cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5517/ccdc.csd.cc26s9s3
title: CCDC 2049155: Experimental Crystal Structure Determination

description: Related Article: Roshan K. Dhungana, Rishi R. Sapkota, Laura M. Wickham, Doleshwar Niroula, Ramesh Giri|2020|J.Am.Chem.Soc.|142|20930|doi:10.1021/jacs.0c09778
DOI: 10.5517/ccdc.csd.cc26s9t4
title: CCDC 2049156: Experimental Crystal Structure Determination

description: Related Article: Sheng Feng, Kang Wang, Yifan Ping, Jianbo Wang|2020|J.Am.Chem.Soc.|142|21032|doi:10.1021/jacs.0c08089
DOI: 10.6084/m9.figshare.12000225
title: Antimicrobial resistance surveillance report, Angkor Hospital for Children, Cambodia, 01 Jan 2016 to 31 Dec 2016

description: Updated on 12<sup>th</sup> January 2021<br> This update fixes inaccurate estimations of the proportion of non-susceptible isolates of <i>E. coli </i>and <i>K. pneumoniae</i> for ampicillin (page 9-10 and page 18-21 in the AMR surveillance report) in AMASS 1.0. The updated AMR surveillance report and output files were generated by AMASS 1.1 using the same data sets and data dictionary files. AMASS 1.1 (figshare link https://figshare.com/articles/dataset/AMASS_zip/7763330) fixes a typo in the R code (z_Rcode.R file) of the AMASS 1.0 that caused the inaccurate estimations.<br>AutoMated tool for Antimicrobial resistance Surveillance System (AMASS) was developed as an offline, open-access and easy-to-use application that allows a hospital to perform data analysis independently and generate isolate-based and sample-based surveillance reports stratified by infection origin from routinely collected electronic databases. AMASS performs data analysis and generates reports automatically. The application can be downloaded from https://www.amass.website.<br>This is a repository of the files for Angkor Hospital for Children. The attached four files are:1) The AMR surveillance report automatically generated from AMASS using hospital admission and microbiology data of Angkor Hospital for Children in Cambodia2) Aggregated summary data in .csv format automatically generated from AMASS3) Data dictionary for microbiology data file of Angkor Hospital for Children (configured by the hospital to be used with the AMASS application)4) Data dictionary for hospital admission data of Angkor Hospital for Children (configured by the hospital to be used with the AMASS application)<br>Please note that the two data dictionary files can be re-used with the data files of the hospital in the future in cases when variables names and values in the raw data remained unchanged.<br><br>
DOI: 10.6084/m9.figshare.12000222
title: Antimicrobial resistance surveillance report, Mahosot Hospital, Lao PDR, 01 Jul 2019 to 30 Sep 2019

description: Updated on 12<sup>th</sup> January 2021<br> This update fixes inaccurate estimations of the proportion of non-susceptible isolates of <i>E. coli </i>and <i>K. pneumoniae</i> for ampicillin (page 9-10 in the AMR surveillance report) in AMASS 1.0. The updated AMR surveillance report and output files were generated by AMASS 1.1 using the same data sets and data dictionary files. AMASS 1.1 (figshare link https://figshare.com/articles/dataset/AMASS_zip/7763330) fixes a typo in the R code (z_Rcode.R file) of the AMASS 1.0 that caused the inaccurate estimations.<br>AutoMated tool for Antimicrobial resistance Surveillance System (AMASS) was developed as an offline, open-access and easy-to-use application that allows a hospital to perform data analysis independently and generate isolate-based and sample-based surveillance reports stratified by infection origin from routinely collected electronic databases. AMASS performs data analysis and generates reports automatically. The application can be downloaded from https://www.amass.website<br>This is a repository of the files for Mahosot Hospital. The attached three files are:1) The AMR surveillance report automatically generated from AMASS using hospital admission and microbiology data of Mahosot Hospital in Lao PDR<br>2) Aggregated summary data in .csv format automatically generated from AMASS3) Data dictionary for microbiology data file of Mahosot Hospital (configured by the hospital to be used with the AMASS application)<br>Please note that the two data dictionary files can be re-used with the data files of the hospital in the future in cases when variables names and values in the raw data remained unchanged.<br>
DOI: 10.6084/m9.figshare.12000222.v2
title: Antimicrobial resistance surveillance report, Mahosot Hospital, Lao PDR, 01 Jul 2019 to 30 Sep 2019

description: Updated on 12<sup>th</sup> January 2021<br> This update fixes inaccurate estimations of the proportion of non-susceptible isolates of <i>E. coli </i>and <i>K. pneumoniae</i> for ampicillin (page 9-10 in the AMR surveillance report) in AMASS 1.0. The updated AMR surveillance report and output files were generated by AMASS 1.1 using the same data sets and data dictionary files. AMASS 1.1 (figshare link https://figshare.com/articles/dataset/AMASS_zip/7763330) fixes a typo in the R code (z_Rcode.R file) of the AMASS 1.0 that caused the inaccurate estimations.<br>AutoMated tool for Antimicrobial resistance Surveillance System (AMASS) was developed as an offline, open-access and easy-to-use application that allows a hospital to perform data analysis independently and generate isolate-based and sample-based surveillance reports stratified by infection origin from routinely collected electronic databases. AMASS performs data analysis and generates reports automatically. The application can be downloaded from https://www.amass.website<br>This is a repository of the files for Mahosot Hospital. The attached three files are:1) The AMR surveillance report automatically generated from AMASS using hospital admission and microbiology data of Mahosot Hospital in Lao PDR<br>2) Aggregated summary data in .csv format automatically generated from AMASS3) Data dictionary for microbiology data file of Mahosot Hospital (configured by the hospital to be used with the AMASS application)<br>Please note that the two data dictionary files can be re-used with the data files of the hospital in the future in cases when variables names and values in the raw data remained unchanged.<br>
DOI: 10.6084/m9.figshare.12000222.v1
title: Antimicrobial resistance surveillance report, Mahosot Hospital, Lao PDR, 01 Jul 2019 to 30 Sep 2019

description: AutoMated tool for Antimicrobial resistance Surveillance System (AMASS) was developed as an offline, open-access and easy-to-use application that allows a hospital to perform data analysis independently and generate isolate-based and sample-based surveillance reports stratified by infection origin from routinely collected electronic databases. AMASS performs data analysis and generates reports automatically. The application can be downloaded from https://www.amass.website<br>This is a repository of the files for Mahosot Hospital. The attached three files are:1) The AMR surveillance report automatically generated from AMASS using hospital admission and microbiology data of Mahosot Hospital in Lao PDR<br>2) Aggregated summary data in .csv format automatically generated from AMASS3) Data dictionary for microbiology data file of Mahosot Hospital (configured by the hospital to be used with the AMASS application)<br>Please note that the two data dictionary files can be re-used with the data files of the hospital in the future in cases when variables names and values in the raw data remained unchanged.<br>
DOI: 10.6084/m9.figshare.12000237
title: Antimicrobial resistance surveillance report, North Okkalapa General and Teaching Hospital, Myanmar, 02 Jan 2019 to 27 Dec 2019

description: Updated on 12<sup>th</sup> January 2021<br> This update fixes inaccurate estimations of the proportion of non-susceptible isolates of <i>E. coli </i>and <i>K. pneumoniae</i> for ampicillin (page 9-10 and page 18-21 in the AMR surveillance report) in AMASS 1.0. The updated AMR surveillance report and output files were generated by AMASS 1.1 using the same data sets and data dictionary files. AMASS 1.1 (figshare link https://figshare.com/articles/dataset/AMASS_zip/7763330) fixes a typo in the R code (z_Rcode.R file) of the AMASS 1.0 that caused the inaccurate estimations.<br>AutoMated tool for Antimicrobial resistance Surveillance System (AMASS) was developed as an offline, open-access and easy-to-use application that allows a hospital to perform data analysis independently and generate isolate-based and sample-based surveillance reports stratified by infection origin from routinely collected electronic databases. AMASS performs data analysis and generates reports automatically. The application can be downloaded from https://www.amass.website.<br>This is a repository of the files for North Okkalapa General and Teaching Hospital. The attached four files are:<br>1) The AMR surveillance report automatically generated from AMASS using hospital admission and microbiology data of North Okkalapa General and Teaching Hospital in Myanmar<br>2) Aggregated summary data in .csv format automatically generated from AMASS<br>3) Data dictionary for microbiology data file of North Okkalapa General and Teaching Hospital (configured by the hospital to be used with the AMASS application)<br>4) Data dictionary for hospital admission data of North Okkalapa General and Teaching Hospital (configured by the hospital to be used with the AMASS application)<br><br>Please note that the two data dictionary files can be re-used with the data files of the hospital in the future in cases when variables names and values in the raw data remained unchanged.
DOI: 10.6084/m9.figshare.12000237.v2
title: Antimicrobial resistance surveillance report, North Okkalapa General and Teaching Hospital, Myanmar, 02 Jan 2019 to 27 Dec 2019

description: Updated on 12<sup>th</sup> January 2021<br> This update fixes inaccurate estimations of the proportion of non-susceptible isolates of <i>E. coli </i>and <i>K. pneumoniae</i> for ampicillin (page 9-10 and page 18-21 in the AMR surveillance report) in AMASS 1.0. The updated AMR surveillance report and output files were generated by AMASS 1.1 using the same data sets and data dictionary files. AMASS 1.1 (figshare link https://figshare.com/articles/dataset/AMASS_zip/7763330) fixes a typo in the R code (z_Rcode.R file) of the AMASS 1.0 that caused the inaccurate estimations.<br>AutoMated tool for Antimicrobial resistance Surveillance System (AMASS) was developed as an offline, open-access and easy-to-use application that allows a hospital to perform data analysis independently and generate isolate-based and sample-based surveillance reports stratified by infection origin from routinely collected electronic databases. AMASS performs data analysis and generates reports automatically. The application can be downloaded from https://www.amass.website.<br>This is a repository of the files for North Okkalapa General and Teaching Hospital. The attached four files are:<br>1) The AMR surveillance report automatically generated from AMASS using hospital admission and microbiology data of North Okkalapa General and Teaching Hospital in Myanmar<br>2) Aggregated summary data in .csv format automatically generated from AMASS<br>3) Data dictionary for microbiology data file of North Okkalapa General and Teaching Hospital (configured by the hospital to be used with the AMASS application)<br>4) Data dictionary for hospital admission data of North Okkalapa General and Teaching Hospital (configured by the hospital to be used with the AMASS application)<br><br>Please note that the two data dictionary files can be re-used with the data files of the hospital in the future in cases when variables names and values in the raw data remained unchanged.
DOI: 10.6084/m9.figshare.12000237.v1
title: Antimicrobial resistance surveillance report, North Okkalapa General and Teaching Hospital, Myanmar, 02 Jan 2019 to 27 Dec 2019

description: AutoMated tool for Antimicrobial resistance Surveillance System (AMASS) was developed as an offline, open-access and easy-to-use application that allows a hospital to perform data analysis independently and generate isolate-based and sample-based surveillance reports stratified by infection origin from routinely collected electronic databases. AMASS performs data analysis and generates reports automatically. The application can be downloaded from https://www.amass.website.<br><br>This is a repository of the files for North Okkalapa General and Teaching Hospital. The attached four files are:<br>1) The AMR surveillance report automatically generated from AMASS using hospital admission and microbiology data of North Okkalapa General and Teaching Hospital in Myanmar<br>2) Aggregated summary data in .csv format automatically generated from AMASS<br>3) Data dictionary for microbiology data file of North Okkalapa General and Teaching Hospital (configured by the hospital to be used with the AMASS application)<br>4) Data dictionary for hospital admission data of North Okkalapa General and Teaching Hospital (configured by the hospital to be used with the AMASS application)<br><br>Please note that the two data dictionary files can be re-used with the data files of the hospital in the future in cases when variables names and values in the raw data remained unchanged.
DOI: 10.6084/m9.figshare.12000252
title: Antimicrobial resistance surveillance report, The Hospital for Tropical Diseases, Vietnam, 01 Jan 2017 to 30 Dec 2017

description: Updated on 12<sup>th</sup> January 2021<br> This update fixes inaccurate estimations of the proportion of non-susceptible isolates of <i>E. coli </i>and <i>K. pneumoniae</i> for ampicillin (page 9-10 in the AMR surveillance report) in AMASS 1.0. The updated AMR surveillance report and output files were generated by AMASS 1.1 using the same data sets and data dictionary files. AMASS 1.1 (figshare link https://figshare.com/articles/dataset/AMASS_zip/7763330) fixes a typo in the R code (z_Rcode.R file) of the AMASS 1.0 that caused the inaccurate estimations.<br>AutoMated tool for Antimicrobial resistance Surveillance System (AMASS) was developed as an offline, open-access and easy-to-use application that allows a hospital to perform data analysis independently and generate isolate-based and sample-based surveillance reports stratified by infection origin from routinely collected electronic databases. AMASS performs data analysis and generates reports automatically. The application can be downloaded from https://www.amass.website<br><br>This is a repository of the files for the Hospital for Tropical Diseases. The attached three files are:<br>1) The AMR surveillance report automatically generated from AMASS using hospital admission and microbiology data of the Hospital for Tropical Diseases in Vietnam<br>2) Aggregated summary data in .csv format automatically generated from AMASS<br>3) Data dictionary for microbiology data file of the Hospital for Tropical Diseases (configured by the hospital to be used with the AMASS application)<br><br>Please note that the two data dictionary files can be re-used with the data files of the hospital in the future in cases when variables names and values in the raw data remained unchanged.
DOI: 10.6084/m9.figshare.12000252.v2
title: Antimicrobial resistance surveillance report, The Hospital for Tropical Diseases, Vietnam, 01 Jan 2017 to 30 Dec 2017

description: Updated on 12<sup>th</sup> January 2021<br> This update fixes inaccurate estimations of the proportion of non-susceptible isolates of <i>E. coli </i>and <i>K. pneumoniae</i> for ampicillin (page 9-10 in the AMR surveillance report) in AMASS 1.0. The updated AMR surveillance report and output files were generated by AMASS 1.1 using the same data sets and data dictionary files. AMASS 1.1 (figshare link https://figshare.com/articles/dataset/AMASS_zip/7763330) fixes a typo in the R code (z_Rcode.R file) of the AMASS 1.0 that caused the inaccurate estimations.<br>AutoMated tool for Antimicrobial resistance Surveillance System (AMASS) was developed as an offline, open-access and easy-to-use application that allows a hospital to perform data analysis independently and generate isolate-based and sample-based surveillance reports stratified by infection origin from routinely collected electronic databases. AMASS performs data analysis and generates reports automatically. The application can be downloaded from https://www.amass.website<br><br>This is a repository of the files for the Hospital for Tropical Diseases. The attached three files are:<br>1) The AMR surveillance report automatically generated from AMASS using hospital admission and microbiology data of the Hospital for Tropical Diseases in Vietnam<br>2) Aggregated summary data in .csv format automatically generated from AMASS<br>3) Data dictionary for microbiology data file of the Hospital for Tropical Diseases (configured by the hospital to be used with the AMASS application)<br><br>Please note that the two data dictionary files can be re-used with the data files of the hospital in the future in cases when variables names and values in the raw data remained unchanged.
DOI: 10.6084/m9.figshare.12000252.v1
title: Antimicrobial resistance surveillance report, The Hospital for Tropical Diseases, Vietnam, 01 Jan 2017 to 30 Dec 2017

description: AutoMated tool for Antimicrobial resistance Surveillance System (AMASS) was developed as an offline, open-access and easy-to-use application that allows a hospital to perform data analysis independently and generate isolate-based and sample-based surveillance reports stratified by infection origin from routinely collected electronic databases. AMASS performs data analysis and generates reports automatically. The application can be downloaded from https://www.amass.website<br><br>This is a repository of the files for the Hospital for Tropical Diseases. The attached three files are:<br>1) The AMR surveillance report automatically generated from AMASS using hospital admission and microbiology data of the Hospital for Tropical Diseases in Vietnam<br>2) Aggregated summary data in .csv format automatically generated from AMASS<br>3) Data dictionary for microbiology data file of the Hospital for Tropical Diseases (configured by the hospital to be used with the AMASS application)<br><br>Please note that the two data dictionary files can be re-used with the data files of the hospital in the future in cases when variables names and values in the raw data remained unchanged.
DOI: 10.6084/m9.figshare.13573988
title: Table S1 from Poorly differentiated XX/XY sex chromosomes are widely shared across skink radiation

description: List of reptiles used in the current study.
DOI: 10.6084/m9.figshare.13573988.v1
title: Table S1 from Poorly differentiated XX/XY sex chromosomes are widely shared across skink radiation

description: List of reptiles used in the current study.
DOI: 10.6084/m9.figshare.13573991.v1
title: Table S3 from Poorly differentiated XX/XY sex chromosomes are widely shared across skink radiation

description: List of primers and qPCR measurements of relative gene dosage in 13 species of skinks and their close outgroups.
DOI: 10.6084/m9.figshare.13573994
title: Table S2 from Poorly differentiated XX/XY sex chromosomes are widely shared across skink radiation

description: Male to female ratios for DNA-seq read coverage in S. scincus. Homology of these genes to the genomes of the chicken Gallus gallus and the common wall lizard Podarcis muralis is given.
DOI: 10.6084/m9.figshare.13573994.v1
title: Table S2 from Poorly differentiated XX/XY sex chromosomes are widely shared across skink radiation

description: Male to female ratios for DNA-seq read coverage in S. scincus. Homology of these genes to the genomes of the chicken Gallus gallus and the common wall lizard Podarcis muralis is given.
DOI: 10.6084/m9.figshare.13573991
title: Table S3 from Poorly differentiated XX/XY sex chromosomes are widely shared across skink radiation

description: List of primers and qPCR measurements of relative gene dosage in 13 species of skinks and their close outgroups.
DOI: 10.15468/yf9fea
title: Revision of the genus Tephrochlaena, with a key to genera of Palaearctic Heteromyzinae (Diptera: Heleomyzidae)

description: This dataset contains the digitized treatments in Plazi based on the original journal article Giudice, Giuseppe Lo, Woźnica, Andrzej Józef (2020): Revision of the genus Tephrochlaena, with a key to genera of Palaearctic Heteromyzinae (Diptera: Heleomyzidae). Zootaxa 4820 (1): 165-176, DOI: https://doi.org/10.11646/zootaxa.4820.1.8
DOI: 10.25919/p45t-xz32
title: Parkes observations for project P971 semester 2020OCTS_01

description: We propose timing observations of the relativistic pulsar - white-dwarf binary, PSR J1141$-$6545. This unique system offers access to a wide range of physics, from relativistic phenomena through pulsar emission cone studies, to the structure and distribution of interstellar plasma along our line-of-sight. The Parkes Ultra Wide Band Low Frequency (UWL) receiver has opened up the possibility of performing the first-ever studies of its orbital dynamics at high temporal resolution. Our analysis of data obtained to date suggests that the pulsar will precess away from our line-of-sight before 2023. Hence, regular observations are crucial to maximize science outcomes with this source.
DOI: 10.6084/m9.figshare.13574059.v1
title: Data from The effect of optic flow cues on honeybee flight control in wind

description: All of the summary data used in the presented analyses
DOI: 10.6084/m9.figshare.13574059
title: Data from The effect of optic flow cues on honeybee flight control in wind

description: All of the summary data used in the presented analyses
DOI: 10.15468/j8s5wj
title: DNA barcodes, morphology and geographic distribution confirm a new butterfly species in the genus Rhamma (Lepidoptera: Lycaenidae)

description: This dataset contains the digitized treatments in Plazi based on the original journal article Prieto, Carlos, Hincapie, Carlos Federico Álvarez, Giraldo, Alejandra Clavijo, Uribe, Sandra (2020): DNA barcodes, morphology and geographic distribution confirm a new butterfly species in the genus Rhamma (Lepidoptera: Lycaenidae). Zootaxa 4821 (1): 181-188, DOI: https://doi.org/10.11646/zootaxa.4821.1.11
DOI: 10.6084/m9.figshare.12962435
title: Waldner_etal-2020-SupplementaryMaterials.pdf

description: This supporting information provides: detailed table of thermochronological dataset (including detailed modeled data) from central Axial Zone, radial plots from AFT data, extended version of QTQt model (Fig. 16) including the whole constraint boxes, and time-temperature plot of un-modelled plutons.
DOI: 10.6084/m9.figshare.12962435.v1
title: Waldner_etal-2020-SupplementaryMaterials.pdf

description: This supporting information provides: detailed table of thermochronological dataset (including detailed modeled data) from central Axial Zone, radial plots from AFT data, extended version of QTQt model (Fig. 16) including the whole constraint boxes, and time-temperature plot of un-modelled plutons.
DOI: 10.5281/zenodo.4438799
title: MIC values from MBL-producing Enterobacterales collection

description: Raw minimum inhibitory concentration values (in µg/mL) obtained for the MBL-producing Enterobacterales collection following the agar dilution standard procedure.
DOI: 10.5281/zenodo.4438798
title: MIC values from MBL-producing Enterobacterales collection

description: Raw minimum inhibitory concentration values (in µg/mL) obtained for the MBL-producing Enterobacterales collection following the agar dilution standard procedure.
DOI: 10.6084/m9.figshare.13570763.v2
title: PLoS One dataset

description: Dataset from figures published in PLoS One<br>
DOI: 10.5255/ukda-sn-854242
title: Integrated construction and environmental management systems in informal settlements in South Africa 2016-2020

description: This data covers Phases 1, 3 and 4 of the ISULabaNtu project. The project collected interview, focus group and survey data as well as photographs and participatory workshops. This collection represents a complete data compilation from across the project's duration and its different phases during which data was collected. Data from Phase 2 is available from a separate collection, see Related resources.