Solvent-Resistant Polymeric Sensors for Adulteration Detection in Liquid Fuels

Polymeric sensors with improved resistance to organic solvents were produced via the layer-by-layer thin film deposition followed by chemical cross-linking. According to UV-vis spectroscopy, the mass loss of polyaniline/poly(vinyl alcohol) and polyaniline/novolac-type resin based films deposited onto glass slides was less than 20% when they were submitted to successive immersions (up to 3,000 immersion cycles) into commercially available ethanol and gasoline fuel samples. Polyallylamine hydrochloride/nickel tetrasulfonated phthalocyanine films presented similar stability. The electrical responses assessed by impedance spectroscopy of films deposited onto Au-interdigitated microelectrodes were relatively unaffected after continuous or cyclic immersions into both fuels. After these studies, an array including these polymeric sensors was employed to detect adulteration in ethanol and gasoline samples. After principal component analysis, it was possible to conclude that the proposed sensor array is capable to discriminate with remarkable reproducibility ethanol samples containing different amounts of water or else gasoline samples containing different amounts of ethanol. In both examples, more than 90% of data variance was retained in the first principal component. For each type of sample, ethanol and gasoline, it was found a linear correlation between one of the principal components and the sample's composition. These findings allow one to conclude that these films present great potential for the development of reliable and low-cost sensors for fuel analysis in liquid phase.

Conductive polymer gas sensor for quantitative detection of methanol in Brazilian sugar-cane spirit

A low-cost chemiresistive gas sensor is described, made by the deposition of a thin film of a conductive polymer, poly(2-dodecanoylsulfanyl-p-phenylenevinylene), doped with dodecylbenzenesulfonic acid (10%, w/w), onto interdigitated electrodes. The sensor exhibits linear electrical conductance changes in function of the concentration of methanol present in sugar-cane spirit in the range between 0.05% and 4.0%. Since the sensor is cheap, easy to fabricate, durable, presents low power consumption, and is not sensitive to ethanol, acetic acid or water, it can be used in portable equipments for monitoring methanol levels in distilled alcoholic beverages such as Brazilian sugar-cane spirit (cachaca). (C) 2011 Elsevier Ltd. All rights reserved.

Detection of glucose and triglycerides using information visualization methods to process impedance spectroscopy data

In this paper we discuss the detection of glucose and triglycerides using information visualization methods to process impedance spectroscopy data. The sensing units contained either lipase or glucose oxidase immobilized in layer-by-layer (LbL) films deposited onto interdigitated electrodes. The optimization consisted in identifying which part of the electrical response and combination of sensing units yielded the best distinguishing ability. It is shown that complete separation can be obtained for a range of concentrations of glucose and triglyceride when the interactive document map (IDMAP) technique is used to project the data into a two-dimensional plot. Most importantly, the optimization procedure can be extended to other types of biosensors, thus increasing the versatility of analysis provided by tailored molecular architectures exploited with various detection principles. (C) 2012 Elsevier B.V. All rights reserved.

Bagging k-dependence probabilistic networks: An alternative powerful fraud detection tool

Fraud is a global problem that has required more attention due to an accentuated expansion of modern technology and communication. When statistical techniques are used to detect fraud, whether a fraud detection model is accurate enough in order to provide correct classification of the case as a fraudulent or legitimate is a critical factor. In this context, the concept of bootstrap aggregating (bagging) arises. The basic idea is to generate multiple classifiers by obtaining the predicted values from the adjusted models to several replicated datasets and then combining them into a single predictive classification in order to improve the classification accuracy. In this paper, for the first time, we aim to present a pioneer study of the performance of the discrete and continuous k-dependence probabilistic networks within the context of bagging predictors classification. Via a large simulation study and various real datasets, we discovered that the probabilistic networks are a strong modeling option with high predictive capacity and with a high increment using the bagging procedure when compared to traditional techniques. (C) 2012 Elsevier Ltd. All rights reserved.

In situ real-time investigation of Organic Ultra-Thin-Film transistors: growth, electrical properties and biosensing applications

Organic electronics has grown enormously during the last decades driven by the encouraging results and the potentiality of these materials for allowing innovative applications, such as flexible-large-area displays, low-cost printable circuits, plastic solar cells and lab-on-a-chip devices. Moreover, their possible field of applications reaches from medicine, biotechnology, process control and environmental monitoring to defense and security requirements. However, a large number of questions regarding the mechanism of device operation remain unanswered. Along the most significant is the charge carrier transport in organic semiconductors, which is not yet well understood. Other example is the correlation between the morphology and the electrical response. Even if it is recognized that growth mode plays a crucial role into the performance of devices, it has not been exhaustively investigated. The main goal of this thesis was the finding of a correlation between growth modes, electrical properties and morphology in organic thin-film transistors (OTFTs). In order to study the thickness dependence of electrical performance in organic ultra-thin-film transistors, we have designed and developed a home-built experimental setup for performing real-time electrical monitoring and post-growth in situ electrical characterization techniques. We have grown pentacene TFTs under high vacuum conditions, varying systematically the deposition rate at a fixed room temperature. The drain source current IDS and the gate source current IGS were monitored in real-time; while a complete post-growth in situ electrical characterization was carried out. At the end, an ex situ morphological investigation was performed by using the atomic force microscope (AFM). In this work, we present the correlation for pentacene TFTs between growth conditions, Debye length and morphology (through the correlation length parameter). We have demonstrated that there is a layered charge carriers distribution, which is strongly dependent of the growth mode (i.e. rate deposition for a fixed temperature), leading to a variation of the conduction channel from 2 to 7 monolayers (MLs). We conciliate earlier reported results that were apparently contradictory. Our results made evident the necessity of reconsidering the concept of Debye length in a layered low-dimensional device. Additionally, we introduce by the first time a breakthrough technique. This technique makes evident the percolation of the first MLs on pentacene TFTs by monitoring the IGS in real-time, correlating morphological phenomena with the device electrical response. The present thesis is organized in the following five chapters. Chapter 1 makes an introduction to the organic electronics, illustrating the operation principle of TFTs. Chapter 2 presents the organic growth from theoretical and experimental points of view. The second part of this chapter presents the electrical characterization of OTFTs and the typical performance of pentacene devices is shown. In addition, we introduce a correcting technique for the reconstruction of measurements hampered by leakage current. In chapter 3, we describe in details the design and operation of our innovative home-built experimental setup for performing real-time and in situ electrical measurements. Some preliminary results and the breakthrough technique for correlating morphological and electrical changes are presented. Chapter 4 meets the most important results obtained in real-time and in situ conditions, which correlate growth conditions, electrical properties and morphology of pentacene TFTs. In chapter 5 we describe applicative experiments where the electrical performance of pentacene TFTs has been investigated in ambient conditions, in contact to water or aqueous solutions and, finally, in the detection of DNA concentration as label-free sensor, within the biosensing framework.

Localized potentials in electrical impedance tomography

In this work we study localized electric potentials that have an arbitrarily high energy on some given subset of a domain and low energy on another. We show that such potentials exist for general L-infinity-conductivities (with positive infima) in almost arbitrarily shaped subregions of a domain, as long as these regions are connected to the boundary and a unique continuation principle is satisfied. From this we deduce a simple, but new, theoretical identifiability result for the famous Calderon problem with partial data. We also show how to construct such potentials numerically and use a connection with the factorization method to derive a new non-iterative algorithm for the detection of inclusions in electrical impedance tomography.

In-situ detection of defect formation in organic flexible electronics by Kelvin Probe Force Microscopy

Organic semiconductor technology has attracted considerable research interest in view of its great promise for large area, lightweight, and flexible electronics applications. Owing to their advantages in processing and unique physical properties, organic semiconductors can bring exciting new opportunities for broad-impact applications requiring large area coverage, mechanical flexibility, low-temperature processing, and low cost. In order to achieve highly flexible device architecture it is crucial to understand on a microscopic scale how mechanical deformation affects the electrical performance of organic thin film devices. Towards this aim, I established in this thesis the experimental technique of Kelvin Probe Force Microscopy (KPFM) as a tool to investigate the morphology and the surface potential of organic semiconducting thin films under mechanical strain. KPFM has been employed to investigate the strain response of two different Organic Thin Film Transistor with active layer made by 6,13-bis(triisopropylsilylethynyl)-pentacene (TIPS-Pentacene), and Poly(3-hexylthiophene-2,5-diyl) (P3HT). The results show that this technique allows to investigate on a microscopic scale failure of flexible TFT with this kind of materials during bending. I find that the abrupt reduction of TIPS-pentacene device performance at critical bending radii is related to the formation of nano-cracks in the microcrystal morphology, easily identified due to the abrupt variation in surface potential caused by local increase in resistance. Numerical simulation of the bending mechanics of the transistor structure further identifies the mechanical strain exerted on the TIPS-pentacene micro-crystals as the fundamental origin of fracture. Instead for P3HT based transistors no significant reduction in electrical performance is observed during bending. This finding is attributed to the amorphous nature of the polymer giving rise to an elastic response without the occurrence of crack formation.

The effect of brief electrical and manual acupuncture stimulation on mechanical experimental pain

Although manual and electrical stimulation are frequently used in acupuncture analgesia, studies comparing both stimulation modalities are contradictory. This blinded, placebo-controlled cross-over study investigates effects of brief manual and electrical acupuncture stimulation on pressure pain detection thresholds (PPDT) compared with nonpenetrating sham acupuncture (NPSA).

On a Microcomputer Implementation of an Intrusion-detection Algorithm

The main objective of this paper is to discuss various aspects of implementing a specific intrusion-detection scheme on a micro-computer system using fixed-point arithmetic. The proposed scheme is suitable for detecting intruder stimuli which are in the form of transient signals. It consists of two stages: an adaptive digital predictor and an adaptive threshold detection algorithm. Experimental results involving data acquired via field experiments are also included.

Application and comparison of classification algorithms for recognition of Alzheimer's disease in electrical brain activity (EEG)

The early detection of subjects with probable Alzheimer's disease (AD) is crucial for effective appliance of treatment strategies. Here we explored the ability of a multitude of linear and non-linear classification algorithms to discriminate between the electroencephalograms (EEGs) of patients with varying degree of AD and their age-matched control subjects. Absolute and relative spectral power, distribution of spectral power, and measures of spatial synchronization were calculated from recordings of resting eyes-closed continuous EEGs of 45 healthy controls, 116 patients with mild AD and 81 patients with moderate AD, recruited in two different centers (Stockholm, New York). The applied classification algorithms were: principal component linear discriminant analysis (PC LDA), partial least squares LDA (PLS LDA), principal component logistic regression (PC LR), partial least squares logistic regression (PLS LR), bagging, random forest, support vector machines (SVM) and feed-forward neural network. Based on 10-fold cross-validation runs it could be demonstrated that even tough modern computer-intensive classification algorithms such as random forests, SVM and neural networks show a slight superiority, more classical classification algorithms performed nearly equally well. Using random forests classification a considerable sensitivity of up to 85% and a specificity of 78%, respectively for the test of even only mild AD patients has been reached, whereas for the comparison of moderate AD vs. controls, using SVM and neural networks, values of 89% and 88% for sensitivity and specificity were achieved. Such a remarkable performance proves the value of these classification algorithms for clinical diagnostics.

Detection of complex point targets with distributed assets in a MIMO radar system

The report explores the problem of detecting complex point target models in a MIMO radar system. A complex point target is a mathematical and statistical model for a radar target that is not resolved in space, but exhibits varying complex reflectivity across the different bistatic view angles. The complex reflectivity can be modeled as a complex stochastic process whose index set is the set of all the bistatic view angles, and the parameters of the stochastic process follow from an analysis of a target model comprising a number of ideal point scatterers randomly located within some radius of the targets center of mass. The proposed complex point targets may be applicable to statistical inference in multistatic or MIMO radar system. Six different target models are summarized here – three 2-dimensional (Gaussian, Uniform Square, and Uniform Circle) and three 3-dimensional (Gaussian, Uniform Cube, and Uniform Sphere). They are assumed to have different distributions on the location of the point scatterers within the target. We develop data models for the received signals from such targets in the MIMO radar system with distributed assets and partially correlated signals, and consider the resulting detection problem which reduces to the familiar Gauss-Gauss detection problem. We illustrate that the target parameter and transmit signal have an influence on the detector performance through target extent and the SNR respectively. A series of the receiver operator characteristic (ROC) curves are generated to notice the impact on the detector for varying SNR. Kullback–Leibler (KL) divergence is applied to obtain the approximate mean difference between density functions the scatterers assume inside the target models to show the change in the performance of the detector with target extent of the point scatterers.

CHARACTERIZATION OF ELECTRODEPOSITED POLYANILINE BIOSENSOR PLATFORM FOR ESCHERICHIA COLI O157:H7 DETECTION

Amperometric electrodeposition has been used to obtain uniform, conductive, and repeatable polyaniline (PANi) thin films for use in nano scaled biochemical sensors. This report describes the characterization of these films. Techniques such as ellipsometry were used to test repeatability of the deposition and the uniformity of the deposited thin films. Raman spectroscopy was utilized to confirm the composition of the deposited PANi thin films. Fluorescence microscopy was used to determine the immobilization of antibodies to the PANi thin films using biotin-avidin interactions, as well as the density of active binding sites. Ellipsometry results demonstrated that biomolecules could be immobilized on PANi films as thin as 9nm. Evidence from the Raman spectroscopy demonstrated the conductive nature of the PANi films. The fluorescence microscopy demonstrated that antibodies could be immobilized on PANi films, although the experiment also demonstrated a low density of binding sites. The characterization demonstrates the utility of the PANi thin films as a conductive interface between the inorganic sensor platform and biochemical molecules.

OUT-OF-STEP DETECTION BASED ON ZUBOV’S APPROXIMATION BOUNDARY METHOD

Disturbances in power systems may lead to electromagnetic transient oscillations due to mismatch of mechanical input power and electrical output power. Out-of-step conditions in power system are common after the disturbances where the continuous oscillations do not damp out and the system becomes unstable. Existing out-of-step detection methods are system specific as extensive off-line studies are required for setting of relays. Most of the existing algorithms also require network reduction techniques to apply in multi-machine power systems. To overcome these issues, this research applies Phasor Measurement Unit (PMU) data and Zubov’s approximation stability boundary method, which is a modification of Lyapunov’s direct method, to develop a novel out-of-step detection algorithm. The proposed out-of-step detection algorithm is tested in a Single Machine Infinite Bus system, IEEE 3-machine 9-bus, and IEEE 10-machine 39-bus systems. Simulation results show that the proposed algorithm is capable of detecting out-of-step conditions in multi-machine power systems without using network reduction techniques and a comparative study with an existing blinder method demonstrate that the decision times are faster. The simulation case studies also demonstrate that the proposed algorithm does not depend on power system parameters, hence it avoids the need of extensive off-line system studies as needed in other algorithms.

Novel lesion detection aids

Several non-invasive and novel aids for the detection of (and in some cases monitoring of) caries lesions have been introduced in the field of 'caries diagnostics' over the last 15 years. This chapter focusses on those available to dentists at the time of writing; continuing research is bound to lead to further developments in the coming years. Laser fluorescence is based on measurements of back-scattered fluorescence of a 655-nm light source. It enhances occlusal and (potentially) approximal lesion detection and enables semi-quantitative caries monitoring. Systematic reviews have identified false-positive results as a limitation. Quantitative light-induced fluorescence is another sensitive method to quantitatively detect and measure mineral loss both in enamel and some dentine lesions; again, the trade-offs with lower specificity when compared with clinical visual detection must be considered. Subtraction radiography is based on the principle of digitally superimposing two radiographs with exactly the same projection geometry. This method is applicable for approximal surfaces and occlusal caries involving dentine but is not yet widely available. Electrical caries measurements gather either site-specific or surface-specific information of teeth and tooth structure. Fixed-frequency devices perform best for occlusal dentine caries but the method has also shown promise for lesions in enamel and other tooth surfaces with multi-frequency approaches. All methods require further research and further validation in well-designed clinical trials. In the future, they could have useful applications in clinical practice as part of a personalized, comprehensive caries management system.