Estimation of variance components and prediction of breeding values in rubber tree breeding using the REML/BLUP procedure

The present paper deals with estimation of variance components, prediction of breeding values and selection in a population of rubber tree [Hevea brasiliensis (Willd. ex Adr. de Juss.) Müell.-Arg.] from Rio Branco, State of Acre, Brazil. The REML/BLUP (restricted maximum likelihood/best linear unbiased prediction) procedure was applied. For this purpose, 37 rubber tree families were obtained and assessed in a randomized complete block design, with three unbalanced replications. The field trial was carried out at the Experimental Station of UNESP, located in Selvíria, State of Mato Grosso do Sul, Brazil. The quantitative traits evaluated were: girth (G), bark thickness (BT), number of latex vessel rings (NR), and plant height (PH). Given the unbalanced condition of the progeny test, the REML/BLUP procedure was used for estimation. The narrow-sense individual heritability estimates were 0.43 for G, 0.18 for BT, 0.01 for NR, and 0.51 for PH. Two selection strategies were adopted: one short-term (ST - selection intensity of 8.85%) and the other long-term (LT - selection intensity of 26.56%). For G, the estimated genetic gains in relation to the population average were 26.80% and 17.94%, respectively, according to the ST and LT strategies. The effective population sizes were 22.35 and 46.03, respectively. The LT and ST strategies maintained 45.80% and 28.24%, respectively, of the original genetic diversity represented in the progeny test. So, it can be inferred that this population has potential for both breeding and ex situ genetic conservation as a supplier of genetic material for advanced rubber tree breeding programs. Copyright by the Brazilian Society of Genetics.

Modeling approach based on experimental results for prediction of measurement errors in energy meters

This paper presents a general modeling approach to investigate and to predict measurement errors in active energy meters both induction and electronic types. The measurement error modeling is based on Generalized Additive Model (GAM), Ridge Regression method and experimental results of meter provided by a measurement system. The measurement system provides a database of 26 pairs of test waveforms captured in a real electrical distribution system, with different load characteristics (industrial, commercial, agricultural, and residential), covering different harmonic distortions, and balanced and unbalanced voltage conditions. In order to illustrate the proposed approach, the measurement error models are discussed and several results, which are derived from experimental tests, are presented in the form of three-dimensional graphs, and generalized as error equations. © 2009 IEEE.

Anfis applied to the prediction of surface roughness in grinding of advanced ceramics

This paper introduces a methodology for predicting the surface roughness of advanced ceramics using Adaptive Neuro-Fuzzy Inference System (ANFIS). To this end, a grinding machine was used, equipped with an acoustic emission sensor and a power transducer connected to the electric motor rotating the diamond grinding wheel. The alumina workpieces used in this work were pressed and sintered into rectangular bars. Acoustic emission and cutting power signals were collected during the tests and digitally processed to calculate the mean, standard deviation, and two other statistical data. These statistics, as well the root mean square of the acoustic emission and cutting power signals were used as input data for ANFIS. The output values of surface roughness (measured during the tests) were implemented for training and validation of the model. The results indicated that an ANFIS network is an excellent tool when applied to predict the surface roughness of ceramic workpieces in the grinding process.

On the influence of the mode-shapes of a marine propulsion shafting system on the prediction of torsional stresses

Torsional vibration predictions and measurements of a marine propulsion system, which has both damping and a highly flexible coupling, are presented in this paper. Using the conventional approach to stress prediction in the shafting system, the numerical predictions and the experimental torsional vibration stress curves in some parts of the shafting system are found to be quite different. The free torsional vibration characteristics and forced torsional vibration response of the system are analyzed in detail to investigate this phenomenon. It is found that the second to fourth natural modes of the shafting system have significant local deformation. This results in large torsional resonant responses in different sections of the system corresponding to different engine speeds. The results show that when there is significant local deformation in the shafting system for different modes, then multi-point measurements should be made, rather than the conventional method of using a single measurement at the free end of the shaft, to obtain the full torsional vibration characteristics of the shafting system.

Mild cognitive impairment (part 2): Biological markers for diagnosis and prediction of dementia in Alzheimer's disease

To present a critical review of publications reporting on the rationale and clinical implications of the use of biomarkers for the early diagnosis of Alzheimer's disease (AD). Methods: We conducted a systematic search of the PubMed and Web of Science electronic databases, limited to articles published in English between 1999 and 2012, and based on the following terms: mild cognitive impairment, Alzheimer's disease OR dementia, biomarkers. We retrieved 1,130 articles, of which 175 were reviews. Overall, 955 original articles were eligible. Results: The following points were considered relevant for the present review: a) rationale for biomarkers research in AD and mild cognitive impairment (MCI); b) usefulness of distinct biomarkers for the diagnosis and prediction of AD; c) the role of multimodality biomarkers for the diagnosis and prediction of AD; d) the role of biomarkers in clinical trials of patients with AD and MCI; and e) current limitations to the widespread use of biomarkers in research and clinical settings. Conclusion: Different biomarkers are useful for the early diagnosis and prediction of AD in at-risk subjects. Nonetheless, important methodological limitations need to be overcome for widespread use of biomarkers in research and clinical settings. © 2013 Associação Brasileira de Psiquiatria.

Magnetic susceptibility in the prediction of soil attributes in two sugarcane harvesting management systems

This study aimed to investigate the potential use of magnetic susceptibility (MS) as pedotransfer function to predict soil attributes under two sugarcane harvesting management systems. For each area of 1 ha (one with green sugarcane mechanized harvesting and other one with burnt sugarcane manual harvesting), 126 soil samples were collected and subjected to laboratory analysis to determine soil physical, chemical and mineralogical attributes and for measuring of MS. Data were submitted to descriptive statistics by calculating the mean and coefficient of variation. In order to compare the means in the different harvesting management systems it was carried out the Tukey test at a significance level of 5%. In order to investigate the correlation of the MS with other soil properties it was made the correlation test and aiming to assess how the MS contributes to the prediction of soil complex attributes it was made the multiple linear regressions. The results demonstrate that MS showed, in both sugarcane harvesting management systems, statistical correlation with chemical, physical and mineralogical soil attributes and it also showed potential to be used as pedotransfer function to predict attributes of the studied oxisol.

Analytical prediction of the spin stabilized satellite's attitude using the solar radiation torque

The aim of this paper is to present an analytical solution for the spin motion equations of spin-stabilized satellite considering only the influence of solar radiation torque. The theory uses a cylindrical satellite on a circular orbit and considers that the satellite is always illuminated. The average components of this torque were determined over an orbital period. These components are substituted in the spin motion equations in order to get an analytical solution for the right ascension and declination of the satellite spin axis. The time evolution for the pointing deviation of the spin axis was also analyzed. These solutions were numerically implemented and compared with real data of the Brazilian Satellite of Data Collection - SCD1 an SCD2. The results show that the theory has consistency and can be applied to predict the spin motion of spin-stabilized artificial satellites.

Prediction of dopant atom distribution on nanocrystals using thermodynamic arguments

A theoretical approach aiming at the prediction of segregation of dopant atoms on nanocrystalline systems is discussed here. It considers the free energy minimization argument in order to provide the most likely dopant distribution as a function of the total doping level. For this, it requires as input (i) a fixed polyhedral geometry with defined facets, and (ii) a set of functions that describe the surface energy as a function of dopant content for different crystallographic planes. Two Sb-doped SnO2 nanocrystalline systems with different morphology and dopant content were selected as a case study, and the calculation of the dopant distributions expected for them is presented in detail. The obtained results were compared to previously reported characterization of this system by a combination of HRTEM and surface energy calculations, and both methods are shown to be equivalent. Considering its application pre-requisites, the present theoretical approach can provide a first estimation of doping atom distribution for a wide range of nanocrystalline systems. We expect that its use will support the reduction of experimental effort for the characterization of doped nanocrystals, and also provide a solution to the characterization of systems where even state-of-art analytical techniques are limited.

Prediction of Oncogenic Interactions and Cancer-Related Signaling Networks Based on Network Topology

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

Assessment of in vitro sperm characteristics and their importance in the prediction of conception rate in a bovine timed-AI program

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Prediction of the combustion process in fluidized bed based on physical-chemical properties of biomass particles and their hydrodynamic behaviors

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

An improved interolog mapping-based computational prediction of protein protein interactions with increased network coverage

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Prediction of genomic-enabled breeding values and genome-wide association study for feedlot average daily weight gain in Nelore cattle

Pós-graduação em Genética e Melhoramento Animal - FCAV

Prediction of soil shear strength in agricultural and natural environments of the Brazilian Cerrado

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)