cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.25919/5c903bb15c24e
title: Parkes observations for project P885 semester 2018OCTS_11

description: We propose to observe PSR J1622-4950 and 1E1547.0-5408 weekly, two
of three magnetars known to currently emit radio pulsations, to
track their rotation, flux density, and polarisation. Less frequently
we will monitor XTE J1810-197, which used to emit radio pulsations,
to be on the lookout for its revival - as recently happened with PSR
J1622-4950, which turned on in 2017 after more than 2 years dormant!
These observations yield a continuous record of torque, illuminating
the continued release of magnetic energy. Our broader aims are to
develop a better understanding of the dynamical behaviour of magnetar
magnetospheres, and to establish the conditions under which radio
emission takes place therein, in addition to characterising their
variable radio emission in order to place constraints on the emission
mechanisms, which in at least some respects differ from those of
ordinary pulsars.
DOI: 10.25919/5c903cb40dfe8
title: Parkes observations for project P995 semester 2018OCTS_18

description: We propose to perform observations of the very young pulsar PSR B0540–69 in the Large Magellanic Cloud to detect pulsed flux from this traditionally radio-quiet source.  We are motivated to do so due to a relatively recent X-ray observation of a 36% change in its spin down rate, thought to be due to a state change in its magnetospheric processes.  There is reason to believe this may be accompanied by an increase in pulsed flux, as has been seen in intermittent pulsar behaviour, for example.  Additionally, PSR B0540–69 is known to emit giant pulses, one of only a small number of pulsars to do so.  With the new Ultra Wideband Low-frequency (UWL) receiver system, we will be able to conduct the highest sensitivity observations of this source yet achieved at radio wavelengths.  A successful detection of pulsed flux will provide important insight into the magnetospheric evolution and behaviour in this pulsar, and a better understanding of how its glitch behaviour may influence its emission.  Even without such a detection, we will be able to study the giant pulse behaviour of PSR B0540–69 with unprecedented sensitivity.
DOI: 10.6073/pasta/62c2572c1532f68fcaefa5d2607b7fbf
title: Plot vegetation surveys at the Sensor Network, 2017 to ongoing

description: Above-ground plant species cover was recorded for vegetation plots in
  the sensor network, starting in 2017. Vegetation plots are numbered
  with the sensor node and soil moisture probe numbers, separated by a
  “.” Cover was measured at peak biomass using a 100 point-intercept
  method. In 2017, only top-hits were recorded, meaning that only the
  tallest species at each point were counted as a hit. In 2018, data for
  both top-hits only and all-hits were recorded. Species that were not
  hit, but were present in the plot were assigned a value of 0.5 hits.
DOI: 10.6073/pasta/7c77d9b858b2f3cf41edbddeb66b9948
title: Periphyton Productivity from the Shark River Slough and Taylor Slough, Everglades National Park (FCE), from October 2001 to Present

description: Periphyton productivity was measured annually at FCE LTER sites in Florida Bay and Shark Slough using light and dark BOD bottle incubations.  Data are presented in terms of mass oxygen and/or carbon produced/consumed per gram of periphyton and per m2 of marsh.  This is part of continuous data collection to test the hypothesis that phosphorus and nitrogen limit productivity at the upstream and downstream ends, respectively, of the FCE transects.  Conclusions await longer-term data collection.
DOI: 10.17632/v75zjvp6ny.1
title: Data for: Microarray-based data mining reveals key genes and potential therapeutic drugs for Cadmium-induced prostate carcinoma

description: The results of DEGs analyzed from GSE9951 (9 specimens of prostate epithelial cells exposed to cadmium vs 10 controls).
DOI: 10.5281/zenodo.2597528
title: The Halo's Ancient Metal-Rich Progenitor Revealed with BHB Stars

description: This data represent properties of Blue Horizontal Branch stars in the Stellar Halo of the Milky Way with properties derived from the Sloan Digital Sky Survey's Data Release 8, the Gaia Mission's Data Release 2, and the work of Xue et al. 2011.  The contents of this data are described in the README file and the full description of the data reduction can be found at (https://arxiv.org/abs/1807.04290)
DOI: 10.5281/zenodo.2597529
title: The Halo's Ancient Metal-Rich Progenitor Revealed with BHB Stars

description: This data represent properties of Blue Horizontal Branch stars in the Stellar Halo of the Milky Way with properties derived from the Sloan Digital Sky Survey's Data Release 8, the Gaia Mission's Data Release 2, and the work of Xue et al. 2011.  The contents of this data are described in the README file and the full description of the data reduction can be found at (https://arxiv.org/abs/1807.04290)
DOI: 10.5517/ccdc.csd.cc215vsw
title: CCDC 1882468: Experimental Crystal Structure Determination

description: Related Article: Ana Sofia Ortega-Villarreal, Eugenio Hernández-Fernández, Christopher Jensen, Gabriel A. Valdivia-Berroeta, Samuel Garrard, Israel López, Stacey J. Smith, Kenneth A. Christensen, Miguel A. Reyes-González, David J. Michaelis|2019|RSC Advances|9|8759|doi:10.1039/C9RA00108E
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.cc216ksm
title: CCDC 1883150: Experimental Crystal Structure Determination

description: Related Article: Yusen Qiao, Thibault Cheisson, Brian C. Manor, Patrick J. Carroll, Eric J. Schelter|2019|Chem.Commun.|55|4067|doi:10.1039/C9CC00282K
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.cc216ktn
title: CCDC 1883151: Experimental Crystal Structure Determination

description: Related Article: Yusen Qiao, Thibault Cheisson, Brian C. Manor, Patrick J. Carroll, Eric J. Schelter|2019|Chem.Commun.|55|4067|doi:10.1039/C9CC00282K
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.cc216kvp
title: CCDC 1883152: Experimental Crystal Structure Determination

description: Related Article: Yusen Qiao, Thibault Cheisson, Brian C. Manor, Patrick J. Carroll, Eric J. Schelter|2019|Chem.Commun.|55|4067|doi:10.1039/C9CC00282K
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.cc216kwq
title: CCDC 1883153: Experimental Crystal Structure Determination

description: Related Article: Yusen Qiao, Thibault Cheisson, Brian C. Manor, Patrick J. Carroll, Eric J. Schelter|2019|Chem.Commun.|55|4067|doi:10.1039/C9CC00282K
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.cc216q33
title: CCDC 1883284: Experimental Crystal Structure Determination

description: Related Article: Andreas Bernd Schnepf, Sebastian Kenzler, Florian Fetzer, Claudio Schrenk, Nia Pollard, Andrew R. Frojd, Andre Z. Clayborne|2019|Angew.Chem.,Int.Ed.|58|5902|doi:10.1002/anie.201900644
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.cc216q44
title: CCDC 1883285: Experimental Crystal Structure Determination

description: Related Article: Andreas Bernd Schnepf, Sebastian Kenzler, Florian Fetzer, Claudio Schrenk, Nia Pollard, Andrew R. Frojd, Andre Z. Clayborne|2019|Angew.Chem.,Int.Ed.|58|5902|doi:10.1002/anie.201900644
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.cc216q55
title: CCDC 1883286: Experimental Crystal Structure Determination

description: Related Article: Andreas Bernd Schnepf, Sebastian Kenzler, Florian Fetzer, Claudio Schrenk, Nia Pollard, Andrew R. Frojd, Andre Z. Clayborne|2019|Angew.Chem.,Int.Ed.|58|5902|doi:10.1002/anie.201900644
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/hbr8p7n526.1
title: Cross-regulation between TDP-43 and paraspeckles promotes pluripotency-differentiation transition. Modic et al

description: Sanger sequencing and confirmatory gel electrophoresis confirming the CRISPR-Cas9 edited human and mouse embryonic stem cells presented in the manuscript under review entitled "Cross-regulation between TDP-43 and paraspeckles promotes pluripotency-differentiation transition"
DOI: 10.21227/haec-fz15
title: DEA Cross-Efficiency Method for Ranking Units Based on Competitive vision

description: Ranking units which include multiple inputs and outputs in natural and social systems is a complex problem. DEA cross-efficiency evaluation method is an effective approach widely used in evaluating and ranking the decision making units to tackle this problem. The traditional cross-efficiency model is lack consideration for the relationships among DMUs. For this problem, the paper constructs the relationship matrix among DMUs to reflect the relationships among DMUs based on competitive interval and competitive vision. the paper start with calculating the efficiency interval based on benevolent and aggressive model, then adopt the ideas of competitive vision to design the competition level, cooperation level and competition-cooperation level coefficients .Thirdly, reconstruct the relation matrix of the DMUs on the basis of definitive efficiency interval using competition-cooperation level coefficient. Fourthly, introduce the relation matrix to cross-efficiency evaluation method for calculating efficient value and ranking DMUs. The method avoids the subjective factors caused by evaluators to accord with the actual situations of DMUs and use process information effectively. Finally, an illustrative example is provided to verify the rationality and validity of the proposed model.
DOI: 10.21227/w69x-0f72
title: DEA Cross-Efficiency Method for Ranking Units Based on Competitive vision

description: Ranking units which include multiple inputs and outputs in natural and social systems is a complex problem. DEA cross-efficiency evaluation method is an effective approach widely used in evaluating and ranking the decision making units to tackle this problem. The traditional cross-efficiency model is lack consideration for the relationships among DMUs. For this problem, the paper constructs the relationship matrix among DMUs to reflect the relationships among DMUs based on competitive interval and competitive vision. the paper start with calculating the efficiency interval based on benevolent and aggressive model, then adopt the ideas of competitive vision to design the competition level, cooperation level and competition-cooperation level coefficients .Thirdly, reconstruct the relation matrix of the DMUs on the basis of definitive efficiency interval using competition-cooperation level coefficient. Fourthly, introduce the relation matrix to cross-efficiency evaluation method for calculating efficient value and ranking DMUs. The method avoids the subjective factors caused by evaluators to accord with the actual situations of DMUs and use process information effectively. Finally, an illustrative example is provided to verify the rationality and validity of the proposed model.
DOI: 10.5517/ccdc.csd.cc20y505
title: CCDC 1875066: Experimental Crystal Structure Determination

description: Related Article: Yue-Lin Wang, Jun-Wei Zhao, Zhong Zhang, Jun-Jun Sun, Xu-Yan Li, Bai-Feng Yang, Guo-Yu Yang|2019|Inorg.Chem.|58|4657|doi:10.1021/acs.inorgchem.9b00258
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.cc20y516
title: CCDC 1875067: Experimental Crystal Structure Determination

description: Related Article: Yue-Lin Wang, Jun-Wei Zhao, Zhong Zhang, Jun-Jun Sun, Xu-Yan Li, Bai-Feng Yang, Guo-Yu Yang|2019|Inorg.Chem.|58|4657|doi:10.1021/acs.inorgchem.9b00258
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.cc20y527
title: CCDC 1875068: Experimental Crystal Structure Determination

description: Related Article: Yue-Lin Wang, Jun-Wei Zhao, Zhong Zhang, Jun-Jun Sun, Xu-Yan Li, Bai-Feng Yang, Guo-Yu Yang|2019|Inorg.Chem.|58|4657|doi:10.1021/acs.inorgchem.9b00258
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.cc20y538
title: CCDC 1875069: Experimental Crystal Structure Determination

description: Related Article: Yue-Lin Wang, Jun-Wei Zhao, Zhong Zhang, Jun-Jun Sun, Xu-Yan Li, Bai-Feng Yang, Guo-Yu Yang|2019|Inorg.Chem.|58|4657|doi:10.1021/acs.inorgchem.9b00258
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.cc20y549
title: CCDC 1875070: Experimental Crystal Structure Determination

description: Related Article: Yue-Lin Wang, Jun-Wei Zhao, Zhong Zhang, Jun-Jun Sun, Xu-Yan Li, Bai-Feng Yang, Guo-Yu Yang|2019|Inorg.Chem.|58|4657|doi:10.1021/acs.inorgchem.9b00258
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.cc213h6w
title: CCDC 1880187: Experimental Crystal Structure Determination

description: Related Article: Jie Wang, Yan-Ling Li, Zhao-Yang Wang, Shuang-Quan Zang|2019|CrystEngComm|21|2264|doi:10.1039/C9CE00054B
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.cc21dmwz
title: CCDC 1888981: Experimental Crystal Structure Determination

description: Related Article: Xiaofeng Zhang, Weiqi Qiu, Jason Evans, Manpreet Kaur, Jerry P. Jasinski, Wei Zhang|2019|Org.Lett.|21|2176|doi:10.1021/acs.orglett.9b00487
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.cc21f9tm
title: CCDC 1889630: Experimental Crystal Structure Determination

description: Related Article: Xiao-Qin Wu, Yan Liu, Pei-Qi Feng, Xue-Hong Wei, Guang-Ming Yang, Xiao-Hang Qiu, Jian-Gong Ma|2019|Chem.Commun.|55|4059|doi:10.1039/C9CC01701A
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.cc21f9vn
title: CCDC 1889631: Experimental Crystal Structure Determination

description: Related Article: Xiao-Qin Wu, Yan Liu, Pei-Qi Feng, Xue-Hong Wei, Guang-Ming Yang, Xiao-Hang Qiu, Jian-Gong Ma|2019|Chem.Commun.|55|4059|doi:10.1039/C9CC01701A
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: 10.6073/pasta/2a97b8449edc360fbc374cce1aa71e89
title: Bioclimatic predictors in Maricopa County, Arizona derived from remotely sensed, daily weather parameters (NASA DAYMET): 2000-2016

description: There is considerable interest in using climatic variables and
  bioclimatic predictors not only in ecological species distribution
  models but in interdisciplinary studies of urban environments. We
  compiled an downloadable geodatabase of monthly environmental
  variables on a 1km x 1km spatial resolution including raw climate
  variables such as precipitation, minimum and maximum air temperature,
  and water vapor pressure obtained from NASA Earth Science Data and
  Information System Daily Surface Weather and Climatological Summaries
  (DAYMET) for Maricopa County. We then used the continuous
  environmental data from DAYMET to create 19 different annual
  bioclimatic predictors for Maricopa County (as defined by Nix, 1986
  and Hijmans, 2004). Our study is the first to utilize NASA DAYMET
  model data to generate bioclimatic predictors. Bioclimatic predictors
  are important variables to use in model development to study nuances
  of seasonality especially when compiling models of species and
  vegetation. This geodatabase of environmental variables provides
  accessible vital data for the entire Central Arizona–Phoenix Long-Term
  Ecological Research (CAP LTER) study area that can be used in an array
  of interdisciplinary studies.

      
  Processed DAYMET data from which the data in this data set were derived
  are accessible from:

      
  Hijmans, R.J., Cameron, S.E., Parra, J.L., Jones, P.G. and Jarvis, A.,
  2004. The WorldClim interpolated global terrestrial climate surfaces.
  Version 1.3.

      
  Nix, Henry A., 1986, A biogeographic analysis of Australian elapid
  snakes, in Longmore, Richard, ed., Atlas of elapid snakes of
  Australia: Canberra, Australian Flora and Fauna Series 7, Australian
  Government Publishing Service, p. 4‒15.
DOI: 10.7910/dvn/ea57ra
title: Do anti-poverty programs sway voters? Experimental evidence from Uganda

description: Impactful policies may not lead to support for the political party that introduces them. In 2008, Uganda’s government encouraged groups of youth to submit proposals to start enterprises. Of 535 eligible groups, a random 265 received grants of nearly $400 per person. Prior work showed that, after four years, YOP raised employment by 17% and earnings by 38%. Here we show that recipients were no more likely to support the ruling party in elections. Rather, recipients slightly increased campaigning and voting for the opposition. Potential mechanisms include program misattributiongroup socialization, and financial independence freeing voters from transactional voting.
DOI: 10.5517/ccdc.csd.cc21l13t
title: CCDC 1894165: Experimental Crystal Structure Determination

description: Related Article: Daniel M. Gill, Louise Male, Alan M. Jones|2019|Chem.Commun.|55|4319|doi:10.1039/C9CC01057B
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.cc21lf36
title: CCDC 1894537: Experimental Crystal Structure Determination

description: Related Article: Linning Ren, Manman Wang, Benyao Fang, Wenquan Yu, Junbiao Chang|2019|Org.Biomol.Chem.|17|3446|doi:10.1039/C9OB00279K
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.cc21lqlz
title: CCDC 1894831: Experimental Crystal Structure Determination

description: Related Article: Carlota Clarasó, Laia Vicens, Alfonso Polo, Miquel Costas|2019|Org.Lett.|21|2430|doi:10.1021/acs.orglett.9b00729
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.