Contrasting Rootstock-Mediated Growth and Yield Responses in Salinized Pepper Plants (Capsicum annuum L.) Are Associated with Changes in the Hormonal Balance

Salinity provokes an imbalance of vegetative to generative growth, thus impairing crop productivity. Unlike breeding strategies, grafting is a direct and quick alternative to improve salinity tolerance in horticultural crops, through rebalancing plant development. Providing that hormones play a key role in plant growth and development and stress responses, we hypothesized that rootstock-mediated reallocation of vegetative growth and yield under salinity was associated with changes in the hormonal balance. To test this hypothesis, the hybrid pepper variety (Capsicum annuum L. “Gacela F1”) was either non-grafted or grafted onto three commercial rootstocks (Creonte, Atlante, and Terrano) and plants were grown in a greenhouse under control (0 mM NaCl) and moderate salinity (35 mM NaCl) conditions. Differential vegetative growth versus fruit yield responses were induced by rootstock and salinity. Atlante strongly increased shoot and root fresh weight with respect to the non-grafted Gacela plants associated with improved photosynthetic rate and K⁺ homeostasis under salinity. The invigorating effect of Atlante can be explained by an efficient balance between cytokinins (CKs) and abscisic acid (ABA). Creonte improved fruit yield and maintained the reproductive to vegetative ratio under salinity as a consequence of its capacity to induce biomass reallocation and to avoid Na⁺ accumulation in the shoot. The physiological responses associated with yield stability in Creonte were mediated by the inverse regulation of CKs and the ethylene precursor 1-aminocyclopropane-1-carboxylic acid. Finally, Terrano limited the accumulation of gibberellins in the shoot thus reducing plant height. Despite scion compactness induced by Terrano, both vegetative and reproductive biomass were maintained under salinity through ABA-mediated control of water relations and K⁺ homeostasis. Our data demonstrate that the contrasting developmental and physiological responses induced by the rootstock genotype in salinized pepper plants were critically mediated by hormones. This will be particularly important for rootstock breeding programs to improve salinity tolerance by focusing on hormonal traits.     

A review on the combination of binary classifiers in multiclass problems

Several real problems involve the classification of data into categories or classes. Given a data set containing data whose classes are known, Machine Learning algorithms can be employed for the induction of a classifier able to predict the class of new data from the same domain, performing the desired discrimination. Some learning techniques are originally conceived for the solution of problems with only two classes, also named binary classification problems. However, many problems require the discrimination of examples into more than two categories or classes. This paper presents a survey on the main strategies for the generalization of binary classifiers to problems with more than two classes, known as multiclass classification problems. The focus is on strategies that decompose the original multiclass problem into multiple binary subtasks, whose outputs are combined to obtain the final prediction.     

Characterizing the measures on the unit circle with exact quadrature formulas in the space of polynomials

In the present paper we characterize the measures on the unit circle for which there exists a quadrature formula with a fixed number of nodes and weights and such that it exactly integrates all the polynomials with complex coefficients. As an application we obtain quadrature rules for polynomial modifications of the Bernstein measures on [−1,1], having a fixed number of nodes and quadrature coefficients and such that they exactly integrate all the polynomials with real coefficients.     

Analyzing Architectural Evolution Issues of Multimedia Frameworks

The growing complexity in the development of Web-based services in general, and multimedia services in particular, makes necessary the application of sound development methods. New multimedia devices, coding algorithms, network protocols, etc., are continually appearing but, unfortunately, current solutions for developing multimedia applications do not accurately support architectural evolution issues for already deployed applications. Thus, the latest Software Engineering technologies should be applied to the development of open, reusable, and high-quality multimedia and Web-based software. In this paper, we apply component and framework technologies, two of the current trends in Software Engineering, to the development of multimedia services over the Web, presenting and comparing widespread solutions in use today.     

Dynamic multi-commodity capacitated facility location: a mathematical modeling framework for strategic supply chain planning

In this paper, we focus on the strategic design of supply chain networks. We propose a mathematical modeling framework that captures many practical aspects of network design problems simultaneously but which have not received adequate attention in the literature. The aspects considered include: dynamic planning horizon, generic supply chain network structure, external supply of materials, inventory opportunities for goods, distribution of commodities, facility configuration, availability of capital for investments, and storage limitations. Moreover, network configuration decisions concerning the gradual relocation of facilities over the planning horizon are considered. To cope with fluctuating demands, capacity expansion and reduction scenarios are also analyzed as well as modular capacity shifts. The relation of the proposed modeling framework with existing models is discussed. For problems of reasonable size, we report on our computational experience with standard mathematical programming software. In particular, useful insights on the impact of various factors on network design decisions are provided.     

Closed loop torque SVM-DTC based on robust super twisting speed controller for induction motor drive with efficiency optimization

This paper presents a space vector modulation (SVM) based Direct Torque Control strategy (DTC) for induction motor (IM) in order to overcome the drawbacks of the classical DTC. SVM can reduce the high torque and flux ripples by preserving a fixed switching frequency. This technique is known by the closed loop torque SVM-DTC. Moreover, the control scheme performance is improved by inserting a second order sliding mode super twisting controller in the outer loop for speed regulation. This nonlinear technique ensures a good dynamic and high robustness against external disturbance. Furthermore, the IM energy optimization is treated in the second objective of this paper. A proposed model based loss minimization strategy is presented for efficiency optimization. This strategy chooses an optimal flux magnitude for each applied load torque. The proposed optimized SVM-DTC algorithm will be investigated by simulation and real time implementation using Matlab/Simulink with real time interface based on dSpace 1104 signal card.     

Modeling of reverse osmosis flux of aqueous solution containing glucose

The aim of the paper is to model the permeate flux during reverse osmosis (RO) of a highly concentrated glucose solution using the osmotic pressure model. Such a model accounts for the effect of the concentration polarization phenomenon on the permeate flux. To apply this model the viscosity, the osmotic pressure of solution and the diffusion coefficient of glucose were estimated. Using mathematical simulation software, the values of mass transfer coefficient for different concentrations of glucose (5, 10, 15 and 20 wt%) and at different feed flow rate were determined. The experimental permeate flux values conducted on flat RO membranes (Type HR-99) agreed well with the values calculated by the osmotic pressure model, as shown by statistical analysis.