992 resultados para Contactless conductivity detection


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Low-temperature dielectric measurements on FeTiMO(6) (M = Ta,Nb,Sb) rutile-type oxides at frequencies from 0.1 Hz to 10 MHz revealed anomalous dielectric relaxations with frequency dispersion. Unlike the high-temperature relaxor response of these materials, the low-temperature relaxations are polaronic in nature. The relationship between frequency and temperature of dielectric loss peak follows T(-1/4) behavior. The frequency dependence of ac conductivity shows the well-known universal dielectric response, while the dc conductivity follows Mott variable range hopping (VRH) behavior, confirming the polaronic origin of the observed dielectric relaxations. The frequency domain analysis of the dielectric spectra shows evidence for two relaxations, with the high-frequency relaxations following Mott VRH behavior more closely. Significantly, the Cr- and Ga-based analogs, CrTiNbO(6) and GaTiMO(6) (M = Ta,Nb), that were also studied, did not show these anomalies.

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We calculate the optical conductivity sigma(omega) for doped rare-earth manganites based on the recently proposed microscopic ``two fluid'' l-b model. We study the temperature dependence of sigma(omega) for La(0.825)Sr(0.175)MnO(3), which has a metallic ground state. At low temperatures, the calculated sigma(omega) shows a ``two-peak'' structure consisting of a far-infrared coherent Drude peak and a broad mid-infrared ``polaron'' peak, as observed in experiments. Upon heating, the Drude peak rapidly loses spectral weight, and sigma(omega) crosses over to having just a single broad mid-infrared peak. The temperature dependence of the mid-infrared peak and the spectral weight transfer between the two peaks are also in agreement with experimental findings. We also study the doping dependence of sigma(omega) for the same compound. The integrated spectral weight under the Drude peak increases rapidly as the doping level is increased from an underdoped, insulating state (x = 0.1) to a highly doped, metallic state (x = 0.3), again in agreement with trends seen experimentally.

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Resistance temperature detectors (RTDs) are being widely used to detect low temperature, while thermocouples (TCs) are being used to detect high temperature. The materials suitable for RTDs are platinum, germanium, carbon, carbon-glass, cernox, etc. Here, we have reported the possible application of another form of carbon i.e. carbon nanotubes in low temperature thermometry. It has been shown the resistance R and the sensitivity of carbon nanotube bundles can be tuned and made suitable for ultralow temperature detection. We report on the R-T measurement of carbon nanotube bundles from room temperature down to 1 K to felicitate the possible application of bundles in low temperature RTDs. ©2008 American Institute of Physics

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Background: Lymphatic filariasis is a painful and profoundly disfiguring disease. Infection is usually acquired in childhood but its visible manifestations occur later in life, causing temporary or permanent disability. The importance of developing effective assays to diagnose, monitor and evaluate human lymphatic filariasis has been emphasized by the WHO. Methods: High-affinity monoclonal antibodies (mAbs) specific for recombinant filarial antigen WbSXP-1 were developed. An ELISA based capture assay using monoclonal and polyclonal antibodies for WbSXP-1 was used for detection of circulating filarial antigen. Results: High-affinity monoclonal antibodies (mAbs) were developed that specifically binds both W. bancrofti and B. malayi mf antigens. Two mAbs (1F6H3 and 2E12E3) of subclass IgG2a and IgM showed high affinity, avidity and reactivity to recombinant and mf native antigen. Both the mAbs were used in combination as capture antibodies and polyclonal as detection antibody to develop the assay. The assay showed very high sensitivity towards W. bancrofti mf positive samples compared to endemic normal samples (P<0.0001). Conclusion: A capture assay using high-affinity monoclonal antibodies for WbSXP-1 was developed for the detection of filarial circulating antigen in clinical samples from bancroftian infection. Besides, this would also help in epidemiological studies in endemic areas of filarial infections. (C) 2011 Elsevier B.V. All rights reserved.

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We are concerned with the situation in which a wireless sensor network is deployed in a region, for the purpose of detecting an event occurring at a random time and at a random location. The sensor nodes periodically sample their environment (e.g., for acoustic energy),process the observations (in our case, using a CUSUM-based algorithm) and send a local decision (which is binary in nature) to the fusion centre. The fusion centre collects these local decisions and uses a fusion rule to process the sensors’ local decisions and infer the state of nature, i.e., if an event has occurred or not. Our main contribution is in analyzing two local detection rules in combination with a simple fusion rule. The local detection algorithms are based on the nonparametric CUSUMprocedure from sequential statistics. We also propose two ways to operate the local detectors after an alarm. These alternatives when combined in various ways yield several approaches. Our contribution is to provide analytical techniques to calculate false alarm measures, by the use of which the local detector thresholds can be set. Simulation results are provided to evaluate the accuracy of our analysis. As an illustration we provide a design example. We also use simulations to compare the detection delays incurred in these algorithms.

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We consider the problem of quickest detection of an intrusion using a sensor network, keeping only a minimal number of sensors active. By using a minimal number of sensor devices,we ensure that the energy expenditure for sensing, computation and communication is minimized (and the lifetime of the network is maximized). We model the intrusion detection (or change detection) problem as a Markov decision process (MDP). Based on the theory of MDP, we develop the following closed loop sleep/wake scheduling algorithms: 1) optimal control of Mk+1, the number of sensors in the wake state in time slot k + 1, 2) optimal control of qk+1, the probability of a sensor in the wake state in time slot k + 1, and an open loop sleep/wake scheduling algorithm which 3) computes q, the optimal probability of a sensor in the wake state (which does not vary with time),based on the sensor observations obtained until time slot k.Our results show that an optimum closed loop control onMk+1 significantly decreases the cost compared to keeping any number of sensors active all the time. Also, among the three algorithms described, we observe that the total cost is minimum for the optimum control on Mk+1 and is maximum for the optimum open loop control on q.