cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.19078064
title: Data_final.sav

description: Among the general population, it is known that low education is associated with poorer health and external and fatalistic control beliefs. Relationships between education, quality of life, and control beliefs in cancer patients remain unclear. In this cross-sectional study, 605 cancer patients from two German cancer registries were analyzed. We used the EORTC QLQ-C30 questionnaire to measure quality of life and the IPC questionannire to assess control beliefs. <br>
DOI: 10.6084/m9.figshare.19078067
title: Dataset and replication files for "Frustrated Aspirations and Different Types of Political Violence: Evidence from 'Folk Knowledge' in Kosovo"

description: Dataset and replication files for "Frustrated Aspirations and Different Types of Political Violence: Evidence from 'Folk Knowledge' in Kosovo"
DOI: 10.6084/m9.figshare.19078067.v2
title: Dataset and replication files for "Frustrated Aspirations and Different Types of Political Violence: Evidence from 'Folk Knowledge' in Kosovo"

description: Dataset and replication files for "Frustrated Aspirations and Different Types of Political Violence: Evidence from 'Folk Knowledge' in Kosovo"
DOI: 10.6084/m9.figshare.19078067.v1
title: Untitled Item

description: Dataset and replication files for "Frustrated Aspirations and Different Types of Political Violence: Evidence from 'Folk Knowledge' in Kosovo"
DOI: 10.6084/m9.figshare.19078058
title: DWF4 files

description: Data was collected on individual plants in a random block design. individual files which where used for specific figures are listed in the README file
DOI: 10.6084/m9.figshare.19078058.v1
title: DWF4 files

description: Data was collected on individual plants in a random block design. individual files which where used for specific figures are listed in the README file
DOI: 10.5281/zenodo.5911185
title: The station-based error information of monthly snow depth, precipitation and air temperature for CMIP6 models in mainland China

description: This dataset contains the data of monthly snow depth in terms of RMSD (cm), spatial correlation (R<sub>s</sub>), temporal correlation (R<sub>t</sub>), consistency index (CI), and Hotspot score (H-score) of the 305 weather stations in China used for evaluating the snow depth simulated or estimated from 31 CMIP6 models, MERRA2 reanalysis and a remte sensing snow depth dataset (Che). It also includes the data of errors and accumulated errors of monthly precipitation (mm) and air temperature (℃) from the 305 stations of all the 31 CMIP6 models, which can be used for constructing the regression models for analyzing error sources of snow depth simulations.
DOI: 10.5281/zenodo.5911174
title: Dataset related to article "Long-term outcomes after pancreatoduodenectomy for ampullary cancer: The influence of the histological subtypes and comparison with the other periampullary neoplasms"

description: This record contains data related to article "Long-term outcomes after pancreatoduodenectomy for ampullary cancer: The influence of the histological subtypes and comparison with the other periampullary neoplasms" <strong>Background. </strong>Ampullary carcinoma (AC) is histologically classified as intestinal (In-AC), pancreaticobiliary (Pb-AC) or mixed-AC. The prognostic role of AC subtypes has been debated and remains unclear. The aims of this study were to evaluate outcomes after pancreatoduodenectomy (PD) for each subtype of AC and to compare these with pancreatic ductal adenocarcinoma [PDAC] and distal cholangiocarcinoma [DCC]. <strong>Methods. </strong>PDs performed for AC between 2010-2018 were retrospectively evaluated. Histological subtype was obtained for all patients. One-year, 3-year and 5-year disease-free-survival (DFS) and overall survival (OS) rates were calculated. Kaplan-Meier survival analysis was performed to compare Pb-AC, In-AC and mixed-AC. Comparison with PDs performed for PDAC and DCC during the same period was also performed. <strong>Results. </strong>A total of 97 patients undergoing PD for AC were evaluated: 34 (35.1%) In-AC, 54 (55.7%) Pb-AC and 9 mixed-AC (9.3%). DFS and OS rates for Pb-AC were significantly lower compared to In-AC (p&lt;0.05 and p&lt;0.01), but similar to mixed-AC (p=0.3 and p=0.4). Adjuvant therapy was not associated with increased survival, regardless of the histological subtype (p&gt;0.05). During the same period, 337 and 53 PDs for PDAC and DCC, respectively, were performed. In-AC was associated with significantly better outcomes compared to PDAC and DCC (p&lt;0.001); DFS and OS rates for Pb-AC and mixed AC were significantly higher compared to PDAC (p&lt;0.001), but similar to DCC (p&gt;0.05). <strong>Conclusions. </strong>Pb-AC has significantly worse survival compared to In-AC. Moreover, mixed-AC should be considered as Pb-AC. Pb-AC and mixed-AC seem to have better prognosis compared to PDAC, but similar to DCC.
DOI: 10.5281/zenodo.5911173
title: Dataset related to article "Long-term outcomes after pancreatoduodenectomy for ampullary cancer: The influence of the histological subtypes and comparison with the other periampullary neoplasms"

description: This record contains data related to article "Long-term outcomes after pancreatoduodenectomy for ampullary cancer: The influence of the histological subtypes and comparison with the other periampullary neoplasms" <strong>Background. </strong>Ampullary carcinoma (AC) is histologically classified as intestinal (In-AC), pancreaticobiliary (Pb-AC) or mixed-AC. The prognostic role of AC subtypes has been debated and remains unclear. The aims of this study were to evaluate outcomes after pancreatoduodenectomy (PD) for each subtype of AC and to compare these with pancreatic ductal adenocarcinoma [PDAC] and distal cholangiocarcinoma [DCC]. <strong>Methods. </strong>PDs performed for AC between 2010-2018 were retrospectively evaluated. Histological subtype was obtained for all patients. One-year, 3-year and 5-year disease-free-survival (DFS) and overall survival (OS) rates were calculated. Kaplan-Meier survival analysis was performed to compare Pb-AC, In-AC and mixed-AC. Comparison with PDs performed for PDAC and DCC during the same period was also performed. <strong>Results. </strong>A total of 97 patients undergoing PD for AC were evaluated: 34 (35.1%) In-AC, 54 (55.7%) Pb-AC and 9 mixed-AC (9.3%). DFS and OS rates for Pb-AC were significantly lower compared to In-AC (p&lt;0.05 and p&lt;0.01), but similar to mixed-AC (p=0.3 and p=0.4). Adjuvant therapy was not associated with increased survival, regardless of the histological subtype (p&gt;0.05). During the same period, 337 and 53 PDs for PDAC and DCC, respectively, were performed. In-AC was associated with significantly better outcomes compared to PDAC and DCC (p&lt;0.001); DFS and OS rates for Pb-AC and mixed AC were significantly higher compared to PDAC (p&lt;0.001), but similar to DCC (p&gt;0.05). <strong>Conclusions. </strong>Pb-AC has significantly worse survival compared to In-AC. Moreover, mixed-AC should be considered as Pb-AC. Pb-AC and mixed-AC seem to have better prognosis compared to PDAC, but similar to DCC.
DOI: 10.6084/m9.figshare.13464586.v1
title: Twelve tips to make successful medical infographics

description: In the health sciences, professionals must keep up to date to conduct their evidence-based practise. Hence, there is a growing need to share medical knowledge efficiently among healthcare professionals, patients, and undergraduate health science students. Infographics (text and image) are a hybrid element that serves to represent information in an attractive and meaningful visual format. Actually, with the use of the Internet and social networks, infographics have become a popular format for sharing medical information around the world. On the basis of a published literature review, we provide 12 tips in this article to make a successfully health-related infographic with the aim of assisting clinicians, educators, and researchers in their task of communicating and transforming complex information into a visual, attractive, didactic and shareable format. By following these basic recommendations, it is possible to improve the dissemination of scientific and health-related knowledge to different audiences who can benefit from infographics.
DOI: 10.6084/m9.figshare.13464586
title: Twelve tips to make successful medical infographics

description: In the health sciences, professionals must keep up to date to conduct their evidence-based practise. Hence, there is a growing need to share medical knowledge efficiently among healthcare professionals, patients, and undergraduate health science students. Infographics (text and image) are a hybrid element that serves to represent information in an attractive and meaningful visual format. Actually, with the use of the Internet and social networks, infographics have become a popular format for sharing medical information around the world. On the basis of a published literature review, we provide 12 tips in this article to make a successfully health-related infographic with the aim of assisting clinicians, educators, and researchers in their task of communicating and transforming complex information into a visual, attractive, didactic and shareable format. By following these basic recommendations, it is possible to improve the dissemination of scientific and health-related knowledge to different audiences who can benefit from infographics.
DOI: 10.6084/m9.figshare.14983820.v1
title: Communication content during debriefing in simulation-based medical education: An analytic framework and mixed-methods analysis

description: Debriefing is an indispensable component of simulation-based medical education, and it has great potential for contributions to reflective learning. Little is known about the relevance of communication during debriefings. We developed a category framework to assess the communication content of debriefings, which we used to analyze possible relationships to participant learning outcomes. We deductively and inductively developed a category framework for qualitative content analysis of debriefings. We coded 20 debriefings using this framework, and correlated debriefing frequency with learning outcomes (i.e. engagement, satisfaction, individual and team learning success). The category framework comprised 9 main and 81 subcategories (48 debriefers, 27 participants, 6 simulated patients), which yielded good intercoder agreement. Debriefers and participants communicated equally using mostly advocacy, inquiry, illustration, and confirmation. Debriefer questions and participant inputs were positively related to learning outcomes. In contrast, guess-what-I-am-thinking, apologies, observations, use of materials, participant descriptions, simple repetition of statements, and evaluation by other participants were not positively associated with learning outcomes. This study provides important new information about communication content during debriefings. The association between communication content and learning outcomes appears particularly relevant to further enhance efficacy of debriefings and simulation-based medical education.
DOI: 10.6084/m9.figshare.14983820
title: Communication content during debriefing in simulation-based medical education: An analytic framework and mixed-methods analysis

description: Debriefing is an indispensable component of simulation-based medical education, and it has great potential for contributions to reflective learning. Little is known about the relevance of communication during debriefings. We developed a category framework to assess the communication content of debriefings, which we used to analyze possible relationships to participant learning outcomes. We deductively and inductively developed a category framework for qualitative content analysis of debriefings. We coded 20 debriefings using this framework, and correlated debriefing frequency with learning outcomes (i.e. engagement, satisfaction, individual and team learning success). The category framework comprised 9 main and 81 subcategories (48 debriefers, 27 participants, 6 simulated patients), which yielded good intercoder agreement. Debriefers and participants communicated equally using mostly advocacy, inquiry, illustration, and confirmation. Debriefer questions and participant inputs were positively related to learning outcomes. In contrast, guess-what-I-am-thinking, apologies, observations, use of materials, participant descriptions, simple repetition of statements, and evaluation by other participants were not positively associated with learning outcomes. This study provides important new information about communication content during debriefings. The association between communication content and learning outcomes appears particularly relevant to further enhance efficacy of debriefings and simulation-based medical education.
DOI: 10.5281/zenodo.5909090
title: Identifying strengths and weaknesses of methods for computational network inference from single cell RNA-seq data

description: These data files contain single-cell RNA-sequencing expression data (expression_data.zip) and pseudotime files (pseudotime.zip) used to conduct comparisons of network inference methods on six published single-cell RNA-sequencing datasets. The resulting networks generated from the network inference methods are also uploaded here (normalized_inferred_networks.zip and imputed_inferred_networks.zip). Finally, the gold standard networks we used as ground truth to measure accuracy of the inferred networks are uploaded here (gold_standard_datasets.zip).
DOI: 10.5281/zenodo.5907527
title: Identifying strengths and weaknesses of methods for computational network inference from single cell RNA-seq data

description: These data files contain single-cell RNA-sequencing expression data (expression_data.zip) and pseudotime files (pseudotime.zip) used to conduct comparisons of network inference methods on six published single-cell RNA-sequencing datasets. The resulting networks generated from the network inference methods are also uploaded here (normalized_inferred_networks.zip and imputed_inferred_networks.zip). Finally, the gold standard networks we used as ground truth to measure accuracy of the inferred networks are uploaded here (gold_standard_datasets.zip).
DOI: 10.5281/zenodo.5909703
title: test upload

description: This contains data and checkpoints for model evaluation. ICML.
DOI: 10.5281/zenodo.5909702
title: test upload

description: This contains data and checkpoints for model evaluation. ICML.
DOI: 10.3886/e120321v11-107642
title: COVID-19 Twitter Dataset with Latent Topics, Sentiments and Emotions Attributes

description: This project aims to present a large dataset for researchers to discover public conversation on Twitter surrounding the COVID-19 pandemic. From 28 January 2020 to 1 September 2021, we collected over 198 million Twitter posts from more than 25 million unique users using four keywords: “corona”, “wuhan”, “nCov” and “covid”. Leveraging topic modeling techniques and pre-trained machine learning-based emotion analytic algorithms, we labeled each tweet with seventeen semantic attributes, including a) ten binary attributes indicating the tweet’s relevance or irrelevance to the top ten detected topics, b) five quantitative emotion attributes indicating the degree of intensity of the valence or sentiment (from 0: very negative to 1: very positive), and the degree of intensity of fear, anger, happiness and sadness emotions (from 0: not at all to 1: extremely intense), and c) two qualitative attributes indicating the sentiment category (very negative, negative, neutral or mixed, positive, very positive) and the dominant emotion category (fear, anger, happiness, sadness, no specific emotion) the tweet is mainly expressing.
description: Twitter posts.
description: The latest version has data updated up to 1 Sep 2021, including additional csv downloads for 29 countries)
DOI: 10.5517/ccdc.csd.cc20ydr4
title: CCDC 1875306: Experimental Crystal Structure Determination

description: Related Article: Aleksei Titov,  Oleg A. Filippov,  Alexander Smol’yakov,  Kristina Baranova,  Ekaterina Titova,  Aleksey Averin,  Elena Shubina|2019|Eur.J.Inorg.Chem.|2019|821|doi:10.1002/ejic.201801318
DOI: 10.5517/ccdc.csd.cc20ydt6
title: CCDC 1875308: Experimental Crystal Structure Determination

description: Related Article: Aleksei Titov,  Oleg A. Filippov,  Alexander Smol’yakov,  Kristina Baranova,  Ekaterina Titova,  Aleksey Averin,  Elena Shubina|2019|Eur.J.Inorg.Chem.|2019|821|doi:10.1002/ejic.201801318
DOI: 10.5517/ccdc.csd.cc22b4n7
title: CCDC 1916378: Experimental Crystal Structure Determination

description: Related Article: Jiamin Qu|2019|CSD Communication|||
DOI: 10.5281/zenodo.5911225
title: Erythroxylum coca zanfona pass 1

description: Reference: Erythroxylum novo. Inferred gap lengths.
DOI: 10.5281/zenodo.5911224
title: Erythroxylum coca zanfona pass 1

description: Reference: Erythroxylum novo. Inferred gap lengths.
DOI: 10.6084/m9.figshare.18737075.v1
title: Mining ultraconserved elements from transcriptome and genome data to explore the phylogenomics of the free-living lice suborder Psocomorpha (Insecta: Psocodea)

description: Supplementary material resulting from the UCE data mining from WGS data, to explore the phylogenetic relationships within a group of freeliving lice order Psocomorpha.
DOI: 10.5281/zenodo.5698732
title: MDMcleaner benchmarking datasets

description: Benchmarking mock SAG datasets used for validation of the MDMcleaner workflow
description: bzip2 compressed
DOI: 10.5281/zenodo.5698731
title: MDMcleaner benchmarking datasets

description: Benchmarking mock SAG datasets used for validation of the MDMcleaner workflow
description: bzip2 compressed
DOI: 10.6084/m9.figshare.19078235
title: drag-data.csv

description: The dataset that underlies my PhD dissertation, and that can be explored visually through my Observable account: https://observablehq.com/collection/@kallewesterling/dissertation-data.
DOI: 10.5281/zenodo.5698995
title: MDMcleaner reference database

description: MDMcleaner reference database used at time of publication. based on: GTDB release r95 RefSeq release 203 Silva version 138.1
DOI: 10.5281/zenodo.5698994
title: MDMcleaner reference database

description: MDMcleaner reference database used at time of publication. based on: GTDB release r95 RefSeq release 203 Silva version 138.1
DOI: 10.5281/zenodo.4302354
title: Bibliometric assessment of marine spatial planning publications (2003-2019)

description: Dataset of marine spatial planning (MSP) publications for the period 2003 - 2019.
DOI: 10.5281/zenodo.4302353
title: Bibliometric assessment of marine spatial planning publications (2003-2019)

description: Dataset of marine spatial planning (MSP) publications for the period 2003 - 2019.
DOI: 10.18739/a2125qb1q
title: Arctic Observing Network (AON) observations from the 2018-2020 Beaufort shelf-edge mooring array

description: This submission contains data collected as a part of the 2018-2020 Beaufort shelf-edge mooring array, which was designed to investigate the manner in which the continental shelves communicate with the interior Arctic basin. Funding was provided by the National Science Foundation (NSF). This submission contains data from the BS3 mooring site, which has collected a consistent and detailed timeseries of physical oceanographic observations beginning in 2002 until present. Funding for this long-term data collection has been supported by the NSF Arctic Observing Network (AON). More information on the AON project can be found at http://aon.whoi.edu/.
DOI: 10.48324/dandi.000213/0.220127.1738
title: Transformation of a Spatial Map across the Hippocampal-Lateral Septal Circuit

description: The hippocampus constructs a map of the environment. How this “cognitive map” is utilized by other brain regions to guide behavior remains unexplored. To examine how neuronal firing patterns in the hippocampus are transmitted and transformed, we recorded neurons in its principal subcortical target, the lateral septum (LS). We observed that LS neurons carry reliable spatial information in the phase of action potentials, relative to hippocampal theta oscillations, while the firing rates of LS neurons remained uninformative. Furthermore, this spatial phase code had an anatomical microstructure within the LS and was bound to the hippocampal spatial code by synchronous gamma frequency cell assemblies. Using a data-driven model, we show that rate-independent spatial tuning arises through the dynamic weighting of CA1 and CA3 cell assemblies. Our findings demonstrate that transformation of the hippocampal spatial map depends on higher-order theta-dependent neuronal sequences.
DOI: 10.6084/m9.figshare.16941089.v1
title: Predicting the COVID-19 Pandemic Impact on Clinical Trial Recruitment

description: Contemporary clinical trials often have complex logistics: they are run across multiple centers/countries and involve a lot of uncertainties about disease prevalence rates, patient characteristics and regulatory requirements, all of which can vary across countries. As a result, planning and delivering such studies on-time has long been recognized as a challenge in the pharmaceutical industry. One well-known approach to modeling recruitment in complex trials, which we use as a starting point of our work is a Poisson-Gamma stochastic model. COVID-19 pandemic brought additional layer of complexity to recruitment modeling: as many countries went into shutdown, sponsors were forced with the dilemma of replanning study delivery rebalancing their portfolios “on the fly.” That translated into the need to adapt the recruitment model to account for effect of COVID-19. In this work we present an approach that blends Poisson–Gamma model, real-time recruitment data updates and epidemiological modeling of COVID-19 spread. At the core of the methodology is sophisticated Bayesian hierarchical model predicting how pandemic intensity affected parameters of Poisson-gamma model. We also build an app conveniently showing many publicly available COVID models in one place. The work is a result of intense collaboration among many statisticians, data scientists and clinical operations professionals.
DOI: 10.6084/m9.figshare.16941089
title: Predicting the COVID-19 Pandemic Impact on Clinical Trial Recruitment

description: Contemporary clinical trials often have complex logistics: they are run across multiple centers/countries and involve a lot of uncertainties about disease prevalence rates, patient characteristics and regulatory requirements, all of which can vary across countries. As a result, planning and delivering such studies on-time has long been recognized as a challenge in the pharmaceutical industry. One well-known approach to modeling recruitment in complex trials, which we use as a starting point of our work is a Poisson-Gamma stochastic model. COVID-19 pandemic brought additional layer of complexity to recruitment modeling: as many countries went into shutdown, sponsors were forced with the dilemma of replanning study delivery rebalancing their portfolios “on the fly.” That translated into the need to adapt the recruitment model to account for effect of COVID-19. In this work we present an approach that blends Poisson–Gamma model, real-time recruitment data updates and epidemiological modeling of COVID-19 spread. At the core of the methodology is sophisticated Bayesian hierarchical model predicting how pandemic intensity affected parameters of Poisson-gamma model. We also build an app conveniently showing many publicly available COVID models in one place. The work is a result of intense collaboration among many statisticians, data scientists and clinical operations professionals.