Optimal fidelity of teleportation with continuous variables using three tunable parameters in a realistic environment

We introduce three tunable parameters to optimize the fidelity of quantum teleportation with continuous-variable in nonideal scheme. Using the characteristic function formalism, we present the condition that the teleportation fidelity is independent of the amplitude of input coherent states for any entangled resource. Then we investigate the effects of tunable parameters on the fidelity with or without the presence of environment and imperfect measurements, by analytically deriving the expression of fidelity for three different input coherent state distributions. It is shown that, for the linear distribution, the optimization with three tunable parameters is the best one with respect to single- and two-parameter optimization. Our results reveal the usefulness of tunable parameters for improving the fidelity of teleportation and the ability against the decoherence.Comment: 11 pages, 9 figure

Preparation and optimization of poly (lactic-co-glycolic acid) rod-shaped particles in nano size range for paclitaxel delivery

Nanoparticle shape has been acknowledged as an important design parameter due to its influence on nanoparticle interaction with biological systems. However, there is lacking of simple and scalable preparation technique for drug loaded non-spherical polymeric nanoparticles for a long time, thus hindering the potential applications. Although our previous research has modified the traditional emulsion solvent evaporation technique by adding guest molecules to prepare non-spherical poly (lactic-co-glycolic acid) (PLGA) particles, it is difficult to obtain nano-sized rods with minor axis less than 200 nm, which may have great potential in cancer therapy. Herein, in present research, the two-step ESE method was used and optimized to prepare poly (lactic-co-glycolic acid) nanorods for paclitaxel delivery. Firstly, the single-factor experiment was used to screen the influence of multi-factors including type of guest molecules, concentration of guest molecules, emulsification method, surfactant concentration, oil volume, poly (lactic-co-glycolic acid) concentration on the size and shape to determine the range of variables; based on the above range, a multi-factor and multi-level orthogonal experiment was designed. The formula is evaluated by the rod fabrication yield and the aspect ratio of major axis to minor axis. The results showed that the yield of nanorods in the optimal formula was 99% and the aspect ratio was 5.35 ± 2.05 with the minor axis of 135.49 ± 72.66 nm, and major axis of 657.77 ± 307.63 nm. In addition, the anti-cancer drug paclitaxel was successfully encapsulated in PLGA nanorods by the same technique. Our results not only enrich the ESE technique for preparing small sized poly (lactic-co-glycolic acid) nanorods, but also envision the potential application of nanorods for targeted cancer therapy with the delivery of paclitaxel

Modeling and Optimization of the Medium-Term Units Commitment of Thermal Power

Coal-fired thermal power plants, which represent the largest proportion of China’s electric power system, are very sluggish in responding to power system load demands. Thus, a reasonable and feasible scheme for the medium-term optimal commitment of thermal units (MOCTU) can ensure that the generation process runs smoothly and minimizes the start-up and shut-down times of thermal units. In this paper, based on the real-world and practical demands of power dispatch centers in China, a flexible mathematical model for MOCTU that uses equal utilization hours for the installed capacity of all thermal power plants as the optimization goal and that considers the award hours for MOCTU is developed. MOCTU is a unit commitment (UC) problem with characteristics of large-scale, high dimensions and nonlinearity. For optimization, an improved progressive optimality algorithm (IPOA) offering the advantages of POA is adopted to overcome the drawback of POA of easily falling into the local optima. In the optimization process, strategies of system operating capacity equalization and single station operating peak combination are introduced to move the target solution from the boundary constraints along the target isopleths into the feasible solution’s interior to guarantee the global optima. The results of a case study consisting of nine thermal power plants with 27 units show that the presented algorithm can obtain an optimal solution and is competent in solving the MOCTU with high efficiency and accuracy as well as that the developed simulation model can be applied to practical engineering needs

Short-Term Peak-Shaving Operation of Head-Sensitive Cascaded Hydropower Plants Based on Spillage Adjustment

There are many cascaded hydropower plants with poor regulation performance and sensitive water heads accompanied by water spillage during the wet season. Faced with the increasing load peak–valley differences, it is necessary to tap the peak-shaving potential of such head-sensitive cascaded hydropower plants (HSCHPs) because relying solely on hydropower plants with better regulation performance for peak shaving is inadequate. To address the modeling, solving, and water spillage treatment difficulties posed by HSCHPs, a new short-term peak-shaving method based on spillage adjustment is introduced. First, fuzzy cluster analysis is used to determine when to release more water spillage by automatically identifying valley periods of the daily load curve. Furthermore, a spillage adjustment strategy, implemented through an easy gate operation, is adopted to readjust the water release during each period of the load curve. The ratio of the water spillage released in advance in a certain period to its total water spillage is defined as the water spillage ratio (WSR) of the period. Finally, a mixed-integer linear programming model linearized by special ordered sets of type two is solved to determine the optimal WSRs, which achieves the optimal peak-shaving effect. HSCHPs in the Hongshui River Basin during the wet season were selected as case studies. The results demonstrate that the proposed method can achieve a good peak-shaving effect without significantly reducing the power generation and adding additional water spillage

Short-Term Wind Power Prediction Based on LightGBM and Meteorological Reanalysis

With the expansion of wind power grid integration, the challenges of sharp fluctuations and high uncertainty in preparing the power grid day-ahead plan and short-term dispatching are magnified. These challenges can be overcome through accurate short-term wind power process prediction based on mining historical operation data and taking full advantage of meteorological forecast information. In this paper, adopting the ERA5 reanalysis dataset as input, a short-term wind power prediction framework is proposed, combining light gradient boosting machine (LightGBM), mutual information coefficient (MIC) and nonparametric regression. Primarily, the reanalysis data of ERA5 provide more meteorological information for the framework, which can help improve the model input features. Furthermore, MIC can identify effective feature subsets from massive feature sets that significantly affect the output, enabling concise understanding of the output. Moreover, LightGBM is a prediction method with a stronger ability of goodness-of-fit, which can fully mine the effective information of wind power historical operation data to improve the prediction accuracy. Eventually, nonparametric regression expands the process prediction to interval prediction, which significantly improves the utility of the prediction results. To quantitatively analyze the prediction results, five evaluation criteria are used, namely, the Pearson correlation coefficient (CORR), the root mean square error (RMSE), the mean absolute error (MAE), the index of agreement (IA) and Kling–Gupta efficiency (KGE). Compared with support vector regression (SVR), random forest (RF) and extreme gradient boosting (XGBoost) models, the present framework can make full use of meteorological information and effectively improve the prediction accuracy, and the generated output prediction interval can also be used to promote the safe operation of power systems

Shock Tube Study on Auto-ignition Delay of Kerosene Aerosol and its Cracked Mixture

AbstractAn aerosol shock tube with piston setup attached to reflection end is developed for ignition delay studies of liquid fuels. Piezoelectric gauge and photomultiplier with filter are used respectively to detect pressure and OH emission signals. Autoignition delay is obtained for kerosene aerosol and its cracked mixture at different temperature and pressure, equivalence ratios. The results show good linearity of ignition delay with temperature inversion at different pressure and equivalence ratio. At high pressure, data of delay is close for aerosol and heating kerosene. But difference is obviously at low temperature. During burning, local shock waves are generated and propagate into burnt and unburnt mixture

Aerosol Shock Tube Designed for Ignition Delay Time Measurements of Low-Vapor-Pressure Fuels and Auto-Ignition Flow-Field Visualization

An aerosol shock tube has been developed for measuring the ignition delay times (tig) of aerosol mixtures of low-vapor-pressure fuels and for visualization of the auto-ignition flow-field. The aerosol mixture was formed in a premixing tank through an atomizing nozzle. Condensation and adsorption of suspended droplets were not observed significantly in the premixing tank and test section. A particle size analyzer was used to measure the Sauter mean diameter (SMD) of the aerosol droplets. Three pressure sensors and a photomultiplier were used to detect local pressure and OH emission respectively. Intensified charge-coupled device cameras were used to capture sequential images of the auto-ignition flow-field. The results indicated that stable and uniform aerosol could be obtained by this kind of atomizing method and gas distribution system. The averaged SMD for droplets of toluene ranged from 2 to 5 μ m at pressures of 0.14–0.19 MPa of dilute gases. In the case of a stoichiometric mixture of toluene/O2/N2, ignition delay times ranged from 77 to 1330 μs at pressures of 0.1–0.3 MPa, temperatures of 1432–1716 K and equivalence ratios of 0.5–1.5. The logarithm of ignition delay times was approximately linearly correlated to 1000/T. In contrast to the reference data, ignition delay times of aerosol toluene/O2/N2 were generally larger. Sequential images of auto-ignition flow-field showed the features of flame from generation to propagation

Facile synthesis of platinum-copper aerogels for the oxygen reduction reaction

Although carbon-supported platinum (Pt/C) has been generally used as a catalyst for the oxygen reduction reaction (ORR) in fuel cells, its practical application is limited by the corrosion reaction of the carbon support. Therefore, it is essential to develop new self-supported catalysts for the ORR. Noble metal aerogels represent highly promising self-supported catalysts with large specific surface area and excellent electrocatalytic activity. Classic sol-gel processes for aerogel synthesis usually take days due to the slow gelation kinetics. Here, we report a straightforward strategy to synthesize platinum-copper (PtCu) aerogels by reducing the metal salt solution with an excess of sodium borohydride at room temperature. The PtCu aerogels are formed in a relatively short time of 1 h through a rapid nucleation mechanism. The obtained PtCu aerogels have a highly porous structure with an appreciable topological surface area of 33.0 m2/g and mainly exposed (111) facets, which are favorable for the ORR. Consequently, the PtCu aerogels exhibit excellent ORR activity with a mass activity of 369.4 mA/mgPt and a specific activity of 0.847 mA/cm2, which are 2.6 and 3.3 times greater than those of Pt/C, respectively. The PtCu aerogels show remarkable ORR catalysis among all the noble metal aerogels that have been reported. The porous morphology and outstanding electrocatalytic activities of the PtCu aerogels illustrate their promising applications in fuel cells