Modelling and characterization of AlN-actuated microcantilevers vibrating in the first in-plane mode

The characterization of the first in-plane mode of aluminum nitride-actuated piezoelectric microcantilevers was carried out by using electrical and optical techniques. The top electrode of the cantilever was specifically designed to allow for an efficient electrical actuation of these in-plane modes. In order to confirm the in-plane nature of the modal vibration, the detection of the electrically induced movement was performed optically with the help of a stroboscopic microscope. In parallel, resonances were also measured electrically by means of an impedance analyzer. The quality factor and the resonant frequencies of the in-plane modes were estimated from the corresponding measurement data when applying both detection techniques. Our results show quality factor values as high as 3,000 for the first in-plane mode in air.     

On the differential benchmarking of promotional efficiency with machine learning modelling (II): Practical applications

The assessment of promotional sales with models constructed by machine learning techniques is arousing interest due, among other reasons, to the current economic situation leading to a more complex environment of simultaneous and concurrent promotional activities. An operative model diagnosis procedure was previously proposed in the companion paper, which can be readily used both for agile decision making on the architecture and implementation details of the machine learning algorithms, and for differential benchmarking among models. In this paper, a detailed example of model analysis is presented for two representative databases with different promotional behaviour, namely, a non-seasonal category (milk) and a heavily seasonal category (beer). The performance of four well-known machine learning techniques with increasing complexity is analyzed in detail here. In particular, k-Nearest Neighbours, General Regression Neural Networks, Multilayer Perceptron (MLP), and Support Vector Machines (SVM), are differentially compared. Present paper evaluates these techniques along the experiments described for both categories when applying the methodological findings obtained in the companion paper. We conclude that some elements included in the architecture are not essential for a good performance of the machine learning promotional models, such as the semiparametric nature of the kernel in SVM models, whereas other can be strongly dependent of the database, such as the convenience of multiple output models in MLP regression schemes. Additionally, the specificity of the behaviour of certain categories and product ranges determines the need to establish suitable and specific procedures for a better prediction and feature extraction.     

On the asymmetrical dependence of the threshold pressure of infiltration on the wettability of the porous solid by the infiltrating liquid

A general equation has been derived for the threshold pressure of infiltration of liquids into porous solids. From this equation all the known equations for the threshold pressure can be obtained, using different assumptions on the morphology of the porous solid and on the way how the liquid infiltrates the solid. Particularly, the Young-Laplace equation, the Carman-equation, and the modification of the Carman equation, suggested by White and later by Mortensen and Cornie have been reproduced as particular cases of the general equation. A new particular solution of this general equation is also suggested, taking into account that the original solid/gas interface inside the porous body is not fully replaced by the solid/liquid interface during infiltration, especially for the case of non-wetting liquids. The new, general equation consists of three semi-empirical parameters, which should be found experimentally for a given type of morphology of the porous solid and for the given ratio of the surface tension to the density of the infiltrating liquid metal. The new equation provides a value of the threshold contact angle to be between 65.5° and 90°, depending on the morphology of the porous solid. Consequently, the threshold pressure appears to be an asymmetrical function of the contact angle. Based on the new equation, the practical constancy of the threshold pressure is predicted in the interval of the contact angles between 120° and 180°.     

Immunohistochemistry of neuronal nitric oxide synthase and protein nitration in the striatum of the aged rat

To ascertain the possible implications of the nitric oxide (NO*) producing system in striatal senescence, and by using immunohistochemistry and image-processing approaches, we describe the presence of the enzyme nitric oxide synthase (NOS), the NADPH-diaphorase (NADPH-d) histochemical marker, and nitrotyrosine-derived complexes (N-Tyr) in the striatum of adult and aged rats. The results showed neuronal NOS immunoreactive (nNOS-IR) aspiny medium-sized neurons and nervous fibres in both age groups, with no variation in the percentage of immunoreactive area but a significant decrease in the intensity and in the number of somata with age, which were not related to the observed increase with age of the striatal bundles of the white matter. In addition, NADPH-d activity was detected in neurons with morphology similar to that of the nNOS-IR cells; a decrease in the percentage of area per field and in the number of cells, but an increase in the intensity of staining for the NADPH-d histochemical marker, were detected with age. The number of neuronal NADPH-d somata was higher than for the nNOS-IR ones in both age groups. Moreover, N-Tyr-IR complexes were observed in cells (neurons and glia) and fibres, with a significant increase in the percentage of the area of immunoreaction, related to the increase of white matter, but a decrease in intensity for the aged group. On the other hand, we did not detect the inducible isoform (iNOS) either in adult or in aged rats. Taken together, these results support the contention that NADPH-d staining is not such an unambiguous marker for nNOS, and that increased protein nitration may participate in striatal aging.     

Groundwater Numerical Simulation in an Open Pit Mine in a Limestone Formation Using MODFLOW

Numerical groundwater simulations of a complex limestone formation quarry in northern Spain enabled problems there to be quantified. A conceptual model of the aquifer, based on extensive in situ field work and information analysis was developed using MODFLOW. Steady state simulations as well as a first transient simulation were performed. The predictions matched the measured flows in the pit reasonably well, allowing practical scenarios of immediate interest to be simulated. Model calibration suggested a new permeability zonation, dependent of the degree of fracturing. The model provides a consistent quantitative framework with which new tests or operations can be evaluated in a cost effective manner.     

Improving spectral results in a GTS context

This paper shows the advantages of post-processing spectral classifications in a Geographical Information System (GIS) context in order to improve results. A maximum-likelihood algorithm was used to classify(both supervised and non-supervised) a Landsat TM sub-image in Central Mexico. Purely spectral processing yielded poor accuracy results, showing the spectral limitation to distinguish classes; as a consequence, merging classes was necessary in order to increase accuracy (from less than 55 to 82 per cent). GIS rules were finally applied based on ancillary data (terrain mapping units and elevation data) improving the final accuracy to 88.2 and 83.0 per cent (supervised and non-supervised classifications).     

Pole-assignment problem for discrete-time linear periodic systems

This paper considers the pole-assignment problem for discrete-time linear periodic systems through the use of linear periodic state-variable feedback control. It is shown that if the N-periodic system with m inputs and n states is completely reachable then the problem can be reduced to the pole-assignment problem for a discrete-time linear invariant system with Nm inputs and n states.     

A metaheuristic-based downlink power allocation for LTE/LTE-A cellular deployments

The explosive growth of cellular networks makes their deployment and maintenance more and more complex, time consuming, and expensive. Self-Organizing Networks have been recognized as a promising way to alleviate this problem by minimizing human intervention in such processes. This paper introduces a novel multiobjective framework, based on evolutionary optimization, aiming at improving network performance and users Quality of Service. By tuning the transmitted power at each cell, average intercell interference levels are minimized. The design of the proposed scheme is feasible for distributed implementations in Long Term Evolution (LTE) and LTE-Advanced networks and its operation is compatible with current specifications. The framework is able to provide effective network-specific optimization and obtained results show that gains in terms of network capacity and cell edge performance are 5 and 10 %, respectively. Energy savings always accompanied such enhancements with reductions up to 35 %.