cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/jszw485f8j.5
title: LUTBIO multimodal biometric database

description: The LUTBIO database provides a comprehensive resource for research in multimodal biometric authentication, featuring the following key aspects:

- Extensive Biometric Modalities: The database contains data from nine biometric modalities: voice, face, fingerprint, contact-based palmprint, electrocardiogram (ECG), opisthenar (back of hand), ear, contactless palmprint, and periocular region.

- Diverse Demographics: Data were collected from 306 individuals, with a balanced gender distribution of 164 males and 142 females, spanning an age range of 8 to 90 years. This diverse age representation enables analyses across a wide demographic spectrum.

- Representative Population Sampling: Volunteers were recruited from naturally occurring communities, ensuring a large-scale, statistically representative population. The collected data encompass variations observed in real-world environments.

- Support for Multimodal and Cross-Modality Research: LUTBIO provides both contact-based and contactless palmprint data, as well as fingerprint data (from optical images and scans), promoting advancements in multimodal biometric authentication. This resource is designed to guide the development of future multimodal databases.

- Flexible, Decouplable Data: The biometric data in the LUTBIO database are designed to be highly decouplable, enabling independent processing of each modality without loss of information. This flexibility supports both single-modality and multimodal analysis, empowering researchers to optimize, combine, and customize biometric features for specific applications.


✅ Data Availability: To facilitate early access, we are initially releasing sample data from 6 individuals. Upon publication of the paper, the full dataset will be made available.

🥸 Important Notice: Please read the data collection protocol of the LUTBIO dataset carefully before use, as it is essential for understanding and correctly interpreting the dataset. Thank you.

😎 Good news! Our paper has received revision comments, and we are carefully making revisions based on the feedback. We appreciate the reviewers and the editor for their efforts.🥰🥰🥰

🤠 We conducted further research based on the LUTBIO database and proposed AuthFormer: An Adaptive Multimodal Biometric Authentication Framework for Secure and Flexible Identity Verification. The code is available at https://github.com/RykerYang/Authformer.git. Our work is currently under review for an international conference, where we are dealing with a malicious reviewer. We are in the process of responding and appealing—wish us luck! 🍀🍀🍀
DOI: 10.17632/jszw485f8j.6
title: LUTBIO multimodal biometric database

description: The LUTBIO database provides a comprehensive resource for research in multimodal biometric authentication, featuring the following key aspects:

- Extensive Biometric Modalities: The database contains data from nine biometric modalities: voice, face, fingerprint, contact-based palmprint, electrocardiogram (ECG), opisthenar (back of hand), ear, contactless palmprint, and periocular region.

- Diverse Demographics: Data were collected from 306 individuals, with a balanced gender distribution of 164 males and 142 females, spanning an age range of 8 to 90 years. This diverse age representation enables analyses across a wide demographic spectrum.

- Representative Population Sampling: Volunteers were recruited from naturally occurring communities, ensuring a large-scale, statistically representative population. The collected data encompass variations observed in real-world environments.

- Support for Multimodal and Cross-Modality Research: LUTBIO provides both contact-based and contactless palmprint data, as well as fingerprint data (from optical images and scans), promoting advancements in multimodal biometric authentication. This resource is designed to guide the development of future multimodal databases.

- Flexible, Decouplable Data: The biometric data in the LUTBIO database are designed to be highly decouplable, enabling independent processing of each modality without loss of information. This flexibility supports both single-modality and multimodal analysis, empowering researchers to optimize, combine, and customize biometric features for specific applications.


✅ Data Availability: If you wish to use the LUTBIO dataset, please download the attached Word document, fill in the information, and send it as an attachment to rykeryang AT 163.com. We will process your request as soon as possible!

🥸 Important Notice: Please read the data collection protocol of the LUTBIO dataset carefully before use, as it is essential for understanding and correctly interpreting the dataset. Thank you.

😎 Good news! Our paper has been accepted by Information Fusion, and the DOI is https://doi.org/10.1016/j.inffus.2025.102945. We appreciate the reviewers and the editor for their efforts.🥰🥰🥰
DOI: 10.17632/6wzjdgbvsz.1
title: Base de datos de entrevistas asociadas a la atención y acceso a salud de personas sordas

description: Base de datos con entrevistas a personas sordas sobre la atención y acceso a la salud en una ciudad del sur de Chile.
DOI: 10.17632/6sfvffhtxs.1
title: A methyltransferase-independent role for METTL1 in tRNA aminoacylation and oncogenic transformation

description: This submission is raw imaging data for our manuscript describing the following: Amplification of chromosomal material derived from 12q13-15 is common in human cancer, and believed to result in overexpression of multiple collaborating oncogenes. To define oncogenes involved, we overexpressed genes recurrently amplified in human liposarcoma using a zebrafish model of the disease. We found several genes whose overexpression collaborated with AKT in sarcomagenesis, including the tRNA methyltransferase METTL1. This was surprising because AKT phosphorylates METTL1 to inactivate its enzymatic activity. Indeed, phosphomimetic S27D or catalytically dead alleles phenocopied the oncogenic activity of wild-type METTL1. We found that METTL1 binds the multi-tRNA synthetase complex, which contains many of the cellular aminoacyl-tRNA synthetases, and promotes tRNA aminoacylation, polysome formation and protein synthesis independent of its methyltransferase activity. METTL1-amplified liposarcomas were hypersensitive to actinomycin D, a clinical inhibitor of ribosome biogenesis. Thus, METTL1 stimulates tRNA aminoacylation and protein synthesis independent of its methyltransferase activity, and this tumor-promoting function confers susceptibility to inhibition of ribosome biogenesis.
DOI: 10.17632/9jdpj94cyd.1
title: Supplementary materials for: The efficacy of longer-term lebrikizumab treatment in patients with moderate-to-severe atopic dermatitis who did not meet protocol-defined response criteria at week 16 in 2 randomized controlled clinical trials

description: Table I. Trial Registration
Table II: Efficacy Outcomes Scales
Table III: Proportion of Patients Achieving EASI 75 During Treatment in the Escape Arm
Table IV. Overview of Adverse Events 
Table V. Rescue Therapy Usage from Week 16 to Week 52 
Figure 1. Study Design for ADvocate1 and ADvocate2 
Figure 2. ADvocate1 and ADvocate2 Pooled Patient Disposition 
Figure 3. Time Course of Response (Supportive Analysis)
DOI: 10.17632/f8mrgft82s.1
title: Research Including "Fake Data" and/or "Fake Information"

description: This dataset provides bibliographic entries in .bib format for studies mentioning "fake information" and/or "fake data". It covers research from 2005 onward, including metadata such as titles, abstract, authors, publication years, journal names, author keywords, index keywords, and DOIs (where available).

Key Features:
Scope: Studies addressing fake information and fake data.
Format: .bib file compatible with tools like Mendeley and Zotero.
Content: Includes metadata and notes on datasets used where applicable.
DOI: 10.17632/5ff8kcg3xj.1
title: Survey of Relationships between CFG’s Chinese Local Team’s Supporter and Manchester City & CFG

description: This is translated questionnaires of the research "The Effect of Manchester City and City Football Group (CFG)’s Glocalization Strategy: Exploring Multi-Club Ownership Models in Cultivating Relationships between CFG’s Chinese Local Team’s Supporter and Global Football Brands". Please remind that this is not original questionnaires, the original questionnaires in Chinese was published on other online survey platform.
DOI: 10.17632/5ff8kcg3xj.2
title: Survey of Relationships between CFG’s Chinese Local Team’s Supporter and Manchester City & CFG

description: This is translated questionnaires of the research "The effect of Manchester City and CFG’s glocalization strategy: fostering relationships between Chinese “glocal” supporters and global football brands". Please remind that this is not original questionnaires, the original questionnaires in Chinese was published on other online survey platform.
DOI: 10.17632/k5zvbmyddv.1
title: A Novel Resilience Measurement Model for Supply Chains Based on Risk Propagation

description: This dataset and code (python) are associated with the article "A Novel Resilience Measurement Model for Supply Chains Based on Risk Propagation".
DOI: 10.15468/dl.nc94rf
title: Occurrence Download

description: A dataset containing 377 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Pampus argenteus (Euphrasen, 1788)",
 "Geometry POLYGON((170 20, 170 50, 120 50, 120 20, 170 20))",
 "HasCoordinate is true"
 ]
}

 The dataset includes 377 records from 21 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004451-250123221155621/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.21227/w25x-n576
title: FedCNO

description: Smart contract vulnerability detection is a critical task in ensuring the security of blockchain systems. However, challenges such as non-public source code and label noise, especially systematic noise, significantly hinder the effectiveness of detection models.  This paper introduces FedCNO (Federated Contract Noise Optimizer), an innovative federated learning framework designed to address these issues. FedCNO uniquely integrates local and global label correction mechanisms to improve label accuracy while maintaining data privacy. Additionally, it introduces a consistency score method to dynamically adjust loss weights based on sample reliability, ensuring robust learning even in high-noise environments. Through these mechanisms, FedCNO effectively mitigates the impact of both random and systematic noise, demonstrating superior robustness and adaptability compared to existing approaches. Under 30\% random noise, FedCNO achieved an F1 score of 87.86\% on the CBGRU model. Under 30\% systematic noise, it achieved an F1 score of 72.59\%. In contrast, other baseline methods failed to improve the performance of detection models under systematic noise and even caused significant performance degradation. Experimental results demonstrate that FedCNO exhibits exceptional robustness in handling both random and systematic label noise, significantly outperforming state-of-the-art federated learning approaches.  Beyond noise correction, the framework promotes collaborative model optimization across distributed datasets without compromising sensitive information. Future work will further explore its applicability to diverse types of vulnerabilities and other blockchain security challenges.
DOI: 10.15468/dl.hctz44
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Stromateus echinogaster Basilewsky, 1855",
 "Geometry POLYGON((170 20, 170 50, 120 50, 120 20, 170 20))",
 "HasCoordinate is true"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004453-250123221155621/datasets/export for details.
DOI: 10.17632/mgdjk8n9k8.1
title: Measured and RT-based Air-to-Ground Channel Dataset (CIR) under Urban Scenarios

description: Air-to-ground (A2G) channels play a pivotal role in reliable communications between drone and ground terminal. A2G channel modeling is a hot topic, however there is little measurement data in real scenarios for model validation and comparison. 
 We have conducted channel measurements in urban scenario at the 3.6 GHz band with a bandwidth of 61.44 MHz. The antennas for both the Tx and Rx are replaced by dipole omnidirectional antennas. The street canyon is approximately 130 m in length and 15 m in width, surrounded by buildings ranging from 20 m to 44 m height. The ground Rx antenna is placed at a height of 2 m. 
 Instrucitons can also be found in the guidemanual_Measured and RT-based Channel Dataset (CIR) under Urban Scenarios.pdf. More details about the channel sounder and dataset can be found in the following references.
[1]. Kai Mao, Qiuming Zhu, et al., A Survey on Channel Sounding Technologies and Measurements for UAV-Assisted Communications. IEEE Transactions on Instrumentation and Measurement, 2024, Vol.73, pp.1-24.
[2]. Kai Mao, Qiuming Zhu, Yanheng Qiu, et al., A UAV-Aided Real-Time Channel Sounder for Highly Dynamic Non-Stationary A2G Scenarios. IEEE Transactions on Instrumentation and Measurement, 2023, 72:1-15.
[3]. Kai Mao, Qiuming Zhu, et al. Demo Abstract: A UAV-Based Real-Time Channel Knowledge Mapping System. IEEE International Conference on Computer Communication (INFOCOM), Vancouver, Canada, May, 2024, 1-2.
DOI: 10.17632/zd3vj49c3t.1
title: Revenue trend analysis - Brand Identity - Economics

description: Dataset Description: Revenue Trend Analysis (2020-2023)
Overview
This dataset provides a comprehensive analysis of revenue data over a three-year period, specifically from 2020 to 2022-2023. It includes revenue figures expressed in Indian Rupees (₹) and utilizes statistical methods to visualize trends and correlations within the data. The analysis employs linear regression to identify trends in revenue growth and generates visual representations through line plots and heatmaps.
Data Structure
The dataset consists of two main columns:
Year: This column indicates the fiscal years under consideration. The years are represented as strings, with the last year in the range specified for "2022-2023."
Revenue (₹ Crores): This column contains revenue figures formatted as strings, including currency symbols and commas.
Data Preparation
Cleaning Revenue Data:
The revenue values are cleaned by removing the currency symbol (₹) and commas, converting them into float data types for numerical analysis.
Handling Year Format:
The year data is processed to ensure consistency, particularly for the entry "2022-2023," which is converted to just "2023" for clarity in analysis.
Growth Rate Calculation:
A new column, "Growth Rate (%)", is added to represent the percentage change in revenue from one year to the next. This is calculated using the pct_change() method, which computes the percentage growth relative to the previous year's revenue.
Statistical Analysis
Linear Regression Model:
A linear regression model is fitted to the data to predict revenue based on the year. The model helps identify trends in revenue growth over time.
Predicted values are generated using the fitted model, which allows for comparison with actual revenue figures.
Visualizations
Revenue Trend Plot:
A line plot illustrates the actual revenue over the years alongside a trend line derived from the linear regression model.
The plot features:
Actual revenue points connected by lines (in blue).
A dashed red line representing the optimal trend line predicted by the linear regression model.
Axes labeled with appropriate titles and a grid for better readability.
Correlation Heatmap:
A heatmap visualizes the correlation between year, revenue, and growth rate metrics.
The correlation matrix is computed from the relevant columns, providing insights into how these variables relate to one another.
The heatmap uses a color gradient to represent correlation coefficients, with annotations indicating precise values.
Conclusion
This dataset serves as a valuable resource for analyzing revenue trends over a specified period while employing statistical methods to derive meaningful insights. By cleaning and processing the data effectively, applying linear regression for trend analysis, and visualizing results through plots and heatmaps, this analysis provides a clear understanding of revenue dynamics and growth patterns from 2020 to 2023.
DOI: 10.17632/74drmd922j.1
title: LOL RAW DATA

description: This dataset was collected to analyze and predict gamer churn in League of Legends (LOL) during Season 13. Data was obtained from the LOL Korea server via Riot Games' API and web scraping tools such as Selenium and Pandas. The raw dataset consists of 295,486 cases.
DOI: 10.17632/rmjdmx6bhp.1
title: Dataset supporting GCA submission

description: Supplementary Data S1 Mineral compositions, typical elemental concentrations and elemental ratios, Li-isotope data and typical chemical weathering indices for the clay-size fraction from core SE3 in the postglacial Qiantang River incised valley
DOI: 10.15468/dl.w8bg47
title: Occurrence Download

description: A dataset containing 193 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Icelus cataphractus (Pavlenko, 1910)",
 "Geometry POLYGON((170 20, 170 50, 120 50, 120 20, 170 20))",
 "HasCoordinate is true"
 ]
}

 The dataset includes 193 records from 8 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004455-250123221155621/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.34740/kaggle/dsv/10590946
title: ⏳ endoflife.date database (duckdb)
DOI: 10.17632/848tsfvzd5.2
title: Homologous recombination repair status in metastatic prostate cancer by next-generation sequencing and functional tissue-based immunofluorescence assays

description: NGS calls and RAD51 IF results for the Arce-Gallego et al, Cell Reports Medicine 2025.
DOI: 10.17632/b784h4dgsv.1
title: JAAD-D-24-02314

description: Supplemental Material
DOI: 10.17632/rmzzbs2dcx.1
title: The Chain Mediation Effect of Performance Expectancy and Perceived Value between College Students’ Perceived Social Influence and Usage Intention towards AI Language Partners

description: The Chain Mediation Effect of Performance Expectancy and Perceived Value between College Students’ Perceived Social Influence and Usage Intention towards AI Language Partners
DOI: 10.15468/dl.qajudg
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Agonocottus cataphractus Pavlenko, 1910",
 "Geometry POLYGON((170 20, 170 50, 120 50, 120 20, 170 20))",
 "HasCoordinate is true"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004457-250123221155621/datasets/export for details.
DOI: 10.17632/k5g548t5x6.1
title: Supplemental Material: Effectiveness and tolerability of ritlecitinib in children with alopecia areata: A case series

description: Supplementary table 1. Characteristics of alopecia areata patients treated with ritlecitinib
Supplementary figures (a, b, c). Clinical images of patients treated with ritlecitinib (figures a, b, and c correspond to patients 1, 2, and 9, respectively).
DOI: 10.15468/dl.7vt4nq
title: Occurrence Download

description: A dataset containing 50 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "StateProvince is one of (Vermont, New Hampshire, New York, Massachusetts, Rhode Island, Connecticut, Maine)",
 "TaxonKey is Strix nebulosa J.R.Forster, 1772"
 ]
}

 The dataset includes 50 records from 7 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004458-250123221155621/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/c4vfptbv77.1
title: Does Futures Market Information Improve Macroeconomic Forecasting: Evidence from China

description: Quarterly data on GDP growth rate, broken down by the three sectors (primary, secondary, and tertiary industries); Monthly data on PMI and PPI; Daily closing prices of commodity futures; Data of the CSI 300 stock index futures, including daily returns, trading volume, log trading volume, change in positions, basis, and amplitude.
DOI: 10.17632/bybj3gm6mb.1
title: Factors Influencing College Students’ Intention to Communicate with AI Language Partners in English Speaking Learning

description: Factors Influencing College Students’ Intention to Communicate with AI Language Partners in English Speaking Learning
DOI: 10.17632/vxxh5j8rv8.1
title: Aquatic Exercise at Elevated Water Temperatures Reduces Cognitive Impairment in Mice with Middle Cerebral Artery Occlusion-induced Ischemic Stroke: Suppression of Astrocyte- and Microglia-related Inflammatory Response

description: These data were used to write research papers and are not permitted to be used for commercial purposes.
DOI: 10.17632/wnshtnw276.1
title: Replication folder for the paper entitled "Penalized quadratic inference functions estimation of fixed effects partially linear varying coefficient spatial error model"

description: This replication folder provides the codes and data to replicate all the results of the paper entitled "Penalized quadratic inference functions estimation of fixed effects partially linear varying coefficient spatial error model". The zip file contains sub-folders, each containing the files to replicate the results in the different sections of the paper. The README.pdf file contains useful information on the replication folder. Please read it before using the replication folder. If you have any problems or questions, please contact lifen18459191151@126.com.
DOI: 10.17632/brktm9jpc6.1
title: Rice straw biochar application improves topsoil aggregate accumulation and rice uptake of phosphorus

description: Study on the effect of gradient biochar application on phosphorus in red paddy soil