cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.21647120
title: Supplementary Material for: Outcomes of Salvage Surgery for Initially Unresectable Hepatocellular Carcinoma Converted by Transcatheter Arterial Chemoembolization Combined with Lenvatinib Plus Anti-PD-1 Antibodies: A Multicenter Retrospective Study

description: Introduction. The actual rate of conversion surgery and its prognostic advantages remain unclear. This study aimed to assess the outcomes of salvage surgery after conversion therapy with triple therapy (transcatheter arterial chemoembolization (TACE) combined with lenvatinib plus anti-PD-1 antibodies) in patients with initially unresectable hepatocellular carcinoma (uHCC). Methods. Patients with initially uHCC who received at least one cycle of first-line triple therapy and salvage surgery at five major cancer centers in China were included. The primary endpoints were overall survival (OS) and recurrence-free survival (RFS) rates after salvage surgery. The secondary endpoints were perioperative complications, 90-day mortality, and pathological tumor response. Results. Between June 2018 and December 2021, 70 patients diagnosed with uHCC who underwent triple therapy and salvage surgery were analyzed: 39 with Barcelona Clinic Liver Cancer (BCLC) stage C, 22 with BCLC stage B, and 9 with BCLC stage A disease. The median interval between the start of triple therapy and salvage surgery was 4.3 months (range, 1.7–14.2 months). Pathological complete response and major pathological response were observed in 29 (41.4%) and 59 (84.3%) patients, respectively. There were two cases of perioperative mortality (4.3%) and five cases of severe perioperative complications (7.1%). With a median follow-up of 12.9 months after surgery (range, 0.3–36.8 months), the median OS and RFS were not reached. The 1- and 2-year OS rates were 97.1% and 94.4%, respectively, and the corresponding RFS rates were 68.9% and 54.4%, respectively. Conclusion. First-line combination of TACE, lenvatinib, and anti-PD-1 antibodies provides a better chance of conversion therapy in patients with initially uHCC. Furthermore, salvage surgery after conversion therapy is effective and safe and has the potential to provide excellent long-term survival benefits.
DOI: 10.5281/zenodo.7543367
title: Like or dislike? The impact of politicians' gender on vertical affective polarization in Flanders (Belgium) (replication data)

description: Replication data for Devroe, R. & Wauters, B. (2023). Like or dislike? The impact of politicians’ gender on vertical affective polarization in Flanders (Belgium)
description: This work was supported by Fonds Wetenschappelijk Onderzoek – Vlaanderen (FWO); under Grant 12ZZ821N.
DOI: 10.5281/zenodo.7543364
title: Like or dislike? The impact of politicians' gender on vertical affective polarization in Flanders (Belgium) (replication data)

description: Replication data for Devroe, R. & Wauters, B. (2023). Like or dislike? The impact of politicians’ gender on vertical affective polarization in Flanders (Belgium)
description: This work was supported by Fonds Wetenschappelijk Onderzoek – Vlaanderen (FWO); under Grant 12ZZ821N.
DOI: 10.5281/zenodo.7528542
title: HeadwaterstreamSNevada: data on riparian vegetation and water parameters of headwater streams in Sierra Nevada, Spain

description: Providing historical data on riparian plant biodiversity and physico-chemical parameters of stream water in Mediterranean mountains helps to assess the effects of climate change and other human stressors on these sensitive and critical ecosystems. This database collects data from the main natural headwater streams of the Sierra Nevada (southeastern Spain), a high mountain (up to 3,479 meters above sea level, m.a.s.l.) recognized as a biodiversity super hotspot (Arroyo et al., 2022) in the Mediterranean Basin. On this mountain, rivers and landscapes depend on snowmelt water, representing an excellent scenario for evaluating global change's impacts. This dataset covers first- to third-order headwater streams at 41 sites from 832 to 1,997 m.a.s.l., collected from December 2006 to July 2007. Our goal is to supply information on the vegetation associated with streambanks, the essential physico-chemical parameters of stream water, and the physiographic features of the subwatersheds. Riparian vegetation data correspond to six plots sampled at each site, including total canopy, individual number, height and DBH (diameter at breast height) in woody species, and cover percentage for herbs. Physico-chemical parameters were measured in situ (electric conductivity, pH, dissolved O2 concentration, stream discharge) and determined in the laboratory [alkalinity, soluble reactive phosphate-phosphorus (SRP), total phosphorus (TP), nitrate-nitrogen (NO3-–N), ammonium-nitrogen (NH4+–N), total nitrogen (TN)]. Watershed physiographic variables comprise drainage area, minimum altitude, maximum altitude, mean slope, orientation, stream order, stream length, and land cover surface percentage. We recorded 197 plant taxa (67 species, 28 subspecies and 2 hybrids), representing 8.4% of the Sierra Nevada vascular flora. Due to the botanical nomenclature used, the database can be linked to FloraSNevada database (Lorite et al., 2020), contributing to Sierra Nevada (Spain) as a laboratory of global processes. For more information about the data, see the metadata document (Metadata_HeadwaterstreamSNevada.docx).
DOI: 10.5281/zenodo.7528541
title: HeadwaterstreamSNevada: data on riparian vegetation and water parameters of headwater streams in Sierra Nevada, Spain

description: Providing historical data on riparian plant biodiversity and physico-chemical parameters of stream water in Mediterranean mountains helps to assess the effects of climate change and other human stressors on these sensitive and critical ecosystems. This database collects data from the main natural headwater streams of the Sierra Nevada (southeastern Spain), a high mountain (up to 3,479 meters above sea level, m.a.s.l.) recognized as a biodiversity super hotspot (Arroyo et al., 2022) in the Mediterranean Basin. On this mountain, rivers and landscapes depend on snowmelt water, representing an excellent scenario for evaluating global change's impacts. This dataset covers first- to third-order headwater streams at 41 sites from 832 to 1,997 m.a.s.l., collected from December 2006 to July 2007. Our goal is to supply information on the vegetation associated with streambanks, the essential physico-chemical parameters of stream water, and the physiographic features of the subwatersheds. Riparian vegetation data correspond to six plots sampled at each site, including total canopy, individual number, height and DBH (diameter at breast height) in woody species, and cover percentage for herbs. Physico-chemical parameters were measured in situ (electric conductivity, pH, dissolved O2 concentration, stream discharge) and determined in the laboratory [alkalinity, soluble reactive phosphate-phosphorus (SRP), total phosphorus (TP), nitrate-nitrogen (NO3-–N), ammonium-nitrogen (NH4+–N), total nitrogen (TN)]. Watershed physiographic variables comprise drainage area, minimum altitude, maximum altitude, mean slope, orientation, stream order, stream length, and land cover surface percentage. We recorded 197 plant taxa (67 species, 28 subspecies and 2 hybrids), representing 8.4% of the Sierra Nevada vascular flora. Due to the botanical nomenclature used, the database can be linked to FloraSNevada database (Lorite et al., 2020), contributing to Sierra Nevada (Spain) as a laboratory of global processes. For more information about the data, see the metadata document (Metadata_HeadwaterstreamSNevada.docx).
DOI: 10.34740/kaggle/dsv/4862976
title: Elon Musk Tweets
DOI: 10.21227/a8wq-cb10
title: Blast Furnace Ironmaking Process Monitoring with Time-Constrained Global and Local Nonlinear Analytic Stationary Subspace Analysis

description: In this paper, a novel time-constrained global and local nonlinear analytic stationary subspace analysis (Tc-GLNASSA) is proposed to enhance blast furnace ironmaking process (BFIP) monitoring. Although existing analytic stationary subspace analysis method has been available for deriving process consistent relationships. However, the presence of complex nonlinear, periodic nonstationary and time-varying smelting conditions renders the satisfactory estimation of stationary projections unattainable. To this end, we leverage multiple kernel functions and manifold learning methods to establish an estimate for the global and local nonlinear structure with time constraints, which will identify the unique nonlinearities excited by periodic nonstationarity. Meanwhile, a singular value decomposition-based modeling efficiency promotion strategy is constructed to reduce the proposed Tc-GLNASSA's computational complexity significantly. The orthogonality of model update scheme is analyzed theoretically, and an overall BFIP monitoring framework is given. Ultimately, practical BFIP case studies fully demonstrate the effectiveness of our proposal.
DOI: 10.6084/m9.figshare.17149208.v9
title: CRISPR/Cas12a-based assay for the rapid and high-sensitivity detection of Streptococcus agalactiae colonization in pregnant women with premature rupture of membrane.xlsx

description: <strong>Background: </strong><em>Streptococcus agalactiae</em> or group B <em>Streptococcus</em> (GBS) is a leading infectious cause of neonatal morbidity and mortality. It is essential to establish a robust method for the rapid and ultra-sensitive detection of GBS in pregnant women with premature rupture of membrane (PROM). <strong>Methods: </strong>This study developed a CRISPR-GBS assay that combined the advantages of the recombinase polymerase amplification (RPA) and CRISPR/Cas12a system for GBS detection. The clinical performance of the CRISPR-GBS assay was assessed using vaginal or cervical swabs that were collected from 179 pregnant women with PROM, compared in parallel to culture-based matrix-assisted laser desorption ionization time-of-flight mass spectrometry (culture-MS) method and real-time quantitative polymerase chain reaction (qPCR) assay. <strong>Results:</strong> The CRISPR-GBS assay can be completed within 35 minutes and the limit of detection was as low as 5 copies μL<sup>-1</sup>. Compared with the culture-MS, the CRISPR-GBS assay demonstrated a sensitivity of 96.64% (144/149, 95% confidence interval [CI] = 92.39–98.56%) and a specificity of 100% (30/30, 95% CI = 88.65–100%). It also had a high concordance rate of 98.88% with the qPCR assay. <strong>Conclusions:</strong> The established CRISPR-GBS platform can detect GBS in a rapid, accurate, easy-to-operate, and cost-efficient manner. It offered a promising tool for the intrapartum screening of GBS colonization.
DOI: 10.21954/ou.rd.21836490.v2
title: The GREEN FORUM COLLECTION about Climate Change and Sustainability Education (CCSE) with green intiiatives, green curriculum recommendations, and green skills

description: The GREEN FORUM COLLECTION about Climate Change and Sustainability Education (CCSE) is a dataset about: <br> The GREEN FORUM participants' views about CCSE (27 members) <br> The GREEN FORUM discussion about CCSE with 7 key challenges and 7 key recommendations <br> The GREEN INITIATIVES about CCSE including resources for: 1. Educational Content and activities for teachers 2. Programmes for schools 3. Initiatives led by academics & scientists 4. Informal & non-formal learning opportunities outside schools 5. Initiatives led by companies and industries 6. Open schooling projects funded by European Union 7. Reports/ papers green skills <br> <strong>TITLE:</strong> CCSE Delphi study online discussion with participants of the GREEN FORUM network <strong>SUBJECT:</strong><br> Education <strong>COLLECTION:</strong><br> Green Forum<br> <br> <strong>TYPE:</strong><br> Word Document – Delphi study online discussion<br> <br> <strong>DATE:</strong><br> 30 Nov 2022<br> <br> <strong>PERIOD</strong>:<br> from May 2022 to Nov 2022. <strong>LANGUAGE:</strong><br> ENGLISH<br> <br> <br> <strong>DESIGN METHOD: </strong> Consensus web conference supported by a Delphi study. This dataset has received Ethics approval by The Open University, HREC – Human Research and Ethics Committee. <strong>FUNDING</strong> This Delphi study is funded by The Open University UK and supported by the European Union CONNECT - inclusive open schooling with engaging and future oriented science, n. 872814; and ENGAGE – Equipping the next generation for active engagement in science n. 612269<br> <strong>DATASET CITATION:</strong> OKADA (2022). CCSE Resources about Climate Change and Sustainability Education shared by participants of the GREEN FORUM network. The Open University – Rumpus Research Group. https://doi.org/10.21954/ou.rd.21647789 <br> <strong>REFERENCE:</strong> Okada. A, Gray, P. (2022). A Climate Change and Sustainability Education Movement: Open Schooling Networks with the ‘CARE-KNOW-DO’ Framework. Sustainability Journal. <br> <strong>SOURCES:</strong> Journal Paper - Special Edition https://www.mdpi.com/journal/sustainability/special_issues/high_quality_education_equity_promoting_educational_sustainable_development <br> Padlet of Initiatives https://padlet.com/alexandraokada/CCSE <br> FlowPaper of Initiatives with Description https://7a0a0732.flowpaper.com/ccse/ <br>
DOI: 10.21954/ou.rd.21836490
title: The GREEN FORUM COLLECTION about Climate Change and Sustainability Education (CCSE) with green intiiatives, green curriculum recommendations, and green skills

description: The GREEN FORUM COLLECTION about Climate Change and Sustainability Education (CCSE) is a dataset about: <br> The GREEN FORUM participants' views about CCSE (27 members) <br> The GREEN FORUM discussion about CCSE with 7 key challenges and 7 key recommendations <br> The GREEN INITIATIVES about CCSE including resources for: 1. Educational Content and activities for teachers 2. Programmes for schools 3. Initiatives led by academics & scientists 4. Informal & non-formal learning opportunities outside schools 5. Initiatives led by companies and industries 6. Open schooling projects funded by European Union 7. Reports/ papers green skills <br> <strong>TITLE:</strong> CCSE Delphi study online discussion with participants of the GREEN FORUM network <strong>SUBJECT:</strong><br> Education <strong>COLLECTION:</strong><br> Green Forum<br> <br> <strong>TYPE:</strong><br> Word Document – Delphi study online discussion<br> <br> <strong>DATE:</strong><br> 30 Nov 2022<br> <br> <strong>PERIOD</strong>:<br> from May 2022 to Nov 2022. <strong>LANGUAGE:</strong><br> ENGLISH<br> <br> <br> <strong>DESIGN METHOD: </strong> Consensus web conference supported by a Delphi study. This dataset has received Ethics approval by The Open University, HREC – Human Research and Ethics Committee. <strong>FUNDING</strong> This Delphi study is funded by The Open University UK and supported by the European Union CONNECT - inclusive open schooling with engaging and future oriented science, n. 872814; and ENGAGE – Equipping the next generation for active engagement in science n. 612269<br> <strong>DATASET CITATION:</strong> OKADA (2022). CCSE Resources about Climate Change and Sustainability Education shared by participants of the GREEN FORUM network. The Open University – Rumpus Research Group. https://doi.org/10.21954/ou.rd.21647789 <br> <strong>REFERENCE:</strong> Okada. A, Gray, P. (2022). A Climate Change and Sustainability Education Movement: Open Schooling Networks with the ‘CARE-KNOW-DO’ Framework. Sustainability Journal. <br> <strong>SOURCES:</strong> Journal Paper - Special Edition https://www.mdpi.com/journal/sustainability/special_issues/high_quality_education_equity_promoting_educational_sustainable_development <br> Padlet of Initiatives https://padlet.com/alexandraokada/CCSE <br> FlowPaper of Initiatives with Description https://7a0a0732.flowpaper.com/ccse/ <br>
DOI: 10.21954/ou.rd.21836490.v1
title: The GREEN FORUM COLLECTION about Climate Change and Sustainability Education (CCSE) with green intiiatives, green curriculum recommendations, and green skills

description: The GREEN FORUM COLLECTION about Climate Change and Sustainability Education (CCSE) is a dataset about: <br> The GREEN FORUM participants' views about CCSE (27 members) <br> The GREEN FORUM discussion about CCSE with 7 key challenges and 7 key recommendations <br> The GREEN INITIATIVES about CCSE including resources for: 1. Educational Content and activities for teachers 2. Programmes for schools 3. Initiatives led by academics & scientists 4. Informal & non-formal learning opportunities outside schools 5. Initiatives led by companies and industries 6. Open schooling projects funded by European Union 7. Reports/ papers green skills <br> <strong>TITLE:</strong> CCSE Delphi study online discussion with participants of the GREEN FORUM network <strong>SUBJECT:</strong><br> Education <strong>COLLECTION:</strong><br> Green Forum<br> <br> <strong>TYPE:</strong><br> Word Document – Delphi study online discussion<br> <br> <strong>DATE:</strong><br> 30 Nov 2022<br> <br> <strong>PERIOD</strong>:<br> from May 2022 to Nov 2022. <strong>LANGUAGE:</strong><br> ENGLISH<br> <br> <br> <strong>DESIGN METHOD: </strong> Consensus web conference supported by a Delphi study. This dataset has received Ethics approval by The Open University, HREC – Human Research and Ethics Committee. <strong>FUNDING</strong> This Delphi study is funded by The Open University UK and supported by the European Union CONNECT - inclusive open schooling with engaging and future oriented science, n. 872814; and ENGAGE – Equipping the next generation for active engagement in science n. 612269<br> <strong>DATASET CITATION:</strong> OKADA (2022). CCSE Resources about Climate Change and Sustainability Education shared by participants of the GREEN FORUM network. The Open University – Rumpus Research Group. https://doi.org/10.21954/ou.rd.21647789 <br> <strong>REFERENCE:</strong> Okada. A, Gray, P. (2022). A Climate Change and Sustainability Education Movement: Open Schooling Networks with the ‘CARE-KNOW-DO’ Framework. Sustainability Journal. <br> <strong>SOURCES:</strong> Journal Paper - Special Edition https://www.mdpi.com/journal/sustainability/special_issues/high_quality_education_equity_promoting_educational_sustainable_development <br> Padlet of Initiatives https://padlet.com/alexandraokada/CCSE <br> FlowPaper of Initiatives with Description https://7a0a0732.flowpaper.com/ccse/ <br>
DOI: 10.5281/zenodo.7272254
title: Artifact of MADUSA: Mobile Application Demo Generation based on Usage Scenarios

description: Artifact of MADUSA: Mobile Application Demo Generation based on Usage Scenarios
DOI: 10.17917/twc6-3b75
title: GWAS Explorer, an open-source tool to explore, visualize, and access GWAS summary statistics

description: GWAS explorer provides an interactive resource for genetics researchers as well as other interested individuals to search for, visualize, and download aggregated association results from DCEG genome-wide association analyses (GWAS). Initial results are posted from The Prostate, Lung, Colorectal, Ovarian (PLCO) Cancer Screening Study, a large population-based randomized trial designed and sponsored by the National Cancer Institute (NCI) to determine the effects of screening on cancer-related mortality and secondary endpoints in men and women aged 55 to 74. The screening component of the trial was completed in 2006. Cohort participants have been followed for more than two decades, resulting in a rich collection of anthropometric, lifestyle, and disease information, and includes data from several smaller-scale molecular studies. As costs for the technology have drastically decreased, the NCI Division of Cancer Epidemiology and Genetics, has genotyped 110,000 PLCO participants and by doing so created a new resource for genomic studies.
DOI: 10.18739/a2rs0x
title: Atmospheric hydrocarbons as tracers for climate change, air transport, and oxidation chemistry in the Arctic, GEOSummit, Greenland, 2008-2017
DOI: 10.21227/0p56-1844
title: Passive Anti-Islanding Protection for Three-Phase Grid-Connected Photovoltaic Power Systems

description: This dataset contains (1) the Simulink model of a three-phase photovoltaic power system with passive anti-islanding protections like over/under current (OUC), over/under voltage (OUV), over/under frequency (OUF), rate of change of frequency (ROCOF), and dc-link voltage and (2) the results in the voltage source converter and the point of common coupling of the photovoltaic system during islanding operation mode and detection times of analyzed anti-islanding methods. The dataset is related with the data used in the "DC-Link Voltage Anti-Islanding Method for Grid-Connected Photovoltaic Power Systems" manuscript submitted to IEEE Transactions on Smart Grid.
DOI: 10.21227/0s0p-s959
title: IoT DoS and DDoS Attack Dataset

description: The network attacks are increasing both in frequency and intensity with the rapid growth of internet of things (IoT) devices. Recently, denial of service (DoS) and distributed denial of service (DDoS) attacks are reported as the most frequent attacks in IoT networks. The traditional security solutions like firewalls, intrusion detection systems, etc., are unable to detect the complex DoS and DDoS attacks since most of them filter the normal and attack traffic based upon the static predefined rules. However, these solutions can become reliable and effective when integrated with artificial intelligence (AI) based techniques. During the last few years, deep learning models especially convolutional neural networks achieved high significance due to their outstanding performance in the image processing field. The potential of these convolutional neural network (CNN) models can be used to efficiently detect the complex DoS and DDoS by converting the network traffic dataset into images. Therefore, in this work, we proposed a methodology to convert the network traffic data into image form and trained a state-of-the-art CNN model, i.e., ResNet over the converted data. The proposed methodology accomplished 99.99% accuracy for detecting the DoS and DDoS in case of binary classification. Furthermore, the proposed methodology achieved 87% average precision for recognizing eleven types of DoS and DDoS attack patterns which is 9% higher as compared to the state-of-the-art.
DOI: 10.21227/mynq-a588
title: Non-Intrusive Similar Loads Identification

description: This data set is composed by samples of load signature of electric devices acquired on a non-intrusively form. The test-bench was performed using four identical fluorescent lamps, four identical slots and four identical switches. Identical term means the same technical specifications (nominal voltage, power, isolation voltage, among others). The sensors are connected to the power supply in order to measure the electrical variations when appliances are turned on/off. We have 16 possible network configurations with 4 appliances, in which one, two, three or four appliances can be turned on. For each configuration, the acquisition of 150 samples was performed in four ways, i. e., 5, 10, 15 and 20 minutes after setting a new configuration, in order to increase the probability of obtaining a more heterogeneous set of samples.