Modelo de avaliação de maturidade em gerenciamento de projetos

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Ecologia da paisagem para avaliação da idoneidade de redes ecológicas, como subsídio para o planejamento territorial

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Mecanismos termorreguladores de cabras da raça Saanen -

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Associação genômica ampla para características reprodutivas em bovinos da raça Nelore

Pós-graduação em Medicina Veterinária - FCAV

Efeito das características do pelame e da taxa de sudação sobre parâmetros reprodutivos em vacas da raça Braford

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Amostragem de sólidos em espectrometria de absorção atômica de fonte contínua com alta resolução: análise de plantas medicinais

Pós-graduação em Química - IQ

Growth curves of Nile tilapia (Oreochromis niloticus) strains cultivated at different temperatures

Growth of Red, GIFT and Supreme Nile tilapia strains were evaluated. Fish were cultivated in indoor recirculation systems in 0.5 m³ tanks with controlled temperatures of 22, 28 and 30°C. Random samples of 20 fish from each strain (10 fish tank-1) were weighed at day 7, 30, 60, 90 and 120. Exponential model (y=AeKx) and Gompertz model (y = Aexp(-Be-Kx)) were fitted and the estimates parameters were obtained by Weighted Least Squares. At 22°C, Red, GIFT and Supreme strain presented similar growth and fit of exponential model. GIFT and Supreme strain presented higher growth rate at 30°C of cultivation when compared to Red strain. Temperature influences weight and age at the inflection point. The temperature of cultivation influences the growth description of Red, GIFT and Supreme tilapia strains. It changes the age and weight at inflection point and the qualities of growth model fits, changing the variation of the batch.

In vivo embryo production in cows superovulated 1 or 2 days after ovum pick-up

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

A Spatial and Temporal Prediction Model of Corn Grain Yield as a Function of Soil Attributes

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

A Multivariate Calibration Procedure for UV/VIS Spectrometric Monitoring of BHK-21 Cell Metabolism and Growth

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Localização automática de pontos de controle em imagens aéreas baseada em cenas terrestres verticais

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Interaction of biologically-relevant peptides with membrane model systems

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Estimação de parâmetros de linhas de transmissão utilizando técnicas de decomposição modal: Aplicação em linhas com plano de simetria vertical

Pós-graduação em Engenharia Elétrica - FEIS

Artificial neural network associated to UV/Vis spectroscopy for monitoring bioreactions in biopharmaceutical processes

Currently, mammalian cells are the most utilized hosts for biopharmaceutical production. The culture media for these cell lines include commonly in their composition a pH indicator. Spectroscopic techniques are used for biopharmaceutical process monitoring, among them, UV–Vis spectroscopy has found scarce applications. This work aimed to define artificial neural networks architecture and fit its parameters to predict some nutrients and metabolites, as well as viable cell concentration based on UV–Vis spectral data of mammalian cell bioprocess using phenol red in culture medium. The BHK-21 cell line was used as a mammalian cell model. Off-line spectra of supernatant samples taken from batches performed at different dissolved oxygen concentrations in two bioreactor configurations and with two pH control strategies were used to define two artificial neural networks. According to absolute errors, glutamine (0.13 ± 0.14 mM), glutamate (0.02 ± 0.02 mM), glucose (1.11 ± 1.70 mM), lactate (0.84 ± 0.68 mM) and viable cell concentrations (1.89 105 ± 1.90 105 cell/mL) were suitably predicted. The prediction error averages for monitored variables were lower than those previously reported using different spectroscopic techniques in combination with partial least squares or artificial neural network. The present work allows for UV–VIS sensor development, and decreases cost related to nutrients and metabolite quantifications.

Locating control points in aerial images with a multi-scale approach based on terrestrial image patches

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)