cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.14278/rodare.3040
title: Optimierte Prozessketten für hydromechanisches Li-Ionen-Batterie-Recycling Helmholtz-Institut Freiberg für Ressourcentechnologie (HIF)

description: The study aimed to develop design for recycling (DfR) recommendations for NMC 811 batteries using a well-defined recycling process. The methodology integrated comprehensive empirical and analytical measurements to construct an accurate thermodynamic simulation of material and substance flow throughout the recycling process. This involved stages of manual dismantling, followed by mechanical, physical, and metallurgical processing of the NMC 811 battery cells. Thermodynamic simulations were conducted using FactSage™ version 8.2 and HSC Chemistry 10 version 10.3.7.1 software to model the recovery of lithium present in the black mass via metallurgical processing methods. The results provided a detailed breakdown of the material composition post-dismantling, revealing that separated cells containing the active NMC 811 material constituted 63.7% of the total weight. The study also introduced a recyclability index to quantify the recovery rates of individual elements, showcasing a recovery rate of 59.7% for lithium and an overall recycling index of 59.4%. The generated data was meticulously formatted to ensure clear comprehension, thereby supporting informed decision-making for optimizing recycling strategies. Key conclusions emphasized the importance of integrating comprehensive material flow analysis and adopting a product-centric approach to enhance recycling efficiency. Recommendations included optimizing the dismantling process to achieve a 21% reduction in environmental impacts, such as Global Warming Potential, and avoiding the use of materials that would be lost in the recycling route. These measures are projected to increase the recycling index to 90%, thereby significantly improving the overall sustainability of the recycling process for NMC 811 batteries.
description: Förderkennzeichen: 03XP0339B; Leitung: AP 6. Prozesssimulation der technisch-physikalischen Aspekte der Recyclingverfahren (Energieströme, Materialeigenschaften, Prozessparameter). AP8. Ableitung von Design-for-Recycling-Konzepten auf Material- bis Zellebene.
DOI: 10.15468/dl.f756xd
title: Occurrence Download

description: A dataset containing 1 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Thailand",
 "DatasetKey is iNaturalist Research-grade Observations",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Hoya engleriana Hosseus",
 "Year 2000-2024"
 ]
}

 The dataset includes 1 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0018894-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.21227/v1vb-px47
title: A Novel Sonar Image Preprocessing Method for AUV Positioning Based on Underwater SLAM

description: The research data folder  contains two primary subfolders, namely the "exper1" and "exper2" folders. These folders hold the experimental data and results relevant to our study.The "exper1" folder is dedicated to the experimental results discussed in Article V.B. Specifically, it contains data on the positioning results of an AUV following a regular path. This folder is comprehensive, including a total of 31 files. Among these, there is one file that contains the real trajectory data, providing the actual path taken by the AUV during the experiment. The remaining 30 files are a collection of comparative experimental results, which are crucial for understanding the performance and accuracy of the AUV's localization under regular path conditions.  Similarly, the "exper2" folder contains another set of data pertaining to Article V.C. This set of experimental results focuses on the localization of the AUV when it follows irregular paths. Like the "exper1" folder, the "exper2" folder also contains a total of 31 files. This includes one file with the real trajectory data, which records the actual irregular path taken by the AUV. The remaining 30 files in this folder are comparative experimental data, which are essential for analyzing how the AUV performs localization tasks under more complex and unpredictable path conditions.
DOI: 10.5281/zenodo.12703719
title: Emission calculation for cut and fill works
DOI: 10.5281/zenodo.12703720
title: Emission calculation for cut and fill works
DOI: 10.15468/mmpak9
title: 2023 am_observation_nsmk_14

description: 2023 National Science Museum of Korea AM Resource
DOI: 10.15468/3u69xe
title: 2023 pi_observation_nsmk_111

description: 2023 National Science Museum of Korea PI Resource
DOI: 10.15468/dl.456amf
title: Occurrence Download

description: A dataset listing the 117 species recorded in GBIF matching the query:
{
 "and" : [
 "DatasetKey is Herbario de la Facultad de Ciencias Biológicas de la Universidad Complutense de Madrid (MACB)",
 "Geometry POLYGON((-8.89023 40.72636,-6.13002 40.72636,-6.13002 41.95476,-8.89023 41.95476,-8.89023 40.72636))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Bryophyta"
 ]
}

 The dataset's 117 records were derived from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0018891-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.w57wkq
title: Occurrence Download

description: A dataset containing 30 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((101.66675 22.76979,98.93016 20.51613,97.48138 19.22832,98.33991 16.81368,97.85699 15.04294,99.57406 12.03806,98.60821 9.24781,100.00333 5.75999,102.73993 5.86731,100.86187 7.26244,100.00333 10.26732,100.64724 12.36001,101.66675 12.36001,105.12181 8.51808,109.60824 11.17952,109.33994 15.57953,105.79847 19.01369,106.22774 20.67711,107.13994 21.42833,106.12042 22.98443,105.31554 23.1454,101.66675 22.76979))",
 "TaxonKey is Ziziphus cambodiana Pierre"
 ]
}

 The dataset includes 30 records from 6 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0018895-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.10042986
title: microCT dataset of cybertype - Xyloplax princealberti n. sp. / SMF 6936

description: A specimen (SMF 6936) preserved in 95% was scanned using a Werth Tomoscope® XS Plus 200 microCT with the following scan parameters: 85 kV voltage, 188 µA generator current, 16 W generator power. Exposure time was 666 ms with a total of 2700 projections (3 projections were averaged). The voxel resolution is 3.56 µm. Surface renderings were generated with the software Drishti v3.1. (National University, Canberra, Australia)
DOI: 10.5281/zenodo.10042987
title: microCT dataset of cybertype - Xyloplax princealberti n. sp. / SMF 6936

description: A specimen (SMF 6936) preserved in 95% was scanned using a Werth Tomoscope® XS Plus 200 microCT with the following scan parameters: 85 kV voltage, 188 µA generator current, 16 W generator power. Exposure time was 666 ms with a total of 2700 projections (3 projections were averaged). The voxel resolution is 3.56 µm. Surface renderings were generated with the software Drishti v3.1. (National University, Canberra, Australia)
DOI: 10.15468/dl.zprvdm
title: Occurrence Download

description: A dataset containing 104 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is one of (Human Observation, Occurrence evidence)",
 "Continent is Asia",
 "Country is one of (China, Hong Kong, Macao)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Elaphe carinata (Günther, 1864)"
 ]
}

 The dataset includes 104 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0018897-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.8099792
title: GEOLAB - CLARIFIER project

description: The existing Critical Infrastructure (CI) of Europe in the water, energy, urban and transport sector is facing major challenges because of pressures such as climate change, extreme weather, geo-hazards, ageing and increased usage, in combination with pivotal changes in the CI to meet long-term societal goals (e.g., energy transition). To address these challenges, scientific research and innovative solutions are needed that can only be achieved by an interdisciplinary, cross-boundary approach and by equipping expert teams with the most advanced suite of physical research infrastructure available. This will allow them to work across spatial scales, explore different theories that describe the pressures and adopt innovative techniques in the development of practical solutions.


The GEOLAB Research Infrastructure (RI) consists of 11 unique installations in Europe developed to study subsurface behavior and the interaction of the subsurface with structural CI elements (e.g., a bridge) and the environment. The overarching aim of GEOLAB is to integrate and advance these key national research infrastructures towards a one-stop-shop of excellent physical research infrastructure specifically for performing ground-breaking research and innovation to address the challenges faced by the CI of Europe. During the GEOLAB Transnational Access (TA), users outside the consortium gain access to the GEOLAB installations to perform research and innovation.


One of the GEOLAB’S TA projects is the project CLARIFIER. For this project, centrifuge tests were conducted at Deltares, in The Netherlands. The main objectives of the CLARIFIER tests are: (a) to evaluate how well partially decomposed fibrous peat can be modelled in a geotechnical centrifuge and to (ii) understand the failure mechanisms under light weight embankments.
DOI: 10.25442/hku.26149387
title: <i>Supporting data for "</i>Towards a Set of Gamification Instructional Design Guidelines for Supporting Intrinsic Motivation"

description: The present study proposed a set of gamification instructional design guidelines to support students' intrinsic motivation. The dataset consists of raw and processed data used to support the doctoral thesis. The subfolder named "Chapter 5 - Pilot Study" corresponds to Chapter 5 and the subfolder named "Chapter 6 - Study Four" corresponds to Chapter 6. Quantitative data included students' motivation scores examined through the motivation questionnaire and Moodle log data. In addition, students' course scores were included for comparison purposes. Qualitative data included transcripts of students' interviews in which students responded to how they perceived their learning experience guided by the design guidelines.
DOI: 10.25442/hku.26149387.v1
title: <i>Supporting data for "</i>Towards a Set of Gamification Instructional Design Guidelines for Supporting Intrinsic Motivation"

description: The present study proposed a set of gamification instructional design guidelines to support students' intrinsic motivation. The dataset consists of raw and processed data used to support the doctoral thesis. The subfolder named "Chapter 5 - Pilot Study" corresponds to Chapter 5 and the subfolder named "Chapter 6 - Study Four" corresponds to Chapter 6. Quantitative data included students' motivation scores examined through the motivation questionnaire and Moodle log data. In addition, students' course scores were included for comparison purposes. Qualitative data included transcripts of students' interviews in which students responded to how they perceived their learning experience guided by the design guidelines.
DOI: 10.18112/openneuro.ds004640.v1.0.3
title: Sustaining wakefulness: Brainstem connectivity in human consciousness
DOI: 10.15468/dl.8td5qy
title: Occurrence Download

description: A dataset containing 145 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is one of (Human Observation, Occurrence evidence)",
 "Continent is Asia",
 "Country is one of (China, Hong Kong, Macao)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Elaphe taeniura (Cope, 1861)"
 ]
}

 The dataset includes 145 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0018899-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.a7pb7f
title: Occurrence Download

description: A dataset containing 5 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is one of (Human Observation, Occurrence evidence)",
 "Continent is Asia",
 "Country is one of (China, Hong Kong, Macao)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Elaphe moellendorffi (Boettger, 1886)"
 ]
}

 The dataset includes 5 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0018898-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.y2t878
title: Occurrence Download

description: A dataset containing 23 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is one of (Human Observation, Occurrence evidence)",
 "Continent is Asia",
 "Country is one of (China, Hong Kong, Macao)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Gonyosoma frenatum (Gray, 1853)"
 ]
}

 The dataset includes 23 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0018900-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.25442/hku.26207357
title: Supporting data for "Towards an instructional design model for supporting students’ self-regulated learning and learning performance in flipped classrooms"

description: Existing empirical studies on implementing SRL support in flipped classrooms have adopted various designs and found inconsistent results, with some studies reporting positive outcomes and others not. For this reason, it is essential to understand why there were inconsistent results, to explore how to design effective SRL, and to develop a guiding framework. Therefore, the HPFR model and a set of design principles were proposed by the author by synthesising previous empirical findings and literature-based rationales. Two empirical studies were conducted and provided evidence of the positive impact of the HPFR model on students’ SRL development and learning performance in flipped classrooms. The open-ended survey and interview responses from the students indicated that they positively perceived the SRL supports designed based on the HPFR model.
DOI: 10.25442/hku.26207357.v1
title: Supporting data for "Towards an instructional design model for supporting students’ self-regulated learning and learning performance in flipped classrooms"

description: Existing empirical studies on implementing SRL support in flipped classrooms have adopted various designs and found inconsistent results, with some studies reporting positive outcomes and others not. For this reason, it is essential to understand why there were inconsistent results, to explore how to design effective SRL, and to develop a guiding framework. Therefore, the HPFR model and a set of design principles were proposed by the author by synthesising previous empirical findings and literature-based rationales. Two empirical studies were conducted and provided evidence of the positive impact of the HPFR model on students’ SRL development and learning performance in flipped classrooms. The open-ended survey and interview responses from the students indicated that they positively perceived the SRL supports designed based on the HPFR model.
DOI: 10.5281/zenodo.10075253
title: Results and code associated with «Predictability of ecological and evolutionary dynamics in a changing world»

description: Below you'll find code and data associated with the following preprint:
Bozzuto, C, Ives, AR (2023): Predictability of ecological and evolutionary dynamics in a changing world. bioRxiv. https://doi.org/10.1101/2023.11.01.565089
ABSTRACT: Ecological and evolutionary predictions are being increasingly employed to inform decision-makers confronted with intensifying pressures menacing life on Earth. For these efforts to effectively guide conservation actions, knowing the limit of predictability is pivotal. In this study, we provide realistic expectations about the enterprise of predicting changes in ecological and evolutionary observations through time. We begin with an intuitive explanation of predictability (that is, the extent to which predictions are possible) employing an easy-to-use metric, predictive power PP(t). To illustrate the challenge of forecasting, we then show that among insects, birds, fishes, and mammals (i) 50% of the populations are predictable at most one year in advance, and (ii) the median one-year-ahead predictive power corresponds to a sobering prediction R^2 of approximately 20%. Nonetheless, predictability is not an immutable property of ecological systems. For example, different harvesting strategies can impact the predictability of exploited populations to varying degrees. Moreover, considering multivariate time series, incorporating explanatory variables or accounting for time trends (environmental forcing) can enhance predictability. To effectively address the urgent challenge of biodiversity loss, researchers and practitioners must be aware of the predictive information within the available data and explore efficient ways to leverage this information for environmental stewardship.
DOI: 10.5281/zenodo.11064252
title: Results and code associated with «Predictability of ecological and evolutionary dynamics in a changing world»

description: Below you'll find results and code associated with the following article (*):

Bozzuto, C, Ives, AR (2024): Predictability of ecological and evolutionary dynamics in a changing world. Proceedings of the Royal Society B, 291: 20240980. https://doi.org/10.1098/rspb.2024.0980

ABSTRACT: Ecological and evolutionary predictions are being increasingly employed to inform decision-makers confronted with intensifying pressures on biodiversity. For these efforts to effectively guide conservation actions, knowing the limit of predictability is pivotal. In this study, we provide realistic expectations for the enterprise of predicting changes in ecological and evolutionary observations through time. We begin with an intuitive explanation of predictability (the extent to which predictions are possible) employing an easy-to-use metric, predictive power PP(t). To illustrate the challenge of forecasting, we then show that among insects, birds, fishes and mammals, (i) 50% of the populations are predictable at most 1 year in advance and (ii) the median 1-year-ahead predictive power corresponds to a prediction R2 of only 20%. Predictability is not an immutable property of ecological systems. For example, different harvesting strategies can impact the predictability of exploited populations to varying degrees. Moreover, incorporating explanatory variables, accounting for time trends and considering multivariate time series can enhance predictability. To effectively address the challenge of biodiversity loss, researchers and practitioners must be aware of the information within the available data that can be used for prediction and explore efficient ways to leverage this knowledge for environmental stewardship.

(*) previously a preprint on bioRxiv: https://doi.org/10.1101/2023.11.01.565089
DOI: 10.5281/zenodo.10075252
title: Results and code associated with «Predictability of ecological and evolutionary dynamics in a changing world»

description: Below you'll find results and code associated with the following article (*):

Bozzuto, C, Ives, AR (2024): Predictability of ecological and evolutionary dynamics in a changing world. Proceedings of the Royal Society B, 291: 20240980. https://doi.org/10.1098/rspb.2024.0980

ABSTRACT: Ecological and evolutionary predictions are being increasingly employed to inform decision-makers confronted with intensifying pressures on biodiversity. For these efforts to effectively guide conservation actions, knowing the limit of predictability is pivotal. In this study, we provide realistic expectations for the enterprise of predicting changes in ecological and evolutionary observations through time. We begin with an intuitive explanation of predictability (the extent to which predictions are possible) employing an easy-to-use metric, predictive power PP(t). To illustrate the challenge of forecasting, we then show that among insects, birds, fishes and mammals, (i) 50% of the populations are predictable at most 1 year in advance and (ii) the median 1-year-ahead predictive power corresponds to a prediction R2 of only 20%. Predictability is not an immutable property of ecological systems. For example, different harvesting strategies can impact the predictability of exploited populations to varying degrees. Moreover, incorporating explanatory variables, accounting for time trends and considering multivariate time series can enhance predictability. To effectively address the challenge of biodiversity loss, researchers and practitioners must be aware of the information within the available data that can be used for prediction and explore efficient ways to leverage this knowledge for environmental stewardship.

(*) previously a preprint on bioRxiv: https://doi.org/10.1101/2023.11.01.565089
DOI: 10.5281/zenodo.10079264
title: Results and code associated with «Predictability of ecological and evolutionary dynamics in a changing world»

description: Below you'll find code and results associated with the following preprint:
Bozzuto, C, Ives, AR (2023): Predictability of ecological and evolutionary dynamics in a changing world. bioRxiv. https://doi.org/10.1101/2023.11.01.565089
ABSTRACT: Ecological and evolutionary predictions are being increasingly employed to inform decision-makers confronted with intensifying pressures menacing life on Earth. For these efforts to effectively guide conservation actions, knowing the limit of predictability is pivotal. In this study, we provide realistic expectations about the enterprise of predicting changes in ecological and evolutionary observations through time. We begin with an intuitive explanation of predictability (that is, the extent to which predictions are possible) employing an easy-to-use metric, predictive power PP(t). To illustrate the challenge of forecasting, we then show that among insects, birds, fishes, and mammals (i) 50% of the populations are predictable at most one year in advance, and (ii) the median one-year-ahead predictive power corresponds to a sobering prediction R^2 of approximately 20%. Nonetheless, predictability is not an immutable property of ecological systems. For example, different harvesting strategies can impact the predictability of exploited populations to varying degrees. Moreover, considering multivariate time series, incorporating explanatory variables or accounting for time trends (environmental forcing) can enhance predictability. To effectively address the urgent challenge of biodiversity loss, researchers and practitioners must be aware of the predictive information within the available data and explore efficient ways to leverage this information for environmental stewardship.