cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5517/ccdc.csd.cc25c66z
title: CCDC 2006760: Experimental Crystal Structure Determination

description: Related Article: Pedro D. García-Fernández, Javier Iglesias-Sigüenza, Paula S. Rivero-Jerez, Elena Díez, Enrique Gómez-Bengoa, Rosario Fernández, José M. Lassaletta|2020|J.Am.Chem.Soc.|142|16082|doi:10.1021/jacs.0c07951
DOI: 10.21227/1swk-1d87
title: Shoulder Physiotherapy Activity Recognition 9-Axis Dataset

description: This dataset contains inertial data consisting of 1) physiotherapy exercise recordings, and 2) unlabeled other activity data recordings, each collected by smart watches worn by healthy subjects. This dataset may be used to perform supervised classification analysis of physiotherapy exercises, or to perform out-of-distribution detection analysis with the unlabeled other activity data.It consists of 9-axis inertial sensor data (accelerometer, gyroscope, and magnetometer) collected using a Huawei Watch 2 from 20 healthy subjects (40 shoulders), as they perform 10 shoulder physiotherapy exercises. This dataset also includes ~3 hours of unlabeled other activity data for each patient that can be used to simulate out-of-distribution data (label 11).Dataset is labeled as follows:0: None1: External Rotation (Isometric)2: Scapula Retraction at 90 Degrees Flexion3: Internal Rotation (Isometric)4: Extension (Isometric)5: Abduction (Isometric)6: External Rotation at 0 Degrees Flexion7: Cross Chest Adduction8: Active Flexion9: Shoulder Girdle Stabilization with Elevation10: Triceps Pull Downs11: OODThe subjects repeat each activity 20 times on each side (left and right). Isometric exercises are low-motion stability exercises.
DOI: 10.21227/yktv-ma60
title: Shoulder Physiotherapy Activity Recognition 9-Axis Dataset

description: This dataset contains inertial data consisting of 1) physiotherapy exercise recordings, and 2) unlabeled other activity data recordings, each collected by smart watches worn by healthy subjects. This dataset may be used to perform supervised classification analysis of physiotherapy exercises, or to perform out-of-distribution detection analysis with the unlabeled other activity data.It consists of 9-axis inertial sensor data (accelerometer, gyroscope, and magnetometer) collected using a Huawei Watch 2 from 20 healthy subjects (40 shoulders), as they perform 10 shoulder physiotherapy exercises. This dataset also includes ~3 hours of unlabeled other activity data for each patient that can be used to simulate out-of-distribution data (label 11).Dataset is labeled as follows:0: None1: External Rotation (Isometric)2: Scapula Retraction at 90 Degrees Flexion3: Internal Rotation (Isometric)4: Extension (Isometric)5: Abduction (Isometric)6: External Rotation at 0 Degrees Flexion7: Cross Chest Adduction8: Active Flexion9: Shoulder Girdle Stabilization with Elevation10: Triceps Pull Downs11: OODThe subjects repeat each activity 20 times on each side (left and right). Isometric exercises are low-motion stability exercises.
DOI: 10.5281/zenodo.4040042
title: Dr.

description: The files contain pedigree, phenotypes and genomic data for two populations: Pinus radiata (Pinus) and Eucalyptus nitens (Eucalyptus). Phenotypic data files contain individual identifiers called "ID" which connects phenotypes with pedigree and genomic markers, design effects and phenotypic data. Eucalyptus_Sib-ship_based_relationship_matrix.csv file contains relatinship matrix derived from sib-ship reconstruction performed in previous study (Klapste et al. 2017) using COLONY package. It contains row and column names associating elements in the relationship matrix to individual identifier "ID". Genomic data files contain genotypes coded as -1, 0 and 1 representing reference allele homozygote, heterozygote and alternative allele homozygote. <br>
description: {"references": ["Klapste et al (2020) Datasets related to DOI: 10.3389/fgene.2020.499094"]}
DOI: 10.5281/zenodo.4040041
title: Dr.

description: The files contain pedigree, phenotypes and genomic data for two populations: Pinus radiata (Pinus) and Eucalyptus nitens (Eucalyptus). Phenotypic data files contain individual identifiers called "ID" which connects phenotypes with pedigree and genomic markers, design effects and phenotypic data. Eucalyptus_Sib-ship_based_relationship_matrix.csv file contains relatinship matrix derived from sib-ship reconstruction performed in previous study (Klapste et al. 2017) using COLONY package. It contains row and column names associating elements in the relationship matrix to individual identifier "ID". Genomic data files contain genotypes coded as -1, 0 and 1 representing reference allele homozygote, heterozygote and alternative allele homozygote. <br>
description: {"references": ["Klapste et al (2020) Datasets related to DOI: 10.3389/fgene.2020.499094"]}
DOI: 10.6084/m9.figshare.12472646.v4
title: Dust, SST, and Productivity Data for ODP 1208A and ODP 885/886 (Abell et al., 2020 - Nature)

description: These Excel files contain all of the elemental, isotopic, export productivity, and SST data for ODP sites 1208 and 885/886 associated with Abell et al., "Poleward and weakened westerlies during Pliocene warmth".<br>Please cite: Abell et al., 2020. Poleward and weakened westerlies during Pliocene warmth. <i>Nature.</i>
DOI: 10.6084/m9.figshare.13087235
title: Open Data Visualized from Police Spreadsheets: A Case Study of Where Force, Race and Space Collided Item

description: <b>Assets:</b>data tables each for city of Indianapolis (IN) and Baltimore (MD) in MS Excel and MS Word, ditto shapefiles in ESRI format; all files ZIPPED<br><b>Context</b> – abstract of report published in a blog at the serial <i>Geospatial World:</i>This case study called into question police conduct and policy injustice discovered in two American big cities. My path to learn about Indianapolis (IN) and Baltimore (MD) policing patterns and crime events was due to availability of open data focused on use-of-force (UOF). My specific goal was to conduct geospatial data analytics aimed at these two cities using location and other key variables. Two spreadsheets captured small data that laid acceptable statistical groundwork for iterations of exploratory spatial data analysis (ESDA). Bivariate scatterplots revealed possible police misconduct. Parallel coordinate plotting – an innovative multivariate tool – was then used to display co-occurrences of plotted UOF and racial variables associated with key police districts in Indianapolis and Baltimore. A final summary visualization sought to cartographically and dramatically compare force and race variables by way of comparative plots, graphs, and maps. I closed with three action items pertaining to a “social-justice” framework for future data-visualization, to the heightening of standards for law enforcement reform, and for a need to make a hypothetical “citizen’s arrest” of police misconduct.
DOI: 10.6084/m9.figshare.13087235.v2
title: Open Data Visualized from Police Spreadsheets: A Case Study of Where Force, Race and Space Collided Item

description: <b>Assets:</b>data tables each for city of Indianapolis (IN) and Baltimore (MD) in MS Excel and MS Word, ditto shapefiles in ESRI format; all files ZIPPED<br><b>Context</b> – abstract of report published in a blog at the serial <i>Geospatial World:</i>This case study called into question police conduct and policy injustice discovered in two American big cities. My path to learn about Indianapolis (IN) and Baltimore (MD) policing patterns and crime events was due to availability of open data focused on use-of-force (UOF). My specific goal was to conduct geospatial data analytics aimed at these two cities using location and other key variables. Two spreadsheets captured small data that laid acceptable statistical groundwork for iterations of exploratory spatial data analysis (ESDA). Bivariate scatterplots revealed possible police misconduct. Parallel coordinate plotting – an innovative multivariate tool – was then used to display co-occurrences of plotted UOF and racial variables associated with key police districts in Indianapolis and Baltimore. A final summary visualization sought to cartographically and dramatically compare force and race variables by way of comparative plots, graphs, and maps. I closed with three action items pertaining to a “social-justice” framework for future data-visualization, to the heightening of standards for law enforcement reform, and for a need to make a hypothetical “citizen’s arrest” of police misconduct.
DOI: 10.6084/m9.figshare.13087235.v1
title: Open Data Visualized from Police Spreadsheets: A Case Study of Where Force, Race and Space Collided Item

description: Assets:tables in MS Excel and MS Word, shapefiles in ESRI format; all files ZIPPED<br>Context: This case study called into question police conduct and policy injustice discovered in two American big cities. My path to learn about Indianapolis (IN) and Baltimore (MD) policing patterns and crime events was due to availability of open data focused on use-of-force (UOF). My specific goal was to conduct geospatial data analytics aimed at these two cities using location and other key variables. Two spreadsheets captured small data that laid acceptable statistical groundwork for iterations of exploratory spatial data analysis (ESDA). Bivariate scatterplots revealed possible police misconduct. Parallel coordinate plotting – an innovative multivariate tool – was then used to display co-occurrences of plotted UOF and racial variables associated with key police districts in Indianapolis and Baltimore. A final summary visualization sought to cartographically and dramatically compare force and race variables by way of comparative plots, graphs, and maps. I closed with three action items pertaining to a “social-justice” framework for future data-visualization, to the heightening of standards for law enforcement reform, and for a need to make a hypothetical “citizen’s arrest” of police misconduct.
DOI: 10.5517/ccdc.csd.cc25h652
title: CCDC 2010603: Experimental Crystal Structure Determination

description: Related Article: Qiang Wang, Wen-Wen Zhang, Hao Song, Jian Wang, Chao Zheng, Qing Gu, Shu-Li You|2020|J.Am.Chem.Soc.|142|15678|doi:10.1021/jacs.0c08205
DOI: 10.5517/ccdc.csd.cc25jllx
title: CCDC 2011949: Experimental Crystal Structure Determination

description: Related Article: Suse S. Bebiano, Joop H. ter Horst, Iain D.H. Oswald|2020|Cryst.Growth Des.|20|6731|doi:10.1021/acs.cgd.0c00871
DOI: 10.5517/ccdc.csd.cc25jlmy
title: CCDC 2011950: Experimental Crystal Structure Determination

description: Related Article: Suse S. Bebiano, Joop H. ter Horst, Iain D.H. Oswald|2020|Cryst.Growth Des.|20|6731|doi:10.1021/acs.cgd.0c00871
DOI: 10.5517/ccdc.csd.cc25jlnz
title: CCDC 2011951: Experimental Crystal Structure Determination

description: Related Article: Suse S. Bebiano, Joop H. ter Horst, Iain D.H. Oswald|2020|Cryst.Growth Des.|20|6731|doi:10.1021/acs.cgd.0c00871
DOI: 10.5517/ccdc.csd.cc25jlq1
title: CCDC 2011953: Experimental Crystal Structure Determination

description: Related Article: Suse S. Bebiano, Joop H. ter Horst, Iain D.H. Oswald|2020|Cryst.Growth Des.|20|6731|doi:10.1021/acs.cgd.0c00871
DOI: 10.5517/ccdc.csd.cc25jlr2
title: CCDC 2011954: Experimental Crystal Structure Determination

description: Related Article: Suse S. Bebiano, Joop H. ter Horst, Iain D.H. Oswald|2020|Cryst.Growth Des.|20|6731|doi:10.1021/acs.cgd.0c00871
DOI: 10.5517/ccdc.csd.cc25jls3
title: CCDC 2011955: Experimental Crystal Structure Determination

description: Related Article: Suse S. Bebiano, Joop H. ter Horst, Iain D.H. Oswald|2020|Cryst.Growth Des.|20|6731|doi:10.1021/acs.cgd.0c00871
DOI: 10.5517/ccdc.csd.cc25jlt4
title: CCDC 2011956: Experimental Crystal Structure Determination

description: Related Article: Suse S. Bebiano, Joop H. ter Horst, Iain D.H. Oswald|2020|Cryst.Growth Des.|20|6731|doi:10.1021/acs.cgd.0c00871
DOI: 10.5517/ccdc.csd.cc25jlv5
title: CCDC 2011957: Experimental Crystal Structure Determination

description: Related Article: Suse S. Bebiano, Joop H. ter Horst, Iain D.H. Oswald|2020|Cryst.Growth Des.|20|6731|doi:10.1021/acs.cgd.0c00871
DOI: 10.5517/ccdc.csd.cc25jlw6
title: CCDC 2011958: Experimental Crystal Structure Determination

description: Related Article: Suse S. Bebiano, Joop H. ter Horst, Iain D.H. Oswald|2020|Cryst.Growth Des.|20|6731|doi:10.1021/acs.cgd.0c00871
DOI: 10.5517/ccdc.csd.cc25jlx7
title: CCDC 2011959: Experimental Crystal Structure Determination

description: Related Article: Suse S. Bebiano, Joop H. ter Horst, Iain D.H. Oswald|2020|Cryst.Growth Des.|20|6731|doi:10.1021/acs.cgd.0c00871
DOI: 10.5517/ccdc.csd.cc25jly8
title: CCDC 2011960: Experimental Crystal Structure Determination

description: Related Article: Suse S. Bebiano, Joop H. ter Horst, Iain D.H. Oswald|2020|Cryst.Growth Des.|20|6731|doi:10.1021/acs.cgd.0c00871
DOI: 10.5517/ccdc.csd.cc25jlz9
title: CCDC 2011961: Experimental Crystal Structure Determination

description: Related Article: Suse S. Bebiano, Joop H. ter Horst, Iain D.H. Oswald|2020|Cryst.Growth Des.|20|6731|doi:10.1021/acs.cgd.0c00871
DOI: 10.5517/ccdc.csd.cc25jm0c
title: CCDC 2011962: Experimental Crystal Structure Determination

description: Related Article: Suse S. Bebiano, Joop H. ter Horst, Iain D.H. Oswald|2020|Cryst.Growth Des.|20|6731|doi:10.1021/acs.cgd.0c00871
DOI: 10.5517/ccdc.csd.cc25jm1d
title: CCDC 2011963: Experimental Crystal Structure Determination

description: Related Article: Suse S. Bebiano, Joop H. ter Horst, Iain D.H. Oswald|2020|Cryst.Growth Des.|20|6731|doi:10.1021/acs.cgd.0c00871
DOI: 10.5517/ccdc.csd.cc25jm2f
title: CCDC 2011964: Experimental Crystal Structure Determination

description: Related Article: Suse S. Bebiano, Joop H. ter Horst, Iain D.H. Oswald|2020|Cryst.Growth Des.|20|6731|doi:10.1021/acs.cgd.0c00871
DOI: 10.5517/ccdc.csd.cc25jm3g
title: CCDC 2011965: Experimental Crystal Structure Determination

description: Related Article: Suse S. Bebiano, Joop H. ter Horst, Iain D.H. Oswald|2020|Cryst.Growth Des.|20|6731|doi:10.1021/acs.cgd.0c00871
DOI: 10.5517/ccdc.csd.cc25jm4h
title: CCDC 2011966: Experimental Crystal Structure Determination

description: Related Article: Suse S. Bebiano, Joop H. ter Horst, Iain D.H. Oswald|2020|Cryst.Growth Des.|20|6731|doi:10.1021/acs.cgd.0c00871
DOI: 10.5517/ccdc.csd.cc25jm6k
title: CCDC 2011968: Experimental Crystal Structure Determination

description: Related Article: Suse S. Bebiano, Joop H. ter Horst, Iain D.H. Oswald|2020|Cryst.Growth Des.|20|6731|doi:10.1021/acs.cgd.0c00871
DOI: 10.5517/ccdc.csd.cc25jm7l
title: CCDC 2011969: Experimental Crystal Structure Determination

description: Related Article: Suse S. Bebiano, Joop H. ter Horst, Iain D.H. Oswald|2020|Cryst.Growth Des.|20|6731|doi:10.1021/acs.cgd.0c00871
DOI: 10.5517/ccdc.csd.cc25jm8m
title: CCDC 2011970: Experimental Crystal Structure Determination

description: Related Article: Suse S. Bebiano, Joop H. ter Horst, Iain D.H. Oswald|2020|Cryst.Growth Des.|20|6731|doi:10.1021/acs.cgd.0c00871
DOI: 10.5517/ccdc.csd.cc25jlp0
title: CCDC 2011952: Experimental Crystal Structure Determination

description: Related Article: Suse S. Bebiano, Joop H. ter Horst, Iain D.H. Oswald|2020|Cryst.Growth Des.|20|6731|doi:10.1021/acs.cgd.0c00871
DOI: 10.5517/ccdc.csd.cc25l576
title: CCDC 2013457: Experimental Crystal Structure Determination

description: Related Article: Johannes Kretsch, Anne Kreyenschmidt, Timo Schillmöller, Regine Herbst-Irmer, Dietmar Stalke|2020|Inorg.Chem.|59|13690|doi:10.1021/acs.inorgchem.0c02066
DOI: 10.5517/ccdc.csd.cc25l587
title: CCDC 2013458: Experimental Crystal Structure Determination

description: Related Article: Johannes Kretsch, Anne Kreyenschmidt, Timo Schillmöller, Regine Herbst-Irmer, Dietmar Stalke|2020|Inorg.Chem.|59|13690|doi:10.1021/acs.inorgchem.0c02066
DOI: 10.5517/ccdc.csd.cc25l598
title: CCDC 2013459: Experimental Crystal Structure Determination

description: Related Article: Johannes Kretsch, Anne Kreyenschmidt, Timo Schillmöller, Regine Herbst-Irmer, Dietmar Stalke|2020|Inorg.Chem.|59|13690|doi:10.1021/acs.inorgchem.0c02066
DOI: 10.5517/ccdc.csd.cc25l5b9
title: CCDC 2013460: Experimental Crystal Structure Determination

description: Related Article: Johannes Kretsch, Anne Kreyenschmidt, Timo Schillmöller, Regine Herbst-Irmer, Dietmar Stalke|2020|Inorg.Chem.|59|13690|doi:10.1021/acs.inorgchem.0c02066
DOI: 10.5517/ccdc.csd.cc25l5cb
title: CCDC 2013461: Experimental Crystal Structure Determination

description: Related Article: Johannes Kretsch, Anne Kreyenschmidt, Timo Schillmöller, Regine Herbst-Irmer, Dietmar Stalke|2020|Inorg.Chem.|59|13690|doi:10.1021/acs.inorgchem.0c02066
DOI: 10.5517/ccdc.csd.cc25l5dc
title: CCDC 2013462: Experimental Crystal Structure Determination

description: Related Article: Johannes Kretsch, Anne Kreyenschmidt, Timo Schillmöller, Regine Herbst-Irmer, Dietmar Stalke|2020|Inorg.Chem.|59|13690|doi:10.1021/acs.inorgchem.0c02066
DOI: 10.5517/ccdc.csd.cc25l5fd
title: CCDC 2013463: Experimental Crystal Structure Determination

description: Related Article: Johannes Kretsch, Anne Kreyenschmidt, Timo Schillmöller, Regine Herbst-Irmer, Dietmar Stalke|2020|Inorg.Chem.|59|13690|doi:10.1021/acs.inorgchem.0c02066
DOI: 10.7931/ndkt-zw49
title: Distributional patterns of native and exotic plant species richness across islands in New Zealand
DOI: 10.25345/c5r193
title: MassIVE MSV000086277 - MDCK cell line adaptation to suspension growth
title: Dataset submission for journal publication: Label-free quantification was performed using the software Progenesis LC-MS 3.0 (Nonlinear Dynamics, Germany). LC-MS runs were aligned to an automatically selected reference run. After peak picking, a list of the features was exported and analyzed using SearchGUI (Vaudel et al. 2011). Therefore, the list was divided 15 times and analyzed using the OMSSA and X!tandem search algorithm through the Uniprot/Trembel database (2013/07) of Canis familiaris entries. Established search parameters: tryptic digest with a maximum of one missed cleavage; fixed modification: carbamidomethylation of cysteine, variable modification: oxidation of methionine; peptide charge 2plus to 4plus; monoisotopic peptide masses; peptide tolerance of 0.3 Da; MS/MS tolerance of 0.5 Da. Data were imported into Peptide-Shaker (Version 0.22.5) and corrected with a false discovery rate of 0.05 (Barsnes et al. 2011; Vaudel et al. 2011). Afterwards, result files were imported to Progenesis and protein lists with calculated protein quantities were exported to Excel. For statistical analysis of the data a Students t-Test with a p-value less then 0.05 was performed with R (Team 2008).
DOI: 10.5281/zenodo.4047874
title: Unilateral Retinoblastoma; natural history and an age-based protocol in 248 patients - A Supplementary

description: An analysis of Unilateral Retinoblastoma Patients from the Registry of Children's Cancer Hospital Egypt between 2007 and 2015.
DOI: 10.5281/zenodo.4047763
title: Unilateral Retinoblastoma; natural history and an age-based protocol in 248 patients - A Supplementary

description: An analysis of Unilateral Retinoblastoma Patients from the Registry of Children's Cancer Hospital Egypt between 2007 and 2015.
DOI: 10.6084/m9.figshare.13087361.v1
title: Pelikan et al., 2020 - Protein and lipid degraders in marine sediments - Supplementary Tables

description: Excel files of Supplementary Tables
DOI: 10.6084/m9.figshare.13087361
title: Pelikan et al., 2020 - Protein and lipid degraders in marine sediments - Supplementary Tables

description: Excel files of Supplementary Tables
DOI: 10.5281/zenodo.4086046
title: Datasets to "Turbulent radiative diffusion and turbulent Newtonian cooling"

description: <pre>This directory contains an index.html file with links to the run directories for Figs.1, 2-6 and idl plotting routines with secondary data for the other figures for the paper "Turbulent radiative diffusion and turbulent Newtonian cooling".</pre>
DOI: 10.5281/zenodo.4085410
title: Datasets to "Turbulent radiative diffusion and turbulent Newtonian cooling"

description: <pre>This directory contains an index.html file with links to the run directories for Figs.1, 2-6 and idl plotting routines with secondary data for the other figures for the paper "Turbulent radiative diffusion and turbulent Newtonian cooling".</pre>
DOI: 10.5517/ccdc.csd.cc25mhmy
title: CCDC 2014740: Experimental Crystal Structure Determination

description: Related Article: Maxwell J. Moore, Shiwei Qu, Ceheng Tan, Yu Cai, Yuzo Mogi, D. Jamin Keith, Dale L. Boger|2020|J.Am.Chem.Soc.|142|16039|doi:10.1021/jacs.0c07433
DOI: 10.5517/ccdc.csd.cc25mv7x
title: CCDC 2015069: Experimental Crystal Structure Determination

description: Related Article: Shan-Shan Zhu, Jiang-Nan Zhou, Quan-Long Wu, Wen-Juan Hao, Shu-Jiang Tu, Bo Jiang|2020|Org.Chem.Front.|7|2975|doi:10.1039/D0QO00917B
DOI: 10.5517/ccdc.csd.cc25lywm
title: CCDC 2014221: Experimental Crystal Structure Determination

description: Related Article: Naoya Kanbayashi, Marina Saegusa, Yuki Ishido, Taka-aki Okamura, Kiyotaka Onitsuka|2020|Polym.Chem.|11|6241|doi:10.1039/D0PY01073A
DOI: 10.5517/ccdc.csd.cc25n5df
title: CCDC 2015384: Experimental Crystal Structure Determination

description: Related Article: Irene Lim, Antoine Vian, Heidi L. van de Wouw, Rachael A. Day, Carlos Gomez, Yucen Liu, Arnold L. Rheingold, Otger Campàs, Ellen M. Sletten|2020|J.Am.Chem.Soc.|142|16072|doi:10.1021/jacs.0c07761
DOI: 10.5517/ccdc.csd.cc25q9bk
title: CCDC 2017428: Experimental Crystal Structure Determination

description: Related Article: Rui-Ying Wang, Ai-Ping Huang, Wen-Bo Wang, Hong-Zhi Sun, Bao-Shan Teng, Yuan-Jun Ma, Ben-Lai Wu|2020|J.Solid State Chem.|292|121702|doi:10.1016/j.jssc.2020.121702
DOI: 10.5517/ccdc.csd.cc25q9cl
title: CCDC 2017429: Experimental Crystal Structure Determination

description: Related Article: Rui-Ying Wang, Ai-Ping Huang, Wen-Bo Wang, Hong-Zhi Sun, Bao-Shan Teng, Yuan-Jun Ma, Ben-Lai Wu|2020|J.Solid State Chem.|292|121702|doi:10.1016/j.jssc.2020.121702
DOI: 10.5281/zenodo.4075487
title: OSIRIS NO2 v6.0.3

description: A nitrogen dioxide (NO2) profile dataset based on spectrograph data from the Canadian OSIRIS instrument on-board the Swedish Odin satellite. The algorithm relies on spectral fitting to obtain slant column densities of NO<sub>2</sub>, followed by inversion using an algebraic reconstruction technique and the SASKTRAN spherical radiative transfer model (RTM) to obtain vertical profiles of local number density.
description: Global Coverage
DOI: 10.25919/5f8616549bd03
title: Parkes observations for project P1064 semester 2020APRS_04

description: The propagation of pulsar signal through the interstellar medium is affected by the fluctuations in the electron density in the line of sight from the pulsar to the observer. This is a frequency dependent phenomenon and will produce brightness variations (scintillation) and also broadening of the otherwise narrow pulse (scatter-broadening). The effect of these two are measurable at different frequencies due to their strong dependence on frequency, viz., broadening will be evident at lower radio frequencies and scintillation will be clearly resolved at higher frequencies. With this proposal, we aim to study the evolution of scatter-broadening and scintillation properties of 137 pulsars with the UWL receiver, and verify their relationship with each other. With this experiment, we aim at testing some of the fundamental theories of ionised interstellar medium. This large sample will also help in improving the understanding of the turbulence characteristics in the inner Galaxy. We request a total of 149 hours for this project.
DOI: 10.6084/m9.figshare.13084145
title: R0190_20170824a_videos

description: Rat 0190, skilled reaching data collected in Leventhal laboratory by Alexandra Bova
DOI: 10.6084/m9.figshare.13084145.v1
title: R0190_20170824a_videos

description: Rat 0190, skilled reaching data collected in Leventhal laboratory by Alexandra Bova
DOI: 10.6084/m9.figshare.13084988
title: R0190_20170826a_videos

description: Rat 0190, skilled reaching data collected in Leventhal laboratory by Alexandra Bova
DOI: 10.6084/m9.figshare.13084988.v1
title: R0190_20170826a_videos

description: Rat 0190, skilled reaching data collected in Leventhal laboratory by Alexandra Bova