ReP USP - Resultado da busca

Artigo de periodico
Impact of the COVID-19 pandemic on dengue in Brazil: interrupted time series analysis of changes in surveillance and transmission (2024)
Roster, Kirstin Oliveira ; Martinell, Tiago; Connaughton, Colm ; Santillana, Mauricio ; Rodrigues, Francisco Aparecido
Fonte: PLoS Neglected Tropical Diseases. Unidade: ICMC
Assuntos: DENGUE, ANÁLISE DE SÉRIES TEMPORAIS, APRENDIZADO COMPUTACIONAL
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ABNT
ROSTER, Kirstin Oliveira et al. Impact of the COVID-19 pandemic on dengue in Brazil: interrupted time series analysis of changes in surveillance and transmission. PLoS Neglected Tropical Diseases, v. 18, n. 12, p. 1-14, 2024Tradução . . Disponível em: https://doi.org/10.1371/ journal.pntd.0012726. Acesso em: 08 out. 2025.
APA
Roster, K. O., Martinell, T., Connaughton, C., Santillana, M., & Rodrigues, F. A. (2024). Impact of the COVID-19 pandemic on dengue in Brazil: interrupted time series analysis of changes in surveillance and transmission. PLoS Neglected Tropical Diseases, 18( 12), 1-14. doi:10.1371/journal.pntd.0012726
NLM
Roster KO, Martinell T, Connaughton C, Santillana M, Rodrigues FA. Impact of the COVID-19 pandemic on dengue in Brazil: interrupted time series analysis of changes in surveillance and transmission [Internet]. PLoS Neglected Tropical Diseases. 2024 ; 18( 12): 1-14.[citado 2025 out. 08 ] Available from: https://doi.org/10.1371/ journal.pntd.0012726
Vancouver
Roster KO, Martinell T, Connaughton C, Santillana M, Rodrigues FA. Impact of the COVID-19 pandemic on dengue in Brazil: interrupted time series analysis of changes in surveillance and transmission [Internet]. PLoS Neglected Tropical Diseases. 2024 ; 18( 12): 1-14.[citado 2025 out. 08 ] Available from: https://doi.org/10.1371/ journal.pntd.0012726
Artigo de periodico
A machine learning approach to predicting dynamical observables from network structure (2024)
Rodrigues, Francisco Aparecido ; Peron, Thomas ; Connaughton, Colm ; Kurths, Jürgen ; Moreno, Yamir
Fonte: Proceedings of the Royal Society A. Unidade: ICMC
Assuntos: REDES COMPLEXAS, APRENDIZADO COMPUTACIONAL, SISTEMAS DINÂMICOS
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ABNT
RODRIGUES, Francisco Aparecido et al. A machine learning approach to predicting dynamical observables from network structure. Proceedings of the Royal Society A, v. 481, p. 1-12, 2024Tradução . . Disponível em: https://doi.org/10.1098/rspa.2024.0435. Acesso em: 08 out. 2025.
APA
Rodrigues, F. A., Peron, T., Connaughton, C., Kurths, J., & Moreno, Y. (2024). A machine learning approach to predicting dynamical observables from network structure. Proceedings of the Royal Society A, 481, 1-12. doi:10.1098/rspa.2024.0435
NLM
Rodrigues FA, Peron T, Connaughton C, Kurths J, Moreno Y. A machine learning approach to predicting dynamical observables from network structure [Internet]. Proceedings of the Royal Society A. 2024 ; 481 1-12.[citado 2025 out. 08 ] Available from: https://doi.org/10.1098/rspa.2024.0435
Vancouver
Rodrigues FA, Peron T, Connaughton C, Kurths J, Moreno Y. A machine learning approach to predicting dynamical observables from network structure [Internet]. Proceedings of the Royal Society A. 2024 ; 481 1-12.[citado 2025 out. 08 ] Available from: https://doi.org/10.1098/rspa.2024.0435
Artigo de periodico-carta/editorial
Complex systems in the spotlight: next steps after the 2021 Nobel Prize in Physics [Editorial] (2023)
Bianconi, Ginestra ; Arenas, Alex ; Biamonte, Jacob ; Carr, Lincoln D ; Kahng, Byungnam ; Kertesz, Janos ; Kurths, Jürgen ; Lü, Linyuan ; Masoller, Cristina ; Motter, Adilson E ; Perc, Matjaz ; Radicchi, Filippo ; Ramaswamy, Ramakrishna ; Rodrigues, Francisco Aparecido ; Sales-Pardo, Marta ; Miguel, Maxi San ; Thurner, Stefan ; Yasseri, Taha
Fonte: Journal of Physics : Complexity. Unidade: ICMC
Assuntos: FUTURO, COMPLEXIDADE, CIÊNCIAS EXATAS
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ABNT
BIANCONI, Ginestra et al. Complex systems in the spotlight: next steps after the 2021 Nobel Prize in Physics [Editorial]. Journal of Physics : Complexity. Bristol: Instituto de Ciências Matemáticas e de Computação, Universidade de São Paulo. Disponível em: https://doi.org/10.1088/2632-072X/ac7f75. Acesso em: 08 out. 2025. , 2023
APA
Bianconi, G., Arenas, A., Biamonte, J., Carr, L. D., Kahng, B., Kertesz, J., et al. (2023). Complex systems in the spotlight: next steps after the 2021 Nobel Prize in Physics [Editorial]. Journal of Physics : Complexity. Bristol: Instituto de Ciências Matemáticas e de Computação, Universidade de São Paulo. doi:10.1088/2632-072X/ac7f75
NLM
Bianconi G, Arenas A, Biamonte J, Carr LD, Kahng B, Kertesz J, Kurths J, Lü L, Masoller C, Motter AE, Perc M, Radicchi F, Ramaswamy R, Rodrigues FA, Sales-Pardo M, Miguel MS, Thurner S, Yasseri T. Complex systems in the spotlight: next steps after the 2021 Nobel Prize in Physics [Editorial] [Internet]. Journal of Physics : Complexity. 2023 ; 4 1-28.[citado 2025 out. 08 ] Available from: https://doi.org/10.1088/2632-072X/ac7f75
Vancouver
Bianconi G, Arenas A, Biamonte J, Carr LD, Kahng B, Kertesz J, Kurths J, Lü L, Masoller C, Motter AE, Perc M, Radicchi F, Ramaswamy R, Rodrigues FA, Sales-Pardo M, Miguel MS, Thurner S, Yasseri T. Complex systems in the spotlight: next steps after the 2021 Nobel Prize in Physics [Editorial] [Internet]. Journal of Physics : Complexity. 2023 ; 4 1-28.[citado 2025 out. 08 ] Available from: https://doi.org/10.1088/2632-072X/ac7f75
Artigo de periodico
Cultural heterogeneity constrains diffusion of innovations (2023)
Pineda, Aruane Mello ; Reia, Sandro Martinelli ; Connaughton, Colm ; Fontanari, José Fernando ; Rodrigues, Francisco Aparecido
Fonte: EPL - Europhysics Letters. Unidades: IFSC, ICMC
Assuntos: MODELOS, COMPORTAMENTO SOCIAL (ESTUDO), CONSCIÊNCIA (PERCEPÇÃO), INTELIGÊNCIA COLETIVA, APRENDIZAGEM SOCIAL, FÍSICA TEÓRICA
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ABNT
PINEDA, Aruane Mello et al. Cultural heterogeneity constrains diffusion of innovations. EPL - Europhysics Letters, v. 143, n. 4, p. 42003-p1-42003-p6, 2023Tradução . . Disponível em: https://doi.org/10.1209/0295-5075/aceeab. Acesso em: 08 out. 2025.
APA
Pineda, A. M., Reia, S. M., Connaughton, C., Fontanari, J. F., & Rodrigues, F. A. (2023). Cultural heterogeneity constrains diffusion of innovations. EPL - Europhysics Letters, 143( 4), 42003-p1-42003-p6. doi:10.1209/0295-5075/aceeab
NLM
Pineda AM, Reia SM, Connaughton C, Fontanari JF, Rodrigues FA. Cultural heterogeneity constrains diffusion of innovations [Internet]. EPL - Europhysics Letters. 2023 ; 143( 4): 42003-p1-42003-p6.[citado 2025 out. 08 ] Available from: https://doi.org/10.1209/0295-5075/aceeab
Vancouver
Pineda AM, Reia SM, Connaughton C, Fontanari JF, Rodrigues FA. Cultural heterogeneity constrains diffusion of innovations [Internet]. EPL - Europhysics Letters. 2023 ; 143( 4): 42003-p1-42003-p6.[citado 2025 out. 08 ] Available from: https://doi.org/10.1209/0295-5075/aceeab
Artigo de periodico
Machine learning-based prediction of Q-voter model in complex networks (2023)
Pineda, Aruane Mello ; Kent, Paul; Connaughton, Colm ; Rodrigues, Francisco Aparecido
Fonte: Journal of Statistical Mechanics. Unidade: ICMC
Assuntos: APRENDIZADO COMPUTACIONAL, COMUNICAÇÃO, REDES DE INFORMAÇÃO
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ABNT
PINEDA, Aruane Mello et al. Machine learning-based prediction of Q-voter model in complex networks. Journal of Statistical Mechanics, v. 2023, p. 1-33, 2023Tradução . . Disponível em: https://doi.org/10.1088/1742-5468/ad06a6. Acesso em: 08 out. 2025.
APA
Pineda, A. M., Kent, P., Connaughton, C., & Rodrigues, F. A. (2023). Machine learning-based prediction of Q-voter model in complex networks. Journal of Statistical Mechanics, 2023, 1-33. doi:10.1088/1742-5468/ad06a6
NLM
Pineda AM, Kent P, Connaughton C, Rodrigues FA. Machine learning-based prediction of Q-voter model in complex networks [Internet]. Journal of Statistical Mechanics. 2023 ; 2023 1-33.[citado 2025 out. 08 ] Available from: https://doi.org/10.1088/1742-5468/ad06a6
Vancouver
Pineda AM, Kent P, Connaughton C, Rodrigues FA. Machine learning-based prediction of Q-voter model in complex networks [Internet]. Journal of Statistical Mechanics. 2023 ; 2023 1-33.[citado 2025 out. 08 ] Available from: https://doi.org/10.1088/1742-5468/ad06a6
Artigo de periodico
Forecasting new diseases in low-data settings using transfer learning (2022)
Roster, Kirstin ; Connaughton, Colm ; Rodrigues, Francisco Aparecido
Fonte: Chaos, Solitons and Fractals. Unidade: ICMC
Assuntos: APRENDIZADO COMPUTACIONAL, COVID-19, ZIKA VÍRUS, TOMADA DE DECISÃO, SURTOS DE DOENÇAS
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ABNT
ROSTER, Kirstin e CONNAUGHTON, Colm e RODRIGUES, Francisco Aparecido. Forecasting new diseases in low-data settings using transfer learning. Chaos, Solitons and Fractals, v. 161, p. 1-8, 2022Tradução . . Disponível em: https://doi.org/10.1016/j.chaos.2022.112306. Acesso em: 08 out. 2025.
APA
Roster, K., Connaughton, C., & Rodrigues, F. A. (2022). Forecasting new diseases in low-data settings using transfer learning. Chaos, Solitons and Fractals, 161, 1-8. doi:10.1016/j.chaos.2022.112306
NLM
Roster K, Connaughton C, Rodrigues FA. Forecasting new diseases in low-data settings using transfer learning [Internet]. Chaos, Solitons and Fractals. 2022 ; 161 1-8.[citado 2025 out. 08 ] Available from: https://doi.org/10.1016/j.chaos.2022.112306
Vancouver
Roster K, Connaughton C, Rodrigues FA. Forecasting new diseases in low-data settings using transfer learning [Internet]. Chaos, Solitons and Fractals. 2022 ; 161 1-8.[citado 2025 out. 08 ] Available from: https://doi.org/10.1016/j.chaos.2022.112306
Artigo de periodico
The rise and fall of countries in the global value chains (2022)
Alves, Luiz Gustavo de Andrade ; Mangioni, Giuseppe ; Rodrigues, Francisco Aparecido ; Panzarasa, Pietro ; Moreno, Yamir
Fonte: Scientific Reports. Unidade: ICMC
Assuntos: ECONOMIA INTERNACIONAL, COMÉRCIO, REDES COMPLEXAS
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ABNT
ALVES, Luiz Gustavo de Andrade et al. The rise and fall of countries in the global value chains. Scientific Reports, v. 12, p. 1-14, 2022Tradução . . Disponível em: https://doi.org/10.1038/s41598-022-12067-x. Acesso em: 08 out. 2025.
APA
Alves, L. G. de A., Mangioni, G., Rodrigues, F. A., Panzarasa, P., & Moreno, Y. (2022). The rise and fall of countries in the global value chains. Scientific Reports, 12, 1-14. doi:10.1038/s41598-022-12067-x
NLM
Alves LG de A, Mangioni G, Rodrigues FA, Panzarasa P, Moreno Y. The rise and fall of countries in the global value chains [Internet]. Scientific Reports. 2022 ; 12 1-14.[citado 2025 out. 08 ] Available from: https://doi.org/10.1038/s41598-022-12067-x
Vancouver
Alves LG de A, Mangioni G, Rodrigues FA, Panzarasa P, Moreno Y. The rise and fall of countries in the global value chains [Internet]. Scientific Reports. 2022 ; 12 1-14.[citado 2025 out. 08 ] Available from: https://doi.org/10.1038/s41598-022-12067-x
Artigo de periodico
Machine-learning-based forecasting of dengue fever in Brazilian cities using epidemiologic and meteorological variables (2022)
Roster, Kirstin ; Connaughton, Colm ; Rodrigues, Francisco Aparecido
Fonte: American Journal of Epidemiology. Unidade: ICMC
Assuntos: DENGUE, SAÚDE PÚBLICA, APRENDIZADO COMPUTACIONAL, PREDIÇÃO
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ABNT
ROSTER, Kirstin e CONNAUGHTON, Colm e RODRIGUES, Francisco Aparecido. Machine-learning-based forecasting of dengue fever in Brazilian cities using epidemiologic and meteorological variables. American Journal of Epidemiology, v. 191, n. 10, p. 1803–1812, 2022Tradução . . Disponível em: https://doi.org/10.1093/aje/kwac090. Acesso em: 08 out. 2025.
APA
Roster, K., Connaughton, C., & Rodrigues, F. A. (2022). Machine-learning-based forecasting of dengue fever in Brazilian cities using epidemiologic and meteorological variables. American Journal of Epidemiology, 191( 10), 1803–1812. doi:10.1093/aje/kwac090
NLM
Roster K, Connaughton C, Rodrigues FA. Machine-learning-based forecasting of dengue fever in Brazilian cities using epidemiologic and meteorological variables [Internet]. American Journal of Epidemiology. 2022 ; 191( 10): 1803–1812.[citado 2025 out. 08 ] Available from: https://doi.org/10.1093/aje/kwac090
Vancouver
Roster K, Connaughton C, Rodrigues FA. Machine-learning-based forecasting of dengue fever in Brazilian cities using epidemiologic and meteorological variables [Internet]. American Journal of Epidemiology. 2022 ; 191( 10): 1803–1812.[citado 2025 out. 08 ] Available from: https://doi.org/10.1093/aje/kwac090
Artigo de periodico
The drivers of systemic risk in financial networks: a data-driven machine learning analysis (2021)
Alexandre, Michel ; Silva, Thiago Christiano ; Connaughton, Colm ; Rodrigues, Francisco Aparecido
Fonte: Chaos, Solitons and Fractals. Unidade: ICMC
Assuntos: REDES COMPLEXAS, INSTITUIÇÕES FINANCEIRAS, RISCO (SEGURO)
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ABNT
ALEXANDRE, Michel et al. The drivers of systemic risk in financial networks: a data-driven machine learning analysis. Chaos, Solitons and Fractals, v. 153, p. 1-11, 2021Tradução . . Disponível em: https://doi.org/10.1016/j.chaos.2021.111588. Acesso em: 08 out. 2025.
APA
Alexandre, M., Silva, T. C., Connaughton, C., & Rodrigues, F. A. (2021). The drivers of systemic risk in financial networks: a data-driven machine learning analysis. Chaos, Solitons and Fractals, 153, 1-11. doi:10.1016/j.chaos.2021.111588
NLM
Alexandre M, Silva TC, Connaughton C, Rodrigues FA. The drivers of systemic risk in financial networks: a data-driven machine learning analysis [Internet]. Chaos, Solitons and Fractals. 2021 ; 153 1-11.[citado 2025 out. 08 ] Available from: https://doi.org/10.1016/j.chaos.2021.111588
Vancouver
Alexandre M, Silva TC, Connaughton C, Rodrigues FA. The drivers of systemic risk in financial networks: a data-driven machine learning analysis [Internet]. Chaos, Solitons and Fractals. 2021 ; 153 1-11.[citado 2025 out. 08 ] Available from: https://doi.org/10.1016/j.chaos.2021.111588
Artigo de periodico
Bayesian reference analysis for the generalized normal linear regression model (2021)
Tomazella, Vera Lucia Damasceno ; Jesus, Sandra Rêgo ; Gazon, Amanda Buosi ; Louzada, Francisco ; Nadarajah, Saralees ; Nascimento, Diego Carvalho ; Rodrigues, Francisco Aparecido ; Ramos, Pedro Luiz
Fonte: Symmetry. Unidade: ICMC
Assuntos: INFERÊNCIA BAYESIANA, ANÁLISE DE REGRESSÃO E DE CORRELAÇÃO, MÉTODOS MCMC
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ABNT
TOMAZELLA, Vera Lucia Damasceno et al. Bayesian reference analysis for the generalized normal linear regression model. Symmetry, v. 13, n. 5, p. 1-20, 2021Tradução . . Disponível em: https://doi.org/10.3390/sym13050856. Acesso em: 08 out. 2025.
APA
Tomazella, V. L. D., Jesus, S. R., Gazon, A. B., Louzada, F., Nadarajah, S., Nascimento, D. C., et al. (2021). Bayesian reference analysis for the generalized normal linear regression model. Symmetry, 13( 5), 1-20. doi:10.3390/sym13050856
NLM
Tomazella VLD, Jesus SR, Gazon AB, Louzada F, Nadarajah S, Nascimento DC, Rodrigues FA, Ramos PL. Bayesian reference analysis for the generalized normal linear regression model [Internet]. Symmetry. 2021 ; 13( 5): 1-20.[citado 2025 out. 08 ] Available from: https://doi.org/10.3390/sym13050856
Vancouver
Tomazella VLD, Jesus SR, Gazon AB, Louzada F, Nadarajah S, Nascimento DC, Rodrigues FA, Ramos PL. Bayesian reference analysis for the generalized normal linear regression model [Internet]. Symmetry. 2021 ; 13( 5): 1-20.[citado 2025 out. 08 ] Available from: https://doi.org/10.3390/sym13050856
Trabalho de evento-resumo periodico
Estimating the causal effect of mobility on Dengue during the COVID-19 pandemic (2021)
Roster, Kirstin ; Connaughton, Colm ; Rodrigues, Francisco Aparecido
Fonte: International Journal of Epidemiology. Nome do evento: IEA World Congress of Epidemiology - WCE. Unidade: ICMC
Assuntos: DENGUE, COVID-19, ANÁLISE DE REGRESSÃO E DE CORRELAÇÃO
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ABNT
ROSTER, Kirstin e CONNAUGHTON, Colm e RODRIGUES, Francisco Aparecido. Estimating the causal effect of mobility on Dengue during the COVID-19 pandemic. International Journal of Epidemiology. Oxford: Oxford University Press. Disponível em: https://doi.org/10.1093/ije/dyab168.572. Acesso em: 08 out. 2025. , 2021
APA
Roster, K., Connaughton, C., & Rodrigues, F. A. (2021). Estimating the causal effect of mobility on Dengue during the COVID-19 pandemic. International Journal of Epidemiology. Oxford: Oxford University Press. doi:10.1093/ije/dyab168.572
NLM
Roster K, Connaughton C, Rodrigues FA. Estimating the causal effect of mobility on Dengue during the COVID-19 pandemic [Internet]. International Journal of Epidemiology. 2021 ; 50( Supplement_1): i200.[citado 2025 out. 08 ] Available from: https://doi.org/10.1093/ije/dyab168.572
Vancouver
Roster K, Connaughton C, Rodrigues FA. Estimating the causal effect of mobility on Dengue during the COVID-19 pandemic [Internet]. International Journal of Epidemiology. 2021 ; 50( Supplement_1): i200.[citado 2025 out. 08 ] Available from: https://doi.org/10.1093/ije/dyab168.572
Trabalho de evento
Discovering causal factors of drought in Ethiopia (2020)
Noorbakhsh, Mohammad ; Connaughton, Colm ; Rodrigues, Francisco Aparecido
Fonte: Proceedings. Nome do evento: International Conference on Climate Informatics. Unidade: ICMC
Assuntos: SECA, EL NIÑO, ANÁLISE DE REGRESSÃO E DE CORRELAÇÃO
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ABNT
NOORBAKHSH, Mohammad e CONNAUGHTON, Colm e RODRIGUES, Francisco Aparecido. Discovering causal factors of drought in Ethiopia. 2020, Anais.. New York: ACM, 2020. Disponível em: https://doi.org/10.1145/3429309.3429320. Acesso em: 08 out. 2025.
APA
Noorbakhsh, M., Connaughton, C., & Rodrigues, F. A. (2020). Discovering causal factors of drought in Ethiopia. In Proceedings. New York: ACM. doi:10.1145/3429309.3429320
NLM
Noorbakhsh M, Connaughton C, Rodrigues FA. Discovering causal factors of drought in Ethiopia [Internet]. Proceedings. 2020 ;[citado 2025 out. 08 ] Available from: https://doi.org/10.1145/3429309.3429320
Vancouver
Noorbakhsh M, Connaughton C, Rodrigues FA. Discovering causal factors of drought in Ethiopia [Internet]. Proceedings. 2020 ;[citado 2025 out. 08 ] Available from: https://doi.org/10.1145/3429309.3429320
Artigo de periodico
Disease and information spreading at different speeds in multiplex networks (2020)
Velasquez-Rojas, Fatima; Silva, Paulo Cesar Ventura da ; Connaughton, Colm ; Moreno, Yamir ; Rodrigues, Francisco Aparecido ; Vazquez, Federico
Fonte: Physical Review E. Unidades: ICMC, IFSC
Assuntos: CONTROLE DE DOENÇAS TRANSMISSÍVEIS, SURTOS DE DOENÇAS, COMPORTAMENTO, MATEMÁTICA APLICADA
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ABNT
VELASQUEZ-ROJAS, Fatima et al. Disease and information spreading at different speeds in multiplex networks. Physical Review E, v. 102, n. 2, p. 022312-1-022312-10, 2020Tradução . . Disponível em: https://doi.org/10.1103/PhysRevE.102.022312. Acesso em: 08 out. 2025.
APA
Velasquez-Rojas, F., Silva, P. C. V. da, Connaughton, C., Moreno, Y., Rodrigues, F. A., & Vazquez, F. (2020). Disease and information spreading at different speeds in multiplex networks. Physical Review E, 102( 2), 022312-1-022312-10. doi:10.1103/PhysRevE.102.022312
NLM
Velasquez-Rojas F, Silva PCV da, Connaughton C, Moreno Y, Rodrigues FA, Vazquez F. Disease and information spreading at different speeds in multiplex networks [Internet]. Physical Review E. 2020 ; 102( 2): 022312-1-022312-10.[citado 2025 out. 08 ] Available from: https://doi.org/10.1103/PhysRevE.102.022312
Vancouver
Velasquez-Rojas F, Silva PCV da, Connaughton C, Moreno Y, Rodrigues FA, Vazquez F. Disease and information spreading at different speeds in multiplex networks [Internet]. Physical Review E. 2020 ; 102( 2): 022312-1-022312-10.[citado 2025 out. 08 ] Available from: https://doi.org/10.1103/PhysRevE.102.022312
Artigo de periodico
Epidemic spreading with awareness and different timescales in multiplex networks (2019)
Silva, Paulo Cesar Ventura da ; Velasquez-Rojas, Fatima; Connaughton, Colm ; Vazquez, Federico; Moreno, Yamir ; Rodrigues, Francisco Aparecido
Fonte: Physical Review E. Unidades: ICMC, IFSC
Assuntos: CONTROLE DE DOENÇAS TRANSMISSÍVEIS, SURTOS DE DOENÇAS, COMPORTAMENTO, MATEMÁTICA APLICADA
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ABNT
SILVA, Paulo Cesar Ventura da et al. Epidemic spreading with awareness and different timescales in multiplex networks. Physical Review E, v. 100, n. 3, p. 032313-1-032313-11, 2019Tradução . . Disponível em: https://doi.org/10.1103/PhysRevE.100.032313. Acesso em: 08 out. 2025.
APA
Silva, P. C. V. da, Velasquez-Rojas, F., Connaughton, C., Vazquez, F., Moreno, Y., & Rodrigues, F. A. (2019). Epidemic spreading with awareness and different timescales in multiplex networks. Physical Review E, 100( 3), 032313-1-032313-11. doi:10.1103/PhysRevE.100.032313
NLM
Silva PCV da, Velasquez-Rojas F, Connaughton C, Vazquez F, Moreno Y, Rodrigues FA. Epidemic spreading with awareness and different timescales in multiplex networks [Internet]. Physical Review E. 2019 ; 100( 3): 032313-1-032313-11.[citado 2025 out. 08 ] Available from: https://doi.org/10.1103/PhysRevE.100.032313
Vancouver
Silva PCV da, Velasquez-Rojas F, Connaughton C, Vazquez F, Moreno Y, Rodrigues FA. Epidemic spreading with awareness and different timescales in multiplex networks [Internet]. Physical Review E. 2019 ; 100( 3): 032313-1-032313-11.[citado 2025 out. 08 ] Available from: https://doi.org/10.1103/PhysRevE.100.032313
Artigo de periodico
Unfolding the complexity of the global value chain: strength and entropy in the single-layer, multiplex, and multi-layer international trade networks (2018)
Alves, Luiz Gustavo de Andrade; Mangioni, Giuseppe; Rodrigues, Francisco Aparecido ; Panzarasa, Pietro; Moreno, Yamir
Fonte: Entropy. Unidade: ICMC
Assuntos: REDES COMPLEXAS, MÉTODOS TOPOLÓGICOS, COMÉRCIO INTERNACIONAL
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ABNT
ALVES, Luiz Gustavo de Andrade et al. Unfolding the complexity of the global value chain: strength and entropy in the single-layer, multiplex, and multi-layer international trade networks. Entropy, v. 20, n. 12, p. 1-14, 2018Tradução . . Disponível em: https://doi.org/10.3390/e20120909. Acesso em: 08 out. 2025.
APA
Alves, L. G. de A., Mangioni, G., Rodrigues, F. A., Panzarasa, P., & Moreno, Y. (2018). Unfolding the complexity of the global value chain: strength and entropy in the single-layer, multiplex, and multi-layer international trade networks. Entropy, 20( 12), 1-14. doi:10.3390/e20120909
NLM
Alves LG de A, Mangioni G, Rodrigues FA, Panzarasa P, Moreno Y. Unfolding the complexity of the global value chain: strength and entropy in the single-layer, multiplex, and multi-layer international trade networks [Internet]. Entropy. 2018 ; 20( 12): 1-14.[citado 2025 out. 08 ] Available from: https://doi.org/10.3390/e20120909
Vancouver
Alves LG de A, Mangioni G, Rodrigues FA, Panzarasa P, Moreno Y. Unfolding the complexity of the global value chain: strength and entropy in the single-layer, multiplex, and multi-layer international trade networks [Internet]. Entropy. 2018 ; 20( 12): 1-14.[citado 2025 out. 08 ] Available from: https://doi.org/10.3390/e20120909

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