cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.25387/g3.9989801.v1
title: Supplemental Material for Reynolds-Peterson et al., 2019

description: Supplemental Materials include Table S1, and three supplemental figures, Figure S1, Figure S2 and Figure S3. Legends accompany each elements separately.<br>
DOI: 10.7910/dvn/1jbndc/3wyprc
title: appendixC.txt

description: :unav
DOI: 10.7910/dvn/1jbndc/l3csxh
title: analyzeSimulationMEQ.r

description: :unav
DOI: 10.7910/dvn/1jbndc/n6ngbh
title: analyzeSimulationUnique.r

description: :unav
DOI: 10.5066/p935dt1g
title: Grids in support of the U.S. Geological Survey Thermal Model for Seismic Hazard Studies

description: A 3D temperature model is constructed in order to support the estimation of physical parameters within the USGS National Crustal Model. The crustal model is defined by a geological framework consisting of various lithologies with distinct mineral compositions. A temperature model is needed to calculate mineral density and bulk and shear modulus as a function of position within the crust. These properties control seismic velocity and impedance, which are needed to accurately estimate earthquake travel times and seismic amplitudes in earthquake hazard analyses. The temperature model is constrained by observations of surface temperature, temperature gradient, and conductivity, inferred Moho temperature and depth, and assumed conductivity at the base of the crust. The continental plate is assumed to have heat production that decreases exponentially with depth and thermal conductivity that exponentially changes from a surface value to 3.6 W/m-K at the Moho. The oceanic plate cools as a halfspace with a geotherm dependent on plate age. Under these conditions and the application of observed surface heat production, predicted Moho temperatures match Moho temperatures inferred from Pn velocities, on average. As has been noted in previous studies, high crustal temperatures are found in the western United States, particularly beneath areas of recent volcanism. In the central and eastern United States, elevated temperatures are found from southeast Texas, into the Mississippi Embayment, and up through Wisconsin.
DOI: 10.7910/dvn/1jbndc/ahthvm
title: appendixC4.R

description: :unav
DOI: 10.7910/dvn/1jbndc/ammgvw
title: appendixE.txt

description: :unav
DOI: 10.7910/dvn/1jbndc/h9ibsf
title: appendixC4_results.RData

description: :unav
DOI: 10.7910/dvn/1jbndc/jrmrk4
title: appendixC3_simulation.r

description: :unav
DOI: 10.7910/dvn/1jbndc/khzyvv
title: appendixE_MEQ.r

description: :unav
DOI: 10.7910/dvn/1jbndc/qyumxj
title: appendixC3.R

description: :unav
DOI: 10.7910/dvn/1jbndc/v0pjhk
title: appendixC1.r

description: :unav
DOI: 10.7910/dvn/1jbndc/xfenoy
title: appendixC4_simulation.R

description: :unav
DOI: 10.7910/dvn/1jbndc/xm5ghm
title: appendixC2.r

description: :unav
DOI: 10.21943/auas.10078253
title: Dataset (SPSS-file) related to "Concurrent validity and discriminative ability of Dutch performance-based motor tests in 5 to 6 years old children"

description: This dataset contains complete testing outcomes of three different motor skill tests, namely the Movement Assessment Battery for Children, the Baecke-Fassaert Motor Test, and the 4- and 8-Skills Scan.<br><br> The study sample consists of 219 primary school children of 5 to 6 years old.Testing took place at 3 schools in Amsterdam, The Netherlands.<br>Project: MAMBO (Measuring Motor Skills Primary School Amsterdam)<br><br> Because of the sensitive nature of the data, the fileset is confidential and will be shared only under strict conditions. For more information contact opensciencesupport@hva.nl.
DOI: 10.7910/dvn/1jbndc/achws1
title: appendixF.txt

description: :unav
DOI: 10.7910/dvn/1jbndc/dvwjti
title: appendixG.txt

description: :unav
DOI: 10.7910/dvn/1jbndc/dygtn7
title: appendixE_simulation_MEQ.r

description: :unav
DOI: 10.7910/dvn/1jbndc/frh5sz
title: appendixE_MEQ_out.rdata

description: :unav
DOI: 10.7910/dvn/1jbndc/sbryva
title: appendixF2.r

description: :unav
DOI: 10.7910/dvn/1jbndc/thzx8h
title: appendixE_Unique.r

description: :unav
DOI: 10.7910/dvn/1jbndc/ubjvqf
title: appendixF1.r

description: :unav
DOI: 10.7910/dvn/1jbndc/vobewr
title: appendixE_simulation_Unique.r

description: :unav
DOI: 10.7910/dvn/1jbndc/w9zowl
title: appendixE_Unique_out.rdata

description: :unav
DOI: 10.7910/dvn/1jbndc/9itjq5
title: appendixI1_CMLEoutput.Rdata

description: :unav
DOI: 10.7910/dvn/1jbndc/aj7xap
title: appendixI1_estimation.R

description: :unav
DOI: 10.7910/dvn/1jbndc/alft2j
title: appendixH.R

description: :unav
DOI: 10.7910/dvn/1jbndc/bs3dfk
title: appendixI2_estimation.R

description: :unav
DOI: 10.7910/dvn/1jbndc/hwngb2
title: appendixG.R

description: :unav
DOI: 10.7910/dvn/1jbndc/k9ee5q
title: appendixI1_output.Rdata

description: :unav
DOI: 10.7910/dvn/1jbndc/nkcpbx
title: appendixH.txt

description: :unav
DOI: 10.7910/dvn/1jbndc/pdde2a
title: appendixI.txt

description: :unav
DOI: 10.7910/dvn/1jbndc/yzbsiz
title: appendixI1_SE.R

description: :unav
DOI: 10.7910/dvn/1jbndc/0tzf1q
title: appendixI3_5yearsSE.R

description: :unav
DOI: 10.7910/dvn/1jbndc/5ldn1z
title: appendixI3_CMLEoutput_5years.Rdata

description: :unav
DOI: 10.7910/dvn/1jbndc/esn0rf
title: appendixI3_1yearsT1.R

description: :unav
DOI: 10.7910/dvn/1jbndc/ivqgrk
title: appendixI3_1yearsT1_SE.R

description: :unav
DOI: 10.7910/dvn/1jbndc/lkj3ev
title: appendixI3_1yearsT12.R

description: :unav
DOI: 10.7910/dvn/1jbndc/ogidgs
title: appendixI3_5years.R

description: :unav
DOI: 10.7910/dvn/1jbndc/tcaukl
title: appendixI3_bootstraps_1yearsT1.rdata

description: :unav
DOI: 10.7910/dvn/1jbndc/tq4twf
title: appendixI3_1yearsT12_SE.R

description: :unav
DOI: 10.5519/qd.ahl5dp78
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (5110 records)
DOI: 10.7910/dvn/1jbndc/fkfdfa
title: appendixI3_CMLEoutput_1yearsT12.Rdata

description: :unav
DOI: 10.7910/dvn/1jbndc/hvhonx
title: baseLinePlotDataMEQ.tab

description: :unav
DOI: 10.7910/dvn/1jbndc/mp5ai0
title: baseLinePlotDataUnique.tab

description: :unav
DOI: 10.7910/dvn/1jbndc/nepqcw
title: CMLE_estimation.py

description: :unav
DOI: 10.7910/dvn/1jbndc/omjobr
title: appendixI3_output_5years.Rdata

description: :unav
DOI: 10.7910/dvn/1jbndc/r56aui
title: appendixI3_output_1yearsT1.Rdata

description: :unav
DOI: 10.7910/dvn/1jbndc/tkg4xr
title: CMLE_estimation_output.rdata

description: :unav
DOI: 10.7910/dvn/1jbndc/u5uoaq
title: appendixI3_output_1yearsT12.Rdata

description: :unav
DOI: 10.7910/dvn/1jbndc/0n1qnj
title: CMLE_functions.py

description: :unav
DOI: 10.7910/dvn/1jbndc/gm4glz
title: CMLE_MonteCarlo_meq.py

description: :unav
DOI: 10.7910/dvn/1jbndc/hsbg4b
title: CMLE_MonteCarlo_unique_support.py

description: :unav
DOI: 10.7910/dvn/1jbndc/iizijq
title: CMLE_MonteCarlo_unique.py

description: :unav
DOI: 10.7910/dvn/1jbndc/ov2qxr
title: CMLE_MonteCarlo_meq_support.r

description: :unav
DOI: 10.7910/dvn/1jbndc/t8gtrq
title: CMLE_functions.R

description: :unav
DOI: 10.7910/dvn/1jbndc/yeg4sr
title: CMLE_MonteCarlo_meq_support.py

description: :unav
DOI: 10.7910/dvn/1jbndc/ze4rum
title: CMLE_estimation_support.R

description: :unav
DOI: 10.7910/dvn/1jbndc/zto8ws
title: CMLE_meq.rdata

description: :unav
DOI: 10.7910/dvn/1jbndc/18k0hd
title: CMLE_sanctionsMC.py

description: :unav
DOI: 10.7910/dvn/1jbndc/bdbe00
title: CMLE_sanctionsMC_support.py

description: :unav
DOI: 10.7910/dvn/1jbndc/ci6rrc
title: CMLE_sanctionsMC_support.r

description: :unav
DOI: 10.7910/dvn/1jbndc/dqybw1
title: CMLE_sanctions_5years_support.R

description: :unav
DOI: 10.7910/dvn/1jbndc/ifkhab
title: CMLE_sanctions_1yearsT12.py

description: :unav
DOI: 10.7910/dvn/1jbndc/kfhyzm
title: CMLE_sanctionsMC.rdata

description: :unav
DOI: 10.7910/dvn/1jbndc/krmj4v
title: CMLE_sanctions_5years.py

description: :unav
DOI: 10.7910/dvn/1jbndc/lywnow
title: CMLE_MonteCarlo_unique_support.r

description: :unav
DOI: 10.7910/dvn/1jbndc/nvrtnd
title: CMLE_sanctions_1yearsT12_support.R

description: :unav
DOI: 10.7910/dvn/1jbndc/2g4n01
title: CMLE_unstable_support.r

description: :unav
DOI: 10.7910/dvn/1jbndc/5zcdjo
title: comparativeStatics.R

description: :unav
DOI: 10.7910/dvn/1jbndc/eu5vsg
title: eqGraph.r

description: :unav
DOI: 10.7910/dvn/1jbndc/hrfwtv
title: CMLE_unstable.rdata

description: :unav
DOI: 10.7910/dvn/1jbndc/l5w9bh
title: CMLE_sanctionsQuarters.py

description: :unav
DOI: 10.7910/dvn/1jbndc/o1feaz
title: CMLE_sanctionsQuarters_support.R

description: :unav
DOI: 10.7910/dvn/1jbndc/qnujpl
title: CMLE_setup.sh

description: :unav
DOI: 10.7910/dvn/1jbndc/qz5s4m
title: CMLE_unique.rdata

description: :unav
DOI: 10.7910/dvn/1jbndc/y3dzc5
title: CMLE_unstable_support.py

description: :unav
DOI: 10.7910/dvn/1jbndc/6un6ds
title: estimation.R

description: :unav
DOI: 10.7910/dvn/1jbndc/ddpjuk
title: figure3.pdf

description: :unav
DOI: 10.7910/dvn/1jbndc/dfuvmf
title: estimationLog.txt

description: :unav
DOI: 10.7910/dvn/1jbndc/gh3u4w
title: figure6.pdf

description: :unav
DOI: 10.7910/dvn/1jbndc/j0tx2r
title: figure8.pdf

description: :unav
DOI: 10.7910/dvn/1jbndc/mslcnn
title: figure4.pdf

description: :unav
DOI: 10.7910/dvn/1jbndc/mxck1s
title: estimation_output.Rdata

description: :unav
DOI: 10.7910/dvn/1jbndc/p6sjey
title: figure2.pdf

description: :unav
DOI: 10.7910/dvn/1jbndc/bfli62
title: figure10.pdf

description: :unav
DOI: 10.7910/dvn/1jbndc/dxvlzg
title: figure17.pdf

description: :unav
DOI: 10.7910/dvn/1jbndc/h23oni
title: figure14.pdf

description: :unav
DOI: 10.7910/dvn/1jbndc/npvqoe
title: figure12.pdf

description: :unav
DOI: 10.7910/dvn/1jbndc/ormbq4
title: figure11.pdf

description: :unav
DOI: 10.7910/dvn/1jbndc/rq7fqp
title: figure16.pdf

description: :unav
DOI: 10.7910/dvn/1jbndc/sj8q9c
title: figure9.pdf

description: :unav
DOI: 10.7910/dvn/1jbndc/tibw2e
title: figure15.pdf

description: :unav
DOI: 10.7910/dvn/1jbndc/zds0ca
title: figure13.pdf

description: :unav
DOI: 10.7910/dvn/1jbndc/4jjbcy
title: figure22.pdf

description: :unav
DOI: 10.7910/dvn/1jbndc/eugzth
title: figure19.pdf

description: :unav
DOI: 10.7910/dvn/1jbndc/juvgjl
title: gradientFunctions.r

description: :unav
DOI: 10.7910/dvn/1jbndc/kvsdvi
title: figure20.pdf

description: :unav
DOI: 10.7910/dvn/1jbndc/lhfyah
title: figure23.pdf

description: :unav
DOI: 10.7910/dvn/1jbndc/mocrsh
title: figure18.pdf

description: :unav
DOI: 10.7910/dvn/1jbndc/nahucz
title: install_Rpackages_noadmin.r

description: :unav
DOI: 10.7910/dvn/1jbndc/pro3el
title: figure24.pdf

description: :unav
DOI: 10.7910/dvn/1jbndc/zst2qy
title: figure21.pdf

description: :unav
DOI: 10.5281/zenodo.3523232
title: Case study test system datasheet

description: This is the datasheet for the examined 30-unit test system including 14 DG (indexed from 1 to 14), 4 IG (indexed from 15 to 18), 4 FD (indexed from 19 to 22), 4 ID (indexed from 23 to 26), and 4 ES units (indexed from 27 to 30).
DOI: 10.7910/dvn/1jbndc/b5xocp
title: MonteCarloResults_MEQ.rdata

description: :unav
DOI: 10.7910/dvn/1jbndc/i0sa6s
title: MonteCarloUnique.r

description: :unav
DOI: 10.7910/dvn/1jbndc/jeln4b
title: MonteCarloResults_Unique.rdata

description: :unav
DOI: 10.7910/dvn/1jbndc/mmhruq
title: MonteCarloLog.txt

description: :unav
DOI: 10.7910/dvn/1jbndc/vblom9
title: MonteCarloUnstable.rdata

description: :unav
DOI: 10.7910/dvn/1jbndc/wasbjq
title: MonteCarloMEQ.r

description: :unav
DOI: 10.7910/dvn/1jbndc/x9if7n
title: MonteCarloCMLE_unstable.py

description: :unav
DOI: 10.7910/dvn/1jbndc/1xccyl
title: replicateAppendixC.sh

description: :unav
DOI: 10.7910/dvn/1jbndc/1xwvoe
title: readme.txt

description: :unav
DOI: 10.7910/dvn/1jbndc/dpv5tt
title: replicateAppendixF.sh

description: :unav
DOI: 10.7910/dvn/1jbndc/iua2xa
title: replicateAppendixE.sh

description: :unav
DOI: 10.7910/dvn/1jbndc/m7hs4p
title: readme.md

description: :unav
DOI: 10.7910/dvn/1jbndc/ulzf6o
title: replicateAppendixH.sh

description: :unav
DOI: 10.7910/dvn/1jbndc/wit7mb
title: parmap.py

description: :unav
DOI: 10.7910/dvn/1jbndc/xiy01s
title: replicateAppendixG.sh

description: :unav
DOI: 10.7910/dvn/1jbndc/ydobuh
title: readme.pdf

description: :unav
DOI: 10.7910/dvn/1jbndc/0yofsw
title: sigInt_0.0.0.9000.tar.gz

description: :unav
DOI: 10.7910/dvn/1jbndc/aoycgw
title: replicateAppendixI.sh

description: :unav
DOI: 10.7910/dvn/1jbndc/hitvdf
title: replicateSanctions.sh

description: :unav
DOI: 10.7910/dvn/1jbndc/msz4oq
title: SanctionsDataSet_prelevant.tab

description: :unav
DOI: 10.7910/dvn/1jbndc/nkwzea
title: SanctionsDataSet.tab

description: :unav
DOI: 10.7910/dvn/1jbndc/nxwmdm
title: replicateMonteCarlos.sh

description: :unav
DOI: 10.7910/dvn/1jbndc/pamgz7
title: SanctionsDataSet_quarterly.tab

description: :unav
DOI: 10.7910/dvn/1jbndc/spfda8
title: SanctionsDataSet_1yearsT12.tab

description: :unav
DOI: 10.7910/dvn/1jbndc/z7cgdw
title: SanctionsDataSet_1yearsT1.rdata

description: :unav
DOI: 10.7910/dvn/1jbndc/zmvsbw
title: SanctionsDataSet_5years.tab

description: :unav
DOI: 10.7910/dvn/1jbndc/1svvrp
title: SIGMA_1yearsT12.rdata

description: :unav
DOI: 10.7910/dvn/1jbndc/drqjch
title: SIGMA.rdata

description: :unav
DOI: 10.7910/dvn/1jbndc/nb4ge3
title: standardErrors.R

description: :unav
DOI: 10.7910/dvn/1jbndc/nneqf8
title: SIGMA_quarters.rdata

description: :unav
DOI: 10.7910/dvn/1jbndc/qmhqz1
title: signalingFunctions_main.r

description: :unav
DOI: 10.7910/dvn/1jbndc/r2xnux
title: SIGMA_5year.rdata

description: :unav
DOI: 10.5281/zenodo.3523236
title: Case Study Test System Datasheet

description: This is the datasheet for the examined 30-unit test system including 14 DG (indexed from 1 to 14), 4 IG (indexed from 15 to 18), 4 FD (indexed from 19 to 22), 4 ID (indexed from 23 to 26), and 4 ES units (indexed from 27 to 30).
DOI: 10.5519/qd.9kjx6q31
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (1672 records)
DOI: 10.18112/openneuro.ds002286.v1.0.0
title: AVLearn
DOI: 10.5281/zenodo.3522452
title: Data for "On data reduction methods for volcanic tremor characterization: The 2012 eruption of Copahue volcano, Southern Andes"

description: mseed.tar.gz contains the raw data of the CNA station in MiniSeed for Z, E, and N channels. DRM.tar.gz contains processed data in HDF format. reports.tar.gz contains the OVDAS reports (in Spanish).
DOI: 10.5519/qd.j1s356zj
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (1842 records)
DOI: 10.5519/qd.409tsavo
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (43 records)
DOI: 10.5281/zenodo.3523212
title: Supplementary data: Hazard from Himalyan glacier lake outburst floods

description: We provide supplementary data to the manuscript by <strong>Veh, G., Korup, O., and Walz A.: "Hazard from Himalayan glacier lake outburst floods".</strong> These datasets (file ending .rds) are ready to use within the R software for statistical programming. Please copy all files into one single directory and follow the instructions given in the scripts. You can find the following scripts on the associated Github page: <strong>https://github.com/geveh/GLOFhazard</strong> bayes_lm_piecewise_regression_stan.R lm_piecewise_const.stan R_Script_lake_area_vs_max_depth.R R_Script_Hazard_from_GLOFs_PNAS_supp.R HDIofMCMC.R Outputs within the scripts are written to disk, again as R-objects, if not suppressed by the user. Make sure you have at least 100 GB of free disk space.
description: {"references": ["S. B. Maharjan, et al., The status of glacial lakes in the Hindu Kush Himalaya-ICIMOD Research Report 2018/1 (2018). ICIMOD Res. Rep. (2018).", "J. E. O'Connor, R. A. Beebee, \"Floods from natural rock-material dams\" in Megaflooding on Earth and Mars, D. M. Burr, P. A. Carling, V. R. Baker, Eds. (Cambridge University Press, 2009), pp. 128\u2013171.", "J. S. Walder, J. E. O'Connor, Methods for predicting peak discharge of floods caused by failure of natural and constructed earthen dams. Water Resour. Res. 33, 2337\u20132348 (1997).", "J. K. Kruschke, Doing Bayesian Data Analysis: A Tutorial with R, JAGS, and Stan. 2nd Edition. Academic Press / Elsevier (2014)."]}
DOI: 10.5281/zenodo.3523213
title: Supplementary data: Hazard from Himalyan glacier lake outburst floods

description: We provide supplementary data to the manuscript by <strong>Veh, G., Korup, O., and Walz A.: "Hazard from Himalayan glacier lake outburst floods".</strong> These datasets (file ending .rds) are ready to use within the R software for statistical programming. Please copy all files into one single directory and follow the instructions given in the scripts. You can find the following scripts on the associated Github page: <strong>https://github.com/geveh/GLOFhazard</strong> bayes_lm_piecewise_regression_stan.R lm_piecewise_const.stan R_Script_lake_area_vs_max_depth.R R_Script_Hazard_from_GLOFs_PNAS_supp.R HDIofMCMC.R Outputs within the scripts are written to disk, again as R-objects, if not suppressed by the user. Make sure you have at least 100 GB of free disk space.
description: {"references": ["S. B. Maharjan, et al., The status of glacial lakes in the Hindu Kush Himalaya-ICIMOD Research Report 2018/1 (2018). ICIMOD Res. Rep. (2018).", "J. E. O'Connor, R. A. Beebee, \"Floods from natural rock-material dams\" in Megaflooding on Earth and Mars, D. M. Burr, P. A. Carling, V. R. Baker, Eds. (Cambridge University Press, 2009), pp. 128\u2013171.", "J. S. Walder, J. E. O'Connor, Methods for predicting peak discharge of floods caused by failure of natural and constructed earthen dams. Water Resour. Res. 33, 2337\u20132348 (1997).", "J. K. Kruschke, Doing Bayesian Data Analysis: A Tutorial with R, JAGS, and Stan. 2nd Edition. Academic Press / Elsevier (2014)."]}
DOI: 10.18119/n9259j
title: Fusarium graminearum PHI-net - whole network
DOI: 10.18119/n9xg68
title: Botrytis cinerea PHI-net - whole network
DOI: 10.5281/zenodo.3522493
title: Data for "A Random Walk" manuscript

description: "GO D-G/" includes gene-annotation bipartite graph "LINCS D-G/" includes gene-drug bipartite graph "LINCS G-G/" includes gene-gene co-expression graph for LINCS cell line data "scRNA G-G/" includes gene-gene co-expression graph for single-cell data
DOI: 10.5281/zenodo.3522494
title: Data for "A Random Walk" manuscript

description: "GO D-G/" includes gene-annotation bipartite graph "LINCS D-G/" includes gene-drug bipartite graph "LINCS G-G/" includes gene-gene co-expression graph for LINCS cell line data "scRNA G-G/" includes gene-gene co-expression graph for single-cell data
DOI: 10.5281/zenodo.3523242
title: CCLM outputs Parameters Sensitivity Investigation Central Asia and Europe

description: Monthly values of 2-meter temperature (T2M), total precipitation (TOT_PREC) and total cloud cover (CLCT) derived from the simulations performed with the Regional Climate Model COSMO-CLM (Roeckel et al. 2008) for the CORDEX Central Asia and Europe Domains, used for the paper "Exploring the Parameters Space of the Regional Climate Model COSMO-CLM 5.0 for the CORDEX Central Asia Domain" by RUSSO et al. (geoscientific model development), submitted for the first time on the 31st of October 2019. The data have a spatial resolution of ~25 km. The data cover mainly the year 2000. These are the sensitivity simulations, initialized on the 01.01.2000 using a restart file derived from the reference simulations for the two domains (ncep022_test_belprat1 and europe_test_belprat1) also provided here. For some realization, a file covering the period 1996-2005 is also present. These data are used to assess the model internal variability over the considered period.
DOI: 10.7910/dvn/v3llle/cf5loj
title: Código de programação - Artigo BPSR.do

description: :unav
DOI: 10.7910/dvn/v3llle/gkadxi
title: Livro de Códigos - 14.06.2019.doc

description: :unav
DOI: 10.7910/dvn/v3llle/koh0mq
title: Material suplementar - analise (1).R

description: :unav
DOI: 10.7910/dvn/v3llle/mf7cko
title: BD_survive - recortada_final.tab

description: :unav
DOI: 10.7910/dvn/v3llle/vkv6se
title: Survival_analysis - BPSR.tab

description: :unav
DOI: 10.7910/dvn/v3llle/yvfxoj
title: BD_survive - recortada_final.csv

description: :unav
DOI: 10.5281/zenodo.3523248
title: travispark/Odontocete-inner-ear-convergence v1.0.0

description: Zenodo activation release
DOI: 10.5281/zenodo.3523249
title: travispark/Odontocete-inner-ear-convergence v1.0.0

description: Zenodo activation release
DOI: 10.5281/zenodo.3522834
title: Non-spherical particles in optical tweezers: a numerical solution

description: We present numerical methods for modeling the dynamics of arbitrarily shaped particles trapped within optical tweezers, which improve the predictive power of numerical simulations for practical use. We study the dependence of trapping on the shape and size of particles in a single continuous wave beam setup. We also consider the implications of different particle compositions, beam types and media. The major result of the study is that for different irregular particle shapes, a range of beam powers generally leads to trapping. The trapping power range depends on whether the particle can be characterized as elongated or flattened, and the range is also limited by Brownian forces. This dataset supplements the publication and contains inputs and processing scripts for usage of scadyn (https://www.github.com/jherrane/scadyn) software for solving dynamical response of arbitrarily shaped particles in electromagnetic fields. Also is contained the minimal dataset (per PLos ONE standards) to reproduce the results presented.
DOI: 10.5281/zenodo.3522835
title: Non-spherical particles in optical tweezers: a numerical solution

description: We present numerical methods for modeling the dynamics of arbitrarily shaped particles trapped within optical tweezers, which improve the predictive power of numerical simulations for practical use. We study the dependence of trapping on the shape and size of particles in a single continuous wave beam setup. We also consider the implications of different particle compositions, beam types and media. The major result of the study is that for different irregular particle shapes, a range of beam powers generally leads to trapping. The trapping power range depends on whether the particle can be characterized as elongated or flattened, and the range is also limited by Brownian forces. This dataset supplements the publication and contains inputs and processing scripts for usage of scadyn (https://www.github.com/jherrane/scadyn) software for solving dynamical response of arbitrarily shaped particles in electromagnetic fields. Also is contained the minimal dataset (per PLos ONE standards) to reproduce the results presented.
DOI: 10.7910/dvn/jceoqj/s5gsxn
title: SIPSIN_Effect of intercropping forages with maize in conventional tillage and conservation agriculture .tab

description: :unav
DOI: 10.25345/c58q20
title: MassIVE MSV000084516 - Mass spec for PTPN22 recombinant protein purified from 293T cells
title: protein was purified from 293T cells treated with Calyculin A and eluted by FLAG tag peptide
DOI: 10.7910/dvn/xs9hso/2ok4cs
title: Job1031-4-banco cliente-final.tab

description: :unav
DOI: 10.7910/dvn/xs9hso/2yicrf
title: World Cup and Presidential Popularity.do

description: :unav
DOI: 10.7910/dvn/xs9hso/55vlax
title: Graficos revisao.tab

description: :unav
DOI: 10.7910/dvn/xs9hso/d3ie3e
title: Codebook and data dictionary.pdf

description: :unav
DOI: 10.7910/dvn/xs9hso/ut40am
title: ead_monthly_app_1.0 - with DATE.tab

description: :unav
DOI: 10.26300/41y9-ts23
title: Source code and data for "Can we use sea surface temperature and productivity proxy records to reconstruct Ekman Upwelling?"