359 resultados para Bio-energy


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We propose a simple and energy efficient distributed change detection scheme for sensor networks based on Page's parametric CUSUM algorithm. The sensor observations are IID over time and across the sensors conditioned on the change variable. Each sensor runs CUSUM and transmits only when the CUSUM is above some threshold. The transmissions from the sensors are fused at the physical layer. The channel is modeled as a multiple access channel (MAC) corrupted with IID noise. The fusion center which is the global decision maker, performs another CUSUM to detect the change. We provide the analysis and simulation results for our scheme and compare the performance with an existing scheme which ensures energy efficiency via optimal power selection.

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A modified form of Green's integral theorem is employed to derive the energy identity in any water wave diffraction problem in a single-layer fluid for free-surface boundary condition with higher-order derivatives. For a two-layer fluid with free-surface boundary condition involving higher-order derivatives, two forms of energy identities involving transmission and reflection coefficients for any wave diffraction problem are also derived here by the same method. Based on this modified Green's theorem, hydrodynamic relations such as the energy-conservation principle and modified Haskind–Hanaoka relation are derived for radiation and diffraction problems in a single as well as two-layer fluid.

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Traditionally, an instruction decoder is designed as a monolithic structure that inhibit the leakage energy optimization. In this paper, we consider a split instruction decoder that enable the leakage energy optimization. We also propose a compiler scheduling algorithm that exploits instruction slack to increase the simultaneous active and idle duration in instruction decoder. The proposed compiler-assisted scheme obtains a further 14.5% reduction of energy consumption of instruction decoder over a hardware-only scheme for a VLIW architecture. The benefits are 17.3% and 18.7% in the context of a 2-clustered and a 4-clustered VLIW architecture respectively.

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In this paper, we are concerned with energy efficient area monitoring using information coverage in wireless sensor networks, where collaboration among multiple sensors can enable accurate sensing of a point in a given area-to-monitor even if that point falls outside the physical coverage of all the sensors. We refer to any set of sensors that can collectively sense all points in the entire area-to-monitor as a full area information cover. We first propose a low-complexity heuristic algorithm to obtain full area information covers. Using these covers, we then obtain the optimum schedule for activating the sensing activity of various sensors that maximizes the sensing lifetime. The scheduling of sensor activity using the optimum schedules obtained using the proposed algorithm is shown to achieve significantly longer sensing lifetimes compared to those achieved using physical coverage. Relaxing the full area coverage requirement to a partial area coverage (e.g., 95% of area coverage as adequate instead of 100% area coverage) further enhances the lifetime.

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A low temperature polyol process, based on glycolaldehyde mediated partial reduction of FeCl3 center dot 6H(2)O at 120 degrees C in the presence of sodium acetate as an alkali source and 2,2'-(ethylenedioxy)-bis-(ethylamine) as an electrostatic stabilizer has been used for the gram-scale preparation of biocompatible, water-dispersible, amine functionalized magnetite nanoparticles (MNPs) with an average diameter of 6 +/- 0.75 nm. With a reasonably high magnetization (37.8 e.m.u.) and amine groups on the outer surface of the nanoparticles, we demonstrated the magnetic separation and concentration implications of these ultrasmall particles in immunoassay. MRI studies indicated that these nanoparticles had the desired relaxivity for T-2 contrast enhancement in vivo. In vitro biocompatibility, cell uptake and MR imaging studies established that these nanoparticles were safe in clinical dosages and by virtue of their ultrasmall sizes and positively charged surfaces could be easily internalized by cancer cells. All these positive attributes make these functional nanoparticles a promising platform for further in vitro and in vivo evaluations.

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Based on the measurements of Alcock and Zador, Grundy et al. estimated an uncertainty of the order of +/- 5 kJ mol(-1) for the standard Gibbs energy of formation of MnO in a recent assessment. Since the evaluation of thermodynamic data for the higher oxides Mn3O4, Mn2O3, and MnO2 depends on values for MnO, a redetermination of its Gibbs energy of formation was undertaken in the temperature range from 875 to 1300 K using a solid-state electrochemical cell incorporating yttria-doped thoria (YDT) as the solid electrolyte and Fe + Fe1-delta O as the reference electrode. The cell can be presented as Pt, Mn + MnO/YDT/Fe + Fe1+delta O, Pt Since the metals Fe and Mn undergo phase transitions in the temperature range of measurement, the reversible emf of the cell is represented by the three linear segments. Combining the emf with the oxygen potential for the reference electrode, the standard Gibbs energy of formation of MnO from alpha-Mn and gaseous diatomic oxygen in the temperature range from 875 to 980 K is obtained as: Delta G(f)(o)/Jmol(-1)(+/- 250) = -385624 + 73.071T From 980 to 1300 K the Gibbs energy of formation of MnO from beta-Mn and oxygen gas is given by: Delta G(f)(o)/Jmol(-1)(+/- 250) = -387850 + 75.36T The new data are in excellent agreement with the earlier measurements of Alcock and Zador. Grundy et al. incorrectly analyzed the data of Alcock and Zador showing relatively large difference (+/- 5 kJ mol(-1)) in Gibbs energies of MnO from their two cells with Fe + Fe1-delta O and Ni + NiO as reference electrodes. Thermodynamic data for MnO is reassessed in the light of the new measurements. A table of refined thermodynamic data for MnO from 298.15 to 2000 K is presented.

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The ground state and low energy excitations of the SU(m|n) supersymmetric Haldane–Shastry spin chain are analyzed. In the thermodynamic limit, it is found that the ground state degeneracy is finite only for the SU(m|0) and SU(m|1) spin chains, while the dispersion relation for the low energy and low momentum excitations is linear for all values of m and n. We show that the low energy excitations of the SU(m|1) spin chain are described by a conformal field theory of m non-interacting Dirac fermions which have only positive energies; the central charge of this theory is m/2. Finally, for ngreater-or-equal, slanted1, the partition functions of the SU(m|n) Haldane–Shastry spin chain and the SU(m|n) Polychronakos spin chain are shown to be related in a simple way in the thermodynamic limit at low temperatures.

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Acoustic emission (AE) energy, instead of amplitude, associated with each of the event is used to estimate the fracture process zone (FPZ) size. A steep increase in the cumulative AE energy of the events with respect to time is correlated with the formation of FPZ. Based on the AE energy released during these events and the locations of the events, FPZ size is obtained. The size-independent fracture energy is computed using the expressions given in the boundary effect model by least squares method since over-determined system of equations are obtained when data from several specimens are used. Instead of least squares method a different method is suggested in which the transition ligament length, measured from the plot of histograms of AE events plotted over the un-cracked ligament, is used directly to obtain size-independent fracture energy. The fracture energy thus calculated seems to be size-independent.

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We describe a noniterative method for recovering optical absorption coefficient distribution from the absorbed energy map reconstructed using simulated and noisy boundary pressure measurements. The source reconstruction problem is first solved for the absorbed energy map corresponding to single- and multiple-source illuminations from the side of the imaging plane. It is shown that the absorbed energy map and the absorption coefficient distribution, recovered from the single-source illumination with a large variation in photon flux distribution, have signal-to-noise ratios comparable to those of the reconstructed parameters from a more uniform photon density distribution corresponding to multiple-source illuminations. The absorbed energy map is input as absorption coefficient times photon flux in the time-independent diffusion equation (DE) governing photon transport to recover the photon flux in a single step. The recovered photon flux is used to compute the optical absorption coefficient distribution from the absorbed energy map. In the absence of experimental data, we obtain the boundary measurements through Monte Carlo simulations, and we attempt to address the possible limitations of the DE model in the overall reconstruction procedure.

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We demonstrate that commonly face-centered cubic (fcc) metallic nanowires can be stabilized in hexagonal structures even when their surface energy contribution is relatively small. With a modified electrochemical growth process, we have grown purely single-crystalline 4H silver nanowires (AgNWs) of diameters as large as 100 nm within nanoporous anodic alumina and polycarbonate templates. The growth process is not limited by the/Ag Nernst equilibrium potential, and time-resolved imaging with high-resolution transmission electron microscopy (TEM) indicates a kinematically new mechanism of nanowire growth. Most importantly, our experiments aim to separate the effects of confinement and growth conditions on the crystal structure of nanoscale systems.

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We consider a scenario in which a wireless sensor network is formed by randomly deploying n sensors to measure some spatial function over a field, with the objective of computing a function of the measurements and communicating it to an operator station. We restrict ourselves to the class of type-threshold functions (as defined in the work of Giridhar and Kumar, 2005), of which max, min, and indicator functions are important examples: our discussions are couched in terms of the max function. We view the problem as one of message-passing distributed computation over a geometric random graph. The network is assumed to be synchronous, and the sensors synchronously measure values and then collaborate to compute and deliver the function computed with these values to the operator station. Computation algorithms differ in (1) the communication topology assumed and (2) the messages that the nodes need to exchange in order to carry out the computation. The focus of our paper is to establish (in probability) scaling laws for the time and energy complexity of the distributed function computation over random wireless networks, under the assumption of centralized contention-free scheduling of packet transmissions. First, without any constraint on the computation algorithm, we establish scaling laws for the computation time and energy expenditure for one-time maximum computation. We show that for an optimal algorithm, the computation time and energy expenditure scale, respectively, as Theta(radicn/log n) and Theta(n) asymptotically as the number of sensors n rarr infin. Second, we analyze the performance of three specific computation algorithms that may be used in specific practical situations, namely, the tree algorithm, multihop transmission, and the Ripple algorithm (a type of gossip algorithm), and obtain scaling laws for the computation time and energy expenditure as n rarr infin. In particular, we show that the computation time for these algorithms scales as Theta(radicn/lo- g n), Theta(n), and Theta(radicn log n), respectively, whereas the energy expended scales as , Theta(n), Theta(radicn/log n), and Theta(radicn log n), respectively. Finally, simulation results are provided to show that our analysis indeed captures the correct scaling. The simulations also yield estimates of the constant multipliers in the scaling laws. Our analyses throughout assume a centralized optimal scheduler, and hence, our results can be viewed as providing bounds for the performance with practical distributed schedulers.

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In this paper we employ the phenomenon of bending deformation induced transport of cations via the polymer chains in the thickness direction of an electro-active polymer (EAP)-metal composite thin film for mechanical energy harvesting. While EAPs have been applied in the past in actuators and artificial muscles, promising applications of such materials in hydrodynamic and vibratory energy harvesting are reported in this paper. For this, functionalization of EAPs with metal electrodes is the key factor in improving the energy harvesting efficiency. Unlike Pt-based electrodes, Ag-based electrodes have been deposited on an EAP membrane made of Nafion. The developed ionic metal polymer composite (IPMC) membrane is subjected to a dynamic bending load, hydrodynamically, and evaluated for the voltage generated against an external electrical load. An increase of a few orders of magnitude has been observed in the harvested energy density and power density in air, deionized water and in electrolyte solutions with varying concentrations of sodium chloride (NaCl) as compared to Pt-based IPMC performances reported in the published literature. This will have potential applications in hydrodynamic and residual environmental energy harvesting to power sensors and actuators based on micro-andn nano-electro-mechanical systems (MEMS and NEMS) for biomedical,maerospace and oceanic applications.

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We study the process of electronic excitation energy transfer from a fluorophore to the electronic energy levels of a single-walled carbon nanotube. The matrix element for the energy transfer involves the Coulombic interaction between the transition densities on the donor and the acceptor. In the Foumlrster approach, this is approximated as the interaction between the corresponding transition dipoles. For energy transfer from a dye to a nanotube, one can use the dipole approximation for the dye, but not for the nanotube. We have therefore calculated the rate using an approach that avoids the dipole approximation for the nanotube. We find that for the metallic nanotubes, the rate has an exponential dependence if the energy that is to be transferred, h is less than a threshold and a d(-5) dependence otherwise. The threshold is the minimum energy required for a transition other than the k(i,perpendicular to)=0 and l=0 transition. Our numerical evaluation of the rate of energy transfer from the dye pyrene to a (5,5) carbon nanotube, which is metallic leads to a distance of similar to 165 A degrees up to which energy transfer is appreciable. For the case of transfer to semiconducting carbon nanotubes, apart from the process of transfer to the electronic energy levels within the one electron picture, we also consider the possibility of energy transfer to the lowest possible excitonic state. Transfer to semiconducting carbon nanotubes is possible only if>=epsilon(g)-epsilon(b). The long range behavior of the rate of transfer has been found to have a d(-5) dependence if h >=epsilon(g). But, when the emission energy of the fluorophore is in the range epsilon(g)>h >=epsilon(g)-epsilon(b), the rate has an exponential dependence on the distance. For the case of transfer from pyrene to the semiconducting (6,4) carbon nanotube, energy transfer is found to be appreciable up to a distance of similar to 175 A degrees.

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In this paper, the effects of energy quantization on different single-electron transistor (SET) circuits (logic inverter, current-biased circuits, and hybrid MOS-SET circuits) are analyzed through analytical modeling and Monte Carlo simulations. It is shown that energy quantizationmainly increases the Coulomb blockade area and Coulomb blockade oscillation periodicity, and thus, affects the SET circuit performance. A new model for the noise margin of the SET inverter is proposed, which includes the energy quantization effects. Using the noise margin as a metric, the robustness of the SET inverter is studied against the effects of energy quantization. An analytical expression is developed, which explicitly defines the maximum energy quantization (termed as ``quantization threshold'') that an SET inverter can withstand before its noise margin falls below a specified tolerance level. The effects of energy quantization are further studiedfor the current-biased negative differential resistance (NDR) circuitand hybrid SETMOS circuit. A new model for the conductance of NDR characteristics is also formulated that explains the energy quantization effects.

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The ferroelectric Pb(Zr0.48Ti0.52)O-3 (PZT) thin films prepared by the pulsed laser deposition technique were studied for their response to high energy lithium ion irradiation through impedance spectroscopy. The Debye peaks, observed in the impedance and modulus plots of irradiatedfilms, shifts towards higher frequencies compared to those of unirradiated films. This is equivalent to the trend observed with increase in temperature in the unirradiated films due to the dielectric relaxation. The irradiated films showed a decrease in the grain resistance compared to the unirradiated films. The activation energy of dielectric relaxation increases from 1.25 eV of unirradiated film to 1.62 eV of irradiated film. The observed modifications in the irradiated film were ascribed to the modifications in the grain structure due to the high value of electronic energy loss.