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LTER-Italy site Lago di Garda figure
<p>Geographical representation of the LTER-Italy site Lago di Garda (LTER_EU_IT_044) - DEIMS-ID <a href="https://deims.org/c713db56-373c-46cc-8828-ce8cadc4f3bb">https://deims.org/c713db56-373c-46cc-8828-ce8cadc4f3bb</a></p>
LTER-Italy site Lago di Orta figure
<p>Geographical representation of the LTER-Italy site Lago di Orta (LTER_EU_IT_042) - DEIMS-ID <a href="https://deims.org/8bd7d2f8-421a-48bd-b212-04bc1e9f31d5">https://deims.org/8bd7d2f8-421a-48bd-b212-04bc1e9f31d5</a></p>
LTER-Italy site Val Masino LOM1 figure
<p>Geographical representation of the LTER-Italy site Val Masino LOM1 (LTER_EU_IT_028) - DEIMS-ID <a href="https://deims.org/68a5673c-9172-48cc-88e5-b9408b203309">https://deims.org/68a5673c-9172-48cc-88e5-b9408b203309</a></p>
Last interglacial sea-level index points in the Western Mediterranean
<p>Sea-level index points, dated samples and correlated metadata for the Western Mediterranean. This dataset was assembled in the framework of the World Atlas of Last Interglacial Shorelines. Field descriptors are available at: https://walis-help.readthedocs.io/en/latest/</p> <p>See readme files for updates with respect to version 2.0</p>
The LYT dataset for 45Sc1H
The dataset is an archive of ExoMol page, https://exomol.com/data/molecules/ScH/45Sc-1H/LYT.<br> Please check the reference details according to the following description or directly from the website.<br><br>Definitions file:<br>45Sc-1H__LYT.def<br>Root references for ExoMol database: <br> 1. J. Tennyson, S.N. Yurchenko A.F. Al-Refaie, V.H.J. Clark, K.L. Chubb,E.K. Conway, A. Dewan, M.N. Gorman, C. Hill, A.E. Lynas-Gray, T. Mellor, L.K. McKemmish, A. Owens, O.L. Polyansky, M. Semenov, W. Somogyi, G. Tinetti, A. Upadhyay, I. Waldmann, Y. Wang, S. Wright and O.P. Yurchenko, The 2020 release of the ExoMol database: molecular line lists for exoplanet and other hot atmospheres, J. Quant. Spectrosc. Rad. Transf., 255, 107228 (2020).[https://doi.org/10.1016/j.jqsrt.2020.107228.]<br><br>LYT: line list<br>The calculated rovibronic spectrum of scandium hydride:<br> 45Sc-1H__LYT.states.bz2<br> Labelled rovibrational states of ScH<br> 45Sc-1H__LYT.trans.bz2<br> Frequency ordered transitions for ScH<br> README_LYT.txt<br> Documentation for the LYT line list for ScH<br>References:<br><br>LYT: partition function<br>The calculated rovibronic spectrum of scandium hydride:<br> 45Sc-1H__LYT.pf<br> Partition function for ScH<br> README_LYT.txt<br> Documentation for the LYT line list for ScH<br>References:<br><br>LYT: opacity<br>The calculated rovibronic spectrum of scandium hydride:<br> 45Sc-1H__LYT.R1000_0.3-50mu.ktable.ARCiS.fits.gz<br> ARCiS k-tables at R= 1000 (0.3-50mu) in fits format (gzipped): LYT (45Sc)(1H) line list.<br> 45Sc-1H__LYT.R1000_0.3-50mu.ktable.petitRADTRANS.h5<br> petitRADTRANS k-tables at R= 1000 (0.3-50mu) in HDF5 format: LYT (45Sc)(1H) line list.<br> 45Sc-1H__LYT.R1000_0.3-50mu.ktable.NEMESIS.kta<br> NEMESIS k-tables at R= 1000 (0.3-50mu) in NEMESIS-kta format: LYT (45Sc)(1H) line list.<br> 45Sc-1H__LYT.R15000_0.3-50mu.xsec.TauREx.h5<br> TauREx k-tables at R= 15000 (0.3-50mu) in HDF5 format: LYT (45Sc)(1H) line list.<br>References:<br> 1. Lodi, L., Yurchenko, S. N., Tennyson, J., "The calculated rovibronic spectrum of scandium hydride, ScH", Molecular Physics 113, 1998-2011 (2015). [http://dx.doi.org/10.1080/00268976.2015.1029996][15LoYuTe.ScH]<br> 2. Chubb, K. L., Rocchetto, M., Yurchenko, S. N., Min, M., Waldmann, I., Barstow, J. K., Molliere, P., Al-Refaie, A. F, Phillips, M. W., Tennyson, J., "The ExoMolOP database: Cross sections and k-tables for molecules of interest in high-temperature exoplanet atmospheres", Astronomy and Astrophysics 646, A21 (2020). [http://dx.doi.org/10.1051/0004-6361/202038350][20ChRoYu.]<br>
The Rivlin dataset for 23Na1H
The dataset is an archive of ExoMol page, https://exomol.com/data/molecules/NaH/23Na-1H/Rivlin.<br> Please check the reference details according to the following description or directly from the website.<br><br>Definitions file:<br>23Na-1H__Rivlin.def<br>Root references for ExoMol database: <br> 1. J. Tennyson, S.N. Yurchenko A.F. Al-Refaie, V.H.J. Clark, K.L. Chubb,E.K. Conway, A. Dewan, M.N. Gorman, C. Hill, A.E. Lynas-Gray, T. Mellor, L.K. McKemmish, A. Owens, O.L. Polyansky, M. Semenov, W. Somogyi, G. Tinetti, A. Upadhyay, I. Waldmann, Y. Wang, S. Wright and O.P. Yurchenko, The 2020 release of the ExoMol database: molecular line lists for exoplanet and other hot atmospheres, J. Quant. Spectrosc. Rad. Transf., 255, 107228 (2020).[https://doi.org/10.1016/j.jqsrt.2020.107228.]<br><br>Rivlin: line list<br>Line lists for NaH and NaD:<br> Rivlin_README.txt<br> Documentation for the NaH line lists of the Rivlin dataset<br> 23Na-1H__Rivlin.states.bz2<br> Labelled rovibrational states of (23Na)(1H)<br> 23Na-1H__Rivlin.trans.bz2<br> Frequency ordered transitions of (23Na)(1H)<br>References:<br> 1. Rivlin, T., Lodi, L., Yurchenko, S. N., Tennyson, J., Le Roy, R. J., "ExoMol molecular line lists X: The spectrum of sodium hydride", Monthly Notices of the Royal Astronomical Society 451, 5153-5157 (2015). [http://dx.doi.org/10.1093/mnras/stv979][15RiLoYu.NaH]<br><br>Rivlin: partition function<br>Line lists for NaH and NaD:<br> Rivlin_README.txt<br> Documentation for the NaH line lists of the Rivlin dataset<br> 23Na-1H__Rivlin.pf<br> Partition function for (23Na)(1H)<br>References:<br> 1. Rivlin, T., Lodi, L., Yurchenko, S. N., Tennyson, J., Le Roy, R. J., "ExoMol molecular line lists X: The spectrum of sodium hydride", Monthly Notices of the Royal Astronomical Society 451, 5153-5157 (2015). [http://dx.doi.org/10.1093/mnras/stv979][15RiLoYu.NaH]<br><br>Rivlin: opacity<br>Line lists for NaH and NaD:<br> 23Na-1H__Rivlin.R1000_0.3-50mu.ktable.ARCiS.fits.gz<br> ARCiS k-tables at R= 1000 (0.3-50mu) in fits format (gzipped): Rivlin (23Na)(1H) line list.<br> 23Na-1H__Rivlin.R1000_0.3-50mu.ktable.petitRADTRANS.h5<br> petitRADTRANS k-tables at R= 1000 (0.3-50mu) in HDF5 format: Rivlin (23Na)(1H) line list.<br> 23Na-1H__Rivlin.R1000_0.3-50mu.ktable.NEMESIS.kta<br> NEMESIS k-tables at R= 1000 (0.3-50mu) in NEMESIS-kta format: Rivlin (23Na)(1H) line list.<br> 23Na-1H__Rivlin.R15000_0.3-50mu.xsec.TauREx.h5<br> TauREx k-tables at R= 15000 (0.3-50mu) in HDF5 format: Rivlin (23Na)(1H) line list.<br>References:<br> 1. Rivlin, T., Lodi, L., Yurchenko, S. N., Tennyson, J., Le Roy, R. J., "ExoMol molecular line lists X: The spectrum of sodium hydride", Monthly Notices of the Royal Astronomical Society 451, 5153-5157 (2015). [http://dx.doi.org/10.1093/mnras/stv979][15RiLoYu.NaH]<br> 2. Chubb, K. L., Rocchetto, M., Yurchenko, S. N., Min, M., Waldmann, I., Barstow, J. K., Molliere, P., Al-Refaie, A. F, Phillips, M. W., Tennyson, J., "The ExoMolOP database: Cross sections and k-tables for molecules of interest in high-temperature exoplanet atmospheres", Astronomy and Astrophysics 646, A21 (2020). [http://dx.doi.org/10.1051/0004-6361/202038350][20ChRoYu.]<br>
The CLT dataset for 7Li1H
The dataset is an archive of ExoMol page, https://exomol.com/data/molecules/LiH/7Li-1H/CLT.<br> Please check the reference details according to the following description or directly from the website.<br><br>Definitions file:<br>7Li-1H__CLT.def<br>Root references for ExoMol database: <br> 1. J. Tennyson, S.N. Yurchenko A.F. Al-Refaie, V.H.J. Clark, K.L. Chubb,E.K. Conway, A. Dewan, M.N. Gorman, C. Hill, A.E. Lynas-Gray, T. Mellor, L.K. McKemmish, A. Owens, O.L. Polyansky, M. Semenov, W. Somogyi, G. Tinetti, A. Upadhyay, I. Waldmann, Y. Wang, S. Wright and O.P. Yurchenko, The 2020 release of the ExoMol database: molecular line lists for exoplanet and other hot atmospheres, J. Quant. Spectrosc. Rad. Transf., 255, 107228 (2020).[https://doi.org/10.1016/j.jqsrt.2020.107228.]<br><br>CLT: line list<br>The CLT data set for line lists and cooling functions of HD+, LiH and LiH+:<br> 7Li-1H__CLT.states.bz2<br> Energy levels file for the CLT line list for (7Li)(1H)<br> 7Li-1H__CLT.trans.bz2<br> Transitions file for the CLT line list for (7Li)(1H)<br>References:<br> 1. Coppola, C. M., Lodi, L., Tennyson, J., "Radiative cooling functions for primordial molecules", Monthly Notices of the Royal Astronomical Society 415, 487-493 (2011). [http://dx.doi.org/10.1111/j.1365-2966.2011.18723.x][11CoLiTe.LiH+]<br><br>CLT: cooling function<br>The CLT data set for line lists and cooling functions of HD+, LiH and LiH+:<br> 7Li-1H__CLT.cf<br> Cooling function for (7Li)(1H) from the CLT data set<br>References:<br> 1. Coppola, C. M., Lodi, L., Tennyson, J., "Radiative cooling functions for primordial molecules", Monthly Notices of the Royal Astronomical Society 415, 487-493 (2011). [http://dx.doi.org/10.1111/j.1365-2966.2011.18723.x][11CoLiTe.LiH+]<br><br>CLT: partition function<br>The CLT data set for line lists and cooling functions of HD+, LiH and LiH+:<br> 7Li-1H__CLT.pf<br> Partition function for (7Li)(1H) from the CLT data set<br>References:<br> 1. Coppola, C. M., Lodi, L., Tennyson, J., "Radiative cooling functions for primordial molecules", Monthly Notices of the Royal Astronomical Society 415, 487-493 (2011). [http://dx.doi.org/10.1111/j.1365-2966.2011.18723.x][11CoLiTe.LiH+]<br><br>CLT: opacity<br>The CLT data set for line lists and cooling functions of HD+, LiH and LiH+:<br> 7Li-1H__CLT.R1000_0.3-50mu.ktable.ARCiS.fits.gz<br> ARCiS k-tables at R= 1000 (0.3-50mu) in fits format (gzipped): CLT (7Li)(1H) line list.<br> 7Li-1H__CLT.R1000_0.3-50mu.ktable.petitRADTRANS.h5<br> petitRADTRANS k-tables at R= 1000 (0.3-50mu) in HDF5 format: CLT (7Li)(1H) line list.<br> 7Li-1H__CLT.R1000_0.3-50mu.ktable.NEMESIS.kta<br> NEMESIS k-tables at R= 1000 (0.3-50mu) in NEMESIS-kta format: CLT(7Li)(1H) line list.<br> 7Li-1H__CLT.R15000_0.3-50mu.xsec.TauREx.h5<br> TauREx k-tables at R= 15000 (0.3-50mu) in HDF5 format: CLT (7Li)(1H) line list.<br>References:<br> 1. Coppola, C. M., Lodi, L., Tennyson, J., "Radiative cooling functions for primordial molecules", Monthly Notices of the Royal Astronomical Society 415, 487-493 (2011). [http://dx.doi.org/10.1111/j.1365-2966.2011.18723.x][11CoLiTe.LiH+]<br> 2. Chubb, K. L., Rocchetto, M., Yurchenko, S. N., Min, M., Waldmann, I., Barstow, J. K., Molliere, P., Al-Refaie, A. F, Phillips, M. W., Tennyson, J., "The ExoMolOP database: Cross sections and k-tables for molecules of interest in high-temperature exoplanet atmospheres", Astronomy and Astrophysics 646, A21 (2020). [http://dx.doi.org/10.1051/0004-6361/202038350][20ChRoYu.]<br>
The MoLLIST dataset for 40Ca1H
The dataset is an archive of ExoMol page, https://exomol.com/data/molecules/CaH/40Ca-1H/MoLLIST.<br> Please check the reference details according to the following description or directly from the website.<br><br>Definitions file:<br>40Ca-1H__MoLLIST.def<br>Root references for ExoMol database: <br> 1. J. Tennyson, S.N. Yurchenko A.F. Al-Refaie, V.H.J. Clark, K.L. Chubb,E.K. Conway, A. Dewan, M.N. Gorman, C. Hill, A.E. Lynas-Gray, T. Mellor, L.K. McKemmish, A. Owens, O.L. Polyansky, M. Semenov, W. Somogyi, G. Tinetti, A. Upadhyay, I. Waldmann, Y. Wang, S. Wright and O.P. Yurchenko, The 2020 release of the ExoMol database: molecular line lists for exoplanet and other hot atmospheres, J. Quant. Spectrosc. Rad. Transf., 255, 107228 (2020).[https://doi.org/10.1016/j.jqsrt.2020.107228.]<br><br>MoLLIST: line list (external)<br>Empirical Diatomic line lists MoLLIST from Bernath lab (bernath.uwaterloo.ca) in standard ExoMol format [Tennyson and Yurchenko (2016)]:<br> 40Ca-1H__MoLLIST.states.bz2<br> MoLLIST (40Ca)(1H) external line list states file<br> 40Ca-1H__MoLLIST.trans.bz2<br> MoLLIST (40Ca)(1H) external line list transition file<br>References:<br> 1. Li, G., Harrison, J. J., Ram, R. S., Western, C. M., Bernath, P. F., "Einstein A coefficients and absolute line intensities for the E 2Π – X 2S+ transition of CaH", Journal of Quantitative Spectroscopy and Radiative Transfer 113, 67-74 (2012). [http://dx.doi.org/10.1016/j.jqsrt.2011.09.010][12LiHaRa.CaH]<br> 2. Shayesteh, A., Walker, K. A., Gordon, I., Appadoo, D. R. T., Bernath, P. F., "New Fourier transform infrared emission spectra of CaH and SrH: combined isotopomer analyses with CaD and SrD", Journal of Molecular Structure: THEOCHEM 695, 23-37 (2004). [http://dx.doi.org/10.1016/j.molstruc.2003.11.001][04ShWaGo.CaH]<br> 3. Alavi, S. F., Shayesteh, A., "Einstein A coefficients for rovibronic lines of the A 2Π → X 2Σ+ and B 2Σ+ → X 2Σ+ transitions of CaH and CaD", Monthly Notices of the Royal Astronomical Society 474, 2-11 (2017). [https://doi.org/10.1093/mnras/stx2681][17AlShxx.CaH]<br> 4. Bernath, P.F., "MoLLIST: Molecular Line Lists, Intensities and Spectra", Journal of Quantitative Spectroscopy and Radiative Transfer 240, 106687 (2020). [https://doi.org/10.1016/j.jqsrt.2019.106687]<br><br>MoLLIST: partition function (external)<br>Empirical Diatomic line lists MoLLIST from Bernath lab (bernath.uwaterloo.ca) in standard ExoMol format [Tennyson and Yurchenko (2016)]:<br> 40Ca-1H__MoLLIST.pf<br> MoLLIST (40Ca)(1H) external line list partition function<br>References:<br> 1. Li, G., Harrison, J. J., Ram, R. S., Western, C. M., Bernath, P. F., "Einstein A coefficients and absolute line intensities for the E 2Π – X 2S+ transition of CaH", Journal of Quantitative Spectroscopy and Radiative Transfer 113, 67-74 (2012). [http://dx.doi.org/10.1016/j.jqsrt.2011.09.010][12LiHaRa.CaH]<br> 2. Bernath, P.F., "MoLLIST: Molecular Line Lists, Intensities and Spectra", Journal of Quantitative Spectroscopy and Radiative Transfer 240, 106687 (2020). [https://doi.org/10.1016/j.jqsrt.2019.106687]<br><br>MoLLIST: opacity<br>Empirical Diatomic line lists MoLLIST from Bernath lab (bernath.uwaterloo.ca) in standard ExoMol format [Tennyson and Yurchenko (2016)]:<br> 40Ca-1H__MoLLIST.R1000_0.3-50mu.ktable.ARCiS.fits.gz<br> ARCiS k-tables at R= 1000 (0.3-50mu) in fits format (gzipped): MoLLIST (40Ca)(1H) line list.<br> 40Ca-1H__MoLLIST.R1000_0.3-50mu.ktable.petitRADTRANS.h5<br> petitRADTRANS k-tables at R= 1000 (0.3-50mu) in HDF5 format: MoLLIST (40Ca)(1H) line list.<br> 40Ca-1H__MoLLIST.R1000_0.3-50mu.ktable.NEMESIS.kta<br> NEMESIS k-tables at R= 1000 (0.3-50mu) in NEMESIS-kta format: MoLLIST (40Ca)(1H) line list.<br> 40Ca-1H__MoLLIST.R15000_0.3-50mu.xsec.TauREx.h5<br> TauREx k-tables at R= 15000 (0.3-50mu) in HDF5 format: MoLLIST (40Ca)(1H) line list.<br>References:<br> 1. Li, G., Harrison, J. J., Ram, R. S., Western, C. M., Bernath, P. F., "Einstein A coefficients and absolute line intensities for the E 2Π – X 2S+ transition of CaH", Journal of Quantitative Spectroscopy and Radiative Transfer 113, 67-74 (2012). [http://dx.doi.org/10.1016/j.jqsrt.2011.09.010][12LiHaRa.CaH]<br> 2. Bernath, P.F., "MoLLIST: Molecular Line Lists, Intensities and Spectra", Journal of Quantitative Spectroscopy and Radiative Transfer 240, 106687 (2020). [https://doi.org/10.1016/j.jqsrt.2019.106687]<br> 3. Chubb, K. L., Rocchetto, M., Yurchenko, S. N., Min, M., Waldmann, I., Barstow, J. K., Molliere, P., Al-Refaie, A. F, Phillips, M. W., Tennyson, J., "The ExoMolOP database: Cross sections and k-tables for molecules of interest in high-temperature exoplanet atmospheres", Astronomy and Astrophysics 646, A21 (2020). [http://dx.doi.org/10.1051/0004-6361/202038350][20ChRoYu.]<br>
The MoLLIST dataset for 56Fe1H
The dataset is an archive of ExoMol page, https://exomol.com/data/molecules/FeH/56Fe-1H/MoLLIST.<br> Please check the reference details according to the following description or directly from the website.<br><br>Definitions file:<br>56Fe-1H__MoLLIST.def<br>Root references for ExoMol database: <br> 1. J. Tennyson, S.N. Yurchenko A.F. Al-Refaie, V.H.J. Clark, K.L. Chubb,E.K. Conway, A. Dewan, M.N. Gorman, C. Hill, A.E. Lynas-Gray, T. Mellor, L.K. McKemmish, A. Owens, O.L. Polyansky, M. Semenov, W. Somogyi, G. Tinetti, A. Upadhyay, I. Waldmann, Y. Wang, S. Wright and O.P. Yurchenko, The 2020 release of the ExoMol database: molecular line lists for exoplanet and other hot atmospheres, J. Quant. Spectrosc. Rad. Transf., 255, 107228 (2020).[https://doi.org/10.1016/j.jqsrt.2020.107228.]<br><br>MoLLIST: line list (external)<br>Empirical Diatomic line lists MoLLIST from Bernath lab (bernath.uwaterloo.ca) in standard ExoMol format [Tennyson and Yurchenko (2016)]:<br> FeH_README__MoLLIST.txt<br> Documentation for FeH external line list of the MoLLIST dataset<br> 56Fe-1H__MoLLIST.states.bz2<br> MoLLIST (56Fe)(1H) external line list states file<br> 56Fe-1H__MoLLIST.trans.bz2<br> MoLLIST (56Fe)(1H) external line list transition file by Dulick et al. (2003)<br>References:<br> 1. Dulick, M., Bauschlicher, C. W,. Burrows, A., Sharp, C. M., Ram, R. S., Bernath, P. F., "Line intensities and molecular opacities of the FeH F 4Δi - X 4Δi transition", The Astrophysical Journal 594, 651-663 (2003). [http://dx.doi.org/10.1086/376791][03DuBaBu.FeH]<br> 2. Bernath, P.F., "MoLLIST: Molecular Line Lists, Intensities and Spectra", Journal of Quantitative Spectroscopy and Radiative Transfer 240, 106687 (2020). [https://doi.org/10.1016/j.jqsrt.2019.106687]<br><br>MoLLIST: partition function (external)<br>Empirical Diatomic line lists MoLLIST from Bernath lab (bernath.uwaterloo.ca) in standard ExoMol format [Tennyson and Yurchenko (2016)]:<br> 56Fe-1H__MoLLIST.pf<br> MoLLIST (56Fe)(1H) external line list partition function<br>References:<br> 1. Bernath, P.F., "MoLLIST: Molecular Line Lists, Intensities and Spectra", Journal of Quantitative Spectroscopy and Radiative Transfer 240, 106687 (2020). [https://doi.org/10.1016/j.jqsrt.2019.106687]<br><br>MoLLIST: opacity<br>Empirical Diatomic line lists MoLLIST from Bernath lab (bernath.uwaterloo.ca) in standard ExoMol format [Tennyson and Yurchenko (2016)]:<br> 56Fe-1H__MoLLIST.R1000_0.3-50mu.ktable.ARCiS.fits.gz<br> ARCiS k-tables at R= 1000 (0.3-50mu) in fits format (gzipped): MoLLIST (56Fe)(1H) line list.<br> 56Fe-1H__MoLLIST.R1000_0.3-50mu.ktable.petitRADTRANS.h5<br> petitRADTRANS k-tables at R= 1000 (0.3-50mu) in HDF5 format: MoLLIST (56Fe)(1H) line list.<br> 56Fe-1H__MoLLIST.R1000_0.3-50mu.ktable.NEMESIS.kta<br> NEMESIS k-tables at R= 1000 (0.3-50mu) in NEMESIS-kta format: MoLLIST (56Fe)(1H) line list.<br> 56Fe-1H__MoLLIST.R15000_0.3-50mu.xsec.TauREx.h5<br> TauREx k-tables at R= 15000 (0.3-50mu) in HDF5 format: MoLLIST (56Fe)(1H) line list.<br>References:<br> 1. Wende, S., Reiners, A., Seifahrt, A., Bernath, P. F., "CRIRES spectroscopy and empirical line-by-line identification of FeH molecular absorption in an M dwarf", Astronomy and Astrophysics 523, A58 (2010). [http://dx.doi.org/10.1051/0004-6361/201015220][10WEReSe.FeH]<br> 2. Bernath, P.F., "MoLLIST: Molecular Line Lists, Intensities and Spectra", Journal of Quantitative Spectroscopy and Radiative Transfer 240, 106687 (2020). [https://doi.org/10.1016/j.jqsrt.2019.106687]<br> 3. Chubb, K. L., Rocchetto, M., Yurchenko, S. N., Min, M., Waldmann, I., Barstow, J. K., Molliere, P., Al-Refaie, A. F, Phillips, M. W., Tennyson, J., "The ExoMolOP database: Cross sections and k-tables for molecules of interest in high-temperature exoplanet atmospheres", Astronomy and Astrophysics 646, A21 (2020). [http://dx.doi.org/10.1051/0004-6361/202038350][20ChRoYu.]<br>
The MoLLIST dataset for 52Cr1H
The dataset is an archive of ExoMol page, https://exomol.com/data/molecules/CrH/52Cr-1H/MoLLIST.<br> Please check the reference details according to the following description or directly from the website.<br><br>Definitions file:<br>52Cr-1H__MoLLIST.def<br>Root references for ExoMol database: <br> 1. J. Tennyson, S.N. Yurchenko A.F. Al-Refaie, V.H.J. Clark, K.L. Chubb,E.K. Conway, A. Dewan, M.N. Gorman, C. Hill, A.E. Lynas-Gray, T. Mellor, L.K. McKemmish, A. Owens, O.L. Polyansky, M. Semenov, W. Somogyi, G. Tinetti, A. Upadhyay, I. Waldmann, Y. Wang, S. Wright and O.P. Yurchenko, The 2020 release of the ExoMol database: molecular line lists for exoplanet and other hot atmospheres, J. Quant. Spectrosc. Rad. Transf., 255, 107228 (2020).[https://doi.org/10.1016/j.jqsrt.2020.107228.]<br><br>MoLLIST: line list (external)<br>Empirical Diatomic line lists MoLLIST from Bernath lab (bernath.uwaterloo.ca) in standard ExoMol format [Tennyson and Yurchenko (2016)]:<br> CrH_README__MoLLIST.txt<br> Documentation for CrH external line list of the MoLLIST dataset<br> 52Cr-1H__MoLLIST.states.bz2<br> MoLLIST (52Cr)(1H) external line list states file<br> 52Cr-1H__MoLLIST.trans.bz2<br> MoLLIST (52Cr)(1H) external line list transition file<br>References:<br> 1. Bernath, P.F., "MoLLIST: Molecular Line Lists, Intensities and Spectra", Journal of Quantitative Spectroscopy and Radiative Transfer 240, 106687 (2020). [https://doi.org/10.1016/j.jqsrt.2019.106687]<br><br>MoLLIST: partition function (external)<br>Empirical Diatomic line lists MoLLIST from Bernath lab (bernath.uwaterloo.ca) in standard ExoMol format [Tennyson and Yurchenko (2016)]:<br> CrH_README__MoLLIST.txt<br> Documentation for CrH external line list of the MoLLIST dataset<br> 52Cr-1H__MoLLIST.pf<br> MoLLIST (52Cr)(1H) external line list partition function<br>References:<br> 1. Bernath, P.F., "MoLLIST: Molecular Line Lists, Intensities and Spectra", Journal of Quantitative Spectroscopy and Radiative Transfer 240, 106687 (2020). [https://doi.org/10.1016/j.jqsrt.2019.106687]<br><br>MoLLIST: opacity<br>Empirical Diatomic line lists MoLLIST from Bernath lab (bernath.uwaterloo.ca) in standard ExoMol format [Tennyson and Yurchenko (2016)]:<br> 52Cr-1H__MoLLIST.R1000_0.3-50mu.ktable.ARCiS.fits.gz<br> ARCiS k-tables at R= 1000 (0.3-50mu) in fits format (gzipped): MoLLIST (52Cr)(1H) line list.<br> 52Cr-1H__MoLLIST.R1000_0.3-50mu.ktable.petitRADTRANS.h5<br> petitRADTRANS k-tables at R= 1000 (0.3-50mu) in HDF5 format: MoLLIST (52Cr)(1H) line list.<br> 52Cr-1H__MoLLIST.R1000_0.3-50mu.ktable.NEMESIS.kta<br> NEMESIS k-tables at R= 1000 (0.3-50mu) in NEMESIS-kta format: MoLLIST (52Cr)(1H) line list.<br> 52Cr-1H__MoLLIST.R15000_0.3-50mu.xsec.TauREx.h5<br> TauREx k-tables at R= 15000 (0.3-50mu) in HDF5 format: MoLLIST (52Cr)(1H) line list.<br>References:<br> 1. Burrows, A., Ram, R. S., Bernath, P., Sharp, C. M., Milsom, J. A., "New CrH opacities for the study of L and brown dwarf atmospheres", Astrophysical Journal 577, 986-992 (2002). [http://dx.doi.org/10.1086/342242][02BuRaBe.CrH]<br> 2. Bernath, P.F., "MoLLIST: Molecular Line Lists, Intensities and Spectra", Journal of Quantitative Spectroscopy and Radiative Transfer 240, 106687 (2020). [https://doi.org/10.1016/j.jqsrt.2019.106687]<br> 3. Chubb, K. L., Rocchetto, M., Yurchenko, S. N., Min, M., Waldmann, I., Barstow, J. K., Molliere, P., Al-Refaie, A. F, Phillips, M. W., Tennyson, J., "The ExoMolOP database: Cross sections and k-tables for molecules of interest in high-temperature exoplanet atmospheres", Astronomy and Astrophysics 646, A21 (2020). [http://dx.doi.org/10.1051/0004-6361/202038350][20ChRoYu.]<br>
The MoLLIST dataset for 48Ti1H
The dataset is an archive of ExoMol page, https://exomol.com/data/molecules/TiH/48Ti-1H/MoLLIST.<br> Please check the reference details according to the following description or directly from the website.<br><br>Definitions file:<br>48Ti-1H__MoLLIST.def<br>Root references for ExoMol database: <br> 1. J. Tennyson, S.N. Yurchenko A.F. Al-Refaie, V.H.J. Clark, K.L. Chubb,E.K. Conway, A. Dewan, M.N. Gorman, C. Hill, A.E. Lynas-Gray, T. Mellor, L.K. McKemmish, A. Owens, O.L. Polyansky, M. Semenov, W. Somogyi, G. Tinetti, A. Upadhyay, I. Waldmann, Y. Wang, S. Wright and O.P. Yurchenko, The 2020 release of the ExoMol database: molecular line lists for exoplanet and other hot atmospheres, J. Quant. Spectrosc. Rad. Transf., 255, 107228 (2020).[https://doi.org/10.1016/j.jqsrt.2020.107228.]<br><br>MoLLIST: line list (external)<br>Empirical Diatomic line lists MoLLIST from Bernath lab (bernath.uwaterloo.ca) in standard ExoMol format [Tennyson and Yurchenko (2016)]:<br> TiH_README__MoLLIST.txt<br> Documentation for TiH external line list of the Bernath dataset<br> 48Ti-1H__MoLLIST.states.bz2<br> MoLLIST (48Ti)(1H) external line list states file<br> 48Ti-1H__MoLLIST.trans.bz2<br> MoLLIST (48Ti)(1H) external line list transition file<br>References:<br> 1. Burrows, A., Dulick, M., Bauschlicher, C. W., Bernath, P. F., Ram, R. S., Sharp, C. M., Milsom, J. A., "Spectroscopic constants, abundances, and opacities of the TiH molecule", Astrophysical Journal 624, 988-1002 (2005). [http://dx.doi.org/10.1086/429366][05BuDuBa.TiH]<br> 2. Bernath, P.F., "MoLLIST: Molecular Line Lists, Intensities and Spectra", Journal of Quantitative Spectroscopy and Radiative Transfer 240, 106687 (2020). [https://doi.org/10.1016/j.jqsrt.2019.106687]<br><br>MoLLIST: partition function (external)<br>Empirical Diatomic line lists MoLLIST from Bernath lab (bernath.uwaterloo.ca) in standard ExoMol format [Tennyson and Yurchenko (2016)]:<br> TiH_README__MoLLIST.txt<br> Documentation for TiH external line list of the Bernath dataset<br> 48Ti-1H__MoLLIST.pf<br> MoLLIST (48Ti)(1H) external line list partition function<br>References:<br> 1. Burrows, A., Dulick, M., Bauschlicher, C. W., Bernath, P. F., Ram, R. S., Sharp, C. M., Milsom, J. A., "Spectroscopic constants, abundances, and opacities of the TiH molecule", Astrophysical Journal 624, 988-1002 (2005). [http://dx.doi.org/10.1086/429366][05BuDuBa.TiH]<br><br>MoLLIST: opacity<br>Empirical Diatomic line lists MoLLIST from Bernath lab (bernath.uwaterloo.ca) in standard ExoMol format [Tennyson and Yurchenko (2016)]:<br> 48Ti-1H__MoLLIST.R1000_0.3-50mu.ktable.ARCiS.fits.gz<br> ARCiS k-tables at R= 1000 (0.3-50mu) in fits format (gzipped): MoLLIST (48Ti)(1H) line list.<br> 48Ti-1H__MoLLIST.R1000_0.3-50mu.ktable.petitRADTRANS.h5<br> petitRADTRANS k-tables at R= 1000 (0.3-50mu) in HDF5 format: MoLLIST (48Ti)(1H) line list.<br> 48Ti-1H__MoLLIST.R1000_0.3-50mu.ktable.NEMESIS.kta<br> NEMESIS k-tables at R= 1000 (0.3-50mu) in NEMESIS-kta format: MoLLIST (48Ti)(1H) line list.<br> 48Ti-1H__MoLLIST.R15000_0.3-50mu.xsec.TauREx.h5<br> TauREx k-tables at R= 15000 (0.3-50mu) in HDF5 format: MoLLIST (48Ti)(1H) line list.<br>References:<br> 1. Burrows, A., Dulick, M., Bauschlicher, C. W., Bernath, P. F., Ram, R. S., Sharp, C. M., Milsom, J. A., "Spectroscopic constants, abundances, and opacities of the TiH molecule", Astrophysical Journal 624, 988-1002 (2005). [http://dx.doi.org/10.1086/429366][05BuDuBa.TiH]<br> 2. Chubb, K. L., Rocchetto, M., Yurchenko, S. N., Min, M., Waldmann, I., Barstow, J. K., Molliere, P., Al-Refaie, A. F, Phillips, M. W., Tennyson, J., "The ExoMolOP database: Cross sections and k-tables for molecules of interest in high-temperature exoplanet atmospheres", Astronomy and Astrophysics 646, A21 (2020). [http://dx.doi.org/10.1051/0004-6361/202038350][20ChRoYu.]<br>
The Darby-Lewis dataset for 9Be1H
The dataset is an archive of ExoMol page, https://exomol.com/data/molecules/BeH/9Be-1H/Darby-Lewis.<br> Please check the reference details according to the following description or directly from the website.<br><br>Definitions file:<br>9Be-1H__Darby-Lewis.def<br>Root references for ExoMol database: <br> 1. J. Tennyson, S.N. Yurchenko A.F. Al-Refaie, V.H.J. Clark, K.L. Chubb,E.K. Conway, A. Dewan, M.N. Gorman, C. Hill, A.E. Lynas-Gray, T. Mellor, L.K. McKemmish, A. Owens, O.L. Polyansky, M. Semenov, W. Somogyi, G. Tinetti, A. Upadhyay, I. Waldmann, Y. Wang, S. Wright and O.P. Yurchenko, The 2020 release of the ExoMol database: molecular line lists for exoplanet and other hot atmospheres, J. Quant. Spectrosc. Rad. Transf., 255, 107228 (2020).[https://doi.org/10.1016/j.jqsrt.2020.107228.]<br><br>Darby-Lewis: line list<br>Darby-Lewis line list for BeH in its X and A electronic states using the Duo program.:<br> 9Be-1H__Darby-Lewis.trans.bz2<br> Transition file for the Darby-Lewis line list for (9Be)(1H)<br> 9Be-1H__Darby-Lewis.states.bz2<br> States file for the Darby-Lewis line list for (9Be)(1H)<br>References:<br><br>Darby-Lewis: partition function<br>Darby-Lewis line list for BeH in its X and A electronic states using the Duo program.:<br> 9Be-1H__Darby-Lewis.pf<br> Partition function of (9Be)(1H) generated using the Darby-Lewis line list<br>References:<br> 1. Darby-Lewis, D., Tennyson, J., Lawson, K. D., Yurchenko, S. N., Stamp, M. F., Shaw, A., Brezinsek, S., JET Contributors, "Synthetic spectra of BeH, BeD and BeT for emission modeling in JET plasmas", J. Phys. B At. Mol. Opt. Phys. 51, 185701 (2018). [https://doi.org/10.1088/1361-6455/aad6d0][18DaTeLa.BeH]<br><br>Darby-Lewis: opacity<br>Darby-Lewis line list for BeH in its X and A electronic states using the Duo program.:<br> 9Be-1H__Darby-Lewis.R1000_0.3-50mu.ktable.ARCiS.fits.gz<br> ARCiS k-tables at R= 1000 (0.3-50mu) in fits format (gzipped): Darby-Lewis (9Be)(1H) line list.<br> 9Be-1H__Darby-Lewis.R1000_0.3-50mu.ktable.petitRADTRANS.h5<br> petitRADTRANS k-tables at R= 1000 (0.3-50mu) in HDF5 format: Darby-Lewis (9Be)(1H) line list.<br> 9Be-1H__Darby-Lewis.R1000_0.3-50mu.ktable.NEMESIS.kta<br> NEMESIS k-tables at R= 1000 (0.3-50mu) in NEMESIS-kta format: Darby-Lewis (9Be)(1H) line list.<br> 9Be-1H__Darby-Lewis.R15000_0.3-50mu.xsec.TauREx.h5<br> TauREx k-tables at R= 15000 (0.3-50mu) in HDF5 format: Darby-Lewis (9Be)(1H) line list.<br>References:<br> 1. Chubb, K. L., Rocchetto, M., Yurchenko, S. N., Min, M., Waldmann, I., Barstow, J. K., Molliere, P., Al-Refaie, A. F, Phillips, M. W., Tennyson, J., "The ExoMolOP database: Cross sections and k-tables for molecules of interest in high-temperature exoplanet atmospheres", Astronomy and Astrophysics 646, A21 (2020). [http://dx.doi.org/10.1051/0004-6361/202038350][20ChRoYu.]<br>
Technical potential of ground-source heat pumps for Western Switzerland
<p>This dataset contains an estimation of the technical potential of shallow ground-source heat pumps (GSHPs) for Western Switzerland, at a spatial resolution of 200 x 200 m<sup>2</sup>. The technical potential is hereby defined as the maximum energy that could be extracted from GSHP systems in case of their dense deployment, such as to <strong>avoid the over-exploitation</strong> of the heat capacity of the ground. We consider GSHPs with <strong>vertical closed-loop borehole heat exchangers</strong> (BHE) installed at depths of 50 - 200 m. The dataset covers around 80,000 property units (parcels) in the Swiss Cantons of Vaud and Geneva, excluding only the areas of the Alps and the Jura mountains.</p> <p>The estimated potential accounts for:</p> <ul> <li>Norms for geothermal installations set by the Swiss Society of Engineers and Architects (SIA 384/6)</li> <li>Thermal interferences between neighbouring boreholes and their impact on the temperature change in the ground</li> <li>Topographic Landscape data to assess the available area for BHE installation</li> </ul> <p>The methodology used to generate the data is described in:</p> <p>Walch, Alina, Nahid Mohajeri, Agust Gudmundsson, and Jean-Louis Scartezzini. ‘Quantifying the Technical Geothermal Potential from Shallow Borehole Heat Exchangers at Regional Scale’. <em>Renewable Energy</em> 165 (2021): 369–80. <a href="https://doi.org/10.1016/j.renene.2020.11.019">https://doi.org/10.1016/j.renene.2020.11.019</a>.</p> <p><strong>Dataset description</strong></p> <p>As the data is targeted to large-scale applications and potential studies, it is shared in the format of <strong>pixels of 200 x 200 m<sup>2</sup></strong>. Upon request it can be provided at different aggregation levels, as it is generated at the resolution of individual building units (parcels). The potential is provided as <strong>annual</strong> <strong>values</strong>, and it can be converted to monthly values using the provided heating degree weights. For each pixel of 200 x 200 m<sup>2</sup>, we provide the following variables:</p> <ul> <li>Annual total technical heat extraction potential (in MWh)</li> <li>Potential heat delivered <em>to buildings </em>(heat pump output), assuming a heat pump performance (COP) of 4.5 (in MWh)</li> <li>Available area for GSHP installation (in m<sup>2</sup>)</li> <li>Number of installed boreholes </li> <li>Average heat extraction rate (in W/m)</li> <li>Average borehole depth (in m)</li> <li>Average borehole spacing within the parcels located in the pixel (in m)</li> <li>Heating degree weights (i.e. heat demand variation) for each month</li> </ul> <p>A description of the metadata is provided in the document <em>gshp_VD_GE_metadata_V1.pdf.</em></p> <p>This work is part of the PhD Thesis of Alina Walch. </p>
Dissolved Cr concentration and stable isotope data presented in "Release from biogenic particles, benthic fluxes, and deep water circulation control Cr and δ53Cr distributions in the ocean interior" (Janssen et al., 2021, EPSL).
<p>This dataset presents all of the dissolved Cr data included and discussed in “Release from biogenic particles, benthic fluxes, and deep water circulation control Cr and δ<sup>53</sup>Cr distributions in the ocean interior” (Janssen et al., 2021, EPSL). Three primary datasets are included:</p> <ol> <li>Dissolved [Cr], [Cr(III)] and d53Cr in samples from shipboard particle regeneration incubations conducted in the subantarctic Southern Ocean.</li> <li>Dissolved [Cr] in porewater samples from a sediment core collected in the Tasman Sea in primarily calcareous sediments, along with [Cr] and δ<sup>53</sup>Cr in overlying bottom waters.</li> <li>3. A compilation of intermediate and deep water dissolved [Cr] and δ<sup>53</sup>Cr from seawater samples from the Southern, Pacific and Atlantic Oceans</li> </ol>
DTOceanPlus Station Keeping Dataset
<p>This dataset of station keeping components was produced as part of the DTOceanPlus project. This is used in the Station Keeping tool, and now can be used for other purposes. It comprises a range of mooring lines and drag anchors that are described either using Excel and JSON format.</p> <p>This dataset comprises a spreadsheet containing the data and a technical note outlining the process of collating data.</p> <p>For more information on the DTOceanPlus tools, visit <code><a href="https://www.dtoceanplus.eu/">https://www.dtoceanplus.eu/</a></code><code>.</code></p>
Structures of S-protein in complex with ligands deposited in the PDB between the 1st January 2021 and the 13th May 2021
<p>All 174 structures of SARS-CoV-2 S-protein in complex with a ligand released on the PDB between the 1<sup>st</sup> January 2021 and the 13<sup>th</sup> May 2021 were categorised by ligand type: hACE2, antibody Fab fragments, VHH antibody fragments or <em>de novo</em> designed peptide scaffolds. Information concerning the method by which the structures were determined and their resolution were retrieved from the PDB. The categorisation of ligands by S-protein binding site were achieved by visual analysis of all the structures using molecular visualisation software PyMOL, in which no new binding sites were found beyond those already categorised for the structures released on the PDB until the 1<sup>st</sup> January 2021 (10.5281/zenodo.5503855).</p> <p>The Pure project is funded by the European Union’s Horizon 2020 program under grant agreement No. 899732.</p> <p> </p>
List of the structures of S-protein in complex with ligands deposited in the Protein Data Bank until the 1st January 2021.
<p>All 131 structures of SARS-CoV-2 S-protein in complex with a ligand released on the PDB until the 1<sup>st</sup> January 2021 were categorised by ligand type: hACE2, antibody Fab fragments, VHH antibody fragments or <em>de novo</em> designed peptide scaffolds. The ligands’ amino acid sequences, the method by which the structures were determined and their resolution were retrieved from the PDB. Information regarding the ligands' production method, dissociation constants (K<sub>D</sub>), S-protein segment against which the K<sub>D</sub> were measured and the determination methods were retrieved from the respective references. The categorisation of ligands by S-protein binding site and listing of S-protein conformation in each structure were achieved by visual analysis of all the structures using molecular visualisation software PyMOL.</p>
Dataset for the study Multisensory spatial perception in visually impaired infants
<p>Data from the study "Multisensory spatial perception in visually impaired infants". Data are in textual tab-delimited format.</p> <p> </p> <p>Summary</p> <p>Congenitally blind infants are not only deprived of visual input but also of visual influences on the intact senses. The important role that vision plays in the early development of multisensory spatial perception<a href="https://www.sciencedirect.com/science/article/pii/S0960982221012513#bib1">1</a>, <a href="https://www.sciencedirect.com/science/article/pii/S0960982221012513#bib2">2</a>, <a href="https://www.sciencedirect.com/science/article/pii/S0960982221012513#bib3">3</a>, <a href="https://www.sciencedirect.com/science/article/pii/S0960982221012513#bib4">4</a>, <a href="https://www.sciencedirect.com/science/article/pii/S0960982221012513#bib5">5</a>, <a href="https://www.sciencedirect.com/science/article/pii/S0960982221012513#bib6">6</a>, <a href="https://www.sciencedirect.com/science/article/pii/S0960982221012513#bib7">7</a> (e.g., in crossmodal calibration<a href="https://www.sciencedirect.com/science/article/pii/S0960982221012513#bib8">8</a>, <a href="https://www.sciencedirect.com/science/article/pii/S0960982221012513#bib9">9</a>, <a href="https://www.sciencedirect.com/science/article/pii/S0960982221012513#bib10">10</a> and in the formation of multisensory spatial representations of the body and the world<a href="https://www.sciencedirect.com/science/article/pii/S0960982221012513#bib1"><sup>1</sup></a><sup>,</sup><a href="https://www.sciencedirect.com/science/article/pii/S0960982221012513#bib2"><sup>2</sup></a>) raises the possibility that impairments in spatial perception are at the heart of the wide range of difficulties that visually impaired infants show across spatial,<a href="https://www.sciencedirect.com/science/article/pii/S0960982221012513#bib8">8</a>, <a href="https://www.sciencedirect.com/science/article/pii/S0960982221012513#bib9">9</a>, <a href="https://www.sciencedirect.com/science/article/pii/S0960982221012513#bib10">10</a>, <a href="https://www.sciencedirect.com/science/article/pii/S0960982221012513#bib11">11</a>, <a href="https://www.sciencedirect.com/science/article/pii/S0960982221012513#bib12">12</a> motor,<a href="https://www.sciencedirect.com/science/article/pii/S0960982221012513#bib13">13</a>, <a href="https://www.sciencedirect.com/science/article/pii/S0960982221012513#bib14">14</a>, <a href="https://www.sciencedirect.com/science/article/pii/S0960982221012513#bib15">15</a>, <a href="https://www.sciencedirect.com/science/article/pii/S0960982221012513#bib16">16</a>, <a href="https://www.sciencedirect.com/science/article/pii/S0960982221012513#bib17">17</a> and social domains.<a href="https://www.sciencedirect.com/science/article/pii/S0960982221012513#bib8"><sup>8</sup></a><sup>,</sup><a href="https://www.sciencedirect.com/science/article/pii/S0960982221012513#bib18"><sup>18</sup></a><sup>,</sup><a href="https://www.sciencedirect.com/science/article/pii/S0960982221012513#bib19"><sup>19</sup></a> But investigations of early development are needed to clarify how visually impaired infants’ spatial hearing and touch support their emerging ability to make sense of their body and the outside world. We compared sighted (S) and severely visually impaired (SVI) infants’ responses to auditory and tactile stimuli presented on their hands. No statistically reliable differences in the direction or latency of responses to <a href="https://www.sciencedirect.com/topics/biochemistry-genetics-and-molecular-biology/auditory-stimulation">auditory stimuli</a> emerged, but significant group differences emerged in responses to tactile and audiotactile stimuli. The visually impaired infants showed attenuated audiotactile spatial integration and interference, weighted more tactile than auditory cues when the two were presented in conflict, and showed a more limited influence of representations of the external layout of the body on tactile spatial perception.<a href="https://www.sciencedirect.com/science/article/pii/S0960982221012513#bib20"><sup>20</sup></a> These findings uncover a distinct phenotype of multisensory spatial perception in early postnatal visual deprivation. Importantly, evidence of audiotactile spatial integration in visually impaired infants, albeit to a lesser degree than in sighted infants, signals the potential of multisensory rehabilitation methods in early development.</p> <p>Orienting responses and reaction times (RT) are reported, based on the scoring of two independent naive raters, for each trial of each subject, group (SVI/S), posture (Uncrossed/Crossed), and sensory condition (Tactile only, Auditory only, Audiotactile congruent, Audiotactile incongruent).</p> <p>Trial is the trial number, condition is the sensory condition, audio and tactile respectively refer to the side of the stimulated hand, response_status reports if the response is defined or undefined, response modality reports if the modality used by subjects to respond/not to respond to stimuli (hand, eye, both hands, no motion), group is if the subject was a sighted (S) or a severely visually impaired (SVI) infant, age_mounth is the age expressed in months, RT_rater1, RT_rater 2 and RT are respectively the RT assigned by the two raters and the merge of the two estimations (for RTs, the mean), the same organization for response_side, and for response_modality (for those variables, when the estimation of the two raters did not agree, the merged classification was set to unknown, that is uncertain/undefined).</p>
Crowd4SDG - Crowdsourced image classification and damage assessment
<p>This data set contains crowdsourced classification and damage assessment of images of an earthquake extracted from social media. <br> <br> A data set of 907 images posted on Twitter related to the 2019 Albanian Earthquake, that are filtered and pre-classified using an automated technique is cross-validated for accuracy by two different crowds. One, digital humanitarian volunteers using the crowdsourcing platform <a href="http://www.crowd4ems.org">CROWD4EMS</a> and another, paid micro-taskers of the Amazon Mechanical Turk. In order to compare and evaluate the efficiency and accuracy of the volunteers and the paid micro taskers, ground truth is established with the help of a team of experts, who validated the same set of data. <br> <br> <strong>Parameters considered for volunteer contributions:</strong> The dataset was imported to the Crowd4EMS platform for Crowd contribution. In the forum, each volunteer will see the image to be validated along with the tweet text and the link to the original tweet. The user has to validate whether the given image is <em>relevant or</em> <em>irrelevant</em> to the disaster. In case of doubt, the user can refer to the tutorial explaining the relevance or skip the task. Once the image's relevance is validated, the user will be asked to label the <em>severity</em> of the impact, as seen in the image.</p> <p>The Automated algorithm has pre-classified the images as <em>severe </em>and <em>minimal </em>damage. The Crowd4EMS platform lets the volunteer label them as '<em>severe damage</em>,' <em>moderate damage'</em>,' <em>minimal damage', </em>and' <em>no damage'.</em> Each task has to be answered <em>at least three times</em>, and the final consensus is taken as per the<em> inter-rater agreement. </em><br> <br> <strong>Parameters considered for micro-taskers contribution:</strong> The dataset was imported to the <em>Amazon Mechanical Turk</em> platform for Crowd contribution. In the platform, each worker will see only the image that is to be categorised as follows: The user has to validate whether the given image depicts <em>severe damage, moderate damage, minimal damage, no damage </em>or <em>irrelevant</em> to the disaster. Each task has to be answered <em>at least ten times</em>, and the final consensus is taken as per the<em> inter-rater agreement. </em><br> <br> <strong>Acknowledgements:</strong> We want to thank Muhammad Imran of Qatar Computing Research Institute for sharing their pre-filtered social media imagery dataset on the Albanian earthquake from the Artificial Intelligence for Disaster Response (AIDR) Platform. We would also like to extend our gratitude to the volunteers for their contribution on the Crowd4EMS Platform.<br> </p>
A vertically-resolved atmospheric dust reanalysis for Mars Years 28-29 using Analysis Correction
<p>This is a dataset of meteorological variables for the atmosphere of Mars, obtained by assimilating measurements (retrievals) of atmospheric temperature and dust opacity into a 3-dimensional, time-dependent numerical model of the Martian atmospheric circulation (known as a “reanalysis”).</p> <p>The observations come from two spacecraft - the Mars Climate Sounder (MCS) instrument on board NASA’s Mars Reconnaissance Orbiter (e.g. Kleinboehl et al. 2009) and the Thermal Emission Imaging Spectrometer (THEMIS) on board NASA’s Mars Odyssey spacecraft, and cover the period from 21 September 2006 until 5 November 2009 (Mars Years 28:Ls=109.98 - 30:Ls=4.78). MCS observations include profiles of temperature and dust opacity from near the surface up to altitudes of around 80 km obtained from infrared limb-sounding (MCS version 3 retrievals, based on opacities at around 21.6 micron wavelengths), while THEMIS measurements are of column dust opacity in the infrared (centred around 9.3 micron wavelength). Further details can be found on the websites</p> <p>https://pds-geosciences.wustl.edu/missions/odyssey/themis.html,<br> https://atmos.nmsu.edu/data and services/atmospheres data/MARS/aerosols.html</p> <p>The model into which the observations are assimilated is the UK version of Laboratoire de Météorologie Dynamique Mars Global Circulation Model (LMDMGCM), a 3-dimensional, time-dependent numerical circulation model of the Martian atmosphere and near-surface environment, simulating the changing winds, temperature, pressure and dust content of the atmosphere across the whole planet. The model solves the equations of motion, mass and energy conservation using a spherical harmonic representation in the horizontal and finite difference formulation in the vertical direction, but outputs the data here on a regular longitude-latitude grid with 72 points in longitude, 36 points in latitude and 25 terrain-following sigma levels in the vertical direction (where sigma = pressure/surface pressure) on a stretched vertical grid that extends from the surface to an altitude of approximately 100 km. More details can be found in publications by Forget et al. (1999), Newman et al. (2001), Mulholland et al. (2013).</p> <p>The observations and model are linked by an assimilation scheme, based on the Analysis Correction (AC) algorithm developed by Lorenc et al. (1991) and adapted for Mars by Lewis et al. (2007). Previous reanalyses of Mars observations using this scheme include the MACDA dataset (Montabone et al. 2014) and OPENMars (Holmes et al. 2020). This new dataset, however, makes use of an extension of the AC scheme to enable assimilation of both column integrated dust opacity measurements and dust opacity profiles in the vertical direction (see Ruan et al. 2021). This new dataset therefore provides a more realistic representation of the distribution of dust loading in the Martian atmosphere than previous work, which may also result in improved representation of other meteorological variables, notably temperature.</p> <p>Data are provided as 2D and 3D fields of variables in netCDF format as generated by the numerical model on the (longitude, latitude, sigma) grid at 2-hourly intervals. Each file contains 360 time steps covering 30 Martian days or sols. The variables contained in each file are as follows:</p> <p> Variables and attributes<br> 0 lon: FLOAT(72) = FLOAT(lon)<br> 0 long_name: longitude<br> 1 units: degrees_east<br> 1 lat: FLOAT(36) = FLOAT(lat)<br> 0 long_name: latitude<br> 1 units: degrees_north<br> 2 sigma: FLOAT(25) = FLOAT(sigma)<br> 0 long_name: sigma<br> 1 units: sigma_level = p/ps<br> 3 soil: FLOAT(18) = FLOAT(soil)<br> 0 long_name: soil levels (i.e. levels below the surface to represent thermal variations)<br> 1 units: none<br> 4 time: FLOAT(360) = FLOAT(time)<br> 0 long_name: model time<br> 1 units: days since 00:00:00 (the beginning of the file)<br> 5 controle: FLOAT(100) = FLOAT(lentable)<br> 0 long_name: Table of run parameters<br> 1 description: MGCM run 5.000<br> 6 Ls: FLOAT(360) = FLOAT(time)<br> 0 Physics_diagnostic: Solar longitude (such that Ls=0 is northern Spring equinox)<br> 1 units: deg<br> 7 tsurf: FLOAT(72,36,360) = FLOAT(lon,lat,time)<br> 0 Physics_diagnostic: Surface temperature<br> 1 units: K<br> 8 ps: FLOAT(72,36,360) = FLOAT(lon,lat,time)<br> 0 Physics_diagnostic: surface pressure<br> 1 units: Pa<br> 9 co2ice: FLOAT(72,36,360) = FLOAT(lon,lat,time)<br> 0 Physics_diagnostic: co2 ice thickness (column mass density)<br> 1 units: kg.m-2<br> 10 fluxsurf_lw: FLOAT(72,36,360) = FLOAT(lon,lat,time)<br> 0 Physics_diagnostic: fluxsurf_lw (surface infrared radiative flux)<br> 1 units: W.m-2<br> 11 fluxsurf_sw: FLOAT(72,36,360) = FLOAT(lon,lat,time)<br> 0 Physics_diagnostic: fluxsurf_sw (surface visible radiative flux)<br> 1 units: W.m-2<br> 12 temp: FLOAT(72,36,25,360) = FLOAT(lon,lat,sigma,time)<br> 0 Physics_diagnostic: temperature<br> 1 units: K<br> 13 u: FLOAT(72,36,25,360) = FLOAT(lon,lat,sigma,time)<br> 0 Physics_diagnostic: Zonal (east-west) wind<br> 1 units: m.s-1<br> 14 v: FLOAT(72,36,25,360) = FLOAT(lon,lat,sigma,time)<br> 0 Physics_diagnostic: Meridional (north-south) wind<br> 1 units: m.s-1<br> 15 rho: FLOAT(72,36,25,360) = FLOAT(lon,lat,sigma,time)<br> 0 Physics_diagnostic: density<br> 1 units: kg.m-3<br> 16 udrag: FLOAT(72,36,360) = FLOAT(lon,lat,time)<br> 0 Physics_diagnostic: Drag velocity<br> 1 units: m/s<br> 17 udragt: FLOAT(72,36,360) = FLOAT(lon,lat,time)<br> 0 Physics_diagnostic: Threshold velocity for dust lifting<br> 1 units: m/s<br> 18 aerosol: FLOAT(72,36,25,360) = FLOAT(lon,lat,sigma,time)<br> 0 Physics_diagnostic: dust opacity considering layer thickness<br> 1 units: SI (opacity/m)<br> 19 taudustvis: FLOAT(72,36,360) = FLOAT(lon,lat,time)<br> 0 Physics_diagnostic: Dust optical depth<br> 1 units: SI<br> 20 q01: FLOAT(72,36,25,360) = FLOAT(lon,lat,sigma,time)<br> 0 Physics_diagnostic: mix. ratio<br> 1 units: kg/kg<br> 21 dqsdevtot: FLOAT(72,36,360) = FLOAT(lon,lat,time)<br> 0 Physics_diagnostic: dust devil lift rate<br> 1 units: kg.m-2.s-1<br> 22 dqsstrtot: FLOAT(72,36,360) = FLOAT(lon,lat,time)<br> 0 Physics_diagnostic: near surface wind stress dust lifting rate<br> 1 units: kg.m-2.s-1<br> 23 dqssedtot: FLOAT(72,36,360) = FLOAT(lon,lat,time)<br> 0 Physics_diagnostic: dust sedimentation rate<br> 1 units: kg.m-2.s-1</p> <p> </p>
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