cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.7554007
title: Multichannel Displacement measurement via self mixing interferometry and neural network : training and test datasets

description: Self mixing interferometry is a simple and robust sensing method which can be used (among other things) to measure the displacement of a target along the light propagation axis. While conceptually simple, the actual use of this method is less straightforward than originally envisioned because reconstructing the target displacement from the interferometric signal is often tricky. A small neural network can do this task very well after proper training, as described in [10.1364/OE.419844], with dataset [10.5281/zenodo.7303745]. Here, the dataset is composed by a training set and a test set, in a specific configuration in which 3 self-mixing sensors measure simultaneously the same target displacement. Both datasets contain the displacement itself and the 3 interferometric signals (1 per sensing channel) <strong>The training set </strong>relies on two python/numpy data files corresponding to <strong>harmonic displacements</strong> for different frequencies ranging from 53 and 93 Hz and amplitudes from 3.5 to 7.5 µm : Training_set_2_lostchannel_displacement.npy : 93744-elements long numpy array containing the target's displacement in units of µm/ms with a 1.024 ms time step. Training_set_2_lostchannel_signal.npy : numpy array of shape (3, 93744, 256, 1) containing the interferometric signals. The first dimension refers to the channel (1, 2 or 3), the second dimension is the number of segments of 256 points. Each segment of 256 points correspond to a 1.024 ms window of signal, matching one element of the displacement. For instance, the displacement value in `displacement[416]` corresponds to the interferometric signal segment `signal[0,416,:,0]` for channel 1, `signal[1,416,:,0]` for channel 2 and `signal[2,416,:,0]` for channel 3. <strong>The test </strong>set follows the same architecture and format as the training set, but contains only <strong>random displacements </strong>generated by a delta-correlated signal, which we Fourier filter with a fifth order Butterworth filter between 10 and 100 Hz : "Displacement_test.npy" : with shape (246078, 1) "Signal_test.npy" : with shape (3, 246078, 256, 1) Only the displacement type has changed from harmonic to random, from the training to the test datasets. These datasets have been used to train and test a 3 channel neural network (after data augmentation) in order to emphasize the high availability potential of multichannel schemes, against backscattered power fluctuations.
DOI: 10.25364/wegc/wps8.0:2023.1
title: WegenerNet climate station network Level 2 data
title: version 8.0 (2007-2022)

description: This dataset contains the latest reprocessed data record (version 8.0) over 2007 to 2022 from the WegenerNet climate station networks, which since 2007 provide measurements with very high spatial and temporal resolution of hydrometeorological variables for two regions in the state of Styria, southeastern Austria:

1) The WegenerNet Feldbach Region, located in the Alpine forelands of southeastern Styria, which extents over an area of about 22 km x 16 km and comprises more than 150 meteorological stations placed on a tightly spaced grid, with an average spatial density of one station per ~2 km² and a temporal sampling of 5 min.

2) The WegenerNet Gesäuse Region, which is a smaller "sister network" of the WegenerNet Feldbach Region. It comprises 15 meteorological stations and two hydrographic stations located in the mountainous Apine region of upper Styria, with station altitudes ranging from below 600 m to over 2100 m. The network extends over an area of about 16 km x 17 km and data are collected with a temporal sampling of 10 min.

These networks are long-term operated and continuously provide quality-controlled data for a multitude of hydrometeorological near-surface and surface variables.

The dataset consists of station time series (as .csv files) for the parameters listed below and gridded data (as NetCDF files) for air temperature, relative humidity, precipitation, heat index, wind speed and direction, and wind gust speed and direction. A detailed description of all measured parameters can be found in Fuchsberger et al. (2021), see related publications below.
DOI: 10.5281/zenodo.7298511
title: Artifact for Paper ParaQooba: A Fast and Flexible Framework for Parallel and Distributed QBF Solving

description: The artifact for the paper "ParaQooba: A Fast and Flexible Framework for Parallel and Distributed QBF Solving" submitted to the TACAS2023 artifact evaluation. We thank the reviewers for their comments and added the missing dependencies to this revised version. No other parts have been changed.
description: {"references": ["Fedyukovich, Grigory, & Mover, Sergio. (2022). TACAS 23 Artifact Evaluation VM - Ubuntu 22.04 LTS (1.0). Zenodo. https://doi.org/"]}
DOI: 10.5281/zenodo.7298512
title: Artifact for Paper ParaQooba: A Fast and Flexible Framework for Parallel and Distributed QBF Solving

description: The artifact for the paper "ParaQooba: A Fast and Flexible Framework for Parallel and Distributed QBF Solving" submitted to the TACAS2023 artifact evaluation.
description: {"references": ["Fedyukovich, Grigory, & Mover, Sergio. (2022). TACAS 23 Artifact Evaluation VM - Ubuntu 22.04 LTS (1.0). Zenodo. https://doi.org/"]}
DOI: 10.5281/zenodo.7554207
title: Artifact for Paper ParaQooba: A Fast and Flexible Framework for Parallel and Distributed QBF Solving

description: The artifact for the paper "ParaQooba: A Fast and Flexible Framework for Parallel and Distributed QBF Solving" submitted to the TACAS2023 artifact evaluation. We thank the reviewers for their comments and added the missing dependencies to this revised version. No other parts have been changed.
description: {"references": ["Fedyukovich, Grigory, & Mover, Sergio. (2022). TACAS 23 Artifact Evaluation VM - Ubuntu 22.04 LTS (1.0). Zenodo. https://doi.org/"]}
DOI: 10.3886/e183662
title: Companion files for MENA health research using NHIS and MEPS linked data

description: This data repository houses SAS and STATA files that correspond with studies evaluating Middle Eastern and North African (MENA) health using linked 2000-2017 NHIS and 2001-2018 MEPS data.
DOI: 10.3886/e183662v1
title: Companion files for MENA health research using NHIS and MEPS linked data

description: This data repository houses SAS and STATA files that correspond with studies evaluating Middle Eastern and North African (MENA) health using linked 2000-2017 NHIS and 2001-2018 MEPS data.
DOI: 10.3886/e183662v2
title: Companion files for MENA health research using NHIS and MEPS linked data

description: This data repository houses SAS and STATA files that correspond with studies evaluating Middle Eastern and North African (MENA) health using linked 2000-2017 NHIS and 2001-2018 MEPS data.
DOI: 10.34740/kaggle/dsv/4876726
title: 2021 World Population (updated daily)
DOI: 10.5281/zenodo.7554349
title: Gender annotations for Multimodal Opinion-level Sentiment Intensity dataset (MOSI)

description: Annotations of perceived gender (female/male) for all files of the Multimodal Opinion-level Sentiment Intensity dataset (MOSI) [ arXiv:1606.06259]. The annotations were done by a single German and English speaking male annotator.
DOI: 10.5281/zenodo.7554348
title: Gender annotations for Multimodal Opinion-level Sentiment Intensity dataset (MOSI)

description: Annotations of perceived gender (female/male) for all files of the Multimodal Opinion-level Sentiment Intensity dataset (MOSI) [ arXiv:1606.06259]. The annotations were done by a single German and English speaking male annotator.
DOI: 10.6084/m9.figshare.21915000
title: Elias 2-24 reduced NACO data and ALMA+NACO models

description: Data and models associated with Pinte et al. 2023, MNRAS : <strong>Kinematic and thermal signatures of the directly imaged protoplanet candidate around Elias 2-24 </strong> <br> Data set includes : Reduced NACO data of Elias 2-24 (originally published in Jorquera et al. 2021, ApJ, 161, 146). Annular PCA post-processing of NACO data with 1 to 50 PCA compoments SPH models of a disk + 1Mjup to 10Mjup planet computed with PHANTOM (Price et al 2018) for 100 orbits. Setup file is included. Selection of radiative transfer models presented in Pinte et al 2023, using MCFOST (Pinte et al 2006, 2009). CO synthetic cubes and continuum images. Parameter file is included. The scripts to rerun the models and reproduce the figures are available at https://github.com/cpinte/elias2-24 <br> <br> <br>
DOI: 10.5281/zenodo.7554425
title: NMA MBES Tautra (NTNU)

description: Multibeam Echosounder Bathymetry, collected by the Norwegian Mapping Authority, released to NTNU AUR Lab The dataset and all derived products can be freely distributed according to Norwegian Mapping Authority document reference 16/01390-2. The dataset is released as open data by the Norwegian Mapping Authority according to Norwegian Licence for Open Government Data (NLOD) 2.0. https://data.norge.no/nlod/en/2.0
DOI: 10.5281/zenodo.7554424
title: NMA MBES Tautra (NTNU)

description: Multibeam Echosounder Bathymetry, collected by the Norwegian Mapping Authority, released to NTNU AUR Lab The dataset and all derived products can be freely distributed according to Norwegian Mapping Authority document reference 16/01390-2. The dataset is released as open data by the Norwegian Mapping Authority according to Norwegian Licence for Open Government Data (NLOD) 2.0. https://data.norge.no/nlod/en/2.0
DOI: 10.5281/zenodo.7554419
title: NMA MBES Selva (NTNU)

description: Multibeam Echosounder Bathymetry, collected by the Norwegian Mapping Authority, released to NTNU AUR Lab The dataset and all derived products can be freely distributed according to Norwegian Mapping Authority document reference 16/01390-2. The dataset is released as open data by the Norwegian Mapping Authority according to Norwegian Licence for Open Government Data (NLOD) 2.0. https://data.norge.no/nlod/en/2.0
DOI: 10.5281/zenodo.7554418
title: NMA MBES Selva (NTNU)

description: Multibeam Echosounder Bathymetry, collected by the Norwegian Mapping Authority, released to NTNU AUR Lab The dataset and all derived products can be freely distributed according to Norwegian Mapping Authority document reference 16/01390-2. The dataset is released as open data by the Norwegian Mapping Authority according to Norwegian Licence for Open Government Data (NLOD) 2.0. https://data.norge.no/nlod/en/2.0
DOI: 10.5281/zenodo.7554401
title: NMA MBES Nordleksa (NTNU)

description: Singlebeam and Multibeam Echosounder Bathymetry, collected by the Norwegian Mapping Authority, released to NTNU AUR Lab<br> The dataset and all derived products can be freely distributed according to Norwegian Mapping Authority document reference 16/01390-2. The dataset is released as open data by the Norwegian Mapping Authority according to Norwegian Licence for Open Government Data (NLOD) 2.0. https://data.norge.no/nlod/en/2.0
DOI: 10.5281/zenodo.7554400
title: NMA MBES Nordleksa (NTNU)

description: Singlebeam and Multibeam Echosounder Bathymetry, collected by the Norwegian Mapping Authority, released to NTNU AUR Lab<br> The dataset and all derived products can be freely distributed according to Norwegian Mapping Authority document reference 16/01390-2. The dataset is released as open data by the Norwegian Mapping Authority according to Norwegian Licence for Open Government Data (NLOD) 2.0. https://data.norge.no/nlod/en/2.0
DOI: 10.5281/zenodo.7554397
title: NMA MBES Agdenes (NTNU)

description: Multibeam Echosounder Bathymetry, collected by the Norwegian Mapping Authority, released to NTNU AUR Lab The dataset and all derived products can be freely distributed according to Norwegian Mapping Authority document reference 16/01390-2. The dataset is released as open data by the Norwegian Mapping Authority according to Norwegian Licence for Open Government Data (NLOD) 2.0. https://data.norge.no/nlod/en/2.0
DOI: 10.5281/zenodo.7554396
title: NMA MBES Agdenes (NTNU)

description: Multibeam Echosounder Bathymetry, collected by the Norwegian Mapping Authority, released to NTNU AUR Lab The dataset and all derived products can be freely distributed according to Norwegian Mapping Authority document reference 16/01390-2. The dataset is released as open data by the Norwegian Mapping Authority according to Norwegian Licence for Open Government Data (NLOD) 2.0. https://data.norge.no/nlod/en/2.0
DOI: 10.6084/m9.figshare.16437281
title: Scaling-up of the adsorption process of ammonia nitrogen onto expanded vermiculite using fixed-bed columns

description: Expanded vermiculite was used as an adsorbent to remove ammonia nitrogen from landfill leachate. Bench and pilot-scale adsorption experiments were performed with leachate collected from a closed sanitary landfill located in Curitiba, southern Brazil. At the bench-scale, two different heights of vermiculite and three different flow rates were tested using a fixed-bed column. These tests produced an average uptake capacity of 33.4 mg g<sup>−1</sup> for the ammonia nitrogen concentration of 2,560 mg L<sup>−1</sup>. The Yan model was used to determine the breakthrough and the exhaustion times due to the best fit of the data to this model. At the pilot-scale, the flow rate was determined from the shortest length of the mass transfer zone obtained from bench-scale experiments. Tests were performed using one stainless-steel column filled with 26.2 kg of expanded vermiculite, which resulted in a bed height of 1.6 m. A leachate flow rate of approximately 350 L d<sup>−1</sup> was applied to achieve the required contact time of 8.3 h. At this scale, an average uptake capacity of 18.1 mg g<sup>−1</sup> was obtained for the ammonia nitrogen concentration of 1,193 mg L<sup>−1</sup>. It is worth mentioning that the flow rate and the concentration of the adsorbate in the feeding solution are fundamental to improve the operational time of the fixed-bed column. The main goal of this research was the determination of operating conditions to scale-up the adsorption process of ammonia nitrogen onto expanded vermiculite. The contact time was a key parameter to reach this goal.
DOI: 10.6084/m9.figshare.16437281.v2
title: Scaling-up of the adsorption process of ammonia nitrogen onto expanded vermiculite using fixed-bed columns

description: Expanded vermiculite was used as an adsorbent to remove ammonia nitrogen from landfill leachate. Bench and pilot-scale adsorption experiments were performed with leachate collected from a closed sanitary landfill located in Curitiba, southern Brazil. At the bench-scale, two different heights of vermiculite and three different flow rates were tested using a fixed-bed column. These tests produced an average uptake capacity of 33.4 mg g<sup>−1</sup> for the ammonia nitrogen concentration of 2,560 mg L<sup>−1</sup>. The Yan model was used to determine the breakthrough and the exhaustion times due to the best fit of the data to this model. At the pilot-scale, the flow rate was determined from the shortest length of the mass transfer zone obtained from bench-scale experiments. Tests were performed using one stainless-steel column filled with 26.2 kg of expanded vermiculite, which resulted in a bed height of 1.6 m. A leachate flow rate of approximately 350 L d<sup>−1</sup> was applied to achieve the required contact time of 8.3 h. At this scale, an average uptake capacity of 18.1 mg g<sup>−1</sup> was obtained for the ammonia nitrogen concentration of 1,193 mg L<sup>−1</sup>. It is worth mentioning that the flow rate and the concentration of the adsorbate in the feeding solution are fundamental to improve the operational time of the fixed-bed column. The main goal of this research was the determination of operating conditions to scale-up the adsorption process of ammonia nitrogen onto expanded vermiculite. The contact time was a key parameter to reach this goal.
DOI: 10.6084/m9.figshare.21931131
title: Batoon et al_CDD_2023_Figshare.xlsx

description: This dataset contains raw data validating the fucntionality of the novel iCasp9 mouse through in vitro and in vivo experimentation. The data are formally presented in the manuscript entitled "Caspase-9 driven murine model of selective cell apoptosis and efefrocytosis".
DOI: 10.25934/pr00008436
title: Development of an Atherosclerosis Reversal Calculator

description: Atherosclerosis is the number one cause of death in the United States, more than all cancers combined.  Recent studies have demonstrated, using the invasive technique of intravascular ultrasound (IVUS), that atherosclerosis is reversible.  This information is critical to the practicing physician who can now prevent heart attacks and strokes in his/her patients.  Unfortunately, there are no non-invasive procedures to permit the physician to predict if his/her patient is reversing their atherosclerosis with statin treatment.

  The basis of the SATURN clinical trial was a comparison of rosuvastatin versus atorvastatin in their ability to reverse atherosclerosis as measured by the negative change in percent atherosclerosis volume (PAV).  Although this difference between these two medications did not reach statistical significance of p<0.05 (the difference was p<0.07), it was evident that rosuvastatin was statistically superior to atorvastatin in many secondary endpoints (e.g., total atherosclerosis volume (TAV)).  Both rosuvastatin and atorvastatin did significantly reverse atherosclerosis in the majority of patients (p<0.01).  Our proposal proposes an in depth regression analysis of cardiovascular risk factors demonstrating reduction in plaque content relating to the degree of reduction in cardiovascular risk factors effected by a patient’s response to rosuvastatin. 

     We will then use this analysis to develop an Atherosclerosis Reversal Calculator, which will be of great importance to the clinician in demonstrating to the patient that the rosuvastatin-induced reduction in cholesterol, LDL, CRP, etc., is reversing his/her vessels’ plaque.  This tool will permit the clinician to assess the likelihood of his/her patient to begin to reverse their atherosclerosis within two years.  A calculator approach has previously been done to predict cardiovascular risk (but not plaque reversal) by Framingham and the American Heart Association/American College of Cardiology.  These risk calculators are referred to as Pooled Cohort Equations (PCE) and are available on the internet at no charge.
DOI: 10.6084/m9.figshare.21883026
title: Figure source data and descriptive statistics

description: Raw data used to construct the figures and descriptive statistics in publication titled: FGF2-induced Redox Signaling: A Mechanism Regulating Pyruvate Dehydrogenase Driven Histone Acetylation and NANOG Upregulation
DOI: 10.6084/m9.figshare.21883026.v1
title: Figure source data and descriptive statistics

description: Raw data used to construct the figures and descriptive statistics in publication titled: FGF2-induced Redox Signaling: A Mechanism Regulating Pyruvate Dehydrogenase Driven Histone Acetylation and NANOG Upregulation
DOI: 10.3886/e183562v1
title: Dissertation quality

description: This data set has data of 367 respondents
DOI: 10.3886/e183562v2
title: Dissertation quality

description: This data set has data of 367 respondents
DOI: 10.3886/e183562
title: Dissertation quality

description: This data set has data of 367 respondents
DOI: 10.3886/e183562v3
title: Dissertation quality

description: This data set has data of 367 respondents
DOI: 10.34740/kaggle/dsv/4876823
title: YouTube Trending Video Dataset (updated daily)
DOI: 10.5281/zenodo.7554387
title: The Russian Invasion of Ukraine and the Strengthening of Ukrainian Identity among Former Soviet Union Immigrants from Ukraine: Israel as a Case Study

description: This research draws on data from an online questionnaire distributed through social networks in July 2022, while the Russian-Ukrainian war was ongoing. One of the main avenues for data collection was the Facebook forum "Russian women without a sense of humor and their friends." This forum was founded in 2014 by social activist and journalist Lena Russovsky, who had immigrated to Israel from Moscow at the age of nine. The group became very popular among Gen 1.5 Israelis, mostly women who immigrated from the FSU, and today numbers 40,000 members (Prashizky, 2020). The collected data were examined in accordance with the demographic and socio-economic characteristics set by the Israel Central Bureau of Statistics. The sample was determined to be representative exclusively of educated women who were born in Ukraine and are between the ages of 25 and 60. Therefore, it was decided to focus on this group of people.
description: Ruppin Academic Center
DOI: 10.5281/zenodo.7554386
title: The Russian Invasion of Ukraine and the Strengthening of Ukrainian Identity among Former Soviet Union Immigrants from Ukraine: Israel as a Case Study

description: This research draws on data from an online questionnaire distributed through social networks in July 2022, while the Russian-Ukrainian war was ongoing. One of the main avenues for data collection was the Facebook forum "Russian women without a sense of humor and their friends." This forum was founded in 2014 by social activist and journalist Lena Russovsky, who had immigrated to Israel from Moscow at the age of nine. The group became very popular among Gen 1.5 Israelis, mostly women who immigrated from the FSU, and today numbers 40,000 members (Prashizky, 2020). The collected data were examined in accordance with the demographic and socio-economic characteristics set by the Israel Central Bureau of Statistics. The sample was determined to be representative exclusively of educated women who were born in Ukraine and are between the ages of 25 and 60. Therefore, it was decided to focus on this group of people.
description: Ruppin Academic Center
DOI: 10.5281/zenodo.7554411
title: NMA MBES NTNU Ocean Lab (NTNU)

description: Multibeam Echosounder Bathymetry, collected by the Norwegian Mapping Authority, released to NTNU AUR Lab The dataset and all derived products can be freely distributed according to Norwegian Mapping Authority document reference 19/43984-3. The dataset is released as open data by the Norwegian Mapping Authority according to Norwegian Licence for Open Government Data (NLOD) 2.0. https://data.norge.no/nlod/en/2.0
DOI: 10.5281/zenodo.7554410
title: NMA MBES NTNU Ocean Lab (NTNU)

description: Multibeam Echosounder Bathymetry, collected by the Norwegian Mapping Authority, released to NTNU AUR Lab The dataset and all derived products can be freely distributed according to Norwegian Mapping Authority document reference 19/43984-3. The dataset is released as open data by the Norwegian Mapping Authority according to Norwegian Licence for Open Government Data (NLOD) 2.0. https://data.norge.no/nlod/en/2.0
DOI: 10.6084/m9.figshare.21931161
title: 1 km-resolution maps reveal increases in above- and belowground forest biomass carbon pools in China over the past 20 years

description: This dataset consists of annual forest aboveground and belowground biomass carbon stock maps for China during 2002~2021. The spatial resolution is 1 km. This new dataset was developed by combining SAR, optical, passive microwave remote sensing data with massive field investigations.
DOI: 10.6084/m9.figshare.20284713.v5
title: Data availability for Mirusviricota and the GOEV database

description: Data availability includes supplemental tables, FASTA files corresponding to the GPEV genomic database, genes, proteins, and phylogenetic trees.