10.001 a 10.010 de 16.049 Resultados
Adobe PDF - 153,0 KB -
MD5: 09bbb7a75ba727239307fda6c9e1fab3
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Hoja de cálculo MS Excel - 15,8 KB -
MD5: 56c87251503e8f77cc857e4bf5d893f5
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Federico, Giovanni; Tena Junguito, Antonio, 2023, "Federico-Tena World Population Historical Database : Martinique (French Colonies)", https://doi.org/10.21950/6RWGVT, e-cienciaDatos, V1
Project developed by Giovanni Federico (New York University Abu Dhabi) and Antonio Tena Junguito (Universidad Carlos III de Madrid). Dataset: Martinique (French Colonies) |
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Adobe PDF - 152,1 KB -
MD5: 14e3dbb970fdb7a13a89194e06bf0d34
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Hoja de cálculo MS Excel - 14,9 KB -
MD5: 5d83a0926fe152e740f93dffe193a139
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Federico, Giovanni; Tena Junguito, Antonio, 2023, "Federico-Tena World Population Historical Database : Jamaica", https://doi.org/10.21950/2CAXYP, e-cienciaDatos, V1
Project developed by Giovanni Federico (New York University Abu Dhabi) and Antonio Tena Junguito (Universidad Carlos III de Madrid). Dataset: Jamaica |
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Adobe PDF - 151,5 KB -
MD5: fb9ed17debcc6250dbddf929ada63f6e
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Hoja de cálculo MS Excel - 14,4 KB -
MD5: 8ff9d2005f7fae780d98545ede2a8119
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26 jun 2023 - Universidad Carlos III de Madrid
Ernesto Gonzalez-Saiz; Daniel Garcia-Gonzalez, 2023, "Model-Driven Identification Framework for Optimal Constitutive Modelling from Kinematics and Rheological Arrangement", https://doi.org/10.5281/ZENODO.8083338
Machine Learning framework for generation of constitutive models capable of automatically identifying the optimal kinematics and rheological model. It consists of a multiphysics model-driven framework that optimally selects the most suitable model kinematics, its rheological comp...Dataset recolectado desde DataCite con autores de la UC3M. El enlace le llevará directamente a los datos originales en dicho archivo. |
25 jun 2023 - Universidad de Alcalá
Amin Khairoun; Florent Mouillot; Wentao Chen; Philippe Ciais; Emilio Chuvieco, 2025, "Fire-related forest loss", https://doi.org/10.5281/ZENODO.8069732
The dataset includes the different figures used in the study.Dataset recolectado desde Zenodo con autores de la UAH. El enlace le llevará directamente a los datos originales en dicho archivo. |
