Field effect and light-assisted a-Si:H sensors for detection of ions in solution

In this paper we present an amorphous silicon device that can be used in two operation modes to measure the concentration of ions in solution. While crystalline devices present a higher sensitivity, their amorphous counterpart present a much lower fabrication cost, thus enabling the production of cheap disposable sensors for use, for example, in the food industry. The devices were fabricated on glass substrates by the PECVD technique in the top gate configuration, where the metallic gate is replaced by an electrolytic solution with an immersed Ag/AgCl reference electrode. Silicon nitride is used as gate dielectric enhancing the sensitivity and passivation layer used to avoid leakage and electrochemical reactions. In this article we report on the semiconductor unit, showing that the device can be operated in a light-assisted mode, where changes in the pH produce changes on the measured ac photocurrent. In alternative the device can be operated as a conventional ion selective field effect device where changes in the pH induce changes in the transistor's threshold voltage.

Low Complexity Intra Mode Selection for Efficient Distributed Video Coding

Motion compensated frame interpolation (MCFI) is one of the most efficient solutions to generate side information (SI) in the context of distributed video coding. However, it creates SI with rather significant motion compensated errors for some frame regions while rather small for some other regions depending on the video content. In this paper, a low complexity Infra mode selection algorithm is proposed to select the most 'critical' blocks in the WZ frame and help the decoder with some reliable data for those blocks. For each block, the novel coding mode selection algorithm estimates the encoding rate for the Intra based and WZ coding modes and determines the best coding mode while maintaining a low encoder complexity. The proposed solution is evaluated in terms of rate-distortion performance with improvements up to 1.2 dB regarding a WZ coding mode only solution.

Studies in 3-oxy-assisted 3-aza Cope rearrangements

On thermolysis appropriately substituted N-silyloxy-N-allyl enamines undergo smooth 3,3-sigmatropic rearrangments to the corresponding N-silyloxy imino ethers.

Application of GIS-based multi-criteria analysis for site selection of aquifer recharge with reclaimed water

Reclaimed water from small wastewater treatment facilities in the rural areas of the Beira Interior region (Portugal) may constitute an alternative water source for aquifer recharge. A 21-month monitoring period in a constructed wetland treatment system has shown that 21,500 m(3) year(-1) of treated wastewater (reclaimed water) could be used for aquifer recharge. A GIS-based multi-criteria analysis was performed, combining ten thematic maps and economic, environmental and technical criteria, in order to produce a suitability map for the location of sites for reclaimed water infiltration. The areas chosen for aquifer recharge with infiltration basins are mainly composed of anthrosol with more than 1 m deep and fine sand texture, which allows an average infiltration velocity of up to 1 m d(-1). These characteristics will provide a final polishing treatment of the reclaimed water after infiltration (soil aquifer treatment (SAT)), suitable for the removal of the residual load (trace organics, nutrients, heavy metals and pathogens). The risk of groundwater contamination is low since the water table in the anthrosol areas ranges from 10 m to 50 m. Oil the other hand, these depths allow a guaranteed unsaturated area suitable for SAT. An area of 13,944 ha was selected for study, but only 1607 ha are suitable for reclaimed water infiltration. Approximately 1280 m(2) were considered enough to set up 4 infiltration basins to work in flooding and drying cycles.

Laser-assisted deposition of thin films from photoexcited vapour phases

Laser-assisted chemical vapour deposition (LCVD) has been extensively studied in the last two decades. A vast range of applications encompass various areas such as microelectronics, micromechanics, microelectromechanics and integrated optics, and a variety of metals, semiconductors and insulators have been grown by LCVD. In this article, we review briefly the LCVD process and present two case studies of thin film deposition related to laser thermal excitation (e.g., boron carbide) and non-thermal excitation (e.g., CrO(2)) of the gas phase.

Desilication of MOR zeolite: Conventional versus microwave assisted heating

MOR zeolites were modified via desilication treatments with NaOH, under conventional and microwave heating. The samples were characterized by powder X-ray diffraction, (27)Al and (29)Si NMR spectroscopy. TEM and N(2) adsorption at -196 degrees C. The acidity of the samples and the space available inside the pores were evaluated through a catalytic model reaction, the isomerization of m-xylene, for which the profiles of the coke thermal decomposition were also analyzed. Powder X-ray diffraction and (29)Si and (27)Al MNR results show that in comparison with conventional heating, microwave irradiation (a less time consuming process) leads to identical amount of Si extraction from the zeolite framework. With this treatment. in addition to the customary mesopores development promoted by conventional heating, a partial conversion of the zeolite microporosity into larger micropores, is observed. The microwave irradiated and conventionally heated samples show different catalytic behavior in the m-xylene isomerization model reaction. It was observed that, by controlling the experimental conditions, it is possible to obtain samples with catalytic properties closer to the parent material, which is also confirmed by the respective coke analysis. (C) 2011 Elsevier B.V. All rights reserved.

Methods for automatic and assisted image annotation

Personal memories composed of digital pictures are very popular at the moment. To retrieve these media items annotation is required. During the last years, several approaches have been proposed in order to overcome the image annotation problem. This paper presents our proposals to address this problem. Automatic and semi-automatic learning methods for semantic concepts are presented. The automatic method is based on semantic concepts estimated using visual content, context metadata and audio information. The semi-automatic method is based on results provided by a computer game. The paper describes our proposals and presents their evaluations.

Feature selection for clustering categorical data with an embedded modelling approach

Research on the problem of feature selection for clustering continues to develop. This is a challenging task, mainly due to the absence of class labels to guide the search for relevant features. Categorical feature selection for clustering has rarely been addressed in the literature, with most of the proposed approaches having focused on numerical data. In this work, we propose an approach to simultaneously cluster categorical data and select a subset of relevant features. Our approach is based on a modification of a finite mixture model (of multinomial distributions), where a set of latent variables indicate the relevance of each feature. To estimate the model parameters, we implement a variant of the expectation-maximization algorithm that simultaneously selects the subset of relevant features, using a minimum message length criterion. The proposed approach compares favourably with two baseline methods: a filter based on an entropy measure and a wrapper based on mutual information. The results obtained on synthetic data illustrate the ability of the proposed expectation-maximization method to recover ground truth. An application to real data, referred to official statistics, shows its usefulness.

ECG Biometrics: A Template Selection Approach

Electrocardiography (ECG) biometrics is emerging as a viable biometric trait. Recent developments at the sensor level have shown the feasibility of performing signal acquisition at the fingers and hand palms, using one-lead sensor technology and dry electrodes. These new locations lead to ECG signals with lower signal to noise ratio and more prone to noise artifacts; the heart rate variability is another of the major challenges of this biometric trait. In this paper we propose a novel approach to ECG biometrics, with the purpose of reducing the computational complexity and increasing the robustness of the recognition process enabling the fusion of information across sessions. Our approach is based on clustering, grouping individual heartbeats based on their morphology. We study several methods to perform automatic template selection and account for variations observed in a person's biometric data. This approach allows the identification of different template groupings, taking into account the heart rate variability, and the removal of outliers due to noise artifacts. Experimental evaluation on real world data demonstrates the advantages of our approach.

Enhancing Multimodal Silent Speech Interfaces With Feature Selection

In research on Silent Speech Interfaces (SSI), different sources of information (modalities) have been combined, aiming at obtaining better performance than the individual modalities. However, when combining these modalities, the dimensionality of the feature space rapidly increases, yielding the well-known "curse of dimensionality". As a consequence, in order to extract useful information from this data, one has to resort to feature selection (FS) techniques to lower the dimensionality of the learning space. In this paper, we assess the impact of FS techniques for silent speech data, in a dataset with 4 non-invasive and promising modalities, namely: video, depth, ultrasonic Doppler sensing, and surface electromyography. We consider two supervised (mutual information and Fisher's ratio) and two unsupervised (meanmedian and arithmetic mean geometric mean) FS filters. The evaluation was made by assessing the classification accuracy (word recognition error) of three well-known classifiers (knearest neighbors, support vector machines, and dynamic time warping). The key results of this study show that both unsupervised and supervised FS techniques improve on the classification accuracy on both individual and combined modalities. For instance, on the video component, we attain relative performance gains of 36.2% in error rates. FS is also useful as pre-processing for feature fusion. Copyright © 2014 ISCA.

Dinuclear Mn (II,II) complexes: magnetic properties and microwave assisted oxidation of alcohols

A series of six new mixed-ligand dinuclear Mn(II, II) complexes of three different hydrazone Schiff bases (H3L1, H3L2 and H3L3), derived from condensation of the aromatic acid hydrazides benzohydrazide, 2-aminobenzohydrazide or 2-hydroxybenzohydrazide, with 2,3-dihydroxy benzaldehyde, respectively, is reported. Reactions of Mn(NO3)(2) center dot 4H(2)O with the H3L1-3 compounds, in the presence of pyridine (1 : 1 : 1 mole ratio), in methanol at room temperature, yield [Mn(H2L1)(py)(H2O)](2)(NO3)(2) center dot 2H(2)O (1 center dot 2H(2)O), [Mn(H2L2)(py)(CH3OH)](2)(NO3)(2) center dot 4H(2)O (2 center dot 4H(2)O) and [Mn(H2L3)(py)(H2O)](2)(NO3)(2) (3) respectively, whereas the use of excess pyridine yields complexes with two axially coordinated pyridine molecules at each Mn(II) centre, viz. [Mn(H2L1)(py)(2)] 2(NO3)(2) center dot H2O (4 center dot H2O), [Mn(H2L2)(py) H-O (6 center dot 2CH(3)OH), respectively. In all the complexes, the (H2L1-3)-ligand coordinates in the keto form. Complexes 1 center dot 2H(2)O, 2 center dot 4H(2)O, 4 center dot H2O, 5 center dot 2H(2)O and 6 center dot 2CH(3)OH are characterized by single crystal X-ray diffraction analysis. The complexes 1, 2 and 6, having different coordination environments, have been selected for variable temperature magnetic susceptibility measurements to examine the nature of magnetic interaction between magnetically coupled Mn(II) centres and also for exploration of the catalytic activity towards microwave assisted oxidation of alcohols. A yield of 81% (acetophenone) is obtained using a maximum of 0.4% molar ratio of catalyst relative to the substrate in the presence of TEMPO and in aqueous basic solution, under mild conditions.

Microwave-assisted and solvent-free peroxidative oxidation of 1-phenylethanol to acetophenone with a CuII-TEMPO catalytic system

The water-soluble copper(II) complex [Cu(H2R)(HL)]center dot H2O (1) was prepared by reaction of copper(II) nitrate hydrate with (E)-2-(((1-hydroxynaphthalen-2-yl)methylene)amino) benzenesulfonic acid (H2L) and diethanolamine (H3R). It was characterized by IR and ESI-MS spectroscopies, elemental and X-ray crystal structural analyses. 1 shows a high catalytic activity for the solvent-free microwave (MW) assisted oxidation of 1-phenylethanol with tert-butylhydroperoxide, leading, in the presence of TEMPO, to yields up to 85% (TON = 850) in a remarkably short reaction time (15 min, with the corresponding TOE value of 3.40 x 10(3) h(-1)) under low power (25W) MW irradiation. Crown Copyright (C) 2014 Published by Elsevier B.V. All rights reserved.

InOx thin films deposited by plasma assisted evaporation: application in light shutters

An integration of undoped InOx and commercial ITO thin films into laboratory assembled light shutter devices is made. Accordingly, undoped transparent conductive InOx thin films, about 100 nm thick, are deposited by radiofrequency plasma enhanced reactive thermal evaporation (rf-PERTE) of indium teardrops with no intentional heating of the glass substrates. The process of deposition occurs at very low deposition rates (0.1-0.3 nm/s) to establish an optimized reaction between the oxygen plasma and the metal vapor. These films show the following main characteristics: transparency of 87% (wavelength, lambda = 632.8 nm) and sheet resistance of 52 Omega/sq; while on commercial ITO films the transparency was of 92% and sheet resistance of 83 Omega/sq. The InOx thin film surface characterized by AFM shows a uniform grain texture with a root mean square surface roughness of Rq similar to 2.276 nm. In contrast, commercial ITO topography is characterized by two regions: one smoother with Rq similar to 0.973 nm and one with big grains (Rq similar to 3.617 nm). For the shutters assembled using commercial ITO, the light transmission coefficient (Tr) reaches the highest value (Tr-max) of 89% and the lowest (Tr-min) of 1.3% [13], while for the InOx shutters these values are 80.1% and 3.2%, respectively. Regarding the electric field required to achieve 90% of the maximum transmission in the ON state (E-on), the one presented by the devices assembled with commercial ITO coated glasses is 2.41 V/mu m while the one presented by the devices assembled with InOx coated glasses is smaller, 1.77 V/mu m. These results corroborate the device quality that depends on the base materials and fabrication process used. (C) 2014 Elsevier Ltd. All rights reserved.

Enhancing the selection of a model-based clustering with external categorical variables

In cluster analysis, it can be useful to interpret the partition built from the data in the light of external categorical variables which are not directly involved to cluster the data. An approach is proposed in the model-based clustering context to select a number of clusters which both fits the data well and takes advantage of the potential illustrative ability of the external variables. This approach makes use of the integrated joint likelihood of the data and the partitions at hand, namely the model-based partition and the partitions associated to the external variables. It is noteworthy that each mixture model is fitted by the maximum likelihood methodology to the data, excluding the external variables which are used to select a relevant mixture model only. Numerical experiments illustrate the promising behaviour of the derived criterion. © 2014 Springer-Verlag Berlin Heidelberg.

An unsupervised approach to feature discretization and selection

Many learning problems require handling high dimensional datasets with a relatively small number of instances. Learning algorithms are thus confronted with the curse of dimensionality, and need to address it in order to be effective. Examples of these types of data include the bag-of-words representation in text classification problems and gene expression data for tumor detection/classification. Usually, among the high number of features characterizing the instances, many may be irrelevant (or even detrimental) for the learning tasks. It is thus clear that there is a need for adequate techniques for feature representation, reduction, and selection, to improve both the classification accuracy and the memory requirements. In this paper, we propose combined unsupervised feature discretization and feature selection techniques, suitable for medium and high-dimensional datasets. The experimental results on several standard datasets, with both sparse and dense features, show the efficiency of the proposed techniques as well as improvements over previous related techniques.