt; sensivity value for acquired events<br> - correction_lists/atten -&gt; attenuation value for acquired events<br> - correction_lists/contam -&gt; additive contaminations (randoms + scatter) for all acquired events<br> - all_xtals/atten -&gt; attenuation values for all possible crystal combinations<br> - all_xtals/sens -&gt; sensitivity values for all possible crystal combinations<br> - all_xtals/xtal_ids -&gt; all possible crystal combinations
DOI: 10.5281/zenodo.8404014
title: GE Discovery TOF MI PET NEMA IQ projector benchmark listmode data

description: ## LIST0000.BLF listmode file from GE Discvoery MI PET/CT containing all acquired emission events (HDF5)<br> of a single bed position NEMA IQ phantom acq. ## corrections.h5 file containing all quantitative corrections estimate using GE's duetto tool box (HDF5) - correction_lists/sens -&gt; sensivity value for acquired events<br> - correction_lists/atten -&gt; attenuation value for acquired events<br> - correction_lists/contam -&gt; additive contaminations (randoms + scatter) for all acquired events<br> - all_xtals/atten -&gt; attenuation values for all possible crystal combinations<br> - all_xtals/sens -&gt; sensitivity values for all possible crystal combinations<br> - all_xtals/xtal_ids -&gt; all possible crystal combinations
DOI: 10.3886/xfe9-z980
title: Liberia Compact - Mt. Coffee and Capacity Building and Sector Reform: Final Analysis Report
DOI: 10.7924/r4fj2p230
title: Data and scripts from: Development of a machine-learning finite-range nonlocal density functional

description: Kohn-Sham density functional theory has been the most popular method in electronic structure calculations. To fulfill the increasing accuracy requirements, new approximate functionals are needed to address key issues in existing approximations. It is well known that nonlocal components are crucial. Current nonlocal functionals mostly require orbital dependence such as in Hartree-Fock exchange and many-body perturbation correlation energy, which, however, leads to higher computational costs. Deviating from this pathway, we describe functional nonlocality in a new approach. By partitioning the total density to atom-centered local densities, a many-body expansion is proposed. This many-body expansion can be truncated at one-body contributions, if a base functional is used and an energy correction is approximated. The contribution from each atom-centered local density is a single finite-range nonlocal functional that is universal for all atoms. We then use machine learning to develop this universal atom-centered functional. Parameters in this functional is determined by fitting to data that are produced by high-level theories. Extensive tests on several different test sets, which include reaction energies, reaction barrier heights and non-covalent interaction energies, show that the new functional, with only the density as the basic variable, can produce results comparable to the best-performing double-hybrid functionals with a lower computational cost. This opens a new pathway to nonlocal functional development and applications. 

This dataset contains: modified MGCDB84, GMTKN55 and MOR41 data files; calculated BLYP wave function files; modified dftd3 program and DFT-D3(BJ) internal data it generated; python scripts used to generate power spectra and the power spectra it calculated; training, validation and test data; python scripts used to train and evaluate the PyTorch model and the resulting models; and the python script generated the carbon atom energy plot.
DOI: 10.6084/m9.figshare.24239182
title: Horticulturae Data FR Lettuce Seedlings.pdf

description: Supplemental far-red radiation to promote lettuce seedling growth.
DOI: 10.6084/m9.figshare.24239182.v1
title: Horticulturae Data FR Lettuce Seedlings.pdf

description: Supplemental far-red radiation to promote lettuce seedling growth.
DOI: 10.5281/zenodo.7404865
title: Data for "Coupled carbon and nitrogen cycling regulates the cnidarian-algal symbiosis"

description: Raw data associated with the publication "Coupled carbon and nitrogen cycling regulates the cnidarian-algal symbiosis". Data for experiment 1 and 2 are uploaded as individual sheets/tabs in the .xslx file. "Exp1NanoSIMS" contains data for NanoSIMS analyses for experiment 1 (Fig. 1). "Exp2Physiology" contains data for NanoSIMS analyses for experiment 2 (Fig. 2, Fig. 3, Fig. S1, Fig. S3). "Exp2NanoSIMS" contains data for NanoSIMS analyses for experiment 2 (Fig. 2, Fig. S2, Fig. S3).
DOI: 10.5281/zenodo.8183702
title: Data for "Coupled carbon and nitrogen cycling regulates the cnidarian-algal symbiosis"

description: Raw data associated with the publication "Coupled carbon and nitrogen cycling regulates the cnidarian-algal symbiosis". Data associated with individual figures and corresponding analyses are uploaded as separate tabs in the Excel file.
DOI: 10.5281/zenodo.7404864
title: Data for "Coupled carbon and nitrogen cycling regulates the cnidarian-algal symbiosis"

description: Raw data associated with the publication "Coupled carbon and nitrogen cycling regulates the cnidarian-algal symbiosis". Data associated with individual figures and corresponding analyses are uploaded as separate tabs in the Excel file. Radecker_etal_NanoSIMS.zip contains the individual NanoSIMS images (names according to treatment). Radecker_etal_Chlorophyll_Fluorescence_Images.zip contains exemplary photographs of chlorophyll fluorescence of Aiptasia (names according to treatment).
DOI: 10.5281/zenodo.8403627
title: Data for "Coupled carbon and nitrogen cycling regulates the cnidarian-algal symbiosis"

description: Raw data associated with the publication "Coupled carbon and nitrogen cycling regulates the cnidarian-algal symbiosis". Data associated with individual figures and corresponding analyses are uploaded as separate tabs in the Excel file. NanoSIMS.zip contains the individual NanoSIMS images (names according to treatment).
DOI: 10.5281/zenodo.8404146
title: Data for "Coupled carbon and nitrogen cycling regulates the cnidarian-algal symbiosis"

description: Raw data associated with the publication "Coupled carbon and nitrogen cycling regulates the cnidarian-algal symbiosis". Data associated with individual figures and corresponding analyses are uploaded as separate tabs in the Excel file. Radecker_etal_NanoSIMS.zip contains the individual NanoSIMS images (names according to treatment). Radecker_etal_Chlorophyll_Fluorescence_Images.zip contains exemplary photographs of chlorophyll fluorescence of Aiptasia (names according to treatment).
DOI: 10.17603/ds2-db7h-t150
title: Soil-Foundation-Structure Interaction Effects on the Cyclic Failure Potential of Silts and Clays

description: Earthquake-induced ground failure has resulted in billions of dollars of damage during recent earthquakes. Soils can be broadly characterized as exhibiting either "sand-like" or "clay-like" behavior with respect to strength loss during earthquakes. This project focuses on cyclic failure of "clay-like" soils, which are less well understood than "sand-like" soils. Cyclic failure of fine-grained soils are often constrained to the regions beneath structures, and not in the free-field soils away from the structures, indicating that soil-foundation-structure interaction plays an important role. This project utilizes centrifuge model testing to study cyclic failure of fine-grained soils beneath structures. This research has produced publicly accessible datasets containing all of the experimental measurements and metadata required for users to make sense of the data.
DOI: 10.17603/ds2bw9w
title: Sandbar Sediment Transport

description: Experimental data collection from the Oregon State University Large Wave Flume associated with sediment transport over a surf zone sandbar. Data were collected from a variety of sensors on the sandbar crest and consist of velocity profiles, water depth, suspended sediment concentration and sheet flow sediment concentration. Offshore forcing conditions from the wave paddle are also provided.
DOI: 10.17603/ds2zq3q
title: Full-Scale Simulation of Peak Responses to Reduce Hurricane Damage to Low Buildings and Use of Related Research to Develop Hurricane-Engineering Expertise

description: The objective of this Faculty Early Career Development (CAREER) Program award is to ascertain the effects of roof shapes and coverings on uplift pressures and the dynamic response of flexible roofing systems subjected to hurricane winds.