cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/t9c3gsysn8.2
title: Microneedling-Assisted Delivery of Type III and Type XVII Collagen for Refractory Androgenetic Alopecia: A 24-Week Pilot Series

description: Supplementary Figure 1: A 52-year-old male with an 8-year history of androgenetic alopecia (AGA) had previously undergone a 3-year course of topical minoxidil and oral finasteride without significant improvement. He discontinued treatment and did not pursue further therapies until receiving a 24-week course of microneedling with type III collagen (COL3) and type XVII collagen (COL17). Serial photographs obtained at baseline, week 12, and week 24 demonstrated a marked improvement in hair density following treatment.
Supplementary Figure 2: A 51-year-old male with a 12-year history of androgenetic alopecia (AGA) underwent microneedling treatment with type III collagen (COL3) and type XVII collagen (COL17). Following 12 weeks of treatment, repigmentation of previously gray hair was observed, and newly grown hair exhibited pigmentation. Newly pigmented hairs are indicated within the dashed circles. (Scale bar = 2 mm.) 
Supplementary Figure 3: A 53-year-old male with a 5-year history of androgenetic alopecia (AGA) underwent a 24-week course of microneedling treatment with type III collagen (COL3) and type XVII collagen (COL17). Pre-treatment and post-treatment high-frequency ultrasound images demonstrate an increase in both superficial dermal (SD) and deep dermal (DD) thickness, with no apparent change in the epidermal layer (E). (Scale bar = 1 mm.)
Supplementary Table 1: Scalp layer thickness measured by high-frequency ultrasound.
Supplementary Table 2：Hair density measured by trichoscopy.
DOI: 10.15468/dl.xanvmt
title: Occurrence Download

description: A dataset containing 11211 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Guarea guidonia)",
 "HasCoordinate is true"
 ]
}

 The dataset includes 11211 records from 425 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0036755-250920141307145/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.6d2pbh
title: Occurrence Download

description: A dataset containing 12 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is one of (Material citation, Specimen)",
 "Country is Mexico",
 "OccurrenceStatus is Present",
 "TaxonKey is Passiflora prolata"
 ]
}

 The dataset includes 12 records from 5 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0036756-250920141307145/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.26023/wvy5-rha6-pv07
title: R/V Mirai LADCP Data: DYNAMO Legacy Collection. Version 1.0

description: This data set contains the water current profile data from the R/V Mirai LADCP (Lowered Acoustic Doppler Current Profiler) during its time on station at 8S and 80.5E for DYNAMO. The data are in NetCDF format.
DOI: 10.17632/s9zdjnrrhv
title: data and code

description: This dataset provides the data and code for the paper: "Central Bank Green Communication and Pollution Premium: Evidence from China." The study's central hypothesis is that green communication by a central bank leads to a "pollution premium," where investors demand higher expected returns as risk compensation for holding stocks of high-polluting firms. 
The data was gathered for A-share listed companies in China from Q1 2007 to Q4 2023, with firm-level financial, governance, and market data sourced from the CSMAR and RESSET databases. The core explanatory variable, the Central Bank Green Communication (DGC) index, was constructed through text analysis of the China Monetary Policy Implementation Reports issued by the People's Bank of China. This process involved creating a specialized Chinese green finance dictionary using machine learning algorithms (Word2Vec) and then quantifying the central bank's green focus by calculating the frequency of green-related terms. 
The data shows that stronger central bank green communication significantly increases the expected stock returns and lowers the valuation (e.g., price-to-earnings ratio) of high-polluting firms. Notable findings reveal that this effect is transmitted through three primary channels: increasing the risk exposure of polluting firms, tightening lending restrictions from commercial banks, and shifting investor preferences toward sustainability. 
The folder contains the main panel dataset for baseline regressions (data.dta), as well as specific datasets for the event study (eventsd.dta), Granger causality tests (granger.dta), and portfolio analysis (portfolio.dta). For a detailed description of all files and all variables, please refer to the README document (Readme.docx) included in the package. Researchers can use this data in conjunction with the provided Stata code file (code.do) to fully replicate all tables and figures presented in the manuscript, thereby verifying its conclusions. The data can also be used to test alternative model specifications or serve as a foundation for future research in green finance, central bank communication, and asset pricing.
DOI: 10.17632/s9zdjnrrhv.1
title: data and code

description: This dataset provides the data and code for the paper: "Central Bank Green Communication and Pollution Premium: Evidence from China." The study's central hypothesis is that green communication by a central bank leads to a "pollution premium," where investors demand higher expected returns as risk compensation for holding stocks of high-polluting firms. 
The data was gathered for A-share listed companies in China from Q1 2007 to Q4 2023, with firm-level financial, governance, and market data sourced from the CSMAR and RESSET databases. The core explanatory variable, the Central Bank Green Communication (DGC) index, was constructed through text analysis of the China Monetary Policy Implementation Reports issued by the People's Bank of China. This process involved creating a specialized Chinese green finance dictionary using machine learning algorithms (Word2Vec) and then quantifying the central bank's green focus by calculating the frequency of green-related terms. 
The data shows that stronger central bank green communication significantly increases the expected stock returns and lowers the valuation (e.g., price-to-earnings ratio) of high-polluting firms. Notable findings reveal that this effect is transmitted through three primary channels: increasing the risk exposure of polluting firms, tightening lending restrictions from commercial banks, and shifting investor preferences toward sustainability. 
The folder contains the main panel dataset for baseline regressions (data.dta), as well as specific datasets for the event study (eventsd.dta), Granger causality tests (granger.dta), and portfolio analysis (portfolio.dta). For a detailed description of all files and all variables, please refer to the README document (Readme.docx) included in the package. Researchers can use this data in conjunction with the provided Stata code file (code.do) to fully replicate all tables and figures presented in the manuscript, thereby verifying its conclusions. The data can also be used to test alternative model specifications or serve as a foundation for future research in green finance, central bank communication, and asset pricing.
DOI: 10.13140/rg.2.2.19297.98407
title: modelos.m
DOI: 10.17632/7p4fjr4h6w
title: A Dataset on Educational, Lifestyle, and Socioeconomic Factors of Bangladeshi Students (DELSFBS)

description: The DELSFBS dataset contains survey data on educational, lifestyle, and socioeconomic factors of 1,504 Bangladeshi students across diverse academic levels and institutions. It captures information on study habits, parental involvement, access to educational resources, extracurricular participation, physical activity, commuting distance, institution type, gender, family income, disability status, and academic performance (GPA for the last three years).

The dataset is organized into three files:

raw_responses.csv – Original survey responses with personally identifiable information (PII) removed.

cleaned_dataset.csv – Curated dataset of validated records (N=1,504) for analysis.

metadata.csv – Detailed variable-level metadata, including descriptions, data types, and allowed values.

File Format:
All files are in UTF-8 encoded CSV format with header rows. They can be imported into Python (Pandas), R, MATLAB, Excel, or other statistical and data analysis tools.

Usage Notes:

Use cleaned_dataset.csv for all analyses; raw_responses.csv is for reference.

Refer to metadata.csv to understand the meaning, type, and permissible values of each variable.

The dataset is self-reported; some responses may contain recall bias or reporting errors.

The sample primarily represents students from urban and semi-urban regions of Bangladesh and is not nationally representative.

Applications:
The DELSFBS dataset can be used for a variety of research and practical purposes, including:

Educational Research: Studying the impact of lifestyle, parental involvement, and access to resources on academic performance.

Behavioral Analysis: Examining patterns in sleep, physical activity, and extracurricular participation among students.

Socioeconomic Studies: Understanding the relationship between family income, commuting distance, and academic outcomes.

Policy Development: Informing evidence-based interventions to improve student well-being and learning outcomes.

Machine Learning and Data Science: Building predictive models for GPA or attendance, clustering student behavior, or feature analysis for educational datasets.

Citation:
Rahman, Anika; Khatun, Mst. Taskia; Hasan, Alfat Tasnim (2025), “A Dataset on Educational, Lifestyle, and Socioeconomic Factors of Bangladeshi Students (DELSFBS)”, Mendeley Data, V1, doi: 10.17632/7p4fjr4h6w.1

License:
CC BY 4.0 – allowing reuse with proper attribution.
DOI: 10.17632/7p4fjr4h6w.1
title: A Dataset on Educational, Lifestyle, and Socioeconomic Factors of Bangladeshi Students (DELSFBS)

description: The DELSFBS dataset contains survey data on educational, lifestyle, and socioeconomic factors of 1,504 Bangladeshi students across diverse academic levels and institutions. It captures information on study habits, parental involvement, access to educational resources, extracurricular participation, physical activity, commuting distance, institution type, gender, family income, disability status, and academic performance (GPA for the last three years).

The dataset is organized into three files:

raw_responses.csv – Original survey responses with personally identifiable information (PII) removed.

cleaned_dataset.csv – Curated dataset of validated records (N=1,504) for analysis.

metadata.csv – Detailed variable-level metadata, including descriptions, data types, and allowed values.

File Format:
All files are in UTF-8 encoded CSV format with header rows. They can be imported into Python (Pandas), R, MATLAB, Excel, or other statistical and data analysis tools.

Usage Notes:

Use cleaned_dataset.csv for all analyses; raw_responses.csv is for reference.

Refer to metadata.csv to understand the meaning, type, and permissible values of each variable.

The dataset is self-reported; some responses may contain recall bias or reporting errors.

The sample primarily represents students from urban and semi-urban regions of Bangladesh and is not nationally representative.

Applications:
The DELSFBS dataset can be used for a variety of research and practical purposes, including:

Educational Research: Studying the impact of lifestyle, parental involvement, and access to resources on academic performance.

Behavioral Analysis: Examining patterns in sleep, physical activity, and extracurricular participation among students.

Socioeconomic Studies: Understanding the relationship between family income, commuting distance, and academic outcomes.

Policy Development: Informing evidence-based interventions to improve student well-being and learning outcomes.

Machine Learning and Data Science: Building predictive models for GPA or attendance, clustering student behavior, or feature analysis for educational datasets.

Citation:
Rahman, Anika; Khatun, Mst. Taskia; Hasan, Alfat Tasnim (2025), “A Dataset on Educational, Lifestyle, and Socioeconomic Factors of Bangladeshi Students (DELSFBS)”, Mendeley Data, V1, doi: 10.17632/7p4fjr4h6w.1

License:
CC BY 4.0 – allowing reuse with proper attribution.
DOI: 10.7910/dvn/afiz0d
title: Low-Frequency Piezoresistive Accelerometer for Control Systems

description: The demand for compact and efficient accelerometers is growing exponentially because of their diverse applications in industries such as automotive, aerospace, consumer electronics, and healthcare. These small devices measure the force of acceleration, allowing the detection of motion, orientation and vibration. As technology advances, manufacturers are constantly striving to create smaller, more accurate accelerometers that can meet a wide variety of requirements. One of the problems associated with managing research tests of LPRE units involves obtaining accurate information about vibration modes, dynamic stability parameters, and dynamic overloads on nodes and power elements. The range of measurable acceleration is from 0±1 g to 0±10 g, and the frequency spectrum is 0–300 Hz. The internal error of the accelerometers must not exceed ±5%. This paper presents two designs of small-size accelerometers: the ultra-compact "SRAmicro" and the slightly larger, higher-accuracy "SRAHi−P re." Both accelerometers are designed to operate in frequency ranges of (0 ÷ 200) Hz and temperatures −50◦C − +180◦C. The SRAmicro model is ideal for applications with limited space, while the SRAHi−P re model offers higher accuracy for mission-critical applications. The paper discusses the structures, materials, and methods used to create and optimize these accelerometers. Experimental results indicate that the SRAHi−P re model, when combined with a thermal compensation circuit, significantly reduces the temperature sensitivity parameter (γ) and improves the overall performance of the device. These compact accelerometers have the potential to meet the increasing demands for diverse applications in various industries. (1985)
DOI: 10.17169/refubium-40027
title: Mikroklimatische Messungen im Berliner Stadtgebiet vom Institut für Meteorologie der Freien Universität Berlin des Jahres 2017
title: Microclimatic measurements in Berlin from the Institute of Meteorology, Freie Universität Berlin from 2017

description: The dataset contains 5 minute data of the Berlin stations from the FU Microclimate network (FUMiNET). This measurement network has been continuously built up since 2017 and is used for scale-dependent research of the urban climate of Berlin, which was funded by the 'Urban Climate under Change' Project (https://www.uc2-program.org/), BMBF. The stations reflect the urban structure and are located at sites which are typical of the Berlin urban area. The stations measure at a height of 2m the temperature and humidity. The data package contains data for the year 2017. For each of the stations there is a file with packed data in CSV format. In a full description contained in a pdf file, the locations are explicitly described.
description: Der Datensatz enthält Messwerte im fünf Minuten Takt des 'FU- Microclimate network' (FUMiNET) aus dem Berliner Stadtgebiet. Dieses Messnetz wurde kontinuierlich seit dem Jahr 2017 aufgebaut und dient der skalenübergreifenden Erfoschung des Stadtklimas von Berlin, welches durch das BMBF 'Stadtklima im Wandel Projektes' (https://www.uc2-program.org/) gefördert wurde. Die Stationen sind so aufgebaut, dass die Stadtstruktur von Berlin gut abgebildet wird. Gemessen wird die 2m Temperatur und Feuchte. Im Datenpaket sind die Daten des Jahres 2017 enthalten. Zu jeder der Stationen gibt es eine Datei mit gepackten Daten im CSV Format. In einer Gesamtbeschreibung als eine pdf Datei sind die Standorte expliziert beschrieben.
DOI: 10.13140/rg.2.2.31461.46560
title: 300 Views
DOI: 10.13140/rg.2.2.28106.02241
title: V Dimitrov & L Eppelbaum in 'People & Earth', Azerbaijan, Sept. 2025.pdf
DOI: 10.6084/m9.figshare.28039478
title: mixed_reality_stereo_vision_dataset

description: A study on the multimodal characterization of stereoscopic visual fatigue induced by mixed reality environments. Please refer to our GitHub repository in details.
DOI: 10.6084/m9.figshare.28039478.v3
title: mixed_reality_stereo_vision_dataset

description: A study on the multimodal characterization of stereoscopic visual fatigue induced by mixed reality environments. Please refer to our GitHub repository in details.
DOI: 10.6084/m9.figshare.28039478.v2
title: mixed_reality_stereo_vision_dataset

description: A study on the multimodal characterization of stereoscopic visual fatigue induced by mixed reality environments. Please refer to our GitHub repository in details.
DOI: 10.17169/refubium-40035
title: The Disaster Research Journals List 2023

description: The 2023 Disaster Research Journals (DRJ) list builds on the Disaster Research Journals Database (DRJD), which encompasses a curated list of journals dedicated to disaster research and science. The primary objective is to serve as a reliable resource for scholars, practitioners, and students navigating the vast and evolving landscape of disaster research literature. While the DRJ list and database can also assist researchers, professionals, and policymakers in identifying relevant publication outlets and consolidated sources of information in the field, they can be tools to track evolving trends and observe the development of the field, which has drastically expanded in the last decades. By August 2023, the DRJD contains 39 dimensions (or data points) for 111 journals. These data points range from basics such as ‘name’, ‘International Standard Serial Number (ISSN)’, ‘Uniform Resource Locator (URL)’, ‘publisher’, ‘country’, and ‘language’, to more specific details such as ‘short description’, ‘classification’, ‘COPE ethics guidelines’ signatory, ‘Open Access policy’, ‘Author Processing Charges (APC)’, ‘Copyrights’, ‘Turnaround times’, and ‘Periodicity’ (i.e., issues per year). Additionally, the database includes journal metrics like ‘Journal Impact Factor’, ‘CiteScore’, and ‘Google Scholar Metrics’.
DOI: 10.26023/k81b-nds1-sp0m
title: R/V Mirai SADCP Data: DYNAMO Legacy Collection. Version 1.0

description: This data set contains the water current profile data from the R/V Mirai SADCP (Shipborne Acoustic Doppler Current Profiler) during its cruise in the Indian Ocean for DYNAMO. The data are in NetCDF format.
DOI: 10.15468/dl.59n87x
title: Occurrence Download

description: A dataset containing 3 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is one of (Material citation, Specimen)",
 "Country is Mexico",
 "OccurrenceStatus is Present",
 "TaxonKey is Passiflora pusilla"
 ]
}

 The dataset includes 3 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0036758-250920141307145/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.mgy2kf
title: Occurrence Download

description: A dataset containing 143 species occurrences available in GBIF matching the query:
{
 "and" : [
 "DatasetKey is Strategic Plan for the Protection of Checkley Plain | Plan stratégique pour la protection de la plaine Checkley",
 "Geometry POLYGON((-66.57368 50.19779,-66.56068 50.19779,-66.56068 50.20605,-66.57368 50.20605,-66.57368 50.19779))"
 ]
}

 The dataset includes 143 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0036757-250920141307145/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.9nys6k
title: Occurrence Download

description: A dataset containing 26 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Hibiscus acetosella",
 "Country is Costa Rica",
 "HasCoordinate is true"
 ]
}

 The dataset includes 26 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0036759-250920141307145/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17169/refubium-40101
title: Protein nanobarcodes enable single-step multiplexed fluorescence imaging
title: Data corresponding to the Main and Supplementary Figures/Tables

description: Multiplexed cellular imaging typically relies on the sequential application of detection probes, as antibodies or DNA barcodes, which is complex and time-consuming. To address this, we developed here protein nanobarcodes, composed of combinations of epitopes recognized by specific sets of nanobodies. The nanobarcodes are read in a single imaging step, relying on nanobodies conjugated to distinct fluorophores, which enables a precise analysis of large numbers of protein combinations. Fluorescence images from nanobarcodes were used as input images for a deep neural network, which was able to identify proteins with high precision. We thus present an efficient and straightforward protein identification method, which is applicable to relatively complex biological assays. We demonstrate this by a multi-cell competition assay, in which we successfully used our nanobarcoded proteins together with neurexin and neuroligin isoforms, thereby testing the preferred binding combinations of multiple isoforms, in parallel.
DOI: 10.17632/hdkks6y2zr.1
title: Metabolic Rewiring by HIF1α/c-Jun-ENO2 Axis Undermines DC Function in Transarterial Embolization-Resistant HCC (Figure 1-7)

description: All data generated or analyzed during“Metabolic Rewiring by HIF1α/c-Jun-ENO2 Axis Undermines DC Function in Transarterial Embolization-Resistant HCC”
DOI: 10.15468/dl.rnst6g
title: Occurrence Download

description: A dataset containing 30 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((-3.193 40.533,-3.163 40.533,-3.163 40.563,-3.193 40.563,-3.193 40.533))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Plantae"
 ]
}

 The dataset includes 30 records from 10 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0036760-250920141307145/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.25573/data.30234610
title: Earth-Based 70-cm Wavelength Radar Maps of the Moon - 8-bit GEOTIFFS

description: This dataset contains Geo-TIFF files of 8-bit images that complement an archive of Earth-based, 70-cm wavelength, dual-polarization radar data collected using the Arecibo and Green Bank Telescopes between 2003 and 2009.The DOI for the primary archive is: https://doi.org/10.25573/data.26218523.v1Please use the suggested journal citations in that archive for credits related to publishing results based on the 8-bit Geo-TIFF files.<br>
DOI: 10.25573/data.30234610.v1
title: Earth-Based 70-cm Wavelength Radar Maps of the Moon - 8-bit GEOTIFFS

description: This dataset contains Geo-TIFF files of 8-bit images that complement an archive of Earth-based, 70-cm wavelength, dual-polarization radar data collected using the Arecibo and Green Bank Telescopes between 2003 and 2009.The DOI for the primary archive is: https://doi.org/10.25573/data.26218523.v1Please use the suggested journal citations in that archive for credits related to publishing results based on the 8-bit Geo-TIFF files.<br>
DOI: 10.17169/refubium-40231
title: Wikidata Research Articles Dataset

description: The "Wikidata Research Articles Dataset" comprises peer-reviewed full research papers about Wikidata from its first decade of existence (2012-2022). This dataset was curated to provide insights into the research focus of Wikidata, identify any gaps, and highlight the institutions actively involved in researching Wikidata.