963 resultados para Frequency Bioelectrical-impedance


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Understanding the changing nature of the intraseasonal oscillatory (ISO) modes of Indian summer monsoon manifested by active and break phase, and their association with extreme rainfall events are necessary for probabilistic estimation of flood-related risks in a warming climate. Here, using ground-based observed rainfall, we define an index to measure the strength of monsoon ISOs and show that the relative strength of the northward-propagating low-frequency ISO (20-60 days) modes have had a significant decreasing trend during the past six decades, possibly attributed to the weakening of large-scale circulation in the region during monsoon season. This reduction is compensated by a gain in synoptic-scale (3-9 days) variability. The decrease in low-frequency ISO variability is associated with a significant decreasing trend in the percentage of extreme events during the active phase of the monsoon. However, this decrease is balanced by significant increasing trends in the percentage of extreme events in the break and transition phases. We also find a significant rise in the occurrence of extremes during early and late monsoon months, mainly over eastern coastal regions. Our study highlights the redistribution of rainfall intensity among periodic (low-frequency) and non-periodic (extreme) modes in a changing climate scenario.

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The synaptic plasticity literature has focused on establishing necessity and sufficiency as two essential and distinct features in causally relating a signaling molecule to plasticity induction, an approach that has been surprisingly lacking in the intrinsic plasticity literature. In this study, we complemented the recently established necessity of inositol trisphosphate (InsP(3)) receptors (InsP(3)R) in a form of intrinsic plasticity by asking if InsP(3)R activation was sufficient to induce intrinsic plasticity in hippocampal neurons. Specifically, incorporation of D-myo-InsP(3) in the recording pipette reduced input resistance, maximal impedance amplitude, and temporal summation but increased resonance frequency, resonance strength, sag ratio, and impedance phase lead. Strikingly, the magnitude of plasticity in all these measurements was dependent on InsP 3 concentration, emphasizing the graded dependence of such plasticity on InsP(3)R activation. Mechanistically, we found that this InsP(3)-induced plasticity depended on hyperpolarization-activated cyclic nucleotide-gated channels. Moreover, this calcium-dependent form of plasticity was critically reliant on the release of calcium through InsP(3)Rs, the influx of calcium through N-methyl-D-aspartate receptors and voltage-gated calcium channels, and on the protein kinase A pathway. Our results delineate a causal role for InsP(3)Rs in graded adaptation of neuronal response dynamics, revealing novel regulatory roles for the endoplasmic reticulum in neural coding and homeostasis.

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Effect of MnO addition on microstructure and ionic transport properties of nanocrystalline cubic(c)-ZrO2 is reported. Monoclinic (m) ZrO2 powders with 10-30 mol% MnO powder are mechanically alloyed in a planetary ball mill at room temperature for 10 h and annealed at 550 degrees C for 6 h. In all compositions m-ZrO2 transforms completely to nanocrystalline c-ZrO2 phase and MnO is fully incorporated into c-ZrO2 lattice. Rietveld's refinement technique is employed for detailed microstructure analysis by analyzing XRD patterns. High resolution transmission electron microscopy (HRTEM) analysis confirms the complete formation of c-ZrO2 phase. Presence of stoichiometric Mn in c-ZrO2 powder is confirmed by Electron Probe Microscopy analysis. XPS analysis reveals that Mn is mostly in Mn2+ oxidation state. A correlation between lattice parameter and oxygen vacancy is established. A detailed ionic conductivity measurement in the 250 degrees-575 degrees C temperature range describes the effect of MnO on conductivity of c-ZrO2. The ionic conductivity (s) of 30 mol% MnO alloyed ZrO2 at 550 degrees C is 0.04 s cm(-1). Electrical relaxation studies are carried out by impedance and modulus spectroscopy. Relaxation frequency is found to increase with temperature and MnO mol fraction. Electrical characterization predicts that these compounds have potentials for use as solid oxide fuel cell electrolyte material. (C) 2015 Elsevier Ltd. All rights reserved.

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The Cognitive Radio (CR) is a promising technology which provides a novel way to subjugate the issue of spectrum underutilization caused due to the fixed spectrum assignment policies. In this paper we report the design and implementation of a soft-real time CR MAC, consisting of multiple secondary users, in a frequency hopping (Fit) primary scenario. This MAC is capable of sensing the spectrum and dynamically allocating the available frequency bands to multiple CR users based on their QoS requirements. As the primary is continuously hopping, a method has also been implemented to detect the hop instant of the primary network. Synchronization usually requires real time support, however we have been able to achieve this with a soft-real time technique which enables a fully software implementation of CR MAC layer. We demonstrate the wireless transmission and reception of video over this CR testbed through opportunistic spectrum access. The experiments carried out use an open source software defined radio package called GNU Radio and a basic radio hardware component USRP.

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Event-triggered sampling (ETS) is a new approach towards efficient signal analysis. The goal of ETS need not be only signal reconstruction, but also direct estimation of desired information in the signal by skillful design of event. We show a promise of ETS approach towards better analysis of oscillatory non-stationary signals modeled by a time-varying sinusoid, when compared to existing uniform Nyquist-rate sampling based signal processing. We examine samples drawn using ETS, with events as zero-crossing (ZC), level-crossing (LC), and extrema, for additive in-band noise and jitter in detection instant. We find that extrema samples are robust, and also facilitate instantaneous amplitude (IA), and instantaneous frequency (IF) estimation in a time-varying sinusoid. The estimation is proposed solely using extrema samples, and a local polynomial regression based least-squares fitting approach. The proposed approach shows improvement, for noisy signals, over widely used analytic signal, energy separation, and ZC based approaches (which are based on uniform Nyquist-rate sampling based data-acquisition and processing). Further, extrema based ETS in general gives a sub-sampled representation (relative to Nyquistrate) of a time-varying sinusoid. For the same data-set size captured with extrema based ETS, and uniform sampling, the former gives much better IA and IF estimation. (C) 2015 Elsevier B.V. All rights reserved.

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Conductivity measurements have been made on x V O-2(5) - (100-x) 0.5 Na2O + 0.5 B2O3] (where 10 a parts per thousand currency sign x a parts per thousand currency sign 50) glasses prepared by using microwave method. DC conductivity (sigma) measurements exhibit temperature-and compositional-dependent trends. It has been found that conductivity in these glasses changes from the predominantly `ionic' to predominantly `electronic' depending upon the chemical composition. The dc conductivity passes through a deep minimum, which is attributed to network disruption. Also, this nonlinear variation in sigma (dc) and activation energy can be interpreted using ion-polaron correlation effect. Electron paramagnetic resonance (EPR) and impedance spectroscopic techniques have been used to elucidate the nature of conduction mechanism. The EPR spectra reveals, in least modified (25 Na2O mol%) glasses, conduction is due to the transfer of electrons via aliovalent vanadium sites, while in highly modified (45 Na2O mol%) glasses Na+ ion transport dominates the electrical conduction. For highly modified glasses, frequency-dependent conductivity has been analysed using electrical modulus formalism and the observations have been discussed.

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For a multilayered specimen, the back-scattered signal in frequency-domain optical-coherence tomography (FDOCT) is expressible as a sum of cosines, each corresponding to a change of refractive index in the specimen. Each of the cosines represent a peak in the reconstructed tomogram. We consider a truncated cosine series representation of the signal, with the constraint that the coefficients in the basis expansion be sparse. An l(2) (sum of squared errors) data error is considered with an l(1) (summation of absolute values) constraint on the coefficients. The optimization problem is solved using Weiszfeld's iteratively reweighted least squares (IRLS) algorithm. On real FDOCT data, improved results are obtained over the standard reconstruction technique with lower levels of background measurement noise and artifacts due to a strong l(1) penalty. The previous sparse tomogram reconstruction techniques in the literature proposed collecting sparse samples, necessitating a change in the data capturing process conventionally used in FDOCT. The IRLS-based method proposed in this paper does not suffer from this drawback.

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Inverters with high voltage conversion ratio are used in systems with sources such as batteries, photovoltaic (PV) modules or fuel cells. Transformers are often used in such inverters to provide the required voltage conversion ratio and isolation. In this paper, a compact high-frequency (HF) transformer interfaced AC link inverter with lossless snubber is discussed. A high performance synchronized modulation scheme is proposed for this inverter. This modulation addresses the issue of over-voltage spikes due to transformer leakage inductance and it is shown that the circuit can operate safely even when the turn-on delay, such as dead-time, is not used in the HF rectifier section. The problem of spurious turn-on in the HF inverter switches is also mitigated by the proposed modulation method. The circuit performance is validated experimentally with a $900W$ prototype inverter.

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Measurement of device current during switching characterisation of an insulated gate bipolar transistor (IGBT) requires a current sensor with low insertion impedance and high bandwidth. This study presents an experimental procedure for evaluating the performance of a coaxial current transformer (CCT), designed for the above purpose. A prototype CCT, which can be mounted directly on a power terminal of a 1200 V/50 A half-bridge IGBT module, is characterised experimentally. The measured characteristics include insertion impedance, gain and phase of the CCT at different frequencies. The bounds of linearity within which the CCT can operate without saturation are determined theoretically, and are also verified experimentally. The experimental study on linearity of the CCT requires a high-amplitude current source. A proportional-resonant (PR) controller-based current-controlled half-bridge inverter is developed for this purpose. A systematic procedure for selection of PR controller parameters is also reported in this study. This set-up is helpful to determine the limit of linearity and also to measure the frequency response of the CCT at realistic amplitudes of current in the low-frequency range.

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Scaling approaches are widely used by hydrologists for Regional Frequency Analysis (RFA) of floods at ungauged/sparsely gauged site(s) in river basins. This paper proposes a Recursive Multi-scaling (RMS) approach to RFA that overcomes limitations of conventional simple- and multi-scaling approaches. The approach involves identification of a separate set of attributes corresponding to each of the sites (being considered in the study area/region) in a recursive manner according to their importance, and utilizing those attributes to construct effective regional regression relationships to estimate statistical raw moments (SMs) of peak flows. The SMs are then utilized to arrive at parameters of flood frequency distribution and quantile estimate(s) corresponding to target return period(s). Effectiveness of the RMS approach in arriving at flood quantile estimates for ungauged sites is demonstrated through leave-one-out cross-validation experiment on watersheds in Indiana State, USA. Results indicate that the approach outperforms index-flood based Region-of-Influence approach, simple- and multi-scaling approaches and a multiple linear regression method. (C) 2015 Elsevier B.V. All rights reserved.

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Index-flood related regional frequency analysis (RFA) procedures are in use by hydrologists to estimate design quantiles of hydrological extreme events at data sparse/ungauged locations in river basins. There is a dearth of attempts to establish which among those procedures is better for RFA in the L-moment framework. This paper evaluates the performance of the conventional index flood (CIF), the logarithmic index flood (LIF), and two variants of the population index flood (PIF) procedures in estimating flood quantiles for ungauged locations by Monte Carlo simulation experiments and a case study on watersheds in Indiana in the U.S. To evaluate the PIF procedure, L-moment formulations are developed for implementing the procedure in situations where the regional frequency distribution (RFD) is the generalized logistic (GLO), generalized Pareto (GPA), generalized normal (GNO) or Pearson type III (PE3), as those formulations are unavailable. Results indicate that one of the variants of the PIF procedure, which utilizes the regional information on the first two L-moments is more effective than the CIF and LIF procedures. The improvement in quantile estimation using the variant of PIF procedure as compared with the CIF procedure is significant when the RFD is a generalized extreme value, GLO, GNO, or PE3, and marginal when it is GPA. (C) 2015 American Society of Civil Engineers.

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The double perovskite Y2NiMnO6 displays ferromagnetic transition at T-c approximate to 81 K. The ferromagnetic order at low temperature is confirmed by the saturation value of magnetization (Ms) and also validated by the refined ordered magnetic moment values extracted from neutron powder diffraction data at 10 K. This way, the dominant Mn4+ and Ni2+ cationic ordering is confirmed. The cation-ordered P2(1)/n nuclear structure is revealed by neutron powder diffraction studies at 300 and 10 K. Analysis of the frequency-dependent dielectric constant and equivalent circuit analysis of impedance data take into account the bulk contribution to the total dielectric constant. This reveals an anomaly which coincides with the ferromagnetic transition temperature (T-c). Pyrocurrent measurements register a current flow with onset near T-c and a peak at 57 K that shifts with temperature ramp rate. The extrinsic nature of the observed pyrocurrent is established by employing a special protocol measurement. It is realized that the origin is due to reorientation of electric dipoles created by the free charge carriers and not by spontaneous electric polarization at variance with recently reported magnetism-driven ferroelectricity in this material.

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Zn1-xMgxO ( <= x <= 0.1) ceramics were fabricated by conventional solid-state reaction of co-precipitated zinc oxide and magnesium hydroxide nanoparticles. Structural and morphological properties of the fabricated ceramics were studied using X-ray diffraction and scanning electron microscopic analysis. The dielectric measurements of the ceramics were carried out as a function of frequency and temperature respectively. Interestingly, Mg doped ZnO (MZO) samples exhibited colossal dielectric response (similar to 1 x 10(4) at 1 kHz) with Debye like relaxation. The detailed dielectric studies and thermal analyses showed that the unusual dielectric response of the samples were originated from the defected grain and grain boundary (GB) conductivity relaxations due to the absorbed atmospheric water vapor (moisture). Impedance spectroscopy was employed to determine the defected grain and GB resistances, capacitances and which supported Maxwell-Wagner type relaxation phenomena. (C) 2015 Elsevier Ltd. All rights reserved.

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In this work, spectrum sensing for cognitive radios is considered in the presence of multiple Primary Users (PU) using frequency-hopping communication over a set of frequency bands. The detection performance of the Fast Fourier Transform (FFT) Average Ratio (FAR) algorithm is obtained in closed-form, for a given FFT size and number of PUs. The effective throughput of the Secondary Users (SU) is formulated as an optimization problem with a constraint on the maximum allowable interference on the primary network. Given the hopping period of the PUs, the sensing duration that maximizes the SU throughput is derived. The results are validated using Monte Carlo simulations. Further, an implementation of the FAR algorithm on the Lyrtech (now, Nutaq) small form factor software defined radio development platform is presented, and the performance recorded through the hardware is observed to corroborate well with that obtained through simulations, allowing for implementation losses. (C) 2015 Elsevier B.V. All rights reserved.

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The world has dominated by automation, wireless communication and various electronic equipments, which has led to the most undesirable offshoots like electromagnetic (EM) pollution. The rationale is environmental concern and the necessity to develop EM absorbing materials. This paper reviews the state of the art of designing polymer based nanocomposites containing nanoscopic particles with high electrical conductivity and complex microwave properties for enhanced EM attenuation. Given the brevity of this review article, herein we have summarized the high frequency millimetre wave absorbing properties of polymer nanocomposites consisting of various nanoparticles that either reflect or absorb microwave radiation like electrically conducting carbon nanotubes (CNTs) and graphene nanosheets (GNs), high dielectric constant ceramic nanoparticles that show relaxation loss in the microwave frequency and magnetic metal and ferrite nanoparticles that absorb microwave radiation through natural resonance, eddy current and hysteresis losses. Furthermore, we have stressed the necessity and impact of hybrid nanoparticles consisting of magnetic and dielectric nanoparticles along with conducting inclusions like CNT and GNs in this review. Electromagnetic interference (EMI) theory and necessary criterion for attenuation has been briefly discussed. The emphasis is made on various mechanisms towards EM attenuation controlled by these nanoparticles. Various structures developed using polymer nanocomposites like bulk, foam and layered structures and their effect on EM attenuation has been elaborately discussed. In addition, various covalent/non-covalent modifications on nanoparticles have been juxtaposed in context to EM attenuation. In addition, we have highlighted important facets and direction for enhancing the microwave attenuation. (C) 2016 Elsevier Ltd. All rights reserved.