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Acknowledgment:

The experiments presented in this paper were carried out using ClusterUY (site: https://cluster.uy)

Publicaciones

En esta sección se encuentran los registros de las publicaciones que se generaron con contribución de cluster.uy.

2023

  1. Delgado, S., Fossati, M. & Santoro, P. (2023). Métodos Numéricos Aplicados a la Gestión de Grandes Cuerpos de Agua a Superficie Libre. Mecánica Computacional, XL, 1601-1610.

2022

  1. Chavat, J., Nesmachnow, S., Graneri, J., & Alvez, G. (2022). ECD-UY, detailed household electricity consumption dataset of Uruguay. Scientific Data, 9(1), 1-16.

  2. Gonella, R., Bourel, M., & Bel, L. (2022). Facing spatial massive data in science and society: Variable selection for spatial models. Spatial Statistics, 100627.

  3. Rivela, C. B., Cardona, A. L., Blanco, M. B., Barnes, I., Kieninger, M., Ventura, O. N., & Teruel, M. A. (2022). Degradation mechanism of 2-fluoropropene by Cl atoms: experimental and theoretical products distribution studies. Physical Chemistry Chemical Physics.

  4. Yunlong Shi, Ari Zeida, Caitlin E. Edwards, Michael L. Mallory, Santiago Sastre, Matías R. Machado, Raymond J. Pickles, Ling Fu, Keke Liu, Jing Yang, Ralph S. Baric, Richard C. Boucher, Rafael Radi, and Kate S. Carrol (2022). Thiol-based chemical probes exhibit antiviral activity against SARS-CoV-2 via allosteric disulfide disruptionin the spike glycoprotein. Proceedings of the National Academy of Sciences, 119(6)

  5. Chavat Pérez, F. (2022). Modelos Seq2Seq para la transcripción de documentos del Archivo Berrutti. Tesis de grado

  6. Gutiérrez, A., & Fovell, R. G. (2018). A new gust parameterization for weather prediction models. Journal of Wind Engineering and Industrial Aerodynamics, 177, 45-59.

  7. Gutiérrez, A., Porrini, C., & Fovell, R. G. (2020). Combination of wind gust models in convective events. Journal of Wind Engineering and Industrial Aerodynamics, 199, 104118.

  8. Rivara-Espasandín, M., Balestrazzi, L., Dufort y Álvarez, G., Ochoa, I., Seroussi, G., Smircich, P., … & Martín, Á. (2022). Nanopore quality score resolution can be reduced with little effect on downstream analysis. Bioinformatics Advances, 2(1), vbac054.

  9. Pazos Obregón, F., Silvera, D., Soto, P., Yankilevich, P., Guerberoff, G., & Cantera, R. (2022). Gene function prediction in five model eukaryotes exclusively based on gene relative location through machine learning. Scientific Reports, 12(1), 1-11.

  10. Silvera, D. (2022). Implementación de clasificadores jerárquicos multiclase para la predicción de función de genes a partir de su ubicación en el genoma. Tesis de Maestría

2021

  1. Barrera, E. E., Zonta, F., & Pantano, S. (2021). Dissecting the role of glutamine in seeding peptide aggregation. Computational and structural biotechnology journal, 19, 1595-1602.

  2. Barrera, E. E., Pantano, S., & Zonta, F. (2021). A homogeneous dataset of polyglutamine and glutamine rich aggregating peptides simulations. Data in Brief, 107109.

  3. Di Chiara, L. (2021). Planificación de largo plazo y caracterización de sistemas eléctricos en américa latina en base a sus recursos. [Tesis de maestría en ingeniería de la energía, Facultad de Ingeniería, UdelaR]

  4. Garay, P. G., Barrera, E. E., Klein, F., Machado, M. R., Soñora, M., & Pantano, S. (2021). The SIRAH-CoV-2 Initiative: a coarse-grained simulations’ dataset of the sars-cov-2 proteome. database, 9, 28.

  5. Klein, F., Sardi, F., Machado, M. R., Ortega, C., Comini, M. A., & Pantano, S. (2021). CUTie2: the attack of the cyclic nucleotide sensor clones. Frontiers in molecular biosciences, 8.

  6. Machado, M. R., & Pantano, S. (2021). Fighting viruses with computers, right now. Current Opinion in Virology, 48, 91-99.

  7. López-Vázquez, C., Tasistro, A., and Hochsztain, E. (2021). Exact tables for the Friedman rank test: Case with ties. Chilean Journal of Statistics, vol 12, 1.

  8. Soñora, M., Martinez, L., Pantano, S., & Machado, M. R. (2021). Wrapping Up Viruses at Multiscale Resolution: Optimizing PACKMOL and SIRAH Execution for Simulating the Zika Virus. Journal of Chemical Information and Modeling, 61(1), 408-422.

  9. González Madina, F., Gutiérrez, A., & Galione, P. (2021). Computational fluid dynamics study of Savonius rotors using OpenFOAM. Wind Engineering, 45(3), 630-647.

2020

  1. Alonso, R., & Solari, S. (2020). Improvement of the high-resolution wave hindcast of the Uruguayan waters focusing on the Río de la Plata Estuary. Coastal Engineering, 161.

  2. Chavat J., Graneri J., Nesmachnow S. (2020) Household Energy Disaggregation Based on Pattern Consumption Similarities. In: Nesmachnow S., Hernández Callejo L. (eds) Smart Cities. ICSC-CITIES 2019. Communications in Computer and Information Science, vol 1152. Springer, Cham

  3. Frigini, E. N., Barrera, E. E., Pantano, S., & Porasso, R. D. (2020). Role of membrane curvature on the activation/deactivation of Carnitine Palmitoyltransferase 1A: A coarse grain molecular dynamic study. Biochimica et Biophysica Acta (BBA)-Biomembranes, 1862(2), 183094.

  4. Gutiérrez, A., Porrini, C., & Fovell, R. G. (2020). Combination of wind gust models in convective events. Journal of Wind Engineering and Industrial Aerodynamics, 199, 104118.

  5. Gutiérrez, A., Porrini, C., & Fovell, R. G. (2020). Combination of wind gust models in convective events. Journal of Wind Engineering and Industrial Aerodynamics, 199, 104118.

  6. Irigaray D., Dufrechou E., Pedemonte M., Ezzatti P., López-Vázquez C. (2020) Accelerating the Calculation of Friedman Test Tables on Many-Core Processors. In: Crespo-Mariño J., Meneses-Rojas E. (eds) High Performance Computing. CARLA 2019. Communications in Computer and Information Science, vol 1087. Springer, Cham

  7. Landry, A. P., Moon, S., Bonanata, J., Cho, U. S., Coitiño, L., & Banerjee, R. (2020). Dismantling and rebuilding the trisulfide cofactor demonstrates its essential role in human sulfide quinone oxidoreductase. bioRxiv.

  8. Pienika, R., Usera, G., & Ramos, H. M. (2020). Simulation of a Hydrostatic Pressure Machine with Caffa3d Solver: Numerical Model Characterization and Evaluation. Water, 12(9), 2419.

  9. Porteiro R., Nesmachnow S., Hernández-Callejo L. (2020) Short Term Load Forecasting of Industrial Electricity Using Machine Learning. In: Nesmachnow S., Hernández Callejo L. (eds) Smart Cities. ICSC-CITIES 2019. Communications in Computer and Information Science, vol 1152. Springer, Cham

  10. Salta, Z., Lupi, J., Tasinato, N., Barone, V., & Ventura, O. N. (2020). Unraveling the role of additional OH-radicals in the H–Abstraction from Dimethyl sulfide using quantum chemical computations. Chemical Physics Letters, 739, 136963.

  11. Salta, Z., Lupi, J., Barone, V., & Ventura, O. (2020). H–Abstraction from Dimethyl Sulfide in the Presence of an Excess of Hydroxyl Radicals. A Quantum Chemical Evaluation of Thermochemical and Kinetic Parameters Unveil an Alternative Pathway to Dimethyl Sulfoxide.

  12. [Ventura, O. (2021). SVECV-F12: A Composite Scheme for an Accurate and Cost Effective Evaluation of Reaction Barriers. I. Benchmarking Using the HTBH38/08 and NHTBH38/08 Barrier Heights Databases.] (https://chemrxiv.org/engage/chemrxiv/article-details/60c7547cbb8c1a1ce63dc224)

  13. de Almeida Lucas, E., Arce, A. G., & Camargo, S. (2020). Pronóstico de energía eólica en Uruguay para horizontes temporales de corto plazo en base a modelo numérico de mesoescala y redes neuronales artificiales. ENERLAC. Revista de energía de Latinoamérica y el Caribe, 4(1), 32-43.

2019

  1. Carlos López-Vázquez & Esther Hochsztain (2019) Extended and updated tables for the Friedman rank test, Communications in Statistics - Theory and Methods, 48:2, 268-281, DOI: 10.1080/03610926.2017.1408829

  2. Garabedian S., Porteiro R., Nesmachnow S. (2019) Generation and Classification of Energy Load Curves Using a Distributed MapReduce Approach. In: Torres M., Klapp J. (eds) Supercomputing. ISUM 2019. Communications in Computer and Information Science, vol 1151. Springer, Cham

  3. Guggeri, A., & Draper, M. (2019). Large Eddy Simulation of an Onshore Wind Farm with the Actuator Line Model Including Wind Turbine’s Control below and above Rated Wind Speed. Energies, 12(18), 3508.

  4. Irving, K., Kieninger, M., & Ventura, O. N. (2019). Basis Set Effects in the Description of the Cl-O Bond in ClO and XClO/ClOX Isomers (X= H, O, and Cl) Using DFT and CCSD (T) Methods. Journal of Chemistry, 2019.

  5. José Lezama (2019) Overcoming the Disentanglement vs Reconstruction Trade-off via Jacobian Supervision. International Conference on Learning Representations

  6. Petsis, G., Salta, Z., Kosmas, A. M., & Ventura, O. N. (2019). Theoretical study of the microhydration of 1‐chloro and 2‐chloro ethanol as a clue for their relative propensity toward dehalogenation. International Journal of Quantum Chemistry, e25931.

  7. Salta, Z., Kosmas, A. M., Ventura, O. N., & Barone, V. (2019). Computational Evidence Suggests That 1-Chloroethanol May Be an Intermediate in the Thermal Decomposition of 2-Chloroethanol into Acetaldehyde and HCl. The Journal of Physical Chemistry A, 123(10), 1983-1998.

  8. Ventura, O.N., Kieninger, M., Salta, Z. et al.(2019) Enthalpies of formation of the benzyloxyl, benzylperoxyl, hydroxyphenyl radicals and related species on the potential energy surface for the reaction of toluene with the hydroxyl radical. Theor Chem Acc 138, 115 .

  9. Villamil, J., Avila, L. J., Morando, M., Sites Jr, J. W., Leaché, A. D., Maneyro, R., & Camargo, A. (2019). Coalescent-based species delimitation in the sand lizards of the Liolaemus wiegmannii complex (Squamata: Liolaemidae). Molecular Phylogenetics and Evolution, 138, 89-101.

2018

  1. Gutiérrez, A., & Fovell, R. G. (2018). A new gust parameterization for weather prediction models. Journal of Wind Engineering and Industrial Aerodynamics, 177, 45-59.