cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.4294811
title: Reproductive notes of Phyllostomid bats in Ecuador

description: <strong>Reproductive notes of Phyllostomid bats in Ecuador</strong> (data_reproductive bats_ecuador.xlsx). Es el producto de seis estudios ambientales realizados en cinco provincias y seis localidades del Ecuador continental. Los muestreos se realizaron en los años: 2009, 2011, 2013, 2019 y 2020. Esta base de datos se usó para evaluar el estado reproductivo de individuos hembra de murciélagos filostómidos, previa publicación en <em>Ecotrópicos</em>, Revista de la Sociedad Venezolana de Ecología.
DOI: 10.5281/zenodo.4059193
title: CNRM-ARPEGE v6.2.4 contribution to Antarctic Cordex

description: This data set is a contribution to Antarctic Polar Cordex using the stretched grid capacity of CNRM-ARPEGE atmospheric GCM. Model outputs have been interpolated from the native ARPEGE grid, with horizontal resolution varying between 35kms (near the stretching pole) to 45 kms on the Antarctic continent, to the ANTi-44 domain (actual lon/lat). The data and metadata format respect almost all of Cordex/CMIP conventions (variables names, units, file names...). The data set consists in six simulations of 30 years time slots : 1981-2010 for "historical" simulations and 2071-2100 for future projections using radiative forcing from RCP8.5 scenario : - ARP-AMIP : amip-style control run driven by observed SST and sea-ice (1981-2100) - ARP-NOR-OC : Future projection driven by NorESM1-M RCP8.5 climate change signal on SST and sea-ice (2071-2100) - ARP-MIR-OC : Future projection driven by MIROC-ESM RCP8.5 climate change signal on SST and sea-ice (2071-2100) More details on these three simulations are given in Beaumet et al., 2019 (<strong>10.5194/tc-13-3023-2019) </strong> - ARP-AMIP-AC : Driven by observed SST and sea-ice + run-time flux bias correction* - ARP-NOR-AOC : Driven by same SST and sea-ice as NOR-OC + run-time flux bias correction* - ARP-MIR-AOC : Driven by same SST and sea-ice as MIR-OC + run-time flux bias correction* Empirical run-time bias correction uses correction terms derived from the climatological mean of tendency errors of a simulation nudged towards climate reanalysis (here ERA-Interim). The method is presented first in Guldberg et al., 2005 (10.1111/j.1600-0870.2005.00120.x) and Krinner et al., 2019 (10.1029/2018MS001438). The method applied with ARPEGE over Antarctica and the evalution of the simulation are presented in this paper : https://doi.org/10.5194/tc-2020-307 (In review) Outputs are available at daily time scale for near-surface atmospherique mean (tas), min (tasmin) and max (tasmax) temperature, total precipitation (pr), snowfall (prsn), snowmelt(snm), surface snow sublimation (sbl_i) and surface runoff (mrros). If you consider using these data, please email me (Julien.Beaumet@univ-grenoble-alpes.fr) to see how I can help and/or be involved.
description: Modelled surface mass balance of the Antarctic ice-sheet can be estimated using precipitation minus surface sublimation and runoff : SMB = pr - sbl_i - mrros
DOI: 10.5281/zenodo.4059192
title: CNRM-ARPEGE v6.2.4 contribution to Antarctic Cordex

description: This data set is a contribution to Antarctic Polar Cordex using the stretched grid capacity of CNRM-ARPEGE atmospheric GCM. Model outputs have been interpolated from the native ARPEGE grid, with horizontal resolution varying between 35kms (near the stretching pole) to 45 kms on the Antarctic continent, to the ANTi-44 domain (actual lon/lat). The data and metadata format respect almost all of Cordex/CMIP conventions (variables names, units, file names...). The data set consists in six simulations of 30 years time slots : 1981-2010 for "historical" simulations and 2071-2100 for future projections using radiative forcing from RCP8.5 scenario : - ARP-AMIP : amip-style control run driven by observed SST and sea-ice (1981-2100) - ARP-NOR-OC : Future projection driven by NorESM1-M RCP8.5 climate change signal on SST and sea-ice (2071-2100) - ARP-MIR-OC : Future projection driven by MIROC-ESM RCP8.5 climate change signal on SST and sea-ice (2071-2100) More details on these three simulations are given in Beaumet et al., 2019 (<strong>10.5194/tc-13-3023-2019) </strong> - ARP-AMIP-AC : Driven by observed SST and sea-ice + run-time flux bias correction* - ARP-NOR-AOC : Driven by same SST and sea-ice as NOR-OC + run-time flux bias correction* - ARP-MIR-AOC : Driven by same SST and sea-ice as MIR-OC + run-time flux bias correction* Empirical run-time bias correction uses correction terms derived from the climatological mean of tendency errors of a simulation nudged towards climate reanalysis (here ERA-Interim). The method is presented first in Guldberg et al., 2005 (10.1111/j.1600-0870.2005.00120.x) and Krinner et al., 2019 (10.1029/2018MS001438). The method applied with ARPEGE over Antarctica and the evalution of the simulation are presented in this paper : https://doi.org/10.5194/tc-2020-307 (In review) Outputs are available at daily time scale for near-surface atmospherique mean (tas), min (tasmin) and max (tasmax) temperature, total precipitation (pr), snowfall (prsn), snowmelt(snm), surface snow sublimation (sbl_i) and surface runoff (mrros). If you consider using these data, please email me (Julien.Beaumet@univ-grenoble-alpes.fr) to see how I can help and/or be involved.
description: Modelled surface mass balance of the Antarctic ice-sheet can be estimated using precipitation minus surface sublimation and runoff : SMB = pr - sbl_i - mrros
DOI: 10.5281/zenodo.4300131
title: chameleon cholesky prof at tupi1 - native

description: git-annex in vgpinto@tupi1:/scratch/vgpinto/perf-ev-341074
DOI: 10.5281/zenodo.4300130
title: chameleon cholesky prof at tupi1 - native

description: git-annex in vgpinto@tupi1:/scratch/vgpinto/perf-ev-341074
DOI: 10.6084/m9.figshare.13153361
title: Data Matrices EcoliOrbitrap

description: Data matrix generated by SLAW and XCMS used in the SLAW article.
DOI: 10.6084/m9.figshare.13153361.v1
title: Data Matrices EcoliOrbitrap

description: Data matrix generated by SLAW and XCMS used in the SLAW article.
DOI: 10.5281/zenodo.4299758
title: Adele 3D seismic survey segy format used in the FORCE 2020 machine learning competition for fault identification

description: Adele seismic 3D survey segy format used in the FORCE 2020 machine learning competition for fault identification. Dataset is courtesy of GEOSCIENCE Australia who need to be acknowledged in each publication
description: a
description: {"references": ["https://github.com/bolgebrygg/Force-2020-Machine-Learning-competition"]}
DOI: 10.5281/zenodo.4299757
title: Adele 3D seismic survey segy format used in the FORCE 2020 machine learning competition for fault identification

description: Adele seismic 3D survey segy format used in the FORCE 2020 machine learning competition for fault identification. Dataset is courtesy of GEOSCIENCE Australia who need to be acknowledged in each publication
description: a
description: {"references": ["https://github.com/bolgebrygg/Force-2020-Machine-Learning-competition"]}
DOI: 10.6084/m9.figshare.11635986
title: The hydraulic performance of the storm chamber in a new manhole designed for separate sewer systems

description: This paper presents the hydraulic study of a new manhole geometry, designed to allow the installation of separate sewer systems in narrow streets. The new manhole design comprises two chambers in one structure to manage separate flows. The new shape of the manhole generates a new flow pattern for stormwater. It is therefore important to understand the hydraulic properties of sewer systems using the newly designed stormwater manhole chamber. The present study focuses on exploring the hydraulic performance of the storm chamber, which is usually characterized by significant head losses and shockwaves, these related to different flow regimes. A physical model was used to carry out a systematic experiment to explore the flow characteristics of the manhole under both subcritical and transitional flow conditions. The results revealed an enhancement in head loss with higher amplitude waves generated at transition flow when compared with a conventional manhole.
DOI: 10.6084/m9.figshare.11635986.v1
title: The hydraulic performance of the storm chamber in a new manhole designed for separate sewer systems

description: This paper presents the hydraulic study of a new manhole geometry, designed to allow the installation of separate sewer systems in narrow streets. The new manhole design comprises two chambers in one structure to manage separate flows. The new shape of the manhole generates a new flow pattern for stormwater. It is therefore important to understand the hydraulic properties of sewer systems using the newly designed stormwater manhole chamber. The present study focuses on exploring the hydraulic performance of the storm chamber, which is usually characterized by significant head losses and shockwaves, these related to different flow regimes. A physical model was used to carry out a systematic experiment to explore the flow characteristics of the manhole under both subcritical and transitional flow conditions. The results revealed an enhancement in head loss with higher amplitude waves generated at transition flow when compared with a conventional manhole.
DOI: 10.6084/m9.figshare.13302686.v1
title: Data and code for POI type embedding model

description: Data and code for POI type embedding model in paper "A GloVe-based POI type embedding model for extracting and identifying urban functional regions"
DOI: 10.5517/ccdc.csd.cc22d0vc
title: CCDC 1918182: Experimental Crystal Structure Determination

description: Related Article: Eric N. T. Cuthbert,  Vincenzo Busico,  David E. Herbert,  Peter H. M. Budzelaar|2019|Eur.J.Inorg.Chem.|2019|3396|doi:10.1002/ejic.201900716
DOI: 10.5517/ccdc.csd.cc234rgh
title: CCDC 1940986: Experimental Crystal Structure Determination

description: Related Article: Florian Rauch, Sonja Fuchs, Alexandra Friedrich, Daniel Sieh, Ivo Krummenacher, Holger Braunschweig, Maik Finze, Todd Benjamin Marder|2020|Chem.-Eur.J.|26|12794|doi:10.1002/chem.201905559
DOI: 10.5517/ccdc.csd.cc234rhj
title: CCDC 1940987: Experimental Crystal Structure Determination

description: Related Article: Florian Rauch, Sonja Fuchs, Alexandra Friedrich, Daniel Sieh, Ivo Krummenacher, Holger Braunschweig, Maik Finze, Todd Benjamin Marder|2020|Chem.-Eur.J.|26|12794|doi:10.1002/chem.201905559
DOI: 10.5517/ccdc.csd.cc234rjk
title: CCDC 1940988: Experimental Crystal Structure Determination

description: Related Article: Florian Rauch, Sonja Fuchs, Alexandra Friedrich, Daniel Sieh, Ivo Krummenacher, Holger Braunschweig, Maik Finze, Todd Benjamin Marder|2020|Chem.-Eur.J.|26|12794|doi:10.1002/chem.201905559
DOI: 10.5517/ccdc.csd.cc234rkl
title: CCDC 1940989: Experimental Crystal Structure Determination

description: Related Article: Florian Rauch, Sonja Fuchs, Alexandra Friedrich, Daniel Sieh, Ivo Krummenacher, Holger Braunschweig, Maik Finze, Todd Benjamin Marder|2020|Chem.-Eur.J.|26|12794|doi:10.1002/chem.201905559
DOI: 10.5517/ccdc.csd.cc234rmn
title: CCDC 1940991: Experimental Crystal Structure Determination

description: Related Article: Florian Rauch, Sonja Fuchs, Alexandra Friedrich, Daniel Sieh, Ivo Krummenacher, Holger Braunschweig, Maik Finze, Todd Benjamin Marder|2020|Chem.-Eur.J.|26|12794|doi:10.1002/chem.201905559
DOI: 10.5517/ccdc.csd.cc234rnp
title: CCDC 1940992: Experimental Crystal Structure Determination

description: Related Article: Florian Rauch, Sonja Fuchs, Alexandra Friedrich, Daniel Sieh, Ivo Krummenacher, Holger Braunschweig, Maik Finze, Todd Benjamin Marder|2020|Chem.-Eur.J.|26|12794|doi:10.1002/chem.201905559
DOI: 10.5517/ccdc.csd.cc23ftr4
title: CCDC 1949706: Experimental Crystal Structure Determination

description: Related Article: Florian Rauch, Sonja Fuchs, Alexandra Friedrich, Daniel Sieh, Ivo Krummenacher, Holger Braunschweig, Maik Finze, Todd Benjamin Marder|2020|Chem.-Eur.J.|26|12794|doi:10.1002/chem.201905559
DOI: 10.5517/ccdc.csd.cc23fts5
title: CCDC 1949707: Experimental Crystal Structure Determination

description: Related Article: Florian Rauch, Sonja Fuchs, Alexandra Friedrich, Daniel Sieh, Ivo Krummenacher, Holger Braunschweig, Maik Finze, Todd Benjamin Marder|2020|Chem.-Eur.J.|26|12794|doi:10.1002/chem.201905559
DOI: 10.5517/ccdc.csd.cc23ftt6
title: CCDC 1949708: Experimental Crystal Structure Determination

description: Related Article: Florian Rauch, Sonja Fuchs, Alexandra Friedrich, Daniel Sieh, Ivo Krummenacher, Holger Braunschweig, Maik Finze, Todd Benjamin Marder|2020|Chem.-Eur.J.|26|12794|doi:10.1002/chem.201905559
DOI: 10.5517/ccdc.csd.cc23k1g6
title: CCDC 1952797: Experimental Crystal Structure Determination

description: Related Article: Dwaipayan Das, Prasun Mukherjee, Asish R. Das|2020|Org.Biomol.Chem.|18|8886|doi:10.1039/D0OB00077A
DOI: 10.5517/ccdc.csd.cc23k4nh
title: CCDC 1952896: Experimental Crystal Structure Determination

description: Related Article: Dwaipayan Das, Prasun Mukherjee, Asish R. Das|2020|Org.Biomol.Chem.|18|8886|doi:10.1039/D0OB00077A
DOI: 10.5517/ccdc.csd.cc20n3mf
title: CCDC 1866374: Experimental Crystal Structure Determination

description: Related Article: Jiong Yang, Xin-Hua Zhao, Yi-Fei Deng, Xin-Yu Zhang, Xiao-Yong Chang, Zhiping Zheng, Yuan-Zhu Zhang|2020|Inorg.Chem.|59|16215|doi:10.1021/acs.inorgchem.0c01917
DOI: 10.5517/ccdc.csd.cc24297s
title: CCDC 1968414: Experimental Crystal Structure Determination

description: Related Article: Jiong Yang, Xin-Hua Zhao, Yi-Fei Deng, Xin-Yu Zhang, Xiao-Yong Chang, Zhiping Zheng, Yuan-Zhu Zhang|2020|Inorg.Chem.|59|16215|doi:10.1021/acs.inorgchem.0c01917
DOI: 10.5517/ccdc.csd.cc2429j2
title: CCDC 1968423: Experimental Crystal Structure Determination

description: Related Article: Jiong Yang, Xin-Hua Zhao, Yi-Fei Deng, Xin-Yu Zhang, Xiao-Yong Chang, Zhiping Zheng, Yuan-Zhu Zhang|2020|Inorg.Chem.|59|16215|doi:10.1021/acs.inorgchem.0c01917
DOI: 10.5517/ccdc.csd.cc24qxrk
title: CCDC 1988239: Experimental Crystal Structure Determination

description: Related Article: Yulia Ganushevich, Almaz Zagidullin, Svetlana Kondrashova, Shamil Latypov, Vasili Miluykov, Peter Lönnecke, Evamarie Hey-Hawkins|2020|RSC Advances|10|39060|doi:10.1039/D0RA08080B
DOI: 10.5517/ccdc.csd.cc25ftm2
title: CCDC 2009284: Experimental Crystal Structure Determination

description: Related Article: Christoph G. P. Ziegler, Clemens Taube, John A. Kelly, Gabriele Hierlmeier, Maria Uttendorfer, Jan J. Weigand, Robert Wolf|2020|Chem.Commun.|56|14071|doi:10.1039/D0CC05365A
DOI: 10.5517/ccdc.csd.cc25ftn3
title: CCDC 2009285: Experimental Crystal Structure Determination

description: Related Article: Christoph G. P. Ziegler, Clemens Taube, John A. Kelly, Gabriele Hierlmeier, Maria Uttendorfer, Jan J. Weigand, Robert Wolf|2020|Chem.Commun.|56|14071|doi:10.1039/D0CC05365A
DOI: 10.5517/ccdc.csd.cc25ftp4
title: CCDC 2009286: Experimental Crystal Structure Determination

description: Related Article: Christoph G. P. Ziegler, Clemens Taube, John A. Kelly, Gabriele Hierlmeier, Maria Uttendorfer, Jan J. Weigand, Robert Wolf|2020|Chem.Commun.|56|14071|doi:10.1039/D0CC05365A
DOI: 10.5517/ccdc.csd.cc25ftq5
title: CCDC 2009287: Experimental Crystal Structure Determination

description: Related Article: Christoph G. P. Ziegler, Clemens Taube, John A. Kelly, Gabriele Hierlmeier, Maria Uttendorfer, Jan J. Weigand, Robert Wolf|2020|Chem.Commun.|56|14071|doi:10.1039/D0CC05365A
DOI: 10.5517/ccdc.csd.cc25l723
title: CCDC 2013514: Experimental Crystal Structure Determination

description: Related Article: Lihua Zeng, Shujian Sun, Zhang-Wen Wei, Yu Xin, Liping Liu, Jianyong Zhang|2020|RSC Advances|10|39323|doi:10.1039/D0RA07509D
DOI: 10.5517/ccdc.csd.cc25vkyk
title: CCDC 2021539: Experimental Crystal Structure Determination

description: Related Article: Minghui Cui, Ai-Ling Wang, Yingfan Liu, Hongping Xiao, Fengcai Li, Liming Zhou, Shaoming Fang, Xi-Li Li|2020|RSC Advances|10|39359|doi:10.1039/D0RA07237K
DOI: 10.5517/ccdc.csd.cc25vkzl
title: CCDC 2021540: Experimental Crystal Structure Determination

description: Related Article: Minghui Cui, Ai-Ling Wang, Yingfan Liu, Hongping Xiao, Fengcai Li, Liming Zhou, Shaoming Fang, Xi-Li Li|2020|RSC Advances|10|39359|doi:10.1039/D0RA07237K
DOI: 10.5517/ccdc.csd.cc2608h0
title: CCDC 2026051: Experimental Crystal Structure Determination

description: Related Article: Qing-Yun Fang, Li-Ming Zhao|2020|Chem.Commun.|56|14079|doi:10.1039/D0CC06061E
DOI: 10.5517/ccdc.csd.cc269rs2
title: CCDC 2035174: Experimental Crystal Structure Determination

description: Related Article: Javier A. Cabeza, Pablo García-Álvarez, Carlos J. Laglera-Gándara, Enrique Pérez-Carreño|2020|Chem.Commun.|56|14095|doi:10.1039/D0CC06614A
DOI: 10.5517/ccdc.csd.cc269rt3
title: CCDC 2035175: Experimental Crystal Structure Determination

description: Related Article: Javier A. Cabeza, Pablo García-Álvarez, Carlos J. Laglera-Gándara, Enrique Pérez-Carreño|2020|Chem.Commun.|56|14095|doi:10.1039/D0CC06614A
DOI: 10.5281/zenodo.4297256
title: data for article "Enhancement of Superconductivity by Amorphizing Molybdenum Silicide Films Using a Focused Ion Beam"

description: This dataset is the compilation of data used in the article "Enhancement of Superconductivity by Amorphizing Molybdenum Silicide Films Using a Focused Ion Beam" (https://doi.org/10.3390/nano10050950). For more info of samples see metadata2.txt
description: This research was funded by the European Union's Horizon 2020 research and innovation programme under grant agreements No 862660 QUANTUM E-LEAPS and No 766853 EFINED, Academy of Finland projects ETHEC No 322580 and UQS No 310909, The UK department of Business, Energy and Industrial Strategy (BEIS) and EPSRC Grant Award EP/R025487/1.
DOI: 10.5281/zenodo.4297255
title: data for article "Enhancement of Superconductivity by Amorphizing Molybdenum Silicide Films Using a Focused Ion Beam"

description: This dataset is the compilation of data used in the article "Enhancement of Superconductivity by Amorphizing Molybdenum Silicide Films Using a Focused Ion Beam" (https://doi.org/10.3390/nano10050950). For more info of samples see metadata2.txt
description: This research was funded by the European Union's Horizon 2020 research and innovation programme under grant agreements No 862660 QUANTUM E-LEAPS and No 766853 EFINED, Academy of Finland projects ETHEC No 322580 and UQS No 310909, The UK department of Business, Energy and Industrial Strategy (BEIS) and EPSRC Grant Award EP/R025487/1.
DOI: 10.5281/zenodo.4297448
title: MENYO-20k: A Multi-domain English - Yorùbá Corpus for Machine Translation

description: MENYO-20k is a multi-domain parallel dataset with texts obtained from news articles, ted talks, movie transcripts, radio transcripts, science and technology texts, and other short articles curated from the web and professional translators. The dataset has 20,100 parallel sentences split into 10,070 training sentences, 3,397 development sentences, and 6,633 test sentences (3,419 multi-domain, 1,714 news domain, and 1,500 ted talks speech transcript domain) The dataset is open but for non-commercial use because some of the data sources like Ted talks and JW news requires permission for commercial use. <strong>Acknowledgement</strong>: This project was supported by the AI4D language dataset fellowship through K4All and Zindi Africa
description: {"references": ["David I. Adelani et al. MENYO-20k: A Multi-domain English - Yor\u00f9b\u00e1 Corpus for Machine Translation. https://github.com/dadelani/menyo-20k_MT"]}
DOI: 10.5281/zenodo.4297447
title: MENYO-20k: A Multi-domain English - Yorùbá Corpus for Machine Translation

description: MENYO-20k is a multi-domain parallel dataset with texts obtained from news articles, ted talks, movie transcripts, radio transcripts, science and technology texts, and other short articles curated from the web and professional translators. The dataset has 20,100 parallel sentences split into 10,070 training sentences, 3,397 development sentences, and 6,633 test sentences (3,419 multi-domain, 1,714 news domain, and 1,500 ted talks speech transcript domain) The dataset is open but for non-commercial use because some of the data sources like Ted talks and JW news requires permission for commercial use. <strong>Acknowledgement</strong>: This project was supported by the AI4D language dataset fellowship through K4All and Zindi Africa
description: {"references": ["David I. Adelani et al. MENYO-20k: A Multi-domain English - Yor\u00f9b\u00e1 Corpus for Machine Translation. https://github.com/dadelani/menyo-20k_MT"]}
DOI: 10.5285/b11f3fa3303e46e6b0d44b058947a3f5
title: ESA Soil Moisture Climate Change Initiative (Soil_Moisture_cci): Version 05.2 data collection

description: Soil Moisture data (version 05.2) from the European Space Agency's (ESA) Soil Moisture Climate Change Initiative (CCI) project. This dataset collection contains three surface soil moisture datasets, alongside ancilliary data products. The ACTIVE and PASSIVE products have been created by fusing satellite scatterometer and radiometer soil moisture products respectively. In the case of the ACTIVE product, these have been derived from the AMI-WS and ASCAT satellite instruments and for the PASSIVE product from the satellite instruments SMMR, SSM/I, TMI, AMSR-E, WindSat, AMSR2, SMOS and SMAP. The COMBINED product is generated from the Level 2 active and passive instruments.. The homogenized and merged products present a global coverage of surface soil moisture at a spatial resolution of 0.25 degrees. The products are provided as global daily images, in NetCDF-4 classic file format, the PASSIVE and COMBINED products covering the period (yyyy-mm-dd) 1978-11-01 to 2019-12-31 and the ACTIVE product covering 1991-08-05 to 2019-12-31. The soil moisture data for the PASSIVE and the COMBINED product are provided in volumetric units [m3 m-3], while the ACTIVE soil moisture data are expressed in percent of saturation [%]. For information regarding the theoretical and algorithmic base of the datasets, please see the Algorithm Theoretical Baseline Document (ATBD). Other additional documentation and information documentation relating to the datasets can also be found on the CCI Soil Moisture project web site or in the Product Specification Document. The data set should be cited using the all of the following references: 1. Gruber, A., Scanlon, T., van der Schalie, R., Wagner, W., and Dorigo, W. (2019). Evolution of the ESA CCI Soil Moisture climate data records and their underlying merging methodology, Earth Syst. Sci. Data, 11, 717–739, https://doi.org/10.5194/essd-11-717-2019 2. Dorigo, W.A., Wagner, W., Albergel, C., Albrecht, F., Balsamo, G., Brocca, L., Chung, D., Ertl, M., Forkel, M., Gruber, A., Haas, E., Hamer, D. P. Hirschi, M., Ikonen, J., De Jeu, R. Kidd, R. Lahoz, W., Liu, Y.Y., Miralles, D., Lecomte, P. (2017). ESA CCI Soil Moisture for improved Earth system understanding: State-of-the art and future directions. In Remote Sensing of Environment, 2017, ISSN 0034-4257, https://doi.org/10.1016/j.rse.2017.07.001 3. Gruber, A., Dorigo, W. A., Crow, W., Wagner W. (2017). Triple Collocation-Based Merging of Satellite Soil Moisture Retrievals. IEEE Transactions on Geoscience and Remote Sensing. PP. 1-13. 10.1109/TGRS.2017.2734070
DOI: 10.5281/zenodo.4300167
title: dataset for paper Vanhaebost J, Faouzi M, Mangin P, Michaud K: New reference tables and user-friendly Internet application for predicted heart weights. Int J Legal Med 2014, 128(4):615-620.

description: The heart weight is the most important parameter in the determination of cardiac hypertrophy. The obtained heart weight value should be compared against tables of normal weights by age, gender and body weight and height In the study by Vanhaebost<em> et al</em>. has been shown in the Swiss population that the heart weight increases along with the increase of the body weight, body height, BMI and body surface area (BSA). The mean heart weight is greater in men than in women at a similar body weight. The reference tables for predicted heart weights obtained from this study are presented as an user-friendly internet application (http://calc.chuv.ch/Heartweight) enabling the comparison of heart weights observed at autopsy with the reference values.