AIMC Topic: Brazil

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Using artificial neural networks to select upright cowpea (Vigna unguiculata) genotypes with high productivity and phenotypic stability.

Genetics and molecular research : GMR
Cowpea (Vigna unguiculata) is grown in three Brazilian regions: the Midwest, North, and Northeast, and is consumed by people on low incomes. It is important to investigate the genotype x environment (GE) interaction to provide accurate recommendation...

Modeling the reflection of Photosynthetically active radiation in a monodominant floodable forest in the Pantanal of Mato Grosso State using multivariate statistics and neural networks.

Anais da Academia Brasileira de Ciencias
The study of radiation entrance and exit dynamics and energy consumption in a system is important for understanding the environmental processes that rule the biosphere-atmosphere interactions of all ecosystems. This study provides an analysis of the ...

Feature Extraction and Machine Learning for the Classification of Brazilian Savannah Pollen Grains.

PloS one
The classification of pollen species and types is an important task in many areas like forensic palynology, archaeological palynology and melissopalynology. This paper presents the first annotated image dataset for the Brazilian Savannah pollen types...

Artificial Intelligence Procedures for Tree Taper Estimation within a Complex Vegetation Mosaic in Brazil.

PloS one
Tree stem form in native tropical forests is very irregular, posing a challenge to establishing taper equations that can accurately predict the diameter at any height along the stem and subsequently merchantable volume. Artificial intelligence approa...

Development of two artificial neural network models to support the diagnosis of pulmonary tuberculosis in hospitalized patients in Rio de Janeiro, Brazil.

Medical & biological engineering & computing
Pulmonary tuberculosis (PTB) remains a worldwide public health problem. Diagnostic algorithms to identify the best combination of diagnostic tests for PTB in each setting are needed for resource optimization. We developed one artificial neural networ...

Development of a quantitative PCR for the detection of Rangelia vitalii.

Veterinary parasitology
The aim of this study was to develop and validate a SYBR Green qPCR assay to detect and quantify a fragment of the 18S rRNA gene of Rangelia vitalii in canine blood. Repeatability of the qPCR was determined by the intra- and inter-assay variations. T...

Family income per capita, age, and smoking status are predictors of low fiber intake in residents of São Paulo, Brazil.

Nutrition research (New York, N.Y.)
We hypothesized that dietary total fiber intake may be less than recommendations and that the intake of total, soluble, and insoluble fiber may be associated with demographic, lifestyle, and socioeconomic factors. Data were drawn from the Health Surv...

Indices of dietary fat quality during midpregnancy is associated with gestational diabetes.

Nutrition (Burbank, Los Angeles County, Calif.)
OBJECTIVE: To investigate the relationship between gestational diabetes mellitus (GDM) and the usual intake of fatty acids and indices of dietary fat quality [the atherogenicity (AI) and thrombogenicity indices (TI), and the ratios of hypo-and hyperc...

Discrimination of Brazilian propolis according to the seasoning using chemometrics and machine learning based on UV-Vis scanning data.

Journal of integrative bioinformatics
Propolis is a chemically complex biomass produced by honeybees (Apis mellifera) from plant resins added of salivary enzymes, beeswax, and pollen. The biological activities described for propolis were also identified for donor plant's resin, but a big...

Predictive modeling based on machine learning for mapping risk areas of human sporotrichosis in southeastern Brazil.

Research in veterinary science
Sporotrichosis, a zoonotic mycosis with a growing public health impact, requires innovative methods to map risk areas. This study applied machine learning techniques, Artificial Neural Networks (ANN), and Decision Trees (DT) to integrate sociodemogra...