cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.4501306
title: Inputdata for NorESM (release-noresm2.0.2) CAM only compset cN1850 at resolution f19_tn14

description: This archive contains all the inputdata needed to run the Norwegian Earth System Model (NorESM) version release-noresm2.0.2 (https://github.com/NorESMhub/NorESM/releases/tag/release-noresm2.0.2) at 2x2 degrees resolution (f19_tn14). The compset long name is 1850_CAM60%NORESM_CLM50%SP_CICE%PRES_DOCN%DOM_MOSART_SGLC_SWAV
description: This work is funded by the Research Council of Norway in the frame of the INES project (270061)
DOI: 10.21227/zrhk-tq74
title: stagnant water

description: This datset contains 2000 images of size 256 X256. The dataset is created by captuirng photos using mobile phone. This dataset is applicable for two classes namely water and wet surface.
DOI: 10.15468/wxgcy7
title: The first record of the genus Myrmozercon Berlese (Acari: Mesostigmata: Laelapidae) in the Neotropical region and a description of a new species

description: This dataset contains the digitized treatments in Plazi based on the original journal article Trach, Viacheslav A., Khaustov, Alexander A. (2018): The first record of the genus Myrmozercon Berlese (Acari: Mesostigmata: Laelapidae) in the Neotropical region and a description of a new species. Acarologia 58 (1): 41-51, DOI: 10.24349/acarologia/20184226
DOI: 10.5285/20f3bf27-bf33-4c21-8164-005667b2ddb8
title: Fine-scale atmosphere-only model simulation of near-surface temperature and wind from a reanalysis-driven Met Office Unified Model simulation of the Brunt Ice Shelf for the year 2015

description: High-resolution simulations of near-surface (1.5 m) temperature and (10 m) zonal and meridional winds over the Brunt Ice Shelf in the Antarctic for the year 2015 were conducted using the atmosphere-only Met Office Unified Model by the British Antarctic Survey, Cambridge, UK. The datasets produced were necessary to place point meteorological measurements from the various automatic weather stations on the Brunt Ice Shelf into a wider spatial context by identifying spatial temperature gradients and investigating how such gradients may have affected the homogeneity of the composite Halley temperature record.
description: We carried out a high-resolution atmosphere-only model simulation of the Brunt Ice Shelf and surrounding area for 2015, using the nested configuration of version 11.1 of the UK Met Office Unified Model (MetUM). The inner model domain had a horizontal resolution of 1.5 km (consisting of 250 × 250 grid points), covering the Brunt Ice Shelf and surrounding area. This domain was nested within a larger outer domain with a horizontal resolution of 4 km (consisting of 200 × 200 grid points), covering a much larger part of the area surrounding the Brunt Ice Shelf. Both domains had 70 vertical levels up to an altitude of 40 km and used a rotated latitude-longitude grid. In order to construct a broadly reasonable coastline of the Brunt Ice Shelf in the innermost domain for the 2015 period, the model coastline and orography was revised using an up-to-date digital elevation model based on the TanDEM-X (TerraSAR-X Add-On for Digital Elevation Measurement) 90-m digital elevation model. The science configuration of the dynamics and physics schemes used by the nested models was the mid-latitude regional atmosphere configuration (RA1-M). The required start data and lateral boundary conditions for the nested domains were supplied by a global version run of the MetUM at N512 resolution (1024 × 768 grid points, equivalent to a horizontal resolution of ~25 km at mid-latitudes), which was itself initialised by the ERA-Interim reanalysis. The model was used to produce a series of 24 hour forecasts, initialised every 12 hours, for the period 01 January 2015, 0000UTC to 31 December 2015, 1200UTC. The initial 12 hours of each forecast was discarded as spin-up, with the remaining part of the forecasts concatenated together to form a continuous time-series for 2015.
description: The model used was version 11.1 of the Met Office Unified Model.
description: Comparison of the model output with the automatic weather station data on Brunt Ice Shelf demonstrated that: i) the model accurately captured the temporal variability of both temperature and wind speed, ii) model temperatures were biased cold, and iii) wind speed and direction were simulated accurately.
DOI: 10.25646/7967
title: Tagesdaten-CSV aus dem DIVI-Intensivregister

description: Die Tagesdaten-CSV entspricht einem Auszug der Daten des DIVI-Intensivregisters. Die Datei enthält eine Aggregation der aktuellsten Meldungen pro Landkreis. Es werden die aktuell gemeldeten Anzahlen der COVID-19 Intensivfälle sowie die gemeldeten intensivmedizinischen Behandlungskapazitäten angezeigt. Die Tagesdaten-CSV liefert dabei ausschließlich einen Blick auf die Daten gemäß dem Stand des betrachteten Tages. Die Daten sind im situationsbedingten Kontext aufbereitet, damit sind verschiedene Tagesdaten-CSVs u.U. nicht direkt miteinander vergleichbar. Die aktuellsten Meldungen werden im gewählten Betrachtungszeitfenster über alle Meldebereiche und Standorte aufsummiert. Weitere Informationen sind zu finden unter https://www.intensivregister.de/#/faq
DOI: 10.5066/f7c82781
title: USA National Phenology Network (USA-NPN) Plant and Animal Phenology Data for the United States, 2011
DOI: 10.25403/upresearchdata.13298036
title: SME access to public procurement in South African water infrastructure projects

description: Dataset for a qualitative research undertaken on SME access to public procurement in South African water infrastructure projects. The following are supporting files for this study:-Transcripts, word documents-Consent forms, PDF<br>-Secondary data, PDF
DOI: 10.25403/upresearchdata.13298036.v1
title: SME access to public procurement in South African water infrastructure projects

description: Dataset for a qualitative research undertaken on SME access to public procurement in South African water infrastructure projects. The following are supporting files for this study:-Transcripts, word documents-Consent forms, PDF<br>-Secondary data, PDF
DOI: 10.5066/f7h1300r
title: USA National Phenology Network (USA-NPN) Plant and Animal Phenology Data for the United States, 2012
DOI: 10.6084/m9.figshare.13704559.v4
title: Supplemental materials

description: Supplemental tables and figures
DOI: 10.5066/f7ms3qrt
title: USA National Phenology Network (USA-NPN) Plant and Animal Phenology Data for the United States, 2012
DOI: 10.5066/f73r0qwg
title: USA National Phenology Network (USA-NPN) Plant and Animal Phenology Data for the United States, 2009
DOI: 10.5517/ccdc.csd.cc1mc5sy
title: CCDC 1500300: Experimental Crystal Structure Determination

description: Related Article: Nicholas D. Shepherd, Yingjie Zhang, Kim T. Lu and Inna Karatchevtseva|2020|CSD Communication|||
DOI: 10.5517/ccdc.csd.cc1mc5tz
title: CCDC 1500301: Experimental Crystal Structure Determination

description: Related Article: Nicholas D. Shepherd, Yingjie Zhang, Kim T. Lu and Inna Karatchevtseva|2020|CSD Communication|||
DOI: 10.5517/ccdc.csd.cc1pq11h
title: CCDC 1570306: Experimental Crystal Structure Determination

description: Related Article: Nicholas Shepherd, Yingjie Zhang, Maxim Avdeev, ZX Cheng, Timothy Murphy, David Harman, Rongkun Zheng, Janice Aldrich-Wright|2020|CSD Communication|||
DOI: 10.5517/ccdc.csd.cc26ftbt
title: CCDC 2039066: Experimental Crystal Structure Determination

description: Related Article: Ye Meng|2020|CSD Communication|||
description: Related Article: Ye Meng, Weiwei Zhao, Jun Zheng, Daofa Jiang, Jie Gao, Yanmei Jin, Peihua Ma|2021|RSC Advances|11|3470|doi:10.1039/D0RA09074C
DOI: 10.5517/ccdc.csd.cc26fw5q
title: CCDC 2039123: Experimental Crystal Structure Determination

description: Related Article: huang linweih|2020|CSD Communication|||
DOI: 10.5517/ccdc.csd.cc1mc5v0
title: CCDC 1500302: Experimental Crystal Structure Determination

description: Related Article: Yingjie Zhang, Jason Roy Price|2020|CSD Communication|||
DOI: 10.5517/ccdc.csd.cc26g0c2
title: CCDC 2039253: Experimental Crystal Structure Determination

description: Related Article: Frederic Bruyneel, Reinhard Neier and Helen Stoeckli-Evans|2020|CSD Communication|||
DOI: 10.5517/ccdc.csd.cc26g1j8
title: CCDC 2039289: Experimental Crystal Structure Determination

description: Related Article: F. Knoch, D. Sellmann, T. Gottschalk-Gaudig|2020|CSD Communication|||
DOI: 10.5517/ccdc.csd.cc26g720
title: CCDC 2039461: Experimental Crystal Structure Determination

description: Related Article: Martin Schoeller, Jan Moncol|2020|CSD Communication|||
DOI: 10.5517/ccdc.csd.cc26g7c9
title: CCDC 2039470: Experimental Crystal Structure Determination

description: Related Article: Benjamin G. Harvey, Atta M. Arif, Richard D. Ernst|2020|CSD Communication|||
DOI: 10.5517/ccdc.csd.cc26gd8c
title: CCDC 2039622: Experimental Crystal Structure Determination

description: Related Article: Andrew D. Bond, Hao-Che Niu, Dominic S. Wright|2020|CSD Communication|||
DOI: 10.5517/ccdc.csd.cc26ggqw
title: CCDC 2039698: Experimental Crystal Structure Determination

description: Related Article: F. Knoch, D. Sellmann, S. Emig|2020|CSD Communication|||
DOI: 10.5517/ccdc.csd.cc26gmgs
title: CCDC 2039845: Experimental Crystal Structure Determination

description: Related Article: H.Kooijman, A.L.Spek, G.Aromi, J.Reedijk|2020|CSD Communication|||
DOI: 10.5517/ccdc.csd.cc26gpgv
title: CCDC 2039907: Experimental Crystal Structure Determination

description: Related Article: Milan Gembicky|2020|CSD Communication|||
DOI: 10.5517/ccdc.csd.cc26gq4k
title: CCDC 2039928: Experimental Crystal Structure Determination

description: Related Article: Diego Merchan-Arenas|2020|CSD Communication|||
description: Related Article: Diego R. Merchán-Arenas, Felipe Sojo, Francisco Arvelo, Vladimir V. Kouznetsov|2020|RSC Advances|10|42287|doi:10.1039/D0RA04555A
DOI: 10.5517/ccdc.csd.cc26gq6m
title: CCDC 2039930: Experimental Crystal Structure Determination

description: Related Article: Tao Wang|2020|CSD Communication|||
DOI: 10.5066/f77h1gkr
title: USA National Phenology Network (USA-NPN) Plant and Animal Phenology Data for the United States, 2010
DOI: 10.5281/zenodo.4501189
title: Models and main dataset - Constraint-based metabolic control analysis for rational strain engineering

description: <strong>Models and dataset needed to reproduce the case studies for the manuscript Constraint-based metabolic control analysis for rational strain engineering by S. Tsouka et al.</strong> The code and software requirements to run simulations explained and available at: https://github.com/EPFL-LCSB/NRA and https://gitlab.com/realLCSB/nra Models: Consistently reduced stoichiometric model of E. coli metabolism in the SBML format (from Kinetic models of metabolism that consider alternative steady-state solutions of intracellular fluxes and concentrations by Hameri et al. - https://doi.org/10.1016/j.ymben.2018.10.005): reducedD1Model_FBA.xml Thermodynamically curated model of E.coli metabolism in MATLAB's mat format (from Kinetic models of metabolism that consider alternative steady-state solutions of intracellular fluxes and concentrations by Hameri et al. - https://doi.org/10.1016/j.ymben.2018.10.005): D1_FDP1.mat Datasets: Files containing various data and options used in the generation of control coefficients (dataInfo.mat, metSampDataD1_FDP1.mat) Files containing statistics for the previously generated population of 50'000 sets of flux and concentration control coefficients (raw data provided below as Supplementary datasets): CpaggDATA.mat (flux CCs), and CxaggDATA.mat (concentration CCs) Files containing the reference and 18 extreme sets of flux and concentration CCs used in the present study: CCforNRA_RXN_GLCptspp.mat (chosen through Principal Component Analysis (PCA) based on the GLCptspp parameter) and CCforNRA_RXN_PYRtex.mat (chosen through PCA based on the PYRtex parameter) Supplementary datasets 1-5, 50 files each containing 1000 sets of flux and concentration CCs, named as DataD1_FDP1xx.mat where xx ranges from 1-50. The files are available as: Supplementary dataset 1: http://doi.org/10.5281/zenodo.4500807 Supplementary dataset 2: http://doi.org/10.5281/zenodo.4500874 Supplementary dataset 3: http://doi.org/10.5281/zenodo.4500971 Supplementary dataset 4: http://doi.org/10.5281/zenodo.4501050 Supplementary dataset 5: http://doi.org/10.5281/zenodo.4501147
description: S.T. and T.H. were supported by the Swiss National Science Foundation grant [315230_163423]. M.A. was supported by the RTD grant MicroscapesX within SystemsX.ch, the Swiss Initiative for Systems Biology evaluated by the Swiss National Science Foundation, and RobustYeast within ERA net project via SystemsX.ch. L.M. and V.H. were supported by the Ecole Polytechnique Fédérale de Lausanne (EPFL).
DOI: 10.5281/zenodo.4501188
title: Models and main dataset - Constraint-based metabolic control analysis for rational strain engineering

description: <strong>Models and dataset needed to reproduce the case studies for the manuscript Constraint-based metabolic control analysis for rational strain engineering by S. Tsouka et al.</strong> The code and software requirements to run simulations explained and available at: https://github.com/EPFL-LCSB/NRA and https://gitlab.com/realLCSB/nra Models: Consistently reduced stoichiometric model of E. coli metabolism in the SBML format (from Kinetic models of metabolism that consider alternative steady-state solutions of intracellular fluxes and concentrations by Hameri et al. - https://doi.org/10.1016/j.ymben.2018.10.005): reducedD1Model_FBA.xml Thermodynamically curated model of E.coli metabolism in MATLAB's mat format (from Kinetic models of metabolism that consider alternative steady-state solutions of intracellular fluxes and concentrations by Hameri et al. - https://doi.org/10.1016/j.ymben.2018.10.005): D1_FDP1.mat Datasets: Files containing various data and options used in the generation of control coefficients (dataInfo.mat, metSampDataD1_FDP1.mat) Files containing statistics for the previously generated population of 50'000 sets of flux and concentration control coefficients (raw data provided below as Supplementary datasets): CpaggDATA.mat (flux CCs), and CxaggDATA.mat (concentration CCs) Files containing the reference and 18 extreme sets of flux and concentration CCs used in the present study: CCforNRA_RXN_GLCptspp.mat (chosen through Principal Component Analysis (PCA) based on the GLCptspp parameter) and CCforNRA_RXN_PYRtex.mat (chosen through PCA based on the PYRtex parameter) Supplementary datasets 1-5, 50 files each containing 1000 sets of flux and concentration CCs, named as DataD1_FDP1xx.mat where xx ranges from 1-50. The files are available as: Supplementary dataset 1: http://doi.org/10.5281/zenodo.4500807 Supplementary dataset 2: http://doi.org/10.5281/zenodo.4500874 Supplementary dataset 3: http://doi.org/10.5281/zenodo.4500971 Supplementary dataset 4: http://doi.org/10.5281/zenodo.4501050 Supplementary dataset 5: http://doi.org/10.5281/zenodo.4501147
description: S.T. and T.H. were supported by the Swiss National Science Foundation grant [315230_163423]. M.A. was supported by the RTD grant MicroscapesX within SystemsX.ch, the Swiss Initiative for Systems Biology evaluated by the Swiss National Science Foundation, and RobustYeast within ERA net project via SystemsX.ch. L.M. and V.H. were supported by the Ecole Polytechnique Fédérale de Lausanne (EPFL).
DOI: 10.6084/m9.figshare.12782339
title: Air entrainment modelling of stepped spillway flow

description: This dataset contains results for simulations with two custom made solvers to model air entrainment using RANS. Both solvers are based on OpenFOAM's interFOAM. It accompanies the following article: <br><br>S. K. Almeland, T. Mukha and R. E. Bensow. An improved air entrainment model for stepped spillways. 2020. <br><br>Kindly, cite the article if you make use of the data.<br><br>The data for each case in the article is found within the different zip-files, sorted in folders according to the name of the solver.<br>OpenFOAM cases for the different cases and at selected grids, are found in the zip-folders named case_*. These cases were initiated from corresponding interFoam runs. <br>
DOI: 10.6084/m9.figshare.12782339.v1
title: Air entrainment modelling of stepped spillway flow

description: This dataset contains results for simulations with two custom made solvers to model air entrainment using RANS. Both solvers are based on OpenFOAM's interFOAM. It accompanies the following article: <br><br>S. K. Almeland, T. Mukha and R. E. Bensow. An improved air entrainment model for stepped spillways. 2020. <br><br>Kindly, cite the article if you make use of the data.<br><br>The data for each case in the article is found within the different zip-files, sorted in folders according to the name of the solver.<br>OpenFOAM cases for the different cases and at selected grids, are found in the zip-folders named case_*. These cases were initiated from corresponding interFoam runs. <br>
DOI: 10.5066/f7028pjs
title: USA National Phenology Network (USA-NPN) Plant and Animal Phenology Data for the United States, 2008
DOI: 10.5066/f7833q2v
title: USA National Phenology Network (USA-NPN) Plant and Animal Phenology Data for the United States, 2013
DOI: 10.25403/upresearchdata.13312835
title: Consulting Portfolio

description: This is a management consulting assignment for a client. Observation and interview sessions were conducted with client Chief Executive Officer and Chief Operating Officer at client's facility to understand the nature of client's business for potential solutions to its operating and marketing challenges.The outcome of the meetings and client's consent were used to develop a consulting report that captured client's problem brief and solutions.<br><br>
DOI: 10.25403/upresearchdata.13312835.v1
title: Consulting Portfolio

description: This is a management consulting assignment for a client. Observation and interview sessions were conducted with client Chief Executive Officer and Chief Operating Officer at client's facility to understand the nature of client's business for potential solutions to its operating and marketing challenges.The outcome of the meetings and client's consent were used to develop a consulting report that captured client's problem brief and solutions.<br><br>
DOI: 10.17632/b23fzm6ccy.1
title: Table listing all applications of hydrological models in Switzerland

description: Table listing all applications of hydrological models in Switzerland. This Excel document was produced for the paper "Why do we have so many different hydrological models? A review based on the case of Switzerland" submitted to Wires Water.
DOI: 10.17632/fgrbgf3bwx.1
title: Data for: "Barriers, Adaptability, Employability and Satisfaction: Career Perceptions of Undergratuate Administration Students" published by RAC-Revista de Administração Contemporânea

description: This database refers to a research that aimed to verify the influence of career barriers’ perceptions and adaptability on employability and career satisfaction among undergraduate Administration students of Higher Education Institutions. A survey-based research was carried out among 358 students from the last semesters of graduation. The database contains three file groups: 1 - Base with scores to each construct / software Statistical Package for Social Sciences (SPSS) (.sav); 2 - Codes / Excel (.xlsx); e, 3 - Template to Structural Equation Modeling / AMOS Graphics - SPSS (.AmosLock, .amp, .amw).
DOI: 10.17632/9ss9d42f74.1
title: HPV prevalence in oral and oropharyngeal squamous cell carcinomas in South America: a systematic review and meta-analysis - Dataset

description: Database (raw and analyzed) and metadata concerning meta-analysis of HPV prevalence in squamous cell carcinomas of the oral cavity and oropharynx in South America. [Base de dados (bruta e analisada) e metadados relativos à metanálise da prevalência do HPV em carcinomas de células escamosas de cavidade oral e orofaringe na América do Sul.]
DOI: 10.17632/nytpb5mrfm.1
title: Bloom Announcement: 2017 Hamilton Harbour Lake Ontario (Ontario Canada) Cyanobacterial Bloom

description: In 2017, cyanobacterial blooms were observed and characterized in Hamilton Harbour, Lake Ontario (Ontario, Canada) along Bayfront Park Beach. Hamilton Harbour is a large embayment at the western part of Lake Ontario with a long history of anthropogenic impacts, particularly from industrial effluent and residential wastewater. The beneficial use of Bayfront Park Beach has been classified as impaired for beneficial use impairment (BUI) #8, Eutrophication or Undesirable Algae, and BUI #10, Beach Closings and Water Contact Sports, under the Hamilton Harbour’s Remedial Action Plan. As part of Environment and Climate Change Canada’s Great Lakes Action Plan, monthly sampling of whole water grabs, within and outside the blooms, occurred from July to November inclusive. This dataset includes biological and physico-chemical data associated with an article published in the peer-reviewed journal, Data in Brief.
DOI: 10.6084/m9.figshare.13713076
title: mussel_fdom_raw_data

description: Dissolved organic matter florescence components for freshwater mussels from 4 rivers across the southeastern USA.
DOI: 10.6084/m9.figshare.13713076.v1
title: mussel_fdom_raw_data

description: Dissolved organic matter florescence components for freshwater mussels from 4 rivers across the southeastern USA.
DOI: 10.17632/7vc3vndc3r.1
title: Supplementary Material from Caroline Kothe's thesis

description: Additional tables for each article added to Caroline Isabel Kothe's thesis manuscript (Publication 1 - 7)
DOI: 10.17632/w5c378y49h.1
title: Evaluation of WHO WPRO Regional TB Framework 2016-2020

description: The information uploaded here was developed/ gathered during an evaluation of the World Health Organization's TB framework for the Western Pacific Region called Regional framework for action on implementation of the End TB Strategy in the Western Pacific, 2016–2020, conducted in 2019. The evaluation was carried out by Professor Ben Marais and Drs Kerri Viney and Chris Lowbridge, contracted by the End TB unit, WHO WPRO.
DOI: 10.17632/j7rj8dbdjj.1
title: Data - IJS

description: In order to show the relevance of patient’s inflammatory status regarding the prognosis of PAD, the primary endpoint was to establish the correlation between pre-operative pro-inflammatory biomarkers represented by NLR, LMR and PLR with short-term mortality at 6-months. The association between the pre-operative PNI with short-term mortality at 6-months revealing the impact of nutritional status. As secondary endpoints, the correlation between pre-operative biomarkers with major amputation at 6 months and hospital stay were studied. This study analyzes the prognostic value of PNI in patients with CLTI, and our findings suggest that PNI is a useful predictor for short-term mortality with high sensitivity and specificity rates (72.2% and 70.4%, respectively) and could be a helpful tool to predict the risk of major amputations. Additionally, it can be calculated routinely and effortlessly in patients diagnosed with CLTI in our daily clinical practice.
DOI: 10.17632/k3phdsh4dg.1
title: Distributed Slip Models for Long-term Transients in Cascadia

description: Distributed slip model files for long-term trenchward transients in Cascadia from Nuyen & Schmidt (2021). Please see README.txt for more information on the data and file formats.
DOI: 10.6084/m9.figshare.13713166.v1
title: mussel_excretion_rates

description: Excretion rates of DOC, NH4, and SRP for 22 species of mussel across 5 rivers in the southeastern USA.
DOI: 10.17632/2447ggdb55.1
title: Electricity and CO2 mitigation indices for solar PV generation in small cities and towns.
DOI: 10.17632/kjxb2bk3mr.1
title: Melting phase change heat transfer in a quasi-petal tube thermal energy storage unit - Dataset

description: The row data for plotting the graphs