cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.13397585.v2
title: Insight into chronic pain in the United States: descriptive results from the Prescription Opioid Misuse and Abuse Questionnaire (POMAQ) validation study

description: A chronic pain patient sample living in the United States who participated in a cross-sectional study to evaluate the validity and reproducibility of the Prescription Opioid Misuse and Abuse Questionnaire is characterized. Patients with chronic pain identified through electronic medical records as refilling at least one opioid prescription within the prior 3 months were recruited from five United States Department of Defense Military Health System clinics. Patients completed the Prescription Opioid Misuse and Abuse Questionnaire, Brief Pain Inventory-Short Form, Medical Outcomes Study: 36-item Short Form, and sociodemographic questions online. Clinical characteristics and electronic medical records for 1 year prior to consent were collected. 809 (86.2%) participants completed the Prescription Opioid Misuse and Abuse Questionnaire. Mean (± standard deviation) age was 55.4 ± 12.7 years; the majority female (55.5%) and white (74.8%). Mean duration of chronic pain was 14.7 ± 10.5 years; the most common pain conditions were lower back pain (76.6%), neck or shoulder pain (60.3%), and osteoarthritis (38.7%). The most commonly prescribed opioids were oxycodone (35.7%), tramadol (34.5%), and hydrocodone (26.9%); 54.8% took one opioid, 44.9% took 2 or more opioids. Participants’ health status was poor; pain severity and interference were moderate. Electronic medical record data revealed high healthcare resource utilization. This chronic pain population was severely impacted by their pain condition(s).
DOI: 10.6084/m9.figshare.13397585.v1
title: Insight into chronic pain in the United States: Descriptive results from the Prescription Opioid Misuse and Abuse Questionnaire (POMAQ) validation study

description: A chronic pain patient sample living in the United States who participated in a cross-sectional study to evaluate the validity and reproducibility of the Prescription Opioid Misuse and Abuse Questionnaire is characterized. Patients with chronic pain identified through electronic medical records as refilling at least one opioid prescription within the prior 3 months were recruited from five United States Department of Defense Military Health System clinics. Patients completed the Prescription Opioid Misuse and Abuse Questionnaire, Brief Pain Inventory-Short Form, Medical Outcomes Study: 36-item Short Form, and sociodemographic questions online. Clinical characteristics and electronic medical records for one year prior to consent were collected. 809 (86.2%) participants completed the Prescription Opioid Misuse and Abuse Questionnaire. Mean (± standard deviation) age was 55.4 ± 12.7 years; the majority female (55.5%) and white (74.8%). Mean duration of chronic pain was 14.7 ± 10.5 years; the most common pain conditions were lower back pain (76.6%), neck or shoulder pain (60.3%), and osteoarthritis (38.7%). The most commonly prescribed opioids were oxycodone (35.7%), tramadol (34.5%), and hydrocodone (26.9%); 54.8% took one opioid, 44.9% took 2 or more opioids. Participants’ health status was poor; pain severity and interference were moderate. electronic medical record data revealed high healthcare resource utilization. This chronic pain population was severely impacted by their pain condition(s).
DOI: 10.3886/e135162v1-81680
title: COVID-19 and intergroup relations

description: COVID-19 and intergroup relations between countries
DOI: 10.14459/2021mp1601286
title: Data for: Soil carbon sequestration by agroforestry systems in China: A meta-analysis

description: Data on soil organic carbon (SOC) storage in agroforestry systems (AFS) in China were gathered in February 2016 from publications in English and Chinese from five academic databases, namely Web of Science, China National Knowledge Infrastructure (CNKI), Springer, Elsevier’s Scopus, and Wiley.
DOI: 10.5281/zenodo.4620669
title: Influence of Fluorination on Single-Molecule Unfolding and RupturePathways of a Mechanostable Protein Adhesion Complex

description: Data underlying the figures in the publication “Influence of Fluorination on Single-Molecule Unfolding and Rupture Pathways of a Mechanostable Protein Adhesion Complex” in <em>Nano Lett.</em> 2020, 20, 12, 8940–8950. Table of contents: 1. Fig 2B_HRMS XMod-Doc(WT)-LEU and –TFL 2. Fig 2C HRMS XMod(XL2V)-Doc-LEU and –TFL 3. Fig 3 XMod-Doc(WT)-LEU 4. Fig 3 XMod-Doc(WT)-TFL 5.Fig 4 XMod(XL2V)-Doc-LEU 6. Fig 4 XMod(XL2V)-Doc-TFL 7. Fig 5b NanoDSF 8. Fig S7 XMod-Doc(WT)-TFL pH 5.5
DOI: 10.5281/zenodo.4620668
title: Influence of Fluorination on Single-Molecule Unfolding and RupturePathways of a Mechanostable Protein Adhesion Complex

description: Data underlying the figures in the publication “Influence of Fluorination on Single-Molecule Unfolding and Rupture Pathways of a Mechanostable Protein Adhesion Complex” in <em>Nano Lett.</em> 2020, 20, 12, 8940–8950. Table of contents: 1. Fig 2B_HRMS XMod-Doc(WT)-LEU and –TFL 2. Fig 2C HRMS XMod(XL2V)-Doc-LEU and –TFL 3. Fig 3 XMod-Doc(WT)-LEU 4. Fig 3 XMod-Doc(WT)-TFL 5.Fig 4 XMod(XL2V)-Doc-LEU 6. Fig 4 XMod(XL2V)-Doc-TFL 7. Fig 5b NanoDSF 8. Fig S7 XMod-Doc(WT)-TFL pH 5.5
DOI: 10.6084/m9.figshare.14222273.v1
title: IEA_AIE_115.zip

description: Dataset for a paper "Continuous Build Outcome Prediction: A Small-N Experiment in Settings of a Real Software Project". The 33th International Conference on Industrial, Engineering & Other Applications of Applied Intelligent Systems
DOI: 10.6084/m9.figshare.14222273.v2
title: IEA_AIE_115.zip

description: Dataset for a paper "Continuous Build Outcome Prediction: A Small-N Experiment in Settings of a Real Software Project". The 34th International Conference on Industrial, Engineering & Other Applications of Applied Intelligent Systems
DOI: 10.6084/m9.figshare.14222273
title: IEA_AIE_115

description: Dataset for a paper "Continuous Build Outcome Prediction: A Small-N Experiment in Settings of a Real Software Project". The 34th International Conference on Industrial, Engineering & Other Applications of Applied Intelligent Systems
DOI: 10.6084/m9.figshare.14222273.v4
title: IEA_AIE_115

description: Dataset for a paper "Continuous Build Outcome Prediction: A Small-N Experiment in Settings of a Real Software Project". The 34th International Conference on Industrial, Engineering & Other Applications of Applied Intelligent Systems
DOI: 10.6084/m9.figshare.14222273.v3
title: IEA_AIE_115

description: Dataset for a paper "Continuous Build Outcome Prediction: A Small-N Experiment in Settings of a Real Software Project". The 34th International Conference on Industrial, Engineering & Other Applications of Applied Intelligent Systems
DOI: 10.23729/7e5c881b-0c80-4edf-b88a-0051b2f63ca0
title: Threatened Species News Dataset

description: This data is part of the research article: Automated retrieval of information on threatened species from online sources using machine learning, Ritwik Kulkarni and Enrico Di Minin, 2021, Methods in Ecology and Evolution Kindly cite this article for the dataset. 1 Considering limited conservation resources, gathering and analyzing information from digital data sources can help investigate the global biodiversity crisis in a cost-efficient manner. Development and application of methods for automated content analysis of digital data sources are especially important in the context of investigating human-nature interactions. 2. In this study, we introduce methods to automatically collect information on species threatened by wildlife trade from online news. An end to end pipeline is constructed that begins from searching and downloading news articles about species listed in Appendix I of the Convention on International Trade in Endangered Species of Wild Fauna and Flora (CITES) and proceeds with implementing natural language processing and machine learning methods to filter and retain only relevant articles. Additional relevant information is then extracted for each article using a Named Entity Recognition model. 3. The data collected over a one month period included 15,088 articles and focused on 585 species listed in Appendix I of CITES. The accuracy of the neural network to detect relevant articles was 95.91% while the Named Entity recognition model helped extract information on prices, location, and quantities of traded animals. A regularly updated database is generated by the system, which can be queried and analysed for various research purposes and to inform conservation decision-making. 4. The results demonstrate that natural language processing can be used in an efficient manner to extract information from digital text content. The proposed methods can be applied to multiple digital data platforms at the same time and used to investigate human-nature interactions in conservation science and practice.
DOI: 10.23729/0561d6f3-e98e-43b7-9af2-e4fc723bbe87
title: Comparing the radiative forcings of the anthropogenic aerosol emissions from Chile and Mexico

description: The setup files used in the ECHAM-HAMMOZ (HAMMOZ consortium, 2019) simulations for "Comparing the radiative forcings of the anthropogenic aerosol emissions from Chile and Mexico" manuscript.
DOI: 10.5281/zenodo.4593208
title: Gap-filling Satellite Land Surface Temperature Over Heatwave Periods with Machine Learning

description: The frequency of heatwave events has increased in recent decades because of global warming. Satellite observed Land Surface Temperature (LST) is a widely used parameter for assessing heatwaves. It provides a wide spatial coverage compared to surface air temperature measured at weather stations. However, LST quality is limited by cloud contamination. Because heatwaves have a limited temporal frame, having a full and cloud-free complement of LST for that period is necessary. In this letter, we explore gap-filling of LST using spatial features like land cover, elevation and vegetation indices in a machine learning approach. We use a seamless open and free daily vegetation index product which is paramount to the success of our study. We create a Random Forest model that provides a ranking of features relevant for predicting LST. We compare the output of our model to an established spatiotemporal gap-filling algorithm to validate the predictive capability of our model. This study validates machine learning as a suitable tool for filling gaps in satellite LST. In addition, we acknowledge that while time is an important factor in predicting LST, additional information on vegetation can improve the predictions of a model This dataset covers gap-filled MODIS LST using machine learning for three heatwave periods in Estonia. The RMSE of the model on the test data is 1.37. Jupyter notebooks used in this project can be found at https://github.com/kwazineutin/Gapfilling-Satellite-LST-with-ML
DOI: 10.21227/qsbr-kw16
title: BanglaMusicStylo-A-Stylometric-Dataset-of-Bangla-Music-Lyrics

description: With the rapid growth of the Bangla music industry huge volume of Bangla songs is produced every day. An immense number of producers, lyricists, singers, and artists are involved in the production of songs from different genres. Among many genres of Bangla music; classical, folk, baul, modern music, Rabindra Sangeet, Nazrul Geeti, film music, rock music, and fusion music have gained the highest popularity. Lyricists try to express their feelings and views towards any situation or subject through their writings. Therefore, each lyricist has their own dictionary of thoughts to put on music lyrics. In this paper, we have presented “BanglaMusicStylo”, the very first stylometric dataset of Bangla music lyrics. We have collected 2824 Bangla song lyrics of 211 lyricists in a digital form. All the lyrics are stored in text format for further use. This dataset could be used for stylometric analysis such as authorship attribution, linguistic forensics, gender identification from textual data, Bangla music genre classification, vandalism detection, emotion classification, etc. Identifying the significant research opportunities in this area, we have formalized this dataset which could be used for stylometric analysis.
DOI: 10.6084/m9.figshare.13107386.v1
title: Sample data

description: sample data for service composition
DOI: 10.48370/ofd/zfqzvk
title: Wierzba trójpręcikowa (Salix triandra L.), 7741

description: Herbarium
DOI: 10.6084/m9.figshare.14247236.v1
title: Big size data

description: data for cloud manufacturing service composition
DOI: 10.6084/m9.figshare.14247245
title: Untitled Item

description: Cloud manufacturing service compoistion
DOI: 10.6084/m9.figshare.14247245.v1
title: Untitled Item

description: Cloud manufacturing service compoistion
DOI: 10.6084/m9.figshare.14247236
title: Big size data

description: data for cloud manufacturing service composition
DOI: 10.6084/m9.figshare.14247200
title: Supplementary Material for: Machine Learning for Prediction and Risk Stratification of Lupus Nephritis Renal Flare

description: <b><i>Background:</i></b> Renal flare of lupus nephritis (LN) is strongly associated with poor kidney outcomes, and predicting renal flare and stratifying its risk are important for clinical decision-making and individualized management to reduce LN flare. <b><i>Methods:</i></b> We randomly divided 1,694 patients with biopsy-proven LN, who had achieved remission after treatment, into a derivation cohort (<i>n</i> = 1,186) and an internal validation cohort (<i>n</i> = 508), at a ratio of 7:3. The risk of renal flare 5 years after remission was predicted using an eXtreme Gradient Boosting (XGBoost) method model, developed from 59 variables, including demographic, clinical, immunological, pathological, and therapeutic characteristics. A simplified risk score prediction model (SRSPM) was developed from important variables selected by XGBoost model using stepwise Cox regression for practical convenience. <b><i>Results:</i></b> The 5-year relapse rates were 39.5% and 38.2% in the derivation and internal validation cohorts, respectively. Both the XGBoost model and the SRSPM had good predictive performance, with a C-index of 0.819 (95% confidence interval [CI]: 0.774–0.857) and 0.746 (95% CI: 0.697–0.795), respectively, in the validation cohort. The SRSPM comprised 6 variables, including partial remission and endocapillary hypercellularity at baseline, age, serum Alb, anti-dsDNA, and serum complement C3 at the point of remission. Using Kaplan-Meier analysis, the SRSPM identified significant risk stratification for renal flares (<i>p</i> &lt; 0.001). <b><i>Conclusions:</i></b> Renal flare of LN can be readily predicted using the XGBoost model and the SRSPM, and the SRSPM can also stratify flare risk. Both models are useful for clinical decision-making and individualized management in LN.
DOI: 10.6084/m9.figshare.14247258.v1
title: Congruus kitcheneri raw measurement data from The skeleton of <i>Congruus kitcheneri</i>, a semiarboreal kangaroo from the Pleistocene of southern Australia

description: Data compiled here for more than 20 species were used for calculations of limb proportions and bone indices.
DOI: 10.6084/m9.figshare.14247258
title: Congruus kitcheneri raw measurement data from The skeleton of <i>Congruus kitcheneri</i>, a semiarboreal kangaroo from the Pleistocene of southern Australia

description: Data compiled here for more than 20 species were used for calculations of limb proportions and bone indices.
DOI: 10.5519/qd.6tgpllge
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (21 records)
DOI: 10.6084/m9.figshare.14247279
title: Data file from Evolutionary loss of a signalling colour is linked to increased response to conspecific chemicals

description: Behavioural responses to communicative signals combine input from multiple sensory modalities and signal compensation theory predicts that evolutionary shifts in one sensory modality could impact response to signals in other sensory modalities. Here, we conducted two types of field experiments with 11 species spread across the lizard genus <i>Sceloporus</i> to test the hypothesis that the loss of visual signal elements affects behavioural responses to a chemical signal (conspecific scents) or to a predominantly visual signal (a conspecific lizard), both of which are used in intraspecific communication. We found that three species that have independently lost a visual signal trait, a colourful belly patch, responded to conspecific scents with increased chemosensory behaviour compared to a chemical control, while species with the belly patch did not. However, most species, with and without the belly patch, responded to live conspecifics with increased visual displays of similar magnitude. While aggressive responses to visual stimuli are taxonomically widespread in <i>Sceloporus</i>, our results suggest that increased chemosensory response behaviour is linked to colour patch loss. Thus, interactions across sensory modalities could constrain the evolution of complex signalling phenotypes, thereby influencing signal diversity.
DOI: 10.6084/m9.figshare.14247282
title: R Code file from Evolutionary loss of a signalling colour is linked to increased response to conspecific chemicals

description: Behavioural responses to communicative signals combine input from multiple sensory modalities and signal compensation theory predicts that evolutionary shifts in one sensory modality could impact response to signals in other sensory modalities. Here, we conducted two types of field experiments with 11 species spread across the lizard genus <i>Sceloporus</i> to test the hypothesis that the loss of visual signal elements affects behavioural responses to a chemical signal (conspecific scents) or to a predominantly visual signal (a conspecific lizard), both of which are used in intraspecific communication. We found that three species that have independently lost a visual signal trait, a colourful belly patch, responded to conspecific scents with increased chemosensory behaviour compared to a chemical control, while species with the belly patch did not. However, most species, with and without the belly patch, responded to live conspecifics with increased visual displays of similar magnitude. While aggressive responses to visual stimuli are taxonomically widespread in <i>Sceloporus</i>, our results suggest that increased chemosensory response behaviour is linked to colour patch loss. Thus, interactions across sensory modalities could constrain the evolution of complex signalling phenotypes, thereby influencing signal diversity.
DOI: 10.6084/m9.figshare.14247282.v1
title: R Code file from Evolutionary loss of a signalling colour is linked to increased response to conspecific chemicals

description: Behavioural responses to communicative signals combine input from multiple sensory modalities and signal compensation theory predicts that evolutionary shifts in one sensory modality could impact response to signals in other sensory modalities. Here, we conducted two types of field experiments with 11 species spread across the lizard genus <i>Sceloporus</i> to test the hypothesis that the loss of visual signal elements affects behavioural responses to a chemical signal (conspecific scents) or to a predominantly visual signal (a conspecific lizard), both of which are used in intraspecific communication. We found that three species that have independently lost a visual signal trait, a colourful belly patch, responded to conspecific scents with increased chemosensory behaviour compared to a chemical control, while species with the belly patch did not. However, most species, with and without the belly patch, responded to live conspecifics with increased visual displays of similar magnitude. While aggressive responses to visual stimuli are taxonomically widespread in <i>Sceloporus</i>, our results suggest that increased chemosensory response behaviour is linked to colour patch loss. Thus, interactions across sensory modalities could constrain the evolution of complex signalling phenotypes, thereby influencing signal diversity.
DOI: 10.6084/m9.figshare.14247296
title: Supplementary Material for: Identifying Responders and Exploring Mechanisms of Action of the Endobronchial Coil Treatment for Emphysema

description: <b><i>Background:</i></b> So far, 3 randomized controlled trials have shown that the endobronchial treatment using coils is safe and effective. However, the more exact underlying mechanism of the treatment and best predictors of response are unknown. <b><i>Objectives:</i></b> The aim of the study was to gain more knowledge about the underlying physiological mechanism of the lung volume reduction coil treatment and to identify potential predictors of response to this treatment. <b><i>Methods:</i></b> This was a prospective nonrandomized single-center study which included patients who were bilaterally treated with coils. Patients underwent an extensive number of physical tests at baseline and 3 months after treatment. <b><i>Results:</i></b> Twenty-four patients (29% male, mean age 62 years, forced expiratory volume in 1 s [FEV<sub>1</sub>] 26% pred, residual volume (RV) 231% pred) were included. Three months after treatment, significant improvements were found in spirometry, static hyperinflation, air trapping, airway resistance, treated lobe RV and treated lobes air trapping measured on CT scan, exercise capacity, and quality of life. The change in RV and airway resistance was significantly associated with a change in FEV<sub>1</sub>, forced vital capacity, air trapping, maximal expiratory pressure, dynamic compliance, and dynamic hyperinflation. Predictors of treatment response at baseline were a higher RV, larger air trapping, higher emphysema score in the treated lobes, and a lower physical activity level. <b><i>Conclusions:</i></b> Our results confirm that emphysema patients benefit from endobronchial coil treatment. The primary mechanism of action is decreasing static hyperinflation with improvement of airway resistance which consequently changes dynamic lung mechanics. However, the right patient population needs to be selected for the treatment to be beneficial which should include patients with severe lung hyperinflation, severe air trapping, and significant emphysema in target lobes.
DOI: 10.5281/zenodo.4616270
title: Supplementary_Tables_S1-S11 from:

description: "Bacterial and Fungal Profiles as Markers of Infliximab Drug Response in Inflammatory Bowel Disease." <em>Journal of Crohn's and Colitis</em>, jjaa252, https://doi.org/10.1093/ecco-jcc/jjaa252 Published: 10 December 2020
description: {"references": ["Ventin-Holmberg, R., Eberl, A., Saqib, S., Korpela, K., Virtanen, S., Sipponen, T., et al. (2020). Bacterial and fungal profiles as markers of infliximab drug response in inflammatory bowel disease. J. Crohns Colitis jjaa252. (in press). doi: 10.1093/ecco-jcc/jjaa252"]}
DOI: 10.5281/zenodo.4616269
title: Supplementary_Tables_S1-S11 from:

description: "Bacterial and Fungal Profiles as Markers of Infliximab Drug Response in Inflammatory Bowel Disease." <em>Journal of Crohn's and Colitis</em>, jjaa252, https://doi.org/10.1093/ecco-jcc/jjaa252 Published: 10 December 2020
description: {"references": ["Ventin-Holmberg, R., Eberl, A., Saqib, S., Korpela, K., Virtanen, S., Sipponen, T., et al. (2020). Bacterial and fungal profiles as markers of infliximab drug response in inflammatory bowel disease. J. Crohns Colitis jjaa252. (in press). doi: 10.1093/ecco-jcc/jjaa252"]}