Phase locked loop-based clock synthesizer for reconfigurable analog-to-digital converters

Analog Integrated Circuits and Signal Processing - This paper presents the complete design of a phase locked loop-based clock synthesizer for reconfigurable analog-to-digital converters. The...     

Design and development of a multichannel potentiometer for monitoring an electrode array and its application in flow analysis

A versatile potentiometer that works with electrode arrays in flow injection and/or monosegmented flow systems is described. The potentiometer is controlled by a microcomputer that allows individual, sequential multiplexed or random accesses to eight electrodes while employing only one reference electrode. The instrument was demonstrated by monitoring an array of seven flow-through ion-selective electrodes for Ag(+) and for three electrodes for Cl(-), Ca(2+) and K(+). The figures of merit of the individual and multiplexed (summed) readings of the electrode array were compared. The absolute standard deviation of the measurements made by summing the potential of two or more electrodes was maintained constant, thus improving the precision of the measurements. This result shows that an attempt to combine the signals of the electrodes to produce a more intense signal in the Hadamard strategy is feasible and accompanied by a proportional improvement in the precision of individual measurements. The preliminary tests suggest that the system can allow for 270 determinations per hour, with a linear range from 1.0 x 10(-2) to 1.0 x 10(-4) mol l(-1) for the three di inverted exclamation markerent analytes. Detection limits were estimated as 3.1 x 10(-5), 3.0 x 10(-6) and 1.0 x 10(-5) mol l(-1) for Cl(-), Ca(2+) and K(+), respectively.     

Ensemble of Efficient Minimal Learning Machines for Classification and Regression

Minimal Learning Machine (MLM) is a recently proposed supervised learning algorithm with performance comparable to most state-of-the-art machine learning methods. In this work, we propose ensemble methods for classification and regression using MLMs. The goal of ensemble strategies is to produce more robust and accurate models when compared to a single classifier or regression model. Despite its successful application, MLM employs a computationally intensive optimization problem as part of its test procedure (out-of-sample data estimation). This becomes even more noticeable in the context of ensemble learning, where multiple models are used. Aiming to provide fast alternatives to the standard MLM, we also propose the Nearest Neighbor Minimal Learning Machine and the Cubic Equation Minimal Learning Machine to cope with classification and single-output regression problems, respectively. The experimental assessment conducted on real-world datasets reports that ensemble of fast MLMs perform comparably or superiorly to reference machine learning algorithms.     

An adaptive learning approach for 3-D surface reconstruction from point clouds.

In this paper, we propose a multiresolution approach for surface reconstruction from clouds of unorganized points representing an object surface in 3-D space. The proposed method uses a set of mesh operators and simple rules for selective mesh refinement, with a strategy based on Kohonen's self-organizing map (SOM). Basically, a self-adaptive scheme is used for iteratively moving vertices of an initial simple mesh in the direction of the set of points, ideally the object boundary. Successive refinement and motion of vertices are applied leading to a more detailed surface, in a multiresolution, iterative scheme. Reconstruction was experimented on with several point sets, including different shapes and sizes. Results show generated meshes very close to object final shapes. We include measures of performance and discuss robustness.     

Response of Corn Seedlings (Zea mays L.) to Different Concentrations of Nitrogen in Absence and Presence of Silicon

Silicon - Corn plants are highly demanding of nitrogen and the application of silicon has been studied because it minimizes stress from different natures, and for the better utilization of some...     

Plant oil bioconversion into increase biological activity through lipases derived from wastes

The aim of this study was to show that abundant and inexpensive plant oils can be biotransformed to increase biological activity (antioxidant, antimicrobial and cytotoxicity) through hydrolysis reaction catalysed by lipases. We tested homemade and commercial lipases through the biotransformation of nine different plant oils in forty different combinations. First, the chemical composition of the samples was investigated. Thereafter, biological tests were conducted to assess the antioxidant and antimicrobial activity of the sampled biotransformation products, as well as analyzed their influence on the viability of healthy and cancer cells. Summarising, sunflower, corn and olive oils modified by orange waste-obtained lipases presented the most promising results, reaching up to 90% of antioxidant activity increase and significant growth inhibition of bacteria colonies belonging to genera Escherichia, Listeria, Staphylococcus, Pseudomonas and Salmonella. In addition, those compounds affected human oral squamous carcinoma cells. The bioconversion of plant oils through lipases improves their biological properties and might be an option for biotechnological application.     

Modification of coconut fibers with polyaniline for manufacture of pressure‐sensitive devices

This article studies the modification of coconut fibers with polyaniline (PAni) with help of statistical experimental design techniques. The main factors studied here were the techniques used for particle dispersion (sonication vs. magnetic stirring) and the type of initiator (ammonium persulfate, APS, vs. ammonium cerium sulfate dihydrate, Ce(IV)). The obtained materials were characterized through low field nuclear magnetic resonance, small‐and wide‐angle X‐ray scattering, scanning electron microscopy, fourier transform infrared spectroscopy, and ultraviolet–visible spectroscopy. Additionally, the electrical resistivities and respective sensitivities to variations of the applied pressure were evaluated for all obtained samples, with help of standard volume resistivity measurements and electro‐mechanical tests. The materials prepared through magnetic stirring with APS presented the best electrical and electromechanical properties, although materials prepared through sonication with Ce(IV) also presented good electrical and electromechanical properties and could be prepared much faster. As a consequence, modification of coconut fibers with PAni, using sonication as the particle dispersion technique and Ce(IV) as initiator, constitutes a very promising procedure for manufacture of pressure‐sensitive devices. POLYM. ENG. SCI., 54:2887–2895, 2014. © 2014 Society of Plastics Engineers