cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5517/ccdc.csd.cc2f56c6
title: CCDC 2239327: Experimental Crystal Structure Determination

description: Related Article: Youcong Li, Jian Su, Yue Zhao, Liang Feng, Lei Gao, Xinyu Xu, Ya Yin, Yifan Liu, Pengwei Xiao, Ling Yuan, Jun-Sheng Qin, Yuanyuan Wang, Shuai Yuan, He Zheng, Jing-Lin Zuo|2023|J.Am.Chem.Soc.|145|10227|doi:10.1021/jacs.3c01219
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.cc2f56d7
title: CCDC 2239328: Experimental Crystal Structure Determination

description: Related Article: Youcong Li, Jian Su, Yue Zhao, Liang Feng, Lei Gao, Xinyu Xu, Ya Yin, Yifan Liu, Pengwei Xiao, Ling Yuan, Jun-Sheng Qin, Yuanyuan Wang, Shuai Yuan, He Zheng, Jing-Lin Zuo|2023|J.Am.Chem.Soc.|145|10227|doi:10.1021/jacs.3c01219
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.cc2f56f8
title: CCDC 2239329: Experimental Crystal Structure Determination

description: Related Article: Youcong Li, Jian Su, Yue Zhao, Liang Feng, Lei Gao, Xinyu Xu, Ya Yin, Yifan Liu, Pengwei Xiao, Ling Yuan, Jun-Sheng Qin, Yuanyuan Wang, Shuai Yuan, He Zheng, Jing-Lin Zuo|2023|J.Am.Chem.Soc.|145|10227|doi:10.1021/jacs.3c01219
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.cc2c7sr5
title: CCDC 2182237: Experimental Crystal Structure Determination

description: Related Article: Charlotte Koschnick, Maxwell W. Terban, Ruggero Frison, Martin Etter, Felix A. Böhm, Davide M. Proserpio, Simon Krause, Robert E. Dinnebier, Stefano Canossa, Bettina V. Lotsch|2023|J.Am.Chem.Soc.|145|10051|doi:10.1021/jacs.2c13731
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.cc2fdct1
title: CCDC 2246223: Experimental Crystal Structure Determination

description: Related Article: Min Li, Yi Zhong, Yunjie Luo, Meng Deng|2023|New J.Chem.|47|22299|doi:10.1039/D3NJ04245F
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.cc2fxf0t
title: CCDC 2261636: Experimental Crystal Structure Determination

description: Related Article: Devyani Srivastava, Aparna Kushwaha, Gabriele Kociok-Köhn, Suresh W. Gosavi, Ratna Chauhan, Abhinav Kumar, Mohd. Muddassir|2023|CrystEngComm|25|6822|doi:10.1039/D3CE00817G
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.cc2h3wk2
title: CCDC 2297644: Experimental Crystal Structure Determination

description: Related Article: Maxim V. Mikhailenko, Vladislav V. Ivanov, Maxim A. Faraonov, Aleksey V. Kuzmin, Salavat S. Khasanov, Akihiro Otsuka, Hideki Yamochi, Hiroshi Kitagawa, Dmitri V. Konarev|2023|New J.Chem.|47|22339|doi:10.1039/D3NJ04615J
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: 10.17632/gr74wwckcp.1
title: ANT 2023: A program for adiabatic and nonadiabatic trajectories

description: ANT 2023 is a program for quasiclassical and semiclassical trajectories, both single-surface trajectories for which the Born-Oppenheimer approximation is valid and multi-surface calculations with electronic state changes, i.e., for electronically adiabatic and electronically nonadiabatic trajectories. There are several methods available for multisurface problems: surface hopping with or without time uncertainty and with or without decoherence, semiclassical Ehrenfest, self-consistent decay of mixing, and coherent switching with decay of mixing (CSDM). The potential surface for single-surface problems may be an analytic potential function supplied by the user, or one may use direct dynamics. To use the adiabatic representation (i.e., electronically adiabatic basis functions) for electronically nonadiabatic dynamics, the user may either provide the adiabatic surfaces and nonadiabatic couplings by direct dynamics, or the program may calculate them from diabatic surfaces and diabatic couplings, which are usually analytic. One can also use analytic fits to the surfaces and couplings to carry out calculations entirely in the diabatic representation. The curvature-driven approximation is available as an option for use with CSDM and trajectory surface hopping. The ANT 2023 program is especially recommended for calculations with analytic potential energy surfaces and couplings because of its high efficiency for such calculations.
DOI: 10.5281/zenodo.10399924
title: A method to investigate Pathological Variant load of Mitochondrial DNA  in single human Mesenchyma stem cells

description: Mesenchymal stem cells (MSCs) are the parent cells to many cells of the musculoskeletal system including osteoblasts. Previous work has shown that in mouse models mitochondrial DNA (mtDNA) pathological variants lead to dysfunction of the respiratory chain of these osteoblasts and the premature development of age related osteoporosis. An increased rate of respiratory chain deficiency has also been observed in human osteoblasts. mtDNA mutates at an enhanced rate compared to nuclear DNA and has been linked to the ageing process in humans. 

We have developed and optimised an experimental pipeline to isolate single MSCs using flow cytometry before performing next generation sequencing to analyse the pathogenic variant load of 13 patients aged 22-88 to assess if pathogenic variants exist in mesenchymal stem cells and if there are age related changes.

Across all patients and all cells mtDNA pathological variants were present at similarly low levels. As per previous studies we found increased pathogenic variants within the mtDNA control region (D-Loop). However overall, there was no significant difference in the distribution of variants across the rest of the genome in all patients. Although a higher proportion of non-synonymous variants were seen this was not statistically significant.

We have shown that it is possible to isolate and sequence individual MSCs and observe mtDNA pathological variants. This gives a snapshot in time of the variant load for each patient. Due to low sample numbers compared to other studies investigate mtDNA in other cell types, we did not observe any age related increase in pathological variants. However this adds further evidence that clonally expanded, somatic mtDNA variants are common and could contribute to age related disease including osteoporosis.
DOI: 10.5519/qd.677a98v1
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (1 records)
DOI: 10.5281/zenodo.10400789
title: Dataset and codes: Abundance of trace fossil Phycosiphon incertum in core sections measured using a convolutional neural network
DOI: 10.5281/zenodo.10400790
title: Dataset and codes: Abundance of trace fossil Phycosiphon incertum in core sections measured using a convolutional neural network
DOI: 10.5519/qd.khxlnau1
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (1 records)
DOI: 10.6084/m9.figshare.24573064
title: Impact of Omicron variant sublineage BA.2.75 on the OnSite COVID-19 Ag Rapid Test: the applicability of rapid antigen test with universal transport media

description: Rapid antigen testing (RAT) is one of the most powerful tools for SARS-CoV-2 detection. The OnSite COVID-19 Ag Rapid Test is an antigen-based, point-of-care test approved by the WHO for Emergency Use Listing. The <i>Nucleocapsid</i> (<i>N</i>) gene mutations found in the emerging Omicron sublineages lead to the question of RAT performance. To ensure the diagnostic performance of the study RAT during rapidly mutated Omicron variants. We independently evaluated the performance of this assay in 1098 archived samples collected in Thailand during October 2022–February 2023, which were 798 and 300 COVID-19 real-time RT-PCR positive and negative, respectively. The assay performed with 100% sensitivity and 100% specificity using a cycle threshold (Ct) of &lt;20 for the RT-PCR. The sensitivity decreased to 88% when using Ct &lt;30. Most of the SARS-CoV-2 found were Omicron BA.2 (99%), harboring six known <i>N</i> mutations (P13L, E31del, S33del, R203K, G204R and S413R). Eight samples containing hybrid variants (XBB.1*, XBB.2 and XBJ) were detected by the study RAT. This RAT detects all Omicron sublineages known to be circulating in Thailand. These results confirmed the good performance of the study RAT for detecting Omicron variants and its appropriateness for individual diagnosis and for genomic surveillance.
DOI: 10.6084/m9.figshare.24573064.v1
title: Impact of Omicron variant sublineage BA.2.75 on the OnSite COVID-19 Ag Rapid Test: the applicability of rapid antigen test with universal transport media

description: Rapid antigen testing (RAT) is one of the most powerful tools for SARS-CoV-2 detection. The OnSite COVID-19 Ag Rapid Test is an antigen-based, point-of-care test approved by the WHO for Emergency Use Listing. The <i>Nucleocapsid</i> (<i>N</i>) gene mutations found in the emerging Omicron sublineages lead to the question of RAT performance. To ensure the diagnostic performance of the study RAT during rapidly mutated Omicron variants. We independently evaluated the performance of this assay in 1098 archived samples collected in Thailand during October 2022–February 2023, which were 798 and 300 COVID-19 real-time RT-PCR positive and negative, respectively. The assay performed with 100% sensitivity and 100% specificity using a cycle threshold (Ct) of &lt;20 for the RT-PCR. The sensitivity decreased to 88% when using Ct &lt;30. Most of the SARS-CoV-2 found were Omicron BA.2 (99%), harboring six known <i>N</i> mutations (P13L, E31del, S33del, R203K, G204R and S413R). Eight samples containing hybrid variants (XBB.1*, XBB.2 and XBJ) were detected by the study RAT. This RAT detects all Omicron sublineages known to be circulating in Thailand. These results confirmed the good performance of the study RAT for detecting Omicron variants and its appropriateness for individual diagnosis and for genomic surveillance.
DOI: 10.6084/m9.figshare.23612612
title: Protecting human health and the environment against siloxanes: The role and effectiveness of wastewater treatment technologies

description: Since they were first synthesized in 1940, siloxanes have been widely exploited by the cosmetic, construction, pharmaceutical, and food industries. Global siloxane production has grown steadily throughout the decades and now exceeds 10 million tons per year. This production growth has resulted in greater environmental spillover, whose adverse impacts are still being studied. Yet, a growing body of reports, government policies, and scientific investigations agree that volatile organic silicon compounds are some of the most noxious forms of siloxane chemistry. Environmental remediation of siloxanes is challenging; therefore, it is strategically advantageous to intercept and treat siloxanes before they reach the environment. Wastewater treatment plants are a primary collection point for siloxanes that originate from the residential sector, where siloxane products are consumed and rinsed away in copious quantities (e.g. cosmetics and personal care products). However, conventional wastewater treatment often cannot entirely remove siloxanes, which means a substantial portion still reaches the environment. There are advanced treatment technologies that target siloxanes (e.g. physical/chemical absorption and membrane separation); however, these technologies substantially increase the treatment cost. Therefore, researchers are pursuing other siloxane treatment strategies, including new biological approaches. This review provides a fresh look at the history, societal importance, and environmental impacts of siloxanes and the methods used to treat them. The review calls upon a wide array of research to compare and critically evaluate these treatment strategies – old and new – using basic concepts of sustainability as criteria.
DOI: 10.6084/m9.figshare.23612612.v1
title: Protecting human health and the environment against siloxanes: The role and effectiveness of wastewater treatment technologies

description: Since they were first synthesized in 1940, siloxanes have been widely exploited by the cosmetic, construction, pharmaceutical, and food industries. Global siloxane production has grown steadily throughout the decades and now exceeds 10 million tons per year. This production growth has resulted in greater environmental spillover, whose adverse impacts are still being studied. Yet, a growing body of reports, government policies, and scientific investigations agree that volatile organic silicon compounds are some of the most noxious forms of siloxane chemistry. Environmental remediation of siloxanes is challenging; therefore, it is strategically advantageous to intercept and treat siloxanes before they reach the environment. Wastewater treatment plants are a primary collection point for siloxanes that originate from the residential sector, where siloxane products are consumed and rinsed away in copious quantities (e.g. cosmetics and personal care products). However, conventional wastewater treatment often cannot entirely remove siloxanes, which means a substantial portion still reaches the environment. There are advanced treatment technologies that target siloxanes (e.g. physical/chemical absorption and membrane separation); however, these technologies substantially increase the treatment cost. Therefore, researchers are pursuing other siloxane treatment strategies, including new biological approaches. This review provides a fresh look at the history, societal importance, and environmental impacts of siloxanes and the methods used to treat them. The review calls upon a wide array of research to compare and critically evaluate these treatment strategies – old and new – using basic concepts of sustainability as criteria.
DOI: 10.6084/m9.figshare.24845739
title: Proton stress - Supplementary Material

description: Supplementary Tables to Thesis Aart Reinier Egas. Chapter 3.
DOI: 10.6084/m9.figshare.24845739.v2
title: Proton stress - Supplementary Material

description: Supplementary Tables to Thesis Aart Reinier Egas. Chapter 3.
DOI: 10.6084/m9.figshare.24845739.v1
title: Proton stress - Supplementary Material

description: Supplementary Tables to Thesis Aart Reinier Egas. Chapter 3.
DOI: 10.5281/zenodo.10400988
title: Python files from representing data graphically
DOI: 10.5281/zenodo.10400989
title: Python files from representing data graphically
DOI: 10.12770/ef7b1eb5-c088-4fb0-929c-8400dd952c40
title: CATDS-CEC-TB SMOS level4 SMAP compatible brightness temperatures

description: The SMOS Level-4 SMAP Compatible Brightness Temperatures (BT) product provides an unbiased version of the SMOS Level-3 BT with respect to the SMAP Enhanced Level-3 BT. This data set is self-sufficient but it can also be used along with the SMAP Level-3 Enhanced BT for applications for which spatial coverage and revisit frequency of the BT measurements are essentials.
DOI: 10.12763/i5ed78/w8tvuq
title: summary.tab

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DOI: 10.12763/i5ed78/hesso9
title: fails.tab

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DOI: 10.12763/i5ed78/nqnd2e
title: hparams.yaml

description: :unav
DOI: 10.12763/i5ed78/vhfptl
title: events.out.tfevents.1678584877.marquerpc.loria.fr

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DOI: 10.12763/i5ed78/zencwk
title: events.out.tfevents.1678571837.marquerpc.loria.fr

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DOI: 10.12763/i5ed78/ecikiy
title: ret-2019-arabic-b512-epoch=48.ckpt

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DOI: 10.12763/i5ed78/ewqumq
title: events.out.tfevents.1678587006.marquerpc.loria.fr

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title: events.out.tfevents.1678584462.marquerpc.loria.fr

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DOI: 10.12763/i5ed78/r5xqsz
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DOI: 10.12763/i5ed78/fhlecs
title: hparams.yaml

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DOI: 10.12763/i5ed78/qkujq6
title: ret-2019-hebrew-b512-epoch=47.ckpt

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DOI: 10.12763/i5ed78/tgup33
title: events.out.tfevents.1678592593.marquerpc.loria.fr

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title: events.out.tfevents.1678587993.marquerpc.loria.fr

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title: fails.tab

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DOI: 10.12763/i5ed78/ffpk0s
title: events.out.tfevents.1678579163.marquerpc.loria.fr

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DOI: 10.12763/i5ed78/uznp6l
title: summary.tab

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DOI: 10.12763/i5ed78/mkmpj8
title: hparams.yaml

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DOI: 10.12763/i5ed78/gibpzs
title: summary.tab

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DOI: 10.12763/i5ed78/9h16vi
title: ret-2019-zulu-b512-epoch=49.ckpt

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DOI: 10.12763/i5ed78/ctdak6
title: events.out.tfevents.1678574833.marquerpc.loria.fr

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DOI: 10.12763/i5ed78/drf6ys
title: ret-2019-zulu-b512-epoch=46.ckpt

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DOI: 10.12763/i5ed78/nmjs2u
title: hparams.yaml

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DOI: 10.12763/i5ed78/40bgfi
title: ret-2019-hebrew-b512-epoch=46.ckpt

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DOI: 10.12763/i5ed78/cs9ij6
title: fails.tab

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DOI: 10.12763/i5ed78/quj46f
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title: events.out.tfevents.1678583966.marquerpc.loria.fr

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title: hparams.yaml

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title: events.out.tfevents.1678560976.marquerpc.loria.fr

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DOI: 10.12763/i5ed78/8uj9m1
title: ret-2016-georgian-b512-epoch=30.ckpt

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DOI: 10.12763/i5ed78/vxisdt
title: ret-2019-arabic-b512-epoch=49.ckpt

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DOI: 10.12763/i5ed78/rq3m4h
title: events.out.tfevents.1678560687.marquerpc.loria.fr

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DOI: 10.12763/i5ed78/macr7p
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DOI: 10.12763/i5ed78/0qowre
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title: ret-2019-welsh-b512-epoch=49.ckpt

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DOI: 10.12763/i5ed78/pcgmm6
title: hparams.yaml

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title: summary.tab

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title: events.out.tfevents.1678561197.marquerpc.loria.fr

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DOI: 10.12763/i5ed78/zkxlcs
title: ret-2019-french-b512-epoch=47.ckpt

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DOI: 10.12763/i5ed78/sm4mfb
title: ret-2016-turkish-b512-epoch=31.ckpt

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DOI: 10.12763/i5ed78/ux4mbc
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DOI: 10.12763/i5ed78/mehma4
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DOI: 10.12763/i5ed78/ivohxe
title: ret-2019-bashkir-b512-epoch=07.ckpt

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title: summary.tab

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title: summary.tab

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DOI: 10.12763/i5ed78/8dnljs
title: ret-2019-sanskrit-b512-epoch=49.ckpt

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title: summary.tab

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title: fails.tab

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DOI: 10.12763/i5ed78/wdivb1
title: ret-2019-french-b512-epoch=49.ckpt

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DOI: 10.12763/i5ed78/unyzoo
title: ret-2019-slovene-b512-epoch=42.ckpt

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DOI: 10.12763/i5ed78/hkmh9l
title: summary.tab

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title: fails.tab

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DOI: 10.12763/i5ed78/xhk6ac
title: ret-2019-zulu-b512-epoch=48.ckpt

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DOI: 10.12763/i5ed78/pktbs6
title: hparams.yaml

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DOI: 10.12763/i5ed78/rbpxyw
title: ret-2019-slovene-b512-epoch=48.ckpt

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title: summary.tab

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DOI: 10.12763/i5ed78/ormnyq
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DOI: 10.12763/i5ed78/jrlvvn
title: events.out.tfevents.1678574657.marquerpc.loria.fr

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DOI: 10.12763/i5ed78/xet8l3
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DOI: 10.12763/i5ed78/emzht1
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DOI: 10.12763/i5ed78/27bhmd
title: summary.tab

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DOI: 10.12763/i5ed78/b9etk3
title: fails.tab

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DOI: 10.12763/i5ed78/bbfmec
title: ret-2019-french-b512-epoch=45.ckpt

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