Microwave assisted extraction method was used to extract polysaccharides from the fruited bodies of Ganoderma lucidum. The extraction process of polysaccharides was optimized and the antioxidant activity was investigated. According to the single factor experimental results, the solid-liquid ratio, extraction time, extraction temperature and extraction power were determined as independent variables, and the content of polysaccharide was chosen as the response value. The optimal extraction conditions were as follows: solid-liquid ratio 1:20(g/mL), extraction time 20 min, extraction temperature 80℃ and extraction power 570 W. The average polysaccharide content was 1.15% by three verification experiments under this process condition. The IC50 value of DPPH free radical scavenging rate and the IC50 value of ABTS free radical scavenging rate were 0.40 mg/mL and 0.21 mg/mL respectively, and the total reducing power of polysaccharide was better. The polysaccharide has antioxidant ability, which provides theoretical basis for further development of Ganoderma lucidum polysaccharide.

Potential targets of action, targets of intersection with hepatotoxicity, protein interaction network, GO analysis, and KEGG analysis of Longdan Xiegan Decoction (LXD) were investigated. A total of 881 potential targets of action were identified by searching the ingredients of LXD through TCMSP and using the SwissTargetPrediction database for potential targets of action. The GeneCards database was used to search for human-related hepatotoxicity targets and intersected with the data of targets related to the ingredients of LXD to obtain 178 common targets. Protein interaction networks were constructed through the STRING database, and 27 core targets were finally identified. Further GO analyses showed that these targets were involved in multiple cellular components, biological processes and molecular functions. The results of KEGG enrichment analysis showed that the pathways associated with liver injury mainly included cancer pathway, hepatitis C, and hepatocellular carcinoma. The results of this study provide some reference for the pharmacological effects and potential toxicity of LXD.

To investigate the effect of quercetin on adipogenic differentiation of 3T3-F442A preadipocytes and explore the mechanism of quercetin's influence on adipocyte differentiation and angiogenesis related gene expression, so as to provide a new basis for the prevention and treatment of obesity. Methods 3-(4,5-dimethylthiazol-2) -2,5-diphenyltetrazolium bromide (MTT) method was used to detect the effect of quercetin on the viability of 3T3-F442A pre-adipocytes. Lipid accumulation was detected by oil red O staining. The effects of quercetin on gene expression of 3T3-F442A differentiation related transcription factors (C/EBP-β, C/EBP-α, PPAR-γ and aP2), lipogenesis related vascular endothelial growth factors and receptors (VEGF-α and VEGFR-2) and matrix metalloproteinases (MMP-2 and MMP-9) were detected by RT-qPCR. The protein expression levels of phosphorylated adenosine monophosphate activated protein kinase (p-AMPK) and its substrate phosphorylated acetyl-CoA carboxylase (p-ACCase) were detected by Western blot analysis after quercetin treatment.Results Quercetin inhibited the viability of 3T3-F442A preadipocytes in a dose-dependent manner with a half-inhibitory concentration of 125.2 μmol/L. The transcription factors associated with 3T3-F442A adipocyte differentiation, C/EPP-β, C/EPP-α, PPAR-γ and aP2, were down-regulated by 120 μmol/L quercetin to 48.42%, 14.67%, 23.15% and 17.79% of the control group, respectively. Vascular endothelial growth factor VEGF-α and VEGFR-2 were down-regulated to 20.21% and 15.78%, matrix metalloproteinase MMP-2 and MMP-9 were down-regulated to 22.17% and 29.10%. The expression levels of phosphorylated AMP-dependent protein kinase (p-AMPK) and phosphorylated acetyl-CoA carboxylase (p-ACCase) were increased to 1.81 and 1.41 times that of the control group, respectively. Conclusion Quercetin down-regulates the expression of transcription factors and angiogenesis factors related to adipocyte differentiation by activating AMPK signaling pathway, and then inhibits the 3T3-F442A pre-adipocytes differentiation. 

 With the rapid development of energy storage technology and modern electronic technology, the demand for high-performance energy storage materials is increasing. Ba0.85Ca0.15Zr0.1Ti0.9O3 (BCZT)-based ceramics have attracted much attention because of their excellent dielectric and ferroelectric properties. However, the low energy storage density and energy storage efficiency limit its further development in the field of energy storage. By precisely controlling the doping concentration and component design, a series of (1-x)[0.92Ba0.85Ca0.15Zr0.1Ti0.9O3-0.08Bi(Zn2/3Ta1/3)O3]-x(Sr0.7Bi0.2)TiO3 ceramics were prepared using BCZT ceramics as the matrix. At the same time, through an in-depth analysis of the structure and dielectric properties of the doped ceramics, the effect of Sr0.7Bi0.2TiO3 doping on the energy storage properties of BCZT-based ceramics was studied. The results show that the doped ceramics samples have a single perovskite structure and the dielectric relaxation behavior is significantly improved. When the amount of Sr0.7Bi0.2TiO3 doping is x = 0.40, the energy storage performance is the best, and the released energy density and energy storage efficiency are Wrec = 5.431 J/cm3 and η = 93.38%, respectively. This provides a theoretical basis and experimental guidance for optimizing the energy storage performance of lead-free ferroelectric ceramics.

Aiming at the problems of inefficiency of dense multi-face detection, faces are easy to be occluded and difficult to be detected with small size, a YOLOv8-IFD dense multi-face detection algorithm is proposed. Based on YOLOv8, firstly, the DCNv2 convolutional variant module is embedded in the backbone network to increase the modulation mechanism and use the weights to adjust dynamically, and enhance the model learning ability to improve the detection accuracy; then, the CA attention mechanism module is introduced in the tail and neck networks of the YOLOv8 backbone network to strengthen the ability of image feature extraction, and inhibit the influence of irrelevant features on the accuracy; finally, a loss WIoD algorithm is introduced based on the dynamic non monotonic focusing mechanism based loss WIoU Loss is introduced as the bounding box regression loss function to accelerate network convergence and improve the detection accuracy of the model. Experiments are conducted using the Wider Face public dataset, and the results show that the improved YOLOv8-IFD algorithm improves the mean average accuracy by 2.4% compared with the original algorithm, and the amount of computation is relatively reduced. In addition, compared with other algorithms, there is a significant improvement in the effect of dense multi-face detection, which verifies the effectiveness and applicability of this improved method.

The power supply adopts TOP244Y chip as ,the main control core, and the feedback circuitcomposed of TL431 and PC817 realizes 4 isolated outputs with a power of 24 W, which can provide an efficientand reliable power supply solution for PMSM system. Through theoretical calculation, simulation and experimental verification, the power supply has achieved good results in the key indicators such as voltage output accuracy, ripple, load regulation and efficiency, and meets the design requirements of PMSM system.

 In response to the issues of significant time lag, slow dynamic response speed, and poor anti-interference capability in the actual operation of the corn alcohol fermentation temperature system, an optimized control strategy for a fuzzy cascaded PID control system based on the particle swarm optimization algorithm has been proposed, building upon the existing single-loop control. A preliminary cascaded PID control scheme was designed based on the single-loop PID, followed by the development of a fuzzy cascaded PID controller and the implementation of the particle swarm algorithm. Simulation analyses were conducted separately on the original traditional single-loop PID control and the particle swarm optimized fuzzy cascaded PID control. The results indicate that the particle swarm optimized fuzzy cascaded PID control strategy exhibits less overshoot, shorter adjustment time, and is more effective in overcoming disturbances within the alcohol fermentation temperature system.

This study explores, through four experimental cases, the application of Mathstudio software in the data processing of physical chemistry experiments, detailing its operational procedures and data processing capabilities. Compared to traditional methods, Mathstudio exhibits advantages such as portability, ease of use, low error rates, and high efficiency, thereby enhancing the quality of data processing and stimulating students' enthusiasm for learning. The experimental results indicate that Mathstudio's calculation accuracy is comparable to that of Python and Origin, while it excels in user experience and compatibility with mobile devices. This research confirms the effectiveness of Mathstudio in the data processing of physical chemistry experiments and contributes to the enhancement of students' innovative abilities and information literacy.

In order to explore the influence of flow field and component concentration distribution on the denitrification efficiency and ammonia escape of SNCR device, and improve the denitrification performance of the device, a three-dimensional computational fluid dynamics model of the boiler denitrification system was established by computational fluid dynamics (CFD) simulation method, and numerical simulation was carried out. By simulating the selective non-catalytic reduction (SNCR) denitrification process of a circulating fluidized bed boiler of a 350MW unit in a plant, the effects of spray gun position, ammonia nitrogen ratio, ammonia spray angle and droplet size on SNCR denitrification effect were studied, and the SNCR denitrification system of the boiler was optimized. The results show that the denitrification efficiency increases with the increase of the molar ratio of ammonia to nitrogen after adjusting to the symmetrical spray gun arrangement. The increase of ammonia spraying speed and the increase of atomized particle size of reducing agent also have a certain impact on the denitrification efficiency and ammonia escape. After the optimization of the boiler SNCR system and operating parameters, the maximum denitrification efficiency reached 79.09%. The results of this study are helpful to improve the denitrification efficiency and provide an important reference for the actual transformation design.

Since defects at welds of pressure pipelines may lead to serious safety accidents and economic losses, the welds must be inspected before being put into service to ensure their structural integrity and safety. To study the influence of defects at the welds of pressure pipelines on the electromagnetic characteristics of eddy current probes, COMSOL finite element simulation software was used to establish models of cracks, pores, weld beads, and arc pits at the welds. The distribution of the magnetic field around the probe and the distribution of eddy currents in the specimen under different defects were analyzed. The impedance waveform diagrams for different defects were derived, and the simulation model was validated through experiments.

Aiming at the Harris Hawk Algorithm (HHO), which has unsatisfactory convergence speed, poor accuracy of optimization search, and easy to fall into local optimization, a combined multi-strategy improved Harris Hawk Algorithm (PTHHO) is proposed.Firstly, the initialization of Piecewise chaotic mapping is used to improve the quality and diversity of the population; secondly, an adaptive t-distribution strategy is introduced in the exploration phase to improve the convergence speed and accuracy; and finally, a dynamic reverse learning strategy is introduced in the development phase to enhance the algorithm's ability of jumping out of the local optimal solution.In the experiments, eight benchmark test functions are simulated to evaluate the algorithm's optimization seeking performance, and the GWO, HHO, CGWO, and PTHHO algorithms are compared and analyzed to verify the effectiveness of the improved strategy.

A deep learning model combining Long Short-Term Memory networks (LSTM) and Parallel Residual Networks (ResNet) is proposed to enhance the accuracy of short-term load forecasting in power systems. This model leverages the time series analysis capabilities of LSTM with the deep feature extraction strengths of ResNet to effectively process complex electrical load data. The forecasting accuracy of the model is comprehensively assessed using three key performance indicators. Additionally, a detailed feature analysis further validates the appropriateness of the input features.

To address the needs of robotic arms in express package dismantling mechanisms, this study investigates the structural design of robotic arms. By employing an improved D-H parameter method, a corresponding joint coordinate parameter table is established. A related robotic arm model is built using MATLAB, and the correctness of its operation is verified through forward and inverse kinematics analysis. The Monte Carlo method is applied to analyze the working space of the robotic arm. Trajectory planning for relevant tasks is carried out in both joint space and Cartesian space, simulating the actual motion of the robotic arm. Additionally, the angles, angular velocities, and angular accelerations of each joint are analyzed for rationality, confirming the feasibility of the robotic arm's cutting motion trajectory.

An orthogonal experiment for plasma spray welding is designed by changing the welding current, welding gun movement speed and powder feeding amount. The optimal welding process parameters are optimized through microscope, metallographic examination, grain statistics, hardness and impact testing. The current is 60A, the moving speed of the welding gun is 40 cm/min, the powder feeding amount is 35%, the corresponding impact toughness is 175 J/cm2, the hardness of the spray welding layer is 678 Hv. After conducting  heat treatment at 1100 oC for 40 minutes in the furnace, the specimens with the optimal welding process are subjected to furnace cooling (annealing), air cooling (normalizing), and water cooling (quenching)+600 oC/2h tempering treatment. Metallographic observation, micro-hardness test, impact toughness test and grain size statistics of the spray welded layer are conducted on the above heat treated samples again. It is found that all three heat treatment processes can cause grain growth, which results in a decrease in the hardness of the spray welding layer. However, the annealing process has improved the toughness of the spray welded layer, with a toughness value of 189 J/cm2. However, the normalizing process has little effect on plasticity, while the quenching and tempering process reduces the plasticity of the spray welding layer. Finally, the annealing process of 1100 oC/40 min is determined as the optimal heat treatment process for the spray welding layer.

Starting from the overall refining process and gasoline pool composition, a Chinese petrochemical company analyzed the current status of gasoline production quality, benchmarking the requirements for upgrading the quality of National VI gasoline. Combining with the actual situation, by upgrading the production process technology of National VI gasoline quality, fully utilizing the existing oil resource structure, a low-temperature sulfuric acid process based on alkylation method was determined, and a simulated accounting production process was developed, laying a theoretical basis for the feasibility of upgrading the quality of National VI gasoline.