cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5517/ccdc.csd.cc29w9n5
title: CCDC 2141407: Experimental Crystal Structure Determination

description: Related Article: Juliana G. Pereira, João M. J. M. Ravasco, João R. Vale, Fausto Queda, Rafael F. A. Gomes|2022|Green Chemistry|24|7131|doi:10.1039/D2GC00253A
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.cc29xf7x
title: CCDC 2142479: Experimental Crystal Structure Determination

description: Related Article: Jiaoyang Gao, Jinjia Guo, Yi Chen, Shunlan Deng, Qidong Lu, Yuxin Ren, Xiaoming Wang, Haibo Fan, Feng Teng, Xuexia He, Hui Jiang, Peng Hu|2022|CrystEngComm|24|6429|doi:10.1039/D2CE00925K
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.cc29ysmp
title: CCDC 2143793: Experimental Crystal Structure Determination

description: Related Article: Xiao-Lin Liu, Xiao-Yi Zhang, Hai-Xia Zhao, La-Sheng Long, Lan-Sun Zheng|2022|Dalton Trans.|51|13826|doi:10.1039/D2DT01980A
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.cc29yt14
title: CCDC 2143806: Experimental Crystal Structure Determination

description: Related Article: Xiao-Lin Liu, Xiao-Yi Zhang, Hai-Xia Zhao, La-Sheng Long, Lan-Sun Zheng|2022|Dalton Trans.|51|13826|doi:10.1039/D2DT01980A
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.cc29yxz5
title: CCDC 2143928: Experimental Crystal Structure Determination

description: Related Article: Yun-Shan Xue, Dan-Ling Sun, Jun-Qing Lv, Shi-Juan Li, Xuan-Rong Chen, Wei-Wei Cheng, Hong-Xiu Wu, Jun Wang|2022|CrystEngComm|24|6376|doi:10.1039/D2CE00631F
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.cc29yy07
title: CCDC 2143929: Experimental Crystal Structure Determination

description: Related Article: Yun-Shan Xue, Dan-Ling Sun, Jun-Qing Lv, Shi-Juan Li, Xuan-Rong Chen, Wei-Wei Cheng, Hong-Xiu Wu, Jun Wang|2022|CrystEngComm|24|6376|doi:10.1039/D2CE00631F
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.cc2b05xg
title: CCDC 2145135: Experimental Crystal Structure Determination

description: Related Article: David Schallenberg, Nils Pardemann, Alexander Villinger, Wolfram W. Seidel|2022|Dalton Trans.|51|13681|doi:10.1039/D2DT00410K
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.cc2b05yh
title: CCDC 2145136: Experimental Crystal Structure Determination

description: Related Article: David Schallenberg, Nils Pardemann, Alexander Villinger, Wolfram W. Seidel|2022|Dalton Trans.|51|13681|doi:10.1039/D2DT00410K
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.cc2b05zj
title: CCDC 2145137: Experimental Crystal Structure Determination

description: Related Article: David Schallenberg, Nils Pardemann, Alexander Villinger, Wolfram W. Seidel|2022|Dalton Trans.|51|13681|doi:10.1039/D2DT00410K
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.cc2b060l
title: CCDC 2145138: Experimental Crystal Structure Determination

description: Related Article: David Schallenberg, Nils Pardemann, Alexander Villinger, Wolfram W. Seidel|2022|Dalton Trans.|51|13681|doi:10.1039/D2DT00410K
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.cc2b061m
title: CCDC 2145139: Experimental Crystal Structure Determination

description: Related Article: David Schallenberg, Nils Pardemann, Alexander Villinger, Wolfram W. Seidel|2022|Dalton Trans.|51|13681|doi:10.1039/D2DT00410K
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.cc2b062n
title: CCDC 2145140: Experimental Crystal Structure Determination

description: Related Article: David Schallenberg, Nils Pardemann, Alexander Villinger, Wolfram W. Seidel|2022|Dalton Trans.|51|13681|doi:10.1039/D2DT00410K
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.cc2b063p
title: CCDC 2145141: Experimental Crystal Structure Determination

description: Related Article: David Schallenberg, Nils Pardemann, Alexander Villinger, Wolfram W. Seidel|2022|Dalton Trans.|51|13681|doi:10.1039/D2DT00410K
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.cc2b064q
title: CCDC 2145142: Experimental Crystal Structure Determination

description: Related Article: David Schallenberg, Nils Pardemann, Alexander Villinger, Wolfram W. Seidel|2022|Dalton Trans.|51|13681|doi:10.1039/D2DT00410K
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.cc2b0nxy
title: CCDC 2145600: Experimental Crystal Structure Determination

description: Related Article: Elena Gascón, Isabel Otal, Sara Maisanaba, María Llana-Ruiz-Cabello, Eva Valero, Guillermo Repetto, Peter G. Jones, Luis Oriol, Josefina Jiménez|2022|Dalton Trans.|51|13657|doi:10.1039/D2DT01963A
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.cc2b6g56
title: CCDC 2151157: Experimental Crystal Structure Determination

description: Related Article: Gleb V. Morozkov, Anton S. Abel, Mikhail A. Filatov, Sergey E Nefedov, Vitaly Alexandrovich Roznyatovsky, Andrei Vladimirovich Cheprakov, Alexander Yu. Mitrofanov, Ilia S. Ziankou, Alexei Averin, Irina P Beletskaya, Julien Michalak, Christophe Bucher, Laurent Bonneviot, Alla Bessmertnykh-Lemeune|2022|Dalton Trans.|51|13612|doi:10.1039/D2DT01364A
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.cc2b71pb
title: CCDC 2151731: Experimental Crystal Structure Determination

description: Related Article: Yu-Qi Miao, Xin-Ying Li, Qiao-Jing Pan, Yubin Ma, Jia-Xin Kang, Yan-Na Ma, Zhenxing Liu, Xuenian Chen|2022|Green Chemistry|24|7113|doi:10.1039/D2GC02313J
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.cc2b71qc
title: CCDC 2151732: Experimental Crystal Structure Determination

description: Related Article: Yu-Qi Miao, Xin-Ying Li, Qiao-Jing Pan, Yubin Ma, Jia-Xin Kang, Yan-Na Ma, Zhenxing Liu, Xuenian Chen|2022|Green Chemistry|24|7113|doi:10.1039/D2GC02313J
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.cc2b71rd
title: CCDC 2151733: Experimental Crystal Structure Determination

description: Related Article: Yu-Qi Miao, Xin-Ying Li, Qiao-Jing Pan, Yubin Ma, Jia-Xin Kang, Yan-Na Ma, Zhenxing Liu, Xuenian Chen|2022|Green Chemistry|24|7113|doi:10.1039/D2GC02313J
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: 10.34740/kaggle/dsv/4228817
title: Mahanagar Yatayat Dataset
DOI: 10.6084/m9.figshare.19650798
title: Devaluation of NoGo stimuli is both robust and fragile

description: Consistently not responding to stimuli during go/no-go training leads to lower evaluations of these NoGo stimuli. How this NoGo-devaluation-effect can be explained has remained unclear. Here, we ran three experiments to test the hypothesis that people form stimulus-stop-associations during the training, which predict the strength of the devaluation-effect. In Experiment 1, we tried to simultaneously measure the stimulus-stop-associations and NoGo-devaluation, but we failed to find these effects. In Experiment 2, we measured NoGo-devaluation with established procedures from previous work, and stimulus-stop-associations with a novel separate task. Results revealed a clear NoGo-devaluation-effect, which remained visible across multiple rating blocks. Interestingly, this devaluation-effect disappeared when stimulus-stop-associations were measured before stimulus evaluations, and there was no evidence supporting the formation of the stimulus-stop-associations. In Experiment 3, we found evidence for the acquisition of stimulus-stop-associations using an established task from previous work, but this time we found no subsequent NoGo-devaluation-effect. The present research suggests that the NoGo-devaluation-effect and stimulus-stop-associations can be found with standard established procedures, but that these effects are very sensitive to alterations of the experimental protocol. Furthermore, we failed to find evidence for both effects within the same experimental protocol, which has important theoretical and applied implications.
DOI: 10.6084/m9.figshare.19650798.v1
title: Devaluation of NoGo stimuli is both robust and fragile

description: Consistently not responding to stimuli during go/no-go training leads to lower evaluations of these NoGo stimuli. How this NoGo-devaluation-effect can be explained has remained unclear. Here, we ran three experiments to test the hypothesis that people form stimulus-stop-associations during the training, which predict the strength of the devaluation-effect. In Experiment 1, we tried to simultaneously measure the stimulus-stop-associations and NoGo-devaluation, but we failed to find these effects. In Experiment 2, we measured NoGo-devaluation with established procedures from previous work, and stimulus-stop-associations with a novel separate task. Results revealed a clear NoGo-devaluation-effect, which remained visible across multiple rating blocks. Interestingly, this devaluation-effect disappeared when stimulus-stop-associations were measured before stimulus evaluations, and there was no evidence supporting the formation of the stimulus-stop-associations. In Experiment 3, we found evidence for the acquisition of stimulus-stop-associations using an established task from previous work, but this time we found no subsequent NoGo-devaluation-effect. The present research suggests that the NoGo-devaluation-effect and stimulus-stop-associations can be found with standard established procedures, but that these effects are very sensitive to alterations of the experimental protocol. Furthermore, we failed to find evidence for both effects within the same experimental protocol, which has important theoretical and applied implications.
DOI: 10.6084/m9.figshare.21166618
title: Multiples lines of evidence unveil cryptic diversity in the <i>Lophostoma brasiliense</i> (Chiroptera: Phyllostomidae) complex

description: Phenotypically similar species – often called cryptic species – represent a challenge for taxonomy and conservation biology because they are usually undetectable to scientists. To unravel these cryptic taxa, studies now employ data from different sources under an integrative approach. We present an assessment of the cryptic diversity of the <i>Lophostoma brasiliense</i> species complex (Chiroptera: Phyllostomidae) based on multiple lines of evidence (molecular, morphological, morphometric, and geographic data) and using molecular (ABGD, ASAP, GMYC, and bPTP) and phenotypic (distance-based approaches and Normal Mixture Model Analyses) species delimitation methods. Our analyses recognized two distinct lineages with clear allopatric distributions. One lineage corresponds to <i>Lophostoma brasiliense</i> with a cis-Andean distribution and the other to the formerly species <i>Lophostoma nicaraguae</i> with a trans-Andean distribution. The two lineages probably diverged from a vicariant speciation driven by the uplift of the Andes less than six million years ago. Our work also shows that the wide range of environmental conditions during the recent history of South America may have promoted restrictions to gene flow among the populations of <i>Lophostoma brasiliense</i>. Finally, we raised <i>L. nicaraguae</i> to species level clarifying the species limit and morphological characteristics of lineages, and we provide an emended diagnosis and comparisons between the two taxa. We highlight the need for multiple lines of evidence to solve the remaining taxonomic problems among the remaining species complexes in <i>Lophostoma</i>.
DOI: 10.6084/m9.figshare.21166618.v1
title: Multiples lines of evidence unveil cryptic diversity in the <i>Lophostoma brasiliense</i> (Chiroptera: Phyllostomidae) complex

description: Phenotypically similar species – often called cryptic species – represent a challenge for taxonomy and conservation biology because they are usually undetectable to scientists. To unravel these cryptic taxa, studies now employ data from different sources under an integrative approach. We present an assessment of the cryptic diversity of the <i>Lophostoma brasiliense</i> species complex (Chiroptera: Phyllostomidae) based on multiple lines of evidence (molecular, morphological, morphometric, and geographic data) and using molecular (ABGD, ASAP, GMYC, and bPTP) and phenotypic (distance-based approaches and Normal Mixture Model Analyses) species delimitation methods. Our analyses recognized two distinct lineages with clear allopatric distributions. One lineage corresponds to <i>Lophostoma brasiliense</i> with a cis-Andean distribution and the other to the formerly species <i>Lophostoma nicaraguae</i> with a trans-Andean distribution. The two lineages probably diverged from a vicariant speciation driven by the uplift of the Andes less than six million years ago. Our work also shows that the wide range of environmental conditions during the recent history of South America may have promoted restrictions to gene flow among the populations of <i>Lophostoma brasiliense</i>. Finally, we raised <i>L. nicaraguae</i> to species level clarifying the species limit and morphological characteristics of lineages, and we provide an emended diagnosis and comparisons between the two taxa. We highlight the need for multiple lines of evidence to solve the remaining taxonomic problems among the remaining species complexes in <i>Lophostoma</i>.
DOI: 10.6084/m9.figshare.21165775
title: LITHME WG7's Survey on Machine Translation Use Habits and Practices

description: Working Group 7 of the COST-Action LITHME (Language in the Human-Machine Era, https://lithme.eu/working-groups/wg7/) has carried out a survey among the LITHME network’s membership (around 170 people) about the members’ Machine Translation use. The questionnaire was circulated electronically on the network’s mailing list. LITHME members are academics and researchers who are focusing on the impact that new technologies have on languages and language use. The main objective of the survey was to see their habits and attitudes towards Machine Translation tools and to compare, if possible, the attitudes of qualified language mediators to those of other language experts. The questionnaire was circulated electronically on the network’s mailing list. The<strong> first PDF</strong> contains the questionnaire The <strong>second PDF</strong> contains a summary of the results The <strong>Excel file</strong> contains the answers.
DOI: 10.6084/m9.figshare.20324814.v2
title: EEL mouse sagittal atlas 168 genes RNA spatial data

description: <strong>Raw RNA locations of the mouse atlas produced by EEL FISH for 168 genes.</strong> <br> RNA files are in the .parquet format which can be opened with FISHscale (https://github.com/linnarsson-lab/FISHscale) or any other parquet file reader (https://arrow.apache.org/docs/index.html) <br> <strong>RNA .parquet files</strong> Seven sagittal sections of the mouse brain with 168 detected genes, sampled at the medial-lateral positions of -140 µm, 600 µm, 1200 µm, 1810 µm, 2420 µm, 3000 µm and 3600 µm measured from the midline. <br> Position and gene label for all RNA molecules. <br> "c_px_microscope_stitched" contains X coordinates. "r_px_microscope_stitched" contians Y coordinates. The unit are pixels with a size of 0.18 micrometer. Multiply by 0.18 to get um scale. <br> <strong>Tissue polygons .csv files</strong> CSV files demarking the sample borders for the 7 mouse atlas sections. -140 µm, 600 µm, 1200 µm, 1810 µm, 2420 µm, 3000 µm, 3600 µm <br> <strong>Gene colors .pkl file</strong> Pickled Python dictionary with gene colors used in the paper for the mouse atlas.
DOI: 10.5281/zenodo.7097340
title: Forest types in South China

description: We used the annual (2002-2017) forest probability maps from Tong et al (2020) which were also derived from MODIS data. A probability threshold of 0.5 was used to define if an area is a forest or not (Tong et al., 2020). We identified three types of forests (Fig.1): (1) old forests (always forest during 2002-2017), (2) new forests (no forest in 2002 but in 2017), and potential forests (never forested during 2002-2017).
DOI: 10.5281/zenodo.7097339
title: Forest types in South China

description: We used the annual (2002-2017) forest probability maps from Tong et al (2020) which were also derived from MODIS data. A probability threshold of 0.5 was used to define if an area is a forest or not (Tong et al., 2020). We identified three types of forests (Fig.1): (1) old forests (always forest during 2002-2017), (2) new forests (no forest in 2002 but in 2017), and potential forests (never forested during 2002-2017).
DOI: 10.6084/m9.figshare.21166369
title: ciconia_boyciana_zanfona_1.fasta.gz

description: .....
DOI: 10.6084/m9.figshare.21166369.v1
title: ciconia_boyciana_zanfona_1.fasta.gz

description: .....
DOI: 10.5281/zenodo.6075446
title: Small-scale fisheries adaptations understudied in climate change hotspots - database

description: Using a systematic review approach, we identified a global dataset of 301 reported adaptation responses of small-scale fishers to climate change. The adaptations were extracted from academic publications and grey literature (reports and Ph.D. theses) published from 2008 to 2020. The database provides coordinates and/or location, climate change hazard identified as motivating the response, small-scale fisher adaptation response, and any other stressor related to the response.
description: J.G.M. is supported by a Japanese Society for the Promotion of Science (JSPS) KAKENHI Grant Number 19H04322.
DOI: 10.5281/zenodo.6075447
title: Small-scale fisheries adaptations understudied in climate change hotspots - database

description: Using a systematic review approach, we identified a global dataset of 299 reported adaptation responses of small-scale fishers to climate change. The adaptations were extracted from academic publications and grey literature (reports and Ph.D. theses) published from 2008 to 2020. The database provides coordinates and/or location, climate change hazard identified as motivating the response, small-scale fisher adaptation response, and any other stressor related to the response.