93 resultados para Efficiency losses
Resumo:
The success of AAV2 mediated hepatic gene transfer in human trials for diseases such as hemophilia has been hampered by a combination of low transduction efficiency and a robust immune response directed against these vectors. We have previously shown that AAV2 is targeted for destruction in the cytoplasm by the host-cellular kinase/ubiquitination/proteasomal degradation machinery and modification of the serine(S)/threonine(T) kinase and lysine(K) targets on AAV capsid is beneficial. Thus targeted single mutations of S/T>A(S489A, S498A, T251A) and K>R (K532R) improved the efficiency of gene transfer in vivo as compared to wild type (WT)-AAV2 vectors (∼6-14 fold). In the present study, we evaluated if combined alteration of the phosphodegrons (PD), which are the phosphorylation sites recognized as degradation signals by ubiquitin ligases, improves further the gene transfer efficiency. Thus, we generated four multiple mutant vectors (PD: 1+3, S489A+K532R, PD: 1+3, S489A+K532R together with T251 residue which did not lie in any of the phosphodegrons but had shown increased transduction efficiency compared to the WT-AAV2 vector (∼6 fold) and was also conserved in 9 out of 10 AAV serotypes (AAV 1 to 10), PD: 1+3, S489A+K532R+S498A and a fourth combination of PD: 3, K532R+T251. We then evaluated them in vitro and in vivo and compared their gene transfer efficiency with either the WT-AAV2 or the best single mutant S489A-AAV2 vector. The novel multiple mutations on the AAV2 capsid did not affect the overall vector packaging efficiency. All the multiple AAV2 mutants showed superior transduction efficiency in HeLa cells in vitro when compared to either the WT (62-72% Vs 21%) or the single mutant S489A (62-72% Vs 50%) AAV2 vectors as demonstrated by FACS analysis (Fig. 1A). On hepatic gene transfer with 5x10^10 vgs per animal in C57BL/6 mice, all the multiple mutants showed increased transgene expression compared to either the WT-AAV2 (∼15-23 fold) or the S489A single mutant vector (∼2-3 fold) (Fig.1B and C). These novel multiple mutant AAV2 vectors also showed higher vector copy number in murine hepatocytes 4 weeks post transduction, as compared to the WT-AAV2 (∼5-6 Vs 1.4 vector copies/diploid genome) and further higher when compared to the single mutant S489A(∼5-6 fold Vs 3.8 fold) (Fig.1D). Further ongoing studies will demonstrate the therapeutic benefit of one or more of the multiple mutants vectors in preclinical models of hemophilia.
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Carbon Nanotubes (CNTs) grown on substrates are potential electron sources in field emission applications. Several studies have reported the use of CNTs in field emission devices, including field emission displays, X-ray tube, electron microscopes, cathode-ray lamps, etc. Also, in recent years, conventional cold field emission cathodes have been realized in micro-fabricated arrays for medical X-ray imaging. CNTbased field emission cathode devices have potential applications in a variety of industrial and medical applications, including cancer treatment. Field emission performance of a single isolated CNT is found to be remarkable, but the situation becomes complex when an array of CNTs is used. At the same time, use of arrays of CNTs is practical and economical. Indeed, such arrays on cathode substrates can be grown easily and their collective dynamics can be utilized in a statistical sense such that the average emission intensity is high enough and the collective dynamics lead to longer emission life. The authors in their previous publications had proposed a novel approach to obtain stabilized field emission current from a stacked CNT array of pointed height distribution. A mesoscopic modeling technique was employed, which took into account electro-mechanical forces in the CNTs, as well as transport of conduction electron coupled with electron phonon induced heat generation from the CNT tips. The reported analysis of pointed arrangements of the array showed that the current density distribution was greatly localized in the middle of the array, the scatter due to electrodynamic force field was minimized, and the temperature transients were much smaller compared to those in an array with random height distribution. In the present paper we develop a method to compute the emission efficiency of the CNT array in terms of the amount of electrons hitting the anode surface using trajectory calculations. Effects of secondary electron emission and parasitic capacitive nonlinearity on the current-voltage signals are accounted. Field emission efficiency of a stacked CNT array with various pointed height distributions are compared to that of arrays with random and uniform height distributions. Effect of this parasitic nonlinearity on the emission switch-on voltage is estimated by model based simulation and Monte Carlo method.
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Single receive antenna selection (AS) is a popular method for obtaining diversity benefits without the additional costs of multiple radio receiver chains. Since only one antenna receives at any time, the transmitter sends a pilot multiple times to enable the receiver to estimate the channel gains of its N antennas to the transmitter and select an antenna. In time-varying channels, the channel estimates of different antennas are outdated to different extents. We analyze the symbol error probability (SEP) in time-varying channels of the N-pilot and (N+1)-pilot AS training schemes. In the former, the transmitter sends one pilot for each receive antenna. In the latter, the transmitter sends one additional pilot that helps sample the channel fading process of the selected antenna twice. We present several new results about the SEP, optimal energy allocation across pilots and data, and optimal selection rule in time-varying channels for the two schemes. We show that due to the unique nature of AS, the (N+1)-pilot scheme, despite its longer training duration, is much more energy-efficient than the conventional N-pilot scheme. An extension to a practical scenario where all data symbols of a packet are received by the same antenna is also investigated.
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In systems biology, questions concerning the molecular and cellular makeup of an organism are of utmost importance, especially when trying to understand how unreliable components-like genetic circuits, biochemical cascades, and ion channels, among others-enable reliable and adaptive behaviour. The repertoire and speed of biological computations are limited by thermodynamic or metabolic constraints: an example can be found in neurons, where fluctuations in biophysical states limit the information they can encode-with almost 20-60% of the total energy allocated for the brain used for signalling purposes, either via action potentials or by synaptic transmission. Here, we consider the imperatives for neurons to optimise computational and metabolic efficiency, wherein benefits and costs trade-off against each other in the context of self-organised and adaptive behaviour. In particular, we try to link information theoretic (variational) and thermodynamic (Helmholtz) free-energy formulations of neuronal processing and show how they are related in a fundamental way through a complexity minimisation lemma.
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Efficient photon detection in gaseous photomultipliers require maximum photoelectron yield from the photocathode surface and also detection of them. In this work we have investigated the parameters that affect the photoelectron yield from the photocathode surface and methods to improve them thus ensuring high detection efficiency of the gaseous photomultiplier. The parameters studied are the electric field at the photocathode surface, surface properties of photocathode and pressure of gas mixture inside the gaseous photomultiplier. It was observed that optimized electric field at the photocathode ensures high detection efficiency. Lower pressure of filled gas increases the photoelectron yield from the photocathode surface but reduces the focusing probability of electrons inside the electron multiplier. Also evacuation for longer duration before gas filling increases the photoelectron yield.
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The rather low scattering or extinction efficiency of small nanoparticles, metallic and otherwise, is significantly enhanced when they are adsorbed on a larger core particle. But the photoabsorption by particles with varying surface area fractions on a larger core particle is found to be limited by saturation. It is found that the core-shell particle can have a lower absorption efficiency than a dielectric core with its surface partially nucleated with absorbing particles-an ``incomplete nanoshell'' particle. We have both numerically and experimentally studied the optical efficiencies of titania (TiO2) nucleated in various degrees on silica (SiO2) nanospheres. We show that optimal surface nucleation over cores of appropriate sizes and optical properties will have a direct impact on the applications exploiting the absorption and scattering properties of such composite particles.
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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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An analysis of the energy budget for the general case of a body translating in a stationary fluid under the action of an external force is used to define a power loss coefficient. This universal definition of power loss coefficient gives a measure of the energy lost in the wake of the translating body and, in general, is applicable to a variety of flow configurations including active drag reduction, self-propulsion and thrust generation. The utility of the power loss coefficient is demonstrated on a model bluff body flow problem concerning a two-dimensional elliptical cylinder in a uniform cross-flow. The upper and lower boundaries of the elliptic cylinder undergo continuous motion due to a prescribed reflectionally symmetric constant tangential surface velocity. It is shown that a decrease in drag resulting from an increase in the strength of tangential surface velocity leads to an initial reduction and eventual rise in the power loss coefficient. A maximum in energetic efficiency is attained for a drag reducing tangential surface velocity which minimizes the power loss coefficient. The effect of the tangential surface velocity on drag reduction and self-propulsion of both bluff and streamlined bodies is explored through a variation in the thickness ratio (ratio of the minor and major axes) of the elliptical cylinders.
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We study consistency properties of surrogate loss functions for general multiclass classification problems, defined by a general loss matrix. We extend the notion of classification calibration, which has been studied for binary and multiclass 0-1 classification problems (and for certain other specific learning problems), to the general multiclass setting, and derive necessary and sufficient conditions for a surrogate loss to be classification calibrated with respect to a loss matrix in this setting. We then introduce the notion of \emph{classification calibration dimension} of a multiclass loss matrix, which measures the smallest `size' of a prediction space for which it is possible to design a convex surrogate that is classification calibrated with respect to the loss matrix. We derive both upper and lower bounds on this quantity, and use these results to analyze various loss matrices. In particular, as one application, we provide a different route from the recent result of Duchi et al.\ (2010) for analyzing the difficulty of designing `low-dimensional' convex surrogates that are consistent with respect to pairwise subset ranking losses. We anticipate the classification calibration dimension may prove to be a useful tool in the study and design of surrogate losses for general multiclass learning problems.
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Transductive SVM (TSVM) is a well known semi-supervised large margin learning method for binary text classification. In this paper we extend this method to multi-class and hierarchical classification problems. We point out that the determination of labels of unlabeled examples with fixed classifier weights is a linear programming problem. We devise an efficient technique for solving it. The method is applicable to general loss functions. We demonstrate the value of the new method using large margin loss on a number of multi-class and hierarchical classification datasets. For maxent loss we show empirically that our method is better than expectation regularization/constraint and posterior regularization methods, and competitive with the version of entropy regularization method which uses label constraints.
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In the present work, the thermal efficiency of a conventional domestic burner is studied both experimentally and numerically for liquefied petroleum gas (LPG) and piped natural gas (PNG) fuels. Three-dimensional computational fluid dynamic (CFD) modeling of the steady-state flow, combustion and heat transfer to the vessel is reported for the first time in such burners. Based on the insights from the CFD model concerning the flow and heat transfer, design modifications in the form of a circular insert and a radiant sheet are proposed which are observed to increase thermal efficiency for LPG. For PNG, predictions showed that loading height was a much more important factor affecting efficiency than these design modifications and an optimal loading height could be identified. Experiments confirm these trends by showing an improvement in burner thermal efficiency of 2.5% for LPG with the modified design, and 10% for PNG with the optimal loading height, demonstrating that the CFD modeling approach developed in the present work is a useful tool to study domestic burners. (C) 2013 Elsevier Ltd. All rights reserved.
Resumo:
Experimental study of a small partial admission axial turbine with low aspect ratio blade has been done. Tests were also performed with full admission stator replacing the partial one for the same rotor to assess the losses occurring due to partial admission. Further tests were conducted with stator admission area split into two and three sectors to study the effects of multiple admission sectors. The method of Ainley and Mathieson with suitable correction for aspect ratio in secondary losses, as proposed by Kacker and Okapuu, gives a good estimate of the efficiency. Estimates of partial admission losses are made and compared with experimentally observed values. The Suter and Traupel correlations for partial admission losses yielded reasonably accurate estimates of efficiency even for small turbines though limited to the region of design u/c(is). Stenning's original concept of expansion losses in a single sector is extended to include multiple sectors of opening. The computed efficiency debit due to each additional sector opened is compared with test values. The agreement is observed to be good. This verified Stenning's original concept of expansion losses. When the expression developed on this extended concept is modified by a correction factor, the prediction of partial admission efficiencies is nearly as good as that of Suter and Traupel. Further, performance benefits accrue if the turbine is configured with increased aspect ratio at the expense of reduced partial admission.
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Among the armoury of photovoltaic materials, thin film heterojunction photovoltaics continue to be a promising candidate for solar energy conversion delivering a vast scope in terms of device design and fabrication. Their production does not require expensive semiconductor substrates and high temperature device processing, which allows reduced cost per unit area while maintaining reasonable efficiency. In this regard, superstrate CdTe/CdS solar cells are extensively investigated because of their suitable bandgap alignments, cost effective methods of production at large scales and stability against proton/electron irradiation. The conversion efficiencies in the range of 6-20% are achieved by structuring the device by varying the absorber/window layer thickness, junction activation/annealing steps, with more suitable front/back contacts, preparation techniques, doping with foreign ions, etc. This review focuses on fundamental and critical aspects like: (a) choice of CdS window layer and CdTe absorber layer; (b) drawbacks associated with the device including environmental problems, optical absorption losses and back contact barriers; (c) structural dynamics at CdS-CdTe interface; (d) influence of junction activation process by CdCl2 or HCF2Cl treatment; (e) interface and grain boundary passivation effects; (f) device degradation due to impurity diffusion and stress; (g) fabrication with suitable front and back contacts; (h) chemical processes occurring at various interfaces; (i) strategies and modifications developed to improve their efficiency. The complexity involved in understanding the multiple aspects of tuning the solar cell efficiency is reviewed in detail by considering the individual contribution from each component of the device. It is expected that this review article will enrich the materials aspects of CdTe/CdS devices for solar energy conversion and stimulate further innovative research interest on this intriguing topic.
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We have recently suggested a method (Pallavi Bhattacharyya and K. L. Sebastian, Physical Review E 2013, 87, 062712) for the analysis of coherence in finite-level systems that are coupled to the surroundings and used it to study the process of energy transfer in the Fenna-Matthews-Olson (FMO) complex. The method makes use of adiabatic eigenstates of the Hamiltonian, with a subsequent transformation of the Hamiltonian into a form where the terms responsible for decoherence and population relaxation could be separated out at the lowest order. Thus one can account for decoherence nonperturbatively, and a Markovian type of master equation could be used for evaluating the population relaxation. In this paper, we apply this method to a two-level system as well as to a seven-level system. Comparisons with exact numerical results show that the method works quite well and is in good agreement with numerical calculations. The technique can be applied with ease to systems with larger numbers of levels as well. We also investigate how the presence of correlations among the bath degrees of freedom of the different bacteriochlorophyll a molecules of the FMO Complex affect the rate of energy transfer. Surprisingly, in the cases that we studied, our calculations suggest that the presence of anticorrelations, in contrast to correlations, make the excitation transfer more facile.
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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.