cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/dpsxm39y5r.1
title: Experimental videos in studying the influences of dry- and wet-bed downstream conditions on dam break multiphase flood waves in a reservoir with 17.5 cm sediment depth (58.3% silted-up)

description: Experimental videos: Herein, 24 distinct video files have been presented which related to dam break multiphase flood shock wave experiments, performed in the Shiraz University, Civil and Environmental Engineering Department’s Hydraulic Lab (Shiraz, Iran). The initial upstream sediment depth was 17.5 cm which makes the upstream reservoir 58.3% silted-up with respect to the total 30 cm height of the reservoir. Different initial downstream conditions have also been considered including dry-bed downstream and wet-bed downstream with different levels of standing water; 2 cm, 4 cm and 5 cm. Considering three cameras which covered length of the flume, 4 different dam break scenarios and 2 repetitions conducted for each test, a total of 24 videos collected which presented in this document. The additional explanations related to video files can be seen in “Explanation table of videos” file which attached to this document in Microsoft Word (DOCX/DOC) format. Foad Vosoughi, Gholamreza Rakhshandehroo, Mohammad Reza Nikoo Affiliations 1st Author: Foad Vosoughi, Research Associate, Department of Civil and Environmental Engineering, Shiraz University, Shiraz, Iran. foad.vosooghi@gmail.com 2nd Author: Gholamreza Rakhshandehroo, Professor, Department of Civil and Environmental Engineering, Shiraz University, Shiraz, Iran. 3rd Author: Mohammad Reza Nikoo, Associate Professor, Department of Civil and Environmental Engineering, Shiraz University, Shiraz, Iran.
DOI: 10.17632/95wbd7kbf2.1
title: Supplement to The influence of changing seawater Ca concentration on Elements/Ca ratios in planktonic foraminifera: a culture experiment - AGU G3

description: Resume table of planktic foraminifera G. siphonifera culture
DOI: 10.17632/gx8dwgvygn.1
title: Spinner Flowmeter

description: A methodology is developed for a new hydraulic characterization of continental hydrological basins. For this purpose, the division of wells into flow stretches with different hydraulic behaviour is made according to the results of the flowmeter, supposing the hypothesis hydraulic head of the deepest flow stretches of the well do not necessarily match the head showed by the overall well. The data used come from a water-well located in a multi-layered aquifer that makes up the detrital continental basin of the Tajo River, in the center of the Iberian Peninsula. These data collect the results of the step-drawdown pumping test, and the flowmeter log data and the fundamental hydraulic parameters needed (Reynolds number, turbulence exponent, friction factor, …). Two files are included in data base: Flowmeter Results CNCP Well (raw-data).txt file shows Depth (m), Measured velocity, Reynold Number, Turbulence exponent, Mean velocity and Friction Factor values. Step-drawdown pumping-test CNCP file shows STEP DRAWDOWN PUMPING TEST data: t (min), Q (ℓ/s) and z (m).
DOI: 10.17632/y3j76mrkdn.1
title: Single-cell characterization of malignant phenotypes and development trajectories of adrenal neuroblastoma. Rui Dong et al

description: Original materials for figures from the paper "Single-cell characterization of malignant phenotypes and development trajectories of adrenal neuroblastoma" by Rui Dong et al.
DOI: 10.17632/vwp3xvp2x8.1
title: Data for "Within- and Between-Person Factor Structure of the Oldenburg Burnout Inventory: Analysis of a Diary Study using Multilevel Confirmatory Factor Analysis"

description: The study examined the factor structure of burnout, as measured with the Oldenburg Burnout Inventory, taking into account a hierarchical data structure: daily evaluations nested in persons. The participants were 235 employees of a public administration agency who assessed their burnout online immediately after office hours for 10 consecutive working days (from Monday to Friday). Two models were tested with multilevel confirmatory factor analysis, assuming the same one or two-factor structure tested at the within- and between-person levels. The results were ambiguous, as both models showed a reasonable fit to the data. However, since exhaustion and disengagement were strongly correlated at each level and within-person reliability for disengagement was rather low, a unidimensional model seems more valid. Nonetheless, cross-level invariance was not confirmed for either of the structures, showing that factor loadings for the same items differ significantly between the levels. These results suggest that burnout is not the same latent variable at each level; rather, there are factors other than daily burnout experiences that influence person-level scores on the items. Ignoring these across-level discrepancies may lead to biased conclusions, since individuals were found to be an unexpected source of construct variability in our study
DOI: 10.17632/38x8ktrx7y.1
title: Categorical auditory working memory in crows

description: Categorical auditory working memory in crows
DOI: 10.17632/ghh6w67vmx.1
title: The short- and long-range RNA-RNA Interactome of SARS-CoV-2. Ziv et al.

description: Supplemental files accompanying Ziv et al.'s paper "The short- and long-range RNA-RNA Interactome of SARS-CoV-2"
DOI: 10.17632/nvkks22k32.1
title: Total FeO contents for uncorrected melt inclusions vs Fo values

description: Figure S1 Total FeO contents for uncorrected melt inclusions vs Fo values of their olivine hosts from Tahe basaltic tranchyandesite. The slightly negative correlation between FeO contents of melt inclusions and Fo values of their olivine host is recognized as the so-called ‘‘Fe-loss’’ [Danyushevsky et al., 2000]. The gray band indicates the initial total FeO content.
DOI: 10.5281/zenodo.4066885
title: Replication package for: The Aggregate Implications of Mergers and Acquisitions

description: The package contains the codes to replicate the figures and tables in David (forthcoming). "The Aggregate Implications of Mergers and Acquisitions." Review of Economic Studies. Detailed instructions are also given about accessing the raw data.
DOI: 10.5281/zenodo.4039888
title: Replication package for: The Aggregate Implications of Mergers and Acquisitions

description: The package contains the codes to replicate the figures and tables in David (forthcoming). "The Aggregate Implications of Mergers and Acquisitions." Review of Economic Studies. Detailed instructions are also given about accessing the raw data.
DOI: 10.5281/zenodo.2578166
title: Initial dataset used in SIMON, an automated machine learning approach

description: The 7-Zip file contains raw data in the CSV file downloaded from Stanford Data Miner and used for further analysis using mulset algorithm and SIMON, as described in the publication: Tomic A, Tomic I, Rosenberg-Hasson Y, Dekker CL, Maecker HT, and Davis MM. SIMON, an automated machine learning system reveals immune signatures of influenza vaccine responses. <em>JImmunol</em>, doi: 10.4049/jimmunol.1900033, 2019. File was compressed using 7-Zip available at https://www.7-zip.org/.
DOI: 10.5281/zenodo.2578165
title: Initial dataset used in SIMON, an automated machine learning approach

description: The 7-Zip file contains raw data in the CSV file downloaded from Stanford Data Miner and used for further analysis using mulset algorithm and SIMON, as described in the publication: Tomic A, Tomic I, Rosenberg-Hasson Y, Dekker CL, Maecker HT, and Davis MM. SIMON, an automated machine learning system reveals immune signatures of influenza vaccine responses. <em>JImmunol</em>, doi: 10.4049/jimmunol.1900033, 2019. File was compressed using 7-Zip available at https://www.7-zip.org/.
DOI: 10.6084/m9.figshare.13122809
title: Genetic diversity and taxonomic status of Gymnocypris chilianensis based on the mitochondrial DNA D-loop region

description: To analyse the genetic diversity and taxonomic status of <i>Gymnocypris chilianensis</i>, <i>D-loop</i> region of the mitochondrial DNA was sequenced in 50 individuals of <i>G. chilianensis</i> obtained from two geographic locations (Heihe River and Shule River) and 25 individuals of <i>G. przewalskii</i>. These samples were analyzed for genetic diversity and sequence divergence, and 25 homologous sequences of another affinity <i>G. eckloni</i> downloaded from GenBank were analyzed. The results revealed that <i>G. chilianensis</i> of the Shule River showed lower haplotype diversity (Hd = 0.963) as well as nucleotide diversity (Pi = 0.00414) than the other populations, indicating that <i>G. chilianensis</i> of the Shule River should be protected preferentially due to its lower level of genetic diversity. The study also demonstrated the genetic distance of <i>G. chilianensis</i> in both Heihe River and Shule River was 0.0013, and the genetic distances between the aforementioned two populations and the <i>G. przewalskii</i> were 0.0143 and 0.0137, respectively. The genetic distances between the two <i>G. chilianensis</i> populations and the <i>G. eckloni</i> were 0.0148 and 0.0141, respectively. The NJ phylogenetic trees showed that <i>G. chilianensis</i> had further genetic distance with <i>G. eckloni</i> and <i>G. przewalskii</i>. Therefore, <i>G. chilianensis</i> could be considered as an independent species of <i>Gymnocypris</i>.
DOI: 10.6084/m9.figshare.13122809.v1
title: Genetic diversity and taxonomic status of Gymnocypris chilianensis based on the mitochondrial DNA D-loop region

description: To analyse the genetic diversity and taxonomic status of <i>Gymnocypris chilianensis</i>, <i>D-loop</i> region of the mitochondrial DNA was sequenced in 50 individuals of <i>G. chilianensis</i> obtained from two geographic locations (Heihe River and Shule River) and 25 individuals of <i>G. przewalskii</i>. These samples were analyzed for genetic diversity and sequence divergence, and 25 homologous sequences of another affinity <i>G. eckloni</i> downloaded from GenBank were analyzed. The results revealed that <i>G. chilianensis</i> of the Shule River showed lower haplotype diversity (Hd = 0.963) as well as nucleotide diversity (Pi = 0.00414) than the other populations, indicating that <i>G. chilianensis</i> of the Shule River should be protected preferentially due to its lower level of genetic diversity. The study also demonstrated the genetic distance of <i>G. chilianensis</i> in both Heihe River and Shule River was 0.0013, and the genetic distances between the aforementioned two populations and the <i>G. przewalskii</i> were 0.0143 and 0.0137, respectively. The genetic distances between the two <i>G. chilianensis</i> populations and the <i>G. eckloni</i> were 0.0148 and 0.0141, respectively. The NJ phylogenetic trees showed that <i>G. chilianensis</i> had further genetic distance with <i>G. eckloni</i> and <i>G. przewalskii</i>. Therefore, <i>G. chilianensis</i> could be considered as an independent species of <i>Gymnocypris</i>.
DOI: 10.6084/m9.figshare.12130980.v47
title: MOOD Maps of Google community mobility change during the COVID-19 outbreak

description: The MOOD project (MOnitoring Outbreak events for Disease surveillance in a data science context. H2020) has geo-referenced the data Google has published as a series of PDF files presenting reports on national and subnational human mobility levels relative to a baseline data of late January 2020. The details and the PDF files can be found at https://www.google.com/covid19/mobility/.<br>More detail on these files can be found at https://www.moodspatialdata.com/humanmobilityforcovid19 <br>The first set of data were released on April 2 2020 and have been revised weekly since then. The maps now utilise the CSV data released by Google. Please note that the maps figures use a mean of the previous three days, while the Google PDFs use a single days data so there will be differences between values in our maps when compare to the Google PDFs.<br>The authors have extracted the majority of these data into a series of excel spreadsheets. Each worksheet provides the data for % change in numbers of records at various types of location categories illustrated by: retail and recreation, grocery and pharmacy, parks and beaches, transit stations, workplaces and residential (columns f to K). A second set of columns calculates the difference of each value from the mean values for each category (columns L to P) Columns A to E contain geographical details. Column Q contains the names used to link to a mapping file.There are separate worksheets for the date of the data from each dated release (e.g. 2903, 0504 etc.) and separate worksheets calculating the changes between specific dates.<br>A second spreadsheet has been added calculating the 3 day moving mean of each day from the 15th of February. Each day is referenced by the Gregorian calendar day count. So day 48 = Feb 17th.<br>The maps (for EU & Global) display these data. We provide 600 dpi jpegs of the Global (“WD”) and European (“EU”) mapped values at the latest date available, for each of the mobility categories: retail and recreation (“retrec”) , grocery and pharmacy (“grocphar”) , parks (“parks”) , transit stations (“transit”), residential (“resid”) and workplaces (“work”). We also provide maps of the changes from the previous week (“ch”).<br>All data extracting and subsequent processing have been carried out by ERGO (Environmental Research Group Oxford) on behalf of the MOOD H2020 project. Data will be periodically updated. Additional maps can be obtained on request to the authors.
DOI: 10.5517/ccdc.csd.cc1jcf6j
title: CCDC 1411157: Experimental Crystal Structure Determination

description: Related Article: Hua Yang, Yan-Xia Meng, Hai-Quan Tian, Da-Cheng Li, Su-Yuan Zeng, You Song, Jian-Min Dou|2020|Dalton Trans.|49|1955|doi:10.1039/C9DT04383G
DOI: 10.5517/ccdc.csd.cc1zqk5f
title: CCDC 1838925: Experimental Crystal Structure Determination

description: Related Article: Manel Mansour, Takoua Ben Issa, Noureddine Issaoui, Ali Harchani, Enrique Guitierrez Puebla, Brahim Ayed|2019|J.Mol.Struct.|1197|478|doi:10.1016/j.molstruc.2019.05.043
DOI: 10.5517/ccdc.csd.cc201zln
title: CCDC 1848951: Experimental Crystal Structure Determination

description: Related Article: Amogh Kulkarni|2018|CSD Communication|||
DOI: 10.5517/ccdc.csd.cc20bmqq
title: CCDC 1857263: Experimental Crystal Structure Determination

description: Related Article: Leijie Zhou, Yuan Zeng, Xing Gao, Qijun Wang, Chang Wang, Bo Wang, Wei Wang, Yongjun Wu, Bing Zheng, Hongchao Guo|2019|Chem.Commun.|55|10464|doi:10.1039/C9CC05483A
DOI: 10.5517/ccdc.csd.cc20nrfw
title: CCDC 1866988: Experimental Crystal Structure Determination

description: Related Article: Suresh Madhu, Krishnaprasad Madica, Rajesh Gonnade, Gangadhar J. Sanjayan|2019|Tetrahedron Lett.|60|150920|doi:10.1016/j.tetlet.2019.07.011
DOI: 10.5517/ccdc.csd.cc21b5bx
title: CCDC 1886608: Experimental Crystal Structure Determination

description: Related Article: Szymon Sobczak, Aleksandra Półrolniczak, Paulina Ratajczyk, Weizhao Cai, Andrzej Gładysiak, Varvara I. Nikolayenko, Dominic C. Castell, Leonard J. Barbour, Andrzej Katrusiak|2020|Chem.Commun.|56|4324|doi:10.1039/D0CC00461H
DOI: 10.5517/ccdc.csd.cc21b5cy
title: CCDC 1886609: Experimental Crystal Structure Determination

description: Related Article: Szymon Sobczak, Aleksandra Półrolniczak, Paulina Ratajczyk, Weizhao Cai, Andrzej Gładysiak, Varvara I. Nikolayenko, Dominic C. Castell, Leonard J. Barbour, Andrzej Katrusiak|2020|Chem.Commun.|56|4324|doi:10.1039/D0CC00461H
DOI: 10.5517/ccdc.csd.cc21f1cx
title: CCDC 1889368: Experimental Crystal Structure Determination

description: Related Article: Pandi Muthukumar, Dohyun Moon, Savarimuthu Philip Anthony|2019|Cat.Sci.Tech.|9|4347|doi:10.1039/C9CY00759H
DOI: 10.5517/ccdc.csd.cc21jwn4
title: CCDC 1893066: Experimental Crystal Structure Determination

description: Related Article: Kenta Kato, Hsing-An Lin, Motonobu Kuwayama, Mai Nagase, Yasutomo Segawa, Lawrence T. Scott, Kenichiro Itami|2019|Chemical Science|10|9038|doi:10.1039/C9SC03061A
DOI: 10.5517/ccdc.csd.cc21khqv
title: CCDC 1893657: Experimental Crystal Structure Determination

description: Related Article: Sara A. Dille, Benjamin Mogesa, Jacilynn Brant, Victor N. Nemykin, Matthias Zeller, and Partha Basu|2019|CSD Communication|||
description: Related Article: Kyle J. Colston, Sara A. Dille, Benjamin Mogesa, Jacilynn Brant, Victor N. Nemykin, Matthias Zeller, Partha Basu|2020|RSC Advances|10|38294|doi:10.1039/D0RA07371G
DOI: 10.5517/ccdc.csd.cc21ntdy
title: CCDC 1896840: Experimental Crystal Structure Determination

description: Related Article: Stefano Racioppi, Michal Andrzejewski, Valentina Colombo, Angelo Sironi, Piero Macchi|2020|Inorg.Chem.|59|2223|doi:10.1021/acs.inorgchem.9b02852
DOI: 10.5517/ccdc.csd.cc21zqnf
title: CCDC 1906365: Experimental Crystal Structure Determination

description: Related Article: Eun Hye Wi, Ji Yeon Ryu, Seul Gi Lee, Ume Farwa, Moumita Pait, Sunwoo Lee, Sung Cho, Junseong Lee|2019|Inorg.Chem.|58|11493|doi:10.1021/acs.inorgchem.9b01288
DOI: 10.5517/ccdc.csd.cc225jld
title: CCDC 1911943: Experimental Crystal Structure Determination

description: Related Article: Sheng Zhang, Wenjiao Mo, Zengqi Zhang, Gaofei Pan, Lei Wang, Dengwei Hu, Sanping Chen|2019|Dalton Trans.|48|12466|doi:10.1039/C9DT02618E
DOI: 10.5517/ccdc.csd.cc1jss03
title: CCDC 1423985: Experimental Crystal Structure Determination

description: Related Article: Yupeng Pan, Chao Guan, Huaifeng Li, Priyanka Chakraborty, Chunhui Zhou, Kuo-Wei Huang|2019|Dalton Trans.|48|12812|doi:10.1039/C9DT01319A
DOI: 10.5517/ccdc.csd.cc2268wg
title: CCDC 1912665: Experimental Crystal Structure Determination

description: Related Article: Wen-Wen Zi, Zihao Gao, Jun Zhang, Jing-Hui Lv, Bao-Xun Zhao, Yu-Fei Jiang, Hong-Bin Du, Fei-Jian Chen|2019|Microporous and Mesoporous Materials|290|109654|doi:10.1016/j.micromeso.2019.109654
DOI: 10.5517/ccdc.csd.cc227czp
title: CCDC 1913722: Experimental Crystal Structure Determination

description: Related Article: Thach N. Tu, Huong T. D. Nguyen, Nhung Thi Tran|2019|Inorg.Chem.Front.|6|2441|doi:10.1039/C9QI00543A
DOI: 10.5517/ccdc.csd.cc22ccnh
title: CCDC 1917556: Experimental Crystal Structure Determination

description: Related Article: Yuanbin Zhang, Lingyao Wang, Jianbo Hu, Simon Duttwyler, Xili Cui, Huabin Xing|2020|CrystEngComm|22|2649|doi:10.1039/D0CE00142B
DOI: 10.6084/m9.figshare.12674006
title: SeaSafe_May_2014_April 2017_final data 2018.xlsx

description: SeaSafe project was developed to provide Lifeguard services in the beach areas of Cox's Bazar District of Bangladesh. The project was established in low resource setting. Under this project daily incidence reports were collected during May 2014 and April 2017 and developed a data bases. The data covered basic information about the drowning casualties as well cause and consequences of the casualties followed by rescue from the water.
DOI: 10.6084/m9.figshare.12674006.v1
title: SeaSafe_May_2014_April 2017_final data 2018.xlsx

description: SeaSafe project was developed to provide Lifeguard services in the beach areas of Cox's Bazar District of Bangladesh. The project was established in low resource setting. Under this project daily incidence reports were collected during May 2014 and April 2017 and developed a data bases. The data covered basic information about the drowning casualties as well cause and consequences of the casualties followed by rescue from the water.
DOI: 10.6084/m9.figshare.13121117.v4
title: Longitudinal cross-sectional dataset of physicians’ personal qualities and online reputation on www.haodf.com.zip

description: This research data is longitudinal cross-sectional data that records the personal characteristics (including competence, benevolence, and integrity) and online reputation (platform’s online scoring and patients’ online reviews) of physicians on www.haodf.com.<br><br>
DOI: 10.6084/m9.figshare.13121117
title: Longitudinal cross-sectional dataset of physicians’ personal qualities and online reputation on www.haodf.com.zip

description: This research data is longitudinal cross-sectional data that records the personal characteristics (including competence, benevolence, and integrity) and online reputation (platform’s online scoring and patients’ online reviews) of physicians on www.haodf.com.<br><br>
DOI: 10.6084/m9.figshare.13121117.v3
title: Longitudinal cross-sectional dataset of physicians’ personal qualities and online reputation on www.haodf.com.zip

description: This research data is longitudinal cross-sectional data that records the personal characteristics (including competence, benevolence, and integrity) and online reputation (platform’s online scoring and patients’ online reviews) of physicians on www.haodf.com.<br><br>
DOI: 10.6084/m9.figshare.13123016
title: Statistics

description: All statistical outcomes from the paper: Synergy activations are similar between gait patterns in cerebral palsy, synergy weights are not.
DOI: 10.6084/m9.figshare.13123016.v1
title: Statistics

description: All statistical outcomes from the paper: Synergy activations are similar between gait patterns in cerebral palsy, synergy weights are not.
DOI: 10.6084/m9.figshare.13122989
title: Data.xlsx

description: All data used in the study: "Synergy activations are similar between gait patterns in cerebral palsy, synergy weights are not"
DOI: 10.6084/m9.figshare.13122989.v1
title: Data.xlsx

description: All data used in the study: "Synergy activations are similar between gait patterns in cerebral palsy, synergy weights are not"
DOI: 10.21227/2csm-3723
title: Simulated InSAR building dataset for CVCMFF Net

description: The simulated InSAR building dataset contains 312 simulated SAR image pairs generated from 39 different building models. Each building model is simulated at 8 viewing-angles. The sample number is 216 of the train set and is 96 of the test set. Each simulated InSAR sample contains three channels: master SAR image, slave SAR image, and interferometric phase image. This dataset serves the CVCMFF Net for building semantic segmentation of InSAR images.
DOI: 10.21227/63jw-2107
title: Simulated InSAR building dataset for CVCMFF Net

description: The simulated InSAR building dataset contains 312 simulated SAR image pairs generated from 39 different building models. Each building model is simulated at 8 viewing-angles. The sample number is 216 of the train set and is 96 of the test set. Each simulated InSAR sample contains three channels: master SAR image, slave SAR image, and interferometric phase image. This dataset serves the CVCMFF Net for building semantic segmentation of InSAR images.
DOI: 10.21227/g7zd-5z33
title: Y-Model 0

description: Y-Model 0
DOI: 10.5281/zenodo.4006120
title: POES N15 spacecraft L* values 1998-2014 determined by the TS05 external magnetic field model

description: L* values for the POES N15 spacecraft from 1998-2014 determined by the TS05 external magnetic field model. L* calculations were performed by the SpacePy package in Python (https://spacepy.github.io/). Each year has been broken up into multiple files in chronological number order (beginning at 1) . The number of files for each year are as follows: 1998 - 5 1999 - 10 2000-2014 - 15 Each file is a gzipped csv file named via the following: poes_n15_YEAR_FILENUM.csv.gz. References: Tsyganenko, N. A., and Sitnov, M. I. (2005), Modeling the dynamics of the inner magnetosphere during strong geomagnetic storms, <em>J. Geophys. Res.</em>, 110, A03208, doi:10.1029/2004JA010798.