cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5517/ccdc.csd.cc1zv21y
title: CCDC 1842300: Experimental Crystal Structure Determination

description: Related Article: Bo Lu, Yujian Zhang, Xiaogang Yang, Kai Wang, Bo Zou, Dongpeng Yan|2018|J.Mater.Chem.C|6|9660|doi:10.1039/C8TC02444H
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: 10.17632/8zf5rf4g6y.4
title: Data for: Tactical Asset Allocation on technical trading rules and Data Snooping

description: This file contains monthly stock indices from 1990/12 to 2017/12: SET, KOSPI, FTSE STI , SENSEX30, Nikkei225, JKSE, KLCI, PSI, SCI, S&P500,HSI, and also the risk-free rate.
DOI: 10.17632/hdwxbdmhx6.1
title: Data for Figures 4 B, C, D, E, F
DOI: 10.17632/k78ct68ypn.1
title: Data for Figures 5 A, C, D, E
DOI: 10.17632/s742krhzmy.1
title: Data for Figures 6 B, D, E, F, G
DOI: 10.5517/ccdc.csd.cc1kx6l8
title: CCDC 1457080: Experimental Crystal Structure Determination

description: Related Article: Xiangyu Zhao, Dawei Yang, Yahui Zhang, Baomin Wang, Jingping Qu|2018|Chem.Commun.|54|11112|doi:10.1039/C8CC05738A
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.cc1kx6m9
title: CCDC 1457081: Experimental Crystal Structure Determination

description: Related Article: Xiangyu Zhao, Dawei Yang, Yahui Zhang, Baomin Wang, Jingping Qu|2018|Chem.Commun.|54|11112|doi:10.1039/C8CC05738A
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.cc1pfm2t
title: CCDC 1562216: Experimental Crystal Structure Determination

description: Related Article: Qinghua Wei, Xiaochu Ma, Jianghui Chen, Li Niu, Xi Yang, Fei Xia, Shunying Liu|2018|Org.Chem.Front.|5|2799|doi:10.1039/C8QO00703A
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.cc1pg36g
title: CCDC 1562685: Experimental Crystal Structure Determination

description: Related Article: Jiaqiong Sun, Guangfan Zheng, Yongmei Fu, Lihong Wang, Yan Li, Qian Zhang|2018|Org.Lett.|20|5597|doi:10.1021/acs.orglett.8b02272
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.cc1pndc3
title: CCDC 1568735: Experimental Crystal Structure Determination

description: Related Article: Xiao-Na Wu, Zhi-Hao You, Yan-Kai Liu|2018|Org.Biomol.Chem.|16|6507|doi:10.1039/C8OB01743C
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.cc1pndg6
title: CCDC 1568738: Experimental Crystal Structure Determination

description: Related Article: Xiao-Na Wu, Zhi-Hao You, Yan-Kai Liu|2018|Org.Biomol.Chem.|16|6507|doi:10.1039/C8OB01743C
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.cc1q4ndx
title: CCDC 1583399: Experimental Crystal Structure Determination

description: Related Article: Xiangyu Zhao, Dawei Yang, Yahui Zhang, Baomin Wang, Jingping Qu|2018|Chem.Commun.|54|11112|doi:10.1039/C8CC05738A
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.cc1zv22z
title: CCDC 1842301: Experimental Crystal Structure Determination

description: Related Article: Bo Lu, Yujian Zhang, Xiaogang Yang, Kai Wang, Bo Zou, Dongpeng Yan|2018|J.Mater.Chem.C|6|9660|doi:10.1039/C8TC02444H
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.cc1zvp2l
title: CCDC 1842890: Experimental Crystal Structure Determination

description: Related Article: Dong Zhang, Lili Lin, Jian Yang, Xiaohua Liu, Xiaoming Feng|2018|Angew.Chem.,Int.Ed.|57|12323|doi:10.1002/anie.201806630
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.cc1zvzh9
title: CCDC 1843182: Experimental Crystal Structure Determination

description: Related Article: Wei-Jun Kong, Qian Shao, Ming-Hong Li, Zeng-Le Zhou, Hui Xu, Hui-Xiong Dai, Jin-Quan Yu|2018|Organometallics|37|2832|doi:10.1021/acs.organomet.8b00457
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.cc1zw679
title: CCDC 1843391: Experimental Crystal Structure Determination

description: Related Article: Dong Zhang, Lili Lin, Jian Yang, Xiaohua Liu, Xiaoming Feng|2018|Angew.Chem.,Int.Ed.|57|12323|doi:10.1002/anie.201806630
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.cc1zwz50
title: CCDC 1844133: Experimental Crystal Structure Determination

description: Related Article: Ana Belén Ruiz-Muelle, Amalia García-García, Antonio A. García-Valdivia, Itziar Oyarzabal, Javier Cepeda, José M. Seco, Enrique Colacio, Antonio Rodríguez-Diéguez, Ignacio Fernández|2018|Dalton Trans.|47|12783|doi:10.1039/C8DT02592D
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.cc2097cy
title: CCDC 1855919: Experimental Crystal Structure Determination

description: Related Article: Ting Li, Huiyan Wang, Pengcheng Qian, Yuhan Yang, Bo Li, Liming Zhang|2018|Chem.Commun.|54|10447|doi:10.1039/C8CC06056H
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: 10.17632/2x7ts7d25m.1
title: Data for Figures 3 A, C, D

description: G- growth affects cell fate choice due to changes in cell cycle dynamics A. G- cells have a longer G2 phase. S and G2 phase lengths were determined from PCNA localization (Muramoto and Chubb, 2008). Only total cell cycle length and G2 phase length of G- grown cells are significantly longer. C. G- cells are biased towards prestalk cell fate. The percentage of prestalk and prespore cells was significantly different in G+ and G- cells in the low-density differentiation assay (t-test; p=5.5 x 10-8, p=6 x 10-7, p=3 x 10-7). D. Stalk cell propensity increases in G- cells with a longer than average cell cycle length Percentages of prespore and prestalk cells were plotted for G+ cells (solid line, see Figure 2D) and G- cells (dashed line) at different cell cycle positions. G- cells with a longer than average cell cycle (&gt;8 hours) showed a much higher propensity to differentiate into prestalk cells.
DOI: 10.17632/3b9p4cv7z9.1
title: Read counts and analyses for datasets from wild type and gefE- cells grown in G+ and G- media
DOI: 10.17632/gg6zz53rhj.1
title: Data for Figures 2 B, C, D
DOI: 10.17632/jxw2cmh8kp.1
title: A nuclear export block triggers the decay of newly synthesized polyadenylated RNA

description: A nuclear export block triggers the decay of newly synthesized polyadenylated RNA Agnieszka Tudek1, Manfred Schmid1, Marius Makaras1, J. David Barrass2, Jean D. Beggs2, Torben Heick Jensen1* 1Department of Molecular Biology and Genetics, Aarhus University, C. F. Møllers Allé 3, building 1130, 8000 Aarhus C, Denmark, 2Wellcome Centre for Cell Biology, University of Edinburgh, Edinburgh EH9 3BF, UK *corresponding author and lead contact: thj@mbg.au.dk Keywords: nuclear export of pA+ RNA, nuclear degradation of pA+ RNA, Mex67p, Nab2p, transcription. ABSTRACT Genomes are promiscuously transcribed necessitating mechanisms that facilitate the sorting of RNA for function or destruction. The polyA (pA) tail is one such distinguishing feature, which in the Saccharomyces cerevisiae nucleus is bound by the Nab2p protein, yielding transcript protection. As Nab2p also contacts the main nuclear export factor Mex67p, we asked whether transport kinetics contributes to RNA sorting. Indeed, 3’end sequencing of newly transcribed pA+ RNAs demonstrates that nuclear depletion of Mex67p elicits their instant and global decay. A similar phenotype is evident upon inactivation of other export factors and proportional to the amount of nuclear pA+ RNA. As RNA expression is partially rescued by Nab2p over-expression, we propose that an export-block out-titrates Nab2p onto nuclear retained pA+ RNA, reducing the pool of Nab2p available to protect new transcripts. More generally, we suggest that nuclear RNA decay, negotiated by Nab2p availability, aids in balancing cellular transcript supply with demand.
DOI: 10.17632/jy4wrgpzyr.1
title: Read counts and analyses of the cell cycle data from (Strasser et al., 2012)
DOI: 10.17632/pwcvkwtjpb.1
title: Counts and analyses for single cell data
DOI: 10.17632/t4yn9tfrhw.1
title: Data for Figure 1 E and F
DOI: 10.17632/wv2yhwn4dp.1
title: Data for: Effect of microstructural refinement and intercritical annealing time on mechanical properties of high-formability dual phase steel

description: Effect of microstructural refinement and intercritical annealing time on mechanical properties of high-formability dual phase steel
DOI: 10.5517/ccdc.csd.cc1q2njz
title: CCDC 1581481: Experimental Crystal Structure Determination

description: Related Article: Oliver Linnenberg, Lisa Mayerl, Kirill Yu. Monakhov|2018|Dalton Trans.|47|14402|doi:10.1039/C8DT02340A
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.cc1q2nk0
title: CCDC 1581482: Experimental Crystal Structure Determination

description: Related Article: Oliver Linnenberg, Lisa Mayerl, Kirill Yu. Monakhov|2018|Dalton Trans.|47|14402|doi:10.1039/C8DT02340A
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.cc1q2nl1
title: CCDC 1581483: Experimental Crystal Structure Determination

description: Related Article: Oliver Linnenberg, Lisa Mayerl, Kirill Yu. Monakhov|2018|Dalton Trans.|47|14402|doi:10.1039/C8DT02340A
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.cc1yymr8
title: CCDC 1815941: Experimental Crystal Structure Determination

description: Related Article: Linh Pham, Khalil A. Abboud, Wolfgang Wernsdorfer, George Christou|2018|Polyhedron|155|34|doi:10.1016/j.poly.2018.07.007
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.cc1yyms9
title: CCDC 1815942: Experimental Crystal Structure Determination

description: Related Article: Linh Pham, Khalil A. Abboud, Wolfgang Wernsdorfer, George Christou|2018|Polyhedron|155|34|doi:10.1016/j.poly.2018.07.007
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.cc1yz3gh
title: CCDC 1816397: Experimental Crystal Structure Determination

description: Related Article: Lei Zhou, Baolei Zhou, Zheng Cui, Bowen Qin, Xiaoying Zhang, Wenliang Li, Jingping Zhang|2018|CrystEngComm|20|5402|doi:10.1039/C8CE00997J
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.cc1yz3hj
title: CCDC 1816398: Experimental Crystal Structure Determination

description: Related Article: Lei Zhou, Baolei Zhou, Zheng Cui, Bowen Qin, Xiaoying Zhang, Wenliang Li, Jingping Zhang|2018|CrystEngComm|20|5402|doi:10.1039/C8CE00997J
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: 10.17632/2f8p4ypdjn.1
title: Teachers ICT adoption in schools

description: A survey with 103 respondents (teachers in elementary school, i.e. pupils in the age: 6-16). The survey includes: Demographics (gender, age, teaching experience). Questions about attitudes of using ICT in school (based on TAM2 and UTAUT model ). Questions about actual use of ICT, e.g. "how often do you arrange teaching in such a way that students use ICT to collaborate during the lecture?") The design of the model was inspired by TAM2 and UTAUT models. A conceptual model is based on a suggested model which highlight the pedagogical aspects beyond the technical ones. The model also includes the adoption of digital techniques in everyday life as a potential predictor of adoption of ICT at work. The sample consists of 103 teachers. This study contributes with a suggested model including a new construct for measuring expected performance from a technological pedagogical point of view. This new construct was a significant predictor to actual use of ICT in school. Furthermore the newnew construct for adoption of ICT in everyday life was also a significant predictor to actual use of ICT.
DOI: 10.17632/436m8s3bpm.2
title: Mesocosm electromotive potential and pore network data

description: Summary of findings: We found that volume-based XCT-metrics were more frequently correlated with metrics describing changes in available energy than medial-axis XCT-metrics. Abundance of significant correlations between pore network metrics and available energy parameters was not only a function of pore architecture, but also of the dimensions of the sub-sample chosen for XCT analysis. Pore network metrics had the greatest power to statistically explain changes in available energy in the smallest volumes analyzed. Our work underscores the importance of scale in observations of natural systems. Two major objectives: 1.) Constrain the size of the soil volume that is "seen" by the tip of a Pt electrode 2.) Find quantitative, numerical indices of soil structure that can be used to test assumptions about causality regarding soil structure - redox state relationships Hypotheses: H1: Electromotive potentials sensed by platinum electrodes respond to changes in water saturation level in a predictable, non-random fashion. We hypothesize that for all electrodes probing the same network architecture type (i.e. sieving treatment), the associated metrics to characterize the available energy of reactions involving electron transfer (AE, parameterized as ΔEPt per time interval and expressed as fraction (%) of the free energy released by the oxidation of CH2O with O2) is more or less constant H2: The ability of XCT-derived pore network metrics to predict AE-metrics improves with decreasing average pore size, or ΔEPt,(a...j) = f(PNA), (PNM 1....18), where PNA = pore network architecture, (a...j) are a set of available energy metrics, and (1...18) is a set of pore network metrics H3: The ability of XCT-derived pore network metrics to predict AE-metrics improves when the volume of the observed pore network is small and immediately surrounds the platinum electrode tip, compared to larger soil volumes or 'the power of XCT derived network metrics to predict change in redox state = f(VoI) H4: AE-metrics are specific to pore network architectures. When subjected to the same moisture changes in AE-metrics should be significantly different between pore network architectures. This hypothesis can be accepted if ΔEPt per time interval ≠ΔEPt between pore network types Electromotive potential curve vs. Pore metrics: Electromotive potential data compared against pore network data derived from XCT measurements of the soil pore network within 9 mesocosms. Relative EPt calculation: Relationship derived to convert electromotive potential data (for each major terminal electron acceptor in soil systems) to energy available on a per electron transferred basis (= available energy) in kJ. Greenhouse electromotive potentials: Electromotive potential data collected from 27 Pt electrodes installed in 9 PVC mesocosms filled with soil from a Mollisol A horizon (Woodburn series).
DOI: 10.17632/5rxcvrsxtn.2
title: Nuclear PGK1 alleviates ADP-dependent inhibition of CDC7 to promote DNA replication

description: Unprocessed data.
DOI: 10.17632/8wznn46d43.2
title: Accurate Drug Reposition through Non-Tissue Specific Core Signatures from Cancer Transcriptomes

description: We used TCGA cancer transcriptomes to generate non-tissue specific core signatures (CSs) of human coding gene mutaitons. Then we used the CSs to scan Connectivity Map (CMap) drug profiles to generate d2gNES and d2gCSI values. A positive d2gNES indicates a drug treatment profile is with the same expression direction of a gene mutation, and a negative d2gNES indicates the opposite direction to a gene mutation. The d2gCSI ranges from 0 to 1, indicating the specificity of a drug targeting a gene.
DOI: 10.17632/bch6yb6j63.1
title: Data for: Environmental impact indicators for the electricity mix and network development planning towards 2050 - a POLES and EUTGRID model

description: Data for: Environmental impact indicators for the electricity mix and network development planning towards 2050 - a POLES and EUTGRID model. Available regionalised database for environmental impact of current and prospective technology based on NEEDS. The data is provided as an Excel file and csv file. Further, the CBA data using a multi-criteria analysis tool (SMAA) is made available using the jsmaa software (http://smaa.fi/jsmaa/) and associated files. The emissions data are already characterised using the ReCiPe characterisation method and results are given in kg/kWh.
DOI: 10.17632/jp5fztws54.1
title: Accelerated aging of a glass fiber/polyurethane composite for automotive applications

description: Data from Dynamic-Mechanical and Three-Point-Bending flexural tests of virgin and aged specimens.
DOI: 10.17632/ngvvjwmv7f.1
title: CHASMplus reveals the scope of somatic missense mutations driving human cancers

description: Raw Data for Jupyter notebook analysis. Notebooks available here: https://github.com/KarchinLab/Tokheim_2018
DOI: 10.17632/pmcxb56t63.2
title: Adaptive Monitoring: A systematic Mapping - Studies RQs data

description: This data corresponds to the information extracted from the studies of a systematic mapping in the adaptive monitoring topic, used for answering the research questions of the review. Data is grouped by study (or resource) and by approach.
DOI: 10.17632/rtyrnscyrh.1
title: Data for: "Network analysis of Contingencies of Self-Worth Scale in 680 university students"

description: The data and code allow for reproducibility of the paper: "Network analysis of Contingencies of Self-Worth Scale in 680 university students".
DOI: 10.17632/zdmb4d9f8k.2
title: Raw Data

description: This file contains the raw data to simulate the macro and micro scale behaviors of polycrystalline materials. First, the related parameters to the macro domain are found. Second, the microscale parameters, including different numbers of grains, are included.