cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/xb5z829g3v.1
title: Death from infection among cancer patients - Supplementary Information

description: Supplementary Information and Supplementary Table 1 for "Death from infection among cancer patients"
DOI: 10.17632/ygtxz64z4h.1
title: Impostorism

description: Imposter syndrome (IS) refers to a sensation of not belonging, out-of-place-ness, and the conviction that one's competence, success is fraudulent and inauthentic. It's often enclosed as an individual problem to be overcome, for example, by keeping a list of achievements to remind oneself of evidenced accomplishments, by talking about one's confusions and precariousness. We aimed to evaluate the prevalence of imposter syndrome, explore the frequency distribution of imposter syndrome in different institutions, and assess the factor contributing to imposter syndrome among medical college students.
DOI: 10.17632/bnxjdwhzh6.1
title: ED-ER

description: Data from experience sampling study exploring the association between negative emotion differentiation and emotion regulation.
DOI: 10.5281/zenodo.4817464
title: Supplementary Material for "Snail Mail Beats Email Any Day: On Effective Operator Security Notifications in the Internet"

description: This record contains supplementary material for the paper "Snail Mail Beats Email Any Day: On Effective Operator Security Notifications in the Internet", published at ARES 2021. It includes the (anonymized) dataset and code required to reproduce the tables and figures of the paper, as well as the code used to collect the dataset. The text of the emails and letters is included in the appendix of the paper and thus not reproduced here.
DOI: 10.5281/zenodo.4817463
title: Supplementary Material for "Snail Mail Beats Email Any Day: On Effective Operator Security Notifications in the Internet"

description: This record contains supplementary material for the paper "Snail Mail Beats Email Any Day: On Effective Operator Security Notifications in the Internet", published at ARES 2021. It includes the (anonymized) dataset and code required to reproduce the tables and figures of the paper, as well as the code used to collect the dataset. The text of the emails and letters is included in the appendix of the paper and thus not reproduced here.
DOI: 10.17632/6n2ccps2jk.2
title: Third-Person Perspectives in Photographs Influence Visual and Spatial Perspectives during Subsequent Memory Retrieval

description: Processed data files
DOI: 10.17632/6nstrjxjvv.1
title: Milos Marius Cristian_Impact of MiFID II on the market volatility

description: Impact of MiFID II on the market volatility
DOI: 10.17632/hm4vp824pz.2
title: Using MATLAB to stage the severity of dementia: a fuzzy-rule based approach to CDR instrument

description: MATLAB codes for a fuzzy rule system for recognition and staging the severity of dementia based on CDR staging dementia rating. The proposed fuzzy-approach to the CDR was developed using the MATLAB Fuzzy Logic Toobox. A user-friendly graphical interface was also developed using the MATLAB GUIs. In what follows, we provide codes and instructions to help any interested user to run the programs.
DOI: 10.17632/v2b3f4t52j.1
title: Teacher's professional competence role in teaching natural scientific concepts

description: This article describes the role of teacher’s professional competence in teaching biology, geography, chemistry and physics; and formation of natural science concepts in the learning process. The scientific concept formation based on the concept's purpose and goals. With the help of keywords, abstract symbols, geometric shapes, letter designations, students study the content of the material on specific biology, geography, chemistry and physics topics and work in pairs and in groups.
DOI: 10.17632/j5wc96m2yg.1
title: LINF_130010100

description: Protein of unknown function (DUF1014); Leishmania infantum
DOI: 10.17632/yx63wzxvcx.1
title: LINF_130009900

description: ATP-dependent RNA helicase; Leishmania infantum
DOI: 10.5281/zenodo.4733698
title: simFSD-18k

description: Created By Félix Gontier and Mathieu Lagrange, LS2N, CNRS, Ecole Centrale Nantes Contact : mathieu.lagrange@cnrs.fr If used for research, please refer to: <pre>@article{gontier2021training, title={Polyphonic training set synthesis improves self-supervised urban sound classification}, author={Félix Gontier and Vincent Lostanlen, and Mathieu Lagrange and Nicolas Fortin and Jean-Francois Petiot and Catherine Lavandier}, journal={The Journal of the Acoustical Society of America}, year={2021}, publisher={Acoustical Society of America} } </pre> simFSD-18k is a dataset of synthetic acoustic scenes made with Freesound and Librispeech samples}<br> simFSD-18k contains 400 scenes acoustic scenes of duration equal to 45 seconds.<br> We synthesized these polyphonic scenes via the simScene software, based on FSD-2k.<br> The total duration of the dataset is equal to 18k seconds, i.e., the same as simFSD-18k. The total duration of the dataset is equal to 18k seconds, i.e., five hours.The audio is made available as third octave spectral data, see demoTob.zip for an implementation of its computation from audio in Python. &gt;&gt;&gt; a=numpy.load('simFSD-18k_training_spectralData.npy') &gt;&gt;&gt; a.shape (280, 351, 29) &gt;&gt;&gt; a=numpy.load('simFSD-18k_training_presence.npy') &gt;&gt;&gt; a.shape (280, 344, 3) The 3 dimensions corresponds to the sceneId, the frameId (time), the sourceId (traffic, voice, birds). Annotation is provided as a binary indicator of source presence for one second, that is 8 consecutive 125 ms frames with a hop of one frame.
DOI: 10.5281/zenodo.4733697
title: simFSD-18k

description: Created By Félix Gontier and Mathieu Lagrange, LS2N, CNRS, Ecole Centrale Nantes Contact : mathieu.lagrange@cnrs.fr If used for research, please refer to: <pre>@article{gontier2021training, title={Polyphonic training set synthesis improves self-supervised urban sound classification}, author={Félix Gontier and Vincent Lostanlen, and Mathieu Lagrange and Nicolas Fortin and Jean-Francois Petiot and Catherine Lavandier}, journal={The Journal of the Acoustical Society of America}, year={2021}, publisher={Acoustical Society of America} } </pre> simFSD-18k is a dataset of synthetic acoustic scenes made with Freesound and Librispeech samples}<br> simFSD-18k contains 400 scenes acoustic scenes of duration equal to 45 seconds.<br> We synthesized these polyphonic scenes via the simScene software, based on FSD-2k.<br> The total duration of the dataset is equal to 18k seconds, i.e., the same as simFSD-18k. The total duration of the dataset is equal to 18k seconds, i.e., five hours.The audio is made available as third octave spectral data, see demoTob.zip for an implementation of its computation from audio in Python. &gt;&gt;&gt; a=numpy.load('simFSD-18k_training_spectralData.npy') &gt;&gt;&gt; a.shape (280, 351, 29) &gt;&gt;&gt; a=numpy.load('simFSD-18k_training_presence.npy') &gt;&gt;&gt; a.shape (280, 344, 3) The 3 dimensions corresponds to the sceneId, the frameId (time), the sourceId (traffic, voice, birds). Annotation is provided as a binary indicator of source presence for one second, that is 8 consecutive 125 ms frames with a hop of one frame.
DOI: 10.5281/zenodo.4889729
title: Video Recommendations Based on Visual Features Extracted with Deep Learning

description: The dataset contains visual features extracted from 12875 movie trailers. The visual features are extracted from key-frames of movie trailers with the VGG-19 CNN, pre-trained on ImageNet. Movies in the datset are identified by their MovieLens movieId.<br> Features_sparse.zip contains the 4096-dimensional feature vectors of each key-frame from every movie. Visual labels.zip contains the1000 dimensional label feature vectors of each key-frame from every movie. DeepCineProp-f.p has combined the label features of each movie into a vector space model with the use of tf-idf. CineSub.p contains the subtitles of each movie represented in a vector space model pre-processed with various nlp techniques and produced using tf-idf. Abstract: <br> When a movie is uploaded to a movie Recommender System (e.g., YouTube), the system can exploit various forms of descriptive features (e.g., tags and genre) in order to generate personalized recommendation for users. However, there are situations where the descriptive features are missing or very limited and the system may fail to include such a movie in the recommendation list, known as Cold-start problem. This thesis investigates recommendation based on a novel form of content features, extracted from movies, in order to generate recommendation for users. Such features represent the visual aspects of movies, based on Deep Learning models, and hence, do not require any human annotation when extracted. The proposed technique has been evaluated in both offline and online evaluations using a large dataset of movies. The online evaluation has been carried out in a evaluation framework developed for this thesis. Results from the offline and online evaluation (N=150) show that automatically extracted visual features can mitigate the cold-start problem by generating recommendation with a superior quality compared to different baselines, including recommendation based on human-annotated features. The results also point to subtitles as a high-quality future source of automatically extracted features.
DOI: 10.17632/6v8rwzd38s.1
title: Final pit limit-block model

description: This database provides the final pit limit block model used in following article. ''Optimization of Open-Pit Mine Production Scheduling Considering Optimum Transportation System between Truck haulage and Semi-Mobile In-Pit Crushing and Conveying System''
DOI: 10.5281/zenodo.4889728
title: Video Recommendations Based on Visual Features Extracted with Deep Learning

description: The dataset contains visual features extracted from 12875 movie trailers. The visual features are extracted from key-frames of movie trailers with the VGG-19 CNN, pre-trained on ImageNet. Movies in the datset are identified by their MovieLens movieId.<br> Features_sparse.zip contains the 4096-dimensional feature vectors of each key-frame from every movie. Visual labels.zip contains the1000 dimensional label feature vectors of each key-frame from every movie. DeepCineProp-f.p has combined the label features of each movie into a vector space model with the use of tf-idf. CineSub.p contains the subtitles of each movie represented in a vector space model pre-processed with various nlp techniques and produced using tf-idf. Abstract: <br> When a movie is uploaded to a movie Recommender System (e.g., YouTube), the system can exploit various forms of descriptive features (e.g., tags and genre) in order to generate personalized recommendation for users. However, there are situations where the descriptive features are missing or very limited and the system may fail to include such a movie in the recommendation list, known as Cold-start problem. This thesis investigates recommendation based on a novel form of content features, extracted from movies, in order to generate recommendation for users. Such features represent the visual aspects of movies, based on Deep Learning models, and hence, do not require any human annotation when extracted. The proposed technique has been evaluated in both offline and online evaluations using a large dataset of movies. The online evaluation has been carried out in a evaluation framework developed for this thesis. Results from the offline and online evaluation (N=150) show that automatically extracted visual features can mitigate the cold-start problem by generating recommendation with a superior quality compared to different baselines, including recommendation based on human-annotated features. The results also point to subtitles as a high-quality future source of automatically extracted features.
DOI: 10.17632/6g9t446prn.1
title: SPIMS data

description: SPIMS data includes the raw data of entire and specific m/z during the experiments.
DOI: 10.17632/xv3vs3hsxs.1
title: Data in Brief_SEJ-D-21-01076

description: Raw data related to the following manuscript: N. Narudin, P. Ekanayake, Y.W. Soon, H. Nakajima, C.M. Lim The submitted manuscript titled: ‘Enhanced propertied of low-cost carbon black-graphite counter electrode in DSSC by incorporating binders’,. Solar Energy, In Press.
DOI: 10.17632/xknf82tbts.1
title: leafmavis20210601

description: Data for music frogs
DOI: 10.17632/zg84vn34ny.2
title: Aeromagnetic data of North-Eastern Morocco

description: According to the Ministry of Energy and Mines, the aeromagnetic surveys used were acquired during the geophysical airborne campaign made in NEM. Measurements were done for three different zones: the Rif at the North, High Plateaus (HP) at the East, and Middle Atlas (MA) at the West. Moreover, aeromagnetic surveys were flown at different flight altitudes; Guercif at 2600 m, Dedbou at 1700 m and Mekkam at 1829 m and along with different flight directions.
DOI: 10.17632/47x8kvzvxs.1
title: Arginine monomethylation by PRMT7 controls MAVS-mediated antiviral innate immunity. Zhu et al.

description: Original iamges
DOI: 10.17632/3bty7tf4fs.1
title: Data from: Effects of rice-field abandonment rates on bird communities in mixed farmland-woodland landscapes in Japan

description: Farmland abandonment can be a significant driver of biodiversity change in many parts of the world. Knowledge of the ecological impact of farmland abandonment at the landscape scale is particularly limited in Asia. We investigated how rice-field abandonment impacts bird diversity (i.e. species richness and composition) during the breeding and wintering seasons. Birds were surveyed in 31 grids (1 × 1 km) in rice ecosystems of central Japan, 16 of which were dominated by farmland while the others were surrounded by woodland. In each landscape type, survey grids were selected to ensure a broad range of abandonment rates, from fully cultivated to largely abandoned sites. Multi-species occupancy models showed that occupancy probabilities were associated with linear and quadratic terms of the abandonment rate, resulting in the highest predicted community-level occupancies and species richness at moderate abandonment rates (51.5‒71%, depending on the season and surrounding landscapes, with the highest percentage in woodland landscapes in winter). Community composition was most associated with surrounding landscapes (i.e. woodland or farmland), followed by the abandonment rate. These results indicate the importance of habitat heterogeneity, related to moderate levels of farmland abandonment, in enhancing bird diversity in both farmland and woodland landscapes. Our findings illustrate the necessity for quantitative measures of farmland abandonment at landscape scales for understanding their nonlinear effects on farmland biodiversity. We suggest that agri-environmental schemes should consider the benefits of enhancing farmland mosaics at landscape scales, especially for small-scale farming in areas where farmland abandonment is accelerating.
DOI: 10.17632/hh4hhn6ny8.1
title: CTD Data over a Repeated Section in the Vema Channel

description: This dataset contains CTD casts at repeated sections across the Vema Channel in the South Atlantic approximately along 31°12' S between longitudes 39°18.0' W and 39°30.0' W. The Vema Channel connects the deep-water parts of the Argentine and Brazil basins. The densest and coldest Antarctic Bottom Water spreads through this channel. The depths of the Vema Channel exceed 4600 m. Its width at its narrowest part is approximately 15 km. The channel was discovered in the 1950s and hydrological measurements began in 1972. The CTD-casts in the region of the standard section across the Vema Channel at latitude 31°12' S have been made 25 times from 1991 to 2020. In some years, a section of 3–6 stations was carried out, sometimes only one station at 31°12' S, 39°18' W was occupied. In this dataset, we present only the data of ten Russian sections.
DOI: 10.5281/zenodo.4730389
title: FSD-2k

description: Created By Félix Gontier and Mathieu Lagrange, LS2N, CNRS, Ecole Centrale Nantes Contact : mathieu.lagrange@cnrs.fr If used for research, please refer to: <pre>@article{gontier2021training, title={Polyphonic training set synthesis improves self-supervised urban sound classification}, author={Félix Gontier and Vincent Lostanlen, and Mathieu Lagrange and Nicolas Fortin and Jean-Francois Petiot and Catherine Lavandier}, journal={The Journal of the Acoustical Society of America}, year={2021}, publisher={Acoustical Society of America} } </pre> FSD-2k contains about 200 monophonic audio clips collected from online resources, which are unrelated to the city of Lorient: Freesound for birds and traffic and Librispeech for voice.<br> <br> The total duration of the dataset is of the order of 2.4k seconds, i.e., 40 minutes. Each audio samples are cut into one or several 3 seconds parts, each resulting into spectrograms of size 23x29, leading to a dataset of 609 spectrograms. Low volume amorphic background noise recordings is added and the cut audio sample is centered within the 3 seconds if shorter. &gt;&gt; import numpy as np &gt;&gt; s=np.load('FSD-2k_train_spectralData.npy') &gt;&gt; print(s.shape) (609, 23, 29) The three dimensions respectively corresponds to the sceneId, the frameId (time), and the spectralId (frequency). &gt;&gt; a=np.load('FSD-2k_train_presence.npy') &gt;&gt; print(a.shape) (609, 16, 3) The 3 dimensions corresponds to the sceneId, the frameId (time), the sourceId (traffic, voice, birds). Annotation is provided as a binary indicator of source presence for one second, that is 8 consecutive 125 ms frames with a hop of one frame.
DOI: 10.17632/4ydrxtrhrk.1
title: A-LRYNGO_Sim_STUDY

description: The aim of this study was to determine which of four laryngoscopes, including A-LRYNGO, a newly developed channel-type video laryngoscope with an embedded artificial intelligence-based glottis guidance system, is appropriate for tracheal intubation training in novice medical students wearing PPE.
DOI: 10.17632/4ydrxtrhrk.2
title: A-LRYNGO_Sim_STUDY

description: The aim of this study was to determine which of four laryngoscopes, including A-LRYNGO, a newly developed channel-type video laryngoscope with an embedded artificial intelligence-based glottis guidance system, is appropriate for tracheal intubation training in novice medical students wearing PPE.
DOI: 10.17632/pt97s4c5g3.1
title: COVID-19 infection rates

description: COVID-19 infection rate data
DOI: 10.5281/zenodo.4733681
title: augCENSE-18k

description: Created By Félix Gontier and Mathieu Lagrange, LS2N, CNRS, Ecole Centrale Nantes Contact : mathieu.lagrange@cnrs.fr If used for research, please refer to: <pre>@article{gontier2021training, title={Polyphonic training set synthesis improves self-supervised urban sound classification}, author={Félix Gontier and Vincent Lostanlen, and Mathieu Lagrange and Nicolas Fortin and Jean-Francois Petiot and Catherine Lavandier}, journal={The Journal of the Acoustical Society of America}, year={2021}, publisher={Acoustical Society of America} } </pre> augCENSE-18k is a derivative of CENSE-2k, obtained by time stretching and pitch shifting audio clips of the \emph{voice} and \emph{birds} classes at random.<br> The total duration of the dataset is equal to 18k seconds, i.e., the same as simCENSE-18k, with balanced material over classes. Each audio samples are cut into one or several 3 seconds parts, each resulting into spectrograms of size 23x29, leading to a dataset of 609 spectrograms. Low volume amorphic background noise recordings is added and the cut audio sample is centered within the 3 seconds if shorter. &gt;&gt;&gt; a=numpy.load('augCENSE-18k_train_spectralData.npy') &gt;&gt;&gt; a.shape (4421, 23, 29) &gt;&gt;&gt; a=numpy.load('augCENSE-18k_train_presence.npy') &gt;&gt;&gt; a.shape (4421, 16, 3) The 3 dimensions corresponds to the sceneId, the frameId (time), the sourceId (traffic, voice, birds). Annotation is provided as a binary indicator of source presence for one second, that is 8 consecutive 125 ms frames with a hop of one frame.
DOI: 10.5281/zenodo.4733680
title: augCENSE-18k

description: Created By Félix Gontier and Mathieu Lagrange, LS2N, CNRS, Ecole Centrale Nantes Contact : mathieu.lagrange@cnrs.fr If used for research, please refer to: <pre>@article{gontier2021training, title={Polyphonic training set synthesis improves self-supervised urban sound classification}, author={Félix Gontier and Vincent Lostanlen, and Mathieu Lagrange and Nicolas Fortin and Jean-Francois Petiot and Catherine Lavandier}, journal={The Journal of the Acoustical Society of America}, year={2021}, publisher={Acoustical Society of America} } </pre> augCENSE-18k is a derivative of CENSE-2k, obtained by time stretching and pitch shifting audio clips of the \emph{voice} and \emph{birds} classes at random.<br> The total duration of the dataset is equal to 18k seconds, i.e., the same as simCENSE-18k, with balanced material over classes. Each audio samples are cut into one or several 3 seconds parts, each resulting into spectrograms of size 23x29, leading to a dataset of 609 spectrograms. Low volume amorphic background noise recordings is added and the cut audio sample is centered within the 3 seconds if shorter. &gt;&gt;&gt; a=numpy.load('augCENSE-18k_train_spectralData.npy') &gt;&gt;&gt; a.shape (4421, 23, 29) &gt;&gt;&gt; a=numpy.load('augCENSE-18k_train_presence.npy') &gt;&gt;&gt; a.shape (4421, 16, 3) The 3 dimensions corresponds to the sceneId, the frameId (time), the sourceId (traffic, voice, birds). Annotation is provided as a binary indicator of source presence for one second, that is 8 consecutive 125 ms frames with a hop of one frame.
DOI: 10.17632/t8wfh63ygc.1
title: LINF_130010400

description: protein of unknown function - conserved; Leishmania infantum
DOI: 10.5517/ccdc.csd.cc1jhb8m
title: CCDC 1414910: Experimental Crystal Structure Determination

description: Related Article: Jinhuan Dong, Lei Wang, Haoyue Li, Xinrong Leng, Xiaoyu Guo, Zhongyan Hu, Xianxiu Xu|2021|Org.Chem.Front.|8|2595|doi:10.1039/D1QO00132A
DOI: 10.5517/ccdc.csd.cc1qbsxr
title: CCDC 1589305: Experimental Crystal Structure Determination

description: Related Article: Fanny Cacheux, Géraldine Le Goff, Jamal Ouazzani, Jérôme Bignon, Pascal Retailleau, Angela Marinetti, Arnaud Voituriez, Jean-François Betzer|2021|Org.Chem.Front.|8|2449|doi:10.1039/D1QO00268F
DOI: 10.5517/ccdc.csd.cc23g0j4
title: CCDC 1949885: Experimental Crystal Structure Determination

description: Related Article: Juan Li, Jing Wang, Zhenzhen Wu, Shanshan Tao, Donglin Jiang|2021|Angew.Chem.,Int.Ed.|60|12918|doi:10.1002/anie.202101400
DOI: 10.17632/sfsvzm2pwn.1
title: LINF_130010600

description: 40S ribosomal protein S12; Leishmania infantum
DOI: 10.5517/ccdc.csd.cc24zxcf
title: CCDC 1995915: Experimental Crystal Structure Determination

description: Related Article: Yashwant Bhaskar Pandit, Yan-Ting Jiang, Jia-Jyun Jian, Tai-Chi Chen, Tung-Chun Kuo, Mu-Jeng Cheng, Rai-Shung Liu|2021|Org.Chem.Front.|8|2563|doi:10.1039/D1QO00026H
DOI: 10.17632/yvkrwzfvc9.1
title: LINF_130010700

description: protein of unknown function - conserved; Leishmania infantum
DOI: 10.5517/ccdc.csd.cc250kzr
title: CCDC 1996554: Experimental Crystal Structure Determination

description: Related Article: Yashwant Bhaskar Pandit, Yan-Ting Jiang, Jia-Jyun Jian, Tai-Chi Chen, Tung-Chun Kuo, Mu-Jeng Cheng, Rai-Shung Liu|2021|Org.Chem.Front.|8|2563|doi:10.1039/D1QO00026H
DOI: 10.5517/ccdc.csd.cc250l82
title: CCDC 1996563: Experimental Crystal Structure Determination

description: Related Article: Yashwant Bhaskar Pandit, Yan-Ting Jiang, Jia-Jyun Jian, Tai-Chi Chen, Tung-Chun Kuo, Mu-Jeng Cheng, Rai-Shung Liu|2021|Org.Chem.Front.|8|2563|doi:10.1039/D1QO00026H
DOI: 10.5517/ccdc.csd.cc25nz4z
title: CCDC 2016151: Experimental Crystal Structure Determination

description: Related Article: Jun Shu, Jian Yue, Xin Qiu, Xiaoqiang Liu, Wang Ren, Qianli Li, Yulong Li, Bin Xu, Kaiming Zhang, Weidong Jiang|2021|Inorg.Chem.Front.|8|2684|doi:10.1039/D1QI00108F