cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.21227/fzj4-8g11
title: Event-Dataset: Temporal information retrieval and text classification dataset

description: Recently, Temporal Information Retrieval (TIR) has grabbed the major attention of the information retrieval community. TIR exploits the temporal dynamics in the information retrieval process and harnesses both textual relevance and temporal relevance to fulfill the temporal information requirements of a user Ur Rehman Khan etal., 2018. The focus time of document is an important temporal aspect which is defined as the time to which the content of the document refers Jatowt etal., 2015; Jatowt etal., 2013; Morbidoni etal., 2018, Khan etal., 2018. To the best of our knowledge, there does not exist any standard benchmark data set (publicly available) that holds the potential to comprehensively evaluate the performance of focus time assessment strategies. Considering these aspects, we have produced the Event-dataset, which is comprised of 35 queries and set of news articles for each query. Each query in the dataset represents a popular event. To annotate these articles into relevant and non-relevant, we have employed a user-study based evaluation method wherein a group of postgraduate students manually annotate the articles into the aforementioned categories. We believe that the generation of such dataset can provide an opportunity for the information retrieval researchers to use it as a benchmark to evaluate focus time assessment methods specifically and information retrieval methods generically.
DOI: 10.21227/c6eq-fx27
title: Event-Dataset: Temporal information retrieval and text classification dataset

description: Recently, Temporal Information Retrieval (TIR) has grabbed the major attention of the information retrieval community. TIR exploits the temporal dynamics in the information retrieval process and harnesses both textual relevance and temporal relevance to fulfill the temporal information requirements of a user Ur Rehman Khan etal., 2018. The focus time of document is an important temporal aspect which is defined as the time to which the content of the document refers Jatowt etal., 2015; Jatowt etal., 2013; Morbidoni etal., 2018, Khan etal., 2018. To the best of our knowledge, there does not exist any standard benchmark data set (publicly available) that holds the potential to comprehensively evaluate the performance of focus time assessment strategies. Considering these aspects, we have produced the Event-dataset, which is comprised of 35 queries and set of news articles for each query. Each query in the dataset represents a popular event. To annotate these articles into relevant and non-relevant, we have employed a user-study based evaluation method wherein a group of postgraduate students manually annotate the articles into the aforementioned categories. We believe that the generation of such dataset can provide an opportunity for the information retrieval researchers to use it as a benchmark to evaluate focus time assessment methods specifically and information retrieval methods generically.
DOI: 10.25592/uhhfdm.1350
title: Hamburg Adult Bilingual LAnguage (HABLA)

description: <strong>This version of the corpus is deprecated and missing files. Please refer to the 0.2 version available here: </strong>https://doi.org/10.25592/uhhfdm.1351
DOI: 10.5517/ccdc.csd.cc11g2k4
title: CCDC 966845: Experimental Crystal Structure Determination

description: Related Article: Guobi Li, Jing Chen, Baiqiao Song, Shaomin Wang, Rongkai Pan, Lingmin Pei, Shenggui Liu, Qingyuan Yang|2020|Sep.Purif.Technol.|256|117781|doi:10.1016/j.seppur.2020.117781
DOI: 10.5517/ccdc.csd.cc2162p1
title: CCDC 1882682: Experimental Crystal Structure Determination

description: Related Article: Feng Wu, Li Zhang, Shifa Zhu|2020|Org.Chem.Front.|7|3387|doi:10.1039/D0QO00825G
DOI: 10.5517/ccdc.csd.cc21rt0n
title: CCDC 1899711: Experimental Crystal Structure Determination

description: Related Article: Zhou Lu, Bhaskar Chilukuri, Chi Yang, Abdel-Monem M. Rawashdeh, Ravi K. Arvapally, Sammer M. Tekarli, Xiaoping Wang, Christian T. Cardenas, Thomas R. Cundari, Mohammad A. Omary|2020|Chemical Science|11|11179|doi:10.1039/D0SC02520H
DOI: 10.5517/ccdc.csd.cc2334w8
title: CCDC 1939449: Experimental Crystal Structure Determination

description: Related Article: Yunhe Lv, Weiya Pu, Xiaoxing Wang|2020|Chem.Commun.|56|12933|doi:10.1039/D0CC05887D
DOI: 10.5517/ccdc.csd.cc23wb4h
title: CCDC 1962676: Experimental Crystal Structure Determination

description: Related Article: Weitao Xu, Huaming Feng, Weiwei Zhao, Chunhua Huang, Carl Redshaw, Zhu Tao, Xin Xiao|2020|Anal.Chim.Acta|1135|142|doi:10.1016/j.aca.2020.09.028
DOI: 10.5517/ccdc.csd.cc25d895
title: CCDC 2007786: Experimental Crystal Structure Determination

description: Related Article: Chao Ye, Wu-Lin Yang, Yufei Zhai, Hua Deng, Xiaoyan Luo, Guoyin Kai, Wei-Ping Deng|2020|Org.Chem.Front.|7|3393|doi:10.1039/D0QO00742K
DOI: 10.5517/ccdc.csd.cc25g3b3
title: CCDC 2009554: Experimental Crystal Structure Determination

description: Related Article: Khaja Mohammad, Vikranth Thaltiri, Nagarjuna Kommu, Anuj A. Vargeese|2020|Chem.Commun.|56|12945|doi:10.1039/D0CC05704E
DOI: 10.5281/zenodo.4084841
title: Exploring the reach of open access content to non-academic audiences

description: Raw data from survey run on nature.com, springerlink and biomedcentral.com in association with VSNU. Relates to publication "Exploring the reach of open access content to non-academic audiences" https://www.doi.org/10.5281/zenodo.4143313
DOI: 10.5281/zenodo.4084840
title: Exploring the reach of open access content to non-academic audiences

description: Raw data from survey run on nature.com, springerlink and biomedcentral.com in association with VSNU. Relates to publication "Exploring the reach of open access content to non-academic audiences" https://www.doi.org/10.5281/zenodo.4143313
DOI: 10.21227/28cx-sr40
title: AURORA, A multi sensor dataset for robotic ocean exploration

description: The current maturity of autonomous underwater vehicles (AUVs) has made their deployment practical and cost-effective, such that many scientific, industrial and military applications now include AUV operations. However, the logistical difficulties and high costs of operating at-sea are still critical limiting factors in further technology development, the benchmarking of new techniques and the reproducibility of research results. To overcome this problem, we present a freely available dataset suitable to test control, navigation, sensor processing algorithms and others tasks. This dataset combines AUV navigation data, side-scan sonar, multibeam echosounder data and seafloor camera image data, and associated sensor acquisition meta-data to provide a detailed characterisation of surveys carried out by the National Oceanography Centre (NOC) in the Greater Haig Fras Marine Conservazion Zone (MCZ) of the U.K in 2015.
DOI: 10.21227/j3te-jb49
title: AURORA, A multi sensor dataset for robotic ocean exploration

description: The current maturity of autonomous underwater vehicles (AUVs) has made their deployment practical and cost-effective, such that many scientific, industrial and military applications now include AUV operations. However, the logistical difficulties and high costs of operating at-sea are still critical limiting factors in further technology development, the benchmarking of new techniques and the reproducibility of research results. To overcome this problem, we present a freely available dataset suitable to test control, navigation, sensor processing algorithms and others tasks. This dataset combines AUV navigation data, side-scan sonar, multibeam echosounder data and seafloor camera image data, and associated sensor acquisition meta-data to provide a detailed characterisation of surveys carried out by the National Oceanography Centre (NOC) in the Greater Haig Fras Marine Conservazion Zone (MCZ) of the U.K in 2015.
DOI: 10.6084/m9.figshare.13191830
title: Phytochemicals isolated from Amazonian Flora

description: All credits to Dr. Rita Saraiva Nunomura and to all students who effectively isolated these substances.
DOI: 10.6084/m9.figshare.13191830.v2
title: Phytochemicals isolated from Amazonian Flora

description: All credits to Dr. Rita Saraiva Nunomura and to all students who effectively isolated these substances.
DOI: 10.6084/m9.figshare.13191830.v1
title: Phytochemicals isolated from Amazonian Flora

description: We believe in the open-science initiative and therefore we organise the structures of several phytochemicals isolated from the Amazonian flora. We credit all efforts to those who isolated them, and thus each structure has its respective reference.
DOI: 10.6084/m9.figshare.13168205
title: Study 1 - Meta-analysis dataset

description: Dataset for the meta-analysis of the published studies on dyslexia treatment 2013-2020<br>
DOI: 10.6084/m9.figshare.13168205.v2
title: Study 1 - Meta-analysis dataset

description: Dataset for the meta-analysis of the published studies on dyslexia treatment 2013-2020<br>
DOI: 10.6084/m9.figshare.13168205.v1
title: Study 1 - Meta-analysis dataset

description: Dataset for the meta-analysis of the published studies on dyslexia treatment 2013-2020<br>
DOI: 10.5284/1083480
title: Russell Pipe Manufactory, Cripplegate, Worcester. (OASIS ID: rogermoo1-395532)

description: A project to determine the scale and design of the clay tobacco pipe kiln in Worcester. Archive and cartography evidence is strong but details less so. Additionally it is hoped to find a bulk assemblage of finished clay pipes made during the period 1818 to 1868 and engage the public with a piece of Worcester Industrial Heritage.
DOI: 10.14768/7f37269b-7e29-42de-a365-139e703a5fc4
title: Simulations of the HDO cycle with LMD Mars GCM

description: We present here simulations of the HDO cycle on Mars, using the LMD Mars GCM. They show the water and HDO cycles, following the reimplementation of tracers related to HDO in the model. In these simulations, the cloud formation is done assuming a simplified scheme, without the details of the condensation nuclei. Clouds are not radiatively active. Two dust scenarios are available: one for the climatology scenario (representative of an average year on Mars), one for the Martian Year 34, during which a global dust storm occured. There are two types of files: one contains column integrated variables, useful for seasonal study. The other are variables rescaled by pressure levels. Finally a file containing the area of each column of the GCM is provided, for example for planetary average computations.
DOI: 10.6084/m9.figshare.13200332.v1
title: R0197_20171213a_videos

description: Rat 0197, skilled reaching data collected in Leventhal laboratory by Alexandra Bova, alternating stimulation session
DOI: 10.21227/t9xz-rd16
title: Roughness of Milling Process

description: This dataset is used to develop an algorithm for evaluating machining quality. When machining a workpiece in a milling process, vibration signals can be recorded by a 3-axis accelerometer, which is attached on the spindle of a CNC milling machine. To evaluate machining quality, the vibration signals can be segmented and extracted the corresponding features, in the time, frequency, and time-frequency domains. After serving with the features, a model can be developed to estimate the machining quality, such as the roughness of a workpiece. The sensing data collected from several tools are provided and recorded in csv format to validate a developed model.
DOI: 10.6084/m9.figshare.13200332
title: R0197_20171213a_videos

description: Rat 0197, skilled reaching data collected in Leventhal laboratory by Alexandra Bova, alternating stimulation session
DOI: 10.21227/efcy-cd38
title: Roughness of Milling Process

description: This dataset is used to develop an algorithm for evaluating machining quality. When machining a workpiece in a milling process, vibration signals can be recorded by a 3-axis accelerometer, which is attached on the spindle of a CNC milling machine. To evaluate machining quality, the vibration signals can be segmented and extracted the corresponding features, in the time, frequency, and time-frequency domains. After serving with the features, a model can be developed to estimate the machining quality, such as the roughness of a workpiece. The sensing data collected from several tools are provided and recorded in csv format to validate a developed model.
DOI: 10.21227/nry4-t596
title: Roughness of Milling Process

description: This dataset is used to develop an algorithm for evaluating machining quality. When machining a workpiece in a milling process, vibration signals can be recorded by a 3-axis accelerometer, which is attached on the spindle of a CNC milling machine. To evaluate machining quality, the vibration signals can be segmented and extracted the corresponding features, in the time, frequency, and time-frequency domains. After serving with the features, a model can be developed to estimate the machining quality, such as the roughness of a workpiece. The sensing data collected from several tools are provided and recorded in csv format to validate a developed model.
DOI: 10.21227/dg9c-m972
title: Roughness of Milling Process

description: This dataset is used to develop an algorithm for evaluating machining quality. When machining a workpiece in a milling process, vibration signals can be recorded by a 3-axis accelerometer, which is attached on the spindle of a CNC milling machine. To evaluate machining quality, the vibration signals can be segmented and extracted the corresponding features, in the time, frequency, and time-frequency domains. After serving with the features, a model can be developed to estimate the machining quality, such as the roughness of a workpiece. The sensing data collected from several tools are provided and recorded in csv format to validate a developed model.
DOI: 10.17179/excli2020-2740/supplementary_data
title: iTRAQ-based proteomics reveals serum protein changes in hypertensive rats induced by a high-salt diet

description: High-salt diets may increase both hypertension and risk of cardiovascular diseases. Although high-salt diets can result in hypertension and impaired vascular function, the molecular mechanisms underlying these dysfunctions are not fully known. Thus, the aims of the present study were to identify key proteins and their signaling pathways and associated molecular mechanisms that may contribute to, as well as be potential biomarkers of, the pathogenesis of hypertension-related cardiovascular diseases. To that end, the present study identified and quantitated serum proteins that were differentially expressed in male rats fed regular chow (n = 4) and those fed a high-salt diet (n = 4) to induce hypertension. The serum was collected from both groups, and the proteins differentially expressed in the serum were identified and quantitated using isobaric tags for relative and absolute quantitation combined with liquid chromatography–tandem mass spectrometry. Of 396 identified proteins, 24 were differentially expressed between the groups: 19 proteins were significantly (P &lt; 0.05) upregulated (&gt; 1.2 fold change), and 5 were significantly downregulated (&lt; 0.8 fold change). Gene ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses indicated that these differentially expressed proteins may contribute to cardiovascular diseases via the roles they play in endothelial function, vascular remodeling, the coagulation cascade, and the complement system. In addition, phagosome processes and the integrin-associated focal adhesion signaling pathway were determined to be potential underlying molecular mechanisms. The key proteins identified in this study warrant further development as new therapeutic targets or biomarkers of cardiovascular diseases associated with high-salt diet-induced hypertension.
description: EXCLI Journal; 19:Doc1496; ISSN 1611-2156
DOI: 10.15468/6s25uj
title: Checklist of algae inhabiting the basidiocarps of wood-decaying Basidiomycetes in the Central Ural

description: This dataset presents a list of 57 algae species inhabiting the basidiocarps of wood-decaying Basidiomycetes in the forests of the Central Ural. It includes 54 species of eukaryotic (45 ˗ Chlorophyta, 5 ˗ Charophyta, 4 ˗ Ochrophyta) and 3 prokaryotic algae. Chlorophyta is the obligate component of mycobiont algal communities, all other algae groups are their optional part. Among the mycetobiont algae, unicellular coccoid algae prevail (48%), other types are less common: trichal (25%), colonial (18%), and monadic (9%). Among algae are no specialized mycobiont species and all of them are widespread soil and epiphytic algae as well as photobionts of ascolichens, which demonstrates the facultative nature of their symbiotic relationship with wood-decaying fungi. As a rule, algae inhabit annual basidiocarps and they do not manifest specificity to fungi species. The widest host-fungi spectrum of Pseudococcomyxa simplex occurs in the basidiocarps of 15 species. Stichococcus bacillaris and Interfilum terricola were found in the basidiocarps of 13 and 11 fungi species correspondingly. The largest numbers of algae species were found in the basidiocarps of Cerrena unicolor (24), Trametes gibbosa (12), Trichaptum abietinum (11), T. biforme (22), T. fuscoviolaceum (17), Stereum hirsutum (11) and S. subtomentosum (19).
DOI: 10.21227/p8c8-d324
title: Roughness of Milling Process

description: This dataset is used to develop an algorithm for evaluating machining quality. When machining a workpiece in a milling process, vibration signals can be recorded by a 3-axis accelerometer, which is attached on the spindle of a CNC milling machine. To evaluate machining quality, the vibration signals can be segmented and extracted the corresponding features, in the time, frequency, and time-frequency domains. After serving with the features, a model can be developed to estimate the machining quality, such as the roughness of a workpiece. The sensing data collected from several tools are provided and recorded in csv format to validate a developed model.
DOI: 10.21227/g6vb-j459
title: ExoNet Database: Wearable Camera Images of Human Locomotion Environments

description: Abstract: Advances in computer vision and artificial intelligence are allowing researchers to develop environment recognition systems for powered lower-limb exoskeletons and prostheses. However, small-scale and private training datasets have impeded the widespread development and dissemination of image classification algorithms for classifying human walking environments. To address these limitations, we developed “ExoNet” - the first open-source, large-scale hierarchical database of high-resolution wearable camera images of human locomotion environments. Unparalleled in scale and diversity, ExoNet contains over 5.6 million RGB images of different indoor and outdoor real-world walking environments, which were collected using a lightweight wearable camera system throughout the summer, fall, and winter seasons. Approximately 923,000 images in ExoNet were human-annotated using a 12-class hierarchical labelling architecture. Available publicly through IEEE DataPort, ExoNet offers an unprecedented communal platform to train, develop, and compare next-generation image classification algorithms for human locomotion environment recognition. Besides the control of powered lower-limb exoskeletons and prostheses, applications of ExoNet could extend to humanoids and autonomous legged robots.Reference: Laschowski B, McNally W, Wong A, and McPhee J. (2020). ExoNet Database: Wearable Camera Images of Human Locomotion Environments. Frontiers in Robotics and Artificial Intelligence. DOI: 10.3389/frobt.2020.562061.
DOI: 10.21227/4nfc-2s89
title: ExoNet Database: Wearable Camera Images of Human Locomotion Environments

description: Abstract: Advances in computer vision and artificial intelligence are allowing researchers to develop environment recognition systems for powered lower-limb exoskeletons and prostheses. However, small-scale and private training datasets have impeded the widespread development and dissemination of image classification algorithms for classifying human walking environments. To address these limitations, we developed “ExoNet” - the first open-source, large-scale hierarchical database of high-resolution wearable camera images of human locomotion environments. Unparalleled in scale and diversity, ExoNet contains over 5.6 million RGB images of different indoor and outdoor real-world walking environments, which were collected using a lightweight wearable camera system throughout the summer, fall, and winter seasons. Approximately 923,000 images in ExoNet were human-annotated using a 12-class hierarchical labelling architecture. Available publicly through IEEE DataPort, ExoNet offers an unprecedented communal platform to train, develop, and compare next-generation image classification algorithms for human locomotion environment recognition. Besides the control of powered lower-limb exoskeletons and prostheses, applications of ExoNet could extend to humanoids and autonomous legged robots.Reference: Laschowski B, McNally W, Wong A, and McPhee J. (2020). ExoNet Database: Wearable Camera Images of Human Locomotion Environments. Frontiers in Robotics and AI. DOI: 10.3389/frobt.2020.562061.
DOI: 10.6084/m9.figshare.13200026
title: PPC data - time-shuffled - catch questions

description: This dataset belongs to the Collection:<br>ter Wal, Marije; Linde Domingo, Juan; Lifanov, Julia; Roux, Frederic; Kolibius, Luca; Gollwitzer, Stephanie; et al. (2020): Data for: Theta rhythmicity governs the timing of behavioural and hippocampal responses in humans specifically during memory-dependent tasks. figshare. Collection. https://doi.org/10.6084/m9.figshare.c.5192567<br><br><br>The dataset contains the following data:<br>Time-shuffled PPC data (100 repetitions) from hippocampal microwire recordings from 10 iEEG patients while they answered catch questions during the retrieval phase of a memory task.<br>The PPC data have been fully anonymized to protect the identity of the patients: information that could reveal the implantation scheme of specific patients has been removed. To this end, the original channel labels have been removed and replaced by bundle IDs.<br>For more details about the data please see the Collection.<br><br>
DOI: 10.5281/zenodo.1409790
title: Dataset of Cervical Cell Images for the Study of Changes Associated with Malignancy in Conventional Pap Test

description: This data set was approved by CEP, a human-research ethics committee {Comitê de Ética em Pesquisa de Campinas}, Brazil <em>(CAAE approval number: 71277217.6.0000.5404) </em> Cervical cancer prevention campaign was carried out at the University of Campinas (Brazil), where 71 women were treated. For this study, six women were chosen: non-pre-menopausal, non-pregnant and between the ages of 25 and 40 years. Samples diagnosed with normal squamous lesions, atypia in squamous cells of undetermined significance (AC-US), low-grade squamous intraepithelial lesion LEI (changes associated with HPV infection or light dislocation (NIC 1)), and immature squamous metaplasia, were chosen. All samples were collected before treatment. The patients were anonymized and assigned a unique identifier. The criterion to limit the number of plates used in this study is related to the large amount of data to be processed and the computational cost necessary for this process. Raw data sets are available as CSV files. Each data was numbered to include the identification of the meta-data, along with the tag of the images following a sequence. For example, the data file<em> “ 01-CAP091868-MORF.csv ”</em> has the prefix 01 that refers to the sequential numbering of the files with the data from the digitized slide. The data set contains 102 digitized images of the human papilloma examination of 7 different patients. They were segmented 962