Prediction of intake and average daily gain by different feeding systems for goats

A main purpose of a mathematical nutrition model (a.k.a., feeding systems) is to provide a mathematical approach for determining the amount and composition of the diet necessary for a certain level of animal productive performance. Therefore, feeding systems should be able to predict voluntary feed intake and to partition nutrients into different productive functions and performances. In the last decades, several feeding systems for goats have been developed. The objective of this paper is to compare and evaluate the main goat feeding systems (AFRC, CSIRO, NRC, and SRNS), using data of individual growing goat kids from seven studies conducted in Brazil. The feeding systems were evaluated by regressing the residuals (observed minus predicted) on the predicted values centered on their means. The comparisons showed that these systems differ in their approach for estimating dry matter intake (DMI) and energy requirements for growing goats. The AFRC system was the most accurate for predicting DMI (mean bias = 91 g/d, P < 0.001; linear bias 0.874). The average ADG accounted for a large part of the bias in the prediction of DMI by CSIRO, NRC, and, mainly, AFRC systems. The CSIRO model gave the most accurate predictions of ADG when observed DMI was used as input in the models (mean bias 12 g/d, P < 0.001; linear bias -0.229). while the AFRC was the most accurate when predicted DMI was used (mean bias 8g/d. P > 0.1; linear bias -0.347). (C) 2011 Elsevier B.V. All rights reserved.

Fine root isotropy in Eucalyptus grandis plantations. Towards the prediction of root length densities from root counts on trench walls

The objectives of the study were to assess changes in fine root anisotropy and specific root lengths throughout the development of Eucalyptus grandis ( W. Hill ex Maiden) plantations and to establish a predictive model of root length density (RLD) from root intercept counts on trench walls. Fine root densities (<1 mm in diameter) were studied in 6-, 12-, 22-, 28-, 54-, 68- and 72-month-old E. grandis plantations established on deep Ferralsols in southern Brazil. Fine root intercepts were counted on 3 faces of 90-198 soil cubes (1 dm(3) in volume) in each stand and fine root lengths (L) were measured inside 576 soil cubes, sampled between the depths of 10 cm and 290 cm. The number of fine root intercepts was counted on one vertical face perpendicular to the planting row (N(t)), one vertical face parallel to the planting row (N(l)) and one horizontal face (N(h)), for each soil cube sampled. An overall isotropy of fine roots was shown by paired Student's t-tests between the numbers of fine roots intersecting each face of soil cubes at most stand ages and soil depths. Specific root lengths decreased with stand age in the upper soil layers and tended to increase in deep soil layers at the end of the rotation. A linear regression established between N(t) and L for all the soil cubes sampled accounted for 36% of the variability of L. Such a regression computed for mean Nt and L values at each sampling depth and stand age explained only 55% of the variability, as a result of large differences in the relationship between L and Nt depending on stand productivity. The equation RLD=1.89*LAI*N(t), where LAI was the stand leaf area index (m(2) m(-2)) and Nt was expressed as the number of root intercepts per cm(2), made it possible to predict accurately (R(2)=0.84) and without bias the mean RLDs (cm cm(-3)) per depth in each stand, for the whole data set of 576 soil cubes sampled between 2 years of age and the end of the rotation.

Spacecraft's attitude prediction: solar radiation torque and the Earth's shadow

A semi-analytical approach is proposed to study the rotational motion of an artificial satellite, under the influence of torque due to the solar radiation pressure, and taking into account the influence of Earth's shadow. Using Andoyer variables the equations for the rotational motion are presented in extended Hamiltonian form. In order to get a solution for the state variables close to an actual motion, the considered model for the shadow function takes into account physical and geometric factors and three specific regions: shadow, penumbra and full light. A mapping for the shadow function is proposed and a semi-analytical process is applied. When the satellite is totally illuminated or it is inside the penumbra, a known analytical solution is used to compute the satellite's attitude. A numerical simulation shows, when the penumbra region is included, the attenuation of the rotational motion during the transition from the shadow to the illuminate region and vice versa. (c) 2005 Published by Elsevier Ltd on behalf of COSPAR.

Analytical attitude prediction of spin stabilized spacecrafts perturbed by magnetic residual torque

An analytical approach for spin-stabilized spacecraft attitude prediction is presented for the influence of the residual magnetic torques. Assuming an inclined dipole model for the Earth's magnetic field, an analytical averaging method is applied to obtain the mean residual torque every orbital period. The orbit mean anomaly is utilized to compute the average components of residual torque in the spacecraft body frame reference system. The theory is developed for time variations in the orbital elements, and non-circular orbits, giving rise to many curvature integrals. It is observed that the residual magnetic torque does not have component along the spin axis. The inclusion of this torque on the rotational motion differential equations of a spin stabilized spacecraft yields conditions to derive an analytical solution. The solution shows that residual torque does not affect the spin velocity magnitude, contributing only for the precession and the drift of the spin axis of the spacecraft. (c) 2005 COSPAR. Published by Elsevier Ltd. All rights reserved.

Search for the standard model Higgs boson decaying to bottom quarks in pp collisions at root s=7 TeV

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

A combined search for the standard model Higgs boson at root S=1.96 TeV

We present new results of the search for WH --> lvb (b) over bar production in p (p) over bar collisions at a center-of-mass energy of root S = 1.96 TeV, based on a dataset with integrated luminosity of 0.44 fb(-1). We combine these new results with previously published searches by the do collaboration, for WH and ZH production analyzed in the E(T)b (b) over bar final state, for ZH (--> l(+)l(-)b (b) over bar) production, for WH (-->. WWW) production, and for H (--> W W) direct production. No signal-like excess is observed either in the W H analysis or in the combination of all D0 Higgs boson analyses. We set 95% C.L. (expected) upper limits on sigma(p (p) over bar --> WH) x B(H --> b (b) over bar) ranging from 1.6 (2.2) ph to 1.9 (3.3) pb for Higgs boson masses between 105 and 145 GeV, to be compared to the theoretical prediction of 0.13 pb for a Standard Model (SM) Higgs boson with mass in m(H) = 115 GeV. After combination with the other do Higgs boson searches, we obtain for in H = 115 GeV an observed (expected) limit 8.5 (12.1) times higher than the SM predicted Higgs boson production cross section. For m(H) = 160 GeV, the corresponding observed (expected) ratio is 10.2 (9.0). (C) 2008 Elsevier B.V. All rights reserved.

Integrodifference model for blowfly invasion

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Is the LHC observing the pseudoscalar state of a two-Higgs-doublet model?

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Carbon Nuclear Magnetic Resonance Spectroscopic Profiles coupled to Partial Least-Squares Multivariate Regression for Prediction of Several Physicochemical Parameters of Brazilian Commercial Gasoline

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Multivariate calibrations on H-1 NMR profiles for prediction of physicochemical parameters of Brazilian commercial gasoline

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Multivariate calibrations in gas chromatographic profiles for prediction of several physicochemical parameters of Brazilian commercial gasoline

Several Brazilian commercial gasoline physicochemical parameters, such as relative density, distillation curve (temperatures related to 10%, 50% and 90% of distilled volume, final boiling point and residue), octane numbers (motor and research octane number and anti-knock index), hydrocarbon compositions (olefins, aromatics and saturates) and anhydrous ethanol and benzene content was predicted from chromatographic profiles obtained by flame ionization detection (GC-FID) and using partial least square regression (PLS). GC-FID is a technique intensively used for fuel quality control due to its convenience, speed, accuracy and simplicity and its profiles are much easier to interpret and understand than results produced by other techniques. Another advantage is that it permits association with multivariate methods of analysis, such as PLS. The chromatogram profiles were recorded and used to deploy PLS models for each property. The standard error of prediction (SEP) has been the main parameter considered to select the "best model". Most of GC-FID-PLS results, when compared to those obtained by the Brazilian Government Petroleum, Natural Gas and Biofuels Agency - ANP Regulation 309 specification methods, were very good. In general, all PLS models developed in these work provide unbiased predictions with lows standard error of prediction and percentage average relative error (below 11.5 and 5.0, respectively). (C) 2007 Elsevier B.V. All rights reserved.

The Chemical Percolation Devolatilization Model Applied to the Devolatilization of Coal in High Intensity Acoustic Fields

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

The STATFLUX code: a statistical method for calculation of flow and set of parameters, based on the Multiple-Compartment Biokinetical Model

The code STATFLUX, implementing a new and simple statistical procedure for the calculation of transfer coefficients in radionuclide transport to animals and plants, is proposed. The method is based on the general multiple-compartment model, which uses a system of linear equations involving geometrical volume considerations. Flow parameters were estimated by employing two different least-squares procedures: Derivative and Gauss-Marquardt methods, with the available experimental data of radionuclide concentrations as the input functions of time. The solution of the inverse problem, which relates a given set of flow parameter with the time evolution of concentration functions, is achieved via a Monte Carlo Simulation procedure.Program summaryTitle of program: STATFLUXCatalogue identifier: ADYS_v1_0Program summary URL: http://cpc.cs.qub.ac.uk/summaries/ADYS_v1_0Program obtainable from: CPC Program Library, Queen's University of Belfast, N. IrelandLicensing provisions: noneComputer for which the program is designed and others on which it has been tested: Micro-computer with Intel Pentium III, 3.0 GHzInstallation: Laboratory of Linear Accelerator, Department of Experimental Physics, University of São Paulo, BrazilOperating system: Windows 2000 and Windows XPProgramming language used: Fortran-77 as implemented in Microsoft Fortran 4.0. NOTE: Microsoft Fortran includes non-standard features which are used in this program. Standard Fortran compilers such as, g77, f77, ifort and NAG95, are not able to compile the code and therefore it has not been possible for the CPC Program Library to test the program.Memory, required to execute with typical data: 8 Mbytes of RAM memory and 100 MB of Hard disk memoryNo. of bits in a word: 16No. of lines in distributed program, including test data, etc.: 6912No. of bytes in distributed Program, including test data, etc.: 229 541Distribution format: tar.gzNature of the physical problem: the investigation of transport mechanisms for radioactive substances, through environmental pathways, is very important for radiological protection of populations. One such pathway, associated with the food chain, is the grass-animal-man sequence. The distribution of trace elements in humans and laboratory animals has been intensively studied over the past 60 years [R.C. Pendlenton, C.W. Mays, R.D. Lloyd, A.L. Brooks, Differential accumulation of iodine-131 from local fallout in people and milk, Health Phys. 9 (1963) 1253-1262]. In addition, investigations on the incidence of cancer in humans, and a possible causal relationship to radioactive fallout, have been undertaken [E.S. Weiss, M.L. Rallison, W.T. London, W.T. Carlyle Thompson, Thyroid nodularity in southwestern Utah school children exposed to fallout radiation, Amer. J. Public Health 61 (1971) 241-249; M.L. Rallison, B.M. Dobyns, F.R. Keating, J.E. Rall, F.H. Tyler, Thyroid diseases in children, Amer. J. Med. 56 (1974) 457-463; J.L. Lyon, M.R. Klauber, J.W. Gardner, K.S. Udall, Childhood leukemia associated with fallout from nuclear testing, N. Engl. J. Med. 300 (1979) 397-402]. From the pathways of entry of radionuclides in the human (or animal) body, ingestion is the most important because it is closely related to life-long alimentary (or dietary) habits. Those radionuclides which are able to enter the living cells by either metabolic or other processes give rise to localized doses which can be very high. The evaluation of these internally localized doses is of paramount importance for the assessment of radiobiological risks and radiological protection. The time behavior of trace concentration in organs is the principal input for prediction of internal doses after acute or chronic exposure. The General Multiple-Compartment Model (GMCM) is the powerful and more accepted method for biokinetical studies, which allows the calculation of concentration of trace elements in organs as a function of time, when the flow parameters of the model are known. However, few biokinetics data exist in the literature, and the determination of flow and transfer parameters by statistical fitting for each system is an open problem.Restriction on the complexity of the problem: This version of the code works with the constant volume approximation, which is valid for many situations where the biological half-live of a trace is lower than the volume rise time. Another restriction is related to the central flux model. The model considered in the code assumes that exist one central compartment (e.g., blood), that connect the flow with all compartments, and the flow between other compartments is not included.Typical running time: Depends on the choice for calculations. Using the Derivative Method the time is very short (a few minutes) for any number of compartments considered. When the Gauss-Marquardt iterative method is used the calculation time can be approximately 5-6 hours when similar to 15 compartments are considered. (C) 2006 Elsevier B.V. All rights reserved.

Weather-based prediction of anthracnose severity using artificial neural network models

Data were collected and analysed from seven field sites in Australia, Brazil and Colombia on weather conditions and the severity of anthracnose disease of the tropical pasture legume Stylosanthes scabra caused by Colletotrichum gloeosporioides. Disease severity and weather data were analysed using artificial neural network (ANN) models developed using data from some or all field sites in Australia and/or South America to predict severity at other sites. Three series of models were developed using different weather summaries. of these, ANN models with weather for the day of disease assessment and the previous 24 h period had the highest prediction success, and models trained on data from all sites within one continent correctly predicted disease severity in the other continent on more than 75% of days; the overall prediction error was 21.9% for the Australian and 22.1% for the South American model. of the six cross-continent ANN models trained on pooled data for five sites from two continents to predict severity for the remaining sixth site, the model developed without data from Planaltina in Brazil was the most accurate, with >85% prediction success, and the model without Carimagua in Colombia was the least accurate, with only 54% success. In common with multiple regression models, moisture-related variables such as rain, leaf surface wetness and variables that influence moisture availability such as radiation and wind on the day of disease severity assessment or the day before assessment were the most important weather variables in all ANN models. A set of weights from the ANN models was used to calculate the overall risk of anthracnose for the various sites. Sites with high and low anthracnose risk are present in both continents, and weather conditions at centres of diversity in Brazil and Colombia do not appear to be more conducive than conditions in Australia to serious anthracnose development.

Model for electrodes' filaments of hot cathode fluorescent lamps, during preheating with constant rms current

This paper presents a new model for the representation of electrodes' filaments of hot-cathode fluorescent lamps, during preheating processes based on the injection of currents with constant root mean square (rms) values. The main improvement obtained with this model is the prediction of the R-h/R-c ratio during the preheating process, as a function of the preheating time and of the rms current injected in the electrodes. Using the proposed model, it is possible to obtain an estimate of the time interval and the current that should be provided by the electronic ballast, in order to ensure a suitable preheating process. is estimate of time and current can be used as input data in the design of electronic ballasts with programmed lamp start, permitting the prediction of the R-h/R-c ratio during the initial steps of the design (theoretical analysis and digital simulation). Therefore, the use of the proposed model permits to reduce the necessity of several empirical adjustments in the prototype, in order to set the operation of electronic ballasts during the preheating process. This fact reduces time and costs associated to the global design procedure of electronic ballasts.