The silver-nano solution was synthesized by reacting silver nitrate with ulla grass and employed to modify linen and wool fabrics. The modified fabrics underwent SEM, FTIR, UV-Vis analysis, as well as antibacterial and washability testing. Optimal modification conditions for achieving bacteriostatic effects on E. coli and B. subtilis were determined by measuring the diameter of the bacteriostatic zone. Results indicated that both modified linen and wool fabrics exhibited a significant presence of particles on their surfaces, with antibacterial bands against E. coli and B. subtilis exceeding 1 mm. Furthermore, the antibacterial rate remained above 95% even after 20 washing cycles. Overall, the treatment process involving reduction of silver nanoparticles led to uniform attachment onto wool fabrics, thereby enhancing their antibacterial properties without compromising original performance characteristics. This environmentally friendly production method offers simplicity in operation while minimizing industrial waste water discharge.

Objective: The Ganoderma lucidum bud (GLB) of Huangsongdian was selected as sample for comparative analysis with the fruit body and spore powder in multiple indexes, which provide reference for further development and utilization. Methods: According to the 2020 edition of Chinese Pharmacopoeia, appearance, thin-layer chromatographic identification (TLC), moisture, ash, heavy metal check and content determination of the main active ingredients were performed. The TLC results of GLB and Ganoderma lucidum control herbs were consistent; the heavy metal contents were 0.1 mg/kg for Pb, 0.07 mg/kg for Cd, 0.2 mg/kg for As, 0.1 mg/kg for Hg, 19 mg/kg for Cu; the moisture content of fresh GLB was 81.31±0.05%, and after drying it was 12.29±2.47%; the ash check was 1.42±0.02%; among the main active ingredients polysaccharide content was 1.42±0.03%, triterpene was 2.83±0.32% and soluble protein was 4.45±0.16 mg/g. Conclusion: GLB polysaccharide and protein were higher than Ganoderma lucidum fruit body and spore powder, and the experimental results helped to promote the sustainable development of the Ganoderma lucidum industry.

At present, fruits are widely planted, but most of the fruit classification is done manually, which consumes a lot of labor costs, and a few machine recognition also has problems such as slow speed and low accuracy. To solve the problem of low efficiency of target detection and recognition, a fruit target detection algorithm based on improved YOLO v7 algorithm is proposed. By introducing ECA attention mechanism, the relevance of channel dimensions is enhanced, and the expression ability and learning effect of the model are improved; PConv is used instead of partial convolution structure, and redundant computing and memory access are reduced to extract spatial features more effectively; The loss function uses MPDIoU, which enhances the gradient differentiability for traditional IoU, facilitating the training and optimization of image segmentation tasks. The improved YOLOv7 algorithm can accurately recognize fruits by improving the precision and average accuracy by 4% and 3% respectively.

Object detection occupies an important place in computer vision and is gradually becoming the technical basis for many applications.The application of object detection in fruit recognition can improve the efficiency of fruit picking, but the efficiency of fruit object recognition based on traditional methods is relatively low due to the problems of background complexity,large model similarity, serious texture interference, and local occlusion of fruits. In order to solve this problem,this paper proposes a fruit detection and classification algorithm MSP-YOLO based on YOLOv5. Firstly,the backbone network of YOLOv5 was replaced with another more lightweight backbone network, MobileNetV3, which could reduce the size of the model and improve the detection rate of fruits. Secondly, this paper introduces the SE attention mechanism into the improved network, and adds the SE attention mechanism to the neck middle layer network of the YOLOv5 base model. The advantage of the SE attention mechanism is that it can help the model pay more attention to the feature channels with the most channel information, so as to suppress those channel features that are not important to the whole, so as to improve the accuracy. Finally, by changing the loss function CIoU to MPDIoU, the similarity comparison between the bounding boxes is simplified, which can better optimize the dataset and improve the recognition accuracy of fruit detection. Experimental results show that the accuracy of MSP-YOLO on the dataset reaches 92.7% mAP, which is 3.3% higher than that of the unimproved YOLOv5, and the improved algorithm is superior to the main object detection models Faster R-CNN, SSD, YOLOv7-tiny, YOLOv3-tiny, YOLOv4 and the original model YOLOv5 in terms of detection accuracy and rate.

With the rise of artificial intelligence, and the rapid development of innovative technologies such as big data and cloud services, the Internet has applied virtual world network technologies to the physical world, ushering in a new era of the "Internet of Everything." Currently, traditional smart home solutions in the market commonly face issues such as high development costs, difficulty in installation, and poor user interaction experiences. To address these problems, a smart home system based on Raspberry Pi has been designed. The system uses Raspberry Pi for data processing and human-computer interaction control, while microcontrollers are employed to control driver modules, achieving home automation and intelligence. The system is composed of subsystems including facial recognition access control, smoke alarms, automatic window closing, voice interaction, and network data collection. After conducting functional tests on each subsystem, the system demonstrates excellent performance, reliable and accurate operation, and meets real-time functional requirements as expected. The system satisfies the demands for home automation and has broad application value.

The combustion system of circulating fluidized bed boiler has complex nonlinear characteristics, so accurate mathematical model is very important for its effective control. In this paper, the factors affecting the dynamic characteristics of bed temperature and steam pressure are analyzed, and a dynamic model between coal feed and primary air volume and bed temperature and steam pressure is established. The parameters of the model are identified by least square method, and the accuracy of the model is verified by simulation. The results show that the model can reflect the dynamic relationship among coal feed, primary air, bed temperature and steam pressure. This model provides a theoretical basis for the optimal control and stable operation of CFB boiler combustion system.

In order to solve the problems of chattering, low accuracy and uncertain parameters in the trajectory tracking of two-link flexible manipulator, an observer-based adaptive second-order sliding mode controller is designed. The dynamic equation of the two-link flexible manipulator is given according to Lagrange equation and energy conservation law, and a sliding mode observer is designed. Then, based on the error state equation, an adaptive second-order sliding mode control law is designed, in which the super-twisting algorithm is used to suppress chattering, and the stability of the closed-loop system is proved by Lyapunov theory. Simulation results show that the proposed control strategy has the advantages of high tracking accuracy, less chattering and better robustness.

The next generation of IPv6 protocol based networks has significantly improved network security compared to IPv4 protocol networks. However, security risks still exist in areas such as IP forgery, address flooding, spoofing, and DDOS denial of service attack,etc. By using SAVI technology, the access layer IPv6 address security issue has been solved, thereby improving the security and reliability of IPv6 network.

Dissolved organic matter (DOM) is widely present in the water ecosystems of the natural world and is a major component of organic matter in aqueous phase. It participates in various biogeochemical processes in water ecosystems and has a significant impact on the structure and function of water ecosystems, making it a hotspot and a difficult point of research in environmental science. In order to explore the existence form of DOM in the Songhua River, the three-dimensional fluorescence spectrum of DOM in the water environment of Songhua River, Jilin City section was measured, and the abundance, fluorescence peaks and fluorescence parameters of FDOM in the Songhua River, Jilin City section were analyzed. The DOM's three-dimensional fluorescence spectrum was resolved by using the fluorescence region integration method, and the structural composition characteristics of DOM were obtained. The results show that the rivers in the urban concentrated area and industrial area have higher FDOM concentrations, and the water body DOM has four fluorescence peaks. The DOM fluorescence peak of the industrial river shows high content of humic-like substances, and the DOM fluorescence peak of the urban concentrated area river shows high content of protein-like fluorescence. The DOM in the rivers of the urban concentrated area and industrial area also has higher fluorescence index (FI), humification index (HIX) and autochthonous source index (BIX). Through the analysis by the fluorescence region integration method, the highest content of humic-like substances in the river DOM, followed by fulvic acid-like substances and dissolved microbial metabolic products.

The orthogonal design method was used to study the formation of magnesium ammonium phosphate (MAP) crystal. The results of variance analysis showed that the pH value of solution, initial P concentration (C₀), and its interaction are the significant factors for the formation of MAP crystal, which play the decisive roles in these process. According to the K values of factors, the optimal formation process of MAP was determined as A₃B₃C₃D₂E₁F₂. And under the optimal condition, 2.241g MAP crystal was prepared. The SEM analyses showed that the composition of the precipitate was mainly magnesium ammonium phosphate. 

Objective: The effects of curcumin on the differentiation and adipogenesis of 3T3-F442A preadipocytes are investigated. Methods: The effects of 0-100 μM curcumin on the proliferation of 3T3-F442A cells at 24, 48 and 72 h are detected by MTT assay; 3T3-F442A preadipocytes are treated with induced differentiation medium supplemented with 30 μM curcumin, and the effects of curcumin on the adipogenicity of 3T3-F442A preadipocytes are observed by Oil Red O staining method; RT-q PCR, Western blot, and ELISA assay are used to detect the effects of curcumin on the expression of 3T3-F442A preadipocyte differentiation-related transcription factors, adipogenesis-associated vascular endothelial growth factors and receptors, and matrix metalloproteinases expression, phosphorylation levels of p38 MAPK. Results: Curcumin inhibits the proliferation of 3T3-F442A adipocytes, down-regulated the expression levels of adipocyte differentiation-related transcription factors, vascular endothelial growth factors and receptors, and matrix metalloproteinases, and also down-regulates the phosphorylation level of p38 MAPK. Conclusion: Curcumin inhibits 3T3-F442A preadipocyte differentiation and adipogenesis by inhibiting the p38 MAPK signalling pathway and matrix metalloproteinase activity.

In this paper, the effects of thermal radiation and magnetic field on the fluid flow and heat transfer of the nanofluids in a square cavity are numerically studied. The square cavity is filled with the absorbing-emitting-scatterng Al₂O₃/water nanofluids, which is assumed to be viscous, incompressible, and also have electrical conductivity. The top and the bottom walls of the square cavity are perfectly insulated while the left and right vertical walls are maintained isothermal. All the governing equations are solved by using the collocation spectral method. After the validation of numerical results, streamlines, isotherms, and Nusselt number are analyzed for the effects of the inclination angle of the magnetic field and the emissivity of walls.

Research on boiler using biomass gas as fuel was of great significance to promoting the utilization of biomass energy.For the first time, a single baffle horizontal boiler burning biomass gas was proposed, which was equipped with a tail flue gas recirculation heat pipe to study the main combustion flow field of the biomass gas furnace. The main combustion flow field of biomass gas furnace was studied at the inlet velocity of 10m/s, 15m/s and 20m/s. the temperature distribution, combustion and flue gas resistance were analyzed, and the central line heating capacity p and

pressure difference d were proposed. It was concluded that under the designed structure, the combustion was rapid, the flame position was stable, the maximum temperature in the furnace was less than 1400K, and there was no thermodynamic NOX produced. The strong heating capacity area was concentrated between the area of Z=0.2~1.5m. The hot water pipe could reduce the maximum exhaust temperature by 176K without producing large flow resistance. However, under condition 3, the positive pressure was partly made in the furnace,which caused the inlet velocity should be controlled. Overall, the design can meet the requirements of stable combustion of biomass gas and made no NOx emissions,which could play an important role in promoting large-scale application of biomass gas and showed obvious environmental and economic values.

This paper proposes an improved optimization algorithm based on SURF image Mosaic algorithm. First, in view of the high computational complexity and low matching accuracy of SURF algorithm when extracting feature points, the principal component analysis method is used to optimize SURF algorithm to reduce the data dimension of feature points, thus reducing the computational workload and improving the matching accuracy. The experimental results show that the proposed optimized SURF image splicing algorithm has higher efficiency and accuracy in the process of extracting feature points and matching, and has achieved significant improvement in image splicing effect.

In the light of frequent electric vehicle charging safety accidents, by analyzing the factors affecting the charging safety of electric vehicle batteries and Charging station, applying the analytic hierarchy process, selecting the indicators that affect the charging safety, constructing an evaluation system for the charging safety of electric vehicles, giving weights to the indicators at all levels, and conducting consistency inspection, this paper analyzes the evaluation results of H electric vehicle charging station, and puts forward suggestions for improving the charging safety of electric vehicles.