Recent Submissions

  • CCDC 1406311: Experimental Crystal Structure Determination

    Gangwar, Manoj Kumar; Butcher, Ray J. (Cambridge Crystallographic Data Centre, 2020-11-27) [Dataset]
  • CCDC 1044413: Experimental Crystal Structure Determination :

    Gangwar, Manoj Kumar; Butcher, Ray J. (Cambridge Crystallographic Data Centre, 2020-11-27) [Dataset]
  • CCDC 1941207: Experimental Crystal Structure Determination

    Das, Pradip K.; Bhunia, Sarmistha; Chakraborty, Priyanka; Chatterjee, Sudipta; Rana, Atanu; Peramaiah, Karthik; Alsabban, Merfat; Dutta, Indranil; Dey, Abhishek; Huang, Kuo-Wei (Cambridge Crystallographic Data Centre, 2020-11-26) [Dataset]
  • CCDC 1941208: Experimental Crystal Structure Determination

    Das, Pradip K.; Bhunia, Sarmistha; Chakraborty, Priyanka; Chatterjee, Sudipta; Rana, Atanu; Peramaiah, Karthik; Alsabban, Merfat; Dutta, Indranil; Dey, Abhishek; Huang, Kuo-Wei (Cambridge Crystallographic Data Centre, 2020-11-26) [Dataset]
  • Data for: Swelling Pressure of Montmorillonite with Multiple Water Layers at Elevated Temperatures and Water Pressures: A Molecular Dynamics Study

    Yang, Yafan; Qiao, Rui; Wang, Yifeng; Sun, Shuyu (Mendeley, 2020-11-12) [Dataset]
    This file includes swelling pressure data shown in Figure 2-4.
  • CCDC 1040448: Experimental Crystal Structure Determination

    Gangwar, Manoj Kumar; Butcher, Ray J. (Cambridge Crystallographic Data Centre, 2020-11-07) [Dataset]
  • CCDC 1023267: Experimental Crystal Structure Determination

    Gangwar, Manoj Kumar; Butcher, Ray J. (Cambridge Crystallographic Data Centre, 2020-11-07) [Dataset]
  • CCDC 2005983: Experimental Crystal Structure Determination : 1,4,10,11,17,20,23,29,30,36,41,47,48,54-tetradecaazaoctacyclo[18.18.18.26,9.212,15.225,28.231,34.243,46.249,52]octahexaconta-4,6,8,10,12,14,16,23,25,27,29,31,33,35,41,43,45,47,49,51,53,57,59,61,63,65,67-heptacosaene chloroform solvate

    Moosa, Basem; Alimi, Lukman Olawale; Shkurenko, Aleksander; Fakim, Aliyah; Bhatt, Prashant; Zhang, Gengwu; Eddaoudi, Mohamed; Khashab, Niveen M. (Cambridge Crystallographic Data Centre, 2020-10-08) [Dataset]
  • CCDC 2005984: Experimental Crystal Structure Determination : 1,4,10,11,17,20,23,29,30,36,41,47,48,54-tetradecaazaoctacyclo[18.18.18.26,9.212,15.225,28.231,34.243,46.249,52]octahexaconta-4,6,8,10,12,14,16,23,25,27,29,31,33,35,41,43,45,47,49,51,53,57,59,61,63,65,67-heptacosaene 1,4-xylene solvate

    Moosa, Basem; Alimi, Lukman Olawale; Shkurenko, Aleksander; Fakim, Aliyah; Bhatt, Prashant; Zhang, Gengwu; Eddaoudi, Mohamed; Khashab, Niveen M. (Cambridge Crystallographic Data Centre, 2020-10-08) [Dataset]
  • Whole-genome re-sequencing of pathogenic E. coli strain PI-7

    Sivakumar, Krishnakumar; Lehmann, Robert; Rachmadi, Andri Taruna; Augsburger, Nicolas; Zaouri, Noor A.; Tegner, Jesper; Hong, Pei-Ying (NCBI, 2020-10-06) [Bioproject, Dataset]
    Elucidating the role of virulence traits in the survival of pathogenic E. coli PI-7 following disinfection
  • Scaled, unmerged X-ray diffraction data from SF2 Nef-Fyn SH3 R96I crystals

    Arold, Stefan T.; Aldehaiman, Abdullah; Shahul Hameed, Umar F. (KAUST Research Repository, 2020-09-27) [Dataset]
    Crystals of the SF2 Nef:FynR96I SH3 complex were obtained by sitting drop vapour diffusion (details to be published). All data for SF2 Nef:FynR96I SH3 were collected at 100K at the beamline Proxima 2A at the SOLEIL Synchrotron (France), EIGER 9M detector, respectively (proposal numbers 2016 0098, 20161236, 20170193). Data from three crystals were processed, scaled and combined using XDS as implemented in the XDSme pipeline. The resulting scaled but unmerged and not anisotropically cut data are deposited here.
  • Data for Long-Wavelength Propagation in Fractured Rock Masses (3D Stress Field)

    Rached, Rached; Garcia, Adrian; Santamarina, Carlos (KAUST Research Repository, 2020-09-23) [Dataset]
    The dataset includes all data that was used to generate Figures 3, 4, 5, 7, and 8.
  • CCDC 2006223: Experimental Crystal Structure Determination

    Scattolin, Thomas; Bortolamiol, Enrica; Palazzolo, Stefano; Caligiuri, Isabella; Perin, Tiziana; Canzonieri, Vincenzo; Demitri, Nicola; Rizzolio, Flavio; Cavallo, Luigi; Dereli, Busra; Mane, Manoj V.; Nolan, Steven P.; Visentin, Fabiano (Cambridge Crystallographic Data Centre, 2020-09-14) [Dataset]
  • Large synthetic datasets for univariate geostatistical modeling

    Abdulah, Sameh; Ltaief, Hatem; Sun, Ying; Genton, Marc G.; Keyes, David E. (KAUST Research Repository, 2020-09-08) [Dataset]
    The enclosed datasets have been generated by the internal spatial data generator tool included in the ExaGeoStat software (https://github.com/ecrc/exageostat). The datasets are univariate 2D spatial data spanning different correlation strengths between the geospatial locations with three different smoothness levels (0.6, 1.5, and 2.3). The main purpose of these datasets is to validate any exact or approximation geospatial modeling algorithm by providing the truth parameters used for generating each dataset. For certain data configurations that are not covered by the provided datasets, ExaGeoStat software can be used directly to generate geospatial data with a prescribed number of locations and prescribed parameter set.
  • 3D Model Construction of SARS-CoV-2 Virus

    Mesri, Youssef; Bader, Wael; Alomairy, Rabab; Ltaief, Hatem; Keyes, David E. (KAUST Research Repository, 2020-09-06) [Dataset]
    Description: The dataset contains SARS-COV-2 virus 3D geometry extracted from the Protein Data Bank (PDB) codenamed PDBID 6VXX available at (https://www.rcsb.org/structure/6VXX). In 3D model construction, we first generate a tetrahedral mesh of the volume surrounding the molecular structure of the Spike glycoprotein of the SARS-CoV-2 virus, a.k.a. the S protein from PDB. Codenamed PDBID 6VXX at the Protein Data Bank (PDB)2, the S protein has been generated with a 2.8Å resolution, i.e., 0.28nm. Once the mesh of the S protein has been constructed, We stitch several S proteins, approximately evenly distributed around the spheric geometry of the virus main body. Based on real geometrical description of the virus structure, we set the virus diameter to 140nm and attach 80 S proteins. We build a CAD model which represents the building block for the simulation pipeline. The CAD model is then triangulated to generate a 3D surface mesh of the overall SARS-COV-2 virus geometry. Software or equipment used to create the data: The mesh is generated using OxyGen Suite with third party tools: TetGen and VTK. OxyGen Suite is a collection of mesh generation, adaptation and deformation algorithms and tools that produces high quality static and dynamic simplex meshes.
  • How does a Pinatubo-size Volcanic Plume Reach the Middle Stratosphere?

    Stenchikov, Georgiy L.; Ukhov, Alexander; Osipov, Sergey; Ahmadov, Ravan; Grell, Georg; Cady-Pereira, Karen; Mlawer, Eli; Iacono, Michael (KAUST Research Repository, 2020-09-01) [Dataset]
    This dataset includes namelist's and other files required to run WRF-Chem simulation.
  • Data for: "Regional Geoengineering to Increase Rainfall over the Red Sea Arabian Coastal Plains by Utilizing Sea Breezes"

    Mostamandi, Suleiman; Predybaylo, Evgeniya; Osipov, Sergey; Zolina, Olga; Gulev, Sergey K.; Parajuli, Sagar P.; Stenchikov, Georgiy L. (KAUST Research Repository, 2020-08-28) [Dataset]
  • Data for: "High summer temperatures amplify functional differences between coral- and algae-dominated reef communities"

    Roth, Florian; Rädecker, Nils; Carvalho, Susana; Duarte, Carlos M.; Saderne, Vincent; Anton, Andrea; Silva, Luis; Calleja, Maria; Voolstra, Christian R.; Kürten, Benjamin; Jones, Burton; Wild, Christian (KAUST Research Repository, 2020-08-26) [Dataset]
    This is the data to "High summer temperatures amplify functional differences between coral- and algae-dominated reef communities". All information on how the dataset was collected can be found in the manuscript.  Abstract of the manuscript: Shifts from coral to algal dominance are expected to increase in tropical coral reefs as a result of anthropogenic disturbances. The consequences for key ecosystem functions such as primary productivity, calcification, and nutrient recycling are poorly understood, particularly under changing environmental conditions. We used a novel in situ incubation approach to compare functions of coral- and algae-dominated communities in the central Red Sea bi-monthly over an entire year. In situ gross and net community primary productivity, calcification, dissolved organic carbon fluxes, dissolved inorganic nitrogen fluxes, and their respective activation energies were quantified to describe the effects of seasonal changes. Overall, coral-dominated communities exhibited 30% lower net productivity and 10 times higher calcification than algae-dominated communities. Estimated activation energies indicated a higher thermal sensitivity of coral-dominated communities. In these communities, net productivity and calcification were negatively correlated with temperature (>40% and >65% reduction, respectively, with +5°C increase from winter to summer), while carbon losses via respiration and dissolved organic carbon release were more than doubled at higher temperatures. In contrast, algae-dominated communities doubled net productivity in summer, while calcification and dissolved organic carbon fluxes were unaffected. These results suggest pronounced changes in community functioning associated with phase shifts. Algae-dominated communities may outcompete coral-dominated communities due to their higher productivity and carbon retention to support fast biomass accumulation while compromising the formation of important reef framework structures. Higher temperatures likely amplify these functional differences, indicating a high vulnerability of ecosystem functions of coral-dominated communities to temperatures even below coral bleaching thresholds. Our results suggest that ocean warming may not only cause but also amplify coral-algal phase shifts in coral reefs. Usage information: The data Excel file contains two data sheets: Sheet 1 (Community composition): This sheet gives the community composition of the assessed benthic communities in % cover of functional groups. Sheet 2 (Metabolism): This sheet contains the metabolic data of the benthic communities. All abbreviations and units are in the related publication.
  • Crustal and upper-mantle structure below Central and Southern Mexico

    Espindola Carmona, Armando; Peter, Daniel; Ortiz Aleman, Carlos (KAUST Research Repository, 2020-08-25) [Dataset]
    3D Velocity Model for Central and Southern Mexico
  • Data underlying the publication: Bacterial community dynamics and disinfection impact in cooling water systems

    Pinel, I.S.M.; Moed, D.H.; Vrouwenvelder, Johannes S.; van Loosdrecht, M.C.M. (4TU.ResearchData, 2020-08-20) [Dataset]
    Raw 16S rRNA gene amplicon sequencing file of the DNA extracted from a full-scale cooling tower water samples during a 5-month period. The files were used to investigate the microbial dynamics and assess the growth or decay of the bacterial community members in the cooling system, when combined to flow cytometry analyses. The method allows to identify microorganisms that demonstrate higher resistance to disinfection. In general, the study contributes to a better knowledge of cooling towers and of the impact of continuous chlorination on the overall microbial community.

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