cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.11583/dtu.13353161.v1
title: TotalControl_cnblz02e3m

description: This repository (DOI: 10.11583/DTU.13160606) contains the publicly available data generated during the TotalControl project: <br>https://www.totalcontrolproject.eu/<br>The dataset has been created using EllipSys3D and Flex5 by Niels Troldborg (ORCID 0000-0003-4508-4837, niet@dtu.dk) and Søren Juhl Andersen (ORCID 0000-0002-5935-751X, sjan@dtu.dk). <br>It contains both LES precursor simulation data and LES wind farm flow data. The LES wind farm flow data is organized in separate folder for each flow scenario and wind farm orientation. The layout of the TotalControl Reference Wind Farm is shown for all directions in "TotalControlReferenceWindFarmLayout.pdf", where all turbines are numbered. <br>The folders are named according to type of boundary layer, e.g. conventional neutral boundary layer ("cnbl"), the roughness length of for instance z0 = 2e-3 m denoted as "z02e3m", and finally the rotation of the TotalControl reference wind farm within the flow, i.e. "rot90". <br>The public database contains the following cases with corresponding DOI:1. "cnblz02e3m": Precursor dataset using z0 = 2e-3 m without wind farm. DOI: 10.11583/DTU.133531612. "cnblz02e3m_rot00": Reference wind farm simulation using with 0 deg rotation. DOI: 10.11583/DTU.131222243. "cnblz02e3m_rot90": Reference wind farm simulation using with 90 deg rotation. DOI: 10.11583/DTU.13090113<br>Files in each folder are given the corresponding naming where “TCal” corresponds to actuator line (AL) simulations performed in TotalControl(TC), while “TCad” corresponds to actuator disc (AD) simulations. The dataset contains the following three datatypes with example names: <br>1. Horizontal (xy) planes of flow fields (u, v, and w) extracted at hub height in standard NetCDF format. Naming: TCal_horiz.nc <br>2. Vertical inflow (yz) planes of flow field (u, v, and w) extracted 1R upstream each of the 32 wind turbine (wt) in standard NetCDF format. Naming: TCal_inflow_wt01.nc <br>3. Time series of each of the 32 wind turbines and their performance and loads in ascii format. The files contain time, u velocity at hub height, power, flapwise bending moment, for the three blades, tower bottom bending moment fore-aft and side-side, thrust force, blade pitch, and rotational speed. Naming: TCal_wt01.dat <br>Additionally, there is data for the benchmark case on wind farm control for FarmConners:https://www.windfarmcontrol.info/The flow is identical to "z02e3m_rot00", but turbines 5 and 25 have been intentionally yawed -20deg and -30deg, respectively, where negative corresponds to counterclockwise rotation as seen from above. DOI: 10.11583/DTU.13274549<br>Additional data can be made available upon request.
DOI: 10.17632/p6vz6gws6k.1
title: Supporting Information for Controls of inherited fault zones on orogenic wedge front deformation: insights from analogue modeling

description: This is supporting Information for "Controls of inherited fault zones on orogenic wedge front deformation: insights from analogue modeling" that will be submitted to Tectonics. This file includes the results of 28 sandbox experiments simulating evolution of thrust wedge and their description, as well as the Mohr circles and fault reativation map (SIbson, 1985) using for interpretate the experimental results. All these could help enhancing our understanding about mountain front deformation and fault system there.
DOI: 10.17632/8h5rtbbx7m.3
title: COVID-19, healthcare facilities, and economic related data in Nigeria

description: Our various datasets are now updated as version 3 on Saturday, December 19, 2020. The dataset describes the healthcare facilities, state budget, and laboratories in Nigeria in response to the COVID-19 pandemic and the economic situation of the entire population of the country amidst the pandemic. We have published a data article titled "An exploratory assessment of a multidimensional healthcare and economic data on COVID-19 in Nigeria" using this data and can be found via https://cutt.ly/ngx3xMw. Please kindly cite this paper if you use any of these datasets: Ogundepo, E., Folorunso, S., Adekanmbi, O., Akinsande, O., Banjo, O., Ogbuju, E., Oladipo, F., Abimbola, O., Oseghale, E., & Babajide, O. (2020). An Exploratory Assessment of a Multidimensional Healthcare and Economic Data on COVID-19 in Nigeria. Data in brief, 106424. doi: https://doi.org/10.1016/j.dib.2020.106424 The GitHub repository of the paper can be found via https://bit.ly/COVID-19data_project_repo.
DOI: 10.17632/x2dmzft9jc.1
title: Blood as fuel: the metabolic cost of pedestrian locomotion in Rhodnius prolixus

description: Rough data respirometric study
DOI: 10.17632/9vxm5y3zy8.1
title: Identifying economics shocks with stock repurchase programs

description: this database contains information on share buyback programs and industrial production in US, Canada, United Kingdom and japan. The data is in STATA format
DOI: 10.17632/mmwd75wx2k.1
title: Datasheet measurement Internet data usage and questionnaire forms

description: Research data was obtained through observation activities in the form of measuring internet data during online learning (C1) and filling out questionnaire forms (C2, C3, C4, C5), obtained from 400 undergraduate students dept. of informatics, Mulawarman University, Indonesia as an alternative in decision making or potential beneficiaries.
DOI: 10.17632/ss9wgrdk4p.2
title: Systematic alteration of in vitro metabolic environment reveals empirical growth relationships in cancer cell phenotypes
DOI: 10.17632/cmnyf9n8tt.1
title: SARS-CoV-2 protein ORF3a is pathogenic in vivo and causes phenotypes associated with COVID-19 post-viral syndrome
DOI: 10.17632/n5psdxbbmw.1
title: ADH Dataset

description: This dataset investigates risk factors for upstaging from atypical ductal hyperplasia (ADH) to ductal carcinoma in situ (DCIS). Data was gathered using pathology databases and electronic medical records. Data is recorded in the excel document with all descriptions at the top of the columns. Our data shows that patients with a concurrent diagnosis of papilloma had a higher risk of upstaging on both univariate and multivariate analysis. This data can be used to identify risk factors for upstaging from ADH to DCIS.
DOI: 10.17632/5b4t3ds3rf.1
title: heart.data

description: This data set contains hear disease rate of people who are running and not running daily. It was collected by research carried out by Centers for Disease Control and Prevention https://www.cdc.gov/heartdisease/index.htm
DOI: 10.17632/53bbvrv5v4.2
title: Cr laterite

description: Supplementary dataset and text for Cr paper
DOI: 10.17632/t7prmcwrsz.3
title: Supplementary Material for Robust Integrated Data-Driven Modeling Strategy for Industrial Gas-Phase Ethylene Polymerization Processes with Noises and Outliers

description: This material contains the additional predicted results of the industrial gas-phase ethylene polymerization process by using ELM, RELM, WRELM and proposed robust integrated SDAE-ENELM strategy in the presence of noises and outliers for article "Robust Integrated Data-Driven Modeling Strategy for Industrial Gas-Phase Ethylene Polymerization Processes with Noises and Outliers ".
DOI: 10.17632/ny25mps867.1
title: TiO2_110x-CNT66Y.all_Δφ.ANI

description: # this file includes the 5 optimized structures of CNT(6,6) at a rutile (110) surface as described # in a paper: "A tight-binding model of a carbon nanotube interacting with TiO2 rutile (110)" # by Tomasz Kostyrko, accepted to Applied Surface Science # the optimized structures correspond to different rotations of the CNT # around its longitudinal symmetry axis # the angles of rotation are in sequence: 0,5,10,15,20 degrees # recommended viewer: jmol
DOI: 10.48370/ofd/uogawb
title: Wiechlina łąkowa (Poa pratensis L. s. str.), 2275

description: Herbarium
DOI: 10.17632/zfxf2zjxt6.1
title: Survey Data on Sustainable Consumption

description: This is survey data on sustainable consumption from Malaysia. It was gathered based on income and consumption data among the household.
DOI: 10.48370/ofd/crpfee
title: Świdośliwka kłosowa (Amelanchier spicata (Lam.) K. Koch), 5594

description: Herbarium
DOI: 10.48370/ofd/rupyhi
title: Świdośliwka kłosowa (Amelanchier spicata (Lam.) K. Koch), 5594

description: Herbarium
DOI: 10.48370/ofd/5sl4kl
title: Wiechlina łąkowa (Poa pratensis L. s. str.), 1289

description: Herbarium
DOI: 10.25403/upresearchdata.13298024
title: The role of the chief digital officer in building dynamic capabilities for digital transformation

description: This dataset contain interview transcripts for a qualitative study, It aims to explore the role of the chief digital officer in building dynamic capabilities of the organisation for digital transformation.
DOI: 10.25403/upresearchdata.13298024.v1
title: The role of the chief digital officer in building dynamic capabilities for digital transformation

description: This dataset contain interview transcripts for a qualitative study, It aims to explore the role of the chief digital officer in building dynamic capabilities of the organisation for digital transformation.
DOI: 10.6084/m9.figshare.13474797
title: Data and Codes for Geospatial Constrained Optimization

description: The shared files provide data and codes to support the paper, which is titled "Geospatial Constrained Optimization to Simulate and Predict Spatiotemporal Trends of Air Pollutants". <br><br>The library files provde necessary R and Python functions to support the extrapolation and geospatial constrained optimization. Specific explanations are given in these files. <br>Please ensure that the following libraries are installed:<br>R packages: rgdal, sp, raster, spatialEco, SpatioTemporal (https://cran.r-project.org/web/packages/SpatioTemporal/index.html), sptemExp (https://cran.r-project.org/web/packages/sptemExp/index.html).<br>Python packages: pandas, numpy, tensorflow and keras. <br><br>Please take the following steps for the proposed method: <br>step1_basisfuncs.R: this tutorial aims to explain how to generate temporal basis functions based on KNN and geospatial basis functions. <br>step2_basisfuncs_extrapolation.py: this tutorial aims to explain how to use CNN to extrapolate temporal basis functions. <br>step3_constrained_opt.R: this tutorial aims to explain how to use constrained optimization. <br>step4_indepdendenttest_PM25.R: this is to illustrate how to use geospatial constraint optimization for location-based cross validation of PM2.5. <br>step4_indepdendenttest_NO2x.R:this is to illustrate how to use geospatial constraint optimization for location-based cross validation of NO2 and NOx. This also illustrates how to use the other variable (e.g., NOx) to constrain the target variable (NO2). <br><br>
DOI: 10.6084/m9.figshare.13474797.v1
title: Data and Codes for Geospatial Constrained Optimization

description: The shared files provide data and codes to support the paper, which is titled "Geospatial Constrained Optimization to Simulate and Predict Spatiotemporal Trends of Air Pollutants". <br><br>The library files provde necessary R and Python functions to support the extrapolation and geospatial constrained optimization. Specific explanations are given in these files. <br>Please ensure that the following libraries are installed:<br>R packages: rgdal, sp, raster, spatialEco, SpatioTemporal (https://cran.r-project.org/web/packages/SpatioTemporal/index.html), sptemExp (https://cran.r-project.org/web/packages/sptemExp/index.html).<br>Python packages: pandas, numpy, tensorflow and keras. <br><br>Please take the following steps for the proposed method: <br>step1_basisfuncs.R: this tutorial aims to explain how to generate temporal basis functions based on KNN and geospatial basis functions. <br>step2_basisfuncs_extrapolation.py: this tutorial aims to explain how to use CNN to extrapolate temporal basis functions. <br>step3_constrained_opt.R: this tutorial aims to explain how to use constrained optimization. <br>step4_indepdendenttest_PM25.R: this is to illustrate how to use geospatial constraint optimization for location-based cross validation of PM2.5. <br>step4_indepdendenttest_NO2x.R:this is to illustrate how to use geospatial constraint optimization for location-based cross validation of NO2 and NOx. This also illustrates how to use the other variable (e.g., NOx) to constrain the target variable (NO2). <br><br>
DOI: 10.25403/upresearchdata.13311743
title: The leadership competencies of strategic and operational leaders necessary in sustaining a successful turnaround intervention in public organisations.

description: Semi-structured interviews for a qualitative study to better understand the leadership competencies of strategic and operational leaders necessary in sustaining a turnaround intervention.
DOI: 10.25403/upresearchdata.13311743.v1
title: The leadership competencies of strategic and operational leaders necessary in sustaining a successful turnaround intervention in public organisations.

description: Semi-structured interviews for a qualitative study to better understand the leadership competencies of strategic and operational leaders necessary in sustaining a turnaround intervention.
DOI: 10.5281/zenodo.4382150
title: Data for Multiscale temporal response of salt intrusion to transient river and ocean forcing

description: Data used in the paper 'Multiscale temporal response of salt intrusion to transient river and ocean forcing'
DOI: 10.5281/zenodo.4382149
title: Data for Multiscale temporal response of salt intrusion to transient river and ocean forcing

description: Data used in the paper 'Multiscale temporal response of salt intrusion to transient river and ocean forcing'
DOI: 10.48370/ofd/bcp4ef
title: Świdośliwka kłosowa (Amelanchier spicata (Lam.) K. Koch), 5672

description: Herbarium
DOI: 10.17632/hgph86s73j.1
title: Lipid and carotenoid production in cane molasses by Rhodosporidium toruloides mutant

description: Cane molasses, as a low-cost carbon source, is suitable for the lipid and carotenoids yields in microalgae or microorganisms. In this study, we investigated the lipid and carotenoid production profile of R. toruloides mutant M18 (MT) in a defined media with various amounts of pretreated cane molasses (TM) under nitrogen-limited conditions. The production of palmitic acid (C16:0) and α-linolenic acid (C18:3) from MT were improved by 16.92% and 21.88% in 100% TM compared to the wild type strain (WT). The torularhodin, torulene and β-carotene content of the MT with cane molasses under nitrogen-limited conditions were 14.68, 1.41 and 1.11-fold higher than that of the WT, respectively. Compared with the effects of cane molasses concentrations on lipid production, we found that cane molasses concentration of 35 g/L (50% TM) and 70 g/L (100% TM) as a low-cost carbon source, is an economical and green strategy for the production of lipid and carotenoids by MT, respectively. Transcriptome sequencing and WGCNA analysis revealed that differentially expressed genes in blue module were identified as significantly highly expressed and were relevant and consistent with the results of phenotype performance of lipid and carotenoids accumulation responses to the stress in cane molasses under nitrogen-limited conditions between the MT and WT strains, including MYB, bHLH, Δ-4 desaturase, Δ-12 desaturase and FA2H genes. Cane molasses, as an alternative to glucose-based medium, is suitable for lipid and carotenoid yields in R. toruloides, which makes it serve as a valuable reference for a cost-saving substance in industrial applications.
DOI: 10.17632/zgh5j94hfc.2
title: Towards an Effective Tuberculosis Surveillance in Indonesia through Google Trends

description: Abstract ----- Background. The search digital footprint, such as in Google Trend (GT), forms a large dataset that is suitable to be used as surveillance data and supports early warning systems. These advantages become great opportunities for disease surveillance agencies in Indonesia to get rapid early disease monitoring. Objective. Due to limited research in this area and the increasing level of internet penetration in Indonesia, a further study is needed in disease monitoring by utilizing Google Trends. In this research, we explore, analyze and create a set of the best search terms to be used in utilizing GT for disease surveillance in Indonesia, especially Tuberculosis. Method. We use correlation as the technique to define the relatedness between the real case data and GT results. We collect data from the Ministry of Health of Indonesia. From the data, we design a set of new search terms to take GT trend data. The collected data is analyzed using the Pearson correlation. Result. The analysis shows that the studied search terms give strong positive relationships between GT trend data and Tuberculosis cases number in Indonesia. From the correlation analysis, we get a set of proposed effective search terms with the highest score equals to 0.907. Conclusion. Finally, it is possible to monitor and make quick surveillance in tuberculosis in Indonesia through Google Trend and we have created a novel set of search terms that can be used as the basis in monitoring other diseases in Indonesia. Jurnal : Fudholi, D., & Fikri, K. (2020). Towards an Effective Tuberculosis Surveillance in Indonesia through Google Trends. Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control, 5(4). doi: https://doi.org/10.22219/kinetik.v5i4.1114
DOI: 10.17632/k4dvwzdwsd.1
title: Analisis Korelasi antara Google Trends dengan Pengawasan Penyakit di Indonesia

description: Abstrak Analisis Korelasi antara Google Trends dengan Pengawasan Penyakit di Indonesia Latar Belakang: Aktivitas pengguna internet meninggalkan jejak digital yang dapat dianalisis. Google Trends adalah salah satu kolektor jejak digital ini. Sejak 2016, Google Trends telah diuji oleh para peneliti seperti di bidang kesehatan. Pemantauan penyebaran penyakit merupakan topik yang paling banyak dibicarakan di luar Indonesia. Tujuan: Sangat penting untuk menganalisis korelasi antara tren Google Trends dan pemantauan penyakit di Indonesia. Pasalnya, Google Trends telah diteliti di luar Indonesia dan pola penyebaran penyakit di Indonesia berbeda dengan negara lain. Tujuan penelitian adalah untuk mengevaluasi korelasi Google Trends dengan pengawasan penyakit dengan 1) menguji istilah penelusuran sebelumnya, 2) menemukan sumber untuk istilah penelusuran baru, 3) membuat istilah penelusuran baru yang relevan, dan 4) membuat templat istilah penelusuran praktik terbaik. Desain: peneliti mengambil laporan surveilance penyakit konvensional dari Direktorat Jenderal P2P Kementerian Kesehatan Republik Indonesia. Tren penyakit dari Google Trends diambil untuk melihat derajat korelasi dengan laporan pengawasan penyakit konvensional. Buku Kapita Selekta Kedoteran di Indonesia dan Related Query di Google Trends merupakan sumber baru dalam membuat istilah pencarian. Perhitungan korelasi menggunakan Pearson Correlation dengan pengujian lebih lanjut berupa uji konsistensi istilah pencarian memiliki tingkat korelasi yang tinggi (&gt; = 0,80). Hasil: Sedikitnya terdapat 32 istilah pencarian dengan tingkat korelasi tertinggi yang dapat digunakan untuk memantau Tuberkulosis di Indonesia. Sedangkan istilah "adalah" dan "ciri-ciri" dapat digunakan untuk penyakit selain Tuberkulosis dengan aturan penggunaan yang telah ditetapkan. Faktor berita, bahasa, populasi, dan akses internet menjadi perhatian penting dalam pengendalian penyakit melalui Google Trends. Masyarakat di Indonesia cenderung mendiagnosis diri sendiri daripada mencari definisi penyakit tertentu. Hal tersebut ditunjukkan dengan banyaknya kecenderungan yang berkaitan dengan diagnosis dibandingkan definisi, epidemiologi, faktor risiko dan tata laksana. Area dengan akses internet minimal dan populasi rendah menjadi sulit untuk dipantau melalui Google Trends. Meskipun pengawasan dilakukan sewaktu- waktu, namun penelitian lebih lanjut tetap diperlukan mengingat belum ditemukan waktu / musim yang efektif untuk melakukan pengawasan atau peringatan dini bagi pemerintah. Kata kunci Google trends, Tuberkulosis, istilah pencarian, Pearson correlation, korelasi. Kumpulan data ini merupakan dataset penelitian tesis saya dan ditujukan untuk penelitian tesis itu sendiri dan penelitian lanjutan tesis dalam bentuk jurnal. Dataset ini memiliki hak milik atas saya dan lembaga terkait yaitu Direktorat Jendral Pencegahan dan Pengendalian Penyakit Menular Langsung Kemkes RI & Departemen Informatika Universitas Islam Indonesia.
DOI: 10.17632/8p3jf6bwzb.1
title: LINF_050006700

description: dihydrolipoamide branched chain transacylase; Leishmania infantum
DOI: 10.17632/jgh63g8rzg.1
title: LINF_050006800

description: Fip1 | zinc finger protein family member Leishmania infantum
DOI: 10.17632/8x6t5n6wz5.1
title: LINF_050006900

description: LSG1 Leishmania infantum
DOI: 10.17632/d5rn9kfwbt.1
title: LINF_050007300

description: viscerotropic leishmaniasis antigen; Leishmania infantum
DOI: 10.17632/34vzndtmfj.1
title: Data to calculate a spatially-explicit water scarcity footprint in LCA

description: This dataset contains life cycle inventory data, a life cycle impact assessment method as well as impact assessment results and SHP files for a spatially-explicit assessment with GIS software solutions. If you have any questions, please contact anna.schomberg@uni-kassel.de
DOI: 10.17632/7rcp6sh8nh.1
title: Do doorways really matter
DOI: 10.48370/ofd/4ud65t
title: Wiechlina łąkowa (Poa pratensis L. s. str.), 1289

description: Herbarium
DOI: 10.17632/bg736dv69b.2
title: Data for: Effects of aeration on the suspended matter from a Tropical and Eutrophic estuary

description: In this doc you will find tables with data from the manuscript Effects of aeration on the suspended matter from a Tropical and Eutrophic estuary under considering for publication.
DOI: 10.17632/gp264xp3rd.1
title: EudraCT 2011-000541-20 protocol and participant level data

description: This deposited dataset represents all deidentified patient and results data for the EudraCT registered clinical trial "Effect of Denosumab on Osteolytic Lesion Activity after Total Hip Arthroplasty", and links to the article published in Lancet Rheumatology under the same name.
DOI: 10.17632/99r49328cb.1
title: Guerra-Coss et al. Modelling and validation of the spatial distribution of suitable habitats for the recruitment of invasive plants on climate change scenarios: an approach from the regeneration niche
DOI: 10.17632/hn3ncrrj95.1
title: Synthetic low-voltage grid and residential solar photovoltaic hosting capacity data

description: Making national and local estimates of grid impacts from end-use-technologies, such as electric vehicles and solar photovoltaic can improve targets and cost-estimates for a fully renewable electricity and transportation system. This dataset contains data from a reference network model that generates synthetic low-voltage grids using public GIS data and national standards and regulations for low-voltage systems. The data and metadata is presented for synthetic low-voltage grids and residential solar photovoltaic hosting capacity in Sweden (SWE), UK (UK) and Germany (DE). Data files contains GIS files and are presented in the EPSG:3035 coordinate reference system.
DOI: 10.17632/66xpn594n9.1
title: A Comparative Study on Therapeutic Effect of Metformin and Sitagliptin/metformin in Infertile Women with Polycystic Ovary Syndrome (PCOS) undergoing intracytoplasmic sperm injection (ICSI)
DOI: 10.17632/w6jt5n3zrn.1
title: Forbes output model

description: ModelVision session file containing full final model parameters for the Forbes potential field model