cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.18716/nmrshiftdb2/88800
title: NMR data for InChI=1S/C17H14O3S/c1-2-13-20-14-17(15-9-5-3-6-10-15)21(18,19)16-11-7-4-8-12-16/h1,3-12,14H,13H2/b17-14- (INChI), LEOHRPOLXPQIGT-VKAVYKQESA-N (InChI Key), InChI=1/C17H14O3S/c1-2-13-20-14-17(15-9-5-3-6-10-15)21(18,19)16-11-7-4-8-12-16/h1,3-12,14H,13H2/b17-14- (InChI with fixed H layer), O=S(=O)(c1ccccc1)C(=COCC#C)c2ccccc2 (SMILES), C([H])#CC([H])([H])OC([H])=C(C1=C([H])C([H])=C([H])C([H])=C1[H])S(=O)(=O)C2=C([H])C([H])=C([H])C([H])=C2[H] (chiral SMILES)
DOI: 10.18716/nmrshiftdb2/88801
title: NMR data for [(Z)-1-(benzenesulfonyl)-2-bromoethenyl]benzene
DOI: 10.18716/nmrshiftdb2/88802
title: NMR data for [(Z)-1-(benzenesulfonyl)-2-iodoethenyl]benzene
DOI: 10.18716/nmrshiftdb2/88803
title: NMR data for [(Z)-1-(benzenesulfonyl)-2-chloroethenyl]benzene
DOI: 10.18716/nmrshiftdb2/88804
title: NMR data for dimethyl(2-phenylethynyl)selanium
DOI: 10.18716/nmrshiftdb2/88805
title: NMR data for 4-chloro-9H-carbazole
DOI: 10.18716/nmrshiftdb2/88806
title: NMR data for 1-but-2-ynoxy-3-iodobenzene
DOI: 10.18716/nmrshiftdb2/88808
title: NMR data for 1-bromo-4-[(2-methylpropan-2-yl)oxy]benzene
DOI: 10.18716/nmrshiftdb2/88807
title: NMR data for ethyl (4-iodophenyl)selanylformate
DOI: 10.18716/nmrshiftdb2/88809
title: NMR data for InChI=1S/C9H18N2O/c1-4-5-6-8-7-12-9(10-8)11(2)3/h8H,4-7H2,1-3H3 (INChI), WWWVTXZVYXQGMB-UHFFFAOYSA-N (InChI Key), InChI=1/C9H18N2O/c1-4-5-6-8-7-12-9(10-8)11(2)3/h8H,4-7H2,1-3H3 (InChI with fixed H layer), N1=C(OCC1CCCC)N(C)C (SMILES)
DOI: 10.18716/nmrshiftdb2/88810
title: NMR data for InChI=1S/C9H16N2O/c1-11(2)9-10-7-5-3-4-6-8(7)12-9/h7-8H,3-6H2,1-2H3 (INChI), BOQMNQXGUGSTNB-UHFFFAOYSA-N (InChI Key), InChI=1/C9H16N2O/c1-11(2)9-10-7-5-3-4-6-8(7)12-9/h7-8H,3-6H2,1-2H3 (InChI with fixed H layer), N1=C(OC2CCCCC12)N(C)C (SMILES)
DOI: 10.18716/nmrshiftdb2/88811
title: NMR data for InChI=1S/C12H16N2OS/c1-12(2,16-3)10-8-15-11(14-10)9-6-4-5-7-13-9/h4-7,10H,8H2,1-3H3 (INChI), SSXPKDOIOXWSRZ-UHFFFAOYSA-N (InChI Key), InChI=1/C12H16N2OS/c1-12(2,16-3)10-8-15-11(14-10)9-6-4-5-7-13-9/h4-7,10H,8H2,1-3H3 (InChI with fixed H layer), n1ccccc1C2=NC(CO2)C(SC)(C)C (SMILES)
DOI: 10.18716/nmrshiftdb2/88812
title: NMR data for InChI=1S/C15H16N2O4S/c1-9-4-6-12(7-5-9)22(18,19)15-14(20-11(3)16-15)13-8-10(2)17-21-13/h4-8,14-15H,1-3H3 (INChI), XGFBJGUBADMJAN-UHFFFAOYSA-N (InChI Key), InChI=1/C15H16N2O4S/c1-9-4-6-12(7-5-9)22(18,19)15-14(20-11(3)16-15)13-8-10(2)17-21-13/h4-8,14-15H,1-3H3 (InChI with fixed H layer), O=S(=O)(c1ccc(cc1)C)C2N=C(OC2c3onc(c3)C)C (SMILES)
DOI: 10.18716/nmrshiftdb2/88813
title: NMR data for 2-nitroethanol
DOI: 10.18716/nmrshiftdb2/88814
title: NMR data for morpholine-4-carbothialdehyde
DOI: 10.18716/nmrshiftdb2/88816
title: NMR data for InChI=1S/C6H13NO2/c1-5(7)6(9-2)3-4-8/h3,5,8H,4,7H2,1-2H3/b6-3- (INChI), VUGJVDGZKRDQKL-UTCJRWHESA-N (InChI Key), InChI=1/C6H13NO2/c1-5(7)6(9-2)3-4-8/h3,5,8H,4,7H2,1-2H3/b6-3- (InChI with fixed H layer), OCC=C(OC)C(N)C (SMILES), C([H])([H])([H])C([H])(C(=C([H])C([H])([H])O[H])OC([H])([H])[H])N([H])[H] (chiral SMILES)
DOI: 10.18716/nmrshiftdb2/88817
title: NMR data for 2-chloroethanesulfonyl chloride
DOI: 10.18716/nmrshiftdb2/88815
title: NMR data for (2E)-4-methylpenta-2,4-dien-1-ol
DOI: 10.18716/nmrshiftdb2/88819
title: NMR data for 2-hydroxyethanesulfonate
DOI: 10.18716/nmrshiftdb2/88818
title: NMR data for 2-chloroethanesulfonate
DOI: 10.18716/nmrshiftdb2/88820
title: NMR data for 2,2,2-trichloroethyl dihydrogen phosphate
DOI: 10.18716/nmrshiftdb2/88821
title: NMR data for 1-sulfinylethane
DOI: 10.18716/nmrshiftdb2/88822
title: NMR data for 1-sulfinylpropane
DOI: 10.18716/nmrshiftdb2/88823
title: NMR data for 2-methyl-1-sulfinylpropane
DOI: 10.18716/nmrshiftdb2/88825
title: NMR data for InChI=1S/C6H9NOS/c1-3-5-7-4(2)6(8)9-5/h5H,3H2,1-2H3 (INChI), QWQRLQOZMFAWLH-UHFFFAOYSA-N (InChI Key), InChI=1/C6H9NOS/c1-3-5-7-4(2)6(8)9-5/h5H,3H2,1-2H3 (InChI with fixed H layer), O=C1SC(N=C1C)CC (SMILES)
DOI: 10.18716/nmrshiftdb2/88824
title: NMR data for InChI=1S/C12H13NO2S2/c1-15-11(12(14)16-2)9-7-17-10-6-4-3-5-8(10)13-9/h3-6,13H,7H2,1-2H3/b11-9- (INChI), ZGTBUVDQRSJOKG-LUAWRHEFSA-N (InChI Key), InChI=1/C12H13NO2S2/c1-15-11(12(14)16-2)9-7-17-10-6-4-3-5-8(10)13-9/h3-6,13H,7H2,1-2H3/b11-9- (InChI with fixed H layer), O=C(SC)C(OC)=C1Nc2ccccc2SC1 (SMILES), C([H])([H])([H])OC(=C1C([H])([H])SC2=C(C([H])=C([H])C([H])=C2[H])N1[H])C(=O)SC([H])([H])[H] (chiral SMILES)
DOI: 10.25824/redu/6kctlh
title: B.3 - TRF1 - JULGADOS APÓS DEPURAÇÃO (BASE DE DADOS).xlsx
DOI: 10.25824/redu/ysqhlv
title: B.2 - STJ - JULGADOS APÓS DEPURAÇÃO (BASE DE DADOS).tab
DOI: 10.25824/redu/cx2lmi
title: B.1 - STF - JULGADOS APÓS DEPURAÇÃO (BASE DE DADOS).xlsx
DOI: 10.25824/redu/hpmewe
title: E.1 - COMPARAÇÃO DOS CLASSIFICADORES.tab
DOI: 10.25824/redu/zd53js
title: C.2 - REGRESSÃO LINEAR TOTAIS X CORRUPÇÃO.xlsx
DOI: 10.25824/redu/nzhpbl
title: A.4 - TRF2 - JULGADOS BUSCADOS NA INTERNET (TODOS).xlsx
DOI: 10.25824/redu/vyuxsl
title: B.6 - TRF4 - JULGADOS APÓS DEPURAÇÃO (BASE DE DADOS).xlsx
DOI: 10.25824/redu/vozcmz
title: D.1 - AMOSTRA DADOS CRIME.xlsx
DOI: 10.25824/redu/llijc7
title: E.3 - DETALHAMENTO DOS 3 CLASSIFICADORES.tab
DOI: 10.25824/redu/wmcumy
title: E.2 - COMPARAÇÃO DE ETAPAS.tab
DOI: 10.5286/isis.e.rb2000191
title: Dynamics of methane in copper zeolites

description: Zeolites are industrially important porous materials used in catalysis, gas separation and ion exchange. Probing the movement of molecules within them is therefore an important topic of research. A variety of factors affecting guest-molecule diffusivities have been deduced, including the size, shape and chemical composition of the zeolite crystal; geometry and topology of the pore system; and the spatial distribution of counterions and active sites within the framework. Our investigation concerns the partial oxidation of methane to methanol with water, where the diffusivity of reactants through the framework is fundamental to understanding the partial oxidation reaction in these systems. This proposal aims to investigate the dynamics of methane during its’ adsorption to three activated copper-zeolite catalysts to complement previous measurements of water diffusion in the same frameworks.
DOI: 10.5286/isis.e.rb2000191-1
title: Dynamics of methane in copper zeolites

description: Zeolites are industrially important porous materials used in catalysis, gas separation and ion exchange. Probing the movement of molecules within them is therefore an important topic of research. A variety of factors affecting guest-molecule diffusivities have been deduced, including the size, shape and chemical composition of the zeolite crystal; geometry and topology of the pore system; and the spatial distribution of counterions and active sites within the framework. Our investigation concerns the partial oxidation of methane to methanol with water, where the diffusivity of reactants through the framework is fundamental to understanding the partial oxidation reaction in these systems. This proposal aims to investigate the dynamics of methane during its’ adsorption to three activated copper-zeolite catalysts to complement previous measurements of water diffusion in the same frameworks.
DOI: 10.5281/zenodo.3228295
title: Wind energy taxonomies and restricted vocabularies

description: This is the update version of the wind energy taxonomies and restricted vocabularies which has been implemented in DTU Data  (https://data.dtu.dk/DTU_Wind_Energy) with the purpose of accurately describing published data sets and data collections. The work on updating and implementing the wind energy taxonomies and restricted vocabularies has been done as a part of an internally funded 'FAIR digitalization' project of DTU Wind Energy(see 10.5281/zenodo.1493874). The work on updating the taxonomies and restricted vocabularies is a continuation of the work previously done under the IRPWind Open Data initiative (see 10.5281/zenodo.1199489).
DOI: 10.5281/zenodo.3228296
title: Wind energy taxonomies and restricted vocabularies

description: This is the update version of the wind energy taxonomies and restricted vocabularies which has been implemented in DTU Data  (https://data.dtu.dk/DTU_Wind_Energy) with the purpose of accurately describing published data sets and data collections. The work on updating and implementing the wind energy taxonomies and restricted vocabularies has been done as a part of an internally funded 'FAIR digitalization' project of DTU Wind Energy(see 10.5281/zenodo.1493874). The work on updating the taxonomies and restricted vocabularies is a continuation of the work previously done under the IRPWind Open Data initiative (see 10.5281/zenodo.1199489).
DOI: 10.25345/c59h0g
title: MassIVE MSV000083854 - Proteome profiling of PPIA KO cells
title: Proteome profiling of PPIA shRNA treated human cell lines.
DOI: 10.17632/nyt2h6n3ct.3
title: Data for: Evaluating the geogenic CO2 flux from geothermal areas by analysing Quaternary travertine masses. New data from western Central Italy and review of previous CO2 flux data.

description: Porosity, CaCO3 and insoluble fractions of Italian travertines
DOI: 10.7910/dvn/n9gvve/lodmjr
title: bangladesh.gph

description: :unav
DOI: 10.7910/dvn/n9gvve/px82qx
title: liberia.gph

description: :unav
DOI: 10.7910/dvn/n9gvve/sg5vf6
title: elsalvador.gph

description: :unav
DOI: 10.25919/5ce81da8f16f3
title: Parkes observations for project P971 semester 2019APRS_03

description: We propose timing observations of the relativistic pulsar - white-dwarf binary PSR J1141-6545. This unique system offers access to a wide range of physics, from relativistic phenomena through pulsar emission cone studies, to the structure and distribution of interstellar plasma along our line-of-sight. The recently installed Parkes Ultra Wide Band Low Frequency (UWL) receiver has opened up the possibility of performing first-ever studies of its orbital dynamics at high temporal resolution and study of the effects of the intra-binary medium on the dispersion and polarisation of the pulse profile. Our analysis of data obtained to date suggests that the pulsar would precess away from our line-of-sight in the next 3-5 years. Hence, regular observations are crucial to maximizing its science outcome
DOI: 10.7910/dvn/n9gvve/0n62sr
title: cambodia.gph

description: :unav
DOI: 10.7910/dvn/n9gvve/3suwug
title: png.gph

description: :unav
DOI: 10.7910/dvn/n9gvve/kj8rda
title: mozambique.gph

description: :unav
DOI: 10.7910/dvn/n9gvve/oyxw2a
title: F1.gph

description: :unav
DOI: 10.7910/dvn/n9gvve/tq86l3
title: 2019-05-08 final data liberal peace.tab

description: Main data
DOI: 10.7910/dvn/n9gvve/wyvoxp
title: F2.gph

description: :unav
DOI: 10.7910/dvn/n9gvve/yq9p9a
title: 2019-05-08 Final do finel.do

description: :unav
DOI: 10.25345/c55p9c
title: MassIVE MSV000083855 - Acetyl-CoA flux regulates the proteome and acetyl-proteome to maintain intracellular metabolic crosstalk - Acetylation Stoichiometry Dataset
title: Acetylation stoichiometry quantification of AT-1 (S113R/+) and AT-1 sTg mouse liver
Samples were pre-fractionated into 6 fractions using an HPRP offline HPLC.
Analysis Logs can be found in the Supplementary Files
DOI: 10.23721/1503876
title: Real Data Corpus - Naval Postgraduate School (2006-01-01 to 2014-12-31)

description: Real Data Corpus

The Real Data Corpus (RDC) is a collection of disk images extracted from secondary storage devices that were acquired from second-hand markets around the world. In total, the RDC currently consists of 58 TiB of data contained in 3,127 disk images from 29 countries. A variety of devices are represented, including magnetic media and solid state storage from laptops, desktops, mobile phones, USB memory sticks, and other media. The dataset is hosted in the HPC infrastructure at the Naval Postgraduate School, as well as in AWS Govcloud.

Potential Uses

The Real Data Corpus is a one-of-a-kind scientific resource for:
-Developing and validating forensic and data recovery tools.
-Training students in forensics and data recovery
-Developing and validating document translation software.
-Exploring and characterizing real-world computing practices, configuration choices, and option settings.
-Studying the storage allocation strategies of file systems under real-world conditions

The RDC has been cited in over 60 articles. See our current list here. Access and Availability

Please contact us if you would like access to the Real Data Corpus. In general, due to privacy concerns, we do not release copies of the data to private individuals. However, depending on the requirements of the project, we may be able to offer access through one of two methods: 1.Mediated Access. Researchers submit source code, build instructions, and detailed instructions for running their experiment. We return sanitized results. This is the most expedient option in cases where the desired experiment does not involve human subjects research. 
2.Direct Access. Researchers create virtual machines on Amazon GovCloud, and these machines are granted access to the dataset. Because this method may involve direct contact with sensitive data, it involves additional review.

Please be aware that due to limited staff we cannot always accommodate all requests. Efforts are underway to develop infrastructure that will allow us to meet a wider range of research requirements without unduly increasing privacy risks. For more information or if you're interested in access to the Real Data Corpus, please contract:

Brittany Ramsey - Research Associate

blramsey@nps.edu (831) 656-2014
DOI: 10.23721/1503877
title: ddosflowgen (2017-09-01)

description: ddosflowgen is a tool that models a DDoS attack and generates synthetic traffic datasets from multiple views. You can define the number of attacking networks and adjust parameters such as the attack vectors present, the amplification factor, and the number of attack sources per network. Our tool includes non-attack traffic in the output by rewriting IP addresses from a reference noise dataset.

Unlike packet-based simulations, which are not feasible at terabit scales, ddosflowgen simulates traffic using a "flow" representation. This format (implemented with SiLK) uses summaries of IP headers to describe traffic in a compact form. Flow representation makes it possible to simulate extremely high packet and bit rates, and we're currently experimenting with 1.2 Tbps attack scenarios.

ddosflowgen simulates a variety of threats:

* amplifiers/reflectors, such as DNS and NTP servers * flooders within a botnet, like Mirai in attack mode * probes from a botnet, like Mirai scanning for IoT

ddosflowgen is open source, and is available on Github. We are releasing this primarily as an aid to other researchers, and to start a discussion about how best to generate repeatable test cases for defenses against massive attacks. Please enjoy, and we're happy to consider updates, but understand that we intend this tool largely as reference material rather than as a long-running software project.

https://github.com/GaloisInc/ddosflowgen

This project is the result of funding provided by the Science and Technology Directorate of the United States Department of Homeland Security under contract number D15PC00186. The views and conclusions contained herein are those of the authors and should not be interpreted as necessarily representing the official policies or endorsements, either expressed or implied, of the Department of Homeland Security, or the U.S. Government.
DOI: 10.17632/js6dd6skfp.1
title: Processed Data for: Active deformation in Ecuador enlightened by a new waveform-based catalog of earthquake focal mechanisms

description: Description of the file “res_inv_parameter.xls”, providing access to the seismic source parameters determined by the MECAVEL method. Column A: earthquake identifier using its date in the given format. Columns B-E (“la_0”, “lo_0”, “pf_0”, “mg_0”) refer to the initial latitude, longitude, depth and magnitude, respectively (latitude and longitude in degrees, depth in km). These parameters come from the IG-EPN catalog and are used as starting parameters for the MECAVEL inversion. Columns F-I (“la_i”, “lo_i”, “pf_i”, “mg_i”) refer to the inverted latitude, longitude, depth and moment magnitude, respectively (latitude and longitude in degrees, depth in km). Columns J-O describe the MECAVEL inverted focal mechanism: “az1”, “dp1” and “rk1” are the strike, dip and rake, respectively, of one of the nodal planes; “az2”, “dp2”, “rk2” are the strike, dip and rake, respectively, of the other nodal plane. All these angles are given in degrees. Column P (“msft”) is the mean misfit between observed and synthetic waveforms. Column Q-S (“NchZ”, “NchN”, “NchE”) are the number of vertical, North-South and East-West channels, respectively, used in the inversion. Column T (“st_tot”) is the total number of stations used and column U (“gap”) is the maximum azimuthal gap in degrees. Column V (“Qlt”) is the quality criteria derived for each solution (based on misfit, number of used waveforms and azimuthal gap): quality A refers to the most reliable solutions, followed by B and C.
DOI: 10.17632/zdzb6m7h4w.1
title: Data for: Variability of stamp impression measurements under different apposition conditions
DOI: 10.6084/m9.figshare.8181725
title: Spirurina 18S and 28S Alignment (Fig. 2B)

description: This is a multiple sequence alignment of 18S and 28S sequences.
DOI: 10.6084/m9.figshare.8181728
title: Spirurina 18S and 28S Alignment incl. 3 individuals of the novel nematode

description: This is a multiple sequence alignment of 18S and 28S sequences.
DOI: 10.7910/dvn/qghdm3/5qsn8g
title: Read_me.txt

description: :unav
DOI: 10.7910/dvn/qghdm3/ezkg33
title: Cust_et_al_JAERE.do

description: :unav
DOI: 10.17632/v4bt7rj9jp.1
title: Data for: Optimization of Novel Reversible Bruton's Tyrosine Kinase Inhibitors Identified using Tethering-Fragment-Based Screens

description: Kinases selectivity data for compounds 43 and 50. Analytical data for the synthesis of compound 50. Cellular IC50 graphs.
DOI: 10.5281/zenodo.2775840
title: Palladium-Catalyzed Directed meta-Selective C–H Allylation of Arenes: Unactivated Internal Olefins as Allyl Surrogates

description: This dataset contains the geometries of all optimized structures (in <em>.xyz</em> format with their associated energy in Hartrees) accompanying the paper "Palladium-Catalyzed Directed meta-Selective CH Allylation of Arenes: Unactivated Internal Olefins as Allyl Surrogates "
DOI: 10.5281/zenodo.2775841
title: Palladium-Catalyzed Directed meta-Selective C–H Allylation of Arenes: Unactivated Internal Olefins as Allyl Surrogates

description: This dataset contains the geometries of all optimized structures (in <em>.xyz</em> format with their associated energy in Hartrees) accompanying the paper "Palladium-Catalyzed Directed meta-Selective CH Allylation of Arenes: Unactivated Internal Olefins as Allyl Surrogates "
DOI: 10.6084/m9.figshare.8181773
title: Spirurina 18S Alignment (118 taxa)

description: This is a multiple sequence alignment of 18S sequences of 118 taxa.
DOI: 10.7910/dvn/bcoz6n/tz8qlw
title: its_not_just_how_the_game_is_played.tar.gz

description: :unav
DOI: 10.24431/rw1k320
title: Alaska juvenile Steller Sea Lion Telemetry Dataset from the Eastern Aleutian Islands, 2000-2002

description: Satellite-linked telemetry tags were deployed on 30 juvenile (ages 5-21 months) Steller sea lions at sites among the central and eastern Aleutian Islands, Alaska to better understand habitat use, movements, and foraging behavior. Positions are calculated and provided by the Argos satellite system through CLS-America. Data are presented in a comma-delimited file that includes positional data and location quality.
DOI: 10.5281/zenodo.3228323
title: massypup64-example-data

description: Data files and results for massypup64 (http://www.lababi.bioprocess.org/index.php/14-sample-data-articles/78-massypup):

* Proteomics

* Metabolomics

* Data Mining
DOI: 10.17632/d64v5mwp4t.1
title: Data for: Simulation study of the liquefaction of low-pressure unconventional natural gas and a novel hybrid liquefaction cycle

description: simulation results of direct liquefaction process, pressure boost liquefaction process and hybrid liquefaction process
DOI: 10.25345/c52051
title: MassIVE MSV000083856 - Identification of RacE binding proteins
title: Dictyostelium cells expressing GFP-RacE proteins were lysed in lysis buffer (150 mM NaCl, 0.5% Triton X-100, 1 mM NaF, 0.5 mM Na3VO4, 1 mM DTT, 10% glycerol, 25 mM Tris-HCl [pH 7.5] and protease-inhibitor cocktail [Roche, 4693159001]) and incubated with GFP-Trap magnetic beads (ChromoTek, gtma-200) for 4 h. The beads were washed, and the bound fractions were analyzed using mass spectrometry at the Johns Hopkins Mass Spectrometry and Proteomics Facility.
DOI: 10.18112/openneuro.ds001946.v1.0.0
title: Hippocampal-neocortical interactions sharpen over time for predictive actions
DOI: 10.21223/p3/zuqhht
title: Dataset for: Transgressive Segregation for Continuous Storage Root Formation and Bulking in F1 Sweetpotato Population

description: The data set for the “Transgressive Segregation for Continuous Storage Root Formation and Bulking in F1 Sweetpotato Population” Agronomy, Open access journal has on-station plant breeding trials conducted at Namulonge in Wakiso districts respectively between 2017 and 2018 leading to an original research article. The on-station data are in Excel format for Sweetpotato Breeding Protocol (manual) http://www.sweetpotatoknowledge.org/). The on-station data on Continuous storage root formation and bulking scores, root numbers, vegetative growth data, and root weight from plots over 4 harvesting times used to estimate growth overtime and compute root yield, and biomass yield was the basis for the article. The pdf file has details on background information, site description, materials and methods, analysis, results and discussion, and relevant tables and illustrations. Supporting raw data and analysis tables include spreadsheets for singles harvests (at 90, 120, 150 and 180 Days after planting), the combined data sheet, and its respective analysis tables, summary means and breeding value estimations.
DOI: 10.25919/5ce858d868921
title: Parkes observations for project P958 semester 2019APRS_23

description: Fast radio bursts (FRBs) continue to raise more questions than they answer. Until a few months ago, only one burst – the only one known to repeat -  had been localized to a bright radio nebula (either a young supernova remnant or pulsar wind nebulae) in a distant dwarf galaxy.   
Over the last year searches with the Australian Square Kilometre Array Pathfinder (ASKAP) have detected 28 bursts, two of which have been localised to host galaxies at redshifts &gt; 0.3. These bursts and their hosts are very unlike the repeater, suggesting there may be a dichotomy in the population.  Over the next six months we expect to detect another 12 FRBs, which will also have sub-arcsecond localisations.   Here we propose to search this population for repeats.  Our comprehensive sample and a dense monitoring campaign of well localised bursts, at a fluence limit more than 60 times lower than that of their detections, will either confirm the presence of additional repeating FRBs or the uniqueness of FRB 121102 amongst the population.
DOI: 10.15151/esrf-es-186851575
title: Structural insight about a novel bacterial defence mechanism
DOI: 10.17632/4fkkrjhx45.1
title: Data for: Secondary metabolites from the mangrove sediment-derived fungus Penicillium pinophilum SCAU037

description: Summplementary data for the manuscirpt
DOI: 10.17632/fmykhdbbr3.1
title: Data for: AppendixA Supplementary data

description: This data set shows the searching method used in the systematic review of Diagnostic accuracy, Validity, and Reliability of Tensiomyography to assess muscle function and exercise-induced fatigue in healthy participants.
DOI: 10.15785/sbgrid/623
title: X-Ray Diffraction data from EpoR complex with dimeric DARPin ANR7, source of 6MOK structure

description: Native Dataset
description: frames 1-90 were processed with XDS
DOI: 10.15785/sbgrid/655
title: X-Ray Diffraction data from Chicken egg white lysozyme, source of 6RT3 structure

description: Low resolution pass