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To realize abnormal-sound diagnosis in hydroelectric generating units, this study proposes a method based on continuous wavelet transform (CWT) and Transfer Learning (TL). A denoising algorithm utilizing spectral noise-gate technology is proposed to enhance fault characteristics in hydroelectric units. Subsequently, Continuous Wavelet Transform is applied to obtain frequency components, and the results are converted into a series of pseudo-color images to highlight information differences. A transfer model is subsequently developed for feature extraction, utilizing simplified fully connected layers to reduce modeling costs. The study optimizes key parameters during the signal-processing stage and achieves an improved parameter-setting scheme. Acoustic signals corresponding to four different fault states and a normal state are collected from a Kaplan hydroelectric generating unit in a hydropower station. The signal diagnosis accuracy rates before filtering are 84.83% and 95.14%. These rates significantly improved to 98.88% and 98.06%, respectively, demonstrating the effectiveness of the noise-reduction process. To demonstrate the superiority of the improved model in this work, a series of classic deep-learning models, including AlexNet, Resnet18, and MobileNetV3, are used for comparative analysis. The proposed method can effectively diagnose faults in Kaplan hydroelectric generating units with a high accuracy, which is crucial for the daily monitoring and maintenance of these units. [ABSTRACT FROM AUTHOR]

The Pelton turbine is an ideal choice for developing high-head hydropower resources. However, its cantilever-beam structure exposes the runner to intense alternating loads from high-velocity jets, causing localized high stresses, structural vibrations, and potential bucket fractures, all of which compromise safe operation. This study employs fluid–structure interaction analysis for the numerical investigation of a six-nozzle Pelton turbine to examine its unstable flow characteristics and hydrodynamic excitation under high-velocity jets. Our findings indicate that low-order frequencies primarily induce overall runner oscillations, while high-order frequencies result in oscillation, torsional displacement, and localized vibrations. Torsional displacement at the free end of the bucket induces stress concentrations at the root of the bucket and the splitter, the outflow edge, and the cut-out. The amplitudes of stress and displacement are correlated with the nozzle opening, with displacement typically in phase with torque, while stress fluctuations exhibit a phase lag. The stress and displacement values are higher on the bucket's front, with maximum stress occurring at the bucket root and maximum displacement at the outflow edge, particularly in regions subjected to prolonged jet impact. The dominant frequency of the stress pulsations matches the number of nozzles. This study elucidates the dynamic response of Pelton turbines under high-velocity jets, correlating fluid load with runner dynamics, identifying maximum stress and deformation points, and providing technical support for performance evaluation. [ABSTRACT FROM AUTHOR]

In this work, electrostatic minimum quantity lubrication (EMQL) has been applied in grinding. When the droplets were charged, it could promote penetrability in the processing area. The electric field formed between the charged droplets and the surface of Cr12 die steel could affect the hardness of the workpiece surface. The grinding mechanism of EMQL has been revealed under different charging voltage by analyzing the wetting angle of droplets and the hardness of Cr12 surface. The reduction of grinding force (11.5% to 49%), surface roughness (10% to 22.1%), and the increase in grinding ratio (1.9% to 27.3%) and surface quality of EMQL under various charging voltages were studied. The results showed that the wetting angle decreased when the droplets were charged. Compared to MQL, the charged lubricant droplets with better penetrability are easier to penetrate and spread on the contact surface between the grinding wheel and the workpiece, thereby improving the lubrication of the friction interface and obtaining better grinding performance. Moreover, we also found that the positively charged EMQL not only effectively improves the penetrability of droplets but reduces the hardness of the Cr12 surface. Thus, the grinding performances under positively charged EMQL are always better than these under negatively charged when grinding Cr12. [ABSTRACT FROM AUTHOR]

The extrusion ratio (ER) is one of the most important factors affecting the service performance of aluminum profiles. In this study, the influence of ER on the mechanical behavior and microstructure evolution of 7003 aluminum alloy at high-speed impact with strain rates ranging from 700 s−1 to 1100 s−1 was investigated. The studied alloy with an ER of 56 formed coarse grain rings during the heat treatment. The microstructure of the alloys with ERs of 20 and 9 is relatively uniform. The results indicate that under high-speed impact, the mechanical response behavior of the 7003-T6 alloy with different ERs is different. For the alloy with an ER of 56, strain hardening is the main mechanism of plastic deformation. In contrast, a flow stress reduction occurs at middle deformation stage for the ones with ERs of 20 and 9 due to concentrated deformation, which is more significant in the alloy with an ER of 20. Under high-speed impact, the alloy with an ER of 56 undergoes uneven plastic deformation due to the presence of coarse grain rings. The deformation is mainly borne by the region of coarse grains near the edge, and the closer to the center, the smaller the deformation. The deformation of the alloys with ERs of 20 and 9 is relatively uniform, but exhibits localized concentrated deformation in the area near the edge. The significant plastic deformation within deformation band causes a local temperature rise, resulting in a slight decrease in flow stress after the peak. These results can provide reliable data support for the application of 7003 aluminum alloy in the vehicle body crash energy absorption structure. [ABSTRACT FROM AUTHOR]

Synthetic Aperture Radar (SAR) enables the acquisition of high-resolution imagery even under severe meteorological and illumination conditions. Its utility is evident across a spectrum of applications, particularly in automatic target recognition (ATR). Since SAR samples are often scarce in practical ATR applications, there is an urgent need to develop sample-efficient augmentation techniques to augment the SAR images. However, most of the existing generative approaches require an excessive amount of training samples for effective modeling of the SAR imaging characteristics. Additionally, they show limitations in augmenting the interesting target samples while maintaining image recognizability. In this study, we introduce an innovative single-sample image generation approach tailored to SAR data augmentation. To closely approximate the target distribution across both the spatial layout and local texture, a multi-level Generative Adversarial Network (GAN) architecture is constructed. It comprises three distinct GANs that independently model the structural, semantic, and texture patterns. Furthermore, we introduce multiple constraints including prior-regularized noise sampling and perceptual loss optimization to enhance the fidelity and stability of the generation process. Comparative evaluations against the state-of-the-art generative methods demonstrate the superior performance of the proposed method in terms of generation diversity, recognizability, and stability. In particular, its advantages over the baseline method are up to 0.2 and 0.22 in the SIFID and SSIM, respectively. It also exhibits stronger robustness in the generation of images across varying spatial sizes. [ABSTRACT FROM AUTHOR]

In this study, a multi-component integrated dissolution evaluation system of Yuanhu Zhitong tablets (YZTs) was established based on in vitro and in vivo correlation (IVIVC). The dissolution tests of five quality markers (Q-markers), including tetrahydropalmatine, α-allocryptopine, protopine, corydaline, and byakangelicin, in YZTs were conducted under different dissolution conditions, and pharmacokinetic studies were performed in beagle dogs to construct a correlation model using numerical deconvolution. The data of the five ingredients were integrated in vitro and in vivo according to the biopharmaceutical classification system (BCS) to establish an IVIVC integrating multiple Q-markers. The dissolution media with the best correlation of components were obtained and validated. The results showed that all five components were classified as BCS I compounds, and α-allocryptopine, byakangelicin, tetrahydropalmatine, and corydaline showed good correlation in the paddle method, 75 rpm, with dissolution media of artificial gastric fluid, acetate buffer, acetate buffer and 0.1 M HCl, respectively. Protopine showed good correlation in the paddle method, 100 rpm, with dissolution media of 0.1 M HCl. The integrated BCS I Q-markers showed the best correlation in the medium of acetate buffer. The multi-component integrated dissolution evaluation system established in this experiment accurately predicted the pharmacokinetic data of YZTs by verifying the media, which can be used for the quality control of YZTs. The present study provides an effective and promising strategy for the dissolution evaluation for traditional Chinese medicine preparations. [ABSTRACT FROM AUTHOR]

The massive grid integration of renewable energy necessitates frequent and rapid response of hydropower output, which has brought enormous challenges to the hydropower operation and new opportunities for hydropower development. To investigate feasible solutions for complementary systems to cope with the energy transition in the context of the constantly changing role of the hydropower plant and the rapid evolution of wind and solar power, the short-term coordinated scheduling model is developed for the wind–solar–hydro hybrid pumped storage (WSHPS) system with peak shaving operation. The effects of different reservoir inflow conditions, different wind and solar power forecast output, and installed capacity of pumping station on the performance of WSHPS system are analyzed. The results show that compared with the wind–solar–hydro hybrid (WSH) system, the total power generation of the WSHPS system in the dry, normal, and wet year increased by 10.69%, 11.40%, and 11.27% respectively. The solar curtailment decreased by 68.97%, 61.61%, and 48.43%, respectively, and the wind curtailment decreased by 76.14%, 58.48%, and 50.91%, respectively. The high proportion of wind and solar energy connected to the grid in summer leads to large net load fluctuations and serious energy curtailment. The increase in the installed capacity of the pumping station will promote the consumption of wind and solar energy in the WSHPS system. The model proposed in this paper can improve the operational flexibility of hydropower station and promote the consumption of wind and solar energy, which provides a reference for the research of cascade hydropower energy storage system. [ABSTRACT FROM AUTHOR]

Hydropower units are the core equipment of hydropower stations, and research on the fault prediction and health management of these units can help improve their safety, stability, and the level of reliable operation and can effectively reduce costs. Therefore, it is necessary to predict the swing trend of these units. Firstly, this study considers the influence of various factors, such as electrical, mechanical, and hydraulic swing factors, on the swing signal of the main guide bearing y-axis. Before swing trend prediction, the multi-index feature selection algorithm is used to obtain suitable state variables, and the low-dimensional effective feature subset is obtained using the Pearson correlation coefficient and distance correlation coefficient algorithms. Secondly, the dilated convolution graph neural network (DCGNN) algorithm, with a dilated convolution graph, is used to predict the swing trend of the main guide bearing. Existing GNN methods rely heavily on predefined graph structures for prediction. The DCGNN algorithm can solve the problem of spatial dependence between variables without defining the graph structure and provides the adjacency matrix of the graph learning layer simulation, avoiding the over-smoothing problem often seen in graph convolutional networks; furthermore, it effectively improves the prediction accuracy. The experimental results showed that, compared with the RNN-GRU, LSTNet, and TAP-LSTM algorithms, the MAEs of the DCGNN algorithm decreased by 6.05%, 6.32%, and 3.04%; the RMSEs decreased by 9.21%, 9.01%, and 2.83%; and the CORR values increased by 0.63%, 1.05%, and 0.37%, respectively. Thus, the prediction accuracy was effectively improved. [ABSTRACT FROM AUTHOR]

With large-scale grid-connected renewable energy, new power systems require more flexible and reliable energy storage power sources. Pumped storage stations play an important role in peak shaving, valley filling, and promoting renewable energy consumption. This paper presents the reasonable energy-abandonment operation of a combined power generation system (CPGS), in which a pumped storage station is the core control power, with an ultra-high proportion of renewable energy. Firstly, based on the seasonal characteristics of wind, solar, and load demand, typical days are selected through improved clustering analysis algorithms. Then, a daily optimal scheduling model for combined power generation systems (CPGS) is developed with the goals of economy, low-carbon, and stable operation. Finally, the correlation between the energy-abandonment rate and pumped storage station peak shaving and system optimization operation indicators is obtained by a reasonable energy-abandonment calculation method considering source-grid-load coordination. Taking the operation data of an energy base in the western region of China as an example, when the penetration rate of renewable energy is 60–70% in the future, the operating cost on the power side is greatly affected by the construction of the source side. When the system operates at a planned reasonable energy-abandonment rate of 2%, electricity regulation, load tracking, and daily operating costs all show better performance. [ABSTRACT FROM AUTHOR]

Nearshore ship detection has significant applications in both the military and civilian domains. Compared to synthetic aperture radar (SAR), polarimetric synthetic aperture radar (PolSAR) provides richer information for analyzing the scattering mechanisms of ships and enables better detection of ship targets. However, ships in nearshore areas tend to be highly concentrated, and ship detection is often affected by adjacent strong scattering, resulting in false alarms or missed detections. While the GP-PNF detector performs well in PolSAR ship detection, it cannot obtain satisfactory results in these scenarios, and it also struggles in the presence of azimuthal ambiguity or strong clutter interference. To address these challenges, we propose a nearshore ship detection method named ECD-PNF by integrating superpixel-level GP-PNF and refined polarimetric decomposition. Firstly, polarimetric superpixel segmentation and sea–land segmentation are performed to reduce the influence of land on ship detection. To estimate the sea clutter more accurately, an automatic censoring (AC) mechanism combined with superpixels is used to select the sea clutter superpixels. By utilizing refined eight-component polarimetric decomposition to improve the scattering vector, the physical interpretability of the detector is enhanced. Additionally, the expression of polarimetric coherence is improved to enhance the target clutter ratio (TCR). Finally, this paper combines the third eigenvalue of eigenvalue–eigenvector decomposition to reduce the impact of azimuthal ambiguity. Three spaceborne PolSAR datasets from Radarsat-2 and GF-3 are adopted in the experiments for comparison. The proposed ECD-PNF method achieves the highest figure of merit (FoM) value of 0.980, 1.000, and 1.000 for three datasets, validating the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

Dry concrete is a kind of concrete whose fresh mixture has almost no flowability and is widely used in the production of small-size unreinforced compression-compacted concrete blocks in plants. Considering the shortage of natural river sand and freshwater for concrete production, this study proposes that sea sand and seawater can be directly used in the manufacture of compression-compacted dry concrete paver blocks. The idea was verified in the laboratory to find suitable mix proportions and forming pressure, which are two key parameters for the production of paver blocks. Furthermore, the effect of sea sand replacement ratio and seawater replacement ratio is investigated, where compression and flexural tensile tests were conducted on lab-made paver blocks at different ages. The experimental results reveal that both the compressive and flexural tensile strengths of paver blocks increased when sea sand and seawater were adopted. It is finally suggested that sea sand and seawater are suitable for the production of unreinforced paver blocks with enhanced mechanical performance. [ABSTRACT FROM AUTHOR]

In this paper, a transcritical carbon dioxide power generation system based on a vortex tube is studied, which has the advantage of the self-condensation of carbon dioxide. The thermodynamic performance of the system was investigated by establishing a mathematical model. The results showed that under fundamental working conditions, the system could output a net power of 271.72 kW, and the thermal efficiency as well as the exergy efficiency of the system could reach 7.38% and 27.09%, respectively. Exergy analysis showed that the turbine had the greatest exergy loss among the system's components, followed by the vortex tube, pump, heater and cooler. Parameter analysis showed that increasing the outlet pressure and inlet temperature of the vortex tube can improve the thermal efficiency and exergy efficiency of the system. In addition, the improvement in the turbine component's efficiency is the most beneficial to the system's performance, among which the turbine's efficiency has the greatest impact. Carbon dioxide can be effectively liquified by expanding it in the vortex tube, and its liquefaction ratio increases with the decrease in the vortex tube's inlet temperature and the increase in the vortex tube's inlet pressure. [ABSTRACT FROM AUTHOR]

Fluid viscosity is one of the key factors affecting the cavitation characteristics of the Helico-axial Multiphase Pump (HAMP). In this paper, fluids with viscosities of 24.46 mm2/s, 48.48 mm2/s, 60.70 mm2/s, and 120.0 mm2/s were investigated by numerical simulation. The Ansys Fluent software was employed to conduct the simulation. The mixture multiphase flow model and the RNG k-ε turbulence model were adopted. The Singhal cavitation model was employed to consider the effects of the non-condensable gas on cavitation. An experiment was carried out to validate the numerical method. The results showed that the Net Positive Suction Head-available (NPSHA) of the pump decreased as the fluid viscosity increased. Under the critical NPSHA condition, the NPSHA decreased from 5.11 m to 3.68 m as the fluid viscosity increased from 24.46 mm2/s to 120.0 mm2/s. This suggested that the cavitation performance of the pump was deteriorated under high fluid viscosity. The impeller passage area occupied by the vapor increased when the fluid viscosity increased. Nearly half of the flow passages were occupied by cavitation bubbles when the fluid viscosity increased to 120.0 mm2/s. The vapor volume fraction, both on the suction surface and pressure surface of the blade, increased with the fluid viscosity. The vapor on the suction surface was mainly distributed in the region with the streamwise between 0 and 0.36 when the fluid viscosity was 24.46 mm2/s; while the high vapor volume fraction range increased to the streamwise of 0.42 when the fluid viscosity increased to 120.0 mm2/s. The higher vapor volume fraction corresponded with the lower pressure. It was also found that the turbulent kinetic energy, both on the suction surface and pressure surface, increased with the fluid viscosity, which was the favorite for producing more cavitation bubbles. Furthermore, the maximum velocity area was mainly concentrated in the inlet area of the impeller. The velocity distribution in the impeller was basically the same with the viscosity of 24.46 mm2/s and 48.48 mm2/s. When the viscosity further increased to 60.70 mm2/s, the maximum velocity area in the impeller was relatively large. This study provides a reference for designing the HAMP. [ABSTRACT FROM AUTHOR]

A two-phase hydraulic turbine's performance and flow field were predicted under different Inlet Gas Volume Fractions (IGVF) with incompressible and compressible models, respectively. The calculation equation of equivalent head, hydraulic efficiency, and flow loss considering the expanding work of compressible gas were deduced based on the energy conservation equations. Then, the incompressible and compressible results, including the output power and flow fields, are compared and analyzed. The compressible gas model's equivalent head, output power, and flow loss are higher than the incompressible model, but the hydraulic efficiency is lower. As the IGVF increases, the gas gradually diffuses from the blade's working surface to its suction surface. The gas–liquid separation happens at the runner outlet in the compressible results due to the gas expansion. The area of the low-pressure zone in the incompressible results increases with the IGVF. However, it decreases with the IGVF in the compressible results. As the gas expands in the blade passage, it takes up more flow area, causing the high liquid velocity in the same passage. The runner's inlet gas distribution affects the liquid flow angle, causing the inlet shock and high TKE areas, especially in the blade passage near the volute tongue. The high TKE area in the compressible results is larger than the incompressible results because the inlet impact loss and the liquid velocity in the blade passage are higher. This paper provides a reference for selecting gas models in the numerical simulation of two-phase hydraulic turbines. [ABSTRACT FROM AUTHOR]

Hydropower unit is the compensation power generation of the energy regulating unit in wind–solar–water multi-energy complementary systems that often require the turbine to operate in a partial working condition area, thereby resulting in problems of low hydraulic efficiency and severe vibration during operation. A multi-objective and multi-condition optimization design method for Francis turbine runner based on the super-transfer approximation approach was proposed in this study. The proposed method aims to improve the hydraulic performance of the turbine, enhance and suppress the vibration of the turbine, and expand the operation range of the turbine on the basis of the actual situation given that Francis turbine frequently operates in low- and ultralow-load areas under the condition of multi-energy complementarity and continuous adjustment of operating conditions. Different operating conditions from low load to full load were selected as performance evaluation conditions. The super-transfer approximation method was used to select the weight co-efficient of water turbine operating conditions, and a multi-objective optimization function with the efficiency and cavitation performance of the water turbine as optimization objectives was constructed to ensure that the optimized water turbine can achieve the optimal performance in the full working condition range. Results showed that the pressure distribution on the blade surface of the optimized runner was uniform and the working ability was enhanced under the condition of ensuring the performance stability of optimal and rated conditions when the original runner was optimized. The hydraulic efficiency of the turbine under the low-load conditions OP1 and OP2 increased by 4.61 and 3.17%, respectively. Hence, the optimized runner is suitable for hydraulic turbines under multi-energy complementary conditions. The results of this study can provide a reference for the optimal design and operation of the turbine runner. [ABSTRACT FROM AUTHOR]

With the increasing proportion of renewable energy in power generation, the mixed utilization of multiple renewable energy sources has gradually become a new trend. Using the natural complementary characteristics of wind power, photovoltaic, and hydropower to evaluate the complementary potential of various energy sources has become a hot issue in the research of mixed utilization. Given that traditional complementarity research can only assess the complementarity between two energy sources, this paper proposes a method to simultaneously determine the complementarity between three large-scale renewable energy sources. Firstly, a three-dimensional vector represents the complementary characteristic combination of any two energy sources. The complementary characteristics of the three energy sources were obtained by finding the optimal solution for the three-dimensional vector. Finally, power stations were selected, located in different spatial areas on the world's largest renewable energy base in Qinghai, China, as the research object to analyze and verify the complementary characteristics of wind-power–photovoltaic-power–hydropower at different spatiotemporal scales. The results show significant differences in the complementary characteristics of different time scales. The farther the spatial distance between different power stations, the stronger their complementarity. The best complementary index on the monthly and daily scales was improved by 8.49% and 6.51%. This study provides a new focus for the future evaluation of the complementary utilization potential of large-scale joint renewable energy in different world regions. [ABSTRACT FROM AUTHOR]

The single-core alternating current (AC) submarine cable can be provided with an outer sheath that is firmly grounded on both ends of the cable. The circulating currents of the outer sheath are generated to be almost as large as the conductor current. The outer sheaths, which have different structures and properties, generate unwanted losses, asymmetric distribution of circulating current, and extra heat in the single-core AC submarine cables. The formation mechanism of the circulating currents in the submarine cable sheath and armoring is analyzed from the perspective of electromagnetic shielding using electromagnetic transient theoretical analysis, simulation calculation, and field experiments. Equations for calculating the circulating currents of the sheath and armoring are proposed, and influences of these relationships that include the different material characteristics of the sheath and armoring are analyzed. The influence factors, which include different levels of magnetic armoring permeability, resistivity, and ground resistance of the outer sheath, can affect the symmetrical distribution of the circulating current in the outer sheaths. We propose using the phase differences to determine the material properties of each metallic section in the submarine cable. [ABSTRACT FROM AUTHOR]

22MnB5 boron steel has become one of the main choices for lightweight vehicles due to its extremely high mechanical properties. To explore the intrinsic relationship between the thermoforming process and thermo-mechanical behavior for constitutive modeling and thermoforming of vehicle structure, thermal tensile tests in wide ranges of deformation temperature (500 °C to 950 °C) and strain rate (0.01 s−1 to 10 s−1) were performed using a Gleeble-1500D thermal simulator with hot-rolled 22MnB5 boron steel. With increasing applied strain and strain rate, the flow stress increases gradually and then tends to saturation after reaching peak stress, except for that at 0.01 s−1 and 500 °C. With increasing deformation temperature, the microstructure transforms from a mixture of bainite, ferrite and pearlite to lath-shaped martensite accompanied with some residual austenite. At 950 °C, the average size of martensite decreases with increasing applied strain rate. After thermoforming with austenitizing temperature of 950 °C, lath-shaped martensite accompanied with some residual austenite is obtained in a thermoformed U-shaped structural part, resulting in a dramatical increase in tensile strength. In contrast, the tensile strength of sidewall is slightly higher than that of bottom. Based on the Arrhenius-type constitutive model, a modified constitutive model is constructed with a relative error of less than 5%, which can well describe the flow stress behavior of the studied 22MnB5 boron steel. [ABSTRACT FROM AUTHOR]

Commercial virtual power plants (CVPP) connect the form of renewable energy resource portfolio to the power market and reduce the risk of the unstable operation of a single renewable energy. Combining different kinds of large-scale renewable energy in CVPP to provide capacity services like base load, peak shaving, and valley-filling, etc., for the system loads is an urgent problem to be solved. Therefore, it is valuable to analyze the capacity allocation ratio of the CVPP to maximize the utilization of all kinds of energy, especially for the large-scale multi-energy base. This paper proposed a multi-energy coordinated operation framework by considering various load demands, including base load and peak shaving for the capacity allocation of CVPP based on the world's largest renewable energy resource base on the upstream area of the Yellow River. The main procedures of this framework are as follows: (1) A paratactic model satisfying base load and peak shaving is proposed to determine the ability of the CVPP operation model's capacity services to meet the different demands of the power system load. (2) A hybrid dimension reduction algorithm with a better convergence rate and optimization effect solves the proposed paratactic model based on the ReliefF and the Adaptive Particle Swarm Optimization (APSO). The results show that the large-scale CVPP with different compositions can achieve both of the goals of a stable base load output and stable residual load under different weather conditions. Compared with the operation on sunny days, the base load fluctuation and residual load fluctuation of CVPP on rainy days are reduced by 14.5% and 21.9%, respectively, proving that CVPP can alleviate renewable energy's dependence on weather and improve energy utilization. [ABSTRACT FROM AUTHOR]

The accurate identification of the gas–liquid two-phase flow pattern within the impeller of a centrifugal pump is critical to develop a reliable model for predicting the gas–liquid two-phase performance of the centrifugal pump. The influences of the inlet gas volume fraction, the liquid phase flow rate and the pump rotational speed on the flow characteristics of the centrifugal pump were investigated experimentally. Four typical flow patterns in the impeller of the centrifugal pump, i.e., the bubble flow, the agglomerated bubble flow, the gas pocket flow and the segregated flow, were obtained, and the corresponding flow pattern maps were drawn. After oversampling based on the SMOTE algorithm, a four-layer artificial neural network model with two hidden layers was constructed. By selecting the appropriate network super parameters, including the neuron numbers in the hidden layer, the learning rate and the activation function, the different flow patterns in the centrifugal pump impeller were identified. The identification rate of the model increased from 89.91% to 94.88% when the original data was oversampled by the SMOTE algorithm. It is demonstrated that the SMOTE algorithm is an effective method to improve the accuracy of the artificial neural network model. In addition, the Kappa coefficient, the Macro-F1 and the Micro-F1 were 0.93, 0.95 and 0.95, respectively, indicating that the model established in this paper can well identify the flow pattern in the impeller of a centrifugal pump. [ABSTRACT FROM AUTHOR]

As an evolutionarily conserved multi-protein complex, the Mediator complex modulates the association between transcription factors and RNA polymerase II to precisely regulate gene transcription. Although numerous studies have shown the diverse functions of Mediator complex in plant development, flowering, hormone signaling, and biotic stress response, its roles in the Abscisic acid (ABA) signaling pathway and abiotic stress response remain largely unclear. It has been recognized that the phytohormone, ABA, plays a predominant role in regulating plant adaption to various abiotic stresses as ABA can trigger extensive changes in the transcriptome to help the plants respond to environmental stimuli. Over the past decade, the Mediator complex has been revealed to play key roles in not only regulating the ABA signaling transduction but also in the abiotic stress responses. In this review, we will summarize current knowledge of the Mediator complex in regulating the plants' response to ABA as well as to the abiotic stresses of cold, drought and high salinity. We will particularly emphasize the involvement of multi-functional subunits of MED25, MED18, MED16, and CDK8 in response to ABA and environmental perturbation. Additionally, we will discuss potential research directions available for further deciphering the role of Mediator complex in regulating ABA and other abiotic stress responses. [ABSTRACT FROM AUTHOR]

MYB proteins are involved in diverse important biological processes in plants. Herein, we obtained the MYB superfamily from the allotetraploid Brassica napus, which contains 227 MYB-related (BnMYBR/Bn1R-MYB), 429 R2R3-MYB (Bn2R-MYB), 22 R1R2R3-MYB (Bn3R-MYB), and two R1R2R2R1/2-MYB (Bn4R-MYB) genes. Phylogenetic analysis classified the Bn2R-MYBs into 43 subfamilies, and the BnMYBRs into five subfamilies. Sequence characteristics and exon/intron structures within each subfamily of the Bn2R-MYBs and BnMYBRs were highly conserved. The whole superfamily was unevenly distributed on 19 chromosomes and underwent unbalanced expansion in B. napus. Allopolyploidy between B. oleracea and B. rapa mainly contributed to the expansion in their descendent B. napus, in which B. rapa-derived genes were more retained. Comparative phylogenetic analysis of 2R-MYB proteins from nine Brassicaceae and seven non-Brassicaceae species identified five Brassicaceae-specific subfamilies and five subfamilies that are lacking from the examined Brassicaceae species, which provided an example for the adaptive evolution of the 2R-MYB gene family alongside angiosperm diversification. Ectopic expression of four Bn2R-MYBs under the control of the viral CaMV35S and/or native promoters could rescue the lesser root hair phenotype of the Arabidopsis thaliana wer mutant plants, proving the conserved negative roles of the 2R-MYBs of the S15 subfamily in root hair development. RNA-sequencing data revealed that the Bn2R-MYBs and BnMYBRs had diverse transcript profiles in roots in response to the treatments with various hormones. Our findings provide valuable information for further functional characterizations of B. napusMYB genes. [ABSTRACT FROM AUTHOR]

Heat transfer of supercritical-pressure kerosene is crucial for regenerative cooling systems in rocket engines. In this study, experiments were devoted to measure the heat transfer of supercritical-pressure kerosene under ultra-high heat fluxes. The kerosene flowed horizontally in a mini circular tube with a 1.0 mm inner diameter and was heated uniformly under pressures of 10–25 MPa, mass fluxes of 8600–51,600 kg/m2 s, and a maximum heat flux of up to 33.6 MW/m2. The effects of the operating parameters on the heat transfer of supercritical-pressure kerosene were discussed. It was observed that the heat transfer coefficient of kerosene increases at a higher mass flux and inlet bulk temperature, but is little affected by pressure. The heat transfer of supercritical-pressure kerosene is classified into two regions: normal heat transfer and enhanced heat transfer. When the wall temperature exceeds a certain value, heat transfer is enhanced, which could be attributed to pseudo boiling. This phenomenon is more likely to occur under higher heat flux and lower mass flux conditions. In addition, the experimental data were compared with several existing heat transfer correlations, in which one of these correlations can relatively well predict the heat transfer of supercritical-pressure kerosene. The results drawn from this study could be beneficial to the regenerative cooling technology for rocket engines. [ABSTRACT FROM AUTHOR]

Arsenic trioxide (ATO) has a significant effect on the treatment of acute promyelocytic leukemia (APL) and advanced primary liver cancer, but it still faces severe side effects. Considering these problems, red blood cell membrane-camouflaged ATO-loaded sodium alginate nanoparticles (RBCM-SA-ATO-NPs, RSANs) were developed to relieve the toxicity of ATO while maintaining its efficacy. ATO-loaded sodium alginate nanoparticles (SA-ATO-NPs, SANs) were prepared by the ion crosslinking method, and then RBCM was extruded onto the surface to obtain RSANs. The average particle size of RSANs was found to be 163.2 nm with a complete shell-core bilayer structure, and the average encapsulation efficiency was 14.31%. Compared with SANs, RAW 264.7 macrophages reduced the phagocytosis of RSANs by 51%, and the in vitro cumulative release rate of RSANs was 95% at 84 h, which revealed a prominent sustained release. Furthermore, it demonstrated that RSANs had lower cytotoxicity as compared to normal 293 cells and exhibited anti-tumor effects on both NB4 cells and 7721 cells. In vivo studies further showed that ATO could cause mild lesions of main organs while RSANs could reduce the toxicity and improve the anti-tumor effects. In brief, the developed RSANs system provides a promising alternative for ATO treatment safely and effectively. [ABSTRACT FROM AUTHOR]

The accurate identification of the gas-liquid two-phase flow pattern within the impeller of a centrifugal pump is critical to develop a reliable model for predicting the gas-liquid two-phase performance of the centrifugal pump. The influences of the inlet gas volume fraction, the liquid phase flow rate and the pump rotational speed on the flow characteristics of the centrifugal pump were investigated experimentally. Four typical flow patterns in the impeller of the centrifugal pump, i.e., the bubble flow, the agglomerated bubble flow, the gas pocket flow and the segregated flow, were obtained, and the corresponding flow pattern maps were drawn. After oversampling based on the SMOTE algorithm, a four-layer artificial neural network model with two hidden layers was constructed. By selecting the appropriate network super parameters, including the neuron numbers in the hidden layer, the learning rate and the activation function, the different flow patterns in the centrifugal pump impeller were identified. The identification rate of the model increased from 89.91% to 94.88% when the original data was oversampled by the SMOTE algorithm. It is demonstrated that the SMOTE algorithm is an effective method to improve the accuracy of the artificial neural network model. In addition, the Kappa coefficient, the Macro-F1 and the Micro-F1 were 0.93, 0.95 and 0.95, respectively, indicating that the model established in this paper can well identify the flow pattern in the impeller of a centrifugal pump.

Arsenic trioxide (ATO) has a significant effect on the treatment of acute promyelocytic leukemia (APL) and advanced primary liver cancer, but it still faces severe side effects. Considering these problems, red blood cell membrane-camouflaged ATO-loaded sodium alginate nanoparticles (RBCM-SA-ATO-NPs, RSANs) were developed to relieve the toxicity of ATO while maintaining its efficacy. ATO-loaded sodium alginate nanoparticles (SA-ATO-NPs, SANs) were prepared by the ion crosslinking method, and then RBCM was extruded onto the surface to obtain RSANs. The average particle size of RSANs was found to be 163.2 nm with a complete shell-core bilayer structure, and the average encapsulation efficiency was 14.31%. Compared with SANs, RAW 264.7 macrophages reduced the phagocytosis of RSANs by 51%, and the in vitro cumulative release rate of RSANs was 95% at 84 h, which revealed a prominent sustained release. Furthermore, it demonstrated that RSANs had lower cytotoxicity as compared to normal 293 cells and exhibited anti-tumor effects on both NB4 cells and 7721 cells. In vivo studies further showed that ATO could cause mild lesions of main organs while RSANs could reduce the toxicity and improve the anti-tumor effects. In brief, the developed RSANs system provides a promising alternative for ATO treatment safely and effectively.

Although glucocorticoids are highly effective in treating various types of inflammation such as skin disease, rheumatic disease, and allergic disease, their application have been seriously limited for their high incidence of side effects, particularly in long term treatment. To improve efficacy and reduce side effects, we encapsulated betamethasone phosphate (BSP) into biocompatible red blood cells (RBCs) and explored its long acting-effect. BSP was loaded into rat autologous erythrocytes by hypotonic preswelling method, and the loading amount was about 2.5 mg/mL cells. In vitro, BSP loaded RBCs (BSP-RBCs) presented similar morphology, osmotic fragility to native RBCs (NRBCs). After the loading process, the loaded cells can maintain around 70% of Na⁺/K⁺-ATPase activity of natural cells. In vivo, a series of tests including survival, pharmacokinetics, and anti-inflammatory effect were carried out to examine the long-acting effect of BSP-RBCs. The results shown that the loaded cells could circulate in plasma for over nine days, the release of BSP can last for over seven days and the anti-inflammatory effect can still be observed on day 5 after injection. Totally, BSP-loaded autologous erythrocytes seem to be a promising sustained releasing delivery system with long anti-inflammatory effect.