cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.4745057
title: Ke'erjian petroglyph panel (Turpan, Xinjiang province, China) - 3D documentation - final products

description: Debating the rock art panel of Ke’erjian (Xinjiang province, China): An early representation of an agropastoral landscape or the world’s oldest interregional map? - FINAL PRODUCTS Humans develop a spatial understanding of the region they dwell. Anthropology and psychology teach us that illiterate groups across encode this ‘spatial cognition’ into maps. However, prehistoric examples of maps remain hotly debated, largely because of the few examples of interregional maps known to date. Consequently, the history of cartography continues to be traced back to antiquity. This paper argues that mapmaking goes back to prehistory (i.e. late Bronze to early Iron Age) and that illiterate groups already developed a complex spatial cognition. Central in this paper stands the Ke’erjian map. This map was discovered when a heavily weathered rock art panel was redocumented with 3D techniques. Located in the eastern Tian Shan and dated to the first half of the first millennium BCE, this rock art map presents itself as a prehistoric map that is based on a detailed topological understanding of the physical landscape. Two interpretations are discussed. First, the panel is explored as an idealized landscape depiction indicating an intricate knowledge of the local environment. Second, based on detailed topographic and geomorphographic comparison the panel is positioned as a plan map of the Tian Shan. Strong correlations indicate that societies along the prehistoric Silk Road developed a spatial cognition extending 1,3 million sq. kilometres.
description: This research was jointly funded by the Strategic Priority Research Program of the Chinese Academy of Sciences (Grant No. XDA20060303) and by the Chinese Academy of Sciences President's International Fellowship Initiative (PIFI) (Grant No. 20188048, 2017VCA0002, 2020VCA001). Special thanks are also for Birger Stichelbaut (UGent), Timothy Nuttens (UGent) and Cornelis Stal (UGent) for their assistance in the fieldwork and the processing. Gino Caspari (University of Sydney) and Morgan De Dapper (UGent) are thanked their advice and discussion. The feedback of Esther Jacobson-Tepfer (University of Oregon) and Nikita Konstantinov (Gorno-Altaisk State University) was greatly appreciated and enabled us to finetune the chronology of the panel and strengthen our interpretation.
DOI: 10.5281/zenodo.4748912
title: All Life journal submission no:219434899_Manuscript Raw Data

description: File includes the raw data of manuscript entitled "<strong>Development of Imidazolone Based Angiotensin II Receptor Type I Inhibitor Small Molecule As A Chemotherapeutic Agent For Cell Cycle Inhibition</strong>".
DOI: 10.5281/zenodo.4748911
title: All Life journal submission no:219434899_Manuscript Raw Data

description: File includes the raw data of manuscript entitled "<strong>Development of Imidazolone Based Angiotensin II Receptor Type I Inhibitor Small Molecule As A Chemotherapeutic Agent For Cell Cycle Inhibition</strong>".
DOI: 10.5281/zenodo.4748846
title: Zanna intricata SPAdes preassembly

description: .
DOI: 10.5281/zenodo.4748845
title: Zanna intricata SPAdes preassembly

description: .
DOI: 10.6084/m9.figshare.14151854
title: RAIG COVID19 compiled dataset.zip

description: Chest X-ray images were selected from a database of chest X-ray images for COVID-19 positive cases along with normal and viral pneumonia images which were collated by researchers from Qatar University and the University of Dhaka along with collaborators from Pakistan and Malaysia and some medical doctors. In their current release, there are 219 COVID-19 positive images, 1341 normal images and 1345 viral pneumonia images (Chowdhury et al., 2020). To ensure multiple representations, the dataset of chest X-ray images for both COVID-19 and normal cases were also selected from Mendeley dataset repository (El-Shafai, 2020) which contains 5500 Non-COVID X-ray images and 4044 COVID-19 X-ray images. This study, therefore, adopted these multi source datasets. Due to limited computing resources, in this study, 1,300 images were selected from each category. That is, 1,300 images of COVID-19 positive cases, 1,300 Normal images and 1,300 images of viral pneumonia cases, totaling 3,900 images in all. It is noted here that further descriptions of the datasets were not provided by the authors of the sources of the datasets.<br>El-Shafai, Walid; Abd El-Samie, Fathi (2020), “Extensive COVID-19 X-Ray and CT Chest Images Dataset”, Mendeley Data, V3, doi: 10.17632/8h65ywd2jr.3<br>Chowdhury, M. E., Rahman, T., Khandakar, A., Mazhar, R., Kadir, M. A., Mahbub, Z. B., . . . Reaz, M. B. (2020, March 29). Can AI help in screening Viral and COVID-19 pneumonia? Retrieved from https://arxiv.org/abs/2003.13145; https://www.kaggle.com/tawsifurrahman/covid19-radiography-database
DOI: 10.6084/m9.figshare.14151854.v3
title: RAIG COVID19 compiled dataset.zip

description: Chest X-ray images were selected from a database of chest X-ray images for COVID-19 positive cases along with normal and viral pneumonia images which were collated by researchers from Qatar University and the University of Dhaka along with collaborators from Pakistan and Malaysia and some medical doctors. In their current release, there are 219 COVID-19 positive images, 1341 normal images and 1345 viral pneumonia images (Chowdhury et al., 2020). To ensure multiple representations, the dataset of chest X-ray images for both COVID-19 and normal cases were also selected from Mendeley dataset repository (El-Shafai, 2020) which contains 5500 Non-COVID X-ray images and 4044 COVID-19 X-ray images. This study, therefore, adopted these multi source datasets. Due to limited computing resources, in this study, 1,300 images were selected from each category. That is, 1,300 images of COVID-19 positive cases, 1,300 Normal images and 1,300 images of viral pneumonia cases, totaling 3,900 images in all. It is noted here that further descriptions of the datasets were not provided by the authors of the sources of the datasets.<br>El-Shafai, Walid; Abd El-Samie, Fathi (2020), “Extensive COVID-19 X-Ray and CT Chest Images Dataset”, Mendeley Data, V3, doi: 10.17632/8h65ywd2jr.3<br>Chowdhury, M. E., Rahman, T., Khandakar, A., Mazhar, R., Kadir, M. A., Mahbub, Z. B., . . . Reaz, M. B. (2020, March 29). Can AI help in screening Viral and COVID-19 pneumonia? Retrieved from https://arxiv.org/abs/2003.13145; https://www.kaggle.com/tawsifurrahman/covid19-radiography-database
DOI: 10.34849/c73yb7/itsfq0
title: APCSF_11x4.7_static_1B.txt

description: :unav
DOI: 10.34849/c73yb7/yfylpq
title: ISAE_3_static_2.txt

description: :unav
DOI: 10.34849/c73yb7/8cm8u2
title: APCSF_11x4.7_static_1A.txt

description: :unav
DOI: 10.34849/c73yb7/wzjnzc
title: APCSF_9x6_static_2.txt

description: :unav
DOI: 10.34849/c73yb7/x4fbv1
title: APCSF_11x4.7_static_2.txt

description: :unav
DOI: 10.34849/c73yb7/5ixni2
title: ISAE_5_static_2.txt

description: :unav
DOI: 10.34849/c73yb7/4pgzcf
title: APCSF_9x6_static_1.txt

description: :unav
DOI: 10.34849/c73yb7/ivg1yg
title: ISAE_4_static_2.txt

description: :unav
DOI: 10.34849/c73yb7/prglgc
title: ISAE_2_static_2.txt

description: :unav
DOI: 10.34849/c73yb7/mpkcma
title: APCSF_9x6_Time_Data.h5

description: :unav
DOI: 10.34849/c73yb7/dqniyp
title: APCSF_9x6_autopower.h5

description: :unav
DOI: 10.34849/c73yb7/bw9dhz
title: APCSF_11x4.7_Time_Data.h5

description: :unav
DOI: 10.34849/c73yb7/7jqrsc
title: ISAE_3_autopower.h5

description: :unav
DOI: 10.34849/c73yb7/bgfa6b
title: APCSF_11x4.7_autopower.h5

description: :unav
DOI: 10.34849/c73yb7/27zwed
title: ISAE_4_autopower.h5

description: :unav
DOI: 10.34849/c73yb7/lnczny
title: ISAE_2_autopower.h5

description: :unav
DOI: 10.34849/c73yb7/8he2yj
title: ISAE_5_autopower.h5

description: :unav
DOI: 10.34849/c73yb7/c5smen
title: ISAE_5_Time_Data.h5

description: :unav
DOI: 10.6084/m9.figshare.14572773
title: Table $1. Frequency (percentage into brackets) of participants that selected each response of the MCQs for each question.

description: This table reflects the nature and frequencies of misunderstanding of fundamental biomedical concepts across a medical curriculum. This data forms part of a bigger study.
DOI: 10.34849/c73yb7/5eybif
title: ISAE_2_Time_Data.h5

description: :unav
DOI: 10.34849/c73yb7/0dv0hx
title: ISAE_3_Time_Data.h5

description: :unav
DOI: 10.34849/c73yb7/7vkeik
title: ISAE_4_Time_Data.h5

description: :unav
DOI: 10.34849/c73yb7/n7qc1h
title: ISAE_3.igs

description: :unav
DOI: 10.34849/c73yb7/xkqddi
title: ISAE_2.igs

description: :unav
DOI: 10.34849/c73yb7/nvji7d
title: ISAE_5.igs

description: :unav
DOI: 10.34849/c73yb7/qia3n7
title: ISAE_4.igs

description: :unav
DOI: 10.34849/c73yb7/339paj
title: example_aerodynamic.m

description: :unav
DOI: 10.34849/c73yb7/pn3c2r
title: example_autopower.m

description: :unav
DOI: 10.5281/zenodo.4748984
title: Zingiber officinale SPAdes preassembly

description: .
DOI: 10.5281/zenodo.4748983
title: Zingiber officinale SPAdes preassembly

description: .
DOI: 10.25989/9wy4-qg13
title: Materials Experiment and Analysis Database: Electrochemistry measurements containing 76 files performed on plate containing Cr,Mn,Ar,O annealed at 550.0C to add O on 2016-02-26 from Run 20160226.132348

description: Files available via S3 at https://renc.osn.xsede.org/ini210004tommorrell/0_gregoire/<br>20160226.132348.copied-20160226162042264PST.zip <a class="btn btn-xs piwik_download" 
            type="application/octet-stream" href="https://renc.osn.xsede.org/ini210004tommorrell/0_gregoire/9wy4-qg13/20160226.132348.copied-20160226162042264PST.zip">
            <i class="fa fa-download"></i> Download</a>    <br>
description: This record is a component of the Materials Experiment and
Analysis Database (MEAD). It contains raw data and metadata from millions 
of materials synthesis and characterization experiments, as well as the 
analysis and distillation of that data into property and performance 
metrics. The unprecedented quantity and diversity of experimental data 
are searchable by experiment and analysis attributes generated by both 
researchers and data processing software.
DOI: 10.25989/9wyg-z356
title: Materials Experiment and Analysis Database: Material library with Ni,Co,Ce,Fe deposited by INKJET on 2015-02-21 from Plate 00017750 annealed at 350.0C to add O on 2015-02-19

description: Files available via S3 at https://renc.osn.xsede.org/ini210004tommorrell/0_gregoire/<br>1775.zip <a class="btn btn-xs piwik_download" 
            type="application/octet-stream" href="https://renc.osn.xsede.org/ini210004tommorrell/0_gregoire/9wyg-z356/1775.zip">
            <i class="fa fa-download"></i> Download</a>    <br>
description: This record is a component of the Materials Experiment and
Analysis Database (MEAD). It contains raw data and metadata from millions 
of materials synthesis and characterization experiments, as well as the 
analysis and distillation of that data into property and performance 
metrics. The unprecedented quantity and diversity of experimental data 
are searchable by experiment and analysis attributes generated by both 
researchers and data processing software.
DOI: 10.25989/9wzg-t502
title: Materials Experiment and Analysis Database: Electrochemistry measurements containing 7035 files performed on plate containing Ni,Fe,Co,Ce,Co annealed at 350.0C to add O on 2013-08-07 from Run 20130807.143305

description: Files available via S3 at https://renc.osn.xsede.org/ini210004tommorrell/0_gregoire/<br>20130807.143305.copied-20150131000000000PST.zip <a class="btn btn-xs piwik_download" 
            type="application/octet-stream" href="https://renc.osn.xsede.org/ini210004tommorrell/0_gregoire/9wzg-t502/20130807.143305.copied-20150131000000000PST.zip">
            <i class="fa fa-download"></i> Download</a>    <br>
description: This record is a component of the Materials Experiment and
Analysis Database (MEAD). It contains raw data and metadata from millions 
of materials synthesis and characterization experiments, as well as the 
analysis and distillation of that data into property and performance 
metrics. The unprecedented quantity and diversity of experimental data 
are searchable by experiment and analysis attributes generated by both 
researchers and data processing software.
DOI: 10.5066/f7m907m8
title: Chemistry of groundwater, pore water, and surface water near wetland P1 in the Cottonwood Lake Study Area, Sutsman County, ND - August 2013

description: Groundwater, soil pore water, and surface water were collected in and near wetland P1 in the Cottonwood Lake Study Area, Stutsman County, North Dakota in August 2013. Groundwater was collected from established wells (17, 18, and 22) via peristaltic pump. Surface water was collected from P1 ponded water via grab sample. Soil pore water was collected using drive point samplers and one suction lysimeter. Water samples were analyzed for pH and major ion chemistry.
DOI: 10.5066/f7057dwm
title: Corescan Hyperspectral Core Imager, Mark III system data collected for the characterization of mineral resources near Nabesna, Alaska, 2014-2016

description: Corescan Hyperspectral Core Imager Mark III (HCI-III) system data were acquired for hand samples, and subsequent billets made from the hand samples, collected during the U.S. Geological Survey (USGS) 2014, 2015, and 2016 field seasons in the Nabesna area of the eastern Alaska Range. This area contains exposed porphyry deposits and hand samples were collected throughout the region in support of the HyMap imaging spectrometer survey (https://doi.org/10.5066/F7DN435W) (Kokaly and others, 2017a). The HCI-III system consists of three different components. The first is an imaging spectrometer which collects reflectance data with a spatial resolution of approximately 500 nanometers (nm) for 514 spectral channels covering the 450-2,500 nm wavelength range of the electromagnetic spectrum (Martini and others, 2017). The second is a spectrally calibrated RGB camera that collects high resolution imagery of the samples with a 50 micrometer pixel size. The third component is a three-dimensional (3D) laser profiler that measures sample texture, surface features and shape with a vertical resolution of 20 micrometer (Martini and others, 2017). The imaging spectrometer raw data were collected with an average bandpass of approximately 6 nm across the Short Wave Infrared (SWIR) but smoothing functions applied by Corescan during the conversion of raw data to reflectance result in a relative bandpass of approximately 13 nm in the data delivered to the USGS. Wavelength evaluations of the imaging spectrometer data revealed that the supplied wavelength values should be shifted and, thus, adjustments were made to the wavelength positions (Kokaly and others, 2017c). The wavelength and bandpass evaluation results are provided in the 'Calibration' section of this data release and were used to adjust the Corescan reflectance data. The calibrated Corescan data were combined into a reflectance data cube mosaic and are provided in the 'HyperspectralCalibrated' section. Calibrated reflectance data from Corescan were processed using the Material Identification and Characterization Algorithm (MICA), a module of the USGS PRISM (Processing Routines in IDL for Spectroscopic Measurements) software (Kokaly, 2011). MICA identifies the spectrally predominant mineral(s) in each pixel of imaging spectrometer data by comparing continuum-removed spectral features in the pixel's reflectance spectrum to continuum-removed absorption features in reference spectra of minerals and other materials. For each pixel, the reference spectrum with the highest fit value identifies the predominant mineral class. White mica wavelength position was computed for each pixel with spectrally predominant muscovite or illite. The computation was made using a function of the USGS PRISM software (Kokaly, 2011). The white mica wavelength values were output as a classification image, with classes in 1 nm increments.
DOI: 10.25989/9x15-wf21
title: Materials Experiment and Analysis Database: Sample imaging and alignment measurements containing 2 files performed on plate containing Mn,Ta,Sb,Co,Co annealed at 350.0C to add O on 2014-04-06 from Run 20140405.171737

description: Files available via S3 at https://renc.osn.xsede.org/ini210004tommorrell/0_gregoire/<br>20140405.171737.copied-20150605223311676PDT.zip <a class="btn btn-xs piwik_download" 
            type="application/octet-stream" href="https://renc.osn.xsede.org/ini210004tommorrell/0_gregoire/9x15-wf21/20140405.171737.copied-20150605223311676PDT.zip">
            <i class="fa fa-download"></i> Download</a>    <br>
description: This record is a component of the Materials Experiment and
Analysis Database (MEAD). It contains raw data and metadata from millions 
of materials synthesis and characterization experiments, as well as the 
analysis and distillation of that data into property and performance 
metrics. The unprecedented quantity and diversity of experimental data 
are searchable by experiment and analysis attributes generated by both 
researchers and data processing software.
DOI: 10.6084/m9.figshare.18864311
title: Maragogipinho_Risk.xls

description: Risk estimation due to soil lead content at Maragogipinho Beazil<br>
DOI: 10.6084/m9.figshare.18864311.v1
title: Maragogipinho_Risk.xls

description: Risk estimation due to soil lead content at Maragogipinho Beazil<br>
DOI: 10.34740/kaggle/dsv/3075048
title: Omicron daily cases by country (COVID-19 variant)
DOI: 10.5517/ccdc.csd.cc28g160
title: CCDC 2098861: Experimental Crystal Structure Determination

description: Related Article: Xiaoxiao Wang, Cheng Zhong, Guohua Xie, Xingguo Chen|2022|J.Mater.Chem.C|10|1127|doi:10.1039/D1TC04941K
DOI: 10.5517/ccdc.csd.cc28h497
title: CCDC 2099918: Experimental Crystal Structure Determination

description: Related Article: Konstantin A. Rufanov, Ilya Yu. Titov, Dmitry A. Lemenovskii, Dmitry P. Krut’ko, Andrei V. Churakov|2022|New J.Chem.|46|1409|doi:10.1039/D1NJ05094J
DOI: 10.5517/ccdc.csd.cc28jl2h
title: CCDC 2101306: Experimental Crystal Structure Determination

description: Related Article: Gang Wang, Nannan Ding, Hongxing Hao, Qingwei Jiang, Qianqian Feng, Ke Liu, Chunxia Hua, Hongtao Bian, Yu Fang, Fengyi Liu|2022|J.Mater.Chem.C|10|1118|doi:10.1039/D1TC04627F
DOI: 10.5517/ccdc.csd.cc28jl3j
title: CCDC 2101307: Experimental Crystal Structure Determination

description: Related Article: Gang Wang, Nannan Ding, Hongxing Hao, Qingwei Jiang, Qianqian Feng, Ke Liu, Chunxia Hua, Hongtao Bian, Yu Fang, Fengyi Liu|2022|J.Mater.Chem.C|10|1118|doi:10.1039/D1TC04627F
DOI: 10.5517/ccdc.csd.cc28jl4k
title: CCDC 2101308: Experimental Crystal Structure Determination

description: Related Article: Gang Wang, Nannan Ding, Hongxing Hao, Qingwei Jiang, Qianqian Feng, Ke Liu, Chunxia Hua, Hongtao Bian, Yu Fang, Fengyi Liu|2022|J.Mater.Chem.C|10|1118|doi:10.1039/D1TC04627F
DOI: 10.5517/ccdc.csd.cc28l7fk
title: CCDC 2102898: Experimental Crystal Structure Determination

description: Related Article: Giliandro Farias, Cristian A. M. Salla, Jéssica Toigo, Luís Gustavo Teixeira Alves Duarte, Adailton J. Bortoluzzi, Edivandro Girotto, Hugo Gallardo, Teresa Dib Zambon Atvars, Bernardo de Souza, Ivan H. Bechtold|2022|Dalton Trans.|51|1008|doi:10.1039/D1DT03912A
DOI: 10.5517/ccdc.csd.cc28l7dj
title: CCDC 2102897: Experimental Crystal Structure Determination

description: Related Article: Giliandro Farias, Cristian A. M. Salla, Jéssica Toigo, Luís Gustavo Teixeira Alves Duarte, Adailton J. Bortoluzzi, Edivandro Girotto, Hugo Gallardo, Teresa Dib Zambon Atvars, Bernardo de Souza, Ivan H. Bechtold|2022|Dalton Trans.|51|1008|doi:10.1039/D1DT03912A
DOI: 10.5066/f7222rxw
title: Data for a Comprehensive Survey of Fault Zones, Breccias, and Fractures in and Flanking the Eastern Espanola Basin, Rio Grande Rift, New Mexico

description: This release provides the data for a comprehensive survey of geologic structures in the eastern Espaola Basin of the Rio Grande rift, New Mexico. The release includes data and analyses from 53 individual fault zones and 22 other brittle structures, such as breccia zones, joints, and veins, investigated at a total of just over 100 sites. Structures were examined and compared from poorly lithified Tertiary sediments, as well as Paleozoic sedimentary and Proterozoic crystalline rocks. Data and analyses, include geologic maps; field observations and measurements; orientation, kinematic paleostress analyses and modeling; statistical examination of 575 fault trace lengths derived from aeromagnetic data in the Espaola and adjacent basins; mineralogy and chemistry of host and fault rocks; and investigation of fault versus bolide impact hypotheses for the origin of enigmatic breccias found in the Proterozoic basement rocks. Kinematic and paleostress analyses suggest a record of transitional, and perhaps partitioned, strains from the Laramide orogeny through Rio Grande rifting. Normal faults within Tertiary basin fill sediments are consistent with more typical WNW-ESE Rio Grande extension, perhaps decoupled from bedrock structures due to strength contrasts favoring the formation of new faults in the relatively weak sediments. Analyses of the fault length data indicate power law length distributions similar to those reported from many geologic settings globally. Mineralogy and chemistry in Proterozoic fault-related rocks reveal geochemical changes tied to hydrothermal alteration and nearly isochemical transformation of feldspars to clay minerals. In sediments, fault rocks are characterized by mechanical entrainment with minor secondary chemical changes. Enigmatic breccias are autoclastic, isochemical with respect to their protoliths, and occur near shatter cones believed to be related to a pre-Pennsylvanian impact event. A weak iridium anomaly is associated with the breccias as well as adjacent protoliths, thus an impact shock wave cannot be ruled out for their origin. The types of faults, associated brittle structures, and geochemical attributes provided here can aid in development of conceptual models and approaches useful in identifying testable hypotheses grounded in geological data when assessing ground- and surface-water resources.
DOI: 10.5517/ccdc.csd.cc28pg2j
title: CCDC 2105987: Experimental Crystal Structure Determination

description: Related Article: Zhi-Gang Yin, Xiong-Wei Liu, Hui-Juan Wang, Min Zhang, Xiong-Li Liu, Ying Zhou|2022|New J.Chem.|46|1295|doi:10.1039/D1NJ05170A
DOI: 10.5517/ccdc.csd.cc28pg4l
title: CCDC 2105989: Experimental Crystal Structure Determination

description: Related Article: Zhi-Gang Yin, Xiong-Wei Liu, Hui-Juan Wang, Min Zhang, Xiong-Li Liu, Ying Zhou|2022|New J.Chem.|46|1295|doi:10.1039/D1NJ05170A
DOI: 10.5517/ccdc.csd.cc28n0ts
title: CCDC 2104615: Experimental Crystal Structure Determination

description: Related Article: Xinxin Liu, Le Zhang, SiSi Zhao, Biao Guo, Zhen Zhao|2022|New J.Chem.|46|974|doi:10.1039/D1NJ05335C
DOI: 10.5517/ccdc.csd.cc288mmt
title: CCDC 2093666: Experimental Crystal Structure Determination

description: Related Article: N. K. Ramya, C. Femina, Suganya Suresh, Divya S. Mohanakumari, Retheesh Krishnan, Reji Thomas|2022|New J.Chem.|46|1339|doi:10.1039/D1NJ04489C
DOI: 10.5517/ccdc.csd.cc288mkr
title: CCDC 2093664: Experimental Crystal Structure Determination

description: Related Article: N. K. Ramya, C. Femina, Suganya Suresh, Divya S. Mohanakumari, Retheesh Krishnan, Reji Thomas|2022|New J.Chem.|46|1339|doi:10.1039/D1NJ04489C
DOI: 10.5517/ccdc.csd.cc288mls
title: CCDC 2093665: Experimental Crystal Structure Determination

description: Related Article: N. K. Ramya, C. Femina, Suganya Suresh, Divya S. Mohanakumari, Retheesh Krishnan, Reji Thomas|2022|New J.Chem.|46|1339|doi:10.1039/D1NJ04489C
DOI: 10.6084/m9.figshare.18857435
title: ChAc shape_analysis_P3.zip.003

description: This dataset is part 3 of the red blood cell shape analysis data for P3 presented in the manuscript Reichel et al., 2021, Changes in blood cell deformability in Chorea-Acanthocytosis and effects of treatment with dasatinib or lithium.