222 resultados para Microdefect densities
Resumo:
Reliable estimates of species density are fundamental to planning conservation strategies for any species; further, it is equally crucial to identify the most appropriate technique to estimate animal density. Nocturnal, small-sized animal species are notoriously difficult to census accurately and this issue critically affects their conservation status, We carried out a field study in southern India to estimate the density of slender loris, a small-sized nocturnal primate using line and strip transects. Actual counts of study individuals yielded a density estimate of 1.61 ha(-1); density estimate from line transects was 1.08 ha(-1); and density estimates varied from 1.06 ha(-1) to 0.59 ha(-1) in different fixed-width strip transects. We conclude that line and strip transects may typically underestimate densities of cryptic, nocturnal primates.
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Chebyshev-inequality-based convex relaxations of Chance-Constrained Programs (CCPs) are shown to be useful for learning classifiers on massive datasets. In particular, an algorithm that integrates efficient clustering procedures and CCP approaches for computing classifiers on large datasets is proposed. The key idea is to identify high density regions or clusters from individual class conditional densities and then use a CCP formulation to learn a classifier on the clusters. The CCP formulation ensures that most of the data points in a cluster are correctly classified by employing a Chebyshev-inequality-based convex relaxation. This relaxation is heavily dependent on the second-order statistics. However, this formulation and in general such relaxations that depend on the second-order moments are susceptible to moment estimation errors. One of the contributions of the paper is to propose several formulations that are robust to such errors. In particular a generic way of making such formulations robust to moment estimation errors is illustrated using two novel confidence sets. An important contribution is to show that when either of the confidence sets is employed, for the special case of a spherical normal distribution of clusters, the robust variant of the formulation can be posed as a second-order cone program. Empirical results show that the robust formulations achieve accuracies comparable to that with true moments, even when moment estimates are erroneous. Results also illustrate the benefits of employing the proposed methodology for robust classification of large-scale datasets.
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A circuit topology based on accumulate-and-use philosophy has been developed to harvest RF energy from ambient radiations such as those from cellular towers. Main functional units of this system are antenna, tuned rectifier, supercapacitor, a gated boost converter and the necessary power management circuits. Various RF aspects of the design philosophy for maximizing the conversion efficiency at an input power level of 15 mu W are presented here. The system is characterized in an anechoic chamber and it has been established that this topology can harvest RF power densities as low as 180 mu W/m(2) and can adaptively operate the load depending on the incident radiation levels. The output of this system can be easily configured at a desired voltage in the range 2.2-4.5 V. A practical CMOS load - a low power wireless radio module has been demonstrated to operate intermittently by this approach. This topology can be easily modified for driving other practical loads, from harvested RF energy at different frequencies and power levels.
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The nanocomposites of xTiO(2)+(1-x)Ni0.53Cu0.12Zn0.35Fe2O4 (where 0 <= x >= 1) were prepared using microwave hydrothermal (M H) method at 165 degrees C/45 min. The as-synthesized powders were characterized using X-ray diffraction (XRD), transmission electron microscopy (TEM) and Fourier transform infrared spectroscopy (FTIR). The particle size of the powder varies from 18 to 35 nm. The as prepared powders were densified at 500 degrees C/30 min using microwave sintering method. The sintered composites were characterized by XRD and scanning electron microscopy (SEM). The bulk densities of the present composites were increasing with the addition of TiO2. The grain sizes of all the composite vary between 65 nm and 90 nm. The addition of TiO2 to ferrite increased the dielectric properties (epsilon' and epsilon `') also the resonant frequency of all the composites was found to be greater than 1 GHz. The imaginary part of permeability mu `' was found to increase with an increase of TiO2.
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We review the spatio-temporal dynamical features of the Ananthakrishna model for the Portevin-Le Chatelier effect, a kind of plastic instability observed under constant strain rate deformation conditions. We then establish a qualitative correspondence between the spatio-temporal structures that evolve continuously in the instability domain and the nature of the irregularity of the scalar stress signal. Rest of the study is on quantifying the dynamical information contained in the stress signals about the spatio-temporal dynamics of the model. We show that at low applied strain rates, there is a one-to-one correspondence with the randomly nucleated isolated bursts of mobile dislocation density and the stress drops. We then show that the model equations are spatio-temporally chaotic by demonstrating the number of positive Lyapunov exponents and Lyapunov dimension scale with the system size at low and high strain rates. Using a modified algorithm for calculating correlation dimension density, we show that the stress-strain signals at low applied strain rates corresponding to spatially uncorrelated dislocation bands exhibit features of low dimensional chaos. This is made quantitative by demonstrating that the model equations can be approximately reduced to space independent model equations for the average dislocation densities, which is known to be low-dimensionally chaotic. However, the scaling regime for the correlation dimension shrinks with increasing applied strain rate due to increasing propensity for propagation of the dislocation bands. The stress signals in the partially propagating to fully propagating bands turn to have features of extensive chaos.
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We extend our analysis of transverse single spin asymmetry in electroproduction of J/psi to include the effect of the scale evolution of the transverse momentum dependent (TMD) parton distribution functions and gluon Sivers function. We estimate single spin asymmetry for JLab, HERMES, COMPASS, and eRHIC energies using the color evaporation model of charmonium production, using an analytically obtained approximate solution of TMD evolution equations discussed in the literature. We find that there is a reduction in the asymmetry compared with our predictions for the earlier case considered by us, wherein the Q(2) dependence came only from DGLAP evolution of the unpolarized gluon densities and a different parametrization of the TMD Sivers function was used.
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In this paper, we analyze the combined effects of size quantization and device temperature variations (T = 50K to 400 K) on the intrinsic carrier concentration (n(i)), electron concentration (n) and thereby on the threshold voltage (V-th) for thin silicon film (t(si) = 1 nm to 10 nm) based fully-depleted Double-Gate Silicon-on-Insulator MOSFETs. The threshold voltage (V-th) is defined as the gate voltage (V-g) at which the potential at the center of the channel (Phi(c)) begins to saturate (Phi(c) = Phi(c(sat))). It is shown that in the strong quantum confinement regime (t(si) <= 3nm), the effects of size quantization far over-ride the effects of temperature variations on the total change in band-gap (Delta E-g(eff)), intrinsic carrier concentration (n(i)), electron concentration (n), Phi(c(sat)) and the threshold voltage (V-th). On the other hand, for t(si) >= 4 nm, it is shown that size quantization effects recede with increasing t(si), while the effects of temperature variations become increasingly significant. Through detailed analysis, a physical model for the threshold voltage is presented both for the undoped and doped cases valid over a wide-range of device temperatures, silicon film thicknesses and substrate doping densities. Both in the undoped and doped cases, it is shown that the threshold voltage strongly depends on the channel charge density and that it is independent of incomplete ionization effects, at lower device temperatures. The results are compared with the published work available in literature, and it is shown that the present approach incorporates quantization and temperature effects over the entire temperature range. We also present an analytical model for V-th as a function of device temperature (T). (C) 2013 AIP Publishing LLC.
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Several concepts have been developed in the recent years for nanomaterial based integrated MEMS platform in order to accelerate the process of biological sample preparation followed by selective screening and identification of target molecules. In this context, there exist several challenges which need to be addressed in the process of electrical lysis of biological cells. These are due to (i) low resource settings while achieving maximal lysis (ii) high throughput of target molecules to be detected (iii) automated extraction and purification of relevant molecules such as DNA and protein from extremely small volume of sample (iv) requirement of fast, accurate and yet scalable methods (v) multifunctionality toward process monitoring and (vi) downward compatibility with already existing diagnostic protocols. This paper reports on the optimization of electrical lysis process based on various different nanocomposite coated electrodes placed in a microfluidic channel. The nanocomposites are synthesized using different nanomaterials like Zinc nanorod dispersion in polymer. The efficiency of electrical lysis with various different electrode coatings has been experimentally verified in terms of DNA concentration, amplification and protein yield. The influence of the coating thickness on the injection current densities has been analyzed. We further correlate experimentally the current density vs. voltage relationship with the extent of bacterial cell lysis. A coupled multiphysics based simulation model is used to predict the cell trajectories and lysis efficiencies under various electrode boundary conditions as estimated from experimental results. Detailed in-situ fluorescence imaging and spectroscopy studies are performed to validate various hypotheses.
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We report on the design, development, and performance study of a packaged piezoelectric thin film impact sensor, and its potential application in non-destructive material discrimination. The impact sensing element employed was a thin circular diaphragm of flexible Phynox alloy. Piezoelectric ZnO thin film as an impact sensing layer was deposited on to the Phynox alloy diaphragm by RF reactive magnetron sputtering. Deposited ZnO thin film was characterized by X-ray diffraction (XRD), Atomic Force Microscopy (AFM), and Scanning Electron Microscopy (SEM) techniques. The d(31) piezoelectric coefficient value of ZnO thin film was 4.7 pm V-1, as measured by 4-point bending method. ZnO film deposited diaphragm based sensing element was properly packaged in a suitable housing made of High Density Polyethylene (HDPE) material. Packaged impact sensor was used in an experimental set-up, which was designed and developed in-house for non-destructive material discrimination studies. Materials of different densities (iron, glass, wood, and plastic) were used as test specimens for material discrimination studies. The analysis of output voltage waveforms obtained reveals lots of valuable information about the impacted material. Impact sensor was able to discriminate the test materials on the basis of the difference in their densities. The output response of packaged impact sensor shows high linearity and repeatability. The packaged impact sensor discussed in this paper is highly sensitive, reliable, and cost-effective.
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Bentonite clays are proven to be attractive as buffer and backfill material in high-level nuclear waste repositories around the world. A quick estimation of swelling pressures of the compacted bentonites for different clay-water-electrolyte interactions is essential in the design of buffer and backfill materials. The theoretical studies on the swelling behavior of bentonites are based on diffuse double layer (DDL) theory. To establish theoretical relationship between void ratio and swelling pressure (e versus P), evaluation of elliptic integral and inverse analysis are unavoidable. In this paper, a novel procedure is presented to establish theoretical relationship of e versus P based on the Gouy-Chapman method. The proposed procedure establishes a unique relationship between electric potentials of interacting and non-interacting diffuse clay-water-electrolyte systems. A procedure is, thus, proposed to deduce the relation between swelling pressures and void ratio from the established relation between electric potentials. This approach is simple and alleviates the need for elliptic integral evaluation and also the inverse analysis. Further, application of the proposed approach to estimate swelling pressures of four compacted bentonites, for example, MX 80, Febex, Montigel and Kunigel V1, at different dry densities, shows that the method is very simple and predicts solutions with very good accuracy. Moreover, the proposed procedure provides continuous distributions of e versus P and thus it is computationally efficient when compared with the existing techniques.
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This paper reports on the mass transport behavior of infinitely extended, continuous, and very thin metallic films under the influence of electric current. Application of direct current of high densities (> 10(8) A/m(2)) results in visible melting of thin film at only one of the electrodes, and the melt then flows towards the other electrode in a circularly symmetric fashion forming a microscale ring pattern. For the two tested thin film systems, namely Cr and Al, of thicknesses ranging from 4 to 20 nm, the above directional flow consistently occurred from cathode to anode and anode to cathode, respectively. Furthermore, application of alternating electric current results in flow of the liquid material from both the electrodes. The dependence of critical flow behavior parameters, such as flow direction, flow velocity, and evolution of the ring diameter, are experimentally determined. Analytical models based on the principles of electromigration in liquid-phase materials are developed to explain the experimental observations.
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This paper reports on the characterization of an integrated micro-fluidic platform for controlled electrical lysis of biological cells and subsequent extraction of intracellular biomolecules. The proposed methodology is capable of high throughput electrical cell lysis facilitated by nano-composite coated electrodes. The nano-composites are synthesized using Carbon Nanotube and ZnO nanorod dispersion in polymer. Bacterial cells are used to demonstrate the lysis performance of these nanocomposite electrodes. Investigation of electrical lysis in the microchannel is carried out under different parameters, one with continuous DC application and the other under DC biased AC electric field. Lysis in DC field is dependent on optimal field strength and governed by the cell type. By introducing the AC electrical field, the electrokinetics is controlled to prevent cell clogging in the micro-channel and ensure uniform cell dispersion and lysis. Lysis mechanism is analyzed with time-resolved fluorescence imaging which reveal the time scale of electrical lysis and explain the dynamic behavior of GFP-expressing E. coli cells under the electric field induced by nanocomposite electrodes. The DNA and protein samples extracted after lysis are compared with those obtained from a conventional chemical lysis method by using a UV-Visible spectroscopy and fluorimetry. The paper also focuses on the mechanistic understanding of the nano-composite coating material and the film thickness on the leakage charge densities which lead to differential lysis efficiency.
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Identifying the determinants of neuronal energy consumption and their relationship to information coding is critical to understanding neuronal function and evolution. Three of the main determinants are cell size, ion channel density, and stimulus statistics. Here we investigate their impact on neuronal energy consumption and information coding by comparing single-compartment spiking neuron models of different sizes with different densities of stochastic voltage-gated Na+ and K+ channels and different statistics of synaptic inputs. The largest compartments have the highest information rates but the lowest energy efficiency for a given voltage-gated ion channel density, and the highest signaling efficiency (bits spike(-1)) for a given firing rate. For a given cell size, our models revealed that the ion channel density that maximizes energy efficiency is lower than that maximizing information rate. Low rates of small synaptic inputs improve energy efficiency but the highest information rates occur with higher rates and larger inputs. These relationships produce a Law of Diminishing Returns that penalizes costly excess information coding capacity, promoting the reduction of cell size, channel density, and input stimuli to the minimum possible, suggesting that the trade-off between energy and information has influenced all aspects of neuronal anatomy and physiology.
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The microstructure and mechanical properties of nanocrystalline Pd films prepared by magnetron sputtering have been investigated as a function of strain. The films were deposited onto polyimide substrates and tested in tensile mode. In order to follow the deformation processes in the material, several samples were strained to defined straining states, up to a maximum engineering strain of 10%, and prepared for post-mortem analysis. The nanocrystalline structure was investigated by quantitative automated crystal orientation mapping (ACOM) in a transmission electron microscope (TEM), identifying grain growth and twinning/detwinning resulting from dislocation activity as two of the mechanisms contributing to the macroscopic deformation. Depending on the initial twin density, the samples behaved differently. For low initial twin densities, an increasing twin density was found during straining. On the other hand, starting from a higher twin density, the twins were depleted with increasing strain. The findings from ACOM-TEM were confirmed by results from molecular dynamics (MD) simulations and from conventional and in-situ synchrotron X-ray diffraction (CXRD, SXRD) experiments.
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We study the effects of optically thin radiative cooling on the structure of radiatively inefficient accretion flows (RIAFs). The flow structure is geometrically thick, and independent of the gas density and cooling, if the cooling time is longer than the viscous time-scale (i.e. t(cool) greater than or similar to t(visc)). For higher densities, the gas can cool before it can accrete and forms the standard geometrically thin, optically thick Shakura-Sunyaev disc. For usual cooling processes (such as bremsstrahlung), we expect an inner hot flow and an outer thin disc. For a short cooling time the accretion flow separates into two phases: a radiatively inefficient hot coronal phase and a cold thin disc. We argue that there is an upper limit on the density of the hot corona corresponding to a critical value of t(cool)/t(ff)( similar to 10-100), the ratio of the cooling time and the free-fall time. Based on our simulations, we have developed a model for transients observed in black hole X-ray binaries (XRBs). An XRB in a quiescent hot RIAF state can transition to a cold blackbody-dominated state because of an increase in the mass accretion rate. The transition from a thin disc to a RIAF happens because of mass exhaustion due to accretion; the transition happens when the cooling time becomes longer than the viscous time at inner radii. Since the viscous time-scale for a geometrically thin disc is quite long, the high-soft state is expected to be long-lived. The different time-scales in black hole transients correspond to different physical processes such as viscous evolution, cooling and free fall. Our model captures the overall features of observed state transitions in XRBs.