988 resultados para Capacitively coupled contactless conductivity detection


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Los sensores inerciales (acelerómetros y giróscopos) se han ido introduciendo poco a poco en dispositivos que usamos en nuestra vida diaria gracias a su minituarización. Hoy en día todos los smartphones contienen como mínimo un acelerómetro y un magnetómetro, siendo complementados en losmás modernos por giróscopos y barómetros. Esto, unido a la proliferación de los smartphones ha hecho viable el diseño de sistemas basados en las medidas de sensores que el usuario lleva colocados en alguna parte del cuerpo (que en un futuro estarán contenidos en tejidos inteligentes) o los integrados en su móvil. El papel de estos sensores se ha convertido en fundamental para el desarrollo de aplicaciones contextuales y de inteligencia ambiental. Algunos ejemplos son el control de los ejercicios de rehabilitación o la oferta de información referente al sitio turístico que se está visitando. El trabajo de esta tesis contribuye a explorar las posibilidades que ofrecen los sensores inerciales para el apoyo a la detección de actividad y la mejora de la precisión de servicios de localización para peatones. En lo referente al reconocimiento de la actividad que desarrolla un usuario, se ha explorado el uso de los sensores integrados en los dispositivos móviles de última generación (luz y proximidad, acelerómetro, giróscopo y magnetómetro). Las actividades objetivo son conocidas como ‘atómicas’ (andar a distintas velocidades, estar de pie, correr, estar sentado), esto es, actividades que constituyen unidades de actividades más complejas como pueden ser lavar los platos o ir al trabajo. De este modo, se usan algoritmos de clasificación sencillos que puedan ser integrados en un móvil como el Naïve Bayes, Tablas y Árboles de Decisión. Además, se pretende igualmente detectar la posición en la que el usuario lleva el móvil, no sólo con el objetivo de utilizar esa información para elegir un clasificador entrenado sólo con datos recogidos en la posición correspondiente (estrategia que mejora los resultados de estimación de la actividad), sino también para la generación de un evento que puede producir la ejecución de una acción. Finalmente, el trabajo incluye un análisis de las prestaciones de la clasificación variando el tipo de parámetros y el número de sensores usados y teniendo en cuenta no sólo la precisión de la clasificación sino también la carga computacional. Por otra parte, se ha propuesto un algoritmo basado en la cuenta de pasos utilizando informaiii ción proveniente de un acelerómetro colocado en el pie del usuario. El objetivo final es detectar la actividad que el usuario está haciendo junto con la estimación aproximada de la distancia recorrida. El algoritmo de cuenta pasos se basa en la detección de máximos y mínimos usando ventanas temporales y umbrales sin requerir información específica del usuario. El ámbito de seguimiento de peatones en interiores es interesante por la falta de un estándar de localización en este tipo de entornos. Se ha diseñado un filtro extendido de Kalman centralizado y ligeramente acoplado para fusionar la información medida por un acelerómetro colocado en el pie del usuario con medidas de posición. Se han aplicado también diferentes técnicas de corrección de errores como las de velocidad cero que se basan en la detección de los instantes en los que el pie está apoyado en el suelo. Los resultados han sido obtenidos en entornos interiores usando las posiciones estimadas por un sistema de triangulación basado en la medida de la potencia recibida (RSS) y GPS en exteriores. Finalmente, se han implementado algunas aplicaciones que prueban la utilidad del trabajo desarrollado. En primer lugar se ha considerado una aplicación de monitorización de actividad que proporciona al usuario información sobre el nivel de actividad que realiza durante un período de tiempo. El objetivo final es favorecer el cambio de comportamientos sedentarios, consiguiendo hábitos saludables. Se han desarrollado dos versiones de esta aplicación. En el primer caso se ha integrado el algoritmo de cuenta pasos en una plataforma OSGi móvil adquiriendo los datos de un acelerómetro Bluetooth colocado en el pie. En el segundo caso se ha creado la misma aplicación utilizando las implementaciones de los clasificadores en un dispositivo Android. Por otro lado, se ha planteado el diseño de una aplicación para la creación automática de un diario de viaje a partir de la detección de eventos importantes. Esta aplicación toma como entrada la información procedente de la estimación de actividad y de localización además de información almacenada en bases de datos abiertas (fotos, información sobre sitios) e información sobre sensores reales y virtuales (agenda, cámara, etc.) del móvil. Abstract Inertial sensors (accelerometers and gyroscopes) have been gradually embedded in the devices that people use in their daily lives thanks to their miniaturization. Nowadays all smartphones have at least one embedded magnetometer and accelerometer, containing the most upto- date ones gyroscopes and barometers. This issue, together with the fact that the penetration of smartphones is growing steadily, has made possible the design of systems that rely on the information gathered by wearable sensors (in the future contained in smart textiles) or inertial sensors embedded in a smartphone. The role of these sensors has become key to the development of context-aware and ambient intelligent applications. Some examples are the performance of rehabilitation exercises, the provision of information related to the place that the user is visiting or the interaction with objects by gesture recognition. The work of this thesis contributes to explore to which extent this kind of sensors can be useful to support activity recognition and pedestrian tracking, which have been proven to be essential for these applications. Regarding the recognition of the activity that a user performs, the use of sensors embedded in a smartphone (proximity and light sensors, gyroscopes, magnetometers and accelerometers) has been explored. The activities that are detected belong to the group of the ones known as ‘atomic’ activities (e.g. walking at different paces, running, standing), that is, activities or movements that are part of more complex activities such as doing the dishes or commuting. Simple, wellknown classifiers that can run embedded in a smartphone have been tested, such as Naïve Bayes, Decision Tables and Trees. In addition to this, another aim is to estimate the on-body position in which the user is carrying the mobile phone. The objective is not only to choose a classifier that has been trained with the corresponding data in order to enhance the classification but also to start actions. Finally, the performance of the different classifiers is analysed, taking into consideration different features and number of sensors. The computational and memory load of the classifiers is also measured. On the other hand, an algorithm based on step counting has been proposed. The acceleration information is provided by an accelerometer placed on the foot. The aim is to detect the activity that the user is performing together with the estimation of the distance covered. The step counting strategy is based on detecting minima and its corresponding maxima. Although the counting strategy is not innovative (it includes time windows and amplitude thresholds to prevent under or overestimation) no user-specific information is required. The field of pedestrian tracking is crucial due to the lack of a localization standard for this kind of environments. A loosely-coupled centralized Extended Kalman Filter has been proposed to perform the fusion of inertial and position measurements. Zero velocity updates have been applied whenever the foot is detected to be placed on the ground. The results have been obtained in indoor environments using a triangulation algorithm based on RSS measurements and GPS outdoors. Finally, some applications have been designed to test the usefulness of the work. The first one is called the ‘Activity Monitor’ whose aim is to prevent sedentary behaviours and to modify habits to achieve desired objectives of activity level. Two different versions of the application have been implemented. The first one uses the activity estimation based on the step counting algorithm, which has been integrated in an OSGi mobile framework acquiring the data from a Bluetooth accelerometer placed on the foot of the individual. The second one uses activity classifiers embedded in an Android smartphone. On the other hand, the design of a ‘Travel Logbook’ has been planned. The input of this application is the information provided by the activity and localization modules, external databases (e.g. pictures, points of interest, weather) and mobile embedded and virtual sensors (agenda, camera, etc.). The aim is to detect important events in the journey and gather the information necessary to store it as a journal page.

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Background: Analysis of exhaled volatile organic compounds (VOCs) in breath is an emerging approach for cancer diagnosis, but little is known about its potential use as a biomarker for colorectal cancer (CRC). We investigated whether a combination of VOCs could distinct CRC patients from healthy volunteers. Methods: In a pilot study, we prospectively analyzed breath exhalations of 38 CRC patient and 43 healthy controls all scheduled for colonoscopy, older than 50 in the average-risk category. The samples were ionized and analyzed using a Secondary ElectroSpray Ionization (SESI) coupled with a Time-of-Flight Mass Spectrometer (SESI-MS). After a minimum of 2 hours fasting, volunteers deeply exhaled into the system. Each test requires three soft exhalations and takes less than ten minutes. No breath condensate or collection are required and VOCs masses are detected in real time, also allowing for a spirometric profile to be analyzed along with the VOCs. A new sampling system precludes ambient air from entering the system, so background contamination is reduced by an overall factor of ten. Potential confounding variables from the patient or the environment that could interfere with results were analyzed. Results: 255 VOCs, with masses ranging from 30 to 431 Dalton have been identified in the exhaled breath. Using a classification technique based on the ROC curve for each VOC, a set of 9 biomarkers discriminating the presence of CRC from healthy volunteers was obtained, showing an average recognition rate of 81.94%, a sensitivity of 87.04% and specificity of 76.85%. Conclusions: A combination of cualitative and cuantitative analysis of VOCs in the exhaled breath could be a powerful diagnostic tool for average-risk CRC population. These results should be taken with precaution, as many endogenous or exogenous contaminants could interfere as confounding variables. On-line analysis with SESI-MS is less time-consuming and doesn’t need sample preparation. We are recruiting in a new pilot study including breath cleaning procedures and spirometric analysis incorporated into the postprocessing algorithms, to better control for confounding variables.

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The early detection of spoiling metabolic products in contaminated food is a very important tool to control quality. Some volatile compounds produce unpleasant odours at very low concentrations, making their early detection very challenging. This is the case of 1,3-pentadiene produced by microorganisms through decarboxylation of the preservative sorbate. In this work, we have developed a methodology to use the data produced by a low-cost, compact MWIR (Mid-Wave IR) spectrometry device without moving parts, which is based on a linear array of 128 elements of VPD PbSe coupled to a linear variable filter (LVF) working in the spectral range between 3 and 4.6 ?m. This device is able to analyze food headspace gases through dedicated sample presentation setup. This methodology enables the detection of CO2 and the volatile compound 1,3-pentadiene, as compared to synthetic patrons. Data analysis is based on an automated multidimensional dynamic processing of the MWIR spectra. Principal component and discriminant analysis allow segregating between four yeast strains including producers and no producers. The segregation power is accounted as a measure of the discrimination quality.

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The invasive signal amplification reaction has been previously developed for quantitative detection of nucleic acids and discrimination of single-nucleotide polymorphisms. Here we describe a method that couples two invasive reactions into a serial isothermal homogeneous assay using fluorescence resonance energy transfer detection. The serial version of the assay generates more than 107 reporter molecules for each molecule of target DNA in a 4-h reaction; this sensitivity, coupled with the exquisite specificity of the reaction, is sufficient for direct detection of less than 1,000 target molecules with no prior target amplification. Here we present a kinetic analysis of the parameters affecting signal and background generation in the serial invasive signal amplification reaction and describe a simple kinetic model of the assay. We demonstrate the ability of the assay to detect as few as 600 copies of the methylene tetrahydrofolate reductase gene in samples of human genomic DNA. We also demonstrate the ability of the assay to discriminate single base differences in this gene by using 20 ng of human genomic DNA.

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The exchangeability of the substrate water molecules at the catalytic site of water oxidation in photosystem II has been probed by isotope-exchange measurements using mass spectrometric detection of flash-induced oxygen evolution. A stirred sample chamber was constructed to reduce the lag time between injection of H2(18)O and the detecting flash by a factor of more than 1000 compared to the original experiments by R. Radmer and O. Ollinger [(1986) FEBS Lett. 195, 285-289]. Our data show that there is a slow (t1/2 approximately 500 ms, 10 degrees C) and a fast (t1/2 <25 ms, 10 degrees C) exchanging substrate water molecule in the S3 state of photosystem II. The slow exchange is coupled with an activation energy of about 75 kJ/mol and is discussed in terms of a terminal manganese oxo ligand, while the faster exchanging substrate molecule may represent a water molecule not directly bound to the manganese center.

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This work explores the multi-element capabilities of inductively coupled plasma - mass spectrometry with collision/reaction cell technology (CCT-ICP-MS) for the simultaneous determination of both spectrally interfered and non-interfered nuclides in wine samples using a single set of experimental conditions. The influence of the cell gas type (i.e. He, He+H2 and He+NH3), cell gas flow rate and sample pre-treatment (i.e. water dilution or acid digestion) on the background-equivalent concentration (BEC) of several nuclides covering the mass range from 7 to 238 u has been studied. Results obtained in this work show that, operating the collision/reaction cell with a compromise cell gas flow rate (i.e. 4 mL min−1) improves BEC values for interfered nuclides without a significant effect on the BECs for non-interfered nuclides, with the exception of the light elements Li and Be. Among the different cell gas mixtures tested, the use of He or He+H2 is preferred over He+NH3 because NH3 generates new spectral interferences. No significant influence of the sample pre-treatment methodology (i.e. dilution or digestion) on the multi-element capabilities of CCT-ICP-MS in the context of simultaneous analysis of interfered and non-interfered nuclides was observed. Nonetheless, sample dilution should be kept at minimum to ensure that light nuclides (e.g. Li and Be) could be quantified in wine. Finally, a direct 5-fold aqueous dilution is recommended for the simultaneous trace and ultra-trace determination of spectrally interfered and non-interfered elements in wine by means of CCT-ICP-MS. The use of the CCT is mandatory for interference-free ultra-trace determination of Ti and Cr. Only Be could not be determined when using the CCT due to a deteriorated limit of detection when compared to conventional ICP-MS.

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A novel method is reported, whereby screen-printed electrodes (SPELs) are combined with dispersive liquid–liquid microextraction. In-situ ionic liquid (IL) formation was used as an extractant phase in the microextraction technique and proved to be a simple, fast and inexpensive analytical method. This approach uses miniaturized systems both in sample preparation and in the detection stage, helping to develop environmentally friendly analytical methods and portable devices to enable rapid and onsite measurement. The microextraction method is based on a simple metathesis reaction, in which a water-immiscible IL (1-hexyl-3-methylimidazolium bis[(trifluoromethyl)sulfonyl]imide, [Hmim][NTf2]) is formed from a water-miscible IL (1-hexyl-3-methylimidazolium chloride, [Hmim][Cl]) and an ion-exchange reagent (lithium bis[(trifluoromethyl)sulfonyl]imide, LiNTf2) in sample solutions. The explosive 2,4,6-trinitrotoluene (TNT) was used as a model analyte to develop the method. The electrochemical behavior of TNT in [Hmim][NTf2] has been studied in SPELs. The extraction method was first optimized by use of a two-step multivariate optimization strategy, using Plackett–Burman and central composite designs. The method was then evaluated under optimum conditions and a good level of linearity was obtained, with a correlation coefficient of 0.9990. Limits of detection and quantification were 7 μg L−1 and 9 μg L−1, respectively. The repeatability of the proposed method was evaluated at two different spiking levels (20 and 50 μg L−1), and coefficients of variation of 7 % and 5 % (n = 5) were obtained. Tap water and industrial wastewater were selected as real-world water samples to assess the applicability of the method.

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A microwave-based thermal nebulizer (MWTN) has been employed for the first time as on-line preconcentration device in inductively coupled plasma atomic emission spectrometry (ICP-AES). By the appropriate selection of the experimental conditions, the MWTN could be either operated as a conventional thermal nebulizer or as on-line analyte preconcentration and nebulization device. Thus, when operating at microwave power values above 100 W and highly concentrated alcohol solutions, the amount of energy per solvent mass liquid unit (EMR) is high enough to completely evaporate the solvent inside the system and, as a consequence, the analyte is deposited (and then preconcentrated) on the inner walls of the MWTN capillary. When reducing the EMR to the appropriate value (e.g., by reducing the microwave power at a constant sample uptake rate) the retained analyte is swept along by the liquid-gas stream and an analyte-enriched aerosol is generated and next introduced into the plasma cell. Emission signals obtained with the MWTN operating in preconcentration-nebulization mode improved when increasing preconcentration time and sample uptake rate as well as when decreasing the nozzle inner diameter. When running with pure ethanol solution at its optimum experimental conditions, the MWTN in preconcentration-nebulization mode afforded limits of detection up to one order of magnitude lowers than those obtained operating the MWTN exclusively as a nebulizer. To validate the method, the multi-element analysis (i.e. Al, Ca, Cd, Cr, Cu, Fe, K, Mg, Mn, Na, Pb and Zn) of different commercial spirit samples in ICP-AES has been performed. Analyte recoveries for all the elements studied ranged between 93% and 107% and the dynamic linear range covered up to 4 orders of magnitude (i.e. from 0.1 to 1000 μg L−1). In these analysis, both MWTN operating modes afforded similar results. Nevertheless, the preconcentration-nebulization mode permits to determine a higher number of analytes due to its higher detection capabilities.

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A novel approach is presented, whereby gold nanostructured screen-printed carbon electrodes (SPCnAuEs) are combined with in-situ ionic liquid formation dispersive liquid–liquid microextraction (in-situ IL-DLLME) and microvolume back-extraction for the determination of mercury in water samples. In-situ IL-DLLME is based on a simple metathesis reaction between a water-miscible IL and a salt to form a water-immiscible IL into sample solution. Mercury complex with ammonium pyrrolidinedithiocarbamate is extracted from sample solution into the water-immiscible IL formed in-situ. Then, an ultrasound-assisted procedure is employed to back-extract the mercury into 10 µL of a 4 M HCl aqueous solution, which is finally analyzed using SPCnAuEs. Sample preparation methodology was optimized using a multivariate optimization strategy. Under optimized conditions, a linear range between 0.5 and 10 µg L−1 was obtained with a correlation coefficient of 0.997 for six calibration points. The limit of detection obtained was 0.2 µg L−1, which is lower than the threshold value established by the Environmental Protection Agency and European Union (i.e., 2 µg L−1 and 1 µg L−1, respectively). The repeatability of the proposed method was evaluated at two different spiking levels (3 and 10 µg L−1) and a coefficient of variation of 13% was obtained in both cases. The performance of the proposed methodology was evaluated in real-world water samples including tap water, bottled water, river water and industrial wastewater. Relative recoveries between 95% and 108% were obtained.

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Inductively Coupled Plasma Optical Emission Spectrometry (ICP-OES) has been employed to carry out the determination of both major anions and cations in water samples. The anion quantification has been performed by means of a new automatic accessory. In this device chloride has been determined by continuously adding a silver nitrate solution. As a result solid silver chloride particles are formed and retained on a nylon filter inserted in the line. The emission intensity is read at a silver characteristic wavelength. By plotting the drop in silver signal versus the chloride concentration, a straight line is obtained. As regards bicarbonate, this anion has been on-line transformed into carbon dioxide with the help of a 2.0 mol L−1 nitric acid stream. Carbon signal is linearly related with bicarbonate concentration. Finally, information about sulfate concentration has been achieved by means of the measurement of sulfur emission intensity. All the steps have been simultaneously and automatically performed. With this setup detection limits have been 1.0, 0.4 and 0.09 mg L−1 for chloride, bicarbonate and sulfate, respectively. Furthermore, it affords good precision with RSD below 6 %. Cation (Ca, Mg, Na and K) concentration, in turn, has been obtained by simultaneously reading the emission intensity at characteristic wavelengths. The obtained limits of detection have been 8 × 10−3, 2 × 10−3, 8 × 10−4 and 10−2 mg L−1 for sodium, potassium, magnesium and calcium, respectively. As regards sample throughput, about 30 samples h−1 can be analysed. Validation results have revealed that the obtained concentrations for these anions are not significantly different as compared to the data provided by conventional methods. Finally, by considering the data for anions and cations, precise ion balances have been obtained for well and mineral water samples.

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Electron-multiplying charge coupled devices promise to revolutionize ultrasensitive optical imaging. The authors present a simple methodology allowing reliable measurement of camera characteristics and statistics of single-electron events, compare the measurements to a simple theoretical model, and report camera performance in a truly photon-counting regime that eliminates the excess noise related to fluctuations of the multiplication gain.

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The recent emergence of a decreased susceptibility of Neisseria gonorrhoeae strains to penicillin in New Caledonia has lead clinicians to operate a change in the treatment strategy. In addition, this important health issue has emphasized the need for a rapid means of detecting penicillin resistance in N. gonorrhoeae in order to select an effective treatment and limit the spread of resistant strains. In recent years, the use of fluorescence resonance energy transfer on the LightCycler has proven to be a valuable tool for the screening of mutations occurring in the genome of various microorganisms. In this study, we developed a real-time PCR assay coupled with a fluorometric hybridization probes system to detect a penicillin resistance-associated mutation on the N. gonorrhoeae ponA gene. Following an extensive evaluation involving 136 isolates, melting curve analysis correctly evidenced a 5 degrees C T-m shift in all N. gonorrhoeae strains possessing this mutation, as determined by conventional sequencing analysis. Moreover, the mutation profiles obtained with the real-time PCR showed good correlation with the pattern of penicillin susceptibility generated with classical antibiograms. Overall, our molecular assay allowed an accurate and reproducible determination of the susceptibility to penicillin corresponding to a mutation present in all chromosomally mediated resistant strains of N. gonorrhoeae.

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We present a model for detection of the states of a coupled quantum dots (qubit) by a quantum point contact. Most proposals for measurements of states of quantum systems are idealized. However in a real laboratory the measurements cannot be perfect due to practical devices and circuits. The models using ideal devices are not sufficient for describing the detection information of the states of the quantum systems. Our model therefore includes the extension to a non-ideal measurement device case using an equivalent circuit. We derive a quantum trajectory that describes the stochastic evolution of the state of the system of the qubit and the measuring device. We calculate the noise power spectrum of tunnelling events in an ideal and a non-ideal quantum point contact measurement respectively. We found that, for the strong coupling case it is difficult to obtain information of the quantum processes in the qubit by measurements using a non-ideal quantum point contact. The noise spectra can also be used to estimate the limits of applicability of the ideal model.