cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.16446393.v3
title: 8-day SIF at 0.05 degree

description: Photosynthesis (or Gross Primary Production, GPP) is a key process in hydrology and ecology linking carbon and water cycles. The newly available satellite-retrieved solar-induced chlorophyll fluorescence (SIF) is a direct measure of photosynthesis globally. However, the existing satellite SIF records are limited by low spatial resolution, sparse data acquisition, or both. The situation changed in 2018 with the launched TROPOspheric Monitoring Instrument (TROPOMI), from which SIF can be retrieved with unprecedented resolution, but the short temporal coverage of this data record precludes its use for many applications. This study reconstructs a long-term contiguous and high resolution TROPOMI SIF product over 2001-2019 at a 0.05° and 8-day resolution using machine learning combined with the physiological constraints. The model provides a significantly more accurate prediction of SIF (R<sup>2</sup>= 0.919, regression slope=1.002), which is consistent with GPP estimations and other independent SIF measurements. The long-term, high-resolution, contiguous global coverage of this dataset will be valuable for estimating GPP to constrain the global carbon budget and related water fluxes.
DOI: 10.17632/ffb35993tw
title: AVETUXIRI trial - Impact of the tumor immune contexture in refractory microsatellite stable metastatic colorectal cancer treated with avelumab, cetuximab and irinotecan

description: The treatment of patients with microsatellite stable (MSS) metastatic colorectal cancer (mCRC) remains a significant clinical challenge. Cetuximab, an anti-EGFR monoclonal antibody, induces immunogenic cell death, potentially synergizing with immune checkpoint inhibitors. The phase 2, proof-of-concept, single-arm AVETUXIRI trial (NCT03608046) evaluates the safety and efficacy of cetuximab, irinotecan (a topoisomerase I inhibitor), and avelumab (an anti-PD-L1) in 57 patients with RAS wild-type or mutated MSS mCRC refractory to chemotherapy and anti-EGFR mAbs. Exploratory objectives include investigating the tumor immune microenvironment within mCRC biopsies performed during the trial and correlating it with treatment activity. A manageable safety profile is observed. Although the overall efficacy endpoints are not met, biomarkers associated with clinical efficacy are identified. Patients exhibiting a high Immunoscore, strong cytotoxic and T cell proximity to tumor cells, and a high genetic immunoediting score within mCRC biopsies before treatment demonstrate significant therapeutic survival benefit, independent of RAS tumor mutation status.
DOI: 10.6084/m9.figshare.26036563.v1
title: <b>Impact of I-PACE Model-Based Mindfulness Training on Fear of Missing Out Among Chinese College Students: A Mixed-Methods Study</b>

description: This study investigates the effectiveness of a mindfulness-based Fear of Missing Out (FoMO) intervention grounded in the Interaction of Person-Affect-Cognition-Execution (I-PACE) model among Chinese college students. Utilizing a mixed-methods approach, we conducted a six-week Mindfulness-Based FoMO Intervention (MBFI) program.
DOI: 10.6084/m9.figshare.27276246.v1
title: snowstorm data

description: 70 year Snowstorm Data in Northern Xinjiang
DOI: 10.6084/m9.figshare.90208.v1
title: How many cells should we count?

description: These data were gathered in an effort to solve a problem with correlating microscopic cell counts and fluorescence measurements taken during the summer of 2000 from an oyster (Crassostrea virginica) grazing experiment reported in Thessen, A.E., Q. Dortch, T.M. Soniat and G.J. Doucette (2009) Crassostrea virginica grazing on toxic and non-toxic diatoms. Toxicon.doi:10.1016/j.toxicon.2009.10.011. The cells in question are the diatom Pseudo-nitzschia. We wanted to answer the question, "Are we counting enough fields and cells to be representative of the sample?" We pulled several slides (slide # 627, 633, 700, 688, 682 and 684) from the experiment of varying cell concentration and species, initially counted at different magnifications. We calculated mean and standard deviation for each field until the two values seemed to stabilize. These data did not solve the correlation problem. We later concluded that a fungal infection in the Pseudo-nitzschia culture had caused the problem.
DOI: 10.6084/m9.figshare.5047666.v3
title: Face Research Lab London Set

description: Images are of 102 adult faces 1350x1350 pixels in full colour. Template files mark out 189 coordinates delineating face shape, for use with Psychomorph or WebMorph.org.<br><br>Self-reported age, gender and ethnicity are included in the file london_faces_info.csv. Attractiveness ratings (on a 1-7 scale from "much less attractiveness than average" to "much more attractive than average") for the neutral front faces from 2513 people (ages 17-90) are included in the file london_faces_ratings.csv.<br><br>All individuals gave signed consent for their images to be "<i>used in lab-based and web-based studies in their original or altered forms and to illustrate research (e.g., in scientific journals, news media or presentations).</i>" Images were taken in London, UK, in April 2012.
DOI: 10.17632/sg46yyrsmv
title: Results of bubble detection and tracking of subcooled boiling flow

description: Results of bubble detection and tracking based on work Github:https://github.com/zhouzhouwen/The-Robust-Development-of-a-TH-Analysis-Method-for-Bubbles-Using-AI
DOI: 10.17632/y5nybjdshn
title: Optimised simulated annealing for Ising spin glasses

description: This program has been imported from the CPC Program Library held at Queen's University Belfast (1969-2018) Abstract We present several efficient implementations of the simulated annealing algorithm for Ising spin glasses on sparse graphs. In particular, we provide a generic code for any choice of couplings, an optimised code for bipartite graphs, and highly optimised implementations using multi-spin coding for graphs with small maximum degree and discrete couplings with a finite range. The latter codes achieve up to 50 spin flips per nanosecond on modern Intel CPUs. We also compare the performance of the c... Title of program: SimAn v1.0 Catalogue Id: AEVZ_v1_0 Nature of problem Ising spin glass ground states on sparse graphs. Versions of this program held in the CPC repository in Mendeley Data AEVZ_v1_0; SimAn v1.0; 10.1016/j.cpc.2015.02.015
DOI: 10.6084/m9.figshare.12227273.v2
title: AquaSat_DSWE

description: The AquaSat_DSWE dataset is a variant to Aquasat (10.6084/m9.figshare.c.4506140) that uses the USGS dynamic surface water extent to delineate water pixels instead of the JRC Global Surface Waters dataset. AquaSat is the largest inland water matchup dataset ever assembled. It pairs more than 600,000 in-situ observations with satellite imagery to provide a large-scale training dataset for continental scale remote sensing of water quality. The code to generate aquasat can be found here: https://github.com/GlobalHydrologyLab/watersat and the paper here: 10.1029/2019WR024883
DOI: 10.6084/m9.figshare.23835165.v3
title: geodl example data

description: Example data associated with geodl package (https://github.com/maxwell-geospatial/geodl).
DOI: 10.6084/m9.figshare.24461014.v2
title: Complementary files - The Single-Cell Transcriptome Program of Nodule Development Cellular Lineages in <i>Medicago truncatula</i>

description: RDS files containing the clustered datasets from "The Single-Cell Transcriptome Program of Nodule Development Cellular Lineages in <i>Medicago truncatula</i>"
DOI: 10.17632/z355dxzyjw
title: Molecular descriptors for corrosion inhibitors

description: Molecular descriptors for 37 selected corrosion inhibitors. These descriptors cover quantum, topological, structural, bioavailability/pharmacokinetic (ADME), and physicochemical aspects, offering a multidimensional insight into the characteristics of the inhibitors
DOI: 10.6084/m9.figshare.21181069.v1
title: A dataset of landscape and road features that drive wildlife mortality in the Amazon

description: Data for publication Medrano-Vizcaíno P., Grilo C., Brito-Zapata, D., and González-Suárez M. 2023. Landscape and road features linked to wildlife mortality in the Amazon. <br> We include ten .csv files with distances to landscape features, percentage of cover, and road sinuosity from roadkill and control sites for: all vertebrates, amphibians, amphibians without cane toad, cane toad, reptiles, birds, mammals, mammals without opossums, opossums, and amphisbaenians and caecilians. <br> For more details, read the readme.txt file. <br>
DOI: 10.6084/m9.figshare.23590302.v2
title: Reconstructing visual illusory experiences from human brain activity

description: This repository provides preprocessed fMRI data, stimulus image features, and pretrained image generators used in the following work.Cheng, F., Horikawa, T., Majima, K., Tanaka, M., Abdelhack, M., Aoki, S. C., Hirano, J., & Kamitani, Y. (2023). Reconstructing visual illusory experiences from human brain activity. bioRxiv. https://doi.org/10.1101/2023.06.15.545037Raw (unpreprocessed) fMRI data are available at https://openneuro.org/datasets/ds004670.Code is available at https://github.com/KamitaniLab/IllusionReconstruction.See the GitHub repository for more details.History2023-09-24 Initial release2023-09-28 Update generators (remove unnecessary files in generator-GAN.zip and add generator-diffusion.zip)
DOI: 10.6084/m9.figshare.28815350.v1
title: Māori perspectives of kaitiakitanga in cities

description: This data set captures the perspectives of Māori pertaining to the concept of Kaitiakitanga in Hamilton, New Zealand. The interview data explores participants childhood, knowledge of local tribal groups and their history, knowledge and practice of kaitiakitanga, wider Māori cultural practices, engagement with local tribes and restoration groups, understandings of aspects that support kaitiakitanga as well as the challenges faced for the expression of kaitiakitanga practices.
DOI: 10.17632/v7gp2bmdfj
title: Archaeological Predictive Model - Pajeú

description: Dataset to build the Pajeú-APM. The dataset contains the socio-environmental raster data, extracted from a SRTM DEM and other spatial data from brazilian government agencies.
DOI: 10.6084/m9.figshare.1588513.v2
title: Face-noise ERP onsets from 194 recording sessions

description: This data package contains ERP onsets estimated from 120 participants, 74 of whom were tested twice. Stimuli were face images and noise textures. Onsets were estimated using ERP data low-pass filtered or not, using t-tests on means or 20% trimmed-means. We corrected for multiple comparisons using cluster based statistics in conjunction with a percentile-t bootstrap procedure. The results were reported in this paper accepted for publication: <strong>A robust and representative lower bound on object processing speed in humans</strong><br>Magdalena Bieniek, Patrick Bennett, Allison Sekuler & Guillaume Rousselet<br><em>European Journal of Neuroscience</em>
DOI: 10.6084/m9.figshare.26537158.v1
title: Automating the assessment of biofouling in images

description: Images and annotations used for training the computer vision models in the <i>Automating the assessment of biofouling in images using expert agreement as a gold standard</i> (2021) paper.
DOI: 10.6084/m9.figshare.27264444.v1
title: Predictions of molecular orientation and charge mobility in organic vacuum-deposited thin films by multiscale simulation

description: LAMMPS input and output files.
DOI: 10.6084/m9.figshare.27642063.v3
title: Fixing of raster upscaling result

description: A method for preserving three spatial features in the upscaling of categorical raster data
DOI: 10.17632/56jyjndvcr
title: Bridging the Gap in Hypertension Management: Evaluating Blood Pressure Control and Associated Risk Factors in a Resource-Constrained Setting

description: Dataset Description

This dataset contains a simulated collection of 1,00000 patient records designed to explore hypertension management in resource-constrained settings. It provides comprehensive data for analyzing blood pressure control rates, associated risk factors, and complications. The dataset is ideal for predictive modelling, risk analysis, and treatment optimization, offering insights into demographic, clinical, and treatment-related variables.

Dataset Structure

1. Dataset Volume

 • Size: 10,000 records.
 • Features: 19 variables, categorized into Sociodemographic, Clinical, Complications, and Treatment/Control groups.

2. Variables and Categories

A. Sociodemographic Variables

 1. Age:
 • Continuous variable in years.
 • Range: 18–80 years.
 • Mean ± SD: 49.37 ± 12.81.
 2. Sex:
 • Categorical variable.
 • Values: Male, Female.
 3. Education:
 • Categorical variable.
 • Values: No Education, Primary, Secondary, Higher Secondary, Graduate, Post-Graduate, Madrasa.
 4. Occupation:
 • Categorical variable.
 • Values: Service, Business, Agriculture, Retired, Unemployed, Housewife.
 5. Monthly Income:
 • Categorical variable in Bangladeshi Taka.
 • Values: &lt;5000, 5001–10000, 10001–15000, &gt;15000.
 6. Residence:
 • Categorical variable.
 • Values: Urban, Sub-urban, Rural.

B. Clinical Variables

 7. Systolic BP:
 • Continuous variable in mmHg.
 • Range: 100–200 mmHg.
 • Mean ± SD: 140 ± 15 mmHg.
 8. Diastolic BP:
 • Continuous variable in mmHg.
 • Range: 60–120 mmHg.
 • Mean ± SD: 90 ± 10 mmHg.
 9. Elevated Creatinine:
 • Binary variable (\geq 1.4 \, \text{mg/dL}).
 • Values: Yes, No.
 10. Diabetes Mellitus:
 • Binary variable.
 • Values: Yes, No.
 11. Family History of CVD:
 • Binary variable.
 • Values: Yes, No.
 12. Elevated Cholesterol:
 • Binary variable (\geq 200 \, \text{mg/dL}).
 • Values: Yes, No.
 13. Smoking:
 • Binary variable.
 • Values: Yes, No.

C. Complications

 14. LVH (Left Ventricular Hypertrophy):
 • Binary variable (ECG diagnosis).
 • Values: Yes, No.
 15. IHD (Ischemic Heart Disease):
 • Binary variable.
 • Values: Yes, No.
 16. CVD (Cerebrovascular Disease):
 • Binary variable.
 • Values: Yes, No.
 17. Retinopathy:
 • Binary variable.
 • Values: Yes, No.

D. Treatment and Control

 18. Treatment:
 • Categorical variable indicating therapy type.
 • Values: Single Drug, Combination Drugs.
 19. Control Status:
 • Binary variable.
 • Values: Controlled, Uncontrolled.

Dataset Applications

 1. Predictive Modeling:
 • Develop models to predict blood pressure control status using demographic and clinical data.
 2. Risk Analysis:
 • Identify significant factors influencing hypertension control and complications.
 3. Severity Scoring:
 • Quantify hypertension severity for patient risk stratification.
 4. Complications Prediction:
 • Forecast complications like IHD, LVH, and CVD for early intervention.
 5. Treatment Guidance:
 • Analyze therapy efficacy to recommend optimal treatment strategies.
DOI: 10.17632/mpvwnhv4vb
title: Extended Federated Ensemble Regression using Classification

description: Datasets used for the evaluation of the Extended Federated Ensemble Regression using Classification algorithm.
DOI: 10.6084/m9.figshare.26213120.v1
title: Resequencing of date palm varieties

description: This data were generated by resequencing 220 date palm accessions using the Illumina HiSeq 4000 platform.
DOI: 10.6084/m9.figshare.28203392.v1
title: DATA SHEET.csv

description: Breast cancer is one of the most prevalent cancers among women worldwide, and early detection is crucial for reducing mortality rates and improving treatment outcomes. Mammography has been the gold standard for breast cancer screening, offering non-invasive imaging to identify suspicious abnormalities. However, mammography has limitations, such as variability in interpretation, false positives, false negatives, and challenges in distinguishing between benign and malignant lesions.Machine learning has the potential to revolutionize breast cancer detection by enhancing the capabilities of mammography. Its ability to improve accuracy, efficiency, and consistency in diagnosis makes it an indispensable tool for early detection efforts.This study focuses on developing a machine learning-based predictive model for the early detection and classification of breast cancer, utilizing the Wisconsin Breast Cancer Diagnostic dataset. Special emphasis is placed on the potential of ML algorithms, particularly the Support Vector Classifier with a Radial Basis Function (SVC-RBF), to enhance diagnostic accuracy and efficiency.Machine learning has the potential to revolutionize breast cancer detection by enhancing the capabilities of mammography. Its ability to improve accuracy, efficiency, and consistency in diagnosis makes it an indispensable tool for early detection efforts.
DOI: 10.6084/m9.figshare.28382285.v1
title: IgHuAb and SynAbLib

description: Antibody pair generating LLMSynthetic Antibody Library<br>
DOI: 10.6084/m9.figshare.28424780.v8
title: Single Cell DNA methylation data for Human Brain altas (MajorType+Region CG allc files)

description: Pseudobulk level allc files, file name format: {MajorType}.{Region}.allc.tsv.gzPlease note:(1). Those allc files contain CG only; there is no CH.(2). The strands are not merged.CitationIf you used this data in your research, please cite:Tian, W., Zhou, J., Bartlett, A., Zeng, Q., Liu, H., Castanon, R. G., ... & Ecker, J. R. (2023). Single-cell DNA methylation and 3D genome architecture in the human brain. Science, 382(6667), eadf5357.PMID: 37824674<br>How to downloadTo quickly download the whole folder, Python package pyfigshare can be implemented. please refer to pyfigshare documentation: https://github.com/DingWB/pyfigsharefor example: <code>figshare download 28424780 -o downlnoaded_data</code>
DOI: 10.6084/m9.figshare.29161076.v1
title: Database (Leaf area index; Wood growth and climate variables)

description: This dataset contains wood growth data, leaf area index, and climatic variables for two hybrid eucalyptus clones (E. grandis × E. urophylla): CO 1407 and VCC 865.
DOI: 10.6084/m9.figshare.3514322.v1
title: Appendix A. A list of variables measured at each site.

description: A list of variables measured at each site.
DOI: 10.6084/m9.figshare.21968078.v1
title: Experimental Dataset for "Ensemble dynamics and information flow deduction from whole-brain imaging data" and "WormTensor: a clustering method for time-series whole-brain activity data from C. elegans”

description: normalize1_withoutremove.zip is the time course of whole-brain activities of C. elegans for 28 animals used in Tsuyuzaki et al, "WormTensor: a clustering method for time-series whole-brain activity data from C. elegans” (BMC Bioinformatics, 2023, https://doi.org/10.1186/s12859-023-05230-2)This dataset is superset of the data used in Toyoshima et al, "Ensemble dynamics and information flow deduction from whole-brain imaging data" (now in press at PLoS Comp Biol, https://doi.org/10.1371/journal.pcbi.1011848) or its preprint on bioRxiv 2022.11.18.517011 (https://doi.org/10.1101/2022.11.18.517011) 20221118freezed.7z is the dataset used in with TDE-RICA (https://github.com/YuToyoshima/TDE-RICA) and gKDR-GMM (https://github.com/yuichiiino1/gKDR-GMM).
DOI: 10.6084/m9.figshare.28517444.v1
title: scopus.csv

description: Bibliometric analysis on media literacy and equality in the Scopus database in the last two decades
DOI: 10.6084/m9.figshare.9383600.v1
title: A critical review of laboratory performance indicators

description: Healthcare budgets worldwide are under constant pressure to reduce costs while improving efficiency and quality. This phenomenon is also visible in clinical laboratories. Efficiency gains can be achieved by reducing the error rate and by improving the laboratory’s layout and logistics. Performance indicators (PIs) play a crucial role in this process as they allow for performance assessment. This review aids in the process for selecting laboratory PIs—which is not trivial—by providing an overview of frequently used PIs in the literature that can also be used in clinical laboratories. We conducted a systematic review of the laboratory medicine literature on PIs. As the testing process in clinical laboratories can be viewed as a production process, we also reviewed the production processes literature on PIs. The reviewed literature relates to the design, optimization or performance assessment of such processes. The most frequently cited PIs relate to pre-analytical errors, timeliness, resource utilization, cost, and the amount of congestion. Their citation frequency in the literature is used as a proxy for their importance. PIs are discussed in terms of their definition, measurability and impact. The use of suitable PIs is crucial in production processes, including clinical laboratories. By also reviewing the production processes literature, additional relevant PIs for clinical laboratories were found. The PIs in the laboratory medicine literature mostly relate to laboratory errors, while the PIs in the production processes literature relate to the amount of congestion in the process.
DOI: 10.6084/m9.figshare.25531519.v1
title: Discussion of ``Nikuradse Roughness Height Derived from a Physically Based Model Applied to a River Channel with Dunes''

description: The code (MATLAB live script) and data used to produce the figures in the Discussion of ``Nikuradse Roughness Height Derived from a Physically Based Model Applied to a River Channel with Dunes''
DOI: 10.6084/m9.figshare.7665770.v1
title: Recurrence determinism and Li–Yorke chaos for interval maps

description: Recurrence determinism, one of the fundamental characteristics of recurrence quantification analysis, measures predictability of a trajectory of a dynamical system. It is tightly connected with the conditional probability that, given a recurrence, following states of the trajectory will be recurrences. In this paper, we study recurrence determinism of interval dynamical systems. We show that recurrence determinism distinguishes three main types of ω-limit sets of zero entropy maps: finite, solenoidal without non-separable points, and solenoidal with non-separable points. As a corollary, we obtain characterizations of strongly non-chaotic and Li–Yorke (non-)chaotic interval maps via recurrence determinism. For strongly non-chaotic maps, recurrence determinism is always equal to one. Li–Yorke non-chaotic interval maps are those for which recurrence determinism is always positive. Finally, Li–Yorke chaos implies the existence of a Cantor set of points with zero determinism.
DOI: 10.17632/4vy9rbjvw7
title: Research Data-Investigating individual learning behaviour of dogs during a yes/no detection task

description: The learning processes of three detection dogs were investigated during tests with familiair samples and novel samples.
The Results of the Criterion Tests and Novel Tests can be read in the dataset.
DOI: 10.17632/hvkcs9v8r3
title: The data set of order picking problem in the online-to-offline grocery

description: The Order set file includes the order set used in the experiments of the comparative study between BP and BSZP.
U(1,5) Random.mat is the order set with U(1,5) order type and Random storage assignment.
U(1,5) ABC.mat is the order set with U(1,5) order type and ABC/ABC-1 storage assignment.
U(1,5) ABC2.mat is the order set with U(1,5) order type and ABC-2 storage assignment.
U(1,10) Random.mat is the order set with U(1,10) order type and Random storage assignment.
U(1,10) ABC.mat is the order set with U(1,10) order type and ABC/ABC-1 storage assignment.
U(1,10) ABC2.mat is the order set with U(1,10) order type and ABC-2 storage assignment.
U(1,15) Random.mat is the order set with U(1,15) order type and Random storage assignment.
U(1,15) ABC.mat is the order set with U(1,15) order type and ABC/ABC-1 storage assignment.
U(1,15) ABC2.mat is the order set with U(1,15) order type and ABC-2 storage assignment.
Note: each .mat file includes the arrival time and the detailed information of the orders for a timeframe of 60 days with 4000 orders.
The arrival time is 0~750. The number of items is 1200.