cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.6545130
title: Comparison of pandemic excess mortality in 2020-2021 across different empirical calculations

description: Different modeling approaches can be used to calculate excess deaths for the COVID-19 pandemic period. We compared 6 calculations of excess deaths (4 previously published and two new ones that we performed with and without age-adjustment) for 2020-2021. With each approach, we calculated excess deaths metrics and the ratio R of excess deaths over recorded COVID-19 deaths. The main analysis focused on 33 high-income countries with weekly deaths in the Human Mortality Database (HMD at mortality.org) and reliable death registration. Secondary analyses compared calculations for other countries, whenever available. Across the 33 high-income countries, excess deaths were 2.0-2.8 million without age-adjustment, and 1.6-2.1 million with age-adjustment with large differences across countries. In our analyses after age-adjustment, 8 of 33 countries had no overall excess deaths; there was a death deficit in children; and 0.478 million (29.7%) of the excess deaths were in people &lt;65 years old. In countries like France, Germany, Italy, and Spain excess death estimates differed 2 to 4-fold between highest and lowest figures. The R values’ range exceeded 0.3 in all 33 countries. In 16 of 33 countries, the range of R exceeded 1. In 25 of 33 countries some calculations suggest R&gt;1 (excess deaths exceeding COVID-19 deaths) while others suggest R&lt;1 (excess deaths smaller than COVID-19 deaths). Inferred data from 4 evaluations for 42 countries and from 3 evaluations for another 98 countries are very tenuous Estimates of excess deaths are analysis-dependent and age-adjustment is important to consider. Excess deaths may be lower than previously calculated.
DOI: 10.5281/zenodo.6545129
title: Comparison of pandemic excess mortality in 2020-2021 across different empirical calculations

description: Different modeling approaches can be used to calculate excess deaths for the COVID-19 pandemic period. We compared 6 calculations of excess deaths (4 previously published and two new ones that we performed with and without age-adjustment) for 2020-2021. With each approach, we calculated excess deaths metrics and the ratio R of excess deaths over recorded COVID-19 deaths. The main analysis focused on 33 high-income countries with weekly deaths in the Human Mortality Database (HMD at mortality.org) and reliable death registration. Secondary analyses compared calculations for other countries, whenever available. Across the 33 high-income countries, excess deaths were 2.0-2.8 million without age-adjustment, and 1.6-2.1 million with age-adjustment with large differences across countries. In our analyses after age-adjustment, 8 of 33 countries had no overall excess deaths; there was a death deficit in children; and 0.478 million (29.7%) of the excess deaths were in people &lt;65 years old. In countries like France, Germany, Italy, and Spain excess death estimates differed 2 to 4-fold between highest and lowest figures. The R values’ range exceeded 0.3 in all 33 countries. In 16 of 33 countries, the range of R exceeded 1. In 25 of 33 countries some calculations suggest R&gt;1 (excess deaths exceeding COVID-19 deaths) while others suggest R&lt;1 (excess deaths smaller than COVID-19 deaths). Inferred data from 4 evaluations for 42 countries and from 3 evaluations for another 98 countries are very tenuous Estimates of excess deaths are analysis-dependent and age-adjustment is important to consider. Excess deaths may be lower than previously calculated.
DOI: 10.5281/zenodo.6562961
title: Svalbox-DOM_2019-0023

description: <strong>Model description: </strong><br> Overview of the lower section of Janusfjellet, exposing outcrops and sequences from the Jurassic to the Cretaceous.<br> <br> <strong>Data availability:</strong><br> All uploaded archives are to be extracted to the same directory for a functional working environment, i.e., at the very least consisting of a project folder with the data and metashape subdirectories. The included processing report specifies the processing parameters that were used as input for the processing software (Agisoft Metashape, v1.7.2.12040).<br> Exported model data use CRS epsg:32633.<br> <br> <strong>Show and visualise on Svalbox.no:</strong><br> Through Svalbox we aim to take geoscientific research and education to the next level – with the simple motto of placing all key information and data sets in their correct spatial position. We bring modern technology, in particular cost-effective digital outcrops, to complement more than 200 years of geoscientific research on Svalbard. Finally, Svalbox provides a sustainable platform for sharing results, workflows and teaching material with the wider geoscientific community.<br> <br> For more information, contact the Svalbox team at svalbox[at]gmail.com.
DOI: 10.5281/zenodo.6542692
title: Svalbox-DOM_2019-0023

description: <strong>Model description: </strong><br> Overview of the lower section of Janusfjellet, exposing outcrops and sequences from the Jurassic to the Cretaceous.<br> <br> <strong>Data availability:</strong><br> All uploaded archives are to be extracted to the same directory for a functional working environment, i.e., at the very least consisting of a project folder with the data and metashape subdirectories. The included processing report specifies the processing parameters that were used as input for the processing software (Agisoft Metashape, v1.7.2.12040).<br> Exported model data use CRS epsg:32633.<br> <br> <strong>Show and visualise on Svalbox.no:</strong><br> Through Svalbox we aim to take geoscientific research and education to the next level – with the simple motto of placing all key information and data sets in their correct spatial position. We bring modern technology, in particular cost-effective digital outcrops, to complement more than 200 years of geoscientific research on Svalbard. Finally, Svalbox provides a sustainable platform for sharing results, workflows and teaching material with the wider geoscientific community.<br> <br> For more information, contact the Svalbox team at svalbox[at]gmail.com.
DOI: 10.5523/bris.3ota45j8tbx332daufr3vp35ad
title: A Model to Investigate Exploiting Intrinsic Multi-Agent Heterogeneity for Spatial Interference Reduction in an Idealised Foraging Task

description: A simple simulation model used to investigate the use of intrinsic traits as a means to resolve spatial interference between 2 or more agents passing back and forth along a route with narrow tunnels. The model is written in python.
DOI: 10.5281/zenodo.6563105
title: The allocation of Chinese and Indian development finance in Nepal and its influence on local election results

description: This realease contains the used datasets and calculations for my Bachelorthesis about Indian and Chinese allocation of Overall Development Assistance in Nepal.
description: {"references": ["Asmus, G., Eichenauer, V.Z., Fuchs, A., and Parks, B. (2021). Does India Use Development Finance to Compete with China? A Subnational Analysis. AidData Working Paper #110. Williamsburg, VA: AidData at William & Mary.", "Custer, S., Dreher, A., Elston, T.B., Fuchs, A., Ghose, S., Lin, J., Malik, A., Parks, B.C., Russell, B., Solomon, K., Strange, A., Tierney, M.J., Walsh, K., Zaleski, L., and Zhang, S. 2021. Tracking Chinese Development Finance: An Application of AidData's TUFF 2.0 Methodology. Williamsburg, VA: AidData at William & Mary."]}
DOI: 10.5281/zenodo.6563144
title: EUCoM Open Data

description: Description to add
description: EMPIR Grant Agreement 17NRM03 EUCoM - This project has received funding from the EMPIR programme co-financed by the Participating States and from the European Union's Horizon 2020 research and innovation programme.
DOI: 10.5281/zenodo.6563143
title: EUCoM Open Data

description: Description to add
description: EMPIR Grant Agreement 17NRM03 EUCoM - This project has received funding from the EMPIR programme co-financed by the Participating States and from the European Union's Horizon 2020 research and innovation programme.
DOI: 10.5517/ccwpmgm
title: CCDC 825141: Experimental Crystal Structure Determination

description: Related Article: Huilu Wu, Tao Sun, Ke Li, Bin Liu, Fei Jia, Jingkun Yuan, Ying Bai|2012|Bioinorg.Chem.Appl.|2012|609796|doi:10.1155/2012/609796
DOI: 10.5281/zenodo.6542693
title: Svalbox-DOM_2019-0023

description: <strong>Model description: </strong><br> Overview of the lower section of Janusfjellet, exposing outcrops and sequences from the Jurassic to the Cretaceous.<br> <br> <strong>Data availability:</strong><br> All uploaded archives are to be extracted to the same directory for a functional working environment, i.e., at the very least consisting of a project folder with the data and metashape subdirectories. The included processing report specifies the processing parameters that were used as input for the processing software (Agisoft Metashape, v1.7.2.12040).<br> Exported model data use CRS epsg:32633.<br> <br> <strong>Show and visualise on Svalbox.no:</strong><br> Through Svalbox we aim to take geoscientific research and education to the next level – with the simple motto of placing all key information and data sets in their correct spatial position. We bring modern technology, in particular cost-effective digital outcrops, to complement more than 200 years of geoscientific research on Svalbard. Finally, Svalbox provides a sustainable platform for sharing results, workflows and teaching material with the wider geoscientific community.<br> <br> For more information, contact the Svalbox team at svalbox[at]gmail.com.
DOI: 10.5281/zenodo.6563146
title: Disco Time: The Relationship Between Perceived Duration and Tempo in Music

description: Data set from a study published in Music & Science.
description: Our perception of the duration of a piece of music is related to its tempo. When listening to music, absolute durations may seem longer as the tempo—the rate of an underlying pulse or beat—increases. Yet, the perception of tempo itself is not absolute. In a study on perceived tempo, participants were able to distinguish between different tempo-shifted versions of the same song (± 5 beats per minute (BPM)), yet their tempo ratings did not match the actual BPM rates; this finding was called tempo anchoring effect (TAE). In order to gain further insights into the relation between duration and tempo perception in music, the present study investigated the effect of musical tempo on two different duration measures, to see if there is an analog to the TAE in duration perception. Using a repeated-measures design, 32 participants (16 musicians) were randomly presented with instrumental excerpts of Disco songs at the original tempi and in tempo-shifted versions. The tasks were (a) to reproduce the absolute duration of each stimulus (14–20 s), (b) to estimate the absolute duration of the stimuli in seconds, and (c) to rate the perceived tempo. Results show that duration reproductions were longer with faster tempi, yet no such effect was found for duration estimations. Thus, lower-level reproductions were affected by the tempo, but higher-level estimations were not. The tempo-shifted versions showed no effect on both duration measures, suggesting that the tempo difference for the duration-lengthening effect requires a difference of at least 20 BPM, depending on the duration measure. Results of perceived tempo replicated the typical rating pattern of the TAE, but this was not found in duration measures. The roles of spontaneous motor tempo and musical experience are discussed, and implications for future studies are given.
DOI: 10.5281/zenodo.6563145
title: Disco Time: The Relationship Between Perceived Duration and Tempo in Music

description: Data set from a study published in Music & Science.
description: Our perception of the duration of a piece of music is related to its tempo. When listening to music, absolute durations may seem longer as the tempo—the rate of an underlying pulse or beat—increases. Yet, the perception of tempo itself is not absolute. In a study on perceived tempo, participants were able to distinguish between different tempo-shifted versions of the same song (± 5 beats per minute (BPM)), yet their tempo ratings did not match the actual BPM rates; this finding was called tempo anchoring effect (TAE). In order to gain further insights into the relation between duration and tempo perception in music, the present study investigated the effect of musical tempo on two different duration measures, to see if there is an analog to the TAE in duration perception. Using a repeated-measures design, 32 participants (16 musicians) were randomly presented with instrumental excerpts of Disco songs at the original tempi and in tempo-shifted versions. The tasks were (a) to reproduce the absolute duration of each stimulus (14–20 s), (b) to estimate the absolute duration of the stimuli in seconds, and (c) to rate the perceived tempo. Results show that duration reproductions were longer with faster tempi, yet no such effect was found for duration estimations. Thus, lower-level reproductions were affected by the tempo, but higher-level estimations were not. The tempo-shifted versions showed no effect on both duration measures, suggesting that the tempo difference for the duration-lengthening effect requires a difference of at least 20 BPM, depending on the duration measure. Results of perceived tempo replicated the typical rating pattern of the TAE, but this was not found in duration measures. The roles of spontaneous motor tempo and musical experience are discussed, and implications for future studies are given.
DOI: 10.3886/e114030v1-118562
title: Replication data for: Automation and New Tasks: How Technology Displaces and Reinstates Labor

description: We present a framework for understanding the effects of automation and other types of technological changes on labor demand, and use it to interpret changes in US employment over the recent past. At the center of our framework is the allocation of tasks to capital and labor—the task content of production. Automation, which enables capital to replace labor in tasks it was previously engaged in, shifts the task content of production against labor because of a displacement effect. As a result, automation always reduces the labor share in value added and may reduce labor demand even as it raises productivity. The effects of automation are counterbalanced by the creation of new tasks in which labor has a comparative advantage. The introduction of new tasks changes the task content of production in favor of labor because of a reinstatement effect, and always raises the labor share and labor demand. We show how the role of changes in the task content of production—due to automation and new tasks—can be inferred from industry-level data. Our empirical decomposition suggests that the slower growth of employment over the last three decades is accounted for by an acceleration in the displacement effect, especially in manufacturing, a weaker reinstatement effect, and slower growth of productivity than in previous decades.
DOI: 10.5281/zenodo.6337742
title: Alfahír [TEI]

description: This object contains is the most comprehensive curated version available at the date of publication. For further information on the content and for other fractions see: Alfahír.<br>Please fill in the following form before requesting access to this dataset:ACCES FORM
description: {"references": ["https://doi.org/10.5281/zenodo.3755323"]}
DOI: 10.5281/zenodo.6536024
title: Shallow and deep subsurface sediment remobilization and intrusion in the Middle Jurassic to Lower Cretaceous Agardhfjellet Formation (Svalbard) [Supplementary material/digital model data]

description: Supplementary model data for the publication Ogata et al. (in review): Most of the models suffer from incorrect location metadata, limiting their use to mostly qualitative interpretations. Shallow and deep subsurface sediment remobilization and intrusion in the Middle Jurassic to Lower Cretaceous Agardhfjellet Formation (Svalbard).
DOI: 10.5281/zenodo.6536023
title: Shallow and deep subsurface sediment remobilization and intrusion in the Middle Jurassic to Lower Cretaceous Agardhfjellet Formation (Svalbard) [Supplementary material/digital model data]

description: Supplementary model data for the publication Ogata et al. (in review): Most of the models suffer from incorrect location metadata, limiting their use to mostly qualitative interpretations. Shallow and deep subsurface sediment remobilization and intrusion in the Middle Jurassic to Lower Cretaceous Agardhfjellet Formation (Svalbard).
DOI: 10.5281/zenodo.6563152
title: Augmented Brain Tumor Multimodal Dataset Based on Reconstruction Consistency Loss

description: We solved the problem that the brain MRI data only has the T2 modality and the other three modalities are missing. The data synthesis of the missing modal I data was completed, and the missing modal data of Flair, T1, and T1ce were completed, and 10,685 pieces of data were generated for each group of modalities.
DOI: 10.5281/zenodo.6563133
title: Dynamic implicit modeling of tunnel unfavorable geology based on multi-source data fusion using support vector machine

description: This is the relevant data of the article "Dynamic implicit modeling of tunnel unfavorable geology based on multi-source data fusion using support vector machine"
DOI: 10.5281/zenodo.6563132
title: Dynamic implicit modeling of tunnel unfavorable geology based on multi-source data fusion using support vector machine

description: This is the relevant data of the article "Dynamic implicit modeling of tunnel unfavorable geology based on multi-source data fusion using support vector machine"
DOI: 10.6084/m9.figshare.16685041
title: TVC Array

description: Matlab Array of TVC Snowpit Data from <i>"Impact of measured and simulated tundra snowpack properties on heat transfer"</i>, Dutch et al. (2021). [DOI Pending]. <br>Version 2.0.<br><br>Code and other data at: https://github.com/V-Dutch/TVCSnowCLM<b><br></b><b>Abstract</b> Snowpack microstructure controls the transfer of heat to, and the temperature of, the underlying soils. In situ measurements of snow and soil properties from four field campaigns during two different winters (March and November 2018, January and March 2019) were compared to an ensemble of CLM5.0 (Community Land Model) simulations, at Trail Valley Creek, Northwest Territories, Canada. Snow MicroPenetrometer profiles allowed snowpack density and thermal conductivity to be derived at higher vertical resolution (1.25 mm) and a larger sample size (n = 1050) compared to traditional snowpit observations (3 cm vertical resolution; n = 115). Comparing measurements with simulations shows CLM overestimated snow thermal conductivity by a factor of 3, leading to a cold bias in wintertime soil temperatures (RMSE = 5.8 ℃). Bias-correction of the simulated thermal conductivity (relative to field measurements) improved simulated soil temperatures (RMSE = 2.1 ℃). Multiple linear regression shows the required correction factor is strongly related to snow depth (R<sup>2</sup> = 0.77, RMSE = 0.066) particularly early in the winter. The use of an alternative parameterisation of snow thermal conductivity also improved simulations of wintertime soil temperatures (RMSE = 2.5 ℃). Furthermore, CLM simulations did not adequately represent the observed high proportions of depth hoar. Addressing uncertainty in simulated snow properties and the corresponding heat flux is important, as wintertime soil temperatures act as a control on subnivean soil respiration, and hence impact Arctic winter carbon fluxes and budgets.
DOI: 10.6084/m9.figshare.16685041.v3
title: TVC Array

description: Matlab Array of TVC Snowpit Data from <i>"Impact of measured and simulated tundra snowpack properties on heat transfer"</i>, Dutch et al. (2021). [DOI Pending]. <br>Version 2.0.<br><br>Code and other data at: https://github.com/V-Dutch/TVCSnowCLM<b><br></b><b>Abstract</b> Snowpack microstructure controls the transfer of heat to, and the temperature of, the underlying soils. In situ measurements of snow and soil properties from four field campaigns during two different winters (March and November 2018, January and March 2019) were compared to an ensemble of CLM5.0 (Community Land Model) simulations, at Trail Valley Creek, Northwest Territories, Canada. Snow MicroPenetrometer profiles allowed snowpack density and thermal conductivity to be derived at higher vertical resolution (1.25 mm) and a larger sample size (n = 1050) compared to traditional snowpit observations (3 cm vertical resolution; n = 115). Comparing measurements with simulations shows CLM overestimated snow thermal conductivity by a factor of 3, leading to a cold bias in wintertime soil temperatures (RMSE = 5.8 ℃). Bias-correction of the simulated thermal conductivity (relative to field measurements) improved simulated soil temperatures (RMSE = 2.1 ℃). Multiple linear regression shows the required correction factor is strongly related to snow depth (R<sup>2</sup> = 0.77, RMSE = 0.066) particularly early in the winter. The use of an alternative parameterisation of snow thermal conductivity also improved simulations of wintertime soil temperatures (RMSE = 2.5 ℃). Furthermore, CLM simulations did not adequately represent the observed high proportions of depth hoar. Addressing uncertainty in simulated snow properties and the corresponding heat flux is important, as wintertime soil temperatures act as a control on subnivean soil respiration, and hence impact Arctic winter carbon fluxes and budgets.
DOI: 10.6084/m9.figshare.16685041.v2
title: TVC Array

description: Matlab Array of TVC Snowpit Data from <i>"Impact of measured and simulated tundra snowpack properties on heat transfer"</i>, Dutch et al. (2021). [DOI Pending]. <br>Version 2.0.<br><br>Code and other data at: https://github.com/V-Dutch/TVCSnowCLM<b><br></b><b>Abstract</b> Snowpack microstructure controls the transfer of heat to, and the temperature of, the underlying soils. In situ measurements of snow and soil properties from four field campaigns during two different winters (March and November 2018, January and March 2019) were compared to an ensemble of CLM5.0 (Community Land Model) simulations, at Trail Valley Creek, Northwest Territories, Canada. Snow MicroPenetrometer profiles allowed snowpack density and thermal conductivity to be derived at higher vertical resolution (1.25 mm) and a larger sample size (n = 1050) compared to traditional snowpit observations (3 cm vertical resolution; n = 115). Comparing measurements with simulations shows CLM overestimated snow thermal conductivity by a factor of 3, leading to a cold bias in wintertime soil temperatures (RMSE = 5.8 ℃). Bias-correction of the simulated thermal conductivity (relative to field measurements) improved simulated soil temperatures (RMSE = 2.1 ℃). Multiple linear regression shows the required correction factor is strongly related to snow depth (R<sup>2</sup> = 0.77, RMSE = 0.066) particularly early in the winter. The use of an alternative parameterisation of snow thermal conductivity also improved simulations of wintertime soil temperatures (RMSE = 2.5 ℃). Furthermore, CLM simulations did not adequately represent the observed high proportions of depth hoar. Addressing uncertainty in simulated snow properties and the corresponding heat flux is important, as wintertime soil temperatures act as a control on subnivean soil respiration, and hence impact Arctic winter carbon fluxes and budgets.
DOI: 10.6084/m9.figshare.19793770.v1
title: Prisma_Destripping_Code.zip

description: Here is the code of the spectral based regression algorithm for destriping the PRISMA dataset <br>