cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5517/ccdc.csd.cc2bv4cq
title: CCDC 2170073: Experimental Crystal Structure Determination

description: Related Article: Penglong Wang, Yue Zhao, Congqing Zhu|2022|Organometallics|41|2448|doi:10.1021/acs.organomet.2c00240
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2bv4dr
title: CCDC 2170074: Experimental Crystal Structure Determination

description: Related Article: Penglong Wang, Yue Zhao, Congqing Zhu|2022|Organometallics|41|2448|doi:10.1021/acs.organomet.2c00240
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2bv4fs
title: CCDC 2170075: Experimental Crystal Structure Determination

description: Related Article: Penglong Wang, Yue Zhao, Congqing Zhu|2022|Organometallics|41|2448|doi:10.1021/acs.organomet.2c00240
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2bywt0
title: CCDC 2173683: Experimental Crystal Structure Determination

description: Related Article: André U. Augustin, Sergio Di Silvio, Ilan Marek|2022|J.Am.Chem.Soc.|144|16298|doi:10.1021/jacs.2c07394
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2bywv1
title: CCDC 2173684: Experimental Crystal Structure Determination

description: Related Article: André U. Augustin, Sergio Di Silvio, Ilan Marek|2022|J.Am.Chem.Soc.|144|16298|doi:10.1021/jacs.2c07394
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2byww2
title: CCDC 2173685: Experimental Crystal Structure Determination

description: Related Article: André U. Augustin, Sergio Di Silvio, Ilan Marek|2022|J.Am.Chem.Soc.|144|16298|doi:10.1021/jacs.2c07394
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2bywx3
title: CCDC 2173686: Experimental Crystal Structure Determination

description: Related Article: André U. Augustin, Sergio Di Silvio, Ilan Marek|2022|J.Am.Chem.Soc.|144|16298|doi:10.1021/jacs.2c07394
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2bywy4
title: CCDC 2173687: Experimental Crystal Structure Determination

description: Related Article: André U. Augustin, Sergio Di Silvio, Ilan Marek|2022|J.Am.Chem.Soc.|144|16298|doi:10.1021/jacs.2c07394
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2c0ty5
title: CCDC 2175547: Experimental Crystal Structure Determination

description: Related Article: André U. Augustin, Sergio Di Silvio, Ilan Marek|2022|J.Am.Chem.Soc.|144|16298|doi:10.1021/jacs.2c07394
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5281/zenodo.7080902
title: ImageJ OIB test files

description: .oib and .oif test files that do not open in ImageJ likely due to Bioformats bug
DOI: 10.5281/zenodo.7080901
title: ImageJ OIB test files

description: .oib and .oif test files that do not open in ImageJ likely due to Bioformats bug
DOI: 10.5517/ccdc.csd.cc2bplsf
title: CCDC 2165715: Experimental Crystal Structure Determination

description: Related Article: Simarjeet Kaur, Moumita Bera, Aakash Santra, Sandip Munshi, George E. Sterbinsky, Tianpin Wu, Dooshaye Moonshiram, Sayantan Paria|2022|Inorg.Chem.|61|14252|doi:10.1021/acs.inorgchem.2c01472
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc28v4jt
title: CCDC 2110496: Experimental Crystal Structure Determination

description: Related Article: Simarjeet Kaur, Moumita Bera, Aakash Santra, Sandip Munshi, George E. Sterbinsky, Tianpin Wu, Dooshaye Moonshiram, Sayantan Paria|2022|Inorg.Chem.|61|14252|doi:10.1021/acs.inorgchem.2c01472
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc28v4kv
title: CCDC 2110497: Experimental Crystal Structure Determination

description: Related Article: Simarjeet Kaur, Moumita Bera, Aakash Santra, Sandip Munshi, George E. Sterbinsky, Tianpin Wu, Dooshaye Moonshiram, Sayantan Paria|2022|Inorg.Chem.|61|14252|doi:10.1021/acs.inorgchem.2c01472
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2c7zby
title: CCDC 2182410: Experimental Crystal Structure Determination

description: Related Article: Yang Li, Kang Min Ok|2022|Cryst.Growth Des.|22|5639|doi:10.1021/acs.cgd.2c00725
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2bv4gt
title: CCDC 2170076: Experimental Crystal Structure Determination

description: Related Article: Penglong Wang, Yue Zhao, Congqing Zhu|2022|Organometallics|41|2448|doi:10.1021/acs.organomet.2c00240
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2chf0b
title: CCDC 2189561: Experimental Crystal Structure Determination

description: Related Article: Yanping Cai, Shengjie Jiang, Thayalan Rajeshkumar, Laurent Maron, Xin Xu|2022|J.Am.Chem.Soc.|144|16647|doi:10.1021/jacs.2c07402
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2chf1c
title: CCDC 2189562: Experimental Crystal Structure Determination

description: Related Article: Yanping Cai, Shengjie Jiang, Thayalan Rajeshkumar, Laurent Maron, Xin Xu|2022|J.Am.Chem.Soc.|144|16647|doi:10.1021/jacs.2c07402
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2chf2d
title: CCDC 2189563: Experimental Crystal Structure Determination

description: Related Article: Yanping Cai, Shengjie Jiang, Thayalan Rajeshkumar, Laurent Maron, Xin Xu|2022|J.Am.Chem.Soc.|144|16647|doi:10.1021/jacs.2c07402
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.6084/m9.figshare.21115123.v1
title: Supplementary Material for: Vaginal Delivery Is Associated with Neurochemical Evidence of Increased Neuroaxonal Remodelling in Infants from the KUNO-Kids Health Study: Cross-Sectional Analysis

description: <b><i>Aim:</i></b> Little is known about neonatal brain plasticity or the impact of birth mode on neurointegrity. As a reflection of neuroaxonal damage, the neuronal structural protein neurofilament light chain (NfL) has emerged as a highly specific biomarker. Our purpose was to test the hypothesis that vaginal delivery is associated with increased NfL in neonates. <b><i>Methods:</i></b> NfL concentrations were measured using single-molecule array immunoassay in umbilical cord serum from healthy term neonates enrolled in the prospective KUNO-Kids Health Study. NfL values were investigated for independent influencing factors using linear and logistic models, followed by post hoc propensity score-matching. <b><i>Results:</i></b> Of 665 neonates, <i>n</i> = 470 (70.7%) were delivered vaginally and <i>n</i> = 195 (29.3%) by cesarean section. Median serum NfL was significantly higher after vaginal delivery 14.4 pg/mL (11.6–18.5) compared to primary 7.5 pg/mL (6.1–8.9) and secondary cesarean delivery 9.3 pg/mL (7.5–12.0). Multivariable logistic regression models showed delivery mode and gestational age to be independently associated with NfL. Propensity score-matching analysis confirmed that assisted vaginal delivery generated higher NfL compared to vaginal (non-assisted), while lowest levels were associated with cesarean section. <b><i>Interpretation:</i></b> Our data confirm the significant impact of birth mode on neonatal NfL levels. The persistence of these differences and their potential long-term impact have yet to be investigated.
DOI: 10.14459/2022mp1686124
title: Lunar Hydrogen Exosphere Predictions

description: "Smolka2022 - Lunar Hydrogen Exosphere Predictions" The dataset contains the three subfolders "mean_loss", "mean_surface_number_density", and "raw_julia". The first two folders contain eight CSV files, one for each of the eight performed studies, which list the empirical mean value over all (4000) Monte-Carlo steps for the losses and the surface number densities, respectively. The losses are given as globally lost particles per second, sorted by the loss mechanism (rows) and the elements H, H2, OH, and H2O (columns). The surface number densities are given as particles per cubic centimeters at the numerical grid points, which are supplied in the form of local time (first column) and subsolar latitude (second column). The used numerical grid is a structured grid with 180 points along the local time and 45 points along the latitude, which discretizes the upper hemisphere, assuming equatorial symmetry. The last folder "raw_julia" contains the compressed Julia data of all Monte-Carlo steps, in ".jld2" format. These can be extracted using the "JLD2" package with the command "jldopen( path &gt;.jld2)".
DOI: 10.6084/m9.figshare.19612971.v3
title: Dances with wolves: Exploring the limits to turning performance with size and shape variation in dogs

description: <br> Supplementary data for: <br> Dances with wolves: Exploring the limits to turning performance with size and shape variation in dogs Tina Haagensen1,2, Johanna T. Schultz1,3, Joshua Gaschk1, Christofer J. Clemente1 <br> 1. School of Science and Engineering, University of the Sunshine Coast, QLD, Australia <br> 2. Kristiansand Dyrepark, 4609 Kardemomme by, Norway <br> 3. The Robotics and Autonomous Systems Group, CSIRO Data61, QLD, Australia <br>
DOI: 10.7910/dvn/zejdqp
title: Best Hijab Collections in 2022: Muslim Fashion Trend

description: Introduction We are wondering where and how to shop for hijabs in Pakistan. We have an answer for you! our extensive collection and accessories is just a click away. Make your shopping experience easy and fun! If you're living in Pakistan and looking for some of the best hijab designers in Pakistan, you've come to the right place. From fashion accessories to headscarves; We will provide you with amazing accessories that are perfect for the modern Pakistani woman. If you're not from Pakistan, head to the Hijab Bride site for our worldwide selection of products for hijabs and fashion clothing. Remember to try our 100% scarf discount code below before checking out! Available in all shapes, sizes, colors, and designs. With the coming of age of worldwide hijab online shopping, the fashion market has been opening up doors to the young generation by offering them pick from traditional to modern-chic. It’s a headscarf worn in front of the chest; it covers the forehead and hair as well but not the face. A religious code for Muslim women, which is especially a part of Muslim culture finds its fashion statement in this beautiful item. Importance of Hijab It’s a form of head covering worn by some Muslim women as a symbol of modesty and privacy. Hijab is often referred to as the headscarf, which can be confusing as this term more often refers to a simple scarf that keeps hair in place. Hijabs are available in all kinds of styles, colors, and fabrics, and they come in many different sizes. The most common type of hijab is a square scarf that covers the head and neck. It usually has fringes on its ends, which are called tassels or knut (plural of the unit). Some have designs or patterns on them, while others are plain. The original Arabic word for "veil" is jilbab (jilbab is also known as burqa). Jilbab means "garment" or "clothing." In the Qur'an, it refers to outer garments worn by both men and women that cover their bodies from the neck down to their ankles. Muslim women are required to cover their heads and body in public. Hijab is an Islamic code of dress that covers the body and hair of a woman. It is hailed as one of the most important concepts in Islam and has been a historical practice since the beginning of Islam. It has been an integral part of the Muslim culture for centuries now. And popularized by various Islamic scholars, such as Syed Ahmed Khan and Maulana Shibli Nomani who propagated it through their writings. The concept behind is that it should not attract attention from people around you; rather it should be something that you wear within yourself, which means that it should not be flashy or colorful either because these things attract attention from others.
DOI: 10.34740/kaggle/dsv/4206556
title: MyWSL2022
DOI: 10.6084/m9.figshare.21113671.v3
title: metadata

description: Metadata- ITS 16S Assembly Experiment
DOI: 10.5281/zenodo.6806398
title: PNS-Cyst

description: Data collected by the PheNeSens (Phenotyping of Nematodes with Sensors) project. The images recorded cysts of sugar beet nematode, together with organic debris from the soil sample, left after the soil processing. All cysts are manually outlined by experts and saved as indexed-PNG images. We used the annotations to train deep neural networks for automatic cyst segmentation in the PheNeSens project. For details of the data collection and deep learning model training, refer to our paper: Chen L, Daub M, Luigs H-G, Jansen M, Strauch M and Merhof D (2022) High-throughput phenotyping of nematode cysts. Front. Plant Sci. 13:965254. doi: 10.3389/fpls.2022.965254 [link]
DOI: 10.5281/zenodo.6725691
title: PNS-Cyst

description: Data collected by the PheNeSens (Phenotyping of Nematodes with Sensors) project. The images recorded cysts of sugar beet nematode, together with organic debris from the soil sample, left after the soil processing. All cysts are manually outlined by experts and saved as indexed-PNG images. We used the annotations to train deep neural networks for automatic cyst segmentation in the PheNeSens project. For details of the data collection and deep learning model training, refer to our paper: Chen L, Daub M, Luigs H-G, Jansen M, Strauch M and Merhof D (2022) High-throughput phenotyping of nematode cysts. Front. Plant Sci. 13:965254. doi: 10.3389/fpls.2022.965254 [link]
DOI: 10.5281/zenodo.6861775
title: PNS-Cyst-Count (Part1): nematode cysts with orgnic debris, annotated with cyst count

description: Data collected by the PheNeSens (Phenotyping of Nematodes with Sensors) project. The images recorded cysts of sugar beet nematode, together with organic debris from the soil sample, left after the soil processing. A total of 48 soil samples are recorded (30 images per sample) and number of cysts are manually counted. This is the first part, in which cysts present along with large amount of organic debris. The second part (cysts without debris) is available under link: https://zenodo.org/record/6861814 For details of the data collection and deep learning model training, refer to our paper: Chen L, Daub M, Luigs H-G, Jansen M, Strauch M and Merhof D (2022) High-throughput phenotyping of nematode cysts. Front. Plant Sci. 13:965254. doi: 10.3389/fpls.2022.965254 [link]
DOI: 10.5281/zenodo.6861774
title: PNS-Cyst-Count (Part1): nematode cysts with orgnic debris, annotated with cyst count

description: Data collected by the PheNeSens (Phenotyping of Nematodes with Sensors) project. The images recorded cysts of sugar beet nematode, together with organic debris from the soil sample, left after the soil processing. A total of 48 soil samples are recorded (30 images per sample) and number of cysts are manually counted. This is the first part, in which cysts present along with large amount of organic debris. The second part (cysts without debris) is available under link: https://zenodo.org/record/6861814 For details of the data collection and deep learning model training, refer to our paper: Chen L, Daub M, Luigs H-G, Jansen M, Strauch M and Merhof D (2022) High-throughput phenotyping of nematode cysts. Front. Plant Sci. 13:965254. doi: 10.3389/fpls.2022.965254 [link]
DOI: 10.5281/zenodo.6861814
title: PNS-Cyst-Count (Part2): hand-picked nematode cysts without organic debris, annotated with cyst count

description: Data collected by the PheNeSens (Phenotyping of Nematodes with Sensors) project. The images recorded cysts of sugar beet nematode, together with organic debris from the soil sample, left after the soil processing. A total of 48 soil samples are recorded (30 images per sample) and number of cysts are manually counted. This is the second part, containing images of hand-picked cysts on filter papers. The cysts before hand-picking (with large amount of organic debris) is available under: https://zenodo.org/record/6861775 For details of the data collection and deep learning model training, refer to our paper: Chen L, Daub M, Luigs H-G, Jansen M, Strauch M and Merhof D (2022) High-throughput phenotyping of nematode cysts. Front. Plant Sci. 13:965254. doi: 10.3389/fpls.2022.965254 [link]
DOI: 10.5281/zenodo.6861813
title: PNS-Cyst-Count (Part2): hand-picked nematode cysts without organic debris, annotated with cyst count

description: Data collected by the PheNeSens (Phenotyping of Nematodes with Sensors) project. The images recorded cysts of sugar beet nematode, together with organic debris from the soil sample, left after the soil processing. A total of 48 soil samples are recorded (30 images per sample) and number of cysts are manually counted. This is the second part, containing images of hand-picked cysts on filter papers. The cysts before hand-picking (with large amount of organic debris) is available under: https://zenodo.org/record/6861775 For details of the data collection and deep learning model training, refer to our paper: Chen L, Daub M, Luigs H-G, Jansen M, Strauch M and Merhof D (2022) High-throughput phenotyping of nematode cysts. Front. Plant Sci. 13:965254. doi: 10.3389/fpls.2022.965254 [link]
DOI: 10.5281/zenodo.6870064
title: PNS-Cyst-Count-Artifical: images of controlled number of nematode cysts with orgnic debris

description: Data collected by the PheNeSens (Phenotyping of Nematodes with Sensors) project. The images recorded cysts of sugar beet nematode, together with organic debris from the soil sample, left after the soil processing. This dataset was generated by manually picking nematode cysts into organic debris, so that the cyst count is known and controlled. A total of 6x8=48 samples were synthesized. Each sample contains 30 images. We also collected images of real soil samples, which is available from the links: https://zenodo.org/record/6861775 https://zenodo.org/record/6861814 For details of the data collection and deep learning model training, refer to our paper: Chen L, Daub M, Luigs H-G, Jansen M, Strauch M and Merhof D (2022) High-throughput phenotyping of nematode cysts. Front. Plant Sci. 13:965254. doi: 10.3389/fpls.2022.965254 [link]