cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.4121/13031837.v1
title: Supplementary data for the paper: Simultaneous orientation and 3D localization microscopy with a Vortex point spread function

description: This dataset contains data collected as part of the development of the Vortex PSF. It consists of raw data to calibrate the aberrations over the field-of-view, verify the vortex PSF model, visualise transitions in orientation and perform Binding-Activated localization microscopy and orientation estimation on lambda-DNA. A drift corrected and non drift corrected processed lambda-DNA dataset is also included to show the possible parameters that one can visualize over the whole field-of-view.<br>The dataset is being made public both to act as supplementary data for publications and in order for other researchers to use this data to verify and develop the method and code.<br>Any reuse of this data should cite the original associated publication.
DOI: 10.4121/13031837
title: Supplementary data for the paper: Simultaneous orientation and 3D localization microscopy with a Vortex point spread function

description: This dataset contains data collected as part of the development of the Vortex PSF. It consists of raw data to calibrate the aberrations over the field-of-view, verify the vortex PSF model, visualise transitions in orientation and perform Binding-Activated localization microscopy and orientation estimation on lambda-DNA. A drift corrected and non drift corrected processed lambda-DNA dataset is also included to show the possible parameters that one can visualize over the whole field-of-view.<br>The dataset is being made public both to act as supplementary data for publications and in order for other researchers to use this data to verify and develop the method and code.<br>Any reuse of this data should cite the original associated publication.
DOI: 10.4121/13026671.v1
title: Complete dataset for the publication: The accuracy challenge of DFT-based molecular assignment of 13C MAS NMR characterization of surface intermediates in zeolite catalysis

description: Complete dataset (archive) of computational results (optimized structures, energetics, predicted spectroscopic data) for the publication A. A. Kolganov, A. A. Gabrienko, I. Yu. Chernyshov, A. G. Stepanov, E. A. Pidko "The accuracy challenge of DFT-based molecular assignment of <sup>13</sup>C MAS NMR characterization of surface intermediates in zeolite catalysis" Phys. Chem. Chem. Phys. 2020DOI: 10.1039/D0CP04439C
DOI: 10.4121/13026671
title: Complete dataset for the publication: The accuracy challenge of DFT-based molecular assignment of 13C MAS NMR characterization of surface intermediates in zeolite catalysis

description: Complete dataset (archive) of computational results (optimized structures, energetics, predicted spectroscopic data) for the publication A. A. Kolganov, A. A. Gabrienko, I. Yu. Chernyshov, A. G. Stepanov, E. A. Pidko "The accuracy challenge of DFT-based molecular assignment of <sup>13</sup>C MAS NMR characterization of surface intermediates in zeolite catalysis" Phys. Chem. Chem. Phys. 2020DOI: 10.1039/D0CP04439C
DOI: 10.4121/uuid:a2db3c82-359a-4adc-b1c8-52bc33ebce7c.v1
title: International Levee Performance Dataset

description: The International Levee Performance Database (ILPD) is a database for data on levee failures and breaches, and other relevant performance cases (incidents, large-scale experiments). The database was developed under the research project SAFElevee, made possible by the Dutch Technology Foundation NWO TTW. This database is a collection of data provided by third parties and is currently being populated with data. No rights can be derived on the data provided in the database. The data is free to use provided the original owners of the data are referenced. For questions about how to contribute to the database please email leveefailures@tudelft.nl
DOI: 10.4121/uuid:a2db3c82-359a-4adc-b1c8-52bc33ebce7c
title: International Levee Performance Dataset

description: The International Levee Performance Database (ILPD) is a database for data on levee failures and breaches, and other relevant performance cases (incidents, large-scale experiments). The database was developed under the research project SAFElevee, made possible by the Dutch Technology Foundation NWO TTW. This database is a collection of data provided by third parties and is currently being populated with data. No rights can be derived on the data provided in the database. The data is free to use provided the original owners of the data are referenced. For questions about how to contribute to the database please email leveefailures@tudelft.nl
DOI: 10.4121/13019864.v1
title: Data presented in the paper: "On-the-fly construction of surrogate constitutive models for concurrent multiscale mechanical analysis through probabilistic machine learning"

description: This package contains data presented in the following publication: I.B.C.M. Rocha, P. Kerfriden, F.P. van der Meer, "On-the-fly construction of surrogate constitutive models for concurrent multiscale mechanical analysis through probabilistic machine learning", 2020. All data have been generated with simulations with the in-house finite element code as described in the paper.<br>
DOI: 10.4121/13019864
title: Data presented in the paper: "On-the-fly construction of surrogate constitutive models for concurrent multiscale mechanical analysis through probabilistic machine learning"

description: This package contains data presented in the following publication: I.B.C.M. Rocha, P. Kerfriden, F.P. van der Meer, "On-the-fly construction of surrogate constitutive models for concurrent multiscale mechanical analysis through probabilistic machine learning", 2020. All data have been generated with simulations with the in-house finite element code as described in the paper.<br>
DOI: 10.4121/12999575.v1
title: Data from: 30 years of large river restoration: how long do restored floodplain channels remain suitable for targeted rheophilic fishes in the lower river Rhine?

description: The ecological efficacy of river restoration projects may change over time, resulting in the loss of their ecological function for targeted species. The goal of this study was to evaluate the rheophilic nursery function of restored floodplain channels over time, by analysing 30 years of monitoring data from 12 restoration projects in the lower river Rhine.
DOI: 10.4121/12999575.v2
title: Data from: 30 years of large river restoration: how long do restored floodplain channels remain suitable for targeted rheophilic fishes in the lower river Rhine?

description: The ecological efficacy of river restoration projects may change over time, resulting in the loss of their ecological function for targeted species. The goal of this study was to evaluate the rheophilic nursery function of restored floodplain channels over time, by analysing 30 years of monitoring data from 12 restoration projects in the lower river Rhine.
DOI: 10.4121/12998669.v1
title: Table 1, Supplementary to manuscript: Progression of acromegalic arthropathy in long-term controlled acromegaly patients: 9 years of longitudinal follow-up

description: Supplementary Table 1 to Manuscript published in Pelsma et al. JCEM (2020) titled: Progression of acromegalic arthropathy in long-term controlled acromegaly patients: 9 years of longitudinal follow-up.
DOI: 10.4121/12998669
title: Table 1, Supplementary to manuscript: Progression of acromegalic arthropathy in long-term controlled acromegaly patients: 9 years of longitudinal follow-up

description: Supplementary Table 1 to Manuscript published in Pelsma et al. JCEM (2020) titled: Progression of acromegalic arthropathy in long-term controlled acromegaly patients: 9 years of longitudinal follow-up.
DOI: 10.4121/uuid:60e8a166-8303-49fa-93b2-dfe622f27405.v1
title: Data and scripts used in the paper: Moving from drought hazard to impact forecasts

description: These are all the data that we used in our Nature publication with the title: Moving from drought hazard to impact forecasts.
DOI: 10.4121/uuid:60e8a166-8303-49fa-93b2-dfe622f27405
title: Data and scripts used in the paper: Moving from drought hazard to impact forecasts

description: These are all the data that we used in our Nature publication with the title: Moving from drought hazard to impact forecasts.<br>The new datasets are intended to replace the drought Standardised Runoff Index (SRI), which was not the final and correct version. The new drought indices that we revised are the final and corrected version. For any further questions, please contact the responding author: Samuel Sutanto (samuel.sutanto@wur.nl).<br>
DOI: 10.4121/uuid:0a9b77bc-3f6d-40e2-846c-ddb992dd78a6
title: Cone Penetration Test (CPT) dataset to study soil heterogeneity.

description: 100 CPTs taken over a 15 m x 50 m area. The data was collected over the crest of a rural dyke and closely spaced.
DOI: 10.4121/12982232
title: Data underlying the MSc thesis: Effects of drought on the traffic capacity of the river Waal and the occurrence of congestion

description: Data files of the hydraulic and transport analyses in MATLAB and R. Traffic simulation files in SIMDAS separated in zip files containing the sensitivity and traffic simulations.<br>Bed level, water level, reference line and beacon line data as well as IVS90 transport and river discharge data are not included in the uploaded files but can be applied for at Rijkswaterstaat.<br>
DOI: 10.4121/12993437.v1
title: Data Set for Stochastic Aircraft Maintenance Check Scheduling

description: Data set for stochastic aircraft maintenance check scheduling optimization.
DOI: 10.4121/12993437
title: Data Set for Stochastic Aircraft Maintenance Check Scheduling

description: Data set for stochastic aircraft maintenance check scheduling optimization.
DOI: 10.4121/uuid:3f42accd-0577-4b29-bc41-77e6a98ef445.v1
title: Data underlying the research of the Effect of Biaxial Loading on Fatigue Properties

description: This dataset contains the data of the fatigue tests are performed on cruciform specimen of Al 2024-T3 under uniaxial and biaxial loading conditions to investigate the effect of biaxial loading on the fatigue behaviour.
DOI: 10.4121/uuid:3f42accd-0577-4b29-bc41-77e6a98ef445
title: Data underlying the research of the Effect of Biaxial Loading on Fatigue Properties

description: This dataset contains the data of the fatigue tests performed on cruciform specimen of Al 2024-T3 under uniaxial and biaxial loading conditions to investigate the effect of biaxial loading on the fatigue behaviour.
DOI: 10.4121/uuid:fd7dda20-37e6-4f96-981d-b1073687cacc
title: Data underlying the research of Distributed temperature measurements and results of active heat tracer test

description: Distributed temperature sensing measurements and results of heat tracer test performed in Schouwen, Zeeland, the Netherlands. The uploaded files contain temperature measurements, estimates of the specific discharge and ratios of specific discharge. All estimates have associated uncertainty distributions. These measurements are also used in "Measuring groundwater flow with aquifer-penetrating distributed temperature sensing" PhD-thesis by Bas des Tombe (unpublished at the time of writing). Naming convention of the uploaded files do not align with the naming convention in the thesis, see notes.txt.
DOI: 10.4121/uuid:88d22c60-21b3-4ea8-90db-20249a5be2a7.v1
title: Autonomous Greenhouse Challenge, Second Edition (2019)

description: The dataset contains data on outdoor and indoor greenhouse climate, irrigation, status of actuators, requested and realized climate setpoints, resource consumption, harvest, crop-related parameters, tomato quality, analysis of irrigation and drain samples and root-zone/slab information. Data were collected during a 6-month cherry tomato production (cv. Axiany) in 6 high-tech glasshouse compartments, located at the Wageningen Research Centre in Bleiswijk (The Netherlands). The dataset was produced during the second edition of Autonomous Greenhouse Challenge. This competition sees five international teams - consisting of scientists, professionals and students with multi-disciplinary expertise - challenging themselves in order to make a large step towards the Autonomous Greenhouse. The teams' names are: The Automators, AICU, IUA.CAAS, Digilog and Automatoes. The teams developed their own intelligent algorithms and used them to determine the set points for climate, irrigation and a number of cultivation-related parameters and control the production of cherry tomato crop remotely. The teams objective was to maximize net profit, by minimizing use of resources (e.g. water, nutrients, energy -heating and electricity- CO2) while optimizing income as a function of production and fruit quality. The achievements in AI-controlled compartments were compared with a reference compartment, operated manually by three Dutch commercial growers (named Reference). The dataset contains raw and processed data. Raw data were collected via climate measuring boxes and sensors, climate and irrigation process computer, weather station, manual registrations (performed by the greenhouse staff).
DOI: 10.4121/12952124.v1
title: Wiener-Hammerstein Process Noise System Time Series

description: The Wiener-Hammerstein system structure is a well-known block-oriented structure. It contains a static nonlinearity that is sandwiched in between two linear time-invariant (LTI) blocks. The presence of the two LTI blocks results in a problem that is harder to identify. The LTI blocks are realized as active filters while the static nonlinearity is implemented as a diode-resistor electronic circuit.<br>The Wiener-Hammerstein system proposed here as a benchmark contains dominant process noise. The process noise enters the system before the static nonlinearity. Two much less significant noise sources are present in the measurement channels of the input and output.<br>All the provided files, data and information on the Wiener-Hammerstein system are available for download here together with an in-depth description of the measured input-output time series. This zip-file contains a detailed system description, an example estimation data set, the test data sets, the datasets measured during the past measurement campaign(s), pictures of the measurement setup, and an indicative electrical circuit schematic of the system. It is possible that the actual implemented Wiener-Hammerstein system deviates at some points (resistor values, opamp type) from the electrical circuit provided here. The data is available in the .csv and .mat file format.<br><br>
DOI: 10.4121/12952124
title: Wiener-Hammerstein benchmark with process noise

description: The Wiener-Hammerstein system structure is a well-known block-oriented structure. It contains a static nonlinearity that is sandwiched in between two linear time-invariant (LTI) blocks. The presence of the two LTI blocks results in a problem that is harder to identify. The LTI blocks are realized as active filters while the static nonlinearity is implemented as a diode-resistor electronic circuit.<br>The Wiener-Hammerstein system proposed here as a benchmark contains dominant process noise. The process noise enters the system before the static nonlinearity. Two much less significant noise sources are present in the measurement channels of the input and output.<br>All the provided files, data and information on the Wiener-Hammerstein system are available for download here together with an in-depth description of the measured input-output time series. This zip-file contains a detailed system description, an example estimation data set, the test data sets, the datasets measured during the past measurement campaign(s), pictures of the measurement setup, and an indicative electrical circuit schematic of the system. It is possible that the actual implemented Wiener-Hammerstein system deviates at some points (resistor values, opamp type) from the electrical circuit provided here. The data is available in the .csv and .mat file format.<br><br>
DOI: 10.4121/12932801.v1
title: Perceived Mental Workload Detection using Multimodal Physiological Data - Deep Learning, GitHub Linked

description: - - See README.md for a more complete overview. - -<br><br><br>This dataset contains data collected during research into mental workload (MWL) detection using deep learning. It is being made public as supplementary data for publications, as well as for reuse in research that seeks to classify MWL using multimodal physiological data.The data in this dataset was collected in the Behavioural, Management, and Social Sciences Lab, University of Twente, Enschede, The Netherlands in June/July 2020.<br><br>Mental workload detection has been attempted using various bio-signals. Recently, deep learning has allowed for novel methods and results within the BCI community. However, studies currently often only use a single modality to classify mental workload, whereas a plethora of modalities have proven to be valuable in this task. The goal of this dataset is to serve as a testing ground for the creation of deep neural networks that can classify MWL using multimodal physiological data.<br>Please refer to the following GitHub repository for the code that was used to create this dataset: https://github.com/Tech4People-BMSLab/mwl-detection, or find it using the following DOI: https://doi.org/10.5281/zenodo.4043058<br>
DOI: 10.4121/12932801
title: Perceived Mental Workload Detection using Multimodal Physiological Data - Deep Learning, GitHub Linked

description: - - See README.md for a more complete overview. - -<br><br><br>This dataset contains data collected during research into mental workload (MWL) detection using deep learning. It is being made public as supplementary data for publications, as well as for reuse in research that seeks to classify MWL using multimodal physiological data.The data in this dataset was collected in the Behavioural, Management, and Social Sciences Lab, University of Twente, Enschede, The Netherlands in June/July 2020.<br><br>Mental workload detection has been attempted using various bio-signals. Recently, deep learning has allowed for novel methods and results within the BCI community. However, studies currently often only use a single modality to classify mental workload, whereas a plethora of modalities have proven to be valuable in this task. The goal of this dataset is to serve as a testing ground for the creation of deep neural networks that can classify MWL using multimodal physiological data.<br>Please refer to the following GitHub repository for the code that was used to create this dataset: https://github.com/Tech4People-BMSLab/mwl-detection, or find it using the following DOI: https://doi.org/10.5281/zenodo.4043058<br>
DOI: 10.4121/12966782.v1
title: Data underlying the research on: An n-alkane-based Holocene climate reconstruction in the Altai Mountains, Arid Central Asia

description: Columns:(1) Depth (cm)(2) Age (yr BP)(3) Paq(4) ACLP<sub>aq</sub>= (C<sub>23</sub>+C<sub>25</sub>)/ (C<sub>23</sub>+C<sub>25</sub>+C<sub>29</sub>+C<sub>31</sub>) <br>ACL= (21*C<sub>21</sub>+23*C<sub>23</sub>+25*C<sub>25</sub>+27*C<sub>27</sub>+29*C<sub>29</sub>+31*C<sub>31</sub>+33*C<sub>33</sub>)/ (C<sub>21</sub>+C<sub>23</sub>+C<sub>25</sub>+C<sub>27</sub>+C<sub>29</sub>+C<sub>31</sub>+C<sub>33</sub>)<br><br>Generally, our data revealed the Holocene moisture and temperature variations in arid central Asia. Paq means the percentage content of aquatic plants in peat sediment and is an indicator of moisture, ACL means average carbon chain length and is an indicator of temperature.<br><br>
DOI: 10.4121/12966782
title: Data underlying the research on: An n-alkane-based Holocene climate reconstruction in the Altai Mountains, Arid Central Asia

description: Columns:(1) Depth (cm)(2) Age (yr BP)(3) Paq(4) ACLP<sub>aq</sub>= (C<sub>23</sub>+C<sub>25</sub>)/ (C<sub>23</sub>+C<sub>25</sub>+C<sub>29</sub>+C<sub>31</sub>) <br>ACL= (21*C<sub>21</sub>+23*C<sub>23</sub>+25*C<sub>25</sub>+27*C<sub>27</sub>+29*C<sub>29</sub>+31*C<sub>31</sub>+33*C<sub>33</sub>)/ (C<sub>21</sub>+C<sub>23</sub>+C<sub>25</sub>+C<sub>27</sub>+C<sub>29</sub>+C<sub>31</sub>+C<sub>33</sub>)<br><br>Generally, our data revealed the Holocene moisture and temperature variations in arid central Asia. Paq means the percentage content of aquatic plants in peat sediment and is an indicator of moisture, ACL means average carbon chain length and is an indicator of temperature.<br><br>
DOI: 10.4121/12954911
title: F-16 Aircraft Benchmark Based on Ground Vibration Test Data

description: The F-16 Ground Vibration Test benchmark features a high order system with clearance and friction nonlinearities at the mounting interface of the payloads.<br><br>The experimental data made available here were acquired on a full-scale F-16 aircraft on the occasion of the Siemens LMS Ground Vibration Testing Master Class.<br><br>During the test campaign, two dummy payloads were mounted at the wing tips to simulate the mass and inertia properties of real devices typically equipping an F-16 in ﬂight. The aircraft structure was instrumented with accelerometers. One shaker was attached underneath the right wing to apply input signals. The dominant source of nonlinearity in the structural dynamics was expected to originate from the mounting interfaces of the two payloads. These interfaces consist of T-shaped connecting elements on the payload side, slid through a rail attached to the wing side. A preliminary investigation showed that the back connection of the right-wing-to-payload interface was the predominant source of nonlinear distortions in the aircraft dynamics, and is therefore the focus of this benchmark study.<br><br>All the provided files and information together with a detailed description of the F-16 aircraft benchmark system are available for download here. This zip-file contains a detailed system description, the estimation and test data sets, and some pictures of the setup. The data is available in the .csv and .mat file format.<br>
DOI: 10.4121/12967592.v1
title: Hysteretic Benchmark with a Dynamic Nonlinearity

description: Hysteresis is a dynamic nonlinearity commonly encountered in very diverse engineering and science disciplines, ranging from solid mechanics, electromagnetism and aerodynamics to biology, ecology and psychology. In particular, the Bouc-Wen model has been intensively exploited during the last decades to represent hysteretic effects in mechanical engineering, especially in the case of random vibrations.<br>It is proposed as a benchmark problem to identify a Bouc-Wen system based on synthetic input-output data time-series. A detailed formulation of the identification problem can be downloaded here. All the provided files and information on the Bouc-Wen system are available for download. The zip-file contains a detailed system description with a signal generation guide and the test data sets. This benchmark requires MATLAB to run.
DOI: 10.4121/12960104
title: Cascaded Tanks Benchmark Combining Soft and Hard Nonlinearities

description: The considered cascaded tanks system is a fluid level control system consisting of two tanks with free outlets fed by a pump. The input signal controls a water pump that delivers the water from a reservoir into the upper water tank. The water of the upper tank flows through a small opening into the lower tank, and finally through a small opening from the lower tank back into the reservoir. This benchmark combines soft and hard nonlinearities to be identified based on relatively short data records.<br>All the provided files and information on the cascaded tanks system are available for download here. The zip-file contains a detailed system description, the estimation and test input-output time series data sets, and some pictures and a video of the setup. The data is available in the .csv and .mat file format.<br>