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3,111 results on '"Souza, Daniel"'

1. Investigation of rotational augmentation mechanisms on wind turbine blade sections based on Quasi-3D simulations

Author

Rodrigues, Pedro, Gennaro, Elmer, and Souza, Daniel

Subjects
Physics - Fluid Dynamics
Abstract

Rotation has been recognized for its ability to decrease the extent of separate flow regions on the inner sections ofhorizontal-axis wind turbine blades. This alteration is often linked to centrifugal pumping. Nevertheless, studies focused on insect flight conditions revealed a significant contribution of the Coriolis acceleration to the balance of vorticity within the leading-edge vortex (LEV). Despite this insight, it remains unexplored whether this phenomenon contributes to the observed rotational augmentation in wind turbines. Our study employed quasi-3D simulations to delve into the impact of Coriolis acceleration on the balance of span-wise vorticity within the region of separate flow along the upper surface of wind turbine blade sections. Our results allowed the identification of two different mechanisms of rotational augmentation, one associated to the height reduction of the region of separate flow and the other associated to the stabilization of the LEV. The former occurred when a trailing-edge separation was observed and the later when the flow featured a leading-edge separation. Within the range of conditions considered, the Coriolis acceleration neutralized up to about 40% of the span-wise vorticity flowing in from the boundary layer to feed the LEV.

Published
2024

2. How Small is Big Enough? Open Labeled Datasets and the Development of Deep Learning

Author

Souza, Daniel, Geuna, Aldo, and Rodríguez, Jeff

Subjects
Economics - General Economics, Computer Science - Computers and Society
Abstract

We investigate the emergence of Deep Learning as a technoscientific field, emphasizing the role of open labeled datasets. Through qualitative and quantitative analyses, we evaluate the role of datasets like CIFAR-10 in advancing computer vision and object recognition, which are central to the Deep Learning revolution. Our findings highlight CIFAR-10's crucial role and enduring influence on the field, as well as its importance in teaching ML techniques. Results also indicate that dataset characteristics such as size, number of instances, and number of categories, were key factors. Econometric analysis confirms that CIFAR-10, a small-but-sufficiently-large open dataset, played a significant and lasting role in technological advancements and had a major function in the development of the early scientific literature as shown by citation metrics.

Published
2024

7. Confinement and semi confinement of lambs in an integrated production system: impacts on production performance, infection by gastrointestinal nematodes, and selected blood analytes/Confinamento e semiconfinamento de cordeiras em um sistema integrado de produção: impactos na produção, infecção por nematódeos gastrointestinais e em variaveis sanguíneas

Author

Schmidt, Elizabeth Moreira Dos Santos, Fachiolli, Daniele Floriano, Soutello, Ricardo Velludo Gomes De, Castilhos, Andre Michel De, Amarante, Alessandra Francisco Talamini Do, Souza, Daniel Martins De, Barros, Juliana Da Silva, and Costa, Ciniro

Published
2024

12. Thin and Deep Gaussian Processes

Author

de Souza, Daniel Augusto, Nikitin, Alexander, John, ST, Ross, Magnus, Álvarez, Mauricio A., Deisenroth, Marc Peter, Gomes, João P. P., Mesquita, Diego, and Mattos, César Lincoln C.

Subjects
Statistics - Machine Learning, Computer Science - Machine Learning
Abstract

Gaussian processes (GPs) can provide a principled approach to uncertainty quantification with easy-to-interpret kernel hyperparameters, such as the lengthscale, which controls the correlation distance of function values. However, selecting an appropriate kernel can be challenging. Deep GPs avoid manual kernel engineering by successively parameterizing kernels with GP layers, allowing them to learn low-dimensional embeddings of the inputs that explain the output data. Following the architecture of deep neural networks, the most common deep GPs warp the input space layer-by-layer but lose all the interpretability of shallow GPs. An alternative construction is to successively parameterize the lengthscale of a kernel, improving the interpretability but ultimately giving away the notion of learning lower-dimensional embeddings. Unfortunately, both methods are susceptible to particular pathologies which may hinder fitting and limit their interpretability. This work proposes a novel synthesis of both previous approaches: Thin and Deep GP (TDGP). Each TDGP layer defines locally linear transformations of the original input data maintaining the concept of latent embeddings while also retaining the interpretation of lengthscales of a kernel. Moreover, unlike the prior solutions, TDGP induces non-pathological manifolds that admit learning lower-dimensional representations. We show with theoretical and experimental results that i) TDGP is, unlike previous models, tailored to specifically discover lower-dimensional manifolds in the input data, ii) TDGP behaves well when increasing the number of layers, and iii) TDGP performs well in standard benchmark datasets., Comment: Accepted at the Conference on Neural Information Processing Systems (NeurIPS) 2023

Published
2023

13. Orbital Lipschitzian mappings and semigroup actions on metric spaces

Author

Espínola, Rafael, Japón, Maria, and Souza, Daniel

Subjects
Mathematics - Functional Analysis, 47H09, 47H10, 47H20, 54E40
Abstract

In this paper we study some results on common fixed points of families of mappings on metric spaces by imposing orbit Lipschitzian conditions on them. These orbit Lipschitzian conditions are weaker than asking the mappings to be Lipschitzian in the traditional way. We provide new results under the two classic approaches in the theory of fixed points for uniformly Lipschitzian mappings: the one under the normal structure property of the space (which can be regarded as the Cassini-Maluta's approach) and the one after the Lifschitz characteristic of the metric space (Lifschitz's approach). Although we focus on the case of semigroup of mappings, our results are new even when a mapping is considered by itself.

Published
2023

15. Statine-based peptidomimetic compounds as inhibitors for SARS-CoV-2 main protease (SARS-CoV‑2 Mpro)

Author

Azevedo, Pedro Henrique R. de A., Camargo, Priscila G., Constant, Larissa E. C., Costa, Stephany da S., Silva, Celimar Sinézia, Rosa, Alice S., Souza, Daniel D. C., Tucci, Amanda R., Ferreira, Vivian N. S., Oliveira, Thamara Kelcya F., Borba, Nathalia R. R., Rodrigues, Carlos R., Albuquerque, Magaly G., Dias, Luiza R. S., Garrett, Rafael, Miranda, Milene D., Allonso, Diego, Lima, Camilo Henrique da S., and Muri, Estela Maris F.

Published
2024
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16. Diving into the proteomic atlas of SARS-CoV-2 infected cells

Author

Carregari, Victor C., Reis-de-Oliveira, Guilherme, Crunfli, Fernanda, Smith, Bradley J., de Souza, Gabriela Fabiano, Muraro, Stéfanie Primon, Saia-Cereda, Veronica M., Vendramini, Pedro H., Baldasso, Paulo A., Silva-Costa, Lícia C., Zuccoli, Giuliana S., Brandão-Teles, Caroline, Antunes, André, Valença, Aline F., Davanzo, Gustavo G., Virgillio-da-Silva, João Victor, dos Reis Araújo, Thiago, Guimarães, Raphael Campos, Chaim, Felipe David Mendonça, Chaim, Elinton Adami, Kawagosi Onodera, Carolina Mie, Ludwig, Raissa Guimarães, Saccon, Tatiana Dandolini, Damásio, André R. L., Leiria, Luiz Osório S., Vinolo, Marco Aurélio R., Farias, Alessandro S., Moraes-Vieira, Pedro M., Mori, Marcelo A., Módena, José Luiz P., and Martins-de-Souza, Daniel

Published
2024
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19. Actually Sparse Variational Gaussian Processes

Author

Cunningham, Harry Jake, de Souza, Daniel Augusto, Takao, So, van der Wilk, Mark, and Deisenroth, Marc Peter

Subjects
Statistics - Machine Learning, Computer Science - Machine Learning
Abstract

Gaussian processes (GPs) are typically criticised for their unfavourable scaling in both computational and memory requirements. For large datasets, sparse GPs reduce these demands by conditioning on a small set of inducing variables designed to summarise the data. In practice however, for large datasets requiring many inducing variables, such as low-lengthscale spatial data, even sparse GPs can become computationally expensive, limited by the number of inducing variables one can use. In this work, we propose a new class of inter-domain variational GP, constructed by projecting a GP onto a set of compactly supported B-spline basis functions. The key benefit of our approach is that the compact support of the B-spline basis functions admits the use of sparse linear algebra to significantly speed up matrix operations and drastically reduce the memory footprint. This allows us to very efficiently model fast-varying spatial phenomena with tens of thousands of inducing variables, where previous approaches failed., Comment: 14 pages, 5 figures, published in AISTATS 2023

Published
2023

20. Combined Physical Training Strategies Improve Physical Fitness, Behavior, and Social Skills of Autistic Children

Author

Haghighi, Amir Hossein, Broughani, Shokofeh, Askari, Roya, Shahrabadi, Hadi, Souza, Daniel, and Gentil, Paulo

Abstract

The present study aimed to investigate the effects of combined physical training (CPT) on social skills and physical fitness (PF) in children with ASD. Sixteen children with autism (age 6-10 years) were randomly assigned into two groups: CPT and control. The CPT group participated in a program involving ball game, rhythmic movements, and resistance training for eight weeks (three sessions per week). PF and behavior profile were assessed before and after training. CPT program had a significant effect on indicators of social skills such as stereotypic behavior and communication, as well as PF such as handgrip strength, upper and lower body power, flexibility, balance, and agility (P < 0.05). CPT in autistic children can improve indicators of social skills and PF.

Published
2023
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22. Fixed points and common fixed points for orbit-nonexpansive mappings in metric spaces

Author

Espínola, Rafael, Japón, Maria, and Souza, Daniel

Subjects
Mathematics - Functional Analysis, 47H09, 47H10, 47H20, 54E4
Abstract

In this paper we introduce an interlacing condition on the elements of a family of operators that allows us to gather together a number of results on fixed points and common fixed points for single and families of mappings defined on metric spaces. The innovative concept studied here deals with nonexpansivity conditions with respect to orbits and under assumptions that only depend on the features of the closed balls of the metric space.

Published
2022

23. Vaccination coverage and delay in vaccination of infants born in 2017 and 2018 in municipalities in the Southern region of Brazil: National Vaccination Coverage Survey 2020

Author

Karin Regina Luhm, Antonio Fernando Boing, Sotero Serrate Mengue, Neiva de Souza Daniel, Tainá Ribas Mélo, Raquel Jaqueline Farion, Ana Paula França, José Cássio de Moraes, Adriana Ilha da Silva, Alberto Novaes Ramos Jr., Andrea de Nazaré Marvão Oliveira, Carla Magda Allan Santos Domingues, Consuelo Silva de Oliveira, Ethel Leonor Noia Maciel, Ione Aquemi Guibu, Isabelle Ribeiro Barbosa Mirabal, Jaqueline Caracas Barbosa, Jaqueline Costa Lima, Karlla Antonieta Amorim Caetano, Luisa Helena de Oliveira Lima, Maria Bernadete de Cerqueira Antunes, Maria da Gloria Teixeira, Maria Denise de Castro Teixeira, Maria Fernanda de Sousa Oliveira Borges, Rejane Christine de Sousa Queiroz, Ricardo Queiroz Gurgel, Rita Barradas Barata, Roberta Nogueira Calandrini de Azevedo, Sandra Maria do Valle Leone de Oliveira, Sheila Araújo Teles, Silvana Granado Nogueira da Gama, Taynãna César Simões, Valdir Nascimento, and Wildo Navegantes de Araújo

Subjects
Vaccination Coverage, Vaccines, Health Surveys, Vaccination Hesitancy, Vaccination Delay, Medicine, Public aspects of medicine, RA1-1270
Abstract

ABSTRACT Objective To evaluate vaccination coverage and delay in vaccine dose administration in infants in six municipalities in the Southern region of Brazil. Methodology National Vaccination Coverage Survey 2020, with infants born alive in 2017 and 2018, carried out from September 2020 to March 2022. Coverage of doses administered, doses administered on time and delay in dose administration were evaluated. Results For 4681 infants analyzed, coverage for vaccines recommended up to 24 months was 68.0% (95%CI 63.9;71.8%) for doses administered and 3.9% (95%CI 2.7%;5.7%) for doses administered on time. Delay time for the majority of late vaccinations was ≤ 3 months. For some boosters, 25% of vaccine administration was delayed by ≥ 6 months. Conclusion In addition to tracking vaccine defaulters, strategies are needed to encourage compliance with the vaccination schedule at the recommended ages.

Published
2024
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24. Neurobiology of Schizophrenia

Author

Schmitt, Andrea, Popovic, David, Raabe, Florian, Papiol, Sergi, Martins-de-Souza, Daniel, Falkai, Peter, Schulze, Thomas G., Section editor, Laje, Gonzalo, Section editor, Tasman, Allan, editor, Riba, Michelle B., editor, Alarcón, Renato D., editor, Alfonso, César A., editor, Kanba, Shigenobu, editor, Lecic-Tosevski, Dusica, editor, Ndetei, David M., editor, Ng, Chee H., editor, and Schulze, Thomas G., editor

Published
2024
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26. Immunization with recombinant LiHyp1 protein plus adjuvant is protective against tegumentary leishmaniasis

Author

Jesus, Marcelo M., Lage, Daniela P., Vale, Danniele L., Freitas, Camila S., Pimenta, Breno L., Moreira, Gabriel J.L., Ramos, Fernanda F., Pereira, Isabela A.G., Bandeira, Raquel S., Ludolf, Fernanda, Tavares, Grasiele S.V., Galdino, Alexsandro S., Duarte, Mariana C., Menezes-Souza, Daniel, Chávez-Fumagalli, Miguel A., Teixeira, Antônio L., Gonçalves, Denise U., Roatt, Bruno M., Christodoulides, Myron, Martins, Vívian T., and Coelho, Eduardo A.F.

Published
2023
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28. Stability of subnanometer MoS wires under realistic environment

Author

de Deus, Dominike A. P., Souza, Daniel F., da Rosa, Andreia L., Pontes, Renato B., and Frauenheim, Th.

Subjects
Condensed Matter - Materials Science
Abstract

We carried out first-principles density functional theory calculations of hydrogen and oxygen adsorption and diffusion on subnanometer MoS nanowires. The nanowires are robust against adsorption of hydrogen. On the other hand, interaction with oxygen shows that the nanowires can oxidize with a small barrier. Our results open the path for understanding the behavior of MoS nanowires under realistic environment.

Published
2022

29. Standing Forest Coin (SFC)

Author

Borges, Marcelo de A., Filho, Guido L. de S., da Silva, Cicero Inacio, Barros, Anderson M. P., Britto, Raul V. B. J., Junior, Nivaldo M. de C., and de Souza, Daniel F. L.

Subjects
Quantitative Finance - General Finance, Computer Science - Cryptography and Security, Computer Science - Computers and Society, J.7
Abstract

This article describes a proposal to create a digital currency that allows the decentralized collection of resources directed to initiatives and activities that aim to protect the Brazilian Amazon ecosystem by using blockchain and digital contracts. In addition to the digital currency, the goal is to design a smart contract based in oracles to ensure credibility and security for investors and donors of financial resources invested in projects within the Standing Forest Coin (SFC - standingforest.org)., Comment: in Portuguese

Published
2022
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31. Fatty acids and volatile compound of cooked green licuri (Syagrus coronata) and naturally ripe licuri almonds from native flora, popularly consumed in Brazil

Author

de Menezes, Anely Vieira, de Souza, Daniel Alves, de Lima, Daniele Pinto, Neta, Maria Terezinha Santos Leite, Almeida-Souza, Thiago Henrique, dos Santos Rodrigues, Rafaela Neto, Sandes, Rafael Donizete Dutra, Mishima, Marcella Duarte Villas, Narain, Narendra, de Almeida, André Quintão, Martino, Hercia Stampini Duarte, and de Carvalho, Izabela Maria Montezano

Published
2024
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32. Parallel MCMC Without Embarrassing Failures

Author

de Souza, Daniel Augusto, Mesquita, Diego, Kaski, Samuel, and Acerbi, Luigi

Subjects
Statistics - Machine Learning, Computer Science - Machine Learning, Statistics - Methodology
Abstract

Embarrassingly parallel Markov Chain Monte Carlo (MCMC) exploits parallel computing to scale Bayesian inference to large datasets by using a two-step approach. First, MCMC is run in parallel on (sub)posteriors defined on data partitions. Then, a server combines local results. While efficient, this framework is very sensitive to the quality of subposterior sampling. Common sampling problems such as missing modes or misrepresentation of low-density regions are amplified -- instead of being corrected -- in the combination phase, leading to catastrophic failures. In this work, we propose a novel combination strategy to mitigate this issue. Our strategy, Parallel Active Inference (PAI), leverages Gaussian Process (GP) surrogate modeling and active learning. After fitting GPs to subposteriors, PAI (i) shares information between GP surrogates to cover missing modes; and (ii) uses active sampling to individually refine subposterior approximations. We validate PAI in challenging benchmarks, including heavy-tailed and multi-modal posteriors and a real-world application to computational neuroscience. Empirical results show that PAI succeeds where previous methods catastrophically fail, with a small communication overhead., Comment: To appear in the 25th International Conference on Artificial Intelligence and Statistics (AISTATS 2022). For associated code, see https://github.com/spectraldani/pai/

Published
2022

34. Ensemble and Mixed Learning Techniques for Credit Card Fraud Detection

Author

de Souza, Daniel H. M. and Bordin Jr, Claudio J.

Subjects
Computer Science - Machine Learning
Abstract

Spurious credit card transactions are a significant source of financial losses and urge the development of accurate fraud detection algorithms. In this paper, we use machine learning strategies for such an aim. First, we apply a mixed learning technique that uses K-means preprocessing before trained classification to the problem at hand. Next, we introduce an adapted detector ensemble technique that uses OR-logic algorithm aggregation to enhance the detection rate. Then, both strategies are deployed in tandem in numerical simulations using real-world transactions data. We observed from simulation results that the proposed methods diminished computational cost and enhanced performance concerning state-of-the-art techniques.

Published
2021

35. CD4+ and CD8+ T-cell multi-epitope chimeric protein associated with an MPLA adjuvant induce protective efficacy and long-term immunological memory for the immunoprophylaxis of American Tegumentary Leishmaniasis

Author

Moura, Dênia Monteiro de, Carvalho, Ana Maria Ravena Severino, Brito, Rory Cristiane Fortes de, Roatt, Bruno Mendes, Lage, Daniela Pagliara, Martins, Vivian Tamietti, Cruz, Luiza dos Reis, Medeiros, Fernanda Alvarenga Cardoso, Batista, Sarah Dutra, Pinheiro, Guilherme Rafael Gomide, da Costa Rocha, Manoel Otávio, Coelho, Eduardo Antonio Ferraz, Duarte, Mariana Costa, Mendes, Tiago Antônio de Oliveira, and Menezes-Souza, Daniel

Published
2024
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36. Changes in neuroinflammatory biomarkers correlate with disease severity and neuroimaging alterations in patients with COVID-19 neurological complications

Author

Barros-Aragão, Fernanda G.Q., Pinto, Talita P., Carregari, Victor C., Rezende, Nathane B.S., Pinheiro, Thaís L., Reis-de-Oliveira, Guilherme, Cabral-Castro, Mauro J., Queiroz, Daniel C., Fonseca, Paula L.C., Gonçalves, Alessandro L., de Freitas, Gabriel R., Sudo, Felipe K., Mattos, Paulo, Bozza, Fernando A., Rodrigues, Erika C., Aguiar, Renato S., Rodrigues, Rosana S., Brandão, Carlos O., Souza, Andrea S., Martins-de-Souza, Daniel, De Felice, Fernanda G., and Tovar-Moll, Fernanda

Published
2024
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39. Development of a topical treatment for tegumentary leishmaniasis using 8-hydroxyquinoline

Author

Rezende Ribeiro, Naianda, Magno Oliveira Santos, Lucas, Silva Costa, Scarleth, Kei Myasaki, Carolina, Pagliara Lage, Daniela, Tamietti Martins, Vivian, Cristiane Fortes De Brito, Rory, Chaves Freire, Larissa, Maria Ravena Severino Carvalho, Ana, Victor Serafim Brigido, Bryan, José Alves, Ricardo, Antonio Ferraz Coelho, Eduardo, Mendes Roatt, Bruno, Menezes-Souza, Daniel, and Costa Duarte, Mariana

Published
2024
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40. Genetic reversal of the globin switch concurrently modulates both fetal and sickle hemoglobin and reduces red cell sickling

Author

De Souza, Daniel C., Hebert, Nicolas, Esrick, Erica B., Ciuculescu, M. Felicia, Archer, Natasha M., Armant, Myriam, Audureau, Étienne, Brendel, Christian, Di Caprio, Giuseppe, Galactéros, Frédéric, Liu, Donghui, McCabe, Amanda, Morris, Emily, Schonbrun, Ethan, Williams, Dillon, Wood, David K., Williams, David A., Bartolucci, Pablo, and Higgins, John M.

Published
2023
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43. Pathophysiology of chikungunya virus infection associated with fatal outcomes

Author

de Souza, William M., Fumagalli, Marcilio J., de Lima, Shirlene T.S., Parise, Pierina L., Carvalho, Deyse C.M., Hernandez, Cristian, de Jesus, Ronaldo, Delafiori, Jeany, Candido, Darlan S., Carregari, Victor C., Muraro, Stefanie P., Souza, Gabriela F., Simões Mello, Leda M., Claro, Ingra M., Díaz, Yamilka, Kato, Rodrigo B., Trentin, Lucas N., Costa, Clauber H.S., Maximo, Ana Carolina B.M., Cavalcante, Karene F., Fiuza, Tayna S., Viana, Vânia A.F., Melo, Maria Elisabeth L., Ferraz, Clarissa P.M., Silva, Débora B., Duarte, Larissa M.F., Barbosa, Priscilla P., Amorim, Mariene R., Judice, Carla C., Toledo-Teixeira, Daniel A., Ramundo, Mariana S., Aguilar, Patricia V., Araújo, Emerson L.L., Costa, Fabio T.M., Cerqueira-Silva, Thiago, Khouri, Ricardo, Boaventura, Viviane S., Figueiredo, Luiz Tadeu M., Fang, Rong, Moreno, Brechla, López-Vergès, Sandra, Mello, Liana Perdigão, Skaf, Munir S., Catharino, Rodrigo R., Granja, Fabiana, Martins-de-Souza, Daniel, Plante, Jessica A., Plante, Kenneth S., Sabino, Ester C., Diamond, Michael S., Eugenin, Eliseo, Proença-Módena, José Luiz, Faria, Nuno R., and Weaver, Scott C.

Published
2024
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