cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.10211818
title: An 800-kyr planktonic 𝜹18O stack for the West Pacific Warm Pool

description: Our 10 core planktonic 𝜹18O WPWP stack is available as the "WPWP_planktonic_stack.txt" file, which contains the age, mean 𝜹18O, and 1 sigma 𝜹18O alignment uncertainty. The same file is also available under the name "stack.txt" in the Output folder.
The previously published depth and planktonic 𝜹18O as well as any radiocarbon or additional age constraints for each core used during stack construction can be found in the Inputs folder. This study's BIGMACS produced age models, depth, and planktonic 𝜹18O data for each core can be found in the Outputs folder under the "results.mat" file or as .txt files in the individual folders named for each core.
Additional BIGMACS input and output files for planktonic 𝜹18O from Timor Sea (near the WPWP) core MD01-2378 (Holborn et al., 2005) are provided to demonstrate the alignment and age model differences between using the our new regional planktonic 𝜹18O WPWP stack and the global benthic 𝜹18O LR04 stack as alignment targets.  Differences between the two stacks during MIS 3 and 4 produce a ~17 kyr error in the alignment of the core to the LR04 stack at ~77 kyr ago (depth 8.81 m in core MD01-2378). Because the planktonic 𝛿18O records near the WPWP share features which differ from those of benthic 𝛿18O, age model results are expected be more accurate when these planktonic 𝛿18O records are aligned to the WPWP stack than to a benthic stack.
Holbourn, A. E., Kuhnt, W., Kawamura, H., Jian, Z. Grootes, P. M., Erlenkeuser, H., and Xu, J.: Stable isotopes on planktic foraminifera of sediment core MD01-2378, PANGAEA [data set], https://doi.org/10.1594/PANGAEA.263757, 2005.
DOI: 10.5281/zenodo.8190828
title: An 800-kyr planktonic 𝜹18O stack for the Western Pacific Warm Pool

description: Our 10 core planktonic 𝜹18O WPWP stack is available as the "WPWP_planktonic_stack.txt" file, which contains the age, mean 𝜹18O, and 1 sigma 𝜹18O alignment uncertainty. The same file is also available under the name "stack.txt" in the Output folder. The stack was produced using alignment software BIGMACS (Lee and Rand et al., 2022).
The previously published depth and planktonic 𝜹18O as well as any radiocarbon or additional age constraints for each core used during stack construction can be found in the Inputs folder. This study's BIGMACS produced age models, depth, and planktonic 𝜹18O data for each core can be found in the Outputs folder under the "results.mat" file or as .txt files in the individual folders named for each core.
Additional BIGMACS input and output files for planktonic 𝜹18O from Timor Sea (near the WPWP) core MD01-2378 (Holborn et al., 2005) are provided to demonstrate the alignment and age model differences between using the our new regional planktonic 𝜹18O WPWP stack and the global benthic 𝜹18O LR04 stack as alignment targets.  Differences between the two stacks during MIS 3 and 4 produce a ~17 kyr error in the alignment of the core to the LR04 stack at ~77 kyr ago (depth 8.81 m in core MD01-2378). Because the planktonic 𝛿18O records near the WPWP share features which differ from those of benthic 𝛿18O, age model results are expected be more accurate when these planktonic 𝛿18O records are aligned to the WPWP stack than to a benthic stack.
Holbourn, A. E., Kuhnt, W., Kawamura, H., Jian, Z. Grootes, P. M., Erlenkeuser, H., and Xu, J.: Stable isotopes on planktic foraminifera of sediment core MD01-2378, PANGAEA [data set], https://doi.org/10.1594/PANGAEA.263757, 2005.
Lee, T., Rand, D., Lisiecki, L. E., Gebbie, G., and Lawrence, C. E.: Bayesian age models and stacks: Combining age inferences from radiocarbon and benthic 𝜹18O stratigraphic alignment, EGUsphere, 1–29, https://doi.org/10.5194/egusphere-2022-734, 2022.
Lisiecki, L. E., and Raymo, M. E.: A Pliocene-Pleistocene stack of 57 globally distributed benthic 𝜹18O records, Paleoceanogr., 20, PA1003, https://doi.org/10.1029/2004PA001071, 2005.
DOI: 10.5281/zenodo.8190829
title: An 800-kyr planktonic 𝜹18O stack for the West Pacific Warm Pool

description: <strong>Our planktonic 𝜹18O WPWP stack is available as the “WPWP_planktonic_stack.txt” file, which contains the age, mean 𝜹18O, and 1 sigma 𝜹18O alignment uncertainty. The same file is also available under the name “stack.txt” in the Output folder. </strong> <strong>The previously published depth and planktonic 𝜹18O as well as any radiocarbon or additional age constraints for each core used during stack construction can be found in the Inputs folder. This study's BIGMACS produced age models, depth, and planktonic 𝜹18O data for each core can be found in the Outputs folder under the “results.mat” file or as .txt files in the individual folders named for each core. </strong>
DOI: 10.3886/e195421
title: data 2023, Shandong Province

description: This data targeted undergraduate and associate degree students attending ordinary universities and colleges in Jinan, Shandong Province. Survey questionnaires were distributed during September-October 2023 through a combination of campus interviews, after-class questionnaires, and electronic questionnaires to ensure the accuracy and credibility of the data collected. A total of 300 questionnaires were distributed, with 285 returned. After eliminating questionnaires with excessively long or short responses, as well as contradictory answers, a total of 268 valid questionnaires were obtained, resulting in an effective response rate of 89.3%. SPSS26.0 and AMOS22.0 were used for statistical analysis based on these valid questionnaires.<br>
description: web-based survey;
DOI: 10.5281/zenodo.10212042
title: Santander Customer Transaction Prediction

description:  Santander's transaction prediction dataset has a total of 200 features. The data is divided into three categories: 'var0-var200' are numerical features, 'IDcode' is a character type ID column, and the 'target' feature is a binary target label represented by 1 and 0. The specific attribute descriptions are shown in the table.
DOI: 10.5281/zenodo.7980289
title: Santander Customer Transaction Prediction

description:  Santander's transaction prediction dataset has a total of 200 features. The data is divided into three categories: 'var0-var200' are numerical features, 'IDcode' is a character type ID column, and the 'target' feature is a binary target label represented by 1 and 0. The specific attribute descriptions are shown in the table.
DOI: 10.5281/zenodo.7980290
title: Santander Customer Transaction Prediction

description: Santander's transaction prediction dataset has a total of 200 features. The data is divided into three categories: 'var0-var200' are numerical features, 'IDcode' is a character type ID column, and the 'target' feature is a binary target label represented by 1 and 0. The specific attribute descriptions are shown in the table.
DOI: 10.25952/5w9g-h542
title: Knowledge and Attitudes of Mental Health Professionals and Students Regarding Recovery in Australia

description: The data measures/assesses mental health professionals' and students' perspectives regarding mental health recovery. The data were collected between February 2021 and June 2022 from Australian mental health professionals and students. It consists of both qualitative and quantitative components. Specifically, the data were used to develop and test a tool to assess knowledge and attitudes toward recovery.
description: The data measures/assesses mental health professionals' and students' perspectives regarding mental health recovery. The data were collected between February 2021 and June 2022 from Australian mental health professionals and students. It consists of both qualitative and quantitative components. Specifically, the data were used to develop and test a tool to assess knowledge and attitudes toward recovery.
DOI: 10.5517/ccdc.csd.cc2dr22b
title: CCDC 2226701: Experimental Crystal Structure Determination

description: Related Article: Beibei Zhao, Jianqiang Feng, Lu Yu, Zhongqiu Xing, Bin Chen, Aokun Liu, Fulu Liu, Fengming Shi, Yue Zhao, Changlin Tian, Binju Wang, Xiaoqiang Huang |2023|Nat. Catal.|6|996|doi:10.1038/s41929-023-01024-0
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: 10.6084/m9.figshare.24647096
title: Additional file 1 of Physiological responses and algae inhibition of Pontederia cordata to simulated eutrophication and acid rain co-pollution

description: Additional file 1. The raw data of the RGR, root activity, Chl T content, SOD activity, CAT activity, REC, and MDA content of P. cordata under the simulated acid rain spraying times, simulated acid rain and simulated eutrophication.
DOI: 10.6084/m9.figshare.24647096.v1
title: Additional file 1 of Physiological responses and algae inhibition of Pontederia cordata to simulated eutrophication and acid rain co-pollution

description: Additional file 1. The raw data of the RGR, root activity, Chl T content, SOD activity, CAT activity, REC, and MDA content of P. cordata under the simulated acid rain spraying times, simulated acid rain and simulated eutrophication.
DOI: 10.5281/zenodo.10212049
title: TREECHANGE: Global tree species' range maps generated via alpha-hull methods

description: Global tree species' range maps generated via alpha-hull methods, as described in Guo, W.-Y., Serra-Diaz, J. M., Schrodt, … Svenning, J.-C. (2022). High exposure of global tree diversity to human pressure. PNAS, doi:10.1073/pnas.2026733119
DOI: 10.5281/zenodo.10212050
title: TREECHANGE: Global tree species' range maps generated via alpha-hull methods

description: Global tree species' range maps generated via alpha-hull methods, as described in Guo, W.-Y., Serra-Diaz, J. M., Schrodt, … Svenning, J.-C. (2022). High exposure of global tree diversity to human pressure. PNAS, doi:10.1073/pnas.2026733119
DOI: 10.6084/m9.figshare.24647394
title: ENVI-D-23-07857-Data.rar

description: This data is for a review paper entitled: "<b>How did VRP grow? Towards Sustainable Models by Developing a Novel Classification</b>".
DOI: 10.25952/kra8-3j40
title: Dataset for PhD "The intimate and the epic in 'Plunge'

description: This dataset is comprised of:<br>
•	Recordings of interviews with elite pool athletes, coaches, parents that were used to create the performance, 'Plunge' (2017) by Kate Shearer<br>
•	Recordings of interviews with the creative team<br>
•	Photographs of the production 'Plunge' (2017)<br>
Data collected 2016-2017
description: This dataset is comprised of:<br>
•	Recordings of interviews with elite pool athletes, coaches, parents that were used to create the performance, 'Plunge' (2017) by Kate Shearer<br>
•	Recordings of interviews with the creative team<br>
•	Photographs of the production 'Plunge' (2017)<br>
Data collected 2016-2017
description: Some interviews with participants contains personal information on mental health.
DOI: 10.6084/m9.figshare.24647424
title: Supplementary Material for: Mitochondrial Common Deletion Level in Adipose Tissue is Not Associated with Obesity but is Associated with a Structural Change in Triglycerides as Revealed by FTIR Spectroscopy

description: Objective: Several studies have shown that the mitochondrial metabolism may be disrupted if the rate of the specific 4977 bp deletion of mitochondrial DNA (mtDNA) reaches a threshold. This study aims to investigate the possible associations between the mtDNA4977 deletion load and obesity-related metabolic abnormalities in the adipose tissue. Methods: The study included thirty obese individuals, who underwent bariatric surgery, and twelve control subjects. mtDNA4977 deletion, adenine nucleotides and lactate levels, which show the bioenergetic status were evaluated in visceral adipose tissues. Fourier transform infrared (FTIR) spectroscopy was used to investigate the structural variations and composition of adipose tissue in the context of deletion load. Results: There were no differences between the two groups in terms of mtDNA4977 deletion, adenine nucleotides, and lactate levels. The FTIR spectra indicated a few obesity-related alterations in adipose tissue that were not related to the mtDNA deletion load. Also, statistical analysis showed a correlation between deletion load and a band shift of 1744 cm-1, which assigns C = O stretching of the carbonyl group of the ester group in triglycerides and other esterified fatty acids, although it is not associated with obesity. Conclusions: Our data suggest that the mtDNA4977 deletion in visceral adipose tissue of obese individuals do not have a significant impact on bioenergetic status. However, the increased accumulation of deletion may be associated with a specific change in the ester bond, indicating structural differences in the lipids. These findings shed light on our understanding of the tissue-specific distribution of mtDNA deletions and obesity-related adipose tissue pathogenesis.
DOI: 10.6084/m9.figshare.24647424.v1
title: Supplementary Material for: Mitochondrial Common Deletion Level in Adipose Tissue is Not Associated with Obesity but is Associated with a Structural Change in Triglycerides as Revealed by FTIR Spectroscopy

description: Objective: Several studies have shown that the mitochondrial metabolism may be disrupted if the rate of the specific 4977 bp deletion of mitochondrial DNA (mtDNA) reaches a threshold. This study aims to investigate the possible associations between the mtDNA4977 deletion load and obesity-related metabolic abnormalities in the adipose tissue. Methods: The study included thirty obese individuals, who underwent bariatric surgery, and twelve control subjects. mtDNA4977 deletion, adenine nucleotides and lactate levels, which show the bioenergetic status were evaluated in visceral adipose tissues. Fourier transform infrared (FTIR) spectroscopy was used to investigate the structural variations and composition of adipose tissue in the context of deletion load. Results: There were no differences between the two groups in terms of mtDNA4977 deletion, adenine nucleotides, and lactate levels. The FTIR spectra indicated a few obesity-related alterations in adipose tissue that were not related to the mtDNA deletion load. Also, statistical analysis showed a correlation between deletion load and a band shift of 1744 cm-1, which assigns C = O stretching of the carbonyl group of the ester group in triglycerides and other esterified fatty acids, although it is not associated with obesity. Conclusions: Our data suggest that the mtDNA4977 deletion in visceral adipose tissue of obese individuals do not have a significant impact on bioenergetic status. However, the increased accumulation of deletion may be associated with a specific change in the ester bond, indicating structural differences in the lipids. These findings shed light on our understanding of the tissue-specific distribution of mtDNA deletions and obesity-related adipose tissue pathogenesis.
DOI: 10.6084/m9.figshare.24647427
title: Supplementary Material for: The Optical Coherence Tomography and Microperimetry Biomarker Evaluation in Patients with Geographic Atrophy (OMEGA) Study: Design and Baseline Characteristics (OMEGA report 1)

description: Introduction: The aim of this study is to describe the design and the participants’ baseline characteristics of a prospective natural-history study of geographic atrophy (GA) secondary to age-related macular degeneration. Methods: The optical coherence tomography (OCT) and microperimetry biomarker evaluation in patients with GA (OMEGA) study was conducted at a tertiary referral center (ClinicalTrials.gov identifier: NCT05963646). Participants were followed for 12 months during 4 visits (baseline and follow-up exams at weeks 12, 24, and 48) with best-corrected ETDRS visual acuity, low-luminance visual acuity, and quick contrast sensitivity function (qCSF) testing. Further, participants underwent spectral-domain OCT, OCT angiography, fundus autofluorescence (FAF) imaging, and mesopic microperimetry testing. Results: Thirty participants (median [IQR] age of 79 [77, 84] years) and 37 study eyes were included with a (median [IQR]) GA area of 1.40 mm2 [0.49, 5.24] at baseline. Out of 37 study eyes, six developed macular neovascularizations (16%). The study-eye BCVA was (median [IQR]) 0.18 logMAR [0.06, 0.26], LLVA 0.66 logMAR [0.36, 0.88], and the microperimetry mean sensitivity 18.4 dB [9.21, 20.9]. The highest correlation between square root GA area and a visual function test was evident for LLVA (R2 of 0.578), followed by AULCSF (0.519) and microperimetral retinal sensitivity (0.487). Conclusion: This report lays out the design and baseline characteristics of the OMEGA study, which aims to contribute to the understanding of the natural history of GA. The OMEGA study will provide estimates of the ability-to-detect change and retest reliability for a panel of structure and function assessments.
DOI: 10.6084/m9.figshare.24647427.v1
title: Supplementary Material for: The Optical Coherence Tomography and Microperimetry Biomarker Evaluation in Patients with Geographic Atrophy (OMEGA) Study: Design and Baseline Characteristics (OMEGA report 1)

description: Introduction: The aim of this study is to describe the design and the participants’ baseline characteristics of a prospective natural-history study of geographic atrophy (GA) secondary to age-related macular degeneration. Methods: The optical coherence tomography (OCT) and microperimetry biomarker evaluation in patients with GA (OMEGA) study was conducted at a tertiary referral center (ClinicalTrials.gov identifier: NCT05963646). Participants were followed for 12 months during 4 visits (baseline and follow-up exams at weeks 12, 24, and 48) with best-corrected ETDRS visual acuity, low-luminance visual acuity, and quick contrast sensitivity function (qCSF) testing. Further, participants underwent spectral-domain OCT, OCT angiography, fundus autofluorescence (FAF) imaging, and mesopic microperimetry testing. Results: Thirty participants (median [IQR] age of 79 [77, 84] years) and 37 study eyes were included with a (median [IQR]) GA area of 1.40 mm2 [0.49, 5.24] at baseline. Out of 37 study eyes, six developed macular neovascularizations (16%). The study-eye BCVA was (median [IQR]) 0.18 logMAR [0.06, 0.26], LLVA 0.66 logMAR [0.36, 0.88], and the microperimetry mean sensitivity 18.4 dB [9.21, 20.9]. The highest correlation between square root GA area and a visual function test was evident for LLVA (R2 of 0.578), followed by AULCSF (0.519) and microperimetral retinal sensitivity (0.487). Conclusion: This report lays out the design and baseline characteristics of the OMEGA study, which aims to contribute to the understanding of the natural history of GA. The OMEGA study will provide estimates of the ability-to-detect change and retest reliability for a panel of structure and function assessments.
DOI: 10.5281/zenodo.10052092
title: DSK manuscript data
DOI: 10.5281/zenodo.10052093
title: DSK manuscript data
DOI: 10.34740/kaggle/dsv/7071061
title: time-series-decomposition data
DOI: 10.25946/24557332
title: Phytochemistry and Bioassay Data

description: Australia is home to a diverse range of unique flora with exceptional survival mechanisms and phytochemicals, which makes them an attractive source for discovering new drugs. This study proposes a bioassay-guided fractionation protocol to effectively screen plants with potential bioactive properties and isolate novel key compounds.
DOI: 10.25946/24557332.v1
title: Phytochemistry and Bioassay Data

description: Australia is home to a diverse range of unique flora with exceptional survival mechanisms and phytochemicals, which makes them an attractive source for discovering new drugs. This study proposes a bioassay-guided fractionation protocol to effectively screen plants with potential bioactive properties and isolate novel key compounds.
DOI: 10.5281/zenodo.10212148
title: Data used in '3D Printable Self-Sensing Magnetorheological Elastomer'

description: This dataset contains the data used in the publication '3D Printable Self-Sensing Magnetorheological Elastomer'
DOI: 10.5281/zenodo.10212167
title: Data used in '3D Printable Self-Sensing Magnetorheological Elastomer'

description: This dataset contains the data used in the publication '3D Printable Self-Sensing Magnetorheological Elastomer'
DOI: 10.34740/kaggle/dsv/7071170
title: 📒 Meta Kaggle ported to MS SQL SERVER 2022 DB
DOI: 10.6084/m9.figshare.24588585.v3
title: WM-connectome-development

description: This repository provides source data of figures in our study "Longitudinal development of brain white matter structural connectome and its association with transcriptomic and cellular architecture".If you use these data, please cite our paper:Guozheng Feng, Rui Chen, Rui Zhao, et al. Longitudinal development of the human white matter structural connectome and its association with brain transcriptomic and cellular architecture. Communications Biology.
DOI: 10.5281/zenodo.10212106
title: Dataset of conversation graphs from  2019 Anti CAA protest in India

description: To facilitate future research in online social movements,  we are publishing this dataset of conversation graphs in the from the 2019 anti-CAA protest tweets.  The conversation graph dataset has two types of conversations:
• Mention Graphs: In this, vertices are users and (directed) edges represent any interaction between the users. Within the context of our dataset, these interactions are limited to mentions alone when a user refers to another user directly by username.
• Reply Graphs: In this case, vertices are users, and a (directed) edge exists if one user replies to another.
The reply graph is built as follows:

Since replies often form chains, find the root 'destination' user nodes that have been replied to at least once.
 Find all the immediate next-level users who directly replied to the root nodes (these are 'source' nodes)
Iteratively map the immediate next level of users who reply to the previous level of corresponding users, stopping when all of the users in the next level have not been replied to (leaf users, so to say).
The mention graph is built as follows:

Since replies often form chains, find the root 'destination' user nodes that have been replied to at least once.
Find all the immediate next-level users who directly replied to the root nodes (these are 'source' nodes)
Iteratively map the immediate next level of users who reply to the previous level of corresponding users, stopping when all of the users in the next level have not been replied to (leaf users, so to say).
Additionally, the dataset has the users and conversation graphs labeled for emotion and toxicity.  Motif count has been provided for each of the graph. 
To maintain confidentiality as per Twitter guidelines, user ids are anonymized  and Tweet IDs and Tweet texts are not part of the dataset.