Prediction Combining
Mostrando 1-12 de 57 artigos, teses e dissertações.
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1. Quantification of Carbon Dioxide (CO2), Methane (CH4), and Nitrous Oxide (N2O) Using Near Infrared Spectroscopy and Multivariate Calibration in High Humidity Levels
In this work we developed a promising analytical method combining Fourier transform near-infrared (FT-NIR) spectroscopic technique and first-order multivariate calibration using partial least-squares (PLS) model to simultaneously quantify the main greenhouse gases (GHG’s): methane (CH4), carbon dioxide (CO2), nitrous oxide (N2O) and water vapor (H2O). The
Journal of the Brazilian Chemical Society. Publicado em: 2022
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2. Estimation of genetic merit of diallel hybrids of sweet pepper by mixed models
RESUMO: A utilização de modelos mistos na avaliação de cruzamentos dialélicos é uma opção altamente oportuna para a fidedigna predição dos valores genéticos das progênies. Na cultura do pimentão, os híbridos são largamente explorados comercialmente, principalmente por suas características de importância econômica. O objetivo deste trabalho
Cienc. Rural. Publicado em: 29/07/2019
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3. New insights into genomic selection through population-based non-parametric prediction methods
ABSTRACT: Genome-wide selection (GWS) is based on a large number of markers widely distributed throughout the genome. Genome-wide selection provides for the estimation of the effect of each molecular marker on the phenotype, thereby allowing for the capture of all genes affecting the quantitative traits of interest. The main statistical tools applied to GWS
Sci. agric. (Piracicaba, Braz.). Publicado em: 2019-07
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4. Mutation Spectrum and Genotype–Phenotype Correlation in a Cohort of Argentine Patients with Ornithine Transcarbamylase Deficiency: A Single-Center Experience
Abstract X-linked ornithine transcarbamylase deficiency (OTCD) is the most common urea cycle disorder. Hemizygous males with complete deficiency manifest neonatal acute hyperammonemia, while those with partial deficiency have a late presentation. The symptomatology of heterozygotes depends on the inactivation pattern of X chromosome. Hyperammonemic episodes
J. inborn errors metab. screen.. Publicado em: 28/02/2019
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5. Candidate mutations used to aid the prediction of genetic merit for female reproductive traits in tropical beef cattle
ABSTRACT In this study, we aimed to provide a wet laboratory validation for a set of single nucleotide polymorphisms (SNP), which had been identified as candidate functional variants in silico. Genotyping for candidate SNP was performed in Brahman and Tropical Composite cattle. After quality control, 29 SNP were first investigated individually for their asso
R. Bras. Zootec.. Publicado em: 29/11/2018
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6. Validation of Four Prediction Scores for Cardiac Surgery-Associated Acute Kidney Injury in Chinese Patients
Abstract Objective: To assess the clinical value of four models for the prediction of cardiac surgery-associated acute kidney injury (CSA-AKI) and severe AKI which renal replacement therapy was needed (RRT-AKI) in Chinese patients. Methods: 1587 patients who underwent cardiac surgery in the department of cardiac surgery in the Zhongshan Hospital, Fudan Uni
Braz. J. Cardiovasc. Surg.. Publicado em: 2017-12
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7. A Hybrid Path Loss Prediction Model based on Artificial Neural Networks using Empirical Models for LTE And LTE-A at 800 MHz and 2600 MHz
Abstract This article presents the analysis of a hybrid, error correction-based, neural network model to predict the path loss for suburban areas at 800 MHz and 2600 MHz, obtained by combining empirical propagation models, ECC-33, Ericsson 9999, Okumura Hata, and 3GPP's TR 36.942, with a feedforward Artificial Neural Network (ANN). The performance of the hyb
J. Microw. Optoelectron. Electromagn. Appl.. Publicado em: 2017-09
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8. Combining ability of sugarcane genotypes based on the selection rates of single cross families
Abstract This study evaluated the genetic potential of parents used in sugarcane genetic breeding programs based on the performance of previously conducted single crosses. The average selection rate of each family, predicted using Best Linear Unbiased Prediction (BLUP) procedure, was used as a surrogate to the cross performance in the initial evaluation phas
Crop Breed. Appl. Biotechnol.. Publicado em: 2017-03
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9. The best of both worlds: Phylogenetic eigenvector regression and mapping
Eigenfunction analyses have been widely used to model patterns of autocorrelation in time, space and phylogeny. In a phylogenetic context, Diniz-Filho et al. (1998) proposed what they called Phylogenetic Eigenvector Regression (PVR), in which pairwise phylogenetic distances among species are submitted to a Principal Coordinate Analysis, and eigenvectors are
Genet. Mol. Biol.. Publicado em: 2015-09
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10. Growth Characteristics Modeling of Mixed Culture of Bifidobacterium bifidum and Lactobacillus acidophilus using Response Surface Methodology and Artificial Neural Network
Different culture conditions viz. additional carbon and nitrogen content, inoculum size and age, temperature and pH of the mixed culture of Bifidobacterium bifidum and Lactobacillus acidophilus were optimized using response surface methodology (RSM) and artificial neural network (ANN). Kinetic growth models were fitted for the cultivations using a Fractional
Braz. arch. biol. technol.. Publicado em: 2014-12
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11. External validation of a brazilian predictive nomogram for pathologic outcomes following radical prostatectomy in tertiary teaching institutions: the USP nomograms
Purposes(a) To externally validate the Crippa and colleagues’ nomograms combining PSA, percentage of positive biopsy cores (PPBC) and biopsy Gleason score to predict organ-confined disease (OCD) in a contemporary sample of patients treated at a tertiary teaching institution. (b) To adjust such variables, resulting in predictive nomograms for OCD and semina
Int. braz j urol.. Publicado em: 2014-04
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12. Growth characteristics modeling of Lactobacillus acidophilus using RSM and ANN
The culture conditions viz. additional carbon and nitrogen content, inoculum size, age, temperature and pH of Lactobacillus acidophilus were optimized using response surface methodology (RSM) and artificial neural network (ANN). Kinetic growth models were fitted to cultivations from a Box-Behnken Design (BBD) design experiments for different variables. This
Braz. arch. biol. technol.. Publicado em: 2014-02