cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/m27cdy3z4c.2
title: 3D printer molds for head phantom shapes

description: Mold shapes for casting gelatine into a head shape for creating head phantoms as used in: - S. Kohli and A. J. Casson, “Removal of gross artifacts of transcranial alternating current stimulation in simultaneous EEG monitoring,” Sensors, vol. 19, no. 190, pp. 1–23, 2019. - S. Kohli and A. J. Casson, “Towards close-loop tES: Workload monitoring during tACS stimulation,” Brain Stimulation, vol. 10, no. 4, pp. e28–e29, 2017. - S. Kohli, S. Krachunov and A. J. Casson, “Towards closed-loop transcranial Electrical Stimulation: a comparison of methods for real time tES-EEG artefact removal using a phantom head model,” Brain Stimulation, vol. 10, no. 2, pp. 467–468, 2017. - S. Kohli and A. J. Casson, “Towards signal processing assisted hardware for continuous in-band electrode impedance monitoring,” IEEE International Symposium on Circuits and Systems, Baltimore, May 2017. Head shape is based upon a human dummy used for automotive testing, with source https://grabcad.com/library/mannequin-1. This has been hollowed out so that it can be filled with gelatine to get the wanted shape. The mold is broken down into 7 pieces, each small enough to be produced on a desktop sized 3D printer. These should be printed, and then a Silicone seal used to to have a water tight connection between the different parts, before filling with gelatine. We usually print in PLA, but a flexible filament could be used to help with easy removal. If you have a larger printer, the pieces could be combined (the best option is to have just two pieces to print and seal together as this will minimize leaks from the seal.)
DOI: 10.17632/mpsz8pjg79.1
title: Microstructure and tensile properties of fine-grained copper

description: Microstructure and tensile properties of fine-grained copper fabricated by thermomechanical consolidation of copper nanopowder/micron-sized powder blend
DOI: 10.17632/2twg33k4vm.1
title: LINF_210027000

description: 60S ribosomal protein L32; Leishmania infantum
DOI: 10.17632/zsns7pjb4w.1
title: Strawberry data for MGIDI paper

description: This file contains data on multiple traits evaluated in a strawberry experiment. See https://doi.org/10.1101/2020.12.30.424876 for information regarding the trait names.
DOI: 10.17632/8zx2mczz6d.1
title: Dataset for "Vegetation and microbes interact to preserve carbon in many wooded peatlands"

description: 1) Compiled mean soil respirations from boreal to tropical peatlands; 2) Soil physicochemical parameters, the decomposing capability of microbes, the temperature sensitivity, and the relative contribution of fungi and bacterial to decomposition in the subtropical shrub-dominated peatland in North Carolina and the boreal Sphagnum-dominated peatland in Minnesota, USA.
DOI: 10.17632/fj42b7v6ky.2
title: This is the dataset for my submission article.

description: This is the dataset for my submission article.
DOI: 10.17632/xp89jmbtjn.1
title: Metabolomic profile of human plasma associated with a comparative drug treatment time course study of two platelet aggregation inhibitors
DOI: 10.17632/4tb88x55y3.1
title: LC-QTOF-MS Chemical compounds quantification in banana peel (Musa sp)

description: This dataset is uploaded as supplementary material for the article.
DOI: 10.17632/d4rjyvdthh.1
title: Soils and Paleosol Carbon Isotope Dataset

description: Soil and paleosol carbon isotope data
DOI: 10.17608/k6.auckland.12886745.v4
title: Untangling the genetic link between type 1 and type 2 diabetes using functional genomics

description: All datasets and supplementary information for this article.
DOI: 10.17632/thtndvvp9s.1
title: Miller_and_Charles_with_concepts_senses

description: This dataset represents the results of the experimentation of a method for evaluating semantic similarity between concepts in a taxonomy. The method is based on the information-theoretic approach and allows senses of concepts in a given context to be considered. The dataset is composed of 28 files. Each file refers to one pair of the well-known Miller and Charles [1] benchmark dataset for assessing semantic similarity. For each pair of concepts, the same 28 pairs are all considered as possible different contexts. We applied our proposal by extending 7 methods for computing semantic similarity in a taxonomy, selected from the literature. The methods considered in the experiment are referred to as (R[2], W&P[3], L[4], J&C[5], P&S[6], A[7], A&M[8]): REFERENCES [1] Miller, G.A., Charles, W.G. Contextual correlates of semantic similarity. Language and Cognitive Processes 6(1), 1-28 (1991) [2] Resnik, P. {\em Using Information Content to Evaluate Semantic Similarity in a Taxonomy}. In Proc. of the Int. Joint Conf. on Artificial Intelligence, Montreal, Quebec, Canada, August 20-25, Morgan Kaufmann, 448-453 (1995)]. [3] Wu, Z., Palmer, M. Verb semantics and lexical selection. In Proc. of the 32nd Annual Meeting of the Associations for Computational Linguistics, Las Cruces, New Mexico, 133-138 (1994). [4] Lin, D. An Information-Theoretic Definition of Similarity. In Proceedings of the Int. Conf. on Machine Learning, Madison, Wisconsin, USA. Morgan Kaufmann, 296-304 (1998). [5] Jiang, J.J., Conrath, D.W. Semantic Similarity Based on Corpus Statistics and Lexical Taxonomy. In Proc. of Inter. Conf. Research on Computational Linguistics (ROCLING X), Taiwan (1997). [6] Pirrò, G. A Semantic Similarity Metric Combining Features and Intrinsic Information Content. Data Knowl. Eng, 68(11), 1289-1308 (2009). [7] Adhikari, A., Dutta, B., Dutta, A., Mondal, D., Singh, S. An intrinsic information content-based semantic similarity measure considering the disjoint common subsumers of concepts of an ontology. J. Assoc. Inf. Sci. Technol. 69(8), 1023-1034 (2018). 7. A&M Adhikari, A., Singh, S., Mondal, D., Dutta, B., Dutta, A. A Novel Information Theoretic Framework for Finding Semantic Similarity in WordNet. CoRR, arXiv:1607.05422, abs/1607.05422 (2016). Finally, in each file, the correlation of our proposal with respect to human judgement is reported.
DOI: 10.17632/3gwfcvhhmv.1
title: 3DU_Technique_and_Dataset

description: 3DU Technique and Dataset
DOI: 10.17632/hwmm8bsjpd.1
title: Global horizontal irradiation data in Brazilian typical meteorological years

description: Global horizontal irradiation data and building performance simulation results derived from the research "Assessment of solar radiation data quality in typical meteorological years and its influence on the building performance simulation results".
DOI: 10.17632/39b9bbprcx.1
title: Dataset: Podporozhye

description: Spatial data are created based on different open data sources for the neighborhood area of the city Podporozhye (Leningrad Region, Russia) with a center in Tokari village. The Dataset consists of: 1. Edges – spatial line data, describing the potential roads. 2. Vertexes – spatial point data, describing the edges endpoints. 3. Terminals – spatial point data, describing centroids of artificial harvest units. 4. Zones – spatial data, used for graph decomposition. Since we are dealing with graph modeling of the forest road network, edge weights are obtained as weighted road construction costs. Used coordinate system: EPSG 32638 Area: approximately 1400 km^2. The graph contains 247 668 nodes, 1 143 690 edges, 239 terminals divided into 11 zones. For legal information please read the relevant file.
DOI: 10.17632/2pyrxc44wp.3
title: Microbiota_elements_recuperation_filters

description: Datasets contains raw and supplemental data for a paper "Elemental and microbiota content in indoor and outdoor air using recuperation unit filters".
DOI: 10.17632/grttt5ks7h.1
title: Stat_data_sOPG and cIMT are Related to High Arterial Stiffness

description: Data spreadsheet of manuscript: Serum Osteoprotegerin and Carotid Intima-Media Thickness are Related to High Arterial Stiffness in Heart Failure with Reduced Ejection Fraction
DOI: 10.17632/k9kvm5tn3f.1
title: Data repository for Camargo, et. al. A comprehensive, open-source dataset of lower limb biomechanics. Part 2 of 3

description: Part 2/3 of the dataset for "Camargo, et. al. A comprehensive, open-source dataset of lower limb biomechanics in multiple conditions of stairs, ramps, and level-ground ambulation and transitions." Dataset linked from https://doi.org/10.1016/j.jbiomech.2021.110320 (2021-02-24)
DOI: 10.5281/zenodo.4563227
title: CoVaxxy Tweet IDs data set

description: A collection of Tweet IDs related to Covid-19 Vaccines, gathered from Twitter since Jan 4, 2021. Please see https://arxiv.org/abs/2101.07694 for more information.
DOI: 10.6084/m9.figshare.14120549
title: test.xlsx

description: A test
DOI: 10.6084/m9.figshare.14120549.v1
title: test.xlsx

description: A test
DOI: 10.5281/zenodo.4563220
title: First DIHARD Challenge -- System Submissions and Scores

description: This dataset contains all submissions to the First DIHARD Speech Diarization Challenge (DIHARD I) as well as the output of the official scoring tool for these submissions. We are releasing it to the research community to support the development of new evaluation metrics for speech activity detection/diarization and system combination techniques. For more details about the evaluation, please consult the evaluation plan: https://zenodo.org/record/1199638 or the evaluation website: https://dihardchallenge.github.io/dihard1/index.html <strong>**NOTE**</strong> that this release only includes the system RTTMs that teams submitted to the DIHARD I scoring server. It does <strong>**NOT** </strong>include the DIHARD I evaluation set reference RTTMs and UEMs, which are needed to score the system outputs. These reference RTTM/UEM files are distributed by the Linguistic Data Consortium (LDC) as part of LDC2019S12 and LDC2019S13: LDC2019S12 -- First DIHARD Challenge Evaluation - Nine Sources LDC2019S13 -- First DIHARD Challenge Evaluation - SEEDLingS
DOI: 10.5281/zenodo.1207281
title: system1

description: system1
DOI: 10.5281/zenodo.4563219
title: First DIHARD Challenge -- System Submissions and Scores

description: This dataset contains all submissions to the First DIHARD Speech Diarization Challenge (DIHARD I) as well as the output of the official scoring tool for these submissions. We are releasing it to the research community to support the development of new evaluation metrics for speech activity detection/diarization and system combination techniques. For more details about the evaluation, please consult the evaluation plan: https://zenodo.org/record/1199638 or the evaluation website: https://dihardchallenge.github.io/dihard1/index.html <strong>**NOTE**</strong> that this release only includes the system RTTMs that teams submitted to the DIHARD I scoring server. It does <strong>**NOT** </strong>include the DIHARD I evaluation set reference RTTMs and UEMs, which are needed to score the system outputs. These reference RTTM/UEM files are distributed by the Linguistic Data Consortium (LDC) as part of LDC2019S12 and LDC2019S13: LDC2019S12 -- First DIHARD Challenge Evaluation - Nine Sources LDC2019S13 -- First DIHARD Challenge Evaluation - SEEDLingS
DOI: 10.5281/zenodo.1206311
title: LateSys

description: LateSys 0
DOI: 10.5281/zenodo.1207280
title: system1

description: system1
DOI: 10.5281/zenodo.1206310
title: LateSys

description: LateSys 0
DOI: 10.5517/ccdc.csd.cc20zr0s
title: CCDC 1876585: Experimental Crystal Structure Determination

description: Related Article: Qiong Zhang, Shujing Wang, Yingzhong Zhu, Chengkai Zhang, Hongzhi Cao, Wen Ma, Xiaohe Tian, Jieying Wu, Hongping Zhou, Yupeng Tian|2021|Inorg.Chem.|60|2362|doi:10.1021/acs.inorgchem.0c03245
DOI: 10.5517/ccdc.csd.cc2356xf
title: CCDC 1941434: Experimental Crystal Structure Determination

description: Related Article: Qiong Zhang, Shujing Wang, Yingzhong Zhu, Chengkai Zhang, Hongzhi Cao, Wen Ma, Xiaohe Tian, Jieying Wu, Hongping Zhou, Yupeng Tian|2021|Inorg.Chem.|60|2362|doi:10.1021/acs.inorgchem.0c03245
DOI: 10.5517/ccdc.csd.cc20ztrl
title: CCDC 1876670: Experimental Crystal Structure Determination

description: Related Article: Qiong Zhang, Shujing Wang, Yingzhong Zhu, Chengkai Zhang, Hongzhi Cao, Wen Ma, Xiaohe Tian, Jieying Wu, Hongping Zhou, Yupeng Tian|2021|Inorg.Chem.|60|2362|doi:10.1021/acs.inorgchem.0c03245
DOI: 10.5517/ccdc.csd.cc20zxkh
title: CCDC 1876757: Experimental Crystal Structure Determination

description: Related Article: Qiong Zhang, Shujing Wang, Yingzhong Zhu, Chengkai Zhang, Hongzhi Cao, Wen Ma, Xiaohe Tian, Jieying Wu, Hongping Zhou, Yupeng Tian|2021|Inorg.Chem.|60|2362|doi:10.1021/acs.inorgchem.0c03245
DOI: 10.5517/ccdc.csd.cc20zyjh
title: CCDC 1876787: Experimental Crystal Structure Determination

description: Related Article: Qiong Zhang, Shujing Wang, Yingzhong Zhu, Chengkai Zhang, Hongzhi Cao, Wen Ma, Xiaohe Tian, Jieying Wu, Hongping Zhou, Yupeng Tian|2021|Inorg.Chem.|60|2362|doi:10.1021/acs.inorgchem.0c03245
DOI: 10.5517/ccdc.csd.cc242smn
title: CCDC 1968891: Experimental Crystal Structure Determination

description: Related Article: Wenjia Hao, Bo Jin, Tao Huang, Jinhao Zhang, Juan Shen, Peng Rufang|2021|J.Solid State Chem.|297|122001|doi:10.1016/j.jssc.2021.122001
DOI: 10.5517/ccdc.csd.cc242srs
title: CCDC 1968895: Experimental Crystal Structure Determination

description: Related Article: Wenjia Hao, Bo Jin, Tao Huang, Jinhao Zhang, Juan Shen, Peng Rufang|2021|J.Solid State Chem.|297|122001|doi:10.1016/j.jssc.2021.122001
DOI: 10.5517/ccdc.csd.cc2446wd
title: CCDC 1970263: Experimental Crystal Structure Determination

description: Related Article: Qiong Zhang, Shujing Wang, Yingzhong Zhu, Chengkai Zhang, Hongzhi Cao, Wen Ma, Xiaohe Tian, Jieying Wu, Hongping Zhou, Yupeng Tian|2021|Inorg.Chem.|60|2362|doi:10.1021/acs.inorgchem.0c03245
DOI: 10.5517/ccdc.csd.cc24ymsj
title: CCDC 1994688: Experimental Crystal Structure Determination

description: Related Article: Peng Zhou, Shan Yan, Yuanyuan Lu, Xiao-Nian Li, Mi Zhang, Qin Li, Xia Chen, Jianping Wang, Hucheng Zhu, Chunmei Chen, Yonghui Zhang|2021|Fitoterapia|150|104840|doi:10.1016/j.fitote.2021.104840
DOI: 10.5517/ccdc.csd.cc25ly0r
title: CCDC 2014194: Experimental Crystal Structure Determination

description: Related Article: Shunya Honda, Ryutaro Sugawara, Shintaro Ishida, Takeaki Iwamoto|2021|J.Am.Chem.Soc.|143|2649|doi:10.1021/jacs.0c12426
DOI: 10.5517/ccdc.csd.cc25ly1s
title: CCDC 2014195: Experimental Crystal Structure Determination

description: Related Article: Shunya Honda, Ryutaro Sugawara, Shintaro Ishida, Takeaki Iwamoto|2021|J.Am.Chem.Soc.|143|2649|doi:10.1021/jacs.0c12426
DOI: 10.5517/ccdc.csd.cc25s044
title: CCDC 2019065: Experimental Crystal Structure Determination

description: Related Article: Pei-Pei Cui, Xiu-Du Zhang, Yan-Shang Kang, Yue Zhao, Wei-Yin Sun|2021|Inorg.Chem.|60|2563|doi:10.1021/acs.inorgchem.0c03461
DOI: 10.5517/ccdc.csd.cc25s066
title: CCDC 2019067: Experimental Crystal Structure Determination

description: Related Article: Pei-Pei Cui, Xiu-Du Zhang, Yan-Shang Kang, Yue Zhao, Wei-Yin Sun|2021|Inorg.Chem.|60|2563|doi:10.1021/acs.inorgchem.0c03461
DOI: 10.5517/ccdc.csd.cc25s077
title: CCDC 2019068: Experimental Crystal Structure Determination

description: Related Article: Pei-Pei Cui, Xiu-Du Zhang, Yan-Shang Kang, Yue Zhao, Wei-Yin Sun|2021|Inorg.Chem.|60|2563|doi:10.1021/acs.inorgchem.0c03461
DOI: 10.5517/ccdc.csd.cc25s088
title: CCDC 2019069: Experimental Crystal Structure Determination

description: Related Article: Pei-Pei Cui, Xiu-Du Zhang, Yan-Shang Kang, Yue Zhao, Wei-Yin Sun|2021|Inorg.Chem.|60|2563|doi:10.1021/acs.inorgchem.0c03461
DOI: 10.5517/ccdc.csd.cc25s099
title: CCDC 2019070: Experimental Crystal Structure Determination

description: Related Article: Pei-Pei Cui, Xiu-Du Zhang, Yan-Shang Kang, Yue Zhao, Wei-Yin Sun|2021|Inorg.Chem.|60|2563|doi:10.1021/acs.inorgchem.0c03461
DOI: 10.3886/e119446v60-80020
title: COVID-19 US State Policy Database

description: For questions or comments about the database please contact:<br>Alexandra Skinner <br>skinnera@bu.edu <br>Research Fellow & Database Manager<br>Department of Health Law, Policy & Management <br>Boston University School of Public Health<br><br>Database of state policies on closures, shelter-in-place orders, housing protections, changes to Medicaid and SNAP, physical distancing closures, reopening, and more created by researchers at the Boston University School of Public Health. Policies included are state-wide directives or mandates, not guidance or recommendations. In order for a policy to be included, it must apply to the entire state. We are working quickly to go through state government websites to make the policy database as complete and accurate as possible in a rapidly changing policy context. If you use data on a given policy, we encourage you to triangulate based on additional sources of policy data and to review the source documentation to consider the coding decisions that are right for your work. Of course, please email us if you note a discrepancy so we can improve the database for everyone. State policy source documentation can be found at: tinyurl.com/statepolicysources.
description: other; Contributors: Megan Cole Brahim, Noa Krawczyk, Carolyn Hoffman, Claire Corkish, Elizabeth Ferrara, Elizabeth Long, Emily Baroni, Faith Contador, Hannah Simon, Morgan Simko, Rachel Scheckman, Sarah Brewer, Sue Kulkarni, Felicia Heykoop, Manish Patel, Aishwarya Vidyasagaran, Andrew Chiao, Cara Safon, Samantha Burkhart, Harry Jung, Victor Lee, Marina MacKinnon, Aarohi Rede, Marie Vearling, Sophie Li, Christina Wang, Tim Levengood, María Jordán P. Emma Chistolini
description: State policies. Smallest Geographic Unit: State
DOI: 10.5517/ccdc.csd.cc26219n
title: CCDC 2027750: Experimental Crystal Structure Determination

description: Related Article: Heekyoung Choi, Soichiro Ogi, Naoki Ando, Shigehiro Yamaguchi|2021|J.Am.Chem.Soc.|143|2953|doi:10.1021/jacs.0c13353
DOI: 10.3886/e100957v1-80040
title: Adults with Asperger syndrome are less proficient in identifying actions portrayed with point-light displayed biological motion

description: The present study investigated the perception of biological motion in healthy adults and adults with Asperger’s or high functioning autism, using an identification task of point-light displayed human actions with or without making contact with objects. Compared to the healthy group (N=30), the AS/HFA group (N=27) had a significantly lower number of correct items and longer response times. Both groups performed better at naming the actions without making contact with objects than those involving objects. Individual differences in the AQ scores correlated with the biological motion task performance such that those exhibited higher autistic traits tended to make more errors and responded more slowly. Our findings suggest that adults with AS/HFA are less proficient in processing biological motion actions.
DOI: 10.5517/ccdc.csd.cc26m0gb
title: CCDC 2044061: Experimental Crystal Structure Determination

description: Related Article: Xu-Long Qin, Ang Li, Fu-She Han|2021|J.Am.Chem.Soc.|143|2994|doi:10.1021/jacs.1c00277
DOI: 10.5281/zenodo.4563236
title: HeteroFuzz

description: HeteroFuzz supplementary material.
DOI: 10.5517/ccdc.csd.cc26xynr
title: CCDC 2053615: Experimental Crystal Structure Determination

description: Related Article: Jason P. Stone, Elizabeth A. Decoteau, Matthew J. Polinski|2021|J.Solid State Chem.|297|122048|doi:10.1016/j.jssc.2021.122048
DOI: 10.5517/ccdc.csd.cc26xyps
title: CCDC 2053616: Experimental Crystal Structure Determination

description: Related Article: Jason P. Stone, Elizabeth A. Decoteau, Matthew J. Polinski|2021|J.Solid State Chem.|297|122048|doi:10.1016/j.jssc.2021.122048
DOI: 10.5517/ccdc.csd.cc26xyqt
title: CCDC 2053617: Experimental Crystal Structure Determination

description: Related Article: Jason P. Stone, Elizabeth A. Decoteau, Matthew J. Polinski|2021|J.Solid State Chem.|297|122048|doi:10.1016/j.jssc.2021.122048
DOI: 10.5517/ccdc.csd.cc26xyrv
title: CCDC 2053618: Experimental Crystal Structure Determination

description: Related Article: Jason P. Stone, Elizabeth A. Decoteau, Matthew J. Polinski|2021|J.Solid State Chem.|297|122048|doi:10.1016/j.jssc.2021.122048
DOI: 10.5517/ccdc.csd.cc26xysw
title: CCDC 2053619: Experimental Crystal Structure Determination

description: Related Article: Jason P. Stone, Elizabeth A. Decoteau, Matthew J. Polinski|2021|J.Solid State Chem.|297|122048|doi:10.1016/j.jssc.2021.122048
DOI: 10.5517/ccdc.csd.cc26xytx
title: CCDC 2053620: Experimental Crystal Structure Determination

description: Related Article: Jason P. Stone, Elizabeth A. Decoteau, Matthew J. Polinski|2021|J.Solid State Chem.|297|122048|doi:10.1016/j.jssc.2021.122048
DOI: 10.5517/ccdc.csd.cc26xyvy
title: CCDC 2053621: Experimental Crystal Structure Determination

description: Related Article: Jason P. Stone, Elizabeth A. Decoteau, Matthew J. Polinski|2021|J.Solid State Chem.|297|122048|doi:10.1016/j.jssc.2021.122048
DOI: 10.5517/ccdc.csd.cc26xywz
title: CCDC 2053622: Experimental Crystal Structure Determination

description: Related Article: Jason P. Stone, Elizabeth A. Decoteau, Matthew J. Polinski|2021|J.Solid State Chem.|297|122048|doi:10.1016/j.jssc.2021.122048
DOI: 10.25822/jpdr-vz50
title: NCH Sleep DataBank
DOI: 10.6084/m9.figshare.14120576
title: Ribosomal protein database of Pseudomonas aeruginosa ATCC 15692

description: This work presents the ribosomal protein database of <i>Pseudomonas aeruginosa </i>ATCC 15692<i>. </i>Original data for the work came from the annotated proteome data of the bacterium downloaded from UniProt. Using an in-house MATLAB ribosomal protein database analysis software, the original proteome data file was parsed to extract protein name and amino acid sequence of all ribosomal proteins in the species. The database also includes calculated variables such as number of residues, molecular weight, and nucleotide sequence. Overall, the presented database could serve as a ribosomal protein mass fingerprint for use in microbial identification, or it could be used in fundamental studies seeking to uncover new insights into ribosomal protein biology.
DOI: 10.6084/m9.figshare.14120576.v1
title: Ribosomal protein database of Pseudomonas aeruginosa ATCC 15692

description: This work presents the ribosomal protein database of <i>Pseudomonas aeruginosa </i>ATCC 15692<i>. </i>Original data for the work came from the annotated proteome data of the bacterium downloaded from UniProt. Using an in-house MATLAB ribosomal protein database analysis software, the original proteome data file was parsed to extract protein name and amino acid sequence of all ribosomal proteins in the species. The database also includes calculated variables such as number of residues, molecular weight, and nucleotide sequence. Overall, the presented database could serve as a ribosomal protein mass fingerprint for use in microbial identification, or it could be used in fundamental studies seeking to uncover new insights into ribosomal protein biology.
DOI: 10.5281/zenodo.4562934
title: Submissions_dcase_2020_task4

description: Predictions and technical reports of the systems submitted to DCASE task 4 2020.
DOI: 10.5281/zenodo.4562933
title: Submissions_dcase_2020_task4

description: Predictions and technical reports of the systems submitted to DCASE task 4 2020.
DOI: 10.25919/9nqb-dy30
title: Parkes observations for project P1092 semester 2020OCTS_11

description: We propose to use the Parkes UWL receiver for confirmation and monitoring a sub-set of bright FAST-discovered pulsars, especially for those discoveries located outside the sky regions covered by the purchased PX-500 project. For special FAST discoveries that already confirmed by Parkes, such as MSPs or pulsars with interesting emission properties, we propose to do long-term monitoring for them as well. These monitoring aim to solve their parameters, binary orbit, and provide significant insight into the special emission properties of these new discoveries and facilitate science. The Parkes UWL system provides a unique capability for studying the pulsars over wide bandwidths, in term of both the timing precision and frequency-dependent observing properties.