Search Results for author: Gabriel R. Palma

Found 6 papers, 1 papers with code

Understanding Social Immunity in Ants: A Markovian Approach to Collective Cleaning Strategies

no code implementations8 Feb 2024 Isabella Bueno, Gabriel R. Palma, Idemauro A. R. Lara, Rafael A. Moral, Italo Delalibera Jr, Wesley A. C. Godoy

We investigate how worker interactions and previous behaviors influence the evolution of social immunity strategies in response to the presence of pathogens and vulnerable colony members.

Decision Making

Forecasting insect abundance using time series embedding and machine learning

no code implementations22 Dec 2023 Gabriel R. Palma, Rodrigo F. Mello, Wesley A. C. Godoy, Eduardo Engel, Douglas Lau, Charles Markham, Rafael A. Moral

We pre-processed the data using our newly proposed approach and more straightforward approaches commonly used to train machine learning algorithms in time series problems.

Time Series

Profiling Television Watching Behaviour Using Bayesian Hierarchical Joint Models for Time-to-Event and Count Data

1 code implementation6 Sep 2022 Rafael A. Moral, Zhi Chen, Shuai Zhang, Sally McClean, Gabriel R. Palma, Brahim Allan, Ian Kegel

The model drastically reduces the dimensionality of the data from thousands of observations per customer to 11 customer-level parameter estimates and random effects.

Descriptive

Bacteriophage effect on parasitism resistance

no code implementations6 May 2022 Gabriel R. Palma, Renato M. Coutinho, Wesley A. C. Godoy, Fernando L. Cônsoli, Roberto A. Kraenkel

Many studies have shown that the protection of the host $\it{Acyrthosiphon~pisum}$ (Hemiptera, Aphididae) against the parasitoid $\it{Aphidius~ervi}$ (Hymenoptera, Braconidae) is conferred by the interaction between the secondary endosymbiont $\it{Hamiltonella~defensa}$ and the bacteriophage $\it{APSE}$ ($\it{Acyrthosiphon~pisum}$ secondary endosymbiont).

Open-Ended Question Answering

New confidence interval methods for Shannon index

no code implementations21 Apr 2022 Gabriel R. Palma, Silvio S. Zocchi, Wesley A. C. Godoy, Jorge A. Wiendl

Then, we generated 1000 samples, built 95% confidence intervals, and calculated the percentage of times they included the community diversity index (coverage percentage) for each community structure.

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