cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.21652007.v6
title: Construction of Chinese baijiu compound database using text mining and its application in assisting compound identification of liquid chromatography-high-resolution mass spectrometry data

description: Comprehensive understanding of the molecular composition in Chinese baijiu is of a great value for understanding the flavor and improving the quality. Liquid chromatography-mass spectrometry (LC-MS) is a good tool for the analysis of Chinese baijiu. However, lack of the related database makes corresponding LC-MS data difficult to be annotated. Therefore, a Chinese baijiu compound database (CBDB) containing 5709 compounds was constructed based on literatures and text mining, and further a Chinese baijiu LC-MS database (LCMS-CBDB) was built by endowing each compound with retention time, exact mass, and MS/MS spectrum. In total 468 compounds were identified in six Chinese baijiu samples by searching LCMS-CBDB. Further, database enhancement strategies were proposed based on biological transformations and theoretical homologue expansion, which allows the identification of new compounds. Four monoglycerides were successfully identified and validated using the extended CBDB, three of them were reported in baijiu for the first time.
DOI: 10.6084/m9.figshare.25160759.v1
title: Supplementary Material for: The association between high-dose allopurinol and erythropoietin hyporesponsiveness in advanced chronic kidney disease. JOINT-KD study

description: Introduction: To explore the association between urate-lowering agents and reduced response to erythropoietin-stimulating agents in patients suffering from chronic kidney disease G5.
Methods: We conducted a cross-sectional, multicenter study in Japan between April and June 2013, enrolling patients aged 20 years or older with an estimated glomerular filtration rate of ≤15 mL/min/1.73 m2. Exclusion criteria encompassed patients with a history of hemodialysis, peritoneal dialysis, or organ transplantation. The patients were categorized into four groups based on the use of urate-lowering drugs: high-dose allopurinol (&gt;50 mg/day), low-dose allopurinol (≤50 mg/day), febuxostat, and no-treatment groups. We used a multivariable logistic regression model, adjusted for covariates, to determine the odds ratio (OR) for erythropoietin hyporesponsiveness, defined by an erythropoietin resistance index (ERI) of ≥10, associated with urate-lowering drugs.
Results: A total of 542 patients were included in the analysis, with 105, 36, 165, and 236 patients in the high-dose allopurinol, low-dose allopurinol, febuxostat, and no-treatment groups, respectively. The median and quartiles of ERIs were 6.3 (0, 12.2), 3.8 (0, 11.2), 3.4 (0, 9.8), and 4.8 (0, 11.2) in the high-dose allopurinol, low-dose allopurinol, febuxostat, and no-treatment groups, respectively. The multivariate regression model showed a statistically significant association between the high-dose allopurinol group and erythropoietin hyporesponsiveness, compared to the no-treatment group (OR=1.98, 95% confidence interval: 1.10–3.57).
Conclusions: Our study suggests that the use of high-dose allopurinol exceeding the optimal dose may lead to hyporesponsiveness to erythropoiesis-stimulating agents.
DOI: 10.17632/r7z9ttvkyh
title: Raw data and source code for: A lettuce growth model responding to a broad range of greenhouse climates

description: The raw data and model program supporting the manuscript entitled ‘A lettuce growth model responding to large scale greenhouse climate’ are shared here.

1. Datasets

To obtain data for calibration and validation of the lettuce growth model, three experiments of greenhouse lettuce cultivation were carried out. The experiment performed in the cold season was used for global calibration and named the calibration experiment (Exp_c). The other two in warm and cold-warm seasons, namely the first validation experiment (Exp_v1) and the second validation experiment (Exp_v2), were used for model validation. The data of each experiment is stored separately in the .xlsx file below.

 Greenhouse Climate & Crop data_Exp_c: Greenhouse climate and lettuce growth states in Exp_c.
 Greenhouse Climate & Crop data_Exp_v1: Greenhouse climate and lettuce growth states in Exp_v1.
 Greenhouse Climate & Crop data_Exp_v2: Greenhouse climate and lettuce growth states in Exp_v2.

These three .xlsx files have the same structure, including the sheets of Greenhouse climate, Lettuce growth, Lettuce growth summary, Lettuce growth summary_Sim, SLA calibration, and Root ratio. One exception is that the ‘Greenhouse Climate & Crop data_Exp_v1’ file contains an additional sheet named ‘Lettuce growth_TOP12’. The specific contents included in each sheet are illustrated as follows:

 Greenhouse climate: Greenhouse climate measurements, which are used as model inputs.
 Lettuce growth: The lettuce growth states measured in the laboratory, covering all the sampled plants in every sampling.
 Lettuce growth_TOP12: The lettuce growth states measured in the laboratory, covering the top 12 of the 18 lettuce samples in crop dry weight in every sampling. This sheet is derived from the sheet of ‘Lettuce growth’.
 Lettuce growth summary: Averages of the lettuce growth states, including crop dry weight and leaf area index that are determined by unit conversion according to plant density. This sheet is derived from ‘Lettuce growth’ or ‘Lettuce growth_TOP12’.
 Lettuce growth summary_Sim: Averages of the lettuce growth states used for global calibration and validation simulations. This sheet is derived from ‘Lettuce growth summary’.
 SLA calibration: The data used for calibrating the sub-model that describes the specific leaf area of new leaves. This sheet is derived from ‘Lettuce growth summary_Sim’ and ‘Greenhouse climate’.
 Root ratio: The data used for root ratio sub-model calibration. This sheet is derived from ‘Lettuce growth summary’.

2. Code

The source code of the lettuce growth model is in MATLAB format. The ‘Lettuce growth model program’ folder contains a script m-file, eight function m-files, and a data file in .xlsx format. The inputs of this code template are from Exp_v2. The principle of programming is to simplify the code and improve the computational efficiency. 

The source code of the smoothed model is also presented.
DOI: 10.6084/m9.figshare.11557860.v1
title: Additional file 4. of Strains used in whole organism Plasmodium falciparum vaccine trials differ in genome structure, sequence, and immunogenic potential

description: Description of var exon 1 sequences. Excel spreadsheet describing var exon 1 sequences recovered from each of the four PfSPZ strains.
DOI: 10.6084/m9.figshare.12061197.v1
title: Example Structure-From-Motion Data

description: Example data for exploring structure-from-motion data from a 100 m x 100 m subset of temperate forest in central Virginia.<br>Data collection and post-processing by:<br>Atticus Stovall, Bailey Costello, and Xi Yang<br>Drone: DJI Mavic Pro with onboard RGB camera
DOI: 10.6084/m9.figshare.19589335.v1
title: sequences and trees.zip

description: sequences and trees
DOI: 10.6084/m9.figshare.23896254.v1
title: Landmark-free statistical shape modelling reveals differing effects of age and sex on whole-muscle morphology among the triceps surae

description: this is the supplementary data from the paper titled "Landmark-free statistical shape modelling reveals differing effects of age and sex on whole-muscle morphology among the triceps surae" which describes the PC's for each of the muscles for each individual in the study.
DOI: 10.6084/m9.figshare.24312826.v1
title: Appendix 1 Oct 2023

description: Appendix 1 Oct 2023
DOI: 10.17632/3wvtjv7cwb
title: Manual Calculation of Pharmaceutical Inventory Logistic

description: This data consisted of detailed drug inventory logistic set at RA Basoeni Hospital, Mojokerto. The research question was to identify the efficient and effective drug inventory planning method taking into consideration the opportunity lost and opportunity cost of stagnant and shortage drugs. EOQ and MMSL had been selected as the methods for comparison with the existing consumption method. We found EOQ produced the lowest opportunity cost for stagnant drugs and the lowest opportunity loss for shortage drugs.
DOI: 10.17632/dmf94j4shn
title: Cognitive decline after subthalamic deep brain stimulation in Parkinson’s disease is preceded by pre-surgery executive deficit: An observational longitudinal study

description: Bayesian multilevel models of long-term post-surgery cognitive decline after subthalamic nucleus deep brain stimulation (STN DBS) in Parkinson's disease (PD).

Files include:
(A) Models reported in the main text ("models with weakly informative priors" folder),
(B) Models used for sensitivity analysis reported in supplemental materials ("models with flat priors" folder),
(C) R scripts to calculate prior predictive check and generate Tables 5 and 6 from the main text ("R scripts" folder).

The study investigated which pre-surgery cognitive profile characteristics are predictive of post-surgery cognitive decline in PD patients treated with STN DBS. Cognitive decline is a severe non-motor complication in PD that can significantly reduce benefits from STN DBS treatment. In the present study, we demonstrated that pre-surgery executive deficit can predict faster post-surgery decline in screening for dementia signs (according to Mattis Dementia Rating Scale, DRS-2).

The sample size of this study was (respectable) 106 patients followed for 3-11 years after STN DBS surgery. Majority of patients had at least three assessments making it easier for us to fit multilevel models and enjoy some of their cool properties such as partial pooling.

Since the study was a series of retrospective clinical observations, it is not ethically acceptable for us to publish patients' raw data. However, you, dear reader, can still inspect all Bayesian models that were fitted, explore their specifications, prior predictions or even use our posteriors as priors for your own research!

Kind regards,
Josef Mana
DOI: 10.17632/m3r8rgv29b
title: Data for: A Descriptive Study of Racial and Ethnic Differences of Drug Overdoses and Naloxone Administration in Pennsylvania

description: Overdose Information Network Data CY January 2018 - Current Monthly County State Police from open data PA available at https://data.pa.gov/Opioid-Related/Overdose-Information-Network-Data-CY-January-2018-/hbkk-dwy3
DOI: 10.6084/m9.figshare.19153760.v1
title: Machine-learning training and validation datasets

description: <b>Contains datasets used in "Computational cytomorphology reveals cellular archetypes in whole blood slides".</b><br><i>datasets.zip</i><br>ZIP file. Contains segmentation datasets for white blood cells in whole blood slides (blood smears) collected in three different settings:<br>- segmentation_dataset_AC1 - images from Addenbrooke's Hospital digitalized using a Hamamatsu Nanozoomer 2.0- segmentation_dataset_AC2 - images from Addenbrooke's Hospital digitalized using an Aperio AT2- segmentation_dataset_MLLC - images from the Munich Leukaemia Laboratory digitalized using a Hamatsu Nanozoomer<br><i>quality-datasets.zip</i><i><br></i>ZIP file. Contains two folders (train and test) with images annotated as being of good (1) or poor (0) quality. Retrieved from the MLL.<br><i>rbc-filtering-dataset.h5</i><i><br></i>Contains an HDF5 file with morphologically characterised objects annotated as ""RBC" (1) and "not RBC" (0) from images retrieved from whole blood slides as well as features characterising them. Divided into two groups "train" (where the train images are) and "test" (where the testing images).
DOI: 10.6084/m9.figshare.25983151.v1
title: University Staff’s Reflections on Generative AI in Higher Education: Insights from Social Media

description: This dataset supports the study exploring university staff’s opinions on the use of generative artificial intelligence (GenAI), specifically focusing on ChatGPT, within higher education. The research utilises social media posts shared on X (formerly Twitter). Posts written or targeted towards higher education staff containing discussions about ChatGPT and higher education were analysed. The dataset includes the original post, initial coding by the research team, included/excluded, reasons for exclusion.
DOI: 10.17632/my9p52xjbr
title: Data for: Energy performance analysis of airport terminal buildings by use of architectural, operational information and benchmark metrics

description: Geometry and operational data for 30 airport terminal buildings in North America.
DOI: 10.6084/m9.figshare.12560933.v1
title: Additional file 7 of Identification of long noncoding RNA RP11-89K21.1 and RP11-357H14.17 as prognostic signature of endometrial carcinoma via integrated bioinformatics analysis

description: Additional file 7. The transcription factors correlated with RP11-357H14.17
DOI: 10.6084/m9.figshare.16968460.v1
title: Partial anonymous data.xlsx

description: This is the data obtained by three participants using eye movement tracker, when they were wayfinding with paper maps, digital maps or voice-assisted digital maps.
DOI: 10.6084/m9.figshare.28585805.v1
title: database

description: The study aims to present a comprehensive model of distress in women facing infertility by examining both socially shaped factors (such as internalized pronatalist values and infertility-related self-stigma) and personal factors (including adult and societal identity resolution, as well as aspects of reproductive identity).
DOI: 10.17632/f6s2dw9mrn
title: Example 4: l-i SEIR-Vaccination model - Effect of Vaccination  on COVID-19 Spread in the United States

description: In examples 1 to 3, we have demonstrated how to use Excel to calculate variables Sn, En, In, Rn, yn in l-i SEIR (Susceptible-Exposed-Infectious-Recovered) model, to determine the time-dependent kn, and to find the number of actual total infections in the absence of vaccination and breakthrough infections. In the l-i SEIR model, l is the time length of latent period, i is the time length of infectious period, and yn is the number of daily-confirmed cases of infections. In this section (Example 4), we will extend l-i SEIR model to l-i SEIR-vaccination model for examining the effect of vaccination on COVID-19 transmission. Two files (one Word file and one Excel files) are attached. In the Word file, the author described how to build the l-i SEIR-vaccination model and how to calculate the number of daily confirmed cases of COVID-19 infections, yn, in Excel. The calculated yn and the reported yn have been compared to each other and displayed graphically in the Excel file
DOI: 10.6084/m9.figshare.1008414.v1
title: Intracellular ROS production in cells following treatment with welding fumes

description: RAW 264.7 cells were pre-treated with DCFH-DA, exposed to suspensions of welding fumes, and plates were read each hour to measure intracellular ROS represented as arbitrary fluorescence units. Values represent means from triplicate wells run in 3 independent experiments.
DOI: 10.6084/m9.figshare.24431146.v3
title: 2016 Glasser MMP1.0 Cortical Atlases

description: The Glasser et al. group level MMP parcellation map projected into volumetric space using registration fusion. Volumetric space is available for two different standard templates. <br>MNI152NLin6Asym - FSL/HCP "standard" space<br>MNI152NLin2009cAsym - fmriprep's default space.glasser_MNI152NLin[2009c|6]Asym_atlas.nii.gz - probabilistic maps projected to two templates' spaces<br>glasser_atlas_labels.txt - labels of parcels above, line order corresponds to volume order.<br>[lr]h_[bmrk5|paingen]_MNI152NLin[2009c|6]Asym.nii.gz - subject specific parcellations projected in templates' space. One per hemisphere<br>[rl]h.HCP.MMP1 - glasser atlas resampled to fsaverage surfaces<br>methods - informal methods description (but still pretty formal)<br><br>The group MMP surface parcellation was resampled from fs_LR to fsaverage space. Surface to volume mappings were then used to transform the group MMP parcellation from fsaverage space into native T1 space. Finally, transformations from native T1 space to the desired template space were applied to transform parcellations into the desired spaces. Individual participant's projections were used to estimate probability maps for each study separately. The resultant study specific probability maps were averaged. Data from two different studies (N=89 and N=241), are incorporated. fmriprep 20.2.3 was run with the --recon-all flag to produce all necessary spatial transformations.Refer to methods.txt for scanning protocols and participant details.
DOI: 10.6084/m9.figshare.25304032.v1
title: data-Health Information Needs and Feedback of Users in the Online TCM Community

description: data-Health Information Needs and Feedback of Users in the Online TCM Community
DOI: 10.6084/m9.figshare.27124563.v1
title: Supplementary Material for: Current Advances in Computerised Cognitive Assessment for Mild Cognitive Impairment and Dementia in Older Adults: A systematic Review

description: Introduction: Timely detection of cognitive impairment such as mild cognitive impairment (MCI) or dementia is pivotal in initiating early interventions to improve patients’ quality of life. Conventional paper-pencil tests, though common, have limited sensitivity in detecting subtle cognitive changes. Computerised assessments offer promising alternatives, overcoming time and manual scoring constraints while potentially providing greater sensitivity.

Methods: A literature search yielded 26 eligible articles (2020-2023). The articles were reviewed according to PRISMA guidelines and the computerised tools were categorised by diagnostic outcome (MCI, dementia, combined). 

Results: The subjects included in the studies were aged 55 to 77 years. The overall gender distribution comprised 60% females and 40% males. The sample sizes varied considerably from 22 to 4486. Convergent validity assessments in 20 studies demonstrated strong positive correlations with traditional tests. Overall classification accuracy in detecting MCI or dementia, distinguishing from normal cognition (NC), reached up to 91%. Impressively, 46% of the studies received high-quality ratings, underscoring the reliability and validity of the findings. 

Conclusion: The review highlights the advancements in computerised cognitive assessments for assessing MCI and dementia. This shift toward technology-based assessments could enhance detection capabilities and facilitate timely interventions for better patient outcomes.
DOI: 10.17632/h4rtr9h5kd
title: Can Big Data Help to Predict Conditional Stock Market Volatility? An Application to Brexit

description: Two appendices describing data and offering a sample code for the paper WCan Big Data Help to Predict Conditional Stock Market Volatility? An Application to Brexit" by V. Bellini, M. Guidolin and M. Pedio. A python sample code is also available. The raw dataset is also available.
DOI: 10.17632/kh3v4zybxr
title: Types du Prodrome de paléontologie stratigraphique universelle de d’Orbigny.

description: Annales de Paléotologie 1925;fasc.4:133–64.
DOI: 10.6084/m9.figshare.12845801.v1
title: modified 33bus IEEE system parameter.docx

description: modified 33bus system data
DOI: 10.6084/m9.figshare.19636389.v1
title: Questionnaire survey

description: The questionnaire survey is developed to collect the respondent's opinion on our findings
DOI: 10.6084/m9.figshare.28233857.v1
title: TempODEGraphNet.zip

description: Research on user churn prediction has been conducted across various domains for a long time. Among these, the gaming domain is characterized by its potential for diverse types of interactions between users. Due to this characteristic, many studies on churn prediction have considered the relationships between users and have primarily applied social network analysis. Recently, the use of Graph Neural Networks (GNNs) has been actively applied. However, existing studies utilizing GNNs have limitations as they use static graphs that do not effectively capture the dynamic nature of interactions that change over time. This study addresses these limitations by proposing a dynamic graph model for predicting user churn in games based on user interactions. Data are sourced from 10,000 users of 'Blade \& Soul' by NCSOFT. The proposed model effectively captures changes in user behavior over time and predicts user churn with a focus on interactions among users. Experimental results reveal that the proposed model achieves a higher F1 score compared with conventional algorithms and static graph models. Dynamic graphs more accurately reflect changes in user behavior compared with static graphs, particularly in domains with active interactions such as massively multiplayer online role-playing games. This work highlights the significance of user churn prediction in the gaming industry and demonstrates the effectiveness of the predictive models that use dynamic graphs.
DOI: 10.6084/m9.figshare.9868004.v1
title: A method to deposit a known number of polystyrene latex particles on a flat surface

description: This study introduces a method to deposit polystyrene latex (PSL) particles on a silicon wafer in a manner that allows their number to be predicted with a high degree of accuracy. A laminar flow growth tube is used to condense supersaturated water vapor on seed aerosol particles that are water-insoluble. After condensation is complete the droplets are accelerated through a nozzle to form an aerosol jet, and the number of droplets in this jet is counted optically. The droplets are then deposited on a flat surface by inertial impaction. The particle number on the surface is predicted by multiplying the droplet number by an experimentally evaluated conversion coefficient of 0.991 ± 0.011 (<i>k</i> = 2). Uncertainty analysis showed with a 95% confidence interval that the particle number on a flat surface is ± 2.0%. The primary application of this method is to make a particle number standard (PNS) wafer whose intended use is to evaluate the counting efficiencies of wafer surface scanners, and this study demonstrates the fabrication of such PNS wafers. A motorized XY-stage moves the surface horizontally to deposit PSL particles along desired paths over a half-inch wafer. The particle number was varied over seven levels ranging from 10 to 10,000. The particle diameter was varied at four levels: 0.814, 0.18, 0.102, and 0.046 µm. In all PNS wafers, the number of deposited particles was counted using optical microscopes. The observed particle numbers were all within the 95% confidence interval of the predicted value. Copyright © 2019 American Association for Aerosol Research
DOI: 10.6084/m9.figshare.1184438.v1
title: Ecology Lab #2- Dataset 1

description: The following data was collected at York University's Keele campus. It took place on Sept. 24/2014 at around 4:00pm in approximately 20 degree celcius weather. A metal quadrat was placed on the ground encompassing an area of vegetation ten times in randomized areas. These areas were visually assessed based on the following characteristics: the percentage of coverage of total vegetation, the percentage of coverage of grass alone, the total abundance of plants in the quadrat, as well as the number of species of plants within the quadrat.
DOI: 10.6084/m9.figshare.13251746.v1
title: Forest_Biomass_Map.zip

description: Forest Biomass map of Europe for 2010 - 32 bit version