E-publishing development and changes in the scholarly communication system

New and alternative scientific publishing business models is a reality driven mostly by the information and communication technologies, by the movements towards the recovery of control of the scientific communication activities by the academic community, and by the open access approaches. The hybrid business model, mixing open and toll-access is a reality and they will probably co-exist with respective trade-offs. This essay discusses the changes driven by the epublishing and the impacts on the scholarly communication system stakeholders' interrelationships (publishers-researchers, publishers-libraries and publishers-users interrelationships), and the changes on the scientific publishing business models, followed by a discussion of possible evolving business models. Whatever the model which evolves and dominates, a huge cultural change in authors' and institutions publishing practices will be necessary in order to make the open access happen and to consolidate the right business models for the traditional publishers. External changes such as policies, rewarding systems and institutions mandates should also happen in order to sustain the whole changing scenario.

Biometrical analysis and selection of tetraploid progenies of Panicum maximum using mixed model methods

The objectives of this work were to estimate the genetic and phenotypic parameters and to predict the genetic and genotypic values of the selection candidates obtained from intraspecific crosses in Panicum maximum as well as the performance of the hybrid progeny of the existing and projected crosses. Seventy-nine intraspecific hybrids obtained from artificial crosses among five apomictic and three sexual autotetraploid individuals were evaluated in a clonal test with two replications and ten plants per plot. Green matter yield, total and leaf dry matter yields and leaf percentage were evaluated in five cuts per year during three years. Genetic parameters were estimated and breeding and genotypic values were predicted using the restricted maximum likelihood/best linear unbiased prediction procedure (REML/BLUP). The dominant genetic variance was estimated by adjusting the effect of full-sib families. Low magnitude individual narrow sense heritabilities (0.02-0.05), individual broad sense heritabilities (0.14-0.20) and repeatability measured on an individual basis (0.15-0.21) were obtained. Dominance effects for all evaluated characteristics indicated that breeding strategies that explore heterosis must be adopted. Less than 5% increase in the parameter repeatability was obtained for a three-year evaluation period and may be the criterion to determine the maximum number of years of evaluation to be adopted, without compromising gain per cycle of selection. The identification of hybrid candidates for future cultivars and of those that can be incorporated into the breeding program was based on the genotypic and breeding values, respectively. The prediction of the performance of the hybrid progeny, based on the breeding values of the progenitors, permitted the identification of the best crosses and indicated the best parents to use in crosses.

Auger-type granular fertylizer distributor: matemathical model and dynamic simulation

The objective of this study was to model mathematically and to simulate the dynamic behavior of an auger-type fertilizer applicator (AFA) in order to use the variable-rate application (VRA) and reduce the coefficient of variation (CV) of the application, proposing an angular speed controller θ' for the motor drive shaft. The input model was θ' and the response was the fertilizer mass flow, due to the construction, density of fertilizer, fill factor and the end position of the auger. The model was used to simulate a control system in open loop, with an electric drive for AFA using an armature voltage (V A) controller. By introducing a sinusoidal excitation signal in V A with amplitude and delay phase optimized and varying θ' during an operation cycle, it is obtained a reduction of 29.8% in the CV (constant V A) to 11.4%. The development of the mathematical model was a first step towards the introduction of electric drive systems and closed loop control for the implementation of AFA with low CV in VRA.

Quality of papaya hybrid grown under different irrigation depths

Irrigation is a practice widely used in fruit production in the Brazilian Northeast region, including in the papaya crop in order to increase their productivity. For the purpose of knowing the productive potential of papaya hybrid irrigated, an experiment was carried out in order to evaluate the performance of a papaya hybrid under different irrigations depths. Four irrigation depths (50, 75, 100 and 125% of ETo) were tested and the reference evapotranspiration was calculated by the Penman-Monteith model. The hybrid papaya used was UENF/Caliman 01, which was planted in single rows, spaced 4 x 2m from each other, and irrigated by dripping. The experimental design in randomized blocks was used with six replications and three plants per plot. The following variables were evaluated: transversal diameter, longitudinal diameter, pulp thickness, external and internal appearances, soluble solids, titratable acidity, pulp pH and soluble solids/titratable acidity relation. The higher transversal and longitudinal diameters of the fruit were obtained applying an irrigation depth of about 108% of evapotranspiration. The UENF/Caliman 01 hybrid can be cultivated in the semiarid region of the State of Paraiba, Brazil, with replacement rate of 100% ETo, without compromising the quality of the fruits.

HYBRID ARTIFICIAL NEURAL NETWORK APPLIEDTO MODELING SCFE OF BASIL AND ROSEMARY OILS

This work presents the results of a Hybrid Neural Network (HNN) technique as applied to modeling SCFE curves obtained from two Brazilian vegetable matrices. A series Hybrid Neural Network was employed to estimate the parameters of the phenomenological model. A small set of SCFE data of each vegetable was used to generate an extended data set, sufficient to train the network. Afterwards, other sets of experimental data, not used in the network training, were used to validate the present approach. The series HNN correlates well the experimental data and it is shown that the predictions accomplished with this technique may be promising for SCFE purposes.