955 resultados para energy gain


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Amplified spontaneous emission (ASE) characteristics of a red fluorescent dye 4-(dicyanomethylene)-2-t-butyl-6(1,1,7,7-tetramethyljulolidyl-9-enyl)-4H-pyran (DCJTB) were significantly improved by assistant Forster energy transfer. The coguest-host system was composed of an electron transport organic molecule tris(8-hydroxyquinoline) aluminum (Alq(3)) as host and a green fluorescent dye (10-(2-benzothiazolyl)-1,1,7,7-tetramethyl-2,3,6,7-tetrahydro-1H,5H,11H-[1]benzopyrano[6,7,8-ij]quinolizin-11-one) (C545T) as assistant dopant codoped with the guest red dye DCJTB as emitter in a matrix of polystyrene (PS).

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The amplified spontaneous emission and gain characteristics of various fluorescent dyes, 2-(1,1-dimethylethyl)-6(2-(2,3,6,7-tetrahydro-1,1,7,7-tetramethyl-1H,5H-benzo[ij] quinolizin-9-1)ethenyl)-4H-pyran-4-ylidene) propanedinitrile (DCJTB) and 4-dicyanomethylene-2-methyl-6-(p-dimethyl-aminostyryl)-4H-pyran (DCM), doped in polystyrene (PS) matrices were studied and compared. It was found that DCJTB has a larger net gain, 40.72 cm(-1), a lower loss, 2.49 cm(-1), and a lower threshold, 0.16 (mJ/pulse)/cm(2), than DCM, which has a net gain of 11.95 cm(-1), a loss of 9.25 cm(-1), and a threshold of 4(mJ/pulse)/cm(2). The improvement of performance in DCJTB PS films is attributed to the larger free volume of DCJTB caused by the introduction of steric spacer groups into the DCJTB molecule.

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The effects of feeding level on growth, retention efficiency, faeces production and energy partitioning of redlip mullet were studied. A practical diet was used and fed at six levels from starvation, 1%, 2%, 3%, 4% of body weight (BW) to satiation for 3 weeks. The temperature was kept at 24 +/- 1 degrees C. Reducing the feeding amount resulted in significantly lower weight gain, and retention efficiency was significantly affected by feeding levels and attained the maximum at maximum feeding intake. Feeding 2% BW was the minimum required for fish to maintain growth. Fish carcass composition under different feeding levels could be divided into three groups: (1) starvation and FL1; (2) FL2 and FL3 and (3) FL4 and satiation, with significant differences among the groups but no differences in the groups except that ash content remained at constant value. Body composition of fish of group 2 was close to initial fish. The thermal-unit coefficient was 0.0381 at satiation, and significantly increased with increasing feeding levels. In order to accurately estimate basal metabolism (HeE), another trial on the relationship between HeE (kJ) and BW (g) was carried out. An exponential curve as HeE=0.1255BW(0.8386) explained this relationship. Intake energy (IE) increased from 11.30 to 63.08 kJ per fish, matching with different feeding levels. Energy allocated to growth of IE decreased with reducing feeding amount. There was a linear relationship between metabolism energy and retention energy in percentage.

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Our goal was to determine the effect of diets with different crude protein (CP) contents and metabolizable energy (W) levels on daily live-weight gain, apparent digestibility, and economic benefit of feedlot yaks on the Tibetan plateau during winter. Yaks were either 2- or 3-years old and randomly selected from the same herd. The 3-year-olds were placed into one of two experimental groups (A and B) and a control (CK1), and the two-year-olds were placed into one of three experimental groups (C, D and E) and a control (CK2) (N per group = 5). Yak in the control groups were allow graze freely, while those in the experimental groups yaks were fed diets higher in contains crude protein and metabolizable energy through a winter period inside a warming shed. Results indicated that live-weight gain of treatment groups was higher than their respective controls during experiment, and that daily live-weight gain of every 10 days among different treatments was significant difference (P < 0.05). In addition, apparent digestibility of different diets was linearly and positively related to feedlotting time, and feed conversion efficiency for A, C, D and E groups was quadratically related to feedlotting time (P < 0.01), however, feed conversion efficiency for B group was linearly and positively related to feedlotting time (P < 0.05). The economic benefit was 1.15 for A, 1.89 for B, 1.16 for C, 1.54 for D, and 4,52 for E. (c) 2005 Elsevier B.V. All rights reserved.

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Similarly to protein folding, the association of two proteins is driven by a free energy funnel, determined by favorable interactions in some neighborhood of the native state. We describe a docking method based on stochastic global minimization of funnel-shaped energy functions in the space of rigid body motions (SE(3)) while accounting for flexibility of the interface side chains. The method, called semi-definite programming-based underestimation (SDU), employs a general quadratic function to underestimate a set of local energy minima and uses the resulting underestimator to bias further sampling. While SDU effectively minimizes functions with funnel-shaped basins, its application to docking in the rotational and translational space SE(3) is not straightforward due to the geometry of that space. We introduce a strategy that uses separate independent variables for side-chain optimization, center-to-center distance of the two proteins, and five angular descriptors of the relative orientations of the molecules. The removal of the center-to-center distance turns out to vastly improve the efficiency of the search, because the five-dimensional space now exhibits a well-behaved energy surface suitable for underestimation. This algorithm explores the free energy surface spanned by encounter complexes that correspond to local free energy minima and shows similarity to the model of macromolecular association that proceeds through a series of collisions. Results for standard protein docking benchmarks establish that in this space the free energy landscape is a funnel in a reasonably broad neighborhood of the native state and that the SDU strategy can generate docking predictions with less than 5 � ligand interface Ca root-mean-square deviation while achieving an approximately 20-fold efficiency gain compared to Monte Carlo methods.

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Schizophrenia represents one of the world’s most devastating illnesses due to its often lifelong course and debilitating nature. The treatment of schizophrenia has vastly improved over recent decades with the discovery of several antipsychotic compounds; however these drugs are not without adverse effects that must be addressed to maximize their therapeutic value. Newer, atypical, antipsychotics are associated with a compilation of serious metabolic side effects including weight gain, insulin resistance, fat deposition, glucose dysregulation and ensuing co-morbidities such as type II diabetes mellitus. The mechanisms underlying these side effects remain to be fully elucidated and adequate interventions are lacking. Further understanding of the factors that contribute these side effects is therefore required in order to develop effective adjunctive therapies and to potentially design antipsychotic drugs in the future with reduced impact on the metabolic health of patients. We investigated if the gut microbiota represented a novel mechanism contributing to the metabolic dysfunction associated with atypical antipsychotics. The gut microbiota comprises the bacteria that exist symbiotically within the gastrointestinal tract, and has been shown in recent years to be involved in several aspects of energy balance and metabolism. We have demonstrated that administration of certain antipsychotics in the rat results in an altered microbiota profile and, moreover, that the microbiota is required for the full scale of metabolic dysfunction to occur. We have further shown that specific antibiotics can attenuate certain aspects of olanzapine and risperidone–induced metabolic dysfunction, in particular fat deposition and adipose tissue inflammation. Mechanisms underlying this novel link appear to involve energy utilization via expression of lipogenic genes as well as reduced inflammatory tone. Taken together, these data indicate that the gut microbiota is an important factor involved in the myriad of metabolic complications associated with antipsychotic therapy. Furthermore, these data support the future investigation of microbial-based therapeutics for not only antipsychotic-induced weight gain but also for tackling the global obesity epidemic.

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The analysis of energy detector systems is a well studied topic in the literature: numerous models have been derived describing the behaviour of single and multiple antenna architectures operating in a variety of radio environments. However, in many cases of interest, these models are not in a closed form and so their evaluation requires the use of numerical methods. In general, these are computationally expensive, which can cause difficulties in certain scenarios, such as in the optimisation of device parameters on low cost hardware. The problem becomes acute in situations where the signal to noise ratio is small and reliable detection is to be ensured or where the number of samples of the received signal is large. Furthermore, due to the analytic complexity of the models, further insight into the behaviour of various system parameters of interest is not readily apparent. In this thesis, an approximation based approach is taken towards the analysis of such systems. By focusing on the situations where exact analyses become complicated, and making a small number of astute simplifications to the underlying mathematical models, it is possible to derive novel, accurate and compact descriptions of system behaviour. Approximations are derived for the analysis of energy detectors with single and multiple antennae operating on additive white Gaussian noise (AWGN) and independent and identically distributed Rayleigh, Nakagami-m and Rice channels; in the multiple antenna case, approximations are derived for systems with maximal ratio combiner (MRC), equal gain combiner (EGC) and square law combiner (SLC) diversity. In each case, error bounds are derived describing the maximum error resulting from the use of the approximations. In addition, it is demonstrated that the derived approximations require fewer computations of simple functions than any of the exact models available in the literature. Consequently, the regions of applicability of the approximations directly complement the regions of applicability of the available exact models. Further novel approximations for other system parameters of interest, such as sample complexity, minimum detectable signal to noise ratio and diversity gain, are also derived. In the course of the analysis, a novel theorem describing the convergence of the chi square, noncentral chi square and gamma distributions towards the normal distribution is derived. The theorem describes a tight upper bound on the error resulting from the application of the central limit theorem to random variables of the aforementioned distributions and gives a much better description of the resulting error than existing Berry-Esseen type bounds. A second novel theorem, providing an upper bound on the maximum error resulting from the use of the central limit theorem to approximate the noncentral chi square distribution where the noncentrality parameter is a multiple of the number of degrees of freedom, is also derived.

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Using C57BL/6J mice fed whey protein isolate (WPI) enriched high fat (HFD) or low-fat diets (LFD), this study tested the hypothesis that WPI directly impacts on adiposity by influencing lipid metabolism. WPI suppressed HFD-induced body fat and increased lean mass at 8 weeks of dietary challenge despite elevated plasma triacylglycerol (TAG) levels, suggesting reduced TAG storage. WPI reduced HFD-associated hypothalamic leptin and insulin receptor (IR) mRNA expression, and prevented HFD-associated reductions in adipose tissue IR and glucose transporter 4 expression. These effects were largely absent at 21 weeks of HFD feeding, however WPI increased lean mass and cause a trend towards decreased fat mass, with notable increased Lactobacillus and decreased Clostridium gut bacterial species. Increasing the protein to carbohydrate ratio enhanced the above effects, and shifted the gut microbiota composition away from the HFD group. Seven weeks of WPI intake with a LFD decreased insulin signalling gene expression in the adipose tissue in association with an increased fat accumulation. WPI reduced intestinal weight and length, suggesting a potential functional relationship between WPI, gastro-intestinal morphology and insulin related signalling in the adipose. Extending the study to 15 weeks, did not affect adipose fat weight, but decreased energy intake, weight gain and intestinal length. The functionality of protein sensing lysophosphatidic acid receptor 5 (LPA5) in 3T3-L1 pre-adipocytes was assessed. Over-expression of the receptor in 3T3-L1 pre-adipocytes provided a growth advantage to the cells and suppressed cellular differentiation into mature fat cells. In conclusion, the data demonstrates WPI impacts on adiposity by influencing lipid metabolism in a temporal manner, resulting possibly due to changes in lean mass, hypothalamic and adipose gene expression, gut microbiota and gastrointestinal morphology. The data also showed LPA5 is a novel candidate in regulating of preadipocyte growth and differentiation, and may mediate dietary protein effects on adipose tissue.

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Driven by a double 75 ps pulse with 2.2 ns separation, saturated operation of nickel-like Ag, In, Sn, and Sm X-ray lasers have been demonstrated with only 75 J drive energy on target. The variation of X-ray laser output with target length is found to fit well to a simple model for an amplified spontaneous emission (ASE) laser including saturation. Small signal gains of similar to 10 cm(-1), effective gain length products of similar to 18, and saturation irradiance of (1-5)x 10(10) W/cm(2) are measured for these lasers using a fitting procedure. (C) 1998 Elsevier Science B.V. All rights reserved.

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The gain coefficient of the strongest 3p --> 3s, J = 2 --> 1 lasing transition at 23.6 nm in the Ne-like Ge collisional excitation scheme has been measured, using the fundamental wavelength from a Nd:glass laser (1.06-mu-m), for a range of incident intensities on massive stripe targets up to 2.2 cm in length. From a threshold incident laser intensity of approximately 6 x 10(12) W/cm2, the gain coefficient rises to approximately 4.5 cm-1 for an irradiation intensity of approximately 2.5 x 10(13) W/cm2, tending towards still higher gain coefficients at higher incident intensities. For targets of maximum length, a gain-length product gL almost-equal-to 10 was reached with a resultant output power at 23.6 nm estimated to be at the approximately kW level. The beam divergence decreased with length to a minimum of approximately 7 mrad but no significant trend in beam pointing with plasma length was observed. From the trend in the gain coefficient, it appears that for a fixed energy laser irradiating a approximately 100-mu-m wide slab targets, an incident intensity of I(i) approximately 1.2 x 10(13) W/cm2 represents an optimum working level, assuming that plasma length is not limited by refractive effects. In addition to the usual valence electron excited 3p --> 3s transitions, the gain coefficient for the core excited 1s(2)2s2p(6)3d --> 1s(2)2s2p(6)3p transition at 19.9 nm has been measured to be approximately 1.5 cm-1 for an incident irradiance of approximately 2.5 x 10(13) W/cm2.

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Many scientific applications are programmed using hybrid programming models that use both message passing and shared memory, due to the increasing prevalence of large-scale systems with multicore, multisocket nodes. Previous work has shown that energy efficiency can be improved using software-controlled execution schemes that consider both the programming model and the power-aware execution capabilities of the system. However, such approaches have focused on identifying optimal resource utilization for one programming model, either shared memory or message passing, in isolation. The potential solution space, thus the challenge, increases substantially when optimizing hybrid models since the possible resource configurations increase exponentially. Nonetheless, with the accelerating adoption of hybrid programming models, we increasingly need improved energy efficiency in hybrid parallel applications on large-scale systems. In this work, we present new software-controlled execution schemes that consider the effects of dynamic concurrency throttling (DCT) and dynamic voltage and frequency scaling (DVFS) in the context of hybrid programming models. Specifically, we present predictive models and novel algorithms based on statistical analysis that anticipate application power and time requirements under different concurrency and frequency configurations. We apply our models and methods to the NPB MZ benchmarks and selected applications from the ASC Sequoia codes. Overall, we achieve substantial energy savings (8.74 percent on average and up to 13.8 percent) with some performance gain (up to 7.5 percent) or negligible performance loss.

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Research on fusion fast ignition (FI) initiated by laser-driven ion beams has made substantial progress in the last years. Compared with electrons, FI based on a beam of quasi-monoenergetic ions has the advantage of a more localized energy deposition, and stiffer particle transport, bringing the required total beam energy close to the theoretical minimum. Due to short pulse laser drive, the ion beam can easily deliver the 200 TW power required to ignite the compressed D-T fuel. In integrated calculations we recently simulated ion-based FI targets with high fusion gain targets and a proof of principle experiment [1]. These simulations identify three key requirements for the success of ion-driven fast ignition (IFI): (1) the generation of a sufficiently high-energetic ion beam (approximate to 400-500 MeV for C), with (2) less than 20% energy spread at (3) more than 10% conversion efficiency of laser to beam energy. Here we present for the first time new experimental results, demonstrating all three parameters in separate experiments. Using diamond nanotargets and ultrahigh contrast laser pulses we were able to demonstrate >500 MeV carbon ions, as well as carbon pulses with Delta E/E

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Multiuser diversity (MUDiv) is one of the central concepts in multiuser (MU) systems. In particular, MUDiv allows for scheduling among users in order to eliminate the negative effects of unfavorable channel fading conditions of some users on the system performance. Scheduling, however, consumes energy (e.g., for making users' channel state information available to the scheduler). This extra usage of energy, which could potentially be used for data transmission, can be very wasteful, especially if the number of users is large. In this paper, we answer the question of how much MUDiv is required for energy limited MU systems. Focusing on uplink MU wireless systems, we develop MU scheduling algorithms which aim at maximizing the MUDiv gain. Toward this end, we introduce a new realistic energy model which accounts for scheduling energy and describes the distribution of the total energy between scheduling and data transmission stages. Using the fact that such energy distribution can be controlled by varying the number of active users, we optimize this number by either i) minimizing the overall system bit error rate (BER) for a fixed total energy of all users in the system or ii) minimizing the total energy of all users for fixed BER requirements. We find that for a fixed number of available users, the achievable MUDiv gain can be improved by activating only a subset of users. Using asymptotic analysis and numerical simulations, we show that our approach benefits from MUDiv gains higher than that achievable by generic greedy access algorithm, which is the optimal scheduling method for energy unlimited systems. © 2010 IEEE.

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The proliferation problem of video streaming applications and mobile devices has prompted wireless network operators to put more efforts into improving quality of experience (QoE) while saving resources that are needed for high transmission rate and large size of video streaming. To deal with this problem, we propose an energy-aware rate and description allocation optimization method for video streaming in cellular network assisted device-to-device (D2D) communications. In particular, we allocate the optimal bit rate to each layer of video segments and packetize the segments into multiple descriptions with embedded forward error correction (FEC) for realtime streaming without retransmission. Simultaneously, the optimal number of descriptions is allocated to each D2D helper for transmission. The two allocation processes are done according to the access rate of segments, channel state information (CSI) of D2D requester, and remaining energy of helpers, to gain the highest optimization performance. Simulation results demonstrate that our proposed method (named OPT) significantly enhances the performance of video streaming in terms of high QoE and energy saving.

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Current variation aware design methodologies, tuned for worst-case scenarios, are becoming increasingly pessimistic from the perspective of power and performance. A good example of such pessimism is setting the refresh rate of DRAMs according to the worst-case access statistics, thereby resulting in very frequent refresh cycles, which are responsible for the majority of the standby power consumption of these memories. However, such a high refresh rate may not be required, either due to extremely low probability of the actual occurrence of such a worst-case, or due to the inherent error resilient nature of many applications that can tolerate a certain number of potential failures. In this paper, we exploit and quantify the possibilities that exist in dynamic memory design by shifting to the so-called approximate computing paradigm in order to save power and enhance yield at no cost. The statistical characteristics of the retention time in dynamic memories were revealed by studying a fabricated 2kb CMOS compatible embedded DRAM (eDRAM) memory array based on gain-cells. Measurements show that up to 73% of the retention power can be saved by altering the refresh time and setting it such that a small number of failures is allowed. We show that these savings can be further increased by utilizing known circuit techniques, such as body biasing, which can help, not only in extending, but also in preferably shaping the retention time distribution. Our approach is one of the first attempts to access the data integrity and energy tradeoffs achieved in eDRAMs for utilizing them in error resilient applications and can prove helpful in the anticipated shift to approximate computing.