892 resultados para Detection system
Resumo:
We analyze the consequences that the choice of the output of the system has in the efficiency of signal detection. It is shown that the output signal and the signal-to-noise ratio (SNR), used to characterize the phenomenon of stochastic resonance, strongly depend on the form of the output. In particular, the SNR may be enhanced for an adequate output.
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A geophysical and geochemical study has been conducted in a fractured carbonate aquifer located at Combioula in the southwestern Swiss Alps with the objective to detect and characterize hydraulically active fractures along a 260-m-deep borehole. Hydrochemical analyses, borehole diameter, temperature and fluid electrical conductivity logging data were integrated in order to relate electrokinetic self-potential signals to groundwater flow inside the fracture network. The results show a generally good, albeit locally variable correlation of variations of the self-potential signals with variations in temperature, fluid electrical conductivity and borehole diameter. Together with the hydrochemical evidence, which was found to be critical for the interpretation of the self-potential data, these measurements not only made it possible to detect the hydraulically active fractures but also to characterize them as zones of fluid gain or fluid loss. The results complement the available information from the corresponding litholog and illustrate the potential of electrokinetic self-potential signals in conjunction with temperature, fluid electrical conductivity and hydrochemical analyses for the characterization of fractured aquifers, and thus may offer a perspective for an effective quantitative characterization of this increasingly important class of aquifers and geothermal reservoirs.
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Combining bacterial bioreporters with microfluidics systems holds great promise for in-field detection of chemical or toxicity targets. Recently we showed how Escherichia coli cells engineered to produce a variant of green fluorescent protein after contact to arsenite and arsenate can be encapsulated in agarose beads and incorporated into a microfluidic chip to create a device for in-field detection of arsenic, a contaminant of well known toxicity and carcinogenicity in potable water both in industrialized and developing countries. Cell-beads stored in the microfluidics chip at -20°C retained inducibility up to one month and we were able to reproducibly discriminate concentrations of 10 and 50 μg arsenite per L (the drinking water standards for European countries and the United States, and for the developing countries, respectively) from the blank in less than 200 minutes. We discuss here the reasons for decreasing bioreporter signal development upon increased storage of cell beads but also show how this decrease can be reduced, leading to a faster detection and a longer lifetime of the device.
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For the past 10 years, mini-host models and in particular the greater wax moth Galleria mellonella have tended to become a surrogate for murine models of fungal infection mainly due to cost, ethical constraints and ease of use. Thus, methods to better assess the fungal pathogenesis in G. mellonella need to be developed. In this study, we implemented the detection of Candida albicans cells expressing the Gaussia princeps luciferase in its cell wall in infected larvae of G. mellonella. We demonstrated that detection and quantification of luminescence in the pulp of infected larvae is a reliable method to perform drug efficacy and C. albicans virulence assays as compared to fungal burden assay. Since the linearity of the bioluminescent signal, as compared to the CFU counts, has a correlation of R(2) = 0.62 and that this method is twice faster and less labor intensive than classical fungal burden assays, it could be applied to large scale studies. We next visualized and followed C. albicans infection in living G. mellonella larvae using a non-toxic and water-soluble coelenterazine formulation and a CCD camera that is commonly used for chemoluminescence signal detection. This work allowed us to follow for the first time C. albicans course of infection in G. mellonella during 4 days.
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The immune system is the responsible for body integrity and prevention of external invasion. On one side, nanoparticles are no triggers that the immune system is prepared to detect, on the other side it is known that foreign bodies, not only bacteria, viruses and parasites, but also inorganic matter, can cause various pathologies such as silicosis, asbestosis or inflammatory reactions. Therefore, nanoparticles entering the body, after interaction with proteins, will be either recognized as self-agents or detected by the immune system, encompassing immunostimulation or immunosuppression responses. The nature of these interactions seems to be dictated not specially by the composition of the material but by modifications of NP coating (composition, surface charge and structure). Herein, we explore the use of gold nanoparticles as substrates to carry multifunctional ligands to manipulate the immune system in a controlled manner, from undetection to immunostimulation. Murine bone marrow macrophages can be activated with artificial nanometric objects consisting of a gold nanoparticle functionalized with peptides. In the presence of some conjugates, macrophage proliferation was stopped and pro-inflammatory cytokines were induced. The biochemical type of response depended on the type of conjugated peptide and was correlated with the degree of ordering in the peptide coating. These findings help to illustrate the basic requirements involved in medical NP conjugate design to either activate the immune system or hide from it, in order to reach their targets before being removed by phagocytes. Additionally, it opens up the possibility to modulate the immune response in order to suppress unwanted responses resulting from autoimmunity, or allergy or to stimulate protective responses against pathogens.
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This work proposes a sequential injection analysis (SIA) system for the spectrophotometric determination of norfloxacin (NOR) and ciprofloxacin (CIP) in pharmaceutical formulations. The methodology was based on the reaction of these drugs with p-(dimethylamino)cinnamaldehyde in micellar medium, producing orange colored products (λmax = 495 nm). Beer´s law was obeyed in the concentration range from 2.75x10-5 to 3.44x10-4 mol L-1 and 3.26x10-5 to 3.54x10-4 mol L-1 for NOR and CIP, respectively and sampling rate was 25 h-1. Commercial samples were analyzed and results obtained through the proposed method were in good agreement with those obtained using the reference procedure for a 95% confidence level.
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Rabies is a neurological disease, but the rabies virus spread to several organs outside the central nervous system (CNS). The rabies virus antigen or RNA has been identified from the salivary glands, the lungs, the kidneys, the heart and the liver. This work aimed to identify the presence of the rabies virus in non-neuronal organs from naturally-infected vampire bats and to study the rabies virus in the salivary glands of healthy vampire bats. Out of the five bats that were positive for rabies in the CNS, by fluorescent antibody test (FAT), viral isolation in N2A cells and reverse transcription - polymerase chain reaction (RT-PCR), 100% (5/5) were positive for rabies in samples of the tongue and the heart, 80% (4/5) in the kidneys, 40% (2/5) in samples of the salivary glands and the lungs, and 20% (1/5) in the liver by RT-PCR test. All the nine bats that were negative for rabies in the CNS, by FAT, viral isolation and RT-PCR were negative for rabies in the salivary glands by RT-PCR test. Possible consequences for rabies epidemiology and pathogenesis are discussed in this work.
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The emergence of multidrug-resistant strains of Mycobacterium tuberculosis has increased the need for rapid drug susceptibility tests, which are needed for adequate patient treatment. The objective of the present study was to evaluate the mycobacteria growth indicator tube (MGIT) system to detect multidrug-resistant M. tuberculosis strains. The MGIT system was compared with two standard methods (proportion and resistance ratio methods). One hundred clinical M. tuberculosis isolates [25 susceptible to isoniazid (INH) and rifampicin (RIF), 20 resistant to INH, 30 resistant to INH-RIF, and 25 resistant to INH-RIF and other drugs] obtained in the State of São Paulo were tested for INH and RIF susceptibility. Full agreement among the tests was found for all sensitive and all INH-resistant strains. For RIF-resistant strains results among the tests agreed for 53 (96.4%) of 55 isolates. Results were obtained within 6 days (range, 5 to 8 days), 28 days and 12 days when using MGIT, the proportion method and the resistance ratio methods, respectively. The MGIT system presented an overall agreement of 96% when compared with two standard methods. These data show that the MGIT system is rapid, sensitive and efficient for the early detection of multidrug-resistant M. tuberculosis.
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The aim of this study was to verify the efficiency of the BAX® system for the detection of Salmonella spp. in raw chicken meat. The conventional culture method (IN 62, MAP) was used as a reference method. A total of 8,813 chicken carcass samples were analyzed. In the first part of the study, 1,200 samples were analyzed using the BAX® System and the conventional culture method. In the second part, 7,613 samples were analyzed by the BAX® system, and the conventional method was used only for samples that tested positive for Salmonella spp. by the BAX® system. The sensitivity, specificity, relative accuracy, positive predictive value, and negative predictive value obtained in the first part of this study were 100%, 92.3%, 96.4%, 53.3% and 100%, respectively. The BAX® system showed no false-negative results and reduced the time to obtain presumptive positive results. It is a suitable method for use in laboratories that perform a large number of food samples analyses daily. However, the conventional method is still required to confirm the presence of Salmonella spp. in samples that test positive using the BAX® system.
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This paper discusses our research in developing a generalized and systematic method for anomaly detection. The key ideas are to represent normal program behaviour using system call frequencies and to incorporate probabilistic techniques for classification to detect anomalies and intrusions. Using experiments on the sendmail system call data, we demonstrate that concise and accurate classifiers can be constructed to detect anomalies. An overview of the approach that we have implemented is provided.
Effectiveness Of Feature Detection Operators On The Performance Of Iris Biometric Recognition System
Resumo:
Iris Recognition is a highly efficient biometric identification system with great possibilities for future in the security systems area.Its robustness and unobtrusiveness, as opposed tomost of the currently deployed systems, make it a good candidate to replace most of thesecurity systems around. By making use of the distinctiveness of iris patterns, iris recognition systems obtain a unique mapping for each person. Identification of this person is possible by applying appropriate matching algorithm.In this paper, Daugman’s Rubber Sheet model is employed for irisnormalization and unwrapping, descriptive statistical analysis of different feature detection operators is performed, features extracted is encoded using Haar wavelets and for classification hammingdistance as a matching algorithm is used. The system was tested on the UBIRIS database. The edge detection algorithm, Canny, is found to be the best one to extract most of the iris texture. The success rate of feature detection using canny is 81%, False Accept Rate is 9% and False Reject Rate is 10%.
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In this report, a face recognition system that is capable of detecting and recognizing frontal and rotated faces was developed. Two face recognition methods focusing on the aspect of pose invariance are presented and evaluated - the whole face approach and the component-based approach. The main challenge of this project is to develop a system that is able to identify faces under different viewing angles in realtime. The development of such a system will enhance the capability and robustness of current face recognition technology. The whole-face approach recognizes faces by classifying a single feature vector consisting of the gray values of the whole face image. The component-based approach first locates the facial components and extracts them. These components are normalized and combined into a single feature vector for classification. The Support Vector Machine (SVM) is used as the classifier for both approaches. Extensive tests with respect to the robustness against pose changes are performed on a database that includes faces rotated up to about 40 degrees in depth. The component-based approach clearly outperforms the whole-face approach on all tests. Although this approach isproven to be more reliable, it is still too slow for real-time applications. That is the reason why a real-time face recognition system using the whole-face approach is implemented to recognize people in color video sequences.
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In this work a hybrid technique that includes probabilistic and optimization based methods is presented. The method is applied, both in simulation and by means of real-time experiments, to the heating unit of a Heating, Ventilation Air Conditioning (HVAC) system. It is shown that the addition of the probabilistic approach improves the fault diagnosis accuracy.
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This paper applies O3BPSK (orthogonal on-off PSK) signaling scheme to multipath fading CDMA channels, for the purpose of near-far resistant detection in the reverse link. Based on the maximum multipath spreading delay, a minimum duration of “off” is suggested, with which the temporally adjacent bits (TABs) from different users at the receiver are decoupled. As a result, a Rake-type one-shot linear decorrelating detector (LDD) is obtained. Since no knowledge of echo amplitudes is needed, a blind detection can be realised.