cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.21227/cbek-p776
title: IEEEXtreme 11: Jarawi and The Interview

description: This dataset contains a total of 2355 submissions, with 5% correct solutions and 75% partial solutions. Link to the original challenge: https://csacademy.com/ieeextreme-practice/task/6f960361da7beb7f3a083f4776c2cf79/ See the included PDF document for details about the original challenge.
DOI: 10.7910/dvn/hkem3i
title: Survei angkatan kerja nasional (Sakernas)

description: Datasets for: 2015-2016,2018-2021
DOI: 10.12754/data-2024-0001
title: AUV based multibeam data for the publication Geersen et al. “A submerged Stone Age hunting architecture from the Western Baltic Sea”

description: Multibeam echosounder data collected with an AUV from the German Aerospace Centre (DLR). The AUV was deployed during FK Littorina cruise L0123 in 2023. The data has been gridded to 0.5 * 0.5 m resolution.
DOI: 10.21227/v3kw-qk57
title: IEEEXtreme 11: Quipu Function

description: This dataset contains a total of 13357 submissions, with 1% correct solutions and 10% partial solutions. Link to the original challenge: https://csacademy.com/ieeextreme-practice/task/5802db6cc4107baa3e135d06a31494b5/ See the included PDF document for details about the original challenge.
DOI: 10.5281/zenodo.10552214
title: Appendix 1 - Database of news and papers

description: Appendix 1 'Database of news and papers' for preprint : Large language models overcome the challenges of unstructured text data in ecology.

By: 

Andry Castro1; João Pinto2; Luís Reino3, 4, 5; Pavel Pipek6,7 César Capinha1,8*

 

1Centro de Estudos Geográficos, Instituto de Geografia e Ordenamento do Território, Universidade de Lisboa, Lisboa, Portugal.

2Global Health and Tropical Medicine, Instituto de Higiene e Medicina Tropical, Universidade Nova de Lisboa, Lisboa, Portugal.

3CIBIO, Centro de Investigação em Biodiversidade e Recursos Genéticos, InBIO Laboratório Associado, Campus de Vairão, Universidade do Porto, Vairão, Portugal.

4BIOPOLIS Program in Genomics, Biodiversity and Land Planning, CIBIO, Vairão, Portugal.

5CIBIO, Centro de Investigação em Biodiversidade e Recursos Genéticos, InBIO Laboratório Associado, Instituto Superior de Agronomia, Universidade de Lisboa, Lisboa, Portugal.

6Department of Invasion Ecology, Institute of Botany, Czech Academy of Sciences, Průhonice, Czech Republic.

7Department of Ecology, Faculty of Science, Charles University, Prague, Czech Republic.

8Associated Laboratory Terra, Portugal.

*Corresponding author.
DOI: 10.5281/zenodo.10552215
title: Appendix 1 - Database of news and papers

description: Appendix 1 'Database of news and papers' for preprint : Large language models overcome the challenges of unstructured text data in ecology.

By: 

Andry Castro1; João Pinto2; Luís Reino3, 4, 5; Pavel Pipek6,7 César Capinha1,8*

 

1Centro de Estudos Geográficos, Instituto de Geografia e Ordenamento do Território, Universidade de Lisboa, Lisboa, Portugal.

2Global Health and Tropical Medicine, Instituto de Higiene e Medicina Tropical, Universidade Nova de Lisboa, Lisboa, Portugal.

3CIBIO, Centro de Investigação em Biodiversidade e Recursos Genéticos, InBIO Laboratório Associado, Campus de Vairão, Universidade do Porto, Vairão, Portugal.

4BIOPOLIS Program in Genomics, Biodiversity and Land Planning, CIBIO, Vairão, Portugal.

5CIBIO, Centro de Investigação em Biodiversidade e Recursos Genéticos, InBIO Laboratório Associado, Instituto Superior de Agronomia, Universidade de Lisboa, Lisboa, Portugal.

6Department of Invasion Ecology, Institute of Botany, Czech Academy of Sciences, Průhonice, Czech Republic.

7Department of Ecology, Faculty of Science, Charles University, Prague, Czech Republic.

8Associated Laboratory Terra, Portugal.

*Corresponding author.
DOI: 10.6084/m9.figshare.25041806
title: Generating Rate Features for Mobile Applications

description: Replication package for the MobileSoft 2024 paper: Generating Rate Features for Mobile Applications
DOI: 10.6084/m9.figshare.25041806.v1
title: Generating Rate Features for Mobile Applications

description: Replication package for the MobileSoft 2024 paper: Generating Rate Features for Mobile Applications
DOI: 10.6084/m9.figshare.22126880
title: Umbrella review of musculoskeletal injury burden in dancers: implication for practice and research

description: Dancers are susceptible to injury. Nevertheless, injury epidemiology research in dancers is inconsistent. Furthermore, ballet dancing has dominated the huge body of reviews analyzing the epidemiology of musculoskeletal injuries in a variety of artistic dance forms, making it challenging to acquire a thorough, comprehensive, and understandable reporting of the available data. The overview and reanalysis of dancers’ musculoskeletal pain and injury load across artistic dance forms. Systematic review of systematic reviews and meta-analysis A search was conducted online for literature written in English using PubMed and Google Scholar (2012–2021). The data gathered was then analyzed using predetermined qualifying criteria. 12 reviews were determined to be qualified, the majority of which had moderate to low confidence and raised concerns about bias based on JBI-URARI and ROBIS. The prevalence of dance-related musculoskeletal injuries ranged from 26% to 84% in any artistic dancers and 42% to 343% in ballet dancers. The incidence was less than 5 per 1000 dance hours in both groups, with lower extremities and back being the commonly reported sites. Reviews themselves stated that the quality of the reviews was often poor. Due to the study’s heterogeneity and methodological inconsistency, data pooling and meta-analysis were not possible. The current review emphasizes the gaps and restrictions in the dance epidemiology literature that make it challenging to quantify and report a single overall injury rate for dancers. These results underline the need for better primary investigations and evidence synthesis. As injury epidemiology is a critical component of the overall injury-prevention puzzle, there is a need for standardization in future research, particularly with active and prospective injury surveillance, injury classification, injury evaluation, and injury reporting. Systematic Review, Level III
DOI: 10.6084/m9.figshare.22032722
title: Sex and gender differences in lower limb chronic exertional compartment syndrome: a systematic review

description: Chronic exertional compartment syndrome (CECS) is a cause of exertional leg pain and has been reported in varying frequencies in males and females. Currently, it is unclear whether there are significant sex and gender differences in lower-limb CECS. Delineating sex and gender differences is vital in determining the causes of CECS and best treatments. This systematic review aimed to determine the sex/gender distribution of CECS and to assess for sex and gender differences in CECS diagnosis and outcomes. PubMed (Medline), Cochrane Library, and EMBASE databases were searched for studies that were published from January 2000-March 2022 and reported lower-limb CECS data in males and/or females. Data on CECS diagnosis (intracompartmental pressures) and outcomes (e.g. post-surgical return-to-sport, need for re-operation) with sex/gender breakdowns were extracted. The sex/gender distribution of CECS and prevalence of CECS by sex/gender were calculated. Forty-one studies were included in the systematic review; there were 27 retrospective reviews, 8 prospective studies, and 6 retrospective studies with prospective follow-ups. Thirty studies involved surgical populations. Sex/gender distribution of CECS was calculated using data from 24 studies; 51% were female. Prevalence of CECS was available in five studies and ranged widely for males (54%-73%) and females (43%-65%). Intracompartmental pressure data varied by sex/gender. Male athletes were more likely than female athletes to return to sport following surgery for CECS, but variations in all other post-surgical outcomes were observed between sexes and genders in the general population. Females represented 51% of the patients who were diagnosed with CECS among studies. Most CECS diagnosis and outcomes data varied by sex/gender, except for post-surgical outcomes data in athletes, which demonstrated that males had higher rates of return to sport than females. Future studies are needed to examine factors contributing to sex and gender differences in CECS diagnosis and outcomes.
DOI: 10.6084/m9.figshare.22068273
title: Do five screening tools identify the same number of runners who require pre-exercise medical clearance? SAFER XXXIV

description: Currently, there are five international screening tools that are recommended to identify individuals who require pre-exercise medical clearance to reduce the risk of medical encounters during exercise. Therefore, the aim was to determine the percentage of race entrants who are advised to obtain pre-exercise medical clearance and the observed agreement between these five different international pre-exercise medical screening tools. In all, 76,654 race entrants from the Two Oceans Marathon (2012–2015) that completed an online pre-race screening questionnaire. Five pre-exercise medical screening tools (American Heart Association (AHA), pre-2015 American College of Sport Medicine (ACSM), post-2015 ACSM, Physical Activity Readiness Questionnaire (PAR-Q), and the European Association of Cardiovascular Prevention and Rehabilitation (EACPR)) were retrospectively applied to all participants. The % (95%CI) race entrants requiring medical clearance identified by each tool and the observed agreement between tools (%) was determined. The % entrants requiring medical clearance varied from 6.7% to 33.9% between the five tools: EACPR (33.9%; 33.5–34.3); pre-2015 ACSM (33.9%; 33.5–34.3); PAR-Q (23.2%; 22.9–23.6); AHA (10.0%; 9.7–10.2); post-2015 ACSM (6.7%; 6.5–6.9). The observed agreement was highest between the pre-2015 ACSM and EACPR (35.4%), for pre-2015 ACSM and PAR-Q (24.8%), PAR-Q and EACPR (24.8%), and lowest between the post-2015 ACSM and AHA (4.1%). The percentage of race entrants identified to seek medical clearance (and observed agreement) varied considerably between pre-exercise medical screening tools. Further research should determine which tool has the best predictive ability in identifying those at higher risk of medical encounters during exercise.
DOI: 10.6084/m9.figshare.22126880.v1
title: Umbrella review of musculoskeletal injury burden in dancers: implication for practice and research

description: Dancers are susceptible to injury. Nevertheless, injury epidemiology research in dancers is inconsistent. Furthermore, ballet dancing has dominated the huge body of reviews analyzing the epidemiology of musculoskeletal injuries in a variety of artistic dance forms, making it challenging to acquire a thorough, comprehensive, and understandable reporting of the available data. The overview and reanalysis of dancers’ musculoskeletal pain and injury load across artistic dance forms. Systematic review of systematic reviews and meta-analysis A search was conducted online for literature written in English using PubMed and Google Scholar (2012–2021). The data gathered was then analyzed using predetermined qualifying criteria. 12 reviews were determined to be qualified, the majority of which had moderate to low confidence and raised concerns about bias based on JBI-URARI and ROBIS. The prevalence of dance-related musculoskeletal injuries ranged from 26% to 84% in any artistic dancers and 42% to 343% in ballet dancers. The incidence was less than 5 per 1000 dance hours in both groups, with lower extremities and back being the commonly reported sites. Reviews themselves stated that the quality of the reviews was often poor. Due to the study’s heterogeneity and methodological inconsistency, data pooling and meta-analysis were not possible. The current review emphasizes the gaps and restrictions in the dance epidemiology literature that make it challenging to quantify and report a single overall injury rate for dancers. These results underline the need for better primary investigations and evidence synthesis. As injury epidemiology is a critical component of the overall injury-prevention puzzle, there is a need for standardization in future research, particularly with active and prospective injury surveillance, injury classification, injury evaluation, and injury reporting. Systematic Review, Level III
DOI: 10.6084/m9.figshare.22032722.v1
title: Sex and gender differences in lower limb chronic exertional compartment syndrome: a systematic review

description: Chronic exertional compartment syndrome (CECS) is a cause of exertional leg pain and has been reported in varying frequencies in males and females. Currently, it is unclear whether there are significant sex and gender differences in lower-limb CECS. Delineating sex and gender differences is vital in determining the causes of CECS and best treatments. This systematic review aimed to determine the sex/gender distribution of CECS and to assess for sex and gender differences in CECS diagnosis and outcomes. PubMed (Medline), Cochrane Library, and EMBASE databases were searched for studies that were published from January 2000-March 2022 and reported lower-limb CECS data in males and/or females. Data on CECS diagnosis (intracompartmental pressures) and outcomes (e.g. post-surgical return-to-sport, need for re-operation) with sex/gender breakdowns were extracted. The sex/gender distribution of CECS and prevalence of CECS by sex/gender were calculated. Forty-one studies were included in the systematic review; there were 27 retrospective reviews, 8 prospective studies, and 6 retrospective studies with prospective follow-ups. Thirty studies involved surgical populations. Sex/gender distribution of CECS was calculated using data from 24 studies; 51% were female. Prevalence of CECS was available in five studies and ranged widely for males (54%-73%) and females (43%-65%). Intracompartmental pressure data varied by sex/gender. Male athletes were more likely than female athletes to return to sport following surgery for CECS, but variations in all other post-surgical outcomes were observed between sexes and genders in the general population. Females represented 51% of the patients who were diagnosed with CECS among studies. Most CECS diagnosis and outcomes data varied by sex/gender, except for post-surgical outcomes data in athletes, which demonstrated that males had higher rates of return to sport than females. Future studies are needed to examine factors contributing to sex and gender differences in CECS diagnosis and outcomes.
DOI: 10.6084/m9.figshare.22068273.v1
title: Do five screening tools identify the same number of runners who require pre-exercise medical clearance? SAFER XXXIV

description: Currently, there are five international screening tools that are recommended to identify individuals who require pre-exercise medical clearance to reduce the risk of medical encounters during exercise. Therefore, the aim was to determine the percentage of race entrants who are advised to obtain pre-exercise medical clearance and the observed agreement between these five different international pre-exercise medical screening tools. In all, 76,654 race entrants from the Two Oceans Marathon (2012–2015) that completed an online pre-race screening questionnaire. Five pre-exercise medical screening tools (American Heart Association (AHA), pre-2015 American College of Sport Medicine (ACSM), post-2015 ACSM, Physical Activity Readiness Questionnaire (PAR-Q), and the European Association of Cardiovascular Prevention and Rehabilitation (EACPR)) were retrospectively applied to all participants. The % (95%CI) race entrants requiring medical clearance identified by each tool and the observed agreement between tools (%) was determined. The % entrants requiring medical clearance varied from 6.7% to 33.9% between the five tools: EACPR (33.9%; 33.5–34.3); pre-2015 ACSM (33.9%; 33.5–34.3); PAR-Q (23.2%; 22.9–23.6); AHA (10.0%; 9.7–10.2); post-2015 ACSM (6.7%; 6.5–6.9). The observed agreement was highest between the pre-2015 ACSM and EACPR (35.4%), for pre-2015 ACSM and PAR-Q (24.8%), PAR-Q and EACPR (24.8%), and lowest between the post-2015 ACSM and AHA (4.1%). The percentage of race entrants identified to seek medical clearance (and observed agreement) varied considerably between pre-exercise medical screening tools. Further research should determine which tool has the best predictive ability in identifying those at higher risk of medical encounters during exercise.
DOI: 10.26025/1912/67490
title: Long-term, quality-controlled observations of near-shore wind momentum and heat flux at the Martha’s Vineyard Coastal Observatory’s Air-Sea Interaction Tower

description: Quality-controlled atmospheric and oceanic observations of the wind momentum flux and heat flux in the surface layer above the ocean are provided based on data collected at Martha’s Vineyard Coastal Observatory (MVCO). The main dataset consists of wind speed, momentum flux, and heat flux observations made in 16 years over a 20 year period at measurement heights of 20 m above mean sea level. Ancillary data for comparison with bulk formula such as coare 3.5 (Edson et al. (2013)) include air temperature, relative humidity, air pressure, ocean surface temperature, ocean current speed, and solar radia- tion. MVCO is composed of three main elements, an Air-Sea Interaction Tower (ASIT, 3 km south of Martha’s Vineyard in 17-m water; Figure 1a), a Meteorological Mast (Met, 4 km northeast of ASIT), and an 12-m underwater node (UN, 1.6 km northeast of ASIT in 12-m water). The majority of the observations were collected at ASIT, while the ancillary data are from a combination of ASIT, Met, and UN.
DOI: 10.21227/t1sx-b585
title: IEEEXtreme11: Pyramid

description: This dataset contains a total of 2430 submissions, with 2% correct solutions and 12% partial solutions. Link to the original challenge: https://csacademy.com/ieeextreme-practice/task/5e98e4b17b3477e671568a437388fb7a/ See the included PDF document for details about the original challenge.
DOI: 10.5066/p91w7c1l
title: Digital elevation model of Mount St. Helens, Washington and vicinity prior to the 1980 eruption

description: On May 18, 1980, Mount St. Helens, Washington, exploded in a spectacular and devastating eruption that resulted in previously unimaginable events that drastically altered the mountain and the surrounding area. One unprecedented event was the collapse of the summit and north flank of the volcano forming a huge landslide known as the ‘debris avalanche’ with a total volume of about 2.5 km3 (3.3 billion cubic yards). The debris avalanche swept around and up ridges to the north, but most of it turned westward as far as 23 km (14 mi) down the valley of the North Fork Toutle River and formed a hummocky deposit. This had a profound effect on the topography of the area, including transforming the summit cone of the volcano into an amphitheater-shaped crater, in places, burying the valley north of the volcano under hundreds of feet of debris, and filling the Spirit Lake basin raising the surface elevation 64 m (210 ft). This release consists of a 10-meter resolution digital elevation model, covering an area of 196.45 sq km, and hillshade map of the summit and valley north of the volcano circa 1952 surface derived from contour lines digitized from historic topographic maps. These data represent the paleo topography of Mt St. Helens and vicinity that were most significantly altered by the 1980 eruption and debris avalanche.
DOI: 10.21227/nt0v-e634
title: IEEEXtreme 11: King Capture

description: This dataset contains a total of 1740 submissions, with 2% correct solutions and 79% partial solutions. Link to the original challenge: https://csacademy.com/ieeextreme-practice/task/cd05154d910e28e73ca3930e9a5103f5/ See the included PDF document for details about the original challenge.
DOI: 10.5281/zenodo.10515858
title: Securing Language Model-Based Code Generation: How Far Are We?

description: This is the replication of the paper "Securing Language Model-Based Code Generation: How Far Are We?"
DOI: 10.5281/zenodo.10515857
title: Fine Tuning Large Language Model for Secure Code Generation

description: This is the replication of the paper "Fine Tuning Large Language Model for Secure Code Generation"
DOI: 10.5281/zenodo.10520381
title: Securing Language Model-Based Code Generation: How Far Are We?

description: This is the replication of the paper "Securing Language Model-Based Code Generation: How Far Are We?"
DOI: 10.5281/zenodo.10521056
title: Fine Tuning Large Language Model for Secure Code Generation

description: This is the replication of the paper "Fine Tuning Large Language Model for Secure Code Generation"
DOI: 10.5281/zenodo.10521074
title: Fine Tuning Large Language Model for Secure Code Generation

description: This is the replication of the paper "Fine Tuning Large Language Model for Secure Code Generation"
DOI: 10.5281/zenodo.10521130
title: Fine Tuning Large Language Model for Secure Code Generation

description: This is the replication of the paper "Fine Tuning Large Language Model for Secure Code Generation"
DOI: 10.5281/zenodo.10552369
title: Fine Tuning Large Language Model for Secure Code Generation

description: This is the replication of the paper "Fine Tuning Large Language Model for Secure Code Generation"
DOI: 10.5281/zenodo.10552339
title: Appendix-2 Table A1 The schedule of nurses

description: Appendix 2 Table A1 The schedule of nurses
DOI: 10.5281/zenodo.7107022
title: Appendix The data in the base case

description: Appendix 1 The information on arrival and discharge for ED and elective patients Appendix 2 The real data of reported COVID-19 from March 1 to March 7 and April 27 to May 03, 2022, from Jilin province in China Appendix 3 The hospitalization information of the three types of patients in the base case
DOI: 10.21227/ac5e-ty14
title: IEEEXtreme 11: Preparing for Xtreme 12.0

description: This dataset contains a total of 2687 submissions, with 6% correct solutions and 63% partial solutions. Link to the original challenge: https://csacademy.com/ieeextreme-practice/task/72a7d67e7e18f4f7d033f7f5a5a09bef/ See the included PDF document for details about the original challenge.
DOI: 10.21227/d4rh-6m47
title: IEEEXtreme 11: Orienteering

description: This dataset contains a total of 1444 submissions, with 10% correct solutions and 34% partial solutions. Link to the original challenge: https://csacademy.com/ieeextreme-practice/task/95352fd33b0e855d337b5b3ed85da3b6/ See the included PDF document for details about the original challenge.
DOI: 10.17632/89g8yn75ch.2
title: Can community service grants foster social and economic integration for youth? A randomized trial in Kazakhstan

description: These are the replication files for the following paper:
Bhanot, S.P., Crost, B., Leight, J., Mvukiyehe, E. and Yedgenov, B., 2021. Can community service grants foster social and economic integration for youth? A randomized trial in Kazakhstan. Journal of Development Economics, 153, p.102718.
DOI: 10.5281/zenodo.10552258
title: Data for: Sustainable Exploitation of Biogas Plant Digestate for the Production of High-Quality Products Using Selective Electrodialysis
DOI: 10.5281/zenodo.10552257
title: Data for: Sustainable Exploitation of Biogas Plant Digestate for the Production of High-Quality Products Using Selective Electrodialysis
DOI: 10.5281/zenodo.10552234
title: Data for: Practical application of UVOX Redox® for pharmaceutical removal from liquid digestate in two biogas plants
DOI: 10.5281/zenodo.10552235
title: Data for: Practical application of UVOX Redox® for pharmaceutical removal from liquid digestate in two biogas plants
DOI: 10.5281/zenodo.10552166
title: Data for: Removal of contaminants of emerging concern from the supernatant of anaerobically digested sludge by O3 and O3/H2O2: Ozone requirements, effects of the matrix, and toxicity
DOI: 10.5281/zenodo.10552167
title: Data for: Removal of contaminants of emerging concern from the supernatant of anaerobically digested sludge by O3 and O3/H2O2: Ozone requirements, effects of the matrix, and toxicity