cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5517/ccdc.csd.cc25cgmn
title: CCDC 2007021: Experimental Crystal Structure Determination

description: Related Article: Hüseyin Ünver, Bahadir Boyacioglu, Neslihan Demir, Celal Tuğrul Zeyrek, Mustafa Yıldız|2020|J.Mol.Struct.|1221|128663|doi:10.1016/j.molstruc.2020.128663
DOI: 10.25442/hku.12758069.v1
title: Attentional and Interpretation Biases in the Context of Pain

description: Specific descriptions of the dataset for each separate study can be found within the zipped file (README.docx).
DOI: 10.25442/hku.12758069
title: Attentional and Interpretation Biases in the Context of Pain

description: Specific descriptions of the dataset for each separate study can be found within the zipped file (README.docx).
DOI: 10.25442/hku.12757802
title: Tracing atmospheric nitrogen deposition and its impact on Hong Kong and Chinese coastal ecosystem

description: Nitrogen deposition plays an important role in both air and water quality. Nitrogen emissions in cities increase are high due mainly due to transportation and industrial activities and predicted to further increase. As nitrogen is often the limiting nutrient in coastal waters, the excess nitrogen deposition may enhance the phytoplankton growth, resulting in eutrophication leading to a cascade of ecological impacts. Thus, understanding the nitrogen sources and its potential impacts are crucial to mitigate the nitrogen pollution in coastal waters. In this thesis, I used multi stable isotope analysis of wet and dry deposition in Hong Kong to identify the atmospheric sources of nitrogen and the seasonal trend. I characterized the δ15N values of wet deposition, which is useful for further analysis of the nitrate sources in seawater. Next, I examined the ecological impact of future trend of nitrogen deposition in China. Specially, I used a biogeochemical model to estimate the future hypoxia area of such deposition, suggesting that reducing nitrogen deposition can reduce the hypoxia area. Moreover, it indicates that nitrogen deposition will potentially affect the hypoxia area if we do not regulate emissions in the future. This thesis provides a new approach to study the trend and impact of nitrogen deposition, which will allow more understanding on its significance to the coastal ecosystem. <br><br>The dataset composed of the dual isotopes analysis of dry and wet deposition, bulk isotopes analysis of dry deposition and ammonia data of dry and wet deposition.<br>
DOI: 10.25442/hku.12757802.v1
title: Tracing atmospheric nitrogen deposition and its impact on Hong Kong and Chinese coastal ecosystem

description: Nitrogen deposition plays an important role in both air and water quality. Nitrogen emissions in cities increase are high due mainly due to transportation and industrial activities and predicted to further increase. As nitrogen is often the limiting nutrient in coastal waters, the excess nitrogen deposition may enhance the phytoplankton growth, resulting in eutrophication leading to a cascade of ecological impacts. Thus, understanding the nitrogen sources and its potential impacts are crucial to mitigate the nitrogen pollution in coastal waters. In this thesis, I used multi stable isotope analysis of wet and dry deposition in Hong Kong to identify the atmospheric sources of nitrogen and the seasonal trend. I characterized the δ15N values of wet deposition, which is useful for further analysis of the nitrate sources in seawater. Next, I examined the ecological impact of future trend of nitrogen deposition in China. Specially, I used a biogeochemical model to estimate the future hypoxia area of such deposition, suggesting that reducing nitrogen deposition can reduce the hypoxia area. Moreover, it indicates that nitrogen deposition will potentially affect the hypoxia area if we do not regulate emissions in the future. This thesis provides a new approach to study the trend and impact of nitrogen deposition, which will allow more understanding on its significance to the coastal ecosystem. <br><br>The dataset composed of the dual isotopes analysis of dry and wet deposition, bulk isotopes analysis of dry deposition and ammonia data of dry and wet deposition.<br>
DOI: 10.5281/zenodo.3978763
title: sbes-2020-nier-death

description: anonymous
DOI: 10.5281/zenodo.3978762
title: sbes-2020-nier-death

description: anonymous
DOI: 10.18434/mds2-2278
title: NIST Fake Dataset for Testing
DOI: 10.34740/kaggle/dsv/1410813
title: COVID-19 Transit Demand Impact
DOI: 10.34740/kaggle/ds/687971
title: COVID-19 Transit Demand Impact
DOI: 10.5519/qd.ecz04uqj
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (1 records)
DOI: 10.5517/ccdc.csd.cc248g30
title: CCDC 1974331: Experimental Crystal Structure Determination

description: Related Article: Daisuke Shimoyama, Ryo Sekiya, Hiroyuki Maekawa, Hiroto Kudo, Takeharu Haino|2020|CrystEngComm|22|4740|doi:10.1039/D0CE00650E
DOI: 10.5517/ccdc.csd.cc248g41
title: CCDC 1974332: Experimental Crystal Structure Determination

description: Related Article: Daisuke Shimoyama, Ryo Sekiya, Hiroyuki Maekawa, Hiroto Kudo, Takeharu Haino|2020|CrystEngComm|22|4740|doi:10.1039/D0CE00650E
DOI: 10.5517/ccdc.csd.cc248g52
title: CCDC 1974333: Experimental Crystal Structure Determination

description: Related Article: Daisuke Shimoyama, Ryo Sekiya, Hiroyuki Maekawa, Hiroto Kudo, Takeharu Haino|2020|CrystEngComm|22|4740|doi:10.1039/D0CE00650E
DOI: 10.5517/ccdc.csd.cc248g63
title: CCDC 1974334: Experimental Crystal Structure Determination

description: Related Article: Daisuke Shimoyama, Ryo Sekiya, Hiroyuki Maekawa, Hiroto Kudo, Takeharu Haino|2020|CrystEngComm|22|4740|doi:10.1039/D0CE00650E
DOI: 10.5517/ccdc.csd.cc248g74
title: CCDC 1974335: Experimental Crystal Structure Determination

description: Related Article: Daisuke Shimoyama, Ryo Sekiya, Hiroyuki Maekawa, Hiroto Kudo, Takeharu Haino|2020|CrystEngComm|22|4740|doi:10.1039/D0CE00650E
DOI: 10.5517/ccdc.csd.cc1zmg46
title: CCDC 1835948: Experimental Crystal Structure Determination

description: Related Article: Wenting Cai, Janet Alvarado, Alejandro Metta-Magaña, Ning Chen, Luis Echegoyen|2020|J.Am.Chem.Soc.|142|13112|doi:10.1021/jacs.0c04888
DOI: 10.5517/ccdc.csd.cc2508j0
title: CCDC 1996261: Experimental Crystal Structure Determination

description: Related Article: Wenting Cai, Janet Alvarado, Alejandro Metta-Magaña, Ning Chen, Luis Echegoyen|2020|J.Am.Chem.Soc.|142|13112|doi:10.1021/jacs.0c04888
DOI: 10.5517/ccdc.csd.cc24z73h
title: CCDC 1995256: Experimental Crystal Structure Determination

description: Related Article: Qinghe Gao, Manman Wu, Ke Zhang, Ning Yang, Mengting Liu, Juan Li, Lizhen Fang, Suping Bai, Yongtao Xu|2020|Org.Lett.|22|5645|doi:10.1021/acs.orglett.0c02001
DOI: 10.5517/ccdc.csd.cc25lpp5
title: CCDC 2013967: Experimental Crystal Structure Determination

description: Related Article: Nan Xia, Jinyun Yuan, Lingwen Liao, Wenhao Zhang, Jin Li, Haiteng Deng, Jinlong Yang, Zhikun Wu|2020|J.Am.Chem.Soc.|142|12140|doi:10.1021/jacs.0c02117
DOI: 10.5517/ccdc.csd.cc25lpq6
title: CCDC 2013968: Experimental Crystal Structure Determination

description: Related Article: Nan Xia, Jinyun Yuan, Lingwen Liao, Wenhao Zhang, Jin Li, Haiteng Deng, Jinlong Yang, Zhikun Wu|2020|J.Am.Chem.Soc.|142|12140|doi:10.1021/jacs.0c02117
DOI: 10.5517/ccdc.csd.cc25lpr7
title: CCDC 2013969: Experimental Crystal Structure Determination

description: Related Article: Liang Fu, Zhihan Zhang, Pinhong Chen, Zhenyang Lin, Guosheng Liu|2020|J.Am.Chem.Soc.|142|12493|doi:10.1021/jacs.0c05373
DOI: 10.5517/ccdc.csd.cc25lps8
title: CCDC 2013970: Experimental Crystal Structure Determination

description: Related Article: Liang Fu, Zhihan Zhang, Pinhong Chen, Zhenyang Lin, Guosheng Liu|2020|J.Am.Chem.Soc.|142|12493|doi:10.1021/jacs.0c05373
DOI: 10.5517/ccdc.csd.cc25lpt9
title: CCDC 2013971: Experimental Crystal Structure Determination

description: Related Article: Liang Fu, Zhihan Zhang, Pinhong Chen, Zhenyang Lin, Guosheng Liu|2020|J.Am.Chem.Soc.|142|12493|doi:10.1021/jacs.0c05373
DOI: 10.5517/ccdc.csd.cc25lpvb
title: CCDC 2013972: Experimental Crystal Structure Determination

description: Related Article: Qiuhan Li, Samuel M. Levi, Eric N. Jacobsen|2020|J.Am.Chem.Soc.|142|11865|doi:10.1021/jacs.0c04255
DOI: 10.5517/ccdc.csd.cc25lpwc
title: CCDC 2013973: Experimental Crystal Structure Determination

description: Related Article: Qiuhan Li, Samuel M. Levi, Eric N. Jacobsen|2020|J.Am.Chem.Soc.|142|11865|doi:10.1021/jacs.0c04255
DOI: 10.5517/ccdc.csd.cc25lqfy
title: CCDC 2013990: Experimental Crystal Structure Determination

description: Related Article: Sakiho Hayakawa, Kyohei Matsuo, Hiroko Yamada, Norihito Fukui, Hiroshi Shinokubo|2020|J.Am.Chem.Soc.|142|11663|doi:10.1021/jacs.0c04096
DOI: 10.21227/4a9d-cv96
title: Deep Xi dataset

description: The training, validation, and test set used for Deep Xi (https://github.com/anicolson/DeepXi). Training set:The clean-speech recordings are from the test-clean-100 set of Librispeech (http://www.openslr.org/12/) and from the CSTR VCTK corpus (https://homepages.inf.ed.ac.uk/jyamagis/page3/page58/page58.html) (the recordings from speakers p232 and p257 are excluded as they are used in the test set of the DEMAND Voicebank dataset (http://ssw9.talp.cat/papers/ssw9_PS2-4_Valentini-Botinhao.pdf)). The noise recordings are from the Environmental Background Noise dataset (https://personal.utdallas.edu/~nxk019000/VAD-dataset/), the Nonspeech dataset (http://web.cse.ohio-state.edu/pnl/corpus/HuNonspeech/HuCorpus.html), the QUT-NOISE dataset (https://research.qut.edu.au/saivt/databases/qut-noise-databases-and-protocols/), multiple Freesound packs (https://freesound.org/), the noise set of the MUSAN corpus (https://www.openslr.org/17/), the RSG-10 noise database (http://www.steeneken.nl/wp-content/uploads/2014/04/RSG-10_Noise-data-base.pdf) (voice babble, F16, and factory (welding) are excluded as they are used in the Deep Xi Test Set and the Test Set From 10.1016/J.SPECOM.2019.06.002) and the Urban Sound dataset (http://www.justinsalamon.com/uploads/4/3/9/4/4394963/salamon_urbansound_acmmm14.pdf) (street music no. 26,270 is excluded as it is used in the Deep Xi Test Set and the Test Set From 10.1016/J.SPECOM.2019.06.002). Note that the clean-speech and noise recordings used for this training set are separate from those used in the test set and the Test Set From 10.1016/J.SPECOM.2019.06.002, and the DEMAND Voicebank test set (http://ssw9.talp.cat/papers/ssw9_PS2-4_Valentini-Botinhao.pdf). Test set:Noisy-speech set used to test Deep Xi (https://github.com/anicolson/DeepXi). The clean speech and noise used to create the noisy-speech set are also available. The clean-speech recordings are from Librispeech test-clean (http://www.openslr.org/12/). The noise recordings are from the RSG-10 noise database (http://www.steeneken.nl/wp-content/uploads/2014/04/RSG-10_Noise-data-base.pdf) and the Urban Sound dataset (http://www.justinsalamon.com/uploads/4/3/9/4/4394963/salamon_urbansound_acmmm14.pdf).The noise recordings are as follows:26270 - A recording of street music. It is recording no. 26,270 from the Urband Sound dataset.SIGNAL019 - A recording of voice babble from the RSG-10 dataset.SIGNAL020 - A recording of an F16 fighter jet from the RSG-10 dataset.SIGNAL021 - A recording of factory welding from the RSG-10 dataset.
DOI: 10.21227/wayz-3082
title: Deep Xi Test Set (depreciated, please see Deep Xi dataset)

description: Noisy-speech set used to test Deep Xi (https://github.com/anicolson/DeepXi). The clean speech and noise used to create the noisy-speech set are also available. The clean-speech recordings are from Librispeech test-clean (http://www.openslr.org/12/). The noise recordings are from the RSG-10 noise database (http://www.steeneken.nl/wp-content/uploads/2014/04/RSG-10_Noise-data-base.pdf) and the Urban Sound dataset (http://www.justinsalamon.com/uploads/4/3/9/4/4394963/salamon_urbansound_acmmm14.pdf).The noise recordings are as follows: 26270 - A recording of street music. It is recording no. 26,270 from the Urband Sound dataset.SIGNAL019 - A recording of voice babble from the RSG-10 dataset.SIGNAL020 - A recording of an F16 fighter jet from the RSG-10 dataset.SIGNAL021 - A recording of factory welding from the RSG-10 dataset.
DOI: 10.5519/qd.doyxxne5
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (1001 records)
DOI: 10.5519/qd.1nds98yy
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (4586103 records)
DOI: 10.21227/93kc-4251
title: Cloud-Based Data Centre with Predictive Machine Learning Server Traces

description: Cloud Computing is been the field for interest by the research community and application development industry for few decades now. The ease of development, deployment and management of applications from wide range of computing paradigm and ability to manage the applications over network enabled systems are the biggest selling points of cloud computing. These benefits are materialized using the mechanism called virtualization on cloud computing and in cloud-based Data Centres. The virtualization technology not only enables the complete virtual view of the physical resource pools, rather also enables few key benefits such as portability, recovery after failure and most prominently generates the fundamental technique for load balancing. In the recent past, a good number of research outcomes are observed in improving the load balancing mechanisms using stochastic methods or by deploying bio-genetic optimization methods. Nonetheless, demand for higher scalability and higher availability for the applications are the constant catalyst for further exploration betterment of the load balancing algorithms. In this work, the fundamental problems with load balancing are analyzed along with the drawbacks of the existing load balancing genetic optimization methods. Primarily the genetic optimization methods are criticized for higher order probabilistic distributions, higher complexity of the solution search spaces and the increasing computational complexity while introducing additional parameters for improving the decision-making capabilities. Thus firstly, this work addresses the possibilities of load characteristics summarization for better implementation of the load prediction analogies using the service request type categorizations. Secondly, for the load summarization process, the equivalence of the related parameters responsible for load calculations are reduced to abridged parametric representations using the correlation-based reduction strategy, which significantly supports of the principle of load characteristics summarization process and finally, this work demonstrates anther strategy for pheromone level prediction using the corrective coefficient based-based method for enhanced prediction over the other standard genetic optimization methods during load balancing. This work utilizes the mathematical modelling methods, data representation methods, simulation over multiple simulation tools and finally the web-based third-party cloud service providers to test and prove the concepts proposed in this work, which are furnished in the subsequent sections of this work. The resultant approach is proven to be the most balanced strategy for power consumption, less VM migrations, reduced time complexity and finally less violation of the service level agreements compared with the other parallel standard methods
DOI: 10.21227/t88h-e712
title: Cloud-Based Data Centre with Predictive Machine Learning Server Traces

description: Cloud Computing is been the field for interest by the research community and application development industry for few decades now. The ease of development, deployment and management of applications from wide range of computing paradigm and ability to manage the applications over network enabled systems are the biggest selling points of cloud computing. These benefits are materialized using the mechanism called virtualization on cloud computing and in cloud-based Data Centres. The virtualization technology not only enables the complete virtual view of the physical resource pools, rather also enables few key benefits such as portability, recovery after failure and most prominently generates the fundamental technique for load balancing. In the recent past, a good number of research outcomes are observed in improving the load balancing mechanisms using stochastic methods or by deploying bio-genetic optimization methods. Nonetheless, demand for higher scalability and higher availability for the applications are the constant catalyst for further exploration betterment of the load balancing algorithms. In this work, the fundamental problems with load balancing are analyzed along with the drawbacks of the existing load balancing genetic optimization methods. Primarily the genetic optimization methods are criticized for higher order probabilistic distributions, higher complexity of the solution search spaces and the increasing computational complexity while introducing additional parameters for improving the decision-making capabilities. Thus firstly, this work addresses the possibilities of load characteristics summarization for better implementation of the load prediction analogies using the service request type categorizations. Secondly, for the load summarization process, the equivalence of the related parameters responsible for load calculations are reduced to abridged parametric representations using the correlation-based reduction strategy, which significantly supports of the principle of load characteristics summarization process and finally, this work demonstrates anther strategy for pheromone level prediction using the corrective coefficient based-based method for enhanced prediction over the other standard genetic optimization methods during load balancing. This work utilizes the mathematical modelling methods, data representation methods, simulation over multiple simulation tools and finally the web-based third-party cloud service providers to test and prove the concepts proposed in this work, which are furnished in the subsequent sections of this work. The resultant approach is proven to be the most balanced strategy for power consumption, less VM migrations, reduced time complexity and finally less violation of the service level agreements compared with the other parallel standard methods
DOI: 10.5281/zenodo.3978740
title: EstSoil-EH: An eco-hydrological modelling parameters dataset derived from the Soil Map of Estonia data deposit

description: We created an extended eco-hydrological dataset for Estonia, the EstSoil-EH v1.0, containing derived numerical values for the following data in all of the mapped soil units in the 1:10 000 soil map: soil profiles (e.g., layers, depths), texture (clay, silt, and sand components), rockiness, and physical variables related to water and carbon (bulk density, hydraulic conductivity, organic carbon content). Ultimately, our objective was to develop a reproducible method for deriving numerical values to support modelling and prediction of eco-hydrological processes in Estonia using the popular Soil and Water Assessment Tool. For more information on the development of this dataset look for "EstSoil-EH v1.0: An eco-hydrological modelling parameters dataset derived from the Soil Map of Estonia", Alexander Kmoch, Arno Kanal†, Alar Astover, Ain Kull, Holger Virro, Aveliina Helm, Meelis Pärtel, Ivika Ostonen and Evelyn Uuemaa, 2019, Earth System Science Data (ESSD), ISSN 1866-3508, eISSN 1866-3516,<br> https://www.earth-syst-sci-data.net/
DOI: 10.5281/zenodo.3967254
title: ChIP-seq of plasma cell-free nucleosomes identifies cell-of-origin gene expression programs

description: Genomic DNA is packed by histone proteins that carry a multitude of post-translational modifications that reflect cellular transcriptional state. Cell-free DNA (cfDNA) is derived from fragmented chromatin in dying cells, and as such it retains the histones markings present in the cells of origin. Here, we pioneer chromatin immunoprecipitation followed by sequencing of cell-free nucleosomes (cfChIP-seq) carrying active chromatin marks. Our results show that cfChIP-seq provides multidimensional epigenetic information that recapitulates the epigenetic and transcriptional landscape in the cells of origin. We applied cfChIP-seq to 268 samples including samples from patients with heart and liver pathologies, and 135 samples from 56 metastatic CRC patients. We show that cfChIP-seq can detect pathology-related transcriptional changes at the site of the disease, beyond the information on tissue of origin. In CRC patients we detect clinically-relevant, and patient-specific information, including transcriptionally active HER2 amplifications. cfChIP-seq provides genome-wide information and requires low sequencing depth. Altogether, we establish cell-free chromatin immunoprecipitation as an exciting modality with potential for diagnosis and interrogation of physiological and pathological processes using a simple blood test.
description: The dataset contains several directories in gziped tar files. SetupFiles.tgz - directory with the files needed to define the regions of the genome used in the analysis. Analysis.tgz - analysis directory with the BED files in the paper. See https://github.com/nirfriedman/cfChIP-seq for code and for detailed instructions on setting up the directories.
DOI: 10.5519/qd.c2wpt3v5
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (751928 records)
DOI: 10.5282/ubm/data.194
title: Paleomagnetism of Paleocene-Maastrichtian (60–70 Ma) lava flows from Tian Shan (Central Asia): directional analysis and paleointensities

description: Specimen-level data for paleodirections and absolute paleointensities
DOI: 10.14457/cu.the.2006.2029
title: A finite element method with polygonal elements for analyzing band gap characteristic in two-dimensional photonic crystals

description: Finite element method (FEM) based on Wachspress interpolation on polygonal elements for analyzing the band gap characteristic of two-dimensional photonic crystals (2D PCs) is proposed in this. The proposed FEM has been coded into program and validated with other method such as conventional finite element method based on triangular elements and plane wave expansion method. Numerical examples on triangular lattice and square lattice photonic crystals have been carried out. The comparison of accuracy between the conventional FEM and the proposed method has been also provided in this thesis. The comparison results show that the polygonal element can yield better accuracy than the conventional FEM with the same number of unknowns in system equations.