990 resultados para Efficient elliptic curve arithmetic


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A balance between excitatory and inhibitory synaptic currents is thought to be important for several aspects of information processing in cortical neurons in vivo, including gain control, bandwidth and receptive field structure. These factors will affect the firing rate of cortical neurons and their reliability, with consequences for their information coding and energy consumption. Yet how balanced synaptic currents contribute to the coding efficiency and energy efficiency of cortical neurons remains unclear. We used single compartment computational models with stochastic voltage-gated ion channels to determine whether synaptic regimes that produce balanced excitatory and inhibitory currents have specific advantages over other input regimes. Specifically, we compared models with only excitatory synaptic inputs to those with equal excitatory and inhibitory conductances, and stronger inhibitory than excitatory conductances (i.e. approximately balanced synaptic currents). Using these models, we show that balanced synaptic currents evoke fewer spikes per second than excitatory inputs alone or equal excitatory and inhibitory conductances. However, spikes evoked by balanced synaptic inputs are more informative (bits/spike), so that spike trains evoked by all three regimes have similar information rates (bits/s). Consequently, because spikes dominate the energy consumption of our computational models, approximately balanced synaptic currents are also more energy efficient than other synaptic regimes. Thus, by producing fewer, more informative spikes approximately balanced synaptic currents in cortical neurons can promote both coding efficiency and energy efficiency.

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A new molecular probe based on an oxidized bis-indolyl skeleton has been developed for rapid and sensitive visual detection of cyanide ions in water and also for the detection of endogenously bound cyanide. The probe allows the naked-eye detection of cyanide ions in water with a visual color change from red to yellow ((max)=80nm) with the immediate addition of the probe. It shows high selectivity towards the cyanide ion without any interference from other anions. The detection of cyanide by the probe is ratiometric, thus making the detection quantitative. A Michael-type addition reaction of the probe with the cyanide ion takes place during this chemodosimetric process. In water, the detection limit was found to be at the parts per million level, which improved drastically when a neutral micellar medium was employed, and it showed a parts-per-billion-level detection, which is even 25-fold lower than the permitted limits of cyanide in water. The probe could also efficiently detect the endogenously bound cyanide in cassava (a staple food) with a clear visual color change without requiring any sample pretreatment and/or any special reaction conditions such as pH or temperature. Thus the probe could serve as a practical naked-eye probe for in-field experiments without requiring any sophisticated instruments.

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With the development of deep sequencing methodologies, it has become important to construct site saturation mutant (SSM) libraries in which every nucleotide/codon in a gene is individually randomized. We describe methodologies for the rapid, efficient, and economical construction of such libraries using inverse polymerase chain reaction (PCR). We show that if the degenerate codon is in the middle of the mutagenic primer, there is an inherent PCR bias due to the thermodynamic mismatch penalty, which decreases the proportion of unique mutants. Introducing a nucleotide bias in the primer can alleviate the problem. Alternatively, if the degenerate codon is placed at the 5' end, there is no PCR bias, which results in a higher proportion of unique mutants. This also facilitates detection of deletion mutants resulting from errors during primer synthesis. This method can be used to rapidly generate SSM libraries for any gene or nucleotide sequence, which can subsequently be screened and analyzed by deep sequencing. (C) 2013 Elsevier Inc. All rights reserved.

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A novel approach toward the synthesis of hollow silver nanoparticle (NP) cages built with building blocks of silver NPs by layer-by-layer (LbL) assembly is demonstrated. The size of the NP cage depends on the size of template used for the LbL assembly. The microcages showed a uniform distribution of spherical silver nanoparticles with an average diameter of 20 +/- 5 nm, which increased to 40 +/- S nm when the AgNO3 concentration was increased from 25 to 50 mM. Heat treatment of the polyelectrolyte capsules at 80 degrees C near their pK(a) values yielded intact nano/micro cages. These cages produced a higher conversion for the epoxidation of olefins and maintained their catalytic activity even after four successive uses. The nanocages exhibited unique and attractive characteristics for metal catalytic systems, thus offering the scope for further development as heterogeneous catalysts.

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The present article describes a working or combined calibration curve in laser-induced breakdown spectroscopic analysis, which is the cumulative result of the calibration curves obtained from neutral and singly ionized atomic emission spectral lines. This working calibration curve reduces the effect of change in matrix between different zone soils and certified soil samples because it includes both the species' (neutral and singly ionized) concentration of the element of interest. The limit of detection using a working calibration curve is found better as compared to its constituent calibration curves (i.e., individual calibration curves). The quantitative results obtained using the working calibration curve is in better agreement with the result of inductively coupled plasma-atomic emission spectroscopy as compared to the result obtained using its constituent calibration curves.

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In this paper, we present a spectral finite element model (SFEM) using an efficient and accurate layerwise (zigzag) theory, which is applicable for wave propagation analysis of highly inhomogeneous laminated composite and sandwich beams. The theory assumes a layerwise linear variation superimposed with a global third-order variation across the thickness for the axial displacement. The conditions of zero transverse shear stress at the top and bottom and its continuity at the layer interfaces are subsequently enforced to make the number of primary unknowns independent of the number of layers, thereby making the theory as efficient as the first-order shear deformation theory (FSDT). The spectral element developed is validated by comparing the present results with those available in the literature. A comparison of the natural frequencies of simply supported composite and sandwich beams obtained by the present spectral element with the exact two-dimensional elasticity and FSDT solutions reveals that the FSDT yields highly inaccurate results for the inhomogeneous sandwich beams and thick composite beams, whereas the present element based on the zigzag theory agrees very well with the exact elasticity solution for both thick and thin, composite and sandwich beams. A significant deviation in the dispersion relations obtained using the accurate zigzag theory and the FSDT is also observed for composite beams at high frequencies. It is shown that the pure shear rotation mode remains always evanescent, contrary to what has been reported earlier. The SFEM is subsequently used to study wavenumber dispersion, free vibration and wave propagation time history in soft-core sandwich beams with composite faces for the first time in the literature. (C) 2014 Elsevier Ltd. All rights reserved.

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The layered ternary chalcogenide, palladium phosphorous sulphide (PdPS), and its composite with reduced graphene oxide are shown to be efficient hydrogen evolution electrocatalysts. The Tafel slope and the exchange current density values associated with hydrogen evolution reaction are determined to be 46 mV dec(-1) and 1.4 x 10(-4) A cm(-2) respectively.

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The efficient deprotection of several acetals, dithioacetals, and tetrahydropyranyl (THP) ethers under ambient conditions, using chloral hydrate in hexane, is described. Excellent yields were realized for a wide range of both aliphatic and aromatic substrates. The method is characterized by mild conditions (room temperatures or below), simple workup, and the ready availability of chloral hydrate. High chemoselectivity was also observed in the deprotection, acetonides, esters, and amides being unaffected under the reaction conditions. Products were generally purified chromatographically and identified spectrally. These results constitute a novel addition to current methodology involving a widely employed deprotection tactic in organic synthesis. It seems likely that the mechanism of the reaction involves adsorption of the substrate on the surface of the sparingly soluble chloral hydrate.

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Programming for parallel architectures that do not have a shared address space is extremely difficult due to the need for explicit communication between memories of different compute devices. A heterogeneous system with CPUs and multiple GPUs, or a distributed-memory cluster are examples of such systems. Past works that try to automate data movement for distributed-memory architectures can lead to excessive redundant communication. In this paper, we propose an automatic data movement scheme that minimizes the volume of communication between compute devices in heterogeneous and distributed-memory systems. We show that by partitioning data dependences in a particular non-trivial way, one can generate data movement code that results in the minimum volume for a vast majority of cases. The techniques are applicable to any sequence of affine loop nests and works on top of any choice of loop transformations, parallelization, and computation placement. The data movement code generated minimizes the volume of communication for a particular configuration of these. We use a combination of powerful static analyses relying on the polyhedral compiler framework and lightweight runtime routines they generate, to build a source-to-source transformation tool that automatically generates communication code. We demonstrate that the tool is scalable and leads to substantial gains in efficiency. On a heterogeneous system, the communication volume is reduced by a factor of 11X to 83X over state-of-the-art, translating into a mean execution time speedup of 1.53X. On a distributed-memory cluster, our scheme reduces the communication volume by a factor of 1.4X to 63.5X over state-of-the-art, resulting in a mean speedup of 1.55X. In addition, our scheme yields a mean speedup of 2.19X over hand-optimized UPC codes.

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Precise experimental implementation of unitary operators is one of the most important tasks for quantum information processing. Numerical optimization techniques are widely used to find optimized control fields to realize a desired unitary operator. However, finding high-fidelity control pulses to realize an arbitrary unitary operator in larger spin systems is still a difficult task. In this work, we demonstrate that a combination of the GRAPE algorithm, which is a numerical pulse optimization technique, and a unitary operator decomposition algorithm Ajoy et al., Phys. Rev. A 85, 030303 (2012)] can realize unitary operators with high experimental fidelity. This is illustrated by simulating the mirror-inversion propagator of an XY spin chain in a five-spin dipolar coupled nuclear spin system. Further, this simulation has been used to demonstrate the transfer of entangled states from one end of the spin chain to the other end.

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Single fluid schemes that rely on an interface function for phase identification in multicomponent compressible flows are widely used to study hydrodynamic flow phenomena in several diverse applications. Simulations based on standard numerical implementation of these schemes suffer from an artificial increase in the width of the interface function owing to the numerical dissipation introduced by an upwind discretization of the governing equations. In addition, monotonicity requirements which ensure that the sharp interface function remains bounded at all times necessitate use of low-order accurate discretization strategies. This results in a significant reduction in accuracy along with a loss of intricate flow features. In this paper we develop a nonlinear transformation based interface capturing method which achieves superior accuracy without compromising the simplicity, computational efficiency and robustness of the original flow solver. A nonlinear map from the signed distance function to the sigmoid type interface function is used to effectively couple a standard single fluid shock and interface capturing scheme with a high-order accurate constrained level set reinitialization method in a way that allows for oscillation-free transport of the sharp material interface. Imposition of a maximum principle, which ensures that the multidimensional preconditioned interface capturing method does not produce new maxima or minima even in the extreme events of interface merger or breakup, allows for an explicit determination of the interface thickness in terms of the grid spacing. A narrow band method is formulated in order to localize computations pertinent to the preconditioned interface capturing method. Numerical tests in one dimension reveal a significant improvement in accuracy and convergence; in stark contrast to the conventional scheme, the proposed method retains its accuracy and convergence characteristics in a shifted reference frame. Results from the test cases in two dimensions show that the nonlinear transformation based interface capturing method outperforms both the conventional method and an interface capturing method without nonlinear transformation in resolving intricate flow features such as sheet jetting in the shock-induced cavity collapse. The ability of the proposed method in accounting for the gravitational and surface tension forces besides compressibility is demonstrated through a model fully three-dimensional problem concerning droplet splash and formation of a crownlike feature. (C) 2014 Elsevier Inc. All rights reserved.

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Following rising demands in positioning with GPS, low-cost receivers are becoming widely available; but their energy demands are still too high. For energy efficient GPS sensing in delay-tolerant applications, the possibility of offloading a few milliseconds of raw signal samples and leveraging the greater processing power of the cloud for obtaining a position fix is being actively investigated. In an attempt to reduce the energy cost of this data offloading operation, we propose Sparse-GPS(1): a new computing framework for GPS acquisition via sparse approximation. Within the framework, GPS signals can be efficiently compressed by random ensembles. The sparse acquisition information, pertaining to the visible satellites that are embedded within these limited measurements, can subsequently be recovered by our proposed representation dictionary. By extensive empirical evaluations, we demonstrate the acquisition quality and energy gains of Sparse-GPS. We show that it is twice as energy efficient than offloading uncompressed data, and has 5-10 times lower energy costs than standalone GPS; with a median positioning accuracy of 40 m.

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We show that the hybrids of single-layer graphene oxide with manganese ferrite magnetic nanoparticles have the best adsorption properties for efficient removal of Pb(II), As(III), and As(V) from contaminated water. The nanohybrids prepared by coprecipitation technique were characterized using atomic force and scanning electron microscopies, Fourier transformed infrared spectroscopy, Raman spectroscopy, X-ray diffraction, and surface area measurements. Magnetic character of the nanohybrids was ascertained by a vibrating sample magnetometer. Batch experiments were carried out to quantify the adsorption kinetics and adsorption capacities of the nanohybrids and compared with the bare nanoparticles of MnFe2O4. The adsorption data from our experiments fit the Langmuir isotherm, yielding the maximum adsorption capacity higher than the reported values so far. Temperature-dependent adsorption studies have been done to estimate the free energy and enthalpy of adsorption. Reusability, ease of magnetic separation, high removal efficiency, high surface area, and fast kinetics make these nanohybrids very attractive candidates for low-cost adsorbents for the effective coremoval of heavy metals from contaminated water.

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Few-layer transition metal dichalcogenide alloys based on molybdenum sulphoselenides MoS2(1-x)Se2x] possess higher hydrogen evolution (HER) activity compared to pristine few-layer MoS2 and MoSe2. Variation of the sulphur or selenium content in the parent dichalcogenides reveals a systematic structure-activity relationship for different compositions of alloys, and it is found that the composition MoS1.0Se1.0 shows the highest HER activity amongst the catalysts studied. The tunable electronic structure of MoS2/MoSe2 upon Se/S incorporation probably assists in the realization of high HER activity.

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A rapid, metal-free and solvent-free (very low loading of solvent in few cases) reaction conditions for synthesizing thioamides and amides using a Bronsted super acid such as triflic acid has been developed. This method shows a broad substrate scope with a variety of electron-rich arenes including thiophene derivatives. The reaction works well for both aromatic as well as aliphatic isothiocyanates. Most of the thioamides are obtained in excellent yields in short reaction times and in most of the examples, a simple work up procedure has been developed which does not require further purification.