845 resultados para Detection and representation


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Exploitation of the electronic properties of carbon nanotubes for the development of voltammetric and amperometric sensors to monitor analytes of environmental relevance has increased in recent years. This work reports the development of a biomimetic sensor based on a carbon paste modified with 5,10,15,20-tetrakis(pentafluorophenyl)-21H,23H-porphyrin iron (III) chloride (a biomimetic catalyst of the P450 enzyme) and multi-wall carbon nanotubes (MWCNT), for the sensitive and selective detection of the herbicide 2,4- dichlorophenoxyacetic acid (2,4-D). The sensor was evaluated using cyclic voltammetry and amperometry, for electrochemical characterization and quantification purposes, respectively. Amperometric analyses were carried out at -100 mV vs. Ag/AgCl(KClsat), using a 0.1 mol L-1 phosphate buffer solution at pH 6.0 as the support electrolyte. Under these optimized analytical conditions, the sensor showed a linear response between 9.9 × 10-6 and 1.4 × 10-4 mol L-1, a sensitivity of 1.8 × 104 (±429) μA L mol -1, and limits of detection and quantification of 2.1 × 10 -6 and 6.8 × 10-6 mol L-1, respectively. The incorporation of functionalized MWCNT in the carbon paste resulted in a 10-fold increase in the response, compared to that of the biomimetic sensor without MWCNT. In addition, the low applied potential (-100 mV) used to obtain high sensitivity also contributed to the excellent selectivity of the proposed sensor. The viability of the application of this sensor for analysis of soil samples was confirmed by satisfactory recovery values, with a mean of 96% and RSD of 2.1% (n = 3). © 2013 Elsevier B.V.

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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Interest in the electronic properties of carbon nanotubes has increased in recent years. These materials can be used in the development of electrochemical sensors for the measurement and monitoring of analytes of environmental interest, such as pharmaceuticals, dyes, and pesticides. This work describes the use of homemade screen-printed electrodes modified with multi-walled carbon nanotubes (MWCNT) for the electrochemical detection of the fungicide thiram. The electrochemical characteristics of the proposed system were evaluated using cyclic voltammetry, with investigation of the electrochemical behavior of the sensor in the presence of the analyte, and estimation of electrochemical parameters including the diffusion coefficient, electron transfer coefficient (α), and number of electrons transferred in the catalytic electro-oxidation. The sensor response was optimized using amperometry. The best sensor performance was obtained in 0.1 mol L-1 phosphate buffer solution at pH 8.0, where a detection limit of 7.9 x 10-6 mol L-1 was achieved. Finally, in order to improve the sensitivity of the sensor, square wave voltammetry (SWV) was used for thiram quantification, instead of amperometry. Using SWV, a response range for thiram from 9.9 x 10-6 to 9.1 x 10-5 mol L-1 was obtained, with a sensitivity of 30948 µA mol L-1, and limits of detection and quantification of 1.6 x 10-6 and 5.4 x 10-6 mol L-1, respectively. The applicability of this efficient new alternative methodology for thiram detection was demonstrated using analyses of enriched soil samples.

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES

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Strains of Lysobacter enzymogenes, a bacterial species with biocontrol activity, have been detected via 16S rDNA sequences in soil in different parts of the world. In most instances, however, their occurrence could not be confirmed by isolation, presumably because the species occurred in low numbers relative to faster-growing species of Bacillus or Pseudomonas. In this study, we developed DNA-based detection and enrichment culturing methods for Lysobacter spp. and L. enzymogenes specifically. In the DNA-based method, a region of 16S rDNA conserved among Lysobacter spp. (L4: GAG CCG ACG TCG GAT TAG CTA GTT), was used as the forward primer in PCR amplification. When L4 and universal bacterial primer 1525R were used to amplify DNA from various bacterial species, an 1100-bp product was found in Lysobacter spp. exclusively. The enrichment culturing method involved culturing soils for 3 days in a chitin-containing broth amended with antibiotics. Bacterial strains in the enrichment culture were isolated on yeast-cell agar and then identified by 16S rDNA sequence analysis. A strain of L. enzymogenes added to soils was detected at populations as low as 102 and 104 CFU/g soil by PCR amplification and enrichment culturing, respectively. In a survey of 58 soil samples, Lysobacter was detected in 41 samples by PCR and enrichment culture, out of which 6 yielded strains of Lysobacter spp. by enrichment culture. Among isolated strains, all were identified to be L. enzymogenes, with the exception of a strain of L. antibioticus. Although neither method alone is completely effective at detecting L. enzymogenes, they are complementary when used together and may provide new information on the spatial distribution of the species in soil.

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[EN] This paper analyzes the detection and localization performance of the participating face and eye algorithms compared with the Viola Jones detector and four leading commercial face detectors. Performance is characterized under the different conditions and parameterized by per-image brightness and contrast. In localization accuracy for eyes, the groups/companies focusing on long-range face detection outperform leading commercial applications.

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The research is part of a survey for the detection of the hydraulic and geotechnical conditions of river embankments funded by the Reno River Basin Regional Technical Service of the Region Emilia-Romagna. The hydraulic safety of the Reno River, one of the main rivers in North-Eastern Italy, is indeed of primary importance to the Emilia-Romagna regional administration. The large longitudinal extent of the banks (several hundreds of kilometres) has placed great interest in non-destructive geophysical methods, which, compared to other methods such as drilling, allow for the faster and often less expensive acquisition of high-resolution data. The present work aims to experience the Ground Penetrating Radar (GPR) for the detection of local non-homogeneities (mainly stratigraphic contacts, cavities and conduits) inside the Reno River and its tributaries embankments, taking into account supplementary data collected with traditional destructive tests (boreholes, cone penetration tests etc.). A comparison with non-destructive methodologies likewise electric resistivity tomography (ERT), Multi-channels Analysis of Surface Waves (MASW), FDEM induction, was also carried out in order to verify the usability of GPR and to provide integration of various geophysical methods in the process of regular maintenance and check of the embankments condition. The first part of this thesis is dedicated to the explanation of the state of art concerning the geographic, geomorphologic and geotechnical characteristics of Reno River and its tributaries embankments, as well as the description of some geophysical applications provided on embankments belonging to European and North-American Rivers, which were used as bibliographic basis for this thesis realisation. The second part is an overview of the geophysical methods that were employed for this research, (with a particular attention to the GPR), reporting also their theoretical basis and a deepening of some techniques of the geophysical data analysis and representation, when applied to river embankments. The successive chapters, following the main scope of this research that is to highlight advantages and drawbacks in the use of Ground Penetrating Radar applied to Reno River and its tributaries embankments, show the results obtained analyzing different cases that could yield the formation of weakness zones, which successively lead to the embankment failure. As advantages, a considerable velocity of acquisition and a spatial resolution of the obtained data, incomparable with respect to other methodologies, were recorded. With regard to the drawbacks, some factors, related to the attenuation losses of wave propagation, due to different content in clay, silt, and sand, as well as surface effects have significantly limited the correlation between GPR profiles and geotechnical information and therefore compromised the embankment safety assessment. Recapitulating, the Ground Penetrating Radar could represent a suitable tool for checking up river dike conditions, but its use has significantly limited by geometric and geotechnical characteristics of the Reno River and its tributaries levees. As a matter of facts, only the shallower part of the embankment was investigate, achieving also information just related to changes in electrical properties, without any numerical measurement. Furthermore, GPR application is ineffective for a preliminary assessment of embankment safety conditions, while for detailed campaigns at shallow depth, which aims to achieve immediate results with optimal precision, its usage is totally recommended. The cases where multidisciplinary approach was tested, reveal an optimal interconnection of the various geophysical methodologies employed, producing qualitative results concerning the preliminary phase (FDEM), assuring quantitative and high confidential description of the subsoil (ERT) and finally, providing fast and highly detailed analysis (GPR). Trying to furnish some recommendations for future researches, the simultaneous exploitation of many geophysical devices to assess safety conditions of river embankments is absolutely suggested, especially to face reliable flood event, when the entire extension of the embankments themselves must be investigated.

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Satellite remote sensing has proved to be an effective support in timely detection and monitoring of marine oil pollution, mainly due to illegal ship discharges. In this context, we have developed a new methodology and technique for optical oil spill detection, which make use of MODIS L2 and MERIS L1B satellite top of atmosphere (TOA) reflectance imagery, for the first time in a highly automated way. The main idea was combining wide swaths and short revisit times of optical sensors with SAR observations, generally used in oil spill monitoring. This arises from the necessity to overcome the SAR reduced coverage and long revisit time of the monitoring area. This can be done now, given the MODIS and MERIS higher spatial resolution with respect to older sensors (250-300 m vs. 1 km), which consents the identification of smaller spills deriving from illicit discharge at sea. The procedure to obtain identifiable spills in optical reflectance images involves removal of oceanic and atmospheric natural variability, in order to enhance oil-water contrast; image clustering, which purpose is to segment the oil spill eventually presents in the image; finally, the application of a set of criteria for the elimination of those features which look like spills (look-alikes). The final result is a classification of oil spill candidate regions by means of a score based on the above criteria.

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Modern control systems are becoming more and more complex and control algorithms more and more sophisticated. Consequently, Fault Detection and Diagnosis (FDD) and Fault Tolerant Control (FTC) have gained central importance over the past decades, due to the increasing requirements of availability, cost efficiency, reliability and operating safety. This thesis deals with the FDD and FTC problems in a spacecraft Attitude Determination and Control System (ADCS). Firstly, the detailed nonlinear models of the spacecraft attitude dynamics and kinematics are described, along with the dynamic models of the actuators and main external disturbance sources. The considered ADCS is composed of an array of four redundant reaction wheels. A set of sensors provides satellite angular velocity, attitude and flywheel spin rate information. Then, general overviews of the Fault Detection and Isolation (FDI), Fault Estimation (FE) and Fault Tolerant Control (FTC) problems are presented, and the design and implementation of a novel diagnosis system is described. The system consists of a FDI module composed of properly organized model-based residual filters, exploiting the available input and output information for the detection and localization of an occurred fault. A proper fault mapping procedure and the nonlinear geometric approach are exploited to design residual filters explicitly decoupled from the external aerodynamic disturbance and sensitive to specific sets of faults. The subsequent use of suitable adaptive FE algorithms, based on the exploitation of radial basis function neural networks, allows to obtain accurate fault estimations. Finally, this estimation is actively exploited in a FTC scheme to achieve a suitable fault accommodation and guarantee the desired control performances. A standard sliding mode controller is implemented for attitude stabilization and control. Several simulation results are given to highlight the performances of the overall designed system in case of different types of faults affecting the ADCS actuators and sensors.

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Data sets describing the state of the earth's atmosphere are of great importance in the atmospheric sciences. Over the last decades, the quality and sheer amount of the available data increased significantly, resulting in a rising demand for new tools capable of handling and analysing these large, multidimensional sets of atmospheric data. The interdisciplinary work presented in this thesis covers the development and the application of practical software tools and efficient algorithms from the field of computer science, aiming at the goal of enabling atmospheric scientists to analyse and to gain new insights from these large data sets. For this purpose, our tools combine novel techniques with well-established methods from different areas such as scientific visualization and data segmentation. In this thesis, three practical tools are presented. Two of these tools are software systems (Insight and IWAL) for different types of processing and interactive visualization of data, the third tool is an efficient algorithm for data segmentation implemented as part of Insight.Insight is a toolkit for the interactive, three-dimensional visualization and processing of large sets of atmospheric data, originally developed as a testing environment for the novel segmentation algorithm. It provides a dynamic system for combining at runtime data from different sources, a variety of different data processing algorithms, and several visualization techniques. Its modular architecture and flexible scripting support led to additional applications of the software, from which two examples are presented: the usage of Insight as a WMS (web map service) server, and the automatic production of a sequence of images for the visualization of cyclone simulations. The core application of Insight is the provision of the novel segmentation algorithm for the efficient detection and tracking of 3D features in large sets of atmospheric data, as well as for the precise localization of the occurring genesis, lysis, merging and splitting events. Data segmentation usually leads to a significant reduction of the size of the considered data. This enables a practical visualization of the data, statistical analyses of the features and their events, and the manual or automatic detection of interesting situations for subsequent detailed investigation. The concepts of the novel algorithm, its technical realization, and several extensions for avoiding under- and over-segmentation are discussed. As example applications, this thesis covers the setup and the results of the segmentation of upper-tropospheric jet streams and cyclones as full 3D objects. Finally, IWAL is presented, which is a web application for providing an easy interactive access to meteorological data visualizations, primarily aimed at students. As a web application, the needs to retrieve all input data sets and to install and handle complex visualization tools on a local machine are avoided. The main challenge in the provision of customizable visualizations to large numbers of simultaneous users was to find an acceptable trade-off between the available visualization options and the performance of the application. Besides the implementational details, benchmarks and the results of a user survey are presented.

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In the last years radar sensor networks for localization and tracking in indoor environment have generated more and more interest, especially for anti-intrusion security systems. These networks often use Ultra Wide Band (UWB) technology, which consists in sending very short (few nanoseconds) impulse signals. This approach guarantees high resolution and accuracy and also other advantages such as low price, low power consumption and narrow-band interference (jamming) robustness. In this thesis the overall data processing (done in MATLAB environment) is discussed, starting from experimental measures from sensor devices, ending with the 2D visualization of targets movements over time and focusing mainly on detection and localization algorithms. Moreover, two different scenarios and both single and multiple target tracking are analyzed.

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Local to regional climate anomalies are to a large extent determined by the state of the atmospheric circulation. The knowledge of large-scale sea level pressure (SLP) variations in former times is therefore crucial when addressing past climate changes across Europe and the Mediterranean. However, currently available SLP reconstructions lack data from the ocean, particularly in the pre-1850 period. Here we present a new statistically-derived 5° × 5° resolved gridded seasonal SLP dataset covering the eastern North Atlantic, Europe and the Mediterranean area (40°W–50°E; 20°N–70°N) back to 1750 using terrestrial instrumental pressure series and marine wind information from ship logbooks. For the period 1750–1850, the new SLP reconstruction provides a more accurate representation of the strength of the winter westerlies as well as the location and variability of the Azores High than currently available multiproxy pressure field reconstructions. These findings strongly support the potential of ship logbooks as an important source to determine past circulation variations especially for the pre-1850 period. This new dataset can be further used for dynamical studies relating large-scale atmospheric circulation to temperature and precipitation variability over the Mediterranean and Eurasia, for the comparison with outputs from GCMs as well as for detection and attribution studies.

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We tested the use of multiplex real-time PCR for detection and quantification of Campylobacter jejuni and Campylobacter coli on broiler carcass neck skin samples collected during 2008 from slaughterhouses in Switzerland. Results from an established TaqMan assay based on two different targets (hipO and ceuE for C. jejuni and C. coli, respectively) were corroborated with data from a newly developed assay based on a single-nucleotide polymorphism in the fusA gene, which allows differentiation between C. jejuni and C. coli. Both multiplex real-time PCRs were applied simultaneously for direct detection, differentiation, and quantification of Campylobacter from 351 neck skin samples and compared with culture methods. There was good correlation in detection and enumeration between real-time PCR results and quantitative culture, with real-time PCR being more sensitive. Overall, 251 (71.5%) of the samples were PCR positive for Campylobacter, with 211 (60.1%) in the hipO-ceuE assays, 244 (69.5%) in the fusA assay, and 204 (58.1%) of them being positive in both PCR assays. Thus, the fusA assay was similarly sensitive to the enrichment culture (72.4% positive); however, it is faster and allows for quantification. In addition, real-time PCR allowed for species differentiation; roughly 60% of positive samples contained C. jejuni, less than 10% C. coli, and more than 30% contained both species. Real-time PCR proved to be a suitable method for direct detection, quantification, and differentiation of Campylobacter from carcasses, and could permit time-efficient surveillance of these zoonotic agents.

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Haemotrophic mycoplasmas (also known as haemoplasmas), small bacterias which parasite the surface of erythrocytes, have been described in several species. Recently, molecular methods were developed for the diagnosis of haemoplasma infection. The presented study describes the first detection and the investigation of prevalence of "Candidatus Mycoplasma haemolamae" in South American Camelids in Switzerland. A random sample of the latter population was tested for haemoplasma infections using real-time PCR. The infection was detected in 18.6% of the animals and was found both in indigenous and in imported camelids. Of the tested herds 39,1% harboured at least one animal positive for haemoplasmas in PCR. There was no difference in prevalence between male and female animals and llamas and alpacas, respectively. Furthermore, the prevalence of infection was not significantly different in diseased animals compared to healthy camelids. From the latter observation and the fact that the high prevalence was accompanied by an undetectable incidence, we concluded that the pathogenicity of "Candidatus Mycoplasma haemolamae" may be low.

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The early detection and treatment of persons at-risk for psychosis is currently regarded a promising strategy in fighting the devastating consequences of psychotic disorders. The two current at-risk approaches, i.e., the "ultra high risk" and the "basic symptom" criteria, were mainly developed on adult samples. Initial evidence suggests, however, that they cannot simply be applied to children and adolescents. For ultra high risk criteria, there is indication of some attenuated psychotic symptoms being potentially non-specific in adolescents and of brief limited intermittent symptoms being difficult to clinically classify in children when observable behavioral correlates are missing. For basic symptoms, too, only preliminary indication of their usefulness in children and adolescents exists. Since developmental peculiarities in the assessment of basic symptoms should be considered, a child and youth version of the Schizophrenia Proneness Instrument (SPI-CY) was developed. In conclusion, research on the clinical-prognostic validity of the at-risk criteria and their potential adoption to the special needs of children and adolescents is needed. If a Prodromal Risk Syndrome for Psychosis or Attenuated Psychotic Symptoms Syndrome will be included into DSM-V, it has to be highlighted that its suitability for children and adolescents is only insufficiently known.