cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.57760/sciencedb.o00114.00034
title: Unsupervised adversarial training-based Chinese-Korean cross-lingual text classification method
title: 基于无监督对抗训练的中朝跨语言文本分类方法

description: This paper proposes a cross-lingual text classification model combining unsupervised word embedding mapping and adversarial training. Firstly, pre-trained monolingual word vectors were mapped into the same semantic space by a linear mapping method, and then adversarial training was performed using the source and target lang uages, thus guiding the classification model to be able to learn language-independent features for the purpose of improving cross-lingual text classification performance. The experimental results show that the method in this paper significantly improves the accuracy of cross-lingual text classification compared with the direct use of cross-lingua l word vectors.
description: This paper proposes a cross-lingual text classification model combining unsupervised word embedding mapping and adversarial training. Firstly, pre-trained monolingual word vectors were mapped into the same semantic space by a linear mapping method, and then adversarial training was performed using the source and target lang uages, thus guiding the classification model to be able to learn language-independent features for the purpose of improving cross-lingual text classification performance. The experimental results show that the method in this paper significantly improves the accuracy of cross-lingual text classification compared with the direct use of cross-lingua l word vectors.
DOI: 10.57760/sciencedb.o00114.00037
title: Gesar Epic Entity Extraction Method Incorporating BERT Syllable Embedding
title: 融合BERT音节嵌入的格萨尔史诗实体抽取方法

description: In deep learning-based Gesar epic named entity recognition, vectorized representation is a central and crucial step. While the traditional syllable vector representation is too homogeneous, which leads to the optimal performance of the downstream task. To address this problem, this paper proposes the BERT-BILSTM-CRF method with Tibetan syllables as the basic unit. BERT, as a multi-layer representation learning, allows for enhanced semantic representation of Tibetan syllables and dynamic generation of syllable vectors based on contextual features through representation learning of Tibetan syllables, and thus more accurate identification of Gesar epic named entities. What is shown experimentally is that the method works well on the Gesar Classic corpus of the Four Descending Histories. The accuracy, recall and F-values were 98.56%, 98.67% and 98.11% respectively, and it was elicited that the line to entity ratio of the Gesar epic was 3:1, involving an equal number of complete lines and entities of the epic. This reflects the fact that the Gesar epic is a very rich dataset of named entities in Tibetan texts, thus demonstrating that named entities are part of the appeal of the epic.
description: In deep learning-based Gesar epic named entity recognition, vectorized representation is a central and crucial step. While the traditional syllable vector representation is too homogeneous, which leads to the optimal performance of the downstream task. To address this problem, this paper proposes the BERT-BILSTM-CRF method with Tibetan syllables as the basic unit. BERT, as a multi-layer representation learning, allows for enhanced semantic representation of Tibetan syllables and dynamic generation of syllable vectors based on contextual features through representation learning of Tibetan syllables, and thus more accurate identification of Gesar epic named entities. What is shown experimentally is that the method works well on the Gesar Classic corpus of the Four Descending Histories. The accuracy, recall and F-values were 98.56%, 98.67% and 98.11% respectively, and it was elicited that the line to entity ratio of the Gesar epic was 3:1, involving an equal number of complete lines and entities of the epic. This reflects the fact that the Gesar epic is a very rich dataset of named entities in Tibetan texts, thus demonstrating that named entities are part of the appeal of the epic.
DOI: 10.57760/sciencedb.o00114.00047
title: Study on Text Sentiment Classification Method Based on TRANSFORMER
title: 基于TRANSFORMER的文本情感分类方法研究

description: Emotion classification is a classification technology with great practical value. It is widely used in some real scenes, such as film box office prediction, and has attracted much attention all the time. In order to explore the performance and defects of the current mainstream deep learning methods in text emotion classification tasks, this paper compares and evaluates several mainstream methods based on transformer, including Bert and its improved models: Roberta, distilbert and minilm. After the experiment on IMDB film review emotion classification task, it is found that the current multilingual pre training method will reduce the classification performance of Bert model; Different from the visual model and the language model simplified by distillation, its classification ability will decline slightly; Roberta's training method is excellent and worthy of in-depth study. This paper provides a further improvement direction for Bert emotion classification.
description: Emotion classification is a classification technology with great practical value. It is widely used in some real scenes, such as film box office prediction, and has attracted much attention all the time. In order to explore the performance and defects of the current mainstream deep learning methods in text emotion classification tasks, this paper compares and evaluates several mainstream methods based on transformer, including Bert and its improved models: Roberta, distilbert and minilm. After the experiment on IMDB film review emotion classification task, it is found that the current multilingual pre training method will reduce the classification performance of Bert model; Different from the visual model and the language model simplified by distillation, its classification ability will decline slightly; Roberta's training method is excellent and worthy of in-depth study. This paper provides a further improvement direction for Bert emotion classification.
DOI: 10.57760/sciencedb.o00015.00008
title: Python Codes for Thermal Properties of Liquid Iron At conditions of Planetary Cores
title: Python Codes for Thermal Properties of Liquid Iron At conditions of Planetary Cores

description: This dataset contains two sets of python codes for the paper "Thermal Properties of Liquid Iron At Conditions of Planetary Cores".1. Thermal.tgz:This compressed package contains python scripts for calculating and plotting thermal properties of liquid iron based on the model constructed in the paper. A GUI interface can be launched by running the 'main.py' script.2. ExoPlex.tgz:This compressed package contains the ExoPlex mass-radius software package (https://github.com/CaymanUnterborn/ExoPlex) that we used to model the internal structure of the planet Kepler-36b. The original ExoPlex code contains only the EoS of hcp solid iron developed by Hakim et al.. To implement the equation of state of liquid iron, we added a new python script (Exoplex/burman/eos/liquid.py) and revised the script (Exoplex/minphys.py). The input file for modeling Kepler-36b is 'Exoplex/Kepler-36b/Kepler_by_mass.py'.
description: This dataset contains two sets of python codes for the paper "Thermal Properties of Liquid Iron At Conditions of Planetary Cores".1. Thermal.tgz:This compressed package contains python scripts for calculating and plotting thermal properties of liquid iron based on the model constructed in the paper. A GUI interface can be launched by running the 'main.py' script.2. ExoPlex.tgz:This compressed package contains the ExoPlex mass-radius software package (https://github.com/CaymanUnterborn/ExoPlex) that we used to model the internal structure of the planet Kepler-36b. The original ExoPlex code contains only the EoS of hcp solid iron developed by Hakim et al.. To implement the equation of state of liquid iron, we added a new python script (Exoplex/burman/eos/liquid.py) and revised the script (Exoplex/minphys.py). The input file for modeling Kepler-36b is 'Exoplex/Kepler-36b/Kepler_by_mass.py'.
DOI: 10.57760/sciencedb.o00019.00006
title: Photoperiod alters the diversity of gut microbiota in Brandt's voles.
title: Photoperiod alters the diversity of gut microbiota in Brandt's voles.

description: Colon microbial faeces of male Brandt's voles were collected at week 2, 4, 6, and 8 of Long-day or short-day photoperiod treatment. Forward primer 341F (5'-CCTAYGGGRBGCASCAG-3') and reverse primer 806R (5'-GGACTACNNGGGTATCTAAT-3') were used to amplify the V3-V4 region of 16S rRNA gene in colon fecal microbiota.
description: Colon microbial faeces of male Brandt's voles were collected at week 2, 4, 6, and 8 of Long-day or short-day photoperiod treatment. Forward primer 341F (5'-CCTAYGGGRBGCASCAG-3') and reverse primer 806R (5'-GGACTACNNGGGTATCTAAT-3') were used to amplify the V3-V4 region of 16S rRNA gene in colon fecal microbiota.
DOI: 10.57760/sciencedb.o00049.00003
title: Raw Data for the article "Enantioselective Construction of 1H-Isoindoles Containing Tri- and Difluoromethylated Quaternary Stereogenic Centers via Palladium-Catalyzed C−H Bond Imidoylation"
title: Raw Data for the article "Enantioselective Construction of 1H-Isoindoles Containing Tri- and Difluoromethylated Quaternary Stereogenic Centers via Palladium-Catalyzed C−H Bond Imidoylation"

description: This zip package includes all the raw data involving in the article "Enantioselective Construction of 1H-Isoindoles Containing Tri- and Difluoromethylated Quaternary Stereogenic Centers via Palladium-Catalyzed C−H Bond Imidoylation" submitted to the journal ACS Catalysis.
description: This zip package includes all the raw data involving in the article "Enantioselective Construction of 1H-Isoindoles Containing Tri- and Difluoromethylated Quaternary Stereogenic Centers via Palladium-Catalyzed C−H Bond Imidoylation" submitted to the journal ACS Catalysis.
DOI: 10.57760/sciencedb.o00061.00002
title: Gene sequences of novel DNA viruses from rodents and shrews in Kenya
title: Gene sequences of novel DNA viruses from rodents and shrews in Kenya

description: This dataset contains partial gene sequences of novel adenovirus, adeno-associated viruses, herpesviruses and polyomaviruses detected in Kenyan rodents and shrew populations, as well as the complete genome sequence of a novel polyomavirus discovered in a grass mouse (Lemnyscomys striatus) from Kenya.
description: This dataset contains partial gene sequences of novel adenovirus, adeno-associated viruses, herpesviruses and polyomaviruses detected in Kenyan rodents and shrew populations, as well as the complete genome sequence of a novel polyomavirus discovered in a grass mouse (Lemnyscomys striatus) from Kenya.
DOI: 10.57760/sciencedb.t00000.00010
title: The estimated actual evapotranspiration over the Tibetan Plateau from 2001 to 2016
title: The estimated actual evapotranspiration over the Tibetan Plateau from 2001 to 2016

description: Terrestrial actual evapotranspiration (ETa) is a key parameter controlling the land-atmosphere interaction processes and the water cycle. However, the spatial distribution and temporal changes of ETa over the Tibetan Plateau (TP) remain very uncertain. Here we estimate the multiyear (2001-2018) monthly ETa and its spatial distribution on the TP by a combination of meteorological data and satellite products. Validation against data from six eddy-covariance monitoring sites yielded a root mean square errors ranging from 9.3 to 14.5 mm mo-1, and correlation coefficients exceeding 0.9. The estimated ETa product is useful for an improved understanding of water and energy cycle changes over the TP.
description: Terrestrial actual evapotranspiration (ETa) is a key parameter controlling the land-atmosphere interaction processes and the water cycle. However, the spatial distribution and temporal changes of ETa over the Tibetan Plateau (TP) remain very uncertain. Here we estimate the multiyear (2001-2018) monthly ETa and its spatial distribution on the TP by a combination of meteorological data and satellite products. Validation against data from six eddy-covariance monitoring sites yielded a root mean square errors ranging from 9.3 to 14.5 mm mo-1, and correlation coefficients exceeding 0.9. The estimated ETa product is useful for an improved understanding of water and energy cycle changes over the TP.
DOI: 10.57760/sciencedb.p00007.00006
title: A Chinese-Uighur comparable corpus
title: 汉语–维吾尔语可比语料数据集

description: The dataset is composed of comparable corpus of Chinese and Uigur, obtained from the Internet. Chinese and Uigur language pairs are textually corresponding. The dataset is mainly from news, including news headlines, time and text. The dataset contains two data files: ch_corpus.zip and uy_corpus.zip. Each package contains four documents, namely document_1, document_2, document_3 and document_4. Each document contains two folders: uy and ch, where uy represents Uyghur, ch represents Chinese, and each folder contains multiple text documents. Uighur and Chinese language pairs are organized correspondingly according to their names.
description: The dataset is composed of comparable corpus of Chinese and Uigur, obtained from the Internet. Chinese and Uigur language pairs are textually corresponding. The dataset is mainly from news, including news headlines, time and text. The dataset contains two data files: ch_corpus.zip and uy_corpus.zip. Each package contains four documents, namely document_1, document_2, document_3 and document_4. Each document contains two folders: uy and ch, where uy represents Uyghur, ch represents Chinese, and each folder contains multiple text documents. Uighur and Chinese language pairs are organized correspondingly according to their names.
DOI: 10.57760/sciencedb.p00007.00005
title: A dataset of Mongolian, Tibetan and Uyghur speech fragments based on voice activity detection
title: 基于端点检测的蒙藏维语音片段数据集

description: Based on the speech data in Mongolian, Tibetan, and Uyghur speech data from Chinese minority regions in 2015, we adopted a double threshold Voice Activity Detection method with short-time energy and short-time zero-crossing rate to obtain multiple voice fragments of each sentence speech. The result dataset contains 1657 Mongolian speech fragments, 666 Tibetan speech fragments and 756 Uygur speech fragments. The total volume of the data is about 111 MB. Through automatic software segmentation and multiple auditing and proofreading by language experts, we have obtained high-quality voice fragment data of Mongolian, Tibetan and Uygur, which can be applied to minority speech recognition, voice activity detection, speech enhancement, speech synthesis and language teaching.
description: Based on the speech data in Mongolian, Tibetan, and Uyghur speech data from Chinese minority regions in 2015, we adopted a double threshold Voice Activity Detection method with short-time energy and short-time zero-crossing rate to obtain multiple voice fragments of each sentence speech. The result dataset contains 1657 Mongolian speech fragments, 666 Tibetan speech fragments and 756 Uygur speech fragments. The total volume of the data is about 111 MB. Through automatic software segmentation and multiple auditing and proofreading by language experts, we have obtained high-quality voice fragment data of Mongolian, Tibetan and Uygur, which can be applied to minority speech recognition, voice activity detection, speech enhancement, speech synthesis and language teaching.
DOI: 10.57760/sciencedb.p00007.00004
title: Mongolian, Tibetan, and Uyghur speech data from Chinese minority regions in 2015
title: 2015年中国少数民族地区蒙藏维言语录音数据集

description: A Mongolian, Tibetan and Uyghur speech data set in 2015, which was collected using a remote speech acquisition software system based on Client/Server architecture. The system reduced the cost and improved the efficiency of collecting Mongolian, Tibetan and Uyghur speech data. The data set contains nearly 800 sentences, with a total size of 136 MB. The speech data is of great theoretical and practical value for speech analysis and teaching, speech recognition and synthesis concerning the minority languages in China. The system can be applied into acquiring other language/dialect speeches with slight modification, and it is easy to operate and economic to install.
description: A Mongolian, Tibetan and Uyghur speech data set in 2015, which was collected using a remote speech acquisition software system based on Client/Server architecture. The system reduced the cost and improved the efficiency of collecting Mongolian, Tibetan and Uyghur speech data. The data set contains nearly 800 sentences, with a total size of 136 MB. The speech data is of great theoretical and practical value for speech analysis and teaching, speech recognition and synthesis concerning the minority languages in China. The system can be applied into acquiring other language/dialect speeches with slight modification, and it is easy to operate and economic to install.
DOI: 10.5281/zenodo.5637824
title: REACH_Subgrantees_RP1Export

description: Export of REACH_SubGrantees_DB at the end of the first reporting period (M13). Only non-privacy sensitive fields from REACH_SubGrantees_DB will be dumped in this export.
DOI: 10.5281/zenodo.5637823
title: REACH_Subgrantees_RP1Export

description: Export of REACH_SubGrantees_DB at the end of the first reporting period (M13). Only non-privacy sensitive fields from REACH_SubGrantees_DB will be dumped in this export.
DOI: 10.6084/m9.figshare.21129052.v1
title: A reconstructed 4D Pacific ocean temperature field from sparse Argo data based on the blocking sparse tensor interpolation

description: Based on the tensor method, we reconstructed the Argo data of ocean temperature spatio-temporal field in the Pacific Ocean. The time range of the data is from January 2004 to December 2020, the spatial range is 60° N -- 60° S, and the depth range is 2.5 dbar -- 1000 dbar with 23 layers in the Pacific Ocean area of 120° E -- 180° -- 60° W. The data product are provided in a NetCDF file. Moreover, compared with other reconstruction dataset products such as BOA and EN4G, this dataset has the following superiorities: In the overall reconstruction accuracy, the accuracy of the dataset based on Tensor method is the highest at each depth layer, and it is continuous at different depths; In terms of the reconstruction accuracy of the typical layer, the Tensor product can reconstruct the local structural characteristics.
DOI: 10.5281/zenodo.6466316
title: Comparison of biomedical relationship extraction methods and models for knowledge graph creation (Gene-Disease relationships)

description: This is the dataset used for classifying Gene-Disease relationship types from sentences. The dataset consists of 3 files: manually_annotated_set.xlsx - set of 2000 manualy annotated sentences with entities Unbalanced_dataset.xlsx - set of 12000 sentences, out of which 2000 are from the first set, manually annotated, and the rest have been added using rule based method by adding sentences where extraction had confidence 1. Balanced_dataset_SUB_PRED.xlsx - balanced dataset generated by taking 2000 manually annotated sentences, but then adding sentences from the rule-based method with confidence 1 in such a way that each relationship class had at least 1400 sentences (for biomarkers, we could obtain 1243 sentences with confidence 1 from a processed portion of the data we had at the time of building the dataset). Please cite: Milosevic, Nikola, and Wolfgang Thielemann. "Comparison of biomedical relationship extraction methods and models for knowledge graph creation." <em>Journal of Web Semantics</em> (2022): 100756. https://doi.org/10.1016/j.websem.2022.100756 Article preprint available at: https://arxiv.org/abs/2201.01647
description: {"references": ["Milosevic, Nikola, and Wolfgang Thielemann. \"Comparison of biomedical relationship extraction methods and models for knowledge graph creation.\" arXiv preprint arXiv:2201.01647 (2022).", "Milosevic, Nikola, and Wolfgang Thielemann. \"Comparison of biomedical relationship extraction methods and models for knowledge graph creation\", Journal of Web Semantics (2022)."]}
DOI: 10.6084/m9.figshare.21129052
title: A reconstructed 4D Pacific ocean temperature field from sparse Argo data based on the blocking sparse tensor interpolation

description: Based on the tensor method, we reconstructed the Argo data of ocean temperature spatio-temporal field in the Pacific Ocean. The time range of the data is from January 2004 to December 2020, the spatial range is 60° N -- 60° S, and the depth range is 2.5 dbar -- 1000 dbar with 23 layers in the Pacific Ocean area of 120° E -- 180° -- 60° W. The data product are provided in a NetCDF file. Moreover, compared with other reconstruction dataset products such as BOA and EN4G, this dataset has the following superiorities: In the overall reconstruction accuracy, the accuracy of the dataset based on Tensor method is the highest at each depth layer, and it is continuous at different depths; In terms of the reconstruction accuracy of the typical layer, the Tensor product can reconstruct the local structural characteristics.
DOI: 10.6084/m9.figshare.21129052.v2
title: A reconstructed 4D Pacific ocean temperature field from sparse Argo data based on the blocking sparse tensor interpolation

description: Based on the tensor method, we reconstructed the Argo data of ocean temperature spatio-temporal field in the Pacific Ocean. The time range of the data is from January 2004 to December 2020, the spatial range is 60° N -- 60° S, and the depth range is 2.5 dbar -- 1000 dbar with 23 layers in the Pacific Ocean area of 120° E -- 180° -- 60° W. The data product are provided in a NetCDF file. Moreover, compared with other reconstruction dataset products such as BOA and EN4G, this dataset has the following superiorities: In the overall reconstruction accuracy, the accuracy of the dataset based on Tensor method is the highest at each depth layer, and it is continuous at different depths; In terms of the reconstruction accuracy of the typical layer, the Tensor product can reconstruct the local structural characteristics.
DOI: 10.5281/zenodo.6969114
title: Benefits of subsidence control for coastal flooding in China

description: This repository contains the data and the scripts used to create results, figures and tables in the paper "Benefits of subsidence control for coastal flooding in China " by Fang et al. (DOI-link to follow).
DOI: 10.25919/nb45-8w35
title: Data for hybpiper2-nf and resolve_paralogs-nf: Containerization and additional options for assembly and paralog detection in target enrichment data

description: This is an example dataset of 24 species of Pycnosorus and Australian Craspedia to illustrate the functionality of hybpiper2-nf and resolve_paralogs-nf, two Nextflow scripts and associated Singularity container developed for the Genomics for Australian Plants consortium's phylogenomic pillar Australian Angiosperms Tree of Life.
DOI: 10.5281/zenodo.6913356
title: Closed-loop optimization of general conditions for heteroaryl Suzuki coupling

description: No description provided.
DOI: 10.5281/zenodo.7099435
title: Closed-loop optimization of general conditions for heteroaryl Suzuki coupling

description: No description provided.
DOI: 10.6084/m9.figshare.19672338.v3
title: Supplemental materials.xlsx

description: This file contains data used to generate the figures in the text, nad the data sources are given in this file.
DOI: 10.15151/esrf-es-883953559
title: The Iberian cryoEM community BAG

description: The Iberian cryoEM BAG is a large consortium (&gt; 30 groups) composed of Portuguese and Spanish groups working in biologically relevant problems including disease related metabolic enzymes, antibiotic resistance, DNA replication and DNA maintenance, protein synthesis, virus structure and mechanisms, and macromolecular complexes involved in the control of key cellular processes like protein folding and degradation.