cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.1285/i11211156a36n2p91
title: Clio in cuffia. Sapere storico, podcast e sfide della divulgazione

description: Da alcuni anni il pubblico generalista sta riservando particolare attenzione ai podcast, e in generale alle produzioni audio, incentrati su temi, personaggi e periodi storici. Il fenomeno, nato come movimento di nicchia, si è irrobustito soprattutto durante la pandemia di Covid-19, quando più forte si è fatto sentire il bisogno di accedere a forme e modi originali di trasmissione del sapere storico, nell'impossibilità di accedere fisicamente ai luoghi della cultura e dell'istruzione. Il presente contributo intende prendere in esame il successo dei podcast storici nel tentativo di capire da un lato cosa distingue una produzione da una mera registrazione audio, dall'altro quali prodotti incontrino il gradimento del pubblico e perché. Infine, l'articolo cerca di comprendere quali temi storiografici si prestino meglio alla serialità tipica dei podcast e se alla base di tali produzioni vi sia, in maniera esclusiva, l'attività delle storiche e degli storici di professione.
description: In recent years, the generalist public has been paying particular attention to podcasts, and audio productions in general, focusing on historical themes, protagonists and periods. This phenomenon, which started out as a niche movement, grew stronger especially during the Covid-19 pandemic, when the need to access original forms and ways of transmitting historical knowledge was felt more acutely, in the impossibility of physically accessing cultural and educational institutions. This paper aims to examine the success of history podcasts in an attempt to understand on the one hand what sets apart a production from a simple audio recording; on the other hand, which products meet the taste of the public, and why. Finally, this paper attempts to understand which historiographical topics best lend themselves to the seriality typical of podcasts and whether the work of professional historians is exclusively behind such productions.
DOI: 10.1285/i11211156a36n2p101
title: Gli abstracts
DOI: 10.5517/ccdc.csd.cc2f23d1
title: CCDC 2236352: Experimental Crystal Structure Determination

description: Related Article: Ryohei Akiyoshi, Akinori Saeki, Kazuyoshi Ogasawara, Hirofumi Yoshikawa, Yuiga Nakamura, Daisuke Tanaka|2023|CrystEngComm|25|2990|doi:10.1039/D3CE00106G
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2f23f2
title: CCDC 2236353: Experimental Crystal Structure Determination

description: Related Article: Ryohei Akiyoshi, Akinori Saeki, Kazuyoshi Ogasawara, Hirofumi Yoshikawa, Yuiga Nakamura, Daisuke Tanaka|2023|CrystEngComm|25|2990|doi:10.1039/D3CE00106G
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.1285/i11211156a36n2p107
title: Gli autori
DOI: 10.26300/vs12-v537
title: Code for "The relationship of age and comorbid conditions to hospital and nursing home days in HIV-positive versus matched HIV-negative Medicaid recipients in United States"
DOI: 10.5517/ccdc.csd.cc2g0tht
title: CCDC 2264906: Experimental Crystal Structure Determination

description: Related Article: Zhao Xiu|2023|CSD Communication|||
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.6092/04f60223-4fe8-4ad9-ac7c-c5771597141b
title: Atlantic Sea DIVA 4D analysis of Water_body_ammonium

description: The "Atlantic Sea DIVA 4D analysis of Water_body_ammonium" is the 4D gridded analysis for Ammonium concentration parameters in the water column in the Atlantic Sea. The analysis was performed per season using DIVA software tool (Data-Interpolating Variational Analysis). The analyses products are stored as NetCDF CF files and made available as WMS layers for easy browsing and adding. Dynamic plots obtained as a combination of WPS/WMS (Density information available by colours, time series and vertical profiles) were uploaded to 'EMODnet Chemistry Viewing and Downloading Service'. Every step of the time dimension corresponds to a 10-year average moving from 1980 to 2014. The depth dimension spans from surface to the seafloor with 30 vertical levels. The data used as input for DIVA have been extracted from the EMODnet Chemistry Download Service: http://emodnet-chemistry.maris2.nl/v_cdi_v3/search.asp
DOI: 10.6092/c19bde54-af7c-47b6-9854-84f8a0db2e12
title: Atlantic Sea DIVA 4D analysis of Water body chlorophyll-a

description: The "Atlantic Sea DIVA 4D analysis of Water body chlorophyll-a" is the 4D gridded analysis for chlorophyll pigment concentrations in water bodies in the North Sea. The analysis was performed per season using DIVA software tool (Data-Interpolating Variational Analysis). The analyses products are stored as NetCDF CF files and made available as WMS layers for easy browsing and adding. Dynamic plots obtained as a combination of WPS/WMS (Density information available by colours, time series and vertical profiles) were uploaded to 'EMODnet Chemistry Viewing and Downloading Service'. Every step of the time dimension corresponds to a 10-year average moving from 1985 to 2014. The depth dimension spans from surface to the seafloor with 14 vertical levels. The data used as input for DIVA have been extracted from the EMODnet Chemistry Download Service: http://emodnet-chemistry.maris2.nl/v_cdi_v3/search.asp
DOI: 10.6092/5ae1f1ce-6c17-49a0-bd6c-a81a2d89173c
title: Atlantic Sea DIVA 4D analysis of Water_body_dissolved_oxygen_concentration

description: The "Atlantic Sea DIVA 4D analysis of Water_body_dissolved_oxygen_concentration" is the 4D gridded analysis for Dissolved oxygen concentration parameters in sediment pore waters in the Atlantic Sea. The analysis was performed per season using DIVA software tool (Data-Interpolating Variational Analysis). The analyses products are stored as NetCDF CF files and made available as WMS layers for easy browsing and adding. Dynamic plots obtained as a combination of WPS/WMS (Density information available by colours, time series and vertical profiles) were uploaded to 'EMODnet Chemistry Viewing and Downloading Service'. Every step of the time dimension corresponds to a 10-year average moving from 1963 to 2014. The depth dimension spans from surface to the seafloor with 30 vertical levels. The data used as input for DIVA have been extracted from the EMODnet Chemistry Download Service: http://emodnet-chemistry.maris2.nl/v_cdi_v3/search.asp
DOI: 10.6092/c413dced-cd97-4c49-bf94-9ba57824492e
title: Atlantic Sea DIVA 4D analysis of Water_body_nitrate_plus_nitrite

description: The "Atlantic Sea DIVA 4D analysis of Water_body_nitrate_plus_nitrite" is the 4D gridded analysis for Nitrate+nitrite concentration parameters in the water column in the Atlantic Sea. The analysis was performed per season using DIVA software tool (Data-Interpolating Variational Analysis). The analyses products are stored as NetCDF CF files and made available as WMS layers for easy browsing and adding. Dynamic plots obtained as a combination of WPS/WMS (Density information available by colours, time series and vertical profiles) were uploaded to 'EMODnet Chemistry Viewing and Downloading Service'. Every step of the time dimension corresponds to a 10-year average moving from 1972 to 2014. The depth dimension spans from surface to the seafloor with 30 vertical levels. The data used as input for DIVA have been extracted from the EMODnet Chemistry Download Service: http://emodnet-chemistry.maris2.nl/v_cdi_v3/search.asp
DOI: 10.6092/a8396ca9-558d-4323-9ff1-3385cab095d5
title: Atlantic Sea DIVA 4D analysis of Water_body_phosphate

description: The "Atlantic Sea DIVA 4D analysis of Water_body_phosphate" is the 4D gridded analysis for Phosphate concentration parameters in the water column in the Atlantic Sea. The analysis was performed per season using DIVA software tool (Data-Interpolating Variational Analysis). The analyses products are stored as NetCDF CF files and made available as WMS layers for easy browsing and adding. Dynamic plots obtained as a combination of WPS/WMS (Density information available by colours, time series and vertical profiles) were uploaded to 'EMODnet Chemistry Viewing and Downloading Service'. Every step of the time dimension corresponds to a 10-year average moving from 1963 to 2014. The depth dimension spans from surface to the seafloor with 30 vertical levels. The data used as input for DIVA have been extracted from the EMODnet Chemistry Download Service: http://emodnet-chemistry.maris2.nl/v_cdi_v3/search.asp
DOI: 10.6092/8835d4d8-120c-4fb9-9f4b-efea6990f743
title: Atlantic Sea DIVA 4D analysis of Water_body_silicate

description: The "Atlantic Sea DIVA 4D analysis of Water_body_silicate" is the 4D gridded analysis for Ammonium concentration parameters in the water column in the Atlantic Sea. The analysis was performed per season using DIVA software tool (Data-Interpolating Variational Analysis). The analyses products are stored as NetCDF CF files and made available as WMS layers for easy browsing and adding. Dynamic plots obtained as a combination of WPS/WMS (Density information available by colours, time series and vertical profiles) were uploaded to 'EMODnet Chemistry Viewing and Downloading Service'. Every step of the time dimension corresponds to a 10-year average moving from 1980 to 2014. The depth dimension spans from surface to the seafloor with 30 vertical levels. The data used as input for DIVA have been extracted from the EMODnet Chemistry Download Service: http://emodnet-chemistry.maris2.nl/v_cdi_v3/search.asp
DOI: 10.13120/e88734d3-b1a9-45a8-b5ad-29d6599000a0
title: Seafloor Litter - Composition of litter according to material categories in percent per trawl 2007/2021 v2021

description: This visualization product displays the marine litter material categories percentage per trawl per year.<br><br>EMODnet Chemistry included the collection of marine litter in its 3rd phase. Since the beginning of 2018, data of seafloor litter collected by international fish-trawl surveys have been gathered and processed in the EMODnet Chemistry Marine Litter Database (MLDB). <br>The harmonization of all the data has been the most challenging task considering the heterogeneity of the data sources, sampling protocols (OSPAR and MEDITS protocols) and reference lists used on a European scale. Moreover, within the same protocol, different gear types are deployed during fishing bottom trawl surveys.<br><br>Unlike other EMODnet seafloor litter products, all trawls surveyed since 2007 are included in this map even if the wingspread and/or the distance are unknown.<br>Only surveys with an unknown number of items were excluded from this product.<br><br>Harmonization of the material categories between ICES and MEDITS lists has been performed and the following calculation has been applied: <br>Material % = (∑Number of items of each material category*100)/(∑Number of items of all material categories)<br><br>More information on data processing and calculation are detailed in the document attached.
DOI: 10.13120/afe2d718-41e6-4bb4-95f5-ad836a45c891
title: Seafloor litter - Density per trawl normalized per km² 2011/2021 v2021

description: This visualization product displays the density of seafloor litter per trawl per year.<br><br>EMODnet Chemistry included the collection of marine litter in its 3rd phase. Since the beginning of 2018, data of seafloor litter collected by international fish-trawl surveys have been gathered and processed in the EMODnet Chemistry Marine Litter Database (MLDB). <br>The harmonization of all the data has been the most challenging task considering the heterogeneity of the data sources, sampling protocols (OSPAR and MEDITS protocols) and reference lists used on a European scale. Moreover, within the same protocol, different gear types are deployed during fishing bottom trawl surveys.<br><br>In cases where the wingspread and/or number of items were unknown, data could not be used because these fields are needed to calculate the density. Data collected before 2011 are affected by this filter.<br><br>When the distance reported in the data was null, it was calculated from:<br>- the ground speed and the haul duration using this formula: Distance (km) = Haul duration (h) * Ground speed (km/h);<br>- the trawl coordinates if the ground speed and the haul duration were not filled in.<br><br>The swept area is calculated from the wingspread (which depends on the fishing gear type) and the distance trawled:<br>Swept area (km²) = Distance (km) * Wingspread (km)<br><br>Densities have been calculated on each trawl and year using the following computation:<br>Density (number of items per km²) = ∑Number of items / Swept area (km²)<br><br>Percentiles 50, 75, 95 & 99 have been calculated taking into account data for all years.<br><br>More information on data processing and calculation are detailed in the document attached.
DOI: 10.13120/e410bd8c-ad38-482b-8a76-d867a40746fc
title: Seafloor litter - Fishing related items density normalized per km² 2011/2021 v2021

description: This visualization product displays fishing related items density per trawl per year.<br><br>EMODnet Chemistry included the collection of marine litter in its 3rd phase. Since the beginning of 2018, data of seafloor litter collected by international fish-trawl surveys have been gathered and processed in the EMODnet Chemistry Marine Litter Database (MLDB). <br>The harmonization of all the data has been the most challenging task considering the heterogeneity of the data sources, sampling protocols (OSPAR and MEDITS protocols) and reference lists used on a European scale. Moreover, within the same protocol, different gear types are deployed during fishing bottom trawl surveys.<br><br>In cases where the wingspread and/or number of items were unknown, data could not be used because these fields are needed to calculate the density. Data collected before 2011 are affected by this filter.<br><br>When the distance reported in the data was null, it was calculated from:<br>- the ground speed and the haul duration using this formula: Distance (km) = Haul duration (h) * Ground speed (km/h);<br>- the trawl coordinates if the ground speed and the haul duration were not filled in.<br><br>The swept area is calculated from the wingspread (which depends on the fishing gear type) and the distance trawled:<br>Swept area (km²) = Distance (km) * Wingspread (km)<br><br>Densities have been calculated on each trawl and year using the following computation:<br>Density of fishing related items (number of items per km²) = ∑Number of fishing related items / Swept area (km²)<br><br>Percentiles 50, 75, 95 & 99 have been calculated taking into account data for all years.<br><br>Fishing related items reference codes taken into account for this product and information on data processing and calculation are detailed in the document attached p22.
DOI: 10.13120/af33bb27-a321-4376-a42e-6f856a936cd9
title: Seafloor litter - Plastic bags density normalized per km² 2012/2021 v2021

description: This visualization product displays plastic bags density per trawl per year.<br><br>EMODnet Chemistry included the collection of marine litter in its 3rd phase. Since the beginning of 2018, data of seafloor litter collected by international fish-trawl surveys have been gathered and processed in the EMODnet Chemistry Marine Litter Database (MLDB). <br>The harmonization of all the data has been the most challenging task considering the heterogeneity of the data sources, sampling protocols (OSPAR and MEDITS protocols) and reference lists used on a European scale. Moreover, within the same protocol, different gear types are deployed during fishing bottom trawl surveys.<br><br>In cases where the wingspread and/or number of items were unknown, data could not be used because these fields are needed to calculate the density. Data collected before 2011 are affected by this filter.<br><br>When the distance reported in the data was null, it was calculated from:<br>- the ground speed and the haul duration using this formula: Distance (km) = Haul duration (h) * Ground speed (km/h);<br>- the trawl coordinates if the ground speed and the haul duration were not filled in.<br><br>The swept area is calculated from the wingspread (which depends on the fishing gear type) and the distance trawled:<br>Swept area (km²) = Distance (km) * Wingspread (km)<br><br>Densities have been calculated on each trawl and year using the following computation:<br>Density of plastic bags (number of items per km²) = ∑Number of plastic bags related items / Swept area (km²)<br><br>Percentiles 50, 75, 95 & 99 have been calculated taking into account data for all years.<br><br>Plastic bags reference codes taken into account for this product and information on data processing and calculation are detailed in the document attached p22.
DOI: 10.21227/m9d4-3d74
title: 	Distributed Joint Resource Allocation for Underwater Acoustic  		Communication Networks: An Extended Bandit Learning Game Approach

description: This paper copes with a joint discrete-channel and continuous-power allocation problem for underwater acoustic communication networks. Hybrid discrete-continuous solution spaces, inevitable interference among multiple users, and unknown time-varying underwater-acoustic communication environments make the proposed problem full of challenges. Firstly, combining multi-armed bandit theory and game theory, an adversarial multiplayer bandit game model is developed to enable the proposed problem to be solved distributedly without any prior perfect channel information. Secondly, a dynamic finite discrete strategy pool learning structure is proposed, which makes the finite discrete strategy pool evolve efficiently over time. Namely, at each learning time, the player can quickly decide based on a finite discrete strategy pool, thereby improving the learning efficiency. With the development of learning time, the dynamic strategy pool can efficiently evolve to extend the whole discrete-continuous space, thereby avoiding missing the real best solution.  Consequently, the bottleneck, which bandit learning algorithms can not be applied to continuous solution spaces, is broken by the proposed learning structure to achieve the best solution of the hybrid discrete-continuous space in an efficient low-cost fashion. Thirdly, a selection probability setting rule is proposed to make the real utility level of strategies for the dynamic strategy pool able to be rapidly identified, thereby significantly enhancing the quick search ability of dynamic best strategies. Finally, the superiority of the proposed algorithm is demonstrated by extensive simulation results.
DOI: 10.13120/ee3dd868-d239-4988-9904-0164df7983c3
title: Seafloor litter - Trawls locations 2006/2021 v2021

description: This visualization product displays the location of all the surveys present in the EMODnet marine litter database (MLDB). The different fishing gears used are represented by different colors. <br><br>EMODnet Chemistry included the collection of marine litter in its 3rd phase. Since the beginning of 2018, data of seafloor litter collected by international fish-trawl surveys have been gathered and processed in the EMODnet Chemistry Marine Litter Database (MLDB). <br>The harmonization of all the data has been the most challenging task considering the heterogeneity of the data sources, sampling protocols (OSPAR and MEDITS protocols) and reference lists used on a European scale. Moreover, within the same protocol, different gear types are deployed during fishing bottom trawl surveys.<br><br>Unlike other EMODnet seafloor litter products, all trawls surveyed since 2006 are included in this map even if the wingspread and/or the distance are unknown.<br>Only surveys with an unknown number of items were excluded from this product.<br><br>More information on data processing and calculation are detailed in the document attached.
DOI: 10.6084/m9.figshare.23055974
title: 2023_Wurm_SurpriseMinimization

description: EEG data repository for Wurm F, Ernst B, Steinhauser M (2023) Surprise-minimization as a solution to the structural credit assignment problem (PsyArXiv, https://doi.org/10.31234/osf.io/kmqp7). For questions, @fwurm / wurmfranz@gmx.de <br> ############################## This work is licensed under a [Creative Commons Attribution 4.0 International License][cc-by]. [![CC BY 4.0][cc-by-image]][cc-by] [cc-by]: http://creativecommons.org/licenses/by/4.0/ [cc-by-image]: https://i.creativecommons.org/l/by/4.0/88x31.png [cc-by-shield]: https://img.shields.io/badge/License-CC BY 4.0-lightgrey.svg
DOI: 10.6084/m9.figshare.23055974.v1
title: 2023_Wurm_SurpriseMinimization

description: EEG data repository for Wurm F, Ernst B, Steinhauser M (2023) Surprise-minimization as a solution to the structural credit assignment problem (PsyArXiv, https://doi.org/10.31234/osf.io/kmqp7). For questions, @fwurm / wurmfranz@gmx.de <br> ############################## This work is licensed under a [Creative Commons Attribution 4.0 International License][cc-by]. [![CC BY 4.0][cc-by-image]][cc-by] [cc-by]: http://creativecommons.org/licenses/by/4.0/ [cc-by-image]: https://i.creativecommons.org/l/by/4.0/88x31.png [cc-by-shield]: https://img.shields.io/badge/License-CC BY 4.0-lightgrey.svg
DOI: 10.6084/m9.figshare.22782212.v1
title: Data for Johnson et al., '<em>Into the danger zone: how the within-host distribution of parasites controls virulence</em>'

description: These files contain the data (field & laboratory) and metadata from Johnson et al. "<em>Into the danger zone: how the within-host distribution of parasites controls virulence</em>"
DOI: 10.3886/e191903
title: AP Calculus and Science Coursetaking: Their Relationships with Choosing a STEM Major and Expecting to Be in a STEM Occupation

description: Some researchers have questioned whether there is a causal connection between Advanced Placement (AP) STEM coursetaking and the choice of a STEM college major and a STEM occupation. Their research findings strongly suggest that if prior interest in STEM as well as other possible confounders are taken into account, the relationships of taking AP mathematics to expecting to be in a STEM major and/or a STEM occupation are small to non-existent. Results from the current study, which uses data from a national longitudinal sample, actual measures of who majors in STEM, and prior interest in STEM along with other possible confounders, indicate that taking AP mathematics and AP science courses is significantly related to majoring in STEM and/or expecting to be in a STEM occupation at age 30—the sole exception being the taking of AP statistics.