cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.31078519.v1
title: Supplementary Material for: Changes in Health Care Utilization Patterns and Outcomes for an Acute Cerebrovascular Events Medicare Cohort, 2018—2022

description: Introduction: The Coronavirus 2019 (COVID-19) pandemic disrupted medical care delivery for cerebrovascular disease. Little is known about the long-term changes in health care utilization and mortality among people who suffered cerebrovascular events. 

Methods: We used 2018—2022 data to identify all Medicare fee-for-service (FFS) and Medicare Advantage (MA) beneficiaries with a diagnosis code for an acute cerebrovascular event (stroke, transient ischemic attack, hemorrhage). We used Poisson-lognormal regression models with an offset term (beneficiary years) to model incident rate ratios (IRR) for late-COVID (2021—2022) versus pre-COVID (2018—2019) for outpatient visits, emergency department (ED) visits, hospitalizations, and mortality in the year following the index event, adjusting for age, sex, and race. We examined patterns overall and by rurality (urban, micropolitan, rural) and quartile (q) of social vulnerability index (SVI).

Results: We identified 7,071,072 and 7,065,171 unique beneficiaries in the pre-COVID and late-COVID periods, respectively, with an acute cerebrovascular event. Our cohort was predominantly non-Hispanic White (73%), female (54%), and urban (83%). Compared to pre-COVID, outpatient care utilization in the year following the acute event was higher in 2021—2022 (IRR=1.14, 95% confidence interval [CI]: 1.13—1.14), while ED visits (IRR=0.92, 95% CI: 0.91—0.92) and inpatient hospitalizations (IRR=0.94, 95% CI: 0.94—0.95) were lower. Mortality was higher during the late-COVID versus pre-COVID period (IRR=1.24, 95% CI: 1.23—1.25). The mortality differences were similar across rural strata, but higher in more socially disadvantaged areas (IRR 1.20, 1.22, 1.24, 1.27 for q1 [reference], p-interaction= q2=0.12, q3=0.01, and q4&lt;0.001).

Conclusions: Medicare beneficiaries who sustained acute cerebrovascular events had marked differences over the subsequent year in healthcare utilization patterns and increased mortality in the late-COVID period compared with their utilization and outcomes pre-COVID. The differences in mortality were the most pronounced for beneficiaries in socially disadvantaged areas.
DOI: 10.6084/m9.figshare.31078522
title: Supplementary Material for: The Relationship between Cardiac Size and Shape Measurements and Cardiac Contractility in Intrauterine Growth Restricted Fetuses

description: Introduction: Fetal growth restriction (FGR) affects cardiac function and increases the risk of cardiac pathologies. We describe the relationship between cardiac contractility and cardiac size and shape in FGR and small-for-gestational age (SGA) fetuses to determine if ultrasound measurements can indicate functional cardiac sequelae. 
Methods: This prospective cohort study included fetuses with gestational ages of 23.0-39.0 weeks (FGR: n=55, SGA: n=40, appropriate for gestational age/AGA: n= 22). FGR was defined as fetuses with EFW &lt;10th centile and abnormal arterial doppler studies; SGA was defined as fetuses with EFW &lt;10th centile with normal doppler studies. Two-dimensional cardiac video clips of the 4-chamber view (4CV) were obtained for all fetuses and measurements of its size and shape were made. Speckle tracing measures of contractility were obtained as previously described. Individual size, shape, and speckle tracing measurements were compared by ANOVA between FGR, SGA, and appropriate for gestational age (AGA) groups. Comparisons by Mann Whitney U were used to compare a combined FGR+SGA group with the AGA group for all measurements. Abnormality was determined by simple count of values &gt;95th centile or &lt;5th centile based on predicted effect of FGR/SGA on each measurement. Frequency was binary, with a fetus assigned a 1 if they had any abnormal measurement, and 0 if not. Severity was determined by summing the abnormal measurements. Frequency and severity were determined independently for contractility versus size and shape and compared across groups using chi-squared and ANOVA respectively.
DOI: 10.6084/m9.figshare.31078522.v1
title: Supplementary Material for: The Relationship between Cardiac Size and Shape Measurements and Cardiac Contractility in Intrauterine Growth Restricted Fetuses

description: Introduction: Fetal growth restriction (FGR) affects cardiac function and increases the risk of cardiac pathologies. We describe the relationship between cardiac contractility and cardiac size and shape in FGR and small-for-gestational age (SGA) fetuses to determine if ultrasound measurements can indicate functional cardiac sequelae. 
Methods: This prospective cohort study included fetuses with gestational ages of 23.0-39.0 weeks (FGR: n=55, SGA: n=40, appropriate for gestational age/AGA: n= 22). FGR was defined as fetuses with EFW &lt;10th centile and abnormal arterial doppler studies; SGA was defined as fetuses with EFW &lt;10th centile with normal doppler studies. Two-dimensional cardiac video clips of the 4-chamber view (4CV) were obtained for all fetuses and measurements of its size and shape were made. Speckle tracing measures of contractility were obtained as previously described. Individual size, shape, and speckle tracing measurements were compared by ANOVA between FGR, SGA, and appropriate for gestational age (AGA) groups. Comparisons by Mann Whitney U were used to compare a combined FGR+SGA group with the AGA group for all measurements. Abnormality was determined by simple count of values &gt;95th centile or &lt;5th centile based on predicted effect of FGR/SGA on each measurement. Frequency was binary, with a fetus assigned a 1 if they had any abnormal measurement, and 0 if not. Severity was determined by summing the abnormal measurements. Frequency and severity were determined independently for contractility versus size and shape and compared across groups using chi-squared and ANOVA respectively.
DOI: 10.5281/zenodo.18267738
title: AYOLLARDA KARERA VA ONALIK O'RTASIDAGI PSIXOLOGIK MUVOZANAT

description: Ushbu ilmiy maqolada ayollarda karera va onalik o‘rtasida yuzaga keladigan psixologik muvozanatning shakllanish omillari, rol integratsiyasi va hissiy barqarorlik jarayonlari ilmiy tahlil qilinadi. Maqolada, ayollarning professional o‘sish bilan oilaviy majburiyatlarni uyg‘unlashtirishida psixologik moslashuvchanlik, ichki motivatsiya va ijtimoiy qo‘llab-quvvatlash tizimlarining ta’siri asoslab beriladi. Natijalar ushbu ikki rol o‘rtasidagi muvozanat ayolning ruhiy farovonligi, ijtimoiy faolligi va shaxsiy o‘sish dinamikasida hal qiluvchi determinant sifatida namoyon bo‘lishini ko‘rsatadi.
DOI: 10.5281/zenodo.18267739
title: AYOLLARDA KARERA VA ONALIK O'RTASIDAGI PSIXOLOGIK MUVOZANAT

description: Ushbu ilmiy maqolada ayollarda karera va onalik o‘rtasida yuzaga keladigan psixologik muvozanatning shakllanish omillari, rol integratsiyasi va hissiy barqarorlik jarayonlari ilmiy tahlil qilinadi. Maqolada, ayollarning professional o‘sish bilan oilaviy majburiyatlarni uyg‘unlashtirishida psixologik moslashuvchanlik, ichki motivatsiya va ijtimoiy qo‘llab-quvvatlash tizimlarining ta’siri asoslab beriladi. Natijalar ushbu ikki rol o‘rtasidagi muvozanat ayolning ruhiy farovonligi, ijtimoiy faolligi va shaxsiy o‘sish dinamikasida hal qiluvchi determinant sifatida namoyon bo‘lishini ko‘rsatadi.
DOI: 10.6084/m9.figshare.31078525
title: Supplementary Material for: Estimates of Global Needs for Neurorehabilitation: A Systematic Analysis Based on the GBD-WHO Rehabilitation Database 2021

description: Abstract
Background: Neurological disorders affect approximately 3.4 billion people worldwide and are the leading cause of disability. We conducted this study to explore global neurorehabilitation requirements and project trends from 2022 to 2036.
Methods: The data on health conditions that may benefit from neurorehabilitation were sourced from the World Health Organization Rehabilitation Need Estimator. Prevalence and years lived with disability (YLDs) of neurorehabilitation needs were analyzed overall and by sex, age, region, country, and health condition. Estimated annual percentage changes (EAPCs) were calculated to quantify trends in age-standardized rates. A decomposition analysis was conducted to identify drivers of changes in neurorehabilitation needs. Projections of neurorehabilitation needs were made until 2036 using Bayesian age–period–cohort analysis (BAPC).
Results: Globally, in 2021, neurological disorders requiring rehabilitation affected 225.38 million (95% UI 215.84–235.21) individuals, contributing to 52.35 million (95% UI 37.57–67.46) YLDs. The age-standardized prevalence rate (ASPR) and YLD rate (ASYR) were 2,758.37 (95% UI 2,644.02–2,878.23) and 640.5 (95% UI 459.39–824.44) per 100,000 persons, respectively. From 1990 to 2021, neurorehabilitation needs increased significantly, with prevalent cases and YLDs rising by 97.5% and 96.4%, respectively. This trend was reflected in a significant annual increase in both ASPR and ASYR, with an EAPC of 0.17 (95% CI 0.15–0.19) and 0.13 (95% CI 0.11–0.15), respectively, and is expected to continue increasing by 2036. Furthermore, decomposition analysis identified population growth and aging as the primary drivers of this increase. Most neurorehabilitation needs occur in low- and middle-income countries (LMICs). From 2021 to 2036, the highest contributors to the global need for neurorehabilitation will remain stroke, cerebral palsy, and Alzheimer's disease and dementia.
Conclusions: Our findings reveal a large and escalating global burden of neurological disorders requiring rehabilitation, driven by demographic aging and population growth. It is essential to expand rehabilitation services and integrate them into primary healthcare systems, particularly in LMICs.
DOI: 10.6084/m9.figshare.31078525.v1
title: Supplementary Material for: Estimates of Global Needs for Neurorehabilitation: A Systematic Analysis Based on the GBD-WHO Rehabilitation Database 2021

description: Abstract
Background: Neurological disorders affect approximately 3.4 billion people worldwide and are the leading cause of disability. We conducted this study to explore global neurorehabilitation requirements and project trends from 2022 to 2036.
Methods: The data on health conditions that may benefit from neurorehabilitation were sourced from the World Health Organization Rehabilitation Need Estimator. Prevalence and years lived with disability (YLDs) of neurorehabilitation needs were analyzed overall and by sex, age, region, country, and health condition. Estimated annual percentage changes (EAPCs) were calculated to quantify trends in age-standardized rates. A decomposition analysis was conducted to identify drivers of changes in neurorehabilitation needs. Projections of neurorehabilitation needs were made until 2036 using Bayesian age–period–cohort analysis (BAPC).
Results: Globally, in 2021, neurological disorders requiring rehabilitation affected 225.38 million (95% UI 215.84–235.21) individuals, contributing to 52.35 million (95% UI 37.57–67.46) YLDs. The age-standardized prevalence rate (ASPR) and YLD rate (ASYR) were 2,758.37 (95% UI 2,644.02–2,878.23) and 640.5 (95% UI 459.39–824.44) per 100,000 persons, respectively. From 1990 to 2021, neurorehabilitation needs increased significantly, with prevalent cases and YLDs rising by 97.5% and 96.4%, respectively. This trend was reflected in a significant annual increase in both ASPR and ASYR, with an EAPC of 0.17 (95% CI 0.15–0.19) and 0.13 (95% CI 0.11–0.15), respectively, and is expected to continue increasing by 2036. Furthermore, decomposition analysis identified population growth and aging as the primary drivers of this increase. Most neurorehabilitation needs occur in low- and middle-income countries (LMICs). From 2021 to 2036, the highest contributors to the global need for neurorehabilitation will remain stroke, cerebral palsy, and Alzheimer's disease and dementia.
Conclusions: Our findings reveal a large and escalating global burden of neurological disorders requiring rehabilitation, driven by demographic aging and population growth. It is essential to expand rehabilitation services and integrate them into primary healthcare systems, particularly in LMICs.
DOI: 10.15468/dl.9xag2w
title: Occurrence Download

description: A dataset containing 94405 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Harmonia axyridis",
 "Country is Germany",
 "HasCoordinate is true"
 ]
}

 The dataset includes 94405 records from 79 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0013926-260108223611665/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.6084/m9.figshare.30857972
title: Blockchain Attack Incidents

description: This dataset provides a comprehensive collection of documented security attacks and vulnerabilities within the blockchain ecosystem. It covers various types of exploits, including smart contract vulnerabilities, protocol-level attacks, and bridge exploits. It is designed for security researchers, data scientists, and blockchain developers to analyze historical attack patterns and improve decentralized system security.
DOI: 10.6084/m9.figshare.30857972.v1
title: Blockchain Attack Incidents

description: This dataset provides a comprehensive collection of documented security attacks and vulnerabilities within the blockchain ecosystem. It covers various types of exploits, including smart contract vulnerabilities, protocol-level attacks, and bridge exploits. It is designed for security researchers, data scientists, and blockchain developers to analyze historical attack patterns and improve decentralized system security.
DOI: 10.5281/zenodo.15838221
title: R Code for Symptom Word Frequency Analysis and Word Cloud Visualization

description:
DOI: 10.5281/zenodo.17351624
title: R Code for Symptom Word Frequency Analysis and Word Cloud Visualization

description:
DOI: 10.15468/dl.x5awx9
title: Occurrence Download

description: A dataset containing 24353 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Ageratum houstonianum"
 ]
}

 The dataset includes 24353 records from 357 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0013942-260108223611665/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.77z69f
title: Occurrence Download

description: A dataset containing 41 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Portugal",
 "DatasetKey is Marine biodiversity of the Southwest Alentejo and Costa Vicentina Natural Park (Project MARSW)",
 "TaxonKey is one of (Laminaria, Laminariaceae, Phyllariopsis, Phyllariopsis brevipes)"
 ]
}

 The dataset includes 41 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0013943-260108223611665/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.yy2gkd
title: Occurrence Download

description: A dataset containing 109111 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Harmonia axyridis",
 "Country is Belgium",
 "HasCoordinate is true"
 ]
}

 The dataset includes 109111 records from 21 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0013921-260108223611665/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.18267758
title: TA'LIM SIFATINI BOSHQARISHDA SUN'IY INTELLEKT TEXNOLOGIYALARINING QO'LLANILISHI

description: Mazkur maqolada ta’lim sifatini boshqarishda sun’iy intellekt texnologiyalarining qo‘llanishi, ularning imkoniyatlari va amaliy samaradorligi ilmiy asosda tahlil qilingan. Sun’iy intellekt vositalari ta’lim jarayonida yig‘iladigan katta hajmdagi ma’lumotlarni qayta ishlash, o‘quvchilarning o‘zlashtirish ko‘rsatkichlarini monitoring qilish, pedagogik faoliyatni baholash va boshqaruv qarorlarini optimallashtirishda qanday rol o‘ynashi izohlangan. Shuningdek, shaxsiylashtirilgan ta’lim, xolis baholash, ta’lim jarayonida yuzaga keladigan xatolarni avtomatik aniqlash kabi yo‘nalishlarda sun’iy intellektning afzalliklari yoritilgan. Tadqiqot natijalari sun’iy intellektning ta’lim sifatini barqaror oshirish va raqamli boshqaruv madaniyatini shakllantirishdagi muhim ahamiyatini ko‘rsatadi.
DOI: 10.5281/zenodo.18267759
title: TA'LIM SIFATINI BOSHQARISHDA SUN'IY INTELLEKT TEXNOLOGIYALARINING QO'LLANILISHI

description: Mazkur maqolada ta’lim sifatini boshqarishda sun’iy intellekt texnologiyalarining qo‘llanishi, ularning imkoniyatlari va amaliy samaradorligi ilmiy asosda tahlil qilingan. Sun’iy intellekt vositalari ta’lim jarayonida yig‘iladigan katta hajmdagi ma’lumotlarni qayta ishlash, o‘quvchilarning o‘zlashtirish ko‘rsatkichlarini monitoring qilish, pedagogik faoliyatni baholash va boshqaruv qarorlarini optimallashtirishda qanday rol o‘ynashi izohlangan. Shuningdek, shaxsiylashtirilgan ta’lim, xolis baholash, ta’lim jarayonida yuzaga keladigan xatolarni avtomatik aniqlash kabi yo‘nalishlarda sun’iy intellektning afzalliklari yoritilgan. Tadqiqot natijalari sun’iy intellektning ta’lim sifatini barqaror oshirish va raqamli boshqaruv madaniyatini shakllantirishdagi muhim ahamiyatini ko‘rsatadi.
DOI: 10.15468/dl.ew92ub
title: Occurrence Download

description: A dataset containing 32759 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Ageratum conyzoides"
 ]
}

 The dataset includes 32759 records from 685 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0013941-260108223611665/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.5tfvjt
title: Occurrence Download

description: A dataset containing 10 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Human Observation",
 "Continent is Asia",
 "Country is India",
 "GadmGid is IND.16.3_1",
 "Month is one of (December, November, October, September, August, July, June, May, April, March, February, January)",
 "OccurrenceStatus is Present",
 "TaxonKey is Pelecanus philippensis Gmelin, 1789",
 "Year is 2011"
 ]
}

 The dataset includes 10 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0011680-250515123054153/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.u3quvy
title: Occurrence Download

description: A dataset containing 393172 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Rana dalmatina Bonaparte, 1840, Coronella austriaca Kristan, 1957, Papilio machaon Schwalbenschwanz, Anser anser (Linnaeus, 1758))",
 "Year is not null",
 "Year is one of (2014, 2015, 2016, 2017, 2018, 2019, 2020, 2021, 2022, 2023, 2024)",
 "HasCoordinate is TRUE",
 "DecimalLatitude is greater than or equal to 47.3024876979",
 "DecimalLatitude is less than or equal to 54.983104153",
 "DecimalLongitude is greater than or equal to 5.98865807458",
 "DecimalLongitude is less than or equal to 15.0169958839",
 "OccurrenceStatus is Present",
 "HasGeospatialIssue is FALSE"
 ]
}

 The dataset includes 393172 records from 70 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0011664-250515123054153/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.15442938
title: How Influencers and Multipliers Drive Polarization and Issue Alignment on Twitter/X - Data

description: Description

We provide anonymized retweet networks extracted from trending topics in Germany collected between 2021 to 2023. 

More specifically, we collected tweets from 2021-03-29 to 2023-07-12 according to the following scheme: at the beginning of each day, we launched a script that collects the current "trending topics" (from now on referred to as "trends") in Germany using the Twitter Trend API (v1). By default, trends are personalized based on the account's Twitter/X usage. One can, however, disable the personalization by setting a specific location from which to draw the trending topics, which then yields "popular topics among people in a specific geographic location" (X/Twitter2025). We re-ran the script every 15 minutes. At the end of each day, we counted the number of times each trending topic appeared during the day and kept the top 5 most frequent ones. This gave us a proxy of the five most important trending topics for that day. We then used the Twitter Search API (v1) to collect German-speaking tweets using the exact trend keyword as a query on the day it trended and the day after (48hrs). All the tweets were collected using a single Twitter API key, collecting tweets for maximally 24 hours every day. 

For each trend, we extract a retweet network, in which nodes are Twitter users and a directed link is drawn from user $i$ to $j$ if $i$ retweets $j$. We provide one retweet network for each trend as a csv after anonymizing the user_ids. There is one csv for each trend containing the columns source,target,weight. The filename contains the date and the keyword that was searched:

T<trend_idx>_<date>_<search_query>.csv

All the individual files are contained in rtn.zip.

Additionally, we computed a topic model on the full text of tweets which allowed us to classify each trend into one larger metatopic (such as Covid, Climate Change, Sports, ...). This topic assignment is contained in trend2topic.csv. For more information on the topic model, please refer to the paper [insert link here].

How to cite

If you use this data, please cite:

Pournaki, A., F. Gaisbauer, and E. Olbrich. "How Influencers and Multipliers Drive Polarization and Issue Alignment on Twitter/X." Proceedings of the International AAAI Conference on Web and Social Media. Vol. 19. 2025.