cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15151/esrf-es-1119937092
title: BAG Barcelona

description: BAG Barcelona has a long tradition of accessing the ESRF. It is constituted by 10 groups that belong to the Institute of Molecular Biology Barcelona from the Spanish Research Council (IBMB-CSIC), the Institute for Research in Biomedicine (IRB), and the Research Institute from Hospital Santa Creu i Sant Pau (HSCSP-IR). The main subjects of research are protein/DBA complexes, molecular machines, compounds of viruses, molecular mechanisms of proteases, and other enzymes. Recently, a new group (E. Marcos) interested in de-novo designed protein scaffolds has joined the BAG. Our Scientific results strongly rely on the high-quality data and excellent performance and support of ESRF macromolecular crystallography beamlines.
DOI: 10.15151/esrf-es-1215822038
title: BAG Barcelona

description: BAG Barcelona has a long tradition of accessing the ESRF. It is constituted by 10 groups that belong to the Institute of Molecular Biology Barcelona from the Spanish Research Council (IBMB-CSIC), the Institute for Research in Biomedicine (IRB), and the Research Institute from Hospital Santa Creu i Sant Pau (HSCSP-IR). The main subjects of research are protein/DBA complexes, molecular machines, compounds of viruses, molecular mechanisms of proteases, and other enzymes. Recently, a new group (E. Marcos) interested in de-novo designed protein scaffolds has joined the BAG. Our Scientific results strongly rely on the high-quality data and excellent performance and support of ESRF macromolecular crystallography beamlines.
DOI: 10.15151/esrf-es-1218735696
title: Cryo-EM structural studies of an assembly factor important for mitochondrial respiration

description: Investigating the structure of the MCIA complex to uncover the interaction between the core proteins and understand its function in relation to the OXPHOS system.
DOI: 10.5281/zenodo.8058527
title: almost 3000 Networks (unweighted, undirected, simple, connected) from Network Repository

description: <strong>Data</strong> All networks from <code>networkrepository.com</code> [1] with at most 1M edges (fall 2020) with the following modifications: weights and edge directions have been ignored multi-edges and self loops have been removed, i.e., the graphs are simple each graph has been reduced to its largest connected component for isomorphic graphs, only one copy has been kept [1] Ryan A. Rossi and Nesreen K. Ahmed, <em>The Network Data Repository with Interactive Graph Analytics and Visualization</em> (AAAI 2015) <strong>Format</strong> The data format is a simple edge list: each row contains two numbers <em>u</em> and <em>v </em>separated by a space representing an edge <em>{u, v}</em> for a graph with <em>n</em> vertices, the numbers range from <em>0 </em>to <em>n - 1</em> for each edge <em>{u, v} </em>only one of the pairs <em>u v</em> or <em>v u</em> is present, i.e., if the graph has <em>m</em> edges, the file contains <em>m</em> rows
DOI: 10.5281/zenodo.6586184
title: almost 3000 Networks (unweighted, undirected, simple, connected) from Network Repository

description: <strong>Data</strong> All networks from <code>networkrepository.com</code> [1] with at most 1M edges (fall 2020) with the following modifications: weights and edge directions have been ignored multi-edges and self loops have been removed, i.e., the graphs are simple each graph has been reduced to its largest connected component for isomorphic graphs, only one copy has been kept [1] Ryan A. Rossi and Nesreen K. Ahmed, <em>The Network Data Repository with Interactive Graph Analytics and Visualization</em> (AAAI 2015) <strong>Format</strong> The data format is a simple edge list: each row contains two numbers <em>u</em> and <em>v </em>separated by a space representing an edge <em>{u, v}</em> for a graph with <em>n</em> vertices, the numbers range from <em>0 </em>to <em>n - 1</em> for each edge <em>{u, v} </em>only one of the pairs <em>u v</em> or <em>v u</em> is present, i.e., if the graph has <em>m</em> edges, the file contains <em>m</em> rows
DOI: 10.5281/zenodo.8046834
title: Input Data for: On the External Validity of Average-Case Analyses of Graph Algorithms

description: <strong>Data</strong> All networks from <code>networkrepository.com</code> [1] with at most 1M edges (fall 2020). Weights and edge directions have been removed. For graphs with isomorphic largest connected component, only one copy has been kept. This is the raw data necessary to reproduce our experiments in <em>On the External Validity of Average-Case Analyses of Graph Algorithms</em>. [1] Ryan A. Rossi and Nesreen K. Ahmed, <em>The Network Data Repository with Interactive Graph Analytics and Visualization</em> (AAAI 2015)
DOI: 10.5281/zenodo.6586236
title: Input Data for: On the External Validity of Average-Case Analyses of Graph Algorithms

description: <strong>Data</strong> All networks from <code>networkrepository.com</code> [1] with at most 1M edges (fall 2020). Weights and edge directions have been removed. For graphs with isomorphic largest connected component, only one copy has been kept. This is the raw data necessary to reproduce our experiments in <em>On the External Validity of Average-Case Analyses of Graph Algorithms</em>. [1] Ryan A. Rossi and Nesreen K. Ahmed, <em>The Network Data Repository with Interactive Graph Analytics and Visualization</em> (AAAI 2015)
DOI: 10.5281/zenodo.8062815
title: Session

description: Datasets for session-based recommendation
DOI: 10.5281/zenodo.8062814
title: Session

description: Datasets for session-based recommendation
DOI: 10.5281/zenodo.7958170
title: Multispectral Images of the Kiev Folia

description: Multispectral Images of the Kiev Folia (F. 301, Nr. 328 P), acquired at the Kiev National Library in 2018. Detailled descriptions of image acquisition, processing and usage are found in<em> Images_Kiev-Folia_zenodo_1.0.pdf </em>
DOI: 10.5281/zenodo.7958171
title: Multispectral Images of the Kiev Folia

description: Multispectral Images of the Kiev Folia (F. 301, Nr. 328 P), acquired at the Kiev National Library in 2018. Detailled descriptions of image acquisition, processing and usage are found in<em> Images_Kiev-Folia_zenodo_1.0.pdf </em>
DOI: 10.6084/m9.figshare.22213747.v1
title: Using conversational AI to automatically extract data from research papers - example of ChatGPT

description: Data supporting the paper entitled "Using conversational AI to automatically extract data from research papers - example of ChatGPT" by Maciej P. Polak and Dane Morgan <br> https://arxiv.org/abs/2303.05352
DOI: 10.6084/m9.figshare.23551656
title: 陶片微量元素测试结果

description: 陶片微量元素测试结果
DOI: 10.6084/m9.figshare.23551656.v1
title: 陶片微量元素测试结果

description: 陶片微量元素测试结果
DOI: 10.6084/m9.figshare.22213747.v2
title: Using conversational AI to automatically extract data from research papers - example of ChatGPT

description: Data supporting the paper entitled "Using conversational AI to automatically extract data from research papers - example of ChatGPT" by Maciej P. Polak and Dane Morgan <br> https://arxiv.org/abs/2303.05352 <br> The files contain the ChatExtract code with a short example (ChatExtract_MPPolak_DMorgan.zip) and two databases (CriticalCoolingRates_MGs_database_MPPolak_DMorgan.xlsx and YieldStrength_HEAs_database_MPPolak_DMorgan.xlsx.xlsx) in all versions described in the paper, i.e. "raw", "cleaned", and "standardized". The critical cooling rate additionally includes manually extracted data serving as ground truth for tests, in sheets labeled as "manual".
DOI: 10.5281/zenodo.7985048
title: Temperature Decrease in Liverpool

description: Green urban infrastructure can play a role in climate change adaptation through reducing air and surface temperature by providing shading and enhancing evapotranspiration, which leads to two benefits: improved thermal comfort and reduced energy use. We address the thermal comfort and reduced energy benefits via physical indicators such as ambient temperature, turbulent fluxes, and energy savings. In this KPI, mean and peak daytime local temperatures will be calculated and used to assess the impact of the NBS. This KPI includes the measurement and calculation of mean and daytime local relative humidity to complete the study.
DOI: 10.5281/zenodo.7985047
title: Temperature Decrease in Liverpool

description: Green urban infrastructure can play a role in climate change adaptation through reducing air and surface temperature by providing shading and enhancing evapotranspiration, which leads to two benefits: improved thermal comfort and reduced energy use. We address the thermal comfort and reduced energy benefits via physical indicators such as ambient temperature, turbulent fluxes, and energy savings. In this KPI, mean and peak daytime local temperatures will be calculated and used to assess the impact of the NBS. This KPI includes the measurement and calculation of mean and daytime local relative humidity to complete the study.
DOI: 10.14469/hpc/12699
title: Diberyllocene, D5d

description: Gaussian 16 (C01) calculation
DOI: 10.14469/hpc/12700
title: Diberyllocene, D5 only

description: Gaussian 16 (C01) calculation
DOI: 10.14469/hpc/12701
title: Diberyllocene, D5 only MOs

description: Gaussian 16 (C01) calculation
DOI: 10.14469/hpc/12704
title: Diberyllocene — and Lithioborocene?
DOI: 10.14469/hpc/12698
title: Diberyllocene, D5h

description: Gaussian 16 (C01) calculation
DOI: 10.14469/hpc/12703
title: Lithioborocene: The LiB analogue of diberyllocene

description: Gaussian 16 (C01) calculation
DOI: 10.6084/m9.figshare.21600915
title: Uncovering a population of gravitational lens galaxies with magnified “standard candle” SN Zwicky

description: Ground based light curve data
DOI: 10.6084/m9.figshare.21600915.v1
title: Uncovering a population of gravitational lens galaxies with magnified “standard candle” SN Zwicky

description: Ground based light curve data
DOI: 10.6084/m9.figshare.22688044.v1
title: Pangolin-inspired untethered magnetic robot for on-demand biomedical heating applications

description: Dataset for the paper
DOI: 10.6084/m9.figshare.22688044
title: Pangolin-inspired untethered magnetic robot for on-demand biomedical heating applications

description: Dataset for the paper
DOI: 10.6084/m9.figshare.22650691.v1
title: UBAP2 plays a role in bone homeostasis through the regulation of osteoblastogenesis and osteoclastogenesis

description: The data of statistical association studies in two Korean women cohorts and experimental studies in cells, zebrafish, and humans for the role of UBAP2.
DOI: 10.6084/m9.figshare.22650691
title: UBAP2 plays a role in bone homeostasis through the regulation of osteoblastogenesis and osteoclastogenesis

description: The data of statistical association studies in two Korean women cohorts and experimental studies in cells, zebrafish, and humans for the role of UBAP2.
DOI: 10.6084/m9.figshare.22657069.v1
title: Seasonal specialization drives divergent population dynamics in two closely related butterflies

description: This file contains all data and scripts needed to reproduce the results in von Schmalensee et al. 2023 Nature Communications.
DOI: 10.6084/m9.figshare.22657069
title: Seasonal specialization drives divergent population dynamics in two closely related butterflies

description: This file contains all data and scripts needed to reproduce the results in von Schmalensee et al. 2023 Nature Communications.
DOI: 10.5517/ccdc.csd.cc2d0l67
title: CCDC 2205098: Experimental Crystal Structure Determination

description: Related Article: Zainab Rehman, W.Trent Franks, Bao Nguyen, Heather Frericks Schmidt, Garry Scrivens, Steven P. Brown|2023|J.Pharm.Sci.|112|1915|doi:10.1016/j.xphs.2023.02.022
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.cc2dpcxd
title: CCDC 2225084: Experimental Crystal Structure Determination

description: Related Article: Shuruthi Senthil, Michael R. Gau, Daniel J. Mindiola|2023|Organometallics|42|1048|doi:10.1021/acs.organomet.2c00638
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: 10.4121/68ef97d7-8aeb-4fdc-92e3-a0947a53400c.v1
title: Data underlying the CSE Research Project: Using the CHSH game quantum network application as a benchmarking tool

description: This dataset was generated as part of the CSE Research Project course. The topic of this research was assessing whether the CHSH game quantum network application should be included in the first ever quantum network benchmark suite. Hence, the main research question was whether the CHSH game application is sensitive in determine errors in the total quantum network system. To answer this question multiple experiment were performed using the SquidASM software development kit to simulate different quantum networks. This dataset contains all the raw data obtain from these experiments meaning the input and output values of each CHSH game. Each experiments assumes a perfect quantum network apart from a single property that is used as the independent variable. Then, using three performance metrics defined in the attached paper three plots are created in the workbook file. For more details, the full paper of the study can be found in the data link section.
DOI: 10.6084/m9.figshare.23551743
title: PONE-D-22-11862 Dataset

description: Dataset from study PONE-D-22-11862 that explored the impact of the COVID-19 pandemic on research activities of a large academic institution (Sapienza University of Rome) in the attempt to identify the most critical issues in a vast multidisciplinary academic community.
DOI: 10.5281/zenodo.7728140
title: Data for publication "Measuring the environment of a Cs qubit with dynamical decoupling sequences"

description: Data sets as plotted in the preprint "Measuring the environment of a Cs qubit with dynamical decoupling sequences" are uploaded.<br> The zip file "data" contains a folder for each figure in the preprint (named after the figure). Each folder contains the data for all graphs in the respective figure.
description: This work was supported by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) via the Collaborative Research Centers SFB/TR185 (Project No. 277625399). S.B. acknowledges funding by Studienstiftung des deutschen Volkes.
DOI: 10.5281/zenodo.7728141
title: Data for publication "Measuring the environment of a Cs qubit with dynamical decoupling sequences"

description: Data sets as plotted in the preprint "Measuring the environment of a Cs qubit with dynamical decoupling sequences" are uploaded.<br> The zip file "data" contains a folder for each figure in the preprint (named after the figure). Each folder contains the data for all graphs in the respective figure.
description: This work was supported by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) via the Collaborative Research Centers SFB/TR185 (Project No. 277625399). S.B. acknowledges funding by Studienstiftung des deutschen Volkes.
DOI: 10.5281/zenodo.8062852
title: Data for publication "Measuring the environment of a Cs qubit with dynamical decoupling sequences"

description: Data sets as plotted in the preprint "Measuring the environment of a Cs qubit with dynamical decoupling sequences" are uploaded.<br> The zip file "data" contains a folder for each figure in the preprint (named after the figure). Each folder contains the data for all graphs in the respective figure.
description: This work was supported by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) via the Collaborative Research Centers SFB/TR185 (Project No. 277625399). S.B. acknowledges funding by Studienstiftung des deutschen Volkes.
DOI: 10.6084/m9.figshare.23551806
title: Supplementary Material for: Construction of an early alert system for intradialytic hypotension before initiating hemodialysis based on machine learning

description: Abstract Introduction: Intradialytic hypotension (IDH) is prevalent and associated with high hospitalization and mortality rates. The purpose of this study was to explore the risk factors for IDH and use artificial intelligence to establish an early alert system before hemodialysis sessions to identify patients at high risk of IDH. Materials and methods: We obtained data on 314534 hemodialysis sessions conducted at Sichuan Provincial People's Hospital from the Renal Disease Treatment Information System. IDH was defined as a systolic blood pressure drop≥20 mmHg, a mean arterial pressure drop≥10 mmHg during dialysis, or the occurrence of clinical hypotensive events requiring nursing intervention. After pre-processing, the data were randomly divided into training (80%) and testing (20%) sets. Four interpolation methods, three feature selection methods, and 18 machine learning algorithms were used to construct predictive models. The area under the receiver operating characteristic curve (AUC) was the main indicator for evaluating the performance of the models, while Shapley Additive ExPlanation (SHAP) was used to explain the contribution of each variable to the best predictive model. Results: A total of 3906 patients and 314534 dialysis sessions were included, of which 142237 cases showed IDH (incidence rate, 45.2%). Nineteen parameters were identified through artificial intelligence feature screening. They included age, pre-dialysis weight, dry weight, pre-dialysis blood pressure, heart rate, prescribed ultrafiltration, blood cell counts (neutrophil, lymphocyte, monocyte, eosinophil, lymphocyte, and platelet counts), hematocrit, serum calcium, creatinine, urea, glucose, and uric acid. Random forest, gradient boosting, and logistic regression were the three best models, and the AUCs were 0.812 (95% confidence interval[CI], 0.811-0.813), 0.748 (95% CI, 0.747-0.749), and 0.743 (95% CI, 0.742-0.744), respectively. Conclusion: Our dialysis software-based artificial intelligence alert system can be used to predict IDH occurrence, enabling the initiation of relevant interventions.
DOI: 10.6084/m9.figshare.23551806.v1
title: Supplementary Material for: Construction of an early alert system for intradialytic hypotension before initiating hemodialysis based on machine learning

description: Abstract Introduction: Intradialytic hypotension (IDH) is prevalent and associated with high hospitalization and mortality rates. The purpose of this study was to explore the risk factors for IDH and use artificial intelligence to establish an early alert system before hemodialysis sessions to identify patients at high risk of IDH. Materials and methods: We obtained data on 314534 hemodialysis sessions conducted at Sichuan Provincial People's Hospital from the Renal Disease Treatment Information System. IDH was defined as a systolic blood pressure drop≥20 mmHg, a mean arterial pressure drop≥10 mmHg during dialysis, or the occurrence of clinical hypotensive events requiring nursing intervention. After pre-processing, the data were randomly divided into training (80%) and testing (20%) sets. Four interpolation methods, three feature selection methods, and 18 machine learning algorithms were used to construct predictive models. The area under the receiver operating characteristic curve (AUC) was the main indicator for evaluating the performance of the models, while Shapley Additive ExPlanation (SHAP) was used to explain the contribution of each variable to the best predictive model. Results: A total of 3906 patients and 314534 dialysis sessions were included, of which 142237 cases showed IDH (incidence rate, 45.2%). Nineteen parameters were identified through artificial intelligence feature screening. They included age, pre-dialysis weight, dry weight, pre-dialysis blood pressure, heart rate, prescribed ultrafiltration, blood cell counts (neutrophil, lymphocyte, monocyte, eosinophil, lymphocyte, and platelet counts), hematocrit, serum calcium, creatinine, urea, glucose, and uric acid. Random forest, gradient boosting, and logistic regression were the three best models, and the AUCs were 0.812 (95% confidence interval[CI], 0.811-0.813), 0.748 (95% CI, 0.747-0.749), and 0.743 (95% CI, 0.742-0.744), respectively. Conclusion: Our dialysis software-based artificial intelligence alert system can be used to predict IDH occurrence, enabling the initiation of relevant interventions.
DOI: 10.6084/m9.figshare.23289836
title: Bone Mineral Data

description: This data has been used and/or analyzed during the current study (without any identifying information) in the study entitled:" <strong>The Effect of Intradialytic Exercise on Calcium, Phosphorus and Parathyroid Hormone: A Randomized Controlled Trial"</strong>
DOI: 10.6084/m9.figshare.23289836.v1
title: Bone Mineral Data

description: This data has been used and/or analyzed during the current study (without any identifying information) in the study entitled:" <strong>The Effect of Intradialytic Exercise on Calcium, Phosphorus and Parathyroid Hormone: A Randomized Controlled Trial"</strong>
DOI: 10.6084/m9.figshare.19115482
title: Enzymatic biodegradation, kinetic study, and detoxification of Reactive Red-195 by <i>Halomonas meridiana</i> isolated from Marine Sediments of Andaman Sea, India

description: Azo dyes are a significant class of hazardous chemicals that are extensively utilised in diverse industries. Industries that manufacture and consume reactive azo dyes generate hyper-saline wastewater. The ability of halotolerant bacteria to thrive under extreme environmental conditions thus makes them a potential candidate for reactive azo dye degradation. An efficient halotolerant bacterium (isolate SAIBP-6) with the capability to degrade 87.15% of azo dye Reactive Red 195 (RR-195) was isolated from sea sediment and identified as <i>Halomonas meridiana</i> SAIBP-6. Strain SAIBP-6 maintained potential decolourisation under a wide range of environmental conditions viz. 35–45°C temperature, 50–450 mg/L RR-195, pH 7–9, and 50–150 g/L NaCl. However, maximum decolourisation occurred at 40°C, 200 mg/L RR-195 dye, pH 9, and 50 g/L NaCl, under static conditions. Tyrosinase and azoreductase were responsible for dye degradation. The reaction catalysed by these enzymes followed zero-order kinetics. The maximum velocity (Vmax) of the enzymatic reaction was 4.221 mg/(L.h) and the Michaelis constant (Km) was 517.982 mg/L. Strain SAIBP-6 also efficiently decolourised Reactive Black-5 and Reactive Yellow-160 dye. The biodegradation process was further studied with the help of UV–Vis spectral scan, ultra-high performance liquid chromatography (UPLC), fourier-transform infra-red spectroscopy (FT–IR), and proton nuclear magnetic resonance (<sup>1</sup>H NMR) analysis. Finally, cytogenotoxicity assay conducted with the meristematic root tip cells of <i>Allium cepa</i> and phytotoxicity assay conducted with the seeds of <i>Vigna mungo</i> led to the inference that strain SAIBP-6 significantly reduced the toxicity of RR-195 after biodegradation.
DOI: 10.6084/m9.figshare.23261075
title: Analysis

description: A summary of all flow cytometry results, scatter plots, and applied gates
DOI: 10.6084/m9.figshare.23261075.v1
title: Analysis

description: A summary of all flow cytometry results, scatter plots, and applied gates