Drift compensation of gas sensor array data by Orthogonal Signal Correction

Drift is an important issue that impairs the reliability of gas sensing systems. Sensor aging, memory effects and environmental disturbances produce shifts in sensor responses that make initial statistical models for gas or odor recognition useless after a relatively short period (typically few weeks). Frequent recalibrations are needed to preserve system accuracy. However, when recalibrations involve numerous samples they become expensive and laborious. An interesting and lower cost alternative is drift counteraction by signal processing techniques. Orthogonal Signal Correction (OSC) is proposed for drift compensation in chemical sensor arrays. The performance of OSC is also compared with Component Correction (CC). A simple classification algorithm has been employed for assessing the performance of the algorithms on a dataset composed by measurements of three analytes using an array of seventeen conductive polymer gas sensors over a ten month period.

Drift compensation of gas sensor array data by common principal component analysis

A new drift compensation method based on Common Principal Component Analysis (CPCA) is proposed. The drift variance in data is found as the principal components computed by CPCA. This method finds components that are common for all gasses in feature space. The method is compared in classification task with respect to the other approaches published where the drift direction is estimated through a Principal Component Analysis (PCA) of a reference gas. The proposed new method ¿ employing no specific reference gas, but information from all gases ¿has shown the same performance as the traditional approach with the best-fitted reference gas. Results are shown with data lasting 7-months including three gases at different concentrations for an array of 17 polymeric sensors.

Fuzzy logic applied to the modeling of water dynamics in an Oxisol in northeastern Brazil

Modeling of water movement in non-saturated soil usually requires a large number of parameters and variables, such as initial soil water content, saturated water content and saturated hydraulic conductivity, which can be assessed relatively easily. Dimensional flow of water in the soil is usually modeled by a nonlinear partial differential equation, known as the Richards equation. Since this equation cannot be solved analytically in certain cases, one way to approach its solution is by numerical algorithms. The success of numerical models in describing the dynamics of water in the soil is closely related to the accuracy with which the water-physical parameters are determined. That has been a big challenge in the use of numerical models because these parameters are generally difficult to determine since they present great spatial variability in the soil. Therefore, it is necessary to develop and use methods that properly incorporate the uncertainties inherent to water displacement in soils. In this paper, a model based on fuzzy logic is used as an alternative to describe water flow in the vadose zone. This fuzzy model was developed to simulate the displacement of water in a non-vegetated crop soil during the period called the emergency phase. The principle of this model consists of a Mamdani fuzzy rule-based system in which the rules are based on the moisture content of adjacent soil layers. The performances of the results modeled by the fuzzy system were evaluated by the evolution of moisture profiles over time as compared to those obtained in the field. The results obtained through use of the fuzzy model provided satisfactory reproduction of soil moisture profiles.

Threading dislocation lines in two-sided flux-array decorations

Two-sided flux decoration experiments indicate that threading dislocation lines (TDLs), which cross the entire film, are sometimes trapped in metastable states. We calculate the elastic energy associated with the meanderings of a TDL. The TDL behaves as an anisotropic and dispersive string with thermal fluctuations largely along its Burgers vector. These fluctuations also modify the structure factor of the vortex solid. Both effects can, in principle, be used to estimate the elastic moduli of the material.

3D dose reconstruction for narrow beams using ion chamber array measurements.

3D dose reconstruction is a verification of the delivered absorbed dose. Our aim was to describe and evaluate a 3D dose reconstruction method applied to phantoms in the context of narrow beams. A solid water phantom and a phantom containing a bone-equivalent material were irradiated on a 6 MV linac. The transmitted dose was measured by using one array of a 2D ion chamber detector. The dose reconstruction was obtained by an iterative algorithm. A phantom set-up error and organ interfraction motion were simulated to test the algorithm sensitivity. In all configurations convergence was obtained within three iterations. A local reconstructed dose agreement of at least 3% / 3mm with respect to the planned dose was obtained, except in a few points of the penumbra. The reconstructed primary fluences were consistent with the planned ones, which validates the whole reconstruction process. The results validate our method in a simple geometry and for narrow beams. The method is sensitive to a set-up error of a heterogeneous phantom and interfraction heterogeneous organ motion.

Investigation of high-resolution functional magnetic resonance imaging by means of surface and array radiofrequency coils at 7 T.

In this investigation, high-resolution, 1x1x1-mm(3) functional magnetic resonance imaging (fMRI) at 7 T is performed using a multichannel array head coil and a surface coil approach. Scan geometry was optimized for each coil separately to exploit the strengths of both coils. Acquisitions with the surface coil focused on partial brain coverage, while whole-brain coverage fMRI experiments were performed with the array head coil. BOLD sensitivity in the occipital lobe was found to be higher with the surface coil than with the head array, suggesting that restriction of signal detection to the area of interest may be beneficial for localized activation studies. Performing independent component analysis (ICA) decomposition of the fMRI data, we consistently detected BOLD signal changes and resting state networks. In the surface coil data, a small negative BOLD response could be detected in these resting state network areas. Also in the data acquired with the surface coil, two distinct components of the positive BOLD signal were consistently observed. These two components were tentatively assigned to tissue and venous signal changes.

Fuzzy logic algorithm to extract specific interaction forces from atomic force microscopy data

The atomic force microscope is not only a very convenient tool for studying the topography of different samples, but it can also be used to measure specific binding forces between molecules. For this purpose, one type of molecule is attached to the tip and the other one to the substrate. Approaching the tip to the substrate allows the molecules to bind together. Retracting the tip breaks the newly formed bond. The rupture of a specific bond appears in the force-distance curves as a spike from which the binding force can be deduced. In this article we present an algorithm to automatically process force-distance curves in order to obtain bond strength histograms. The algorithm is based on a fuzzy logic approach that permits an evaluation of "quality" for every event and makes the detection procedure much faster compared to a manual selection. In this article, the software has been applied to measure the binding strength between tubuline and microtubuline associated proteins.

Multiway Array Decomposition Analysis of EEGs in Alzheimer’s Disease

Methods for the extraction of features from physiological datasets are growing needs as clinical investigations of Alzheimer’s disease (AD) in large and heterogeneous population increase. General tools allowing diagnostic regardless of recording sites, such as different hospitals, are essential and if combined to inexpensive non-invasive methods could critically improve mass screening of subjects with AD. In this study, we applied three state of the art multiway array decomposition (MAD) methods to extract features from electroencephalograms (EEGs) of AD patients obtained from multiple sites. In comparison to MAD, spectral-spatial average filter (SSFs) of control and AD subjects were used as well as a common blind source separation method, algorithm for multiple unknown signal extraction (AMUSE). We trained a feed-forward multilayer perceptron (MLP) to validate and optimize AD classification from two independent databases. Using a third EEG dataset, we demonstrated that features extracted from MAD outperformed features obtained from SSFs AMUSE in terms of root mean squared error (RMSE) and reaching up to 100% of accuracy in test condition. We propose that MAD maybe a useful tool to extract features for AD diagnosis offering great generalization across multi-site databases and opening doors to the discovery of new characterization of the disease.

Implantació d'un sistema SCADA en una cèl·lula flexible de fabricació

La Universitat de Vic disposa, entre altres equips, d’una cèl·lula flexible de fabricació, del fabricant Festo, que simula un procés de formació de palets amb els productes que es disposen en un magatzem intermedi. Aquesta cèl·lula està composta de quatre estacions de muntatge diferenciades (càrrega de palets, càrrega de plaques, magatzem intermedi i transport). Cada una disposa d'un PLC SIEMENS S7-300 per la seva automatització, i tots aquests es troben interconnectats amb una xarxa industrial Profibus. L'objectiu d'aquest projecte és implantar el sistema SCADA Vijeo Citect pel control i supervisió de l'estació magatzem d'aquesta cèl·lula flexible de fabricació, establint també un intercanvi de dades entre l'SCADA i el Microsoft Access, per poder ser utilitzat per la docència. Aquest projecte s'ha desenvolupat en cinc fases diferents: 1. La primera fase s'ha dedicat a l'automatització pròpiament de l'estació magatzem a partir de l'autòmat programable Siemens S7-300 i complint amb les necessitats plantejades. 2. En la segona fase s'ha programat i establert la comunicació per l'intercanvi de dades (lectura i escriptura) entre el sistema SCADA Vijeo Citect i la base de dades de Microsoft Access. 3. En la tercera fase s'ha elaborat i programat l'entorn gràfic de supervisió i control del procés a partir del sistema SCADA Vijeo Citect. 4. En la quarta fase s'ha instal·lat un OPC Server en el PC i s'ha establert la comunicació entre el PLC i el sistema SCADA. 5. Finalment s'ha anat revisant i depurant les diferents programacions i comunicacions per tal de que el sistema funcioni com a un conjunt.

Efficient targeted transcript discovery via array-based normalization of RACE libraries.

Rapid amplification of cDNA ends (RACE) is a widely used approach for transcript identification. Random clone selection from the RACE mixture, however, is an ineffective sampling strategy if the dynamic range of transcript abundances is large. To improve sampling efficiency of human transcripts, we hybridized the products of the RACE reaction onto tiling arrays and used the detected exons to delineate a series of reverse-transcriptase (RT)-PCRs, through which the original RACE transcript population was segregated into simpler transcript populations. We independently cloned the products and sequenced randomly selected clones. This approach, RACEarray, is superior to direct cloning and sequencing of RACE products because it specifically targets new transcripts and often results in overall normalization of transcript abundance. We show theoretically and experimentally that this strategy leads indeed to efficient sampling of new transcripts, and we investigated multiplexing the strategy by pooling RACE reactions from multiple interrogated loci before hybridization.

A Classification of Tools for Learning Logic

A table showing a comparison and classification of tools (intelligent tutoring systems) for e-learning of Logic at a college level.

Subtelomeric 6p deletion: clinical and array-CGH characterization in two patients

We report on two patients with de novo subtelomeric terminal deletion of chromosome 6p. Patient 1 is an 8-month-old female born with normal growth parameters, typical facial features of 6pter deletion, bilateral corectopia, and protruding tongue. She has severe developmental delay, profound bilateral neurosensory deafness, poor visual contact, and hypsarrhythmia since the age of 6 months. Patient 2 is a 5-year-old male born with normal growth parameters and unilateral hip dysplasia; he has a characteristic facial phenotype, bilateral embryotoxon, and moderate mental retardation. Further characterization of the deletion, using high-resolution array comparative genomic hybridization (array-CGH; Agilent Human Genome kit 244 K), revealed that Patient 1 has a 8.1 Mb 6pter-6p24.3 deletion associated with a contiguous 5.8 Mb 6p24.3-6p24.1 duplication and Patient 2 a 5.7 Mb 6pter-6p25.1 deletion partially overlapping with that of Patient 1. Complementary FISH and array analysis showed that the inv del dup(6) in Patient 1 originated de novo. Our results demonstrate that simple rearrangements are often more complex than defined by standard techniques. We also discuss genotype-phenotype correlations including previously reported cases of deletion 6p.