Search

The high-head pumped storage power station (PSPS) has complex working conditions and severe transient processes. Under load rejection conditions, the turbine speed and the flow channel pressure will threaten the unit. By adjusting the wicket gate closing law (WGCL), we can effectively alleviate the adverse effects of the transient process. In this study, a full flow channel refined model of a high-head PSPS was constructed, and the influence mechanism of load rejection conditions on key parameters was analyzed by tracking the operating trajectory on the S characteristic curves and simulating the transient flow field inside the pumped turbine by three-dimensional computational fluid dynamics (3D-CFD). Given the contradiction between different parameters in the wicket gate closing process, a third-generation non-dominated genetic algorithm based on reference point selection (NSGA-III) was introduced, and a high-dimensional multi-objective WGCL optimization model was constructed. We compared parameter changes in the two-phase and three-phase WGCL optimized elite solutions and explained the rationality of adopting the three-phase WGCL in high-head PSPSs. By proposing an improved three-phase WGCL, a new scheme—the most suitable WGCL under load rejection—was obtained through precise optimization. The research embodied the excellent effect of the heuristic multi-objective (MO) optimization algorithm based on the Pareto strategy in solving the operation problem of the large fluctuation transient process of hydraulic machinery. It revealed the theoretical basis of engineering adjustment for the safe production and operation of hydropower.

Forecasted inflow is one of the most important input information for reservoir operation planning. However, current inflow prediction accuracy is difficult to meet the needs of long-term operation. Therefore, it is of great significance to consider the uncertainty of inflow forecast and study its influence on reservoir operation decisions. In this paper, a long-term scheduling framework considering inflow forecast uncertainty based on a temporal disaggregation method is proposed. First, the uncertainty of forecast is described from two aspects. Gaussian distribution is used to simulate the annual forecast error, and an Adaptive Nearest Neighbor Gaussian sampling method (A-NGS) is proposed to decompose annual inflow into temporal series. Based on the implicit scheduling model, the sample set of generation scheduling plans, actual dispatching schemes and theoretical optimal results are constructed. On this basis, a series of indexes are presented to evaluate the inflow simulation performance and the scheduling benefits. A case study of the Xiluodu-Xiangjiaba cascade reservoirs is conducted to analyze the effects of forecast uncertainty on operation benefits, and the effectiveness of forecast information is identified. Compared with the deterministic fragment method, the inflow processes simulated by A-NGS achieve better precision and behave more conducive to the scheduling. Although the uncertainty of forecast errors will bring some hydropower generation losses, a certain degree of forecast accuracy is effective to improve scheduling benefits when in the electricity market.

Based on the problem of abandoned water and insufficient output caused by runoff randomness, the short-term runoff inflow interval prediction method combined with nonparametric kernel density estimation (NKDE)and Monte Carlo (MC)sampling is proposed. The method analyzes the impact of hydropower station abandonment risk and insufficient output risk caused by inflow uncertainty on hydropower station output and thermal power output in the power grid, and the corresponding output adjustment strategy is given. This paper mainly carries out these studies: real-time load distribution, short-term runoff interval prediction and real-time output adjustment of hydro-thermal power plant under uncertain incoming water: (1) Risk factors of water and electricity may be involved in the scheduling process, the process of considering runoff uncertainty on hydropower unit output, analyze the impact of hydropower abandoned water risk, estimate based on short-term nonparametric kernel density estimation (NKDE) runoff forecasting methods, given the range of the forecast runoff, reducing forecast error runoff, combine Monte Carlo (MC) sampling and propose a new real-time power control adjustment strategy. (2) Taking Qingjiang cascade power station as a case study, considering the increase of incoming water and the decrease of incoming water, the impact of water abandonment risk and insufficient output risk on short-term power generation plan is verified. The results show that the proposed hydropower and thermal power output adjustment can effectively deal with the risk of abandoned water and the risk of insufficient output. It is of positive significance to make full use of hydropower resources. It is helpful for the safe and stable operation of Hubei Power Grid.

Large hydropower stations often undertake peak regulation tasks during the non-abandoning water season. This requires a reasonable arrangement of unit commitment and load distribution (UCLD). In this study, a load distribution model considering constraints of substations was established, and a novel refined and practical method (RPM) was proposed by considering a whole plant-substation module, substation-unit module, and adjustment module along with practical strategies. The Three Gorges hydropower station in China was selected to demonstrate the effects of the RPM. The results showed that the RPM with high calculation timeliness can obtain UCLD schemes with high rationality and practicability under the constraints of the whole plant, substations, and units. The relative mean absolute error of the simulation outflow could be controlled within 1%, thereby providing a valuable reference for forecasting the outflow process which involving the unit level.

Introduction Atherosclerosis is one of the major causes of cardiovascular diseases. Lipid uptake and accumulation in macrophages play a major role in atherosclerotic plaque formation from its initiation to advanced atheroma formation. The dipeptidyl peptidase-4 (DPP-4) inhibitor Linagliptin is commonly used to lower blood glucose in type 2 diabetes patients. Recent studies report that Linagliptin has cardiovascular protective and anti-inflammatory effects. Methods THP-1 macrophage cells were treated with 100 nM PMA for 72 hour to induce foam cell formation. The differentiated cells were exposed to 100 μg/mL ox-LDL in the presence or absence of the DPP-4 inhibitor Linagliptin. The expression levels of DPP-4 and inflammatory cytokines were detected by RT-PCR, ELISA, and Western blot experiments. The cellular ROS level was measured by staining the cells with the fluorescent probe DCFH-DA. The separation of lipoprotein fractions was achieved by high-performance liquid chromatography (HPLC). The cells were labeled with fluorescent-labeled cholesterol to measure cholesterol efflux, and lipid droplets were revealed by Nile red staining. Results The presence of Linagliptin significantly reduced ox-LDL-induced cytokine production (IL-1β and IL-6) and ROS production. Linagliptin ameliorated ox-LDL-induced lipid accumulation and impaired cholesterol efflux in macrophages. Mechanistically, this study showed that Linagliptin mitigated ox-LDL-induced expression of the scavenger receptors CD36 and LOX-1, but not SRA. Furthermore, Linagliptin increased the expression of the cholesterol transporter ABCG1, but not ABCA1. Conclusion Linagliptin possesses a potent inhibitory effect on THP-1 macrophage-derived foam cell formation in response to ox-LDL. This effect could be mediated through a decrease in the expression of CD36 and LOX-1 on macrophages and an increase in the expression of the cholesterol transporter ABCG1. This study indicates that the DPP-4 inhibitor Linagliptin plays a critical role in preventing foam cell formation in vitro. However, future research using an atherosclerotic animal model is necessary to determine its effectiveness and to prove its potential implication in the prevention and treatment of atherosclerosis.

Accurate and reliable wind speed forecasting is vital in power system scheduling and management. Ensemble techniques are widely employed to enhance wind speed forecasting accuracy. This paper proposes a negative correlation learning-based regularized extreme learning machine ensemble model (NCL-RELM) integrated with optimal variational mode decomposition (OVMD) and sample entropy (SampEn) for multi-step ahead wind speed forecasting. For this purpose, the original wind speed time series is firstly decomposed into a few variational modes and a residue using OVMD, and then the decomposed subseries with approximate SampEn values are aggregated into a new subseries to reduce the computational burden. Secondly, a NCL-RELM ensemble model is employed to model each aggregated subseries. The NCL technique is employed to enhance the diversity among multiple sub-RELM models such that the predictability of a single RELM model can be enhanced. Finally, the prediction results of all subseries are added up to obtain an aggregated result for the original wind speed. The simulation results indicate that: (1) the NCL-RELM model performs better than other ensemble approaches including BAGTREE, BOOST and random forest; (2) the proposed OS-NCL-RELM model obtains the best statistical metrics from 1- to 3-step ahead forecasting compared with the other nine benchmark models.

Hydrological forecasting plays an important role in basin flood control systems, and the uncertainty of hydrological forecasting is helpful to reveal basin hydrological characteristics and provide support to decision makers in formulating water resources management schemes. The hydrologic uncertainty processor (HUP) has been widely employed in hydrological uncertainty prediction. However, in the HUP normal quantile transform (NQT) space, the posteriori distribution is derived from the Bayesian theory. This increases the difficulty of the theory and calculations. In this paper, a new method is proposed to deduce the posterior residual equation, and the HUP-Gaussian mixture model (HUP-GMM) is adopted to simplify the calculations. By maintaining the original hypothesis, since the posterior residual is known to follow a normal distribution, the posterior linear correlation equation can be directly assumed without prior and likelihood inferences. In particular, the complex Bayesian inference is replaced with simple linear equations. By converting the linear equation into the original space, we obtain a new method consisting of the HUP linear GMM (HUP-LG). In the study area, the parameters of the HUP-LG and HUP-GMM in the NQT space are calculated, and corresponding expressions of the probability density in the original space are obtained. The results reveal that the HUP-LG simplifies the calculation process in the NQT space, and attains the same performance as that of the HUP-GMM.

In this study, different derivatives of exopolysaccharides (EPS-2) from Lactobacillus helveticus MB2-1 including acetylated EPS-2 (A-EPS-2), carboxymethyl EPS-2 (C-EPS-2), sulfated EPS-2 (S-EPS-2) and phosphorylated EPS-2 (P-EPS-2) were prepared. Furthermore, the structure, physicochemical properties and antioxidant activities of EPS-2 and its derivatives were compared. The introduction of different chemical groups was confirmed using Fourier-transform infrared spectroscopy and nuclear magnetic resonance spectrogram, and the degrees of substitution (DS) for A-EPS-2, C-EPS-2, S-EPS-2 and P-EPS-2 were 0.439, 0.526, 0.625 and 0.432, respectively. Among four derivatives, the particle size distribution of A-EPS-2, C-EPS-2 and P-EPS-2 was in accordance with the molecular weight (Mw) distribution. Besides, the results of scanning electron micrograph, thermogravimetric analysis and differential scanning calorimetry indicated the surface morphology and thermal behavior of EPS-2 had greatly changed after modification. Notably, several derivatives especially S-EPS-2 exhibited improved antioxidant activities when compared with EPS-2, implying the derivatives of EPS-2 might have wide applications as antioxidants in food industry.

Laser cladding coating with wolfram carbide (WC) as enhanced particles can improve the performance of nickel-based materials. However, there still exists several problems, such as serious element segregation and unequal distribution of the reinforcement phase. In order to improve the mechanical properties further, IN718/WC coatings were prepared by ultrasonic vibration-assisted laser cladding. The effects of ultrasonic vibration on the ceramic distribution, microstructure, and wear performance were systematically studied. The results show that ultrasonic vibration can promote the uniform distribution of WC particles without changing the phase composition of the coating. The cavitation and acoustic flow induced by ultrasonic vibration interrupt the growth of columnar dendrites and refine the grains. In addition, the microhardness of the ultrasonic vibration-assisted coating is enhanced by 15.6% to 475 HV0.2. The average coefficient of friction (COF) of the ultrasonic vibration-assisted coating is 0.452, which is 17.5% lower than that of the unassisted coating. The wear volume of the coating is decreased significantly, and the wear characteristics change from severe adhesive wear to the slight coexistence of abrasive wear and adhesive wear.

Fe901/Al2O3 metal matrix composite (MMC) coatings were deposited on the surface of 45 steel via electromagnetic field (EF)-assisted laser cladding technology. The influences of EF on the microstructure, phase composition, microhardness, and wear resistance of the Fe901/Al2O3 MMC coating were investigated. The generated Lorentz force (FL) and Joule heating due to the application of EF had a positive effect on wear resistance. The results showed that FL broke up the columnar dendrites. Joule heating produced more nuclei, resulting in the formation of fine columnar dendrites, equiaxed dendrites, and cells. The EF affected the content of hard phase in the coatings while it did not change the phase composition of the coating, because the coatings with and without EF assistance contained (Fe, Cr), (Fe, Cr)7C3, Fe3Al, and (Al, Fe)4Cr phases. The microhardness under 20 mT increased by 84.5 HV0.2 compared to the coating without EF due to the refinement of grains and the increased content of hard phase. Additionally, the main wear mechanism switched from adhesive wear to abrasive wear.

The zein-tannic acid nanoparticles (ZTNPs) were developed as antioxidants for oxidation inhibition of blackberry seed oils. These particles were spherical with an average diameter below 200 nm. The results of structural characterization indicated that tannic acid was bound to zein by electrostatic, hydrophobic, and hydrogen bonding interactions, resulting in the conformational changes of zein. The antioxidant capacity of zein was significantly improved by binding of tannic acid, which suggested ZTNPs had a 2-Phenyl-4,4,5,5-tetramethylimidazoline-1-oxyl 3-Oxide (PTIO) radical scavenging rate as high as 77.5 % at pH 4. Moreover, ZTNPs at pH 7 exhibited a higher thermal stability and better resistance to emulsion lipid oxidation. They inhibited the formation of ROOH and TBARS of blackberry seed oil emulsions during storage by covering at the oil-water interface with an adsorption rate of approximately 100 %, forming a dense particle film to reduce the oxygen content and prevent the continuation of the oxidation process.

Soybean whey, as a byproduct of soybean industry, has caused considerable concern recently because of its abundant nutrients. To further utilize soybean whey, it was fermented with

Multireservoir joint flood control operation is an important nonstructural measure for flood control in some basins. Owing to the existence of uncertainties in flood control operation, various degrees of risk can be shown in flood control operation systems. Examining these uncertainties and the resulting risk of failure in multireservoir operation systems is extremely beneficial and indispensable for basin flood mitigation. In this study, different stochastic simulation methods were employed to generate streamflow series at multiple stations and other uncertainties such as the flood forecast errors, discharge capacity, and reservoir storage. Then, the Monte Carlo framework was established based on the simulation sequence to estimate the risk of a failure of each flood control unit in the flood control system. Furthermore, a comprehensive risk assessment indicator was proposed to consider the failure probability and failure consequences at the same time. The Xiluodu‐Xiangjiaba‐Three Gorges cascade reservoirs were selected as a case study. Results show that the applied probabilistic simulation methods could simulate various uncertainties in a multireservoir flood control system effectively, and the proposed risk analysis method could comprehensively evaluate the risks of reservoir overtopping, flood flows exceeding a standard, and flood diversion from the perspective of overall watershed security.

A blueberry anthocyanin extract was obtained from Brightwell blueberry fruits cultivated in eastern China and the extraction and purification conditions were optimized. The components of the anthocyanin extract were identified using ultra-performance liquid chromatography-electrospray ionization interface-mass spectrometer. The antioxidant and antibacterial activities of the blueberry fruit supernatant (BFS), blueberry anthocyanin crude extract (BCE), and blueberry anthocyanin rich extract (BRE) were evaluated. The extraction yield was 1.79 ± 0.0014 mg/g under the following optimal conditions: 1:20 solid-to-liquid ratio (v/w), 24 h, 34 °C, and 90% ethanol containing 0.21% (v/v) hydrochloric acid. With regard to purification, anthocyanin purity increased 19.1-fold. Nine fractions were identified as the glycosides of delphinidin, cyanidin, petunidin, and malvidin. The biological activities of the blueberry anthocyanin extract were improved through extraction and purification. Compared with BFS and BCE, BRE had a higher DPPH radical scavenging activity (EC50 = 0.51 mg/mL), ABTS antioxidant capacity (EC50 = 0.32 mg/mL), and oxygen radical absorbance capacity (0.43 mmol Trolox/g). Furthermore, BRE (2 mg/mL) showed a maximum of 84.64 ± 0.35% reduction in the biofilm biomass of Listeria monocytogenes and the inhibition zone given by BRE against Escherichia coli was 16.04 ± 0.38 mm. BRE showed the highest antioxidant capacities and obvious antibacterial effects against food-related microorganisms than the other samples. Therefore, BRE can be used as a natural antioxidant and antibacterial agent and has potential health advantages and food industry applications.