cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.8334762
title: Pipe rheology of wet aqueous application foams

description: Foam application of chemicals to the wet web is currently being developed for the paper and board industry. An important part of this work is to understand the rheology of the used application foams. Polyvinyl alcohol (PVOH) is widely used as a strength additive in paper and board, and it was the main surfactant in this study. The PVOH foam density varied between 100 kg/m<sup>3</sup> and 300 kg/m<sup>3</sup> and the dosage of PVOH varied between 0.5% to 6%. The foam viscosity and slip flow were determined with a pipe rheometer using three pipe diameters. The slip velocity was quantified by recording the foam motion in the vicinity of the wall of an acrylic pipe with a high-speed video camera. A measurement setup was also built for measuring the slip flow indirectly in opaque pipes. General formulas for the foam viscosity and slip flow, based on several physical quantities describing both the foam and the base liquid, were obtained using dimensional analysis. Specifically, dimensionless shear stress and dimensionless wall shear stress were found to be proportional to certain powers of the capillary number and slip capillary number, respectively. The contribution of the slip flow to the total flow rate was significant, especially with lower flow rates when most of the volumetric flow was due to the slip. In the literature, many papers have suggested that there is no slip flow in steel pipes. Our results suggest that this is due to the high pipe roughness used in those works. In our measurements, the slip velocity of a smooth-walled steel pipe was equal to the slip in an acrylic pipe. The obtained viscosity and slip models form a solid basis for developing and running various industrial processes including foam application processes. For new foam recipes, quite a small number of rheological measurements are needed to determine the model parameters.
DOI: 10.5281/zenodo.8334761
title: Pipe rheology of wet aqueous application foams

description: Foam application of chemicals to the wet web is currently being developed for the paper and board industry. An important part of this work is to understand the rheology of the used application foams. Polyvinyl alcohol (PVOH) is widely used as a strength additive in paper and board, and it was the main surfactant in this study. The PVOH foam density varied between 100 kg/m<sup>3</sup> and 300 kg/m<sup>3</sup> and the dosage of PVOH varied between 0.5% to 6%. The foam viscosity and slip flow were determined with a pipe rheometer using three pipe diameters. The slip velocity was quantified by recording the foam motion in the vicinity of the wall of an acrylic pipe with a high-speed video camera. A measurement setup was also built for measuring the slip flow indirectly in opaque pipes. General formulas for the foam viscosity and slip flow, based on several physical quantities describing both the foam and the base liquid, were obtained using dimensional analysis. Specifically, dimensionless shear stress and dimensionless wall shear stress were found to be proportional to certain powers of the capillary number and slip capillary number, respectively. The contribution of the slip flow to the total flow rate was significant, especially with lower flow rates when most of the volumetric flow was due to the slip. In the literature, many papers have suggested that there is no slip flow in steel pipes. Our results suggest that this is due to the high pipe roughness used in those works. In our measurements, the slip velocity of a smooth-walled steel pipe was equal to the slip in an acrylic pipe. The obtained viscosity and slip models form a solid basis for developing and running various industrial processes including foam application processes. For new foam recipes, quite a small number of rheological measurements are needed to determine the model parameters.
DOI: 10.5281/zenodo.8385839
title: MATLAB codes for : "Diagnosis and Prognosis of Faults in High-Speed Aeronautical Bearings with a Collaborative Selection Incremental Deep Transfer Learning Approach".

description: The package contains all the materials needed to reproduce the findings of our paper. The paper is published by MDPI Applied Sciences journal and its details are as follow. Berghout, T.; Benbouzid, M. Diagnosis and Prognosis of Faults in High-Speed Aeronautical Bearings with a Collaborative Selection Incremental Deep Transfer Learning Approach. <em>Appl. Sci.</em> <strong>2023</strong>, <em>13</em>, 10916. https://doi.org/10.3390/app131910916 1) Please you need to download the dataset from original link provided by introductory paper (Please read the above paper to find out about the datset used).<br> 2) Put the data in folders "RawData" for both experments.<br> 3) Please run the files for each experiment as provided, in alphabetical order.
description: {"references": ["Berghout, T.; Benbouzid, M. Diagnosis and Prognosis of Faults in High-Speed Aeronautical Bearings with a Collaborative Selection Incremental Deep Transfer Learning Approach. Appl. Sci. 2023, 13, 10916. https://doi.org/10.3390/app131910916"]}
DOI: 10.5281/zenodo.8385838
title: MATLAB codes for : "Diagnosis and Prognosis of Faults in High-Speed Aeronautical Bearings with a Collaborative Selection Incremental Deep Transfer Learning Approach".

description: The package contains all the materials needed to reproduce the findings of our paper. The paper is published by MDPI Applied Sciences journal and its details are as follow. Berghout, T.; Benbouzid, M. Diagnosis and Prognosis of Faults in High-Speed Aeronautical Bearings with a Collaborative Selection Incremental Deep Transfer Learning Approach. <em>Appl. Sci.</em> <strong>2023</strong>, <em>13</em>, 10916. https://doi.org/10.3390/app131910916 1) Please you need to download the dataset from original link provided by introductory paper (Please read the above paper to find out about the datset used).<br> 2) Put the data in folders "RawData" for both experments.<br> 3) Please run the files for each experiment as provided, in alphabetical order.
description: {"references": ["Berghout, T.; Benbouzid, M. Diagnosis and Prognosis of Faults in High-Speed Aeronautical Bearings with a Collaborative Selection Incremental Deep Transfer Learning Approach. Appl. Sci. 2023, 13, 10916. https://doi.org/10.3390/app131910916"]}
DOI: 10.18712/nsd-nsd2344-v8
title: Norwegian Citizen Panel Round 6, 2016

description: The Norwegian Citizen Panel is a platform for internet surveys of public opinion in important areas of society and politics in Norway. Participants are randomly recruited from the Norwegian population register, and they are encouraged to participate over time. The panel was fielded for the first time the fall of 2013 and as of 2017 the survey is carried out three times a year. The University of Bergen owns and is responsible for the Citizen panel. The company ideas2evidence recruits respondents, produces the survey, and provides documentation of the data. Data is stored and shared by the Norwegian centre for research data (NSD). For access to time series data, or text data, please contact DIGSSCORE. The Norwegian Citizen Panel welcomes research proposals for survey content. More information about calls and other updates are available at www.medborger.uib.no
DOI: 10.25919/g6p2-4v97
title: Parkes observations for project P1054 semester 2023APRS_16

description: With this proposal we ask time to continue our timing follow-up campaign of pulsars discovered with the MeerKAT telescope. Twenty sources have been discovered in targeted observations of Fermi unidentified point sources, one in association with a Supernova Remnant, 13 in the Magellanic Clouds, 71 in Globular Clusters and 74 in a survey of the Galactic plane. A large fraction of the new discoveries are recycled pulsars (including at least one double neutron star system and several 'spider' binaries), or young pulsars. Timing observations have an essential role in exploiting the full potential of any pulsar discovery, allowing the precise measurement of rotational, astrometric and orbital parameters which, in turn, give us powerful tools to improve our understanding of the physics in extreme environments as well as of the population of neutron stars as a whole. The UWL receiver of the Parkes telescope is a sensitive, versatile instrument that is allowing us to successfully time these new sources, in the bright-end of TRAPUM discoveries.
DOI: 10.48366/r642266
title: A catalog of systems papers for tabular data annotation published by SemTab@ISWC since 2019

description: Tabular datasets are constructed by extracting and organizing information from data sources. These data sources can be structured such as databases, Knowledge Graphs (e.g., Wikidata, DBpedia, ORKG), semi-structured such as tables or unstructured such as text in scientific literature. To increase the utility of tabular datasets, they are annotated by matching their content to Knowledge Graphs classes, properties and instances. This is called tabular data annotation or tabular data to knowledge graph matching.


Semantic Table to Knowledge Graph Matching (SemTab) challenge aims at providing a common framework to conduct a systematic evaluation of datasets and systems published by researchers. Thus, since 2019, SemTab@ISWC is publishing researchers' contributions to this research problem. The following comparison table presents all the systems proposed by the SemTab community since 2019. It is built using a template (https://orkg.org/template/R286081), that can be considered as a conceptual model for the semantification of SemTab systems papers using ORKG. In this table, the left panel contains the different comparison criterion used and the right panel the different contributions of the authors.
DOI: 10.17632/5v93bv2xnv.1
title: Polyphasic Identification of Aspergillus section Flavi from grains and chicken feeds

description: Raw data tables used in the Polyphasic Identification of Aspergillus section Flavi from grains and chicken feeds from Malysia and Nigeria
DOI: 10.17632/hd9pf4hmhp.2
title: báscula automática

description: Báscula de pesaje para lisímetro En este repositorio se comparte la información requerida para desarrollar una báscula de pesaje utilizando un micro controlador arduino, una celda de carga de 5 kg de capacidad y un amplificador HX711. El código se desarrolló basado en la librería HX711_ADC 24-Bit Analog-to-Digital Converter for Weight Scales de Olav Kallhovd sept2017. El valor de calibración indicado en el código que se comparte en este repositorio debe ser sustituido por aquel que se determine especificamente para la celda de carga que otros desarrolladores implementen para desarrollar la báscula. Adicionalmente, se incluyen líneas de código para que la celda de carga trabaje en conjunto con una reloj, una memoria mSD y un display LCD 16x2. Para facilitar el montaje de los componentes electrónicos se comparte un archivo para imprimir una tarjeta PCB y un esquema del armazón de acero que se fabricó para el montaje de la celda de carga.
DOI: 10.17632/hd9pf4hmhp.3
title: Báscula para mini lisímetro

description: Báscula de pesaje para lisímetro En este repositorio se comparte la información requerida para desarrollar una báscula de pesaje utilizando un micro controlador arduino, una celda de carga de 5 kg de capacidad y un amplificador HX711. El código se desarrolló basado en la librería HX711_ADC 24-Bit Analog-to-Digital Converter for Weight Scales de Olav Kallhovd sept2017. El valor de calibración indicado en el código que se comparte en este repositorio debe ser sustituido por aquel que se determine especificamente para la celda de carga que otros desarrolladores implementen para desarrollar la báscula. Adicionalmente, se incluyen líneas de código para que la celda de carga trabaje en conjunto con una reloj, una memoria mSD y un display LCD 16x2. Para facilitar el montaje de los componentes electrónicos se comparte un archivo para imprimir una tarjeta PCB y un esquema del armazón de acero que se fabricó para el montaje de la celda de carga.
DOI: 10.17632/58mttpbc7x.1
title: Arab Computational Propaganda on Twitter

description: The database includes five datasets. Three datasets were extracted from a dataset published by Twitter that includes tweets from malicious accounts trying to manipulate public opinion in the Kingdom of Saudi Arabia. We focused on sports and banking topics when extracting data. Although the propagandist tweets were published by malicious accounts, as Twitter stated, the tweets at their level were not classified as propaganda or not. Propagandists usually mix propaganda and non-propaganda tweets in an attempt to hide their identities. Therefore, it was necessary to classify their tweets as propaganda or not, based on the propaganda technique used. Since the datasets are very large, we annotated a sample of 2,100 tweets. As for reliable account data, we were keen to identify reliable Saudi sources. Then, their tweets that discussed the same topics discussed by the malicious users were crawled. There are two datasets for reliable users in sports and banking topics. The dataset is made up of 16,355,558 tweets from propagandist users and 156,524 tweets from reliable users for the time period of January 1, 2019, to December 31, 20202.
DOI: 10.17632/58mttpbc7x.2
title: Arab Computational Propaganda on X (Twitter)

description: The database includes five datasets. Three datasets were extracted from a dataset published by X (Twitter Transparancy websites) that includes tweets from malicious accounts trying to manipulate public opinion in the Kingdom of Saudi Arabia. We focused on sports and banking topics when extracting data. Although the propagandist tweets were published by malicious accounts, as X (Twitter) stated, the tweets at their level were not classified as propaganda or not. Propagandists usually mix propaganda and non-propaganda tweets in an attempt to hide their identities. Therefore, it was necessary to classify their tweets as propaganda or not, based on the propaganda technique used. Since the datasets are very large, we annotated a sample of 2,100 tweets. As for reliable account data, we were keen to identify reliable Saudi sources. Then, their tweets that discussed the same topics discussed by the malicious users were crawled. There are two datasets for reliable users in sports and banking topics. The dataset is made up of 16,355,558 tweets from propagandist users and 156,524 tweets from reliable users for the time period of January 1, 2019, to December 31, 20202.
DOI: 10.17632/58mttpbc7x.3
title: Arab Computational Propaganda on X (Twitter)

description: The database includes three datasets. All of them were extracted from a dataset published by X (Twitter Transparency Websites) that includes tweets from malicious accounts trying to manipulate public opinion in the Kingdom of Saudi Arabia. Although the propagandist tweets were published by malicious accounts, as X (Twitter) stated, the tweets at their level were not classified as propaganda or not. Propagandists usually mix propaganda and non-propaganda tweets in an attempt to hide their identities. Therefore, it was necessary to classify their tweets as propaganda or not, based on the propaganda technique used. Since the datasets are very large, we annotated a sample of 2,100 tweets. The datasets are made up of 16,355,558 tweets from propagandist users focused on sports and banking topics.
DOI: 10.17632/x2rg2mfrw7.1
title: Variation in Racial Disparities in Police Use of Force

description: Replication data for "Variation in Racial Disparities in Police Use of Force" forthcoming in the Journal of Urban Economics. See README files for information. carl.lieberman@census.gov carl.ac
DOI: 10.17632/fhy4m48xkf.1
title: Automatic Commentary Training Speech Synthesis System for Broadcasting

description: Thanks to the rapid progress in deep learning technology, the text-to-speech (TTS) system we developed has achieved the same quality as human speech, enabling us to launch a fully automatic program production system known as “AI Anchor.” The TTS system needs a large amount of speech and label data, but data production costs are high and TTS speakers cannot be easily added. This paper presents a novel TTS method featuring automatic training from broadcast commentary. It uses an approach that allows for a new semi-supervised learning method using an accentual data recognition method specialized for TTS. We have automated the entire training process for generating training data and performing label data recognition from broadcast commentary. In this paper, we present practical examples of automated program production such as an automatic weather forecast system for radio, automatic sports commentary system, and slow and easy-to-understand commentary news using our automated TTS training system based on broadcast commentary.
DOI: 10.17632/hsddc6nmzw.1
title: Organ-specific Immunity: A Tissue Analysis Framework for Investigating Local Immune Responses to SARS-CoV-2. Ng et al.

description: 53 regions-of-interest (ROIs) of spatial transcript data (21 lung, 32 Gut). Each ROI is scaled to have the same 75th percentile (Q3 normalization), and genes that fall below limit of detection in more than 85% of ROIs are not included.
DOI: 10.17632/79zj6yp7k8.1
title: Emerging implications of bacterial biofilm in cancer biology

description: Recent insights have unveiled exciting opportunities to explore the intricate interplay between bacterial biofilms, tumor cells, and the immune system, offering new perspectives on cancer biology. The implications of bacterial biofilms in this context are remarkably multifaceted. Biofilms can promote tumor growth and invasiveness by inducing chronic inflammation, remodeling the extracellular matrix, and modulating the immune response, which promotes cancer development. Recent evidence has illustrated the role of specific bacteria, such as Salmonella typhi in gall bladder cancer, Helicobacter pylori in gastric cancer, and Fusobacterium nucleatum in oral cancer. These studies have revealed that these bacteria are more abundant in cancer patients compared to healthy individuals. Moreover, these bacteria form biofilms and exhibit resistance to cancer therapy. In this review, we intend to explore the recent updates, the myriad influences of various bacteria, and the potential molecular pathways by which bacterial biofilms contribute to cancer development.
DOI: 10.17632/9zrj6vbymy.1
title: Rodencal et al 2023

description: This is supplemental data for Rodencal et al., 2023.
DOI: 10.17632/9zrj6vbymy.2
title: Rodencal et al 2023

description: This is supplemental data for Rodencal et al., 2023.
DOI: 10.17632/9zrj6vbymy.3
title: Rodencal et al 2023

description: This is supplemental data for Rodencal et al., 2023.
DOI: 10.17632/9zrj6vbymy.4
title: Rodencal et al 2023

description: This is supplemental data for Rodencal et al., 2023.
DOI: 10.17632/jkgpz8362b.1
title: Data for: Production- and Consumption-Based Emissions in Carbon Exporters and Importers: A Large Panel Data Analysis for the EKC Hypothesis

description: This document includes the dataset used in the paper "Production- and Consumption-Based Emissions in Carbon Exporters and Importers: A Large Panel Data Analysis for the EKC Hypothesis".
DOI: 10.17632/cfvzwyndmv.1
title: Data for Elucidating the role of tectonics & climate changes in sedimentation patterns of the SW sub-basin of the South China Sea since the Early – Middle Miocene

description: Table 1 Trace element compositions of Site 1433 Table 2 Sr-Nd Isotope composition of Site 1433 Table 3 Zircon U-Pb dating of Site l433 Table 4 Sr-Nd data of the potential sources Table 5 Zircon U-Pb dating of the potential sources
DOI: 10.17632/t4psgftvkf.1
title: Replication - Crozet, Hering and Poncet Looking for the bright side of the China Syndrome: Rising export opportunities and life satisfaction in China

description: This folder contains all do files necessary to replicate the results from the article "Looking for the bright side of the China Syndrome: Rising export opportunities and life satisfaction in China" by Matthieu Crozet, Laura Hering and Sandra Poncet, The World Bank Economic Review, 2023. The archive contains a number of Stata do files necessary for replicating the regression results in the above mentioned article. Do files are in the folder "DofilesWBER". There are two distinct do files that use the various datasets to generate the results tables in the paper and the online appendix.
DOI: 10.17632/32dwj5szvc.1
title: LAGA-assisted Lung Ablation

description: This dataset contains more than 400 ablations of more than 200 patients. RFA, MWA, and water-enhanced needle included.
DOI: 10.17632/m3n5sjxtjy.1
title: Dataset for Detection and Segmentation of the Radiographic Features of Pulmonary Edema

description: Objectives: This comprehensive dataset is well suited for training, evaluating, and using machine learning models to detect, segment, and analyze radiological features associated with pulmonary edema in chest X-ray images. Description: This dataset consists of a collection of chest X-rays extracted from the MIMIC database, carefully collected at the Beth Israel Deaconess Medical Center. In total, it comprises 1000 chest X-rays obtained from 741 patients with features suggestive of edema. These X-rays were carefully selected for manual annotation. The annotations are rich and detailed, covering specific radiological features commonly associated with pulmonary edema, including cephalization, Kerley lines, peribronchial cuffing, pleural effusions, bat wings, and infiltrates. Furthermore, each chest radiograph is thoughtfully assigned a severity category, categorizing it as "no edema", "vascular congestion", "interstitial edema", or "alveolar edema". Annotation Method: The annotation process was meticulously performed by a highly qualified clinician with over 10 years of radiology experience, utilizing both frontal and lateral views for each chest X-ray study. Cephalization and Kerley lines were delineated using polylines, while other features were delineated using binary masks. This methodological approach was carefully chosen to provide a comprehensive data set that would ensure accuracy in subsequent analyses and label assignments. Features and Severity Labels: The dataset includes a wide variety of radiological features, with a total of 4293 annotations. These include: 1. Cephalization: 1656 annotations 2. Kerley lines: 609 annotations 3. Peribronchial cuffings: 30 annotations 4. Pleural Effusions: 317 annotations 5. Bat wings: 1604 annotations 6. Infiltrate: 77 annotations At the same time, the dataset features a wealth of severity labels, totaling 741 cases, thoughtfully categorized as: 1. No edema: 21 cases 2. Vascular congestion: 74 cases 3. Interstitial edema: 51 cases 4. Alveolar edema: 595 cases Notably, all features are represented as bounding boxes, meticulously defined by their respective upper-left (x1; y1) and lower-right (x2; y2) corners. In addition, selected features are provided with masks encoded in base 64 format. To facilitate seamless decoding, we provide a conversion script called " mask_converter.py" that allows the transformation of encoded masks into a versatile numpy array format. This feature improves the usability of the dataset for precise analysis and deep learning applications.
DOI: 10.17632/s5z2sm9pfx.1
title: Projection and uncertainty analysis of future temperature change over the Yarlung Tsangpo-Brahmaputra River Basin based on CMIP6

description: The BMA method was used here to fuse the CMIP6 multi-model data. variable: daily maximum (Tmax) and minimum temperatures (Tmin) Basin: Yarlung Tsangpo-Brahmaputra River Basin scenarios: different future shared socioeconomic path (SSP) scenarios (SSP126, SSP245, SSP370, and SSP585) 9 models: ACCESS-ESM1-5 BCC-CSM2-MR CanESM5 CMCC-CM2-SR5 EC-Earth3-Veg GFDL-ESM4 IPSL-CM6A-LR MIROC6 MRI-ESM2-0