cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.5542727
title: Reproducible, high-dimensional imaging in archival human tissue by Multiplexed Ion Beam Imaging by Time-of-Flight (MIBI-TOF)

description: Single-channel MIBI-TOF images for Liu CC, Bosse M, et al. All folders are labeled as Slide[Number]Stain[Number]_Point[Number]_[TMACoreIndex], where the slide number and stain number correspond to the slide and day of staining, the point number corresponds to the order in which the images were collected for each slide, and the TMA core index corresponds to the ID of the tissue microarray core. Each folder contains single-channel TIFFs for each marker. See paper for details.
DOI: 10.57760/sciencedb.j00001.01153
title: CDCSL
title: CDCSL

description: The CDCSL contains meta-information on 26,036 Chinese papers, including title, author, abstract, keyword, author unit, funding information, publication, year of publication, and research field, from 18 Chinese core journals in six fields. After processing, each paper and author are numbered to obtain the final data set.The data set is stored in JSON format, where each record is meta-information about a paper, where:(1) paper_id is the number that uniquely identifies the paper.(2) title is the title in the paper information.(3) authors is author information, where author_id is the number that uniquely identifies the author, and name is the author's name.(4) organ is the name of the author's unit.(5) venue is the name of the publication in which the paper was published.(6) keyword is the keyword for the paper.(7) abstract is the abstract text of the paper.(8) year is the year in which the paper was published.(9) fund is the fund information of the paper.(10) field is the information of the field to which the paper belongs.Main field number and length statistics: Number of papers: 26036, number of authors: 79724, venue number: 18, field number: 6, keyword number: 63965, fund number: 49271, title average length: 23, abstract average length: 338
description: The CDCSL contains meta-information on 26,036 Chinese papers, including title, author, abstract, keyword, author unit, funding information, publication, year of publication, and research field, from 18 Chinese core journals in six fields. After processing, each paper and author are numbered to obtain the final data set.The data set is stored in JSON format, where each record is meta-information about a paper, where:(1) paper_id is the number that uniquely identifies the paper.(2) title is the title in the paper information.(3) authors is author information, where author_id is the number that uniquely identifies the author, and name is the author's name.(4) organ is the name of the author's unit.(5) venue is the name of the publication in which the paper was published.(6) keyword is the keyword for the paper.(7) abstract is the abstract text of the paper.(8) year is the year in which the paper was published.(9) fund is the fund information of the paper.(10) field is the information of the field to which the paper belongs.Main field number and length statistics: Number of papers: 26036, number of authors: 79724, venue number: 18, field number: 6, keyword number: 63965, fund number: 49271, title average length: 23, abstract average length: 338
DOI: 10.57760/sciencedb.o00009.00215
title: Spatial maps of MLP and CNN models from 03:00 to 04:00 UTC on August 10, 2019, over the Northwest Pacific region
title: Spatial maps of MLP and CNN models from 03:00 to 04:00 UTC on August 10, 2019, over the Northwest Pacific region

description: The results of precipitation retrieval using MLP and CNN models from 03:00 to 04:00 UTC on August 10, 2019, over the Northwest Pacific region.
description: The results of precipitation retrieval using MLP and CNN models from 03:00 to 04:00 UTC on August 10, 2019, over the Northwest Pacific region.
DOI: 10.5281/zenodo.3357224
title: The Intersection of Tibetan Buddhism & Western Psychology: A Cultural Immersion Study

description: Data Set used for qualitative research project re: Intersection of Buddhism and Western Psychology.<br> <br> Abstract: Western psychology has a long history of incorporating Buddhist practices and traditions into aspects of treatment, perhaps most predominantly the practice and theory of mindfulness (Bankart, 2003; Chan-Wiles, 2013; Dryden & Still, 2006; Kress, 1993; Rhys-Davids, 1924). This qualitative study critically examines the integration of Buddhism and psychology through the lived experiences of four clinical psychology doctoral students. These students attended a 9-day meditation retreat and seminar in France which involved the study of Tibetan Buddhism and how it integrates with Western psychology. The lived experience was captured through in vivo journaling, retrospective journaling, and interviews between the students. This material was then analyzed using the Consensual Qualitative Research (CQR) procedure outlined by Hill (2012), which incorporates phenomenological grounded theory and comprehensive process analysis (Hill et al., 2005). Four themes were identified: acceptance as an aspect of creating change, greater awareness for the concepts of Buddhism, Bodhicitta and the value of suffering, and integrating the experience and carrying it forward. The content of these themes is explored, along with implications for increased cultural sensitivity and clinical effectiveness in the implementation of mindfulness practices and other Tibetan Buddhist concepts in the practice of Western psychology.
description: data set including in vivo journaling, retrospective journaling, interview transcripts
DOI: 10.5281/zenodo.7668170
title: Juneau Alaska Invasive Plant Control Sites (2020-2022)

description: This dataset provides the location of invasive plant sites where herbicide was used to control reed canarygrass, Bohemian knotweed, European mountain ash, and European bird cherry that threaten salmon and steelhead habitat in the City and Borough of Juneau, Alaska (2020-2022).
DOI: 10.5281/zenodo.1200441
title: Raw

description: This is the system which uses raw speech .
DOI: 10.57760/sciencedb.space.00998
title: Transient photocurrent test and defect detection, TCAD simulation results
title: 瞬态光电流试验和缺陷检测、TCAD仿真结果

description: Using DLTS technology combined with TACD simulation experiments to detect defects in transient photocurrent test samples and explain the mechanism of current rise
description: Using DLTS technology combined with TACD simulation experiments to detect defects in transient photocurrent test samples and explain the mechanism of current rise
DOI: 10.5281/zenodo.3888543
title: Plant CME Methods - Raw Data

description: Raw data for figures
DOI: 10.5281/zenodo.4567527
title: DBLP Article Similarities (DBLP-ArtSim) dataset

description: This dataset contains similarity scores among articles in AMiner's DBLP v10 dataset. Similarities are calculated using the JoinSim [1] similarity measure on the derived citation network using the following metapaths: Paper - Author - Paper (PAP.csv.gz) Paper - Topic - Paper (PTP.csv.gz) Paper - Venue - Paper (PVP.csv.gz) The Paper to Venue relationships also also provided in PV_relationships.csv.gz. The file aminer_ids.csv.gz contains a mapping from AMiner's ids to our internal numeric ids used in the similarities files. [1] Xiong, Y., Zhu, Y., Yu, P.S.: Top-k similarity join in heterogeneous information networks. IEEE Transactions on Knowledge and Data Engineering 27(6), 1710– 1723 (2015)
description: We acknowledge support of this work by the project "Moving from Big Data Management to Data Science" (MIS 5002437/3) which is implemented under the Action "Reinforcement of the Research and Innovation Infrastructure", funded by the Operational Programme "Competitiveness, Entrepreneurship and Innovation" (NSRF 2014-2020) and co-financed by Greece and the European Union (European Regional Development Fund).
DOI: 10.5281/zenodo.6647203
title: iPPG2BP: excerpts taken from the test set

description: Excerpts taken from the test set. Use them to test the neural networks described in the orginal article (available here).
DOI: 10.57760/sciencedb.01928
title: A dataset of summer and winter fractional vegetation coverage in 32 provincial capital cities in China in 2021
title: 2000-2021年中国32个省会城市夏季与冬季植被覆盖度数据集

description: This data set is the summer and winter vegetation coverage image data of 32 provincial capitals in China from 2000 to 2021. The data format is * TIF format, the spatial resolution is 30 meters, and the coordinate system is WGS 1984 geographic coordinate system. Each pixel value of the image represents the vegetation coverage of the pixel, and the value range of vegetation coverage is between 0-1. The data set contains 22 compressed files, each named after the year, with a total size of 143 GB. The data set contains the distribution maps of vegetation coverage in summer and winter of 32 provincial capitals in China from 2000 to 2021, totaling 1190 pieces . The files are named by the combination of year, city name and season.
description: 本数据集为2000-2021年中国32个省会城市夏季与冬季植被覆盖度影像数据，数据格式为*.tif格式，空间分辨率为30米，坐标系为WGS 1984地理坐标系，影像的每个像元值即代表该像元的植被覆盖度，植被覆盖度的取值范围在0-1之间。数据集包含22个压缩文件，每个压缩文件以年份命名，压缩文件大小总计143 GB。该数据集包含2000-2021年中国32个省会城市夏季和冬季的植被覆盖度分布图，共计1190张。文件以年份、城市名称和季节的组合命名。
DOI: 10.5281/zenodo.239084
title: Processed Brats 2013 Hg Data

description: Real high grade glioma patient MRI data from the BraTS 2013 challenge with N3 bias field correction for T1, T1ce, T2, histogram-matched, normalized by mean CSF value and T1ce-T1 subtraction map as fifth channel. Data includes the following features for each of the 5 channels: Gaussian smoothing (0.7; 1.6), Gaussian gradient magnitude (0.7; 1.6), Laplacian of Gaussian (0.7; 1.6), 3 Hessian of Gaussian eigenvalues (0.7; 1.6), 3 structure tensor eigenvalues (0.7; 1.6). Format is HDF5, features along last axis.
DOI: 10.5281/zenodo.4108636
title: InaGeedicke/saltmarsh-invasion: First Release of code for saltmarsh invasion manuscript

description: This repository contains the code and data for our manuscript "Freshwater input drives invasion success of exotic plants in saltmarsh communities by Geedicke et al. It is accepted for the Journal Austral Ecology in 2020.
DOI: 10.57760/sciencedb.08372
title: Figure 2-3
title: Figure 2-3

description: Figure 2. Lung mean injury score. The lung injury score was determined following a five-point scale from 0 to 4 as follows: 0, 1, 2, 3, and 4 represent no damage, mild damage, moderate damage, severe damage, and very severe damage, respectively. Data was expressed as means ± SEM. n=5. **p&lt;0.01 vs the control group. #p&lt;0.05 vs the LPS group. Figure 3. Effects of OGE on LPS-induced proinflammatory cytokine secretion. The blood serum was collected to detect levels of proinflammatory cytokines by ELISA. Data was expressed as means ± SEM. n=5. *p&lt;0.05 vs the control group. #p&lt;0.05 vs the LPS group. 
description: Figure 2. Lung mean injury score. The lung injury score was determined following a five-point scale from 0 to 4 as follows: 0, 1, 2, 3, and 4 represent no damage, mild damage, moderate damage, severe damage, and very severe damage, respectively. Data was expressed as means ± SEM. n=5. **p&lt;0.01 vs the control group. #p&lt;0.05 vs the LPS group. Figure 3. Effects of OGE on LPS-induced proinflammatory cytokine secretion. The blood serum was collected to detect levels of proinflammatory cytokines by ELISA. Data was expressed as means ± SEM. n=5. *p&lt;0.05 vs the control group. #p&lt;0.05 vs the LPS group.
DOI: 10.6084/m9.figshare.28329411
title: Variable selection in linear regressions with possibly all strongly correlated covariates

description: Penalized regression methods, particularly LASSO, require the irrepresentable condition for variable selection consistency. This condition places an upper bound on the magnitudes of correlation between the signals and the rest of the covariates under consideration. Chudik, Kapetanios, and Pesaran (2018) proposed an alternative procedure called the one covariate at a time multiple testing (OCMT) that does not impose restrictions on the magnitude of these correlations. However, it requires that the number of covariates correlated with the signals grows at a rate less than the square root of the number of observations, denoted by <i>T</i>. Notably, the required conditions for both LASSO and OCMT can be challenged when possibly all the covariates under consideration are correlated with the signals. In this article, we follow the ideas from latent factor literature to adapt OCMT to allow for such scenarios. We refer to our proposed method as generalized one covariate at a time multiple testing (GOCMT). We establish that GOCMT selects a model that contains all the signals and none of the noise variables asymptotically. We also show that the least squares estimator of the post GOCMT selected model is T-consistent. The proposed method demonstrates promising finite-sample performance in our Monte Carlo experiments. An empirical application in risk factor selection within asset pricing further underscores the utility of our method.
DOI: 10.6084/m9.figshare.28329411.v1
title: Variable selection in linear regressions with possibly all strongly correlated covariates

description: Penalized regression methods, particularly LASSO, require the irrepresentable condition for variable selection consistency. This condition places an upper bound on the magnitudes of correlation between the signals and the rest of the covariates under consideration. Chudik, Kapetanios, and Pesaran (2018) proposed an alternative procedure called the one covariate at a time multiple testing (OCMT) that does not impose restrictions on the magnitude of these correlations. However, it requires that the number of covariates correlated with the signals grows at a rate less than the square root of the number of observations, denoted by <i>T</i>. Notably, the required conditions for both LASSO and OCMT can be challenged when possibly all the covariates under consideration are correlated with the signals. In this article, we follow the ideas from latent factor literature to adapt OCMT to allow for such scenarios. We refer to our proposed method as generalized one covariate at a time multiple testing (GOCMT). We establish that GOCMT selects a model that contains all the signals and none of the noise variables asymptotically. We also show that the least squares estimator of the post GOCMT selected model is T-consistent. The proposed method demonstrates promising finite-sample performance in our Monte Carlo experiments. An empirical application in risk factor selection within asset pricing further underscores the utility of our method.
DOI: 10.5281/zenodo.5834841
title: AI tutorial data

description: Preprocessing demo
DOI: 10.6084/m9.figshare.28326737
title: [WSESE] [Prompt Engineering in Data Analysis] Included and Excluded Papers

description: Context. The use of large language models for qualitative analysis is gaining attention in various fields, including software engineering, where qualitative methods are essential to understanding human and social factors. Goal. This study aimed to investigate how LLMs are currently used in qualitative analysis and how they can be used in software engineering research, focusing on identifying the benefits, limitations, and practices associated with their application. Method. We conducted a systematic mapping study and analyzed 21 relevant studies to explore reports of using LLM for qualitative analysis reported in the literature. Findings. Our findings indicate that LLMs are primarily used for tasks such as coding, thematic analysis, and data categorization, with benefits including increased efficiency and support for new researchers. However, limitations such as output variability, challenges capturing nuanced perspectives, and ethical concerns regarding privacy and transparency were also evident. Discussions. The study highlights the need for structured strategies and guidelines to optimize LLM use in qualitative research within software engineering. Such strategies could enhance the effectiveness of LLMs while addressing ethical considerations. Conclusion. While LLMs show promise for supporting qualitative analysis, human expertise remains essential for data interpretation, and continued exploration of best practices will be crucial for their effective integration into empirical software engineering research.
DOI: 10.6084/m9.figshare.28326737.v5
title: [WSESE] [Prompt Engineering in Data Analysis] Included and Excluded Papers

description: Context. The use of large language models for qualitative analysis is gaining attention in various fields, including software engineering, where qualitative methods are essential to understanding human and social factors. Goal. This study aimed to investigate how LLMs are currently used in qualitative analysis and how they can be used in software engineering research, focusing on identifying the benefits, limitations, and practices associated with their application. Method. We conducted a systematic mapping study and analyzed 21 relevant studies to explore reports of using LLM for qualitative analysis reported in the literature. Findings. Our findings indicate that LLMs are primarily used for tasks such as coding, thematic analysis, and data categorization, with benefits including increased efficiency and support for new researchers. However, limitations such as output variability, challenges capturing nuanced perspectives, and ethical concerns regarding privacy and transparency were also evident. Discussions. The study highlights the need for structured strategies and guidelines to optimize LLM use in qualitative research within software engineering. Such strategies could enhance the effectiveness of LLMs while addressing ethical considerations. Conclusion. While LLMs show promise for supporting qualitative analysis, human expertise remains essential for data interpretation, and continued exploration of best practices will be crucial for their effective integration into empirical software engineering research.
DOI: 10.15468/dl.ghfxzh
title: Occurrence Download

description: A dataset containing 863 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Specimen",
 "OccurrenceStatus is Present",
 "TaxonKey is Psittacanthus schiedeanus (Cham. & Schltdl.) G.Don"
 ]
}

 The dataset includes 863 records from 79 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007535-250127130748423/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.4633000
title: Evolution of Brightness and Color of the Night Sky in Madrid

description: Major schemes to replace other streetlight technologies with Light-Emitting Diode (LED) lamps are being undertaken across much of the world. This is predicted to have important consequences for nighttime sky brightness and color.
DOI: 10.5281/zenodo.4633001
title: Evolution of Brightness and Color of the Night Sky in Madrid

description: Major schemes to replace other streetlight technologies with Light-Emitting Diode (LED) lamps are being undertaken across much of the world. This is predicted to have important consequences for nighttime sky brightness and color.
DOI: 10.15468/dl.pthxws
title: Occurrence Download

description: A dataset containing 46362 species occurrences available in GBIF matching the query:
{
 "and" : [
 {
 "or" : [
 "Geometry POLYGON((-180 -90,180 -90,180 90,-180 90,-180 -90))",
 "Geometry POLYGON((-78.91942 -4.97296,-67.11936 -4.97296,-67.11936 12.39238,-78.91942 12.39238,-78.91942 -4.97296))"
 ]
 },
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Fuchsia L."
 ]
}

 The dataset includes 46362 records from 531 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007536-250127130748423/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.3886/e215382
title: RAPID: Media Exposure, Objective Knowledge, Risk Perceptions, and Risk Management Preferences of Americans Regarding the Novel Coronavirus Outbreak

description: Risk analysis has a long history of assessing the antecedents and
outcomes of public risk perceptions, and their mutual relationships, but has
emphasized cross-sectional rather than longitudinal studies as being more
feasible. However, cross-sectional studies not only fail to track the dynamics
of these factors and their relationships over time—which is particularly
crucial in understanding responses to a novel hazard such as that posed by the
COVID-19 pandemic—but they are unable to test even some basic hypotheses for
hazard management, such as whether a person with high risk perceptions at one
time is likely to have enacted protective behaviors at a later time, or that a
person who has adopted several protective behaviors at one time is likely to
have lower risk perceptions at a later time. This does not mean that
cross-sectional studies are useless, only that scholars of risk perceptions
should be doing what they can to increase the number of longitudinal studies
despite their logistical challenges.

<br><br>This project used a 6-wave U.S. longitudinal panel survey using
the Prolific online panel to test how views and behavior regarding personal and
collective solutions to what became an emerging pandemic (COVID-19) were
affected by various beliefs and attitudes, between persons and within persons
over time. This effort built upon both the Protective Action Decision Model
(e.g., by including stages of behavior change measures; new measures of threat
perception) and the researcher’s prior work (e.g., by generalizing temporal
trends across far more measures) to assess how people respond to unexpected
zoonoses (diseases that jump the species barrier) in a changing world, and why.
By collecting data at roughly two-month intervals between February 2020 (when
confirmed SARS-CoV-2 coronavirus infections in the U.S. were &lt; 50) and April
2021 (when many Americans had been vaccinated), this effort provided a dynamic
picture of both changing and unchanging views and reported behaviors and policy
support over 14 months.
description: Convenience sample
description: Smallest Geographic Unit: United States
description: web-based survey;
DOI: 10.15468/dl.k2ethm
title: Occurrence Download

description: A dataset containing 4222 species occurrences available in GBIF matching the query:
{
 "and" : [
 {
 "or" : [
 "PublishingCountry is Colombia",
 {
 "and" : [
 "Country is Colombia",
 {
 "not" : {
 "Issue" : [
 "is Country coordinate mismatch"
 ]
 }
 }
 ]
 }
 ]
 },
 "TaxonKey is one of (Alouatta seniculus (Linnaeus, 1766))"
 ]
}

 The dataset includes 4222 records from 204 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007538-250127130748423/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ftcn57
title: Occurrence Download

description: A dataset containing 535505 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is Insect Species Occurrence Data from Multiple Projects Worldwide with Focus on Bees and Wasps in North America"
 ]
}

 The dataset includes 535505 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007537-250127130748423/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.jxbute
title: Occurrence Download

description: A dataset containing 270 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Ariocarpus agavoides (Castañeda) E.F.Anderson"
 ]
}

 The dataset includes 270 records from 19 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007539-250127130748423/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.