With the rapid development of automation and artificial intelligence,mobile robots have been widely penetrated into all walks of life,and path planning technology is the key to ensuring their autonomy and efficiency.This paper deeply analyzes several mainstream path planning algorithms,including graph search,random sampling,intelligent bionics,and deep reinforcement learning,and reveals the advantages and challenges of each algorithm in practical applications.This paper further classifies the path planning research according to the application scenarios and specifically analyzes the path planning methods and development trends of land robots,unmanned aerial vehicles,and underwater robots in their respective fields.In addition,this paper also looks forward to the possible future development directions of path planning techniques.Through this overview,this paper aims to provide valuable information and research ideas for researchers in this field.

Aiming at the problems of long training time and slow convergence speed of deep reinforcement learning methods in robot path planning,an improved Twin Delayed Deep Deterministic Policy Gradient (TD3) algorithm is proposed.The algorithm introduces the gravitational field and repulsive field in the artificial potential field to optimize the reward function of TD3,which guides the robot to avoid obstacles to the target point reasonably,so as to improve the convergence speed and accuracy of the algorithm;at the same time,it applies motion constraints rules to constrain the direction of the robot’s motion,which makes the trajectory smoother and more fluent.The results of simulation experiments show that in a multi-obstacle environment,the proposed algorithm can effectively make the robot avoid obstacles and plan a reasonable path,and the improved algorithm has a higher planning success rate and a shorter planning path compared with other methods.

When processing the heterogeneous data over the years in the multi-source big data fusion stage,multi-index and multi-dimensional problems are involved,and cleaning,transformation,mapping and alignment operations are needed.Related data processing tools and methods are gradually emerging,but it is still difficult to solve the problem of cross-fusion of a large number of data.Multi-source heterogeneous data fusion methods were studied based on ETL technology,the common ETL tools and data fusion techniques were analyzed,including data extraction,conversion,loading tools,and the data-processing algorithms.This paper analyzes the heterogeneity of data sources,data structure difference,difficulty of data update frequency,and studies the methods of modular extension and repeated use of ETL tools from modular design,logical and parameter separation,standardized component library,configuration file in lightweight JSON format,so as to better handle large-scale heterogeneous data.It solves the problem of cross-fusion in the multi-source big data fusion stage,which is of great significance to improve data processing efficiency,ensure data quality,and support more in-depth data analysis and decision-making.

A novel polymerized aluminum ferrosilicate flocculant (PSAFC) was prepared by using the acid leaching and alkali dissolved method based on the utilization of the natural composition of Si,Al,Fe,and Ca in coal gasification fine slag.Based upon the optimized preparation conditions,PSAFC was characterized by using X-ray fluorescence spectroscopy (XRF),X-ray diffraction (XRD),and Fourier-transform infrared spectroscopy (FT-IR).It was found that PSAFC was an amorphous,non-crystalline polymer inorganic flocculant formed by the aggregation of Si,Al,Fe,Ca elements.Subsequently,the flocculation performance of PSAFC was investigated by using kaolin suspension as the target.The results revealed that PSAFC exhibited optimal performance for kaolin suspensions with the removal efficiency more than 95% under the optimal conditions of the initial turbidity of 1 439 NTU,the mass concentration of PSAFC of 50 mg/L and pH 10.This investigation offers a novel approach and method for the comprehensive utilization of coal gasification fine slag and the preparation of polymer inorganic flocculants with high-performance.

Based on the First Principles,using the CASTEP module and virtual crystal approximation model,utilizing GGA+PBE functional correlation function,the influence of composition on mechanical properties parameters in AlSi7MgX (X=0.1~0.5) and AlSiXMg0.3 (X=6~9) alloys was studied.It is shown that the lattice constant decreases with the increase of the content of the alloy elements,and there exists a difference of approximately 0.265% between the maximum and minimum values;the elastic constants C11,C12,and C44 meet the structural stability conditions.The volume elastic modulus B,shear modulus G,Young’s modulus E,and Poisson's ratio u vary with Si and Mg content in A356 alloy.The change of Mg content has a more sensitive effect on the shear modulus G and Young's modulus E than the change of Si content.The comparison between the calculation results and existing experimental data shows that the calculation results are close to the experimental data,and it is feasible by using the First Principles to calculate the material parameters.

The incidence of hyperuricemia is increasing year by year,and the impact of hyperuricemia on human health has become a hot and cutting-edge issue in the field of biomedicine.Existing studies have confirmed that long-term high uric acid levels can cause chronic damage to patients′ joints and kidneys,but there are still few studies on the impact on immune homeostasis.This study successfully constructed three mouse models of hyperuricemia using different chemical inducers,and analyzed changes in uric acid,renal pathological changes,B cells in peripheral blood that are mainly responsible for humoral immunity,T cells that are responsible for cellular immunity,and innate proportion of immune cells such as NK cells and other immune cells was studied in detail.The results showed that compared with the normal control group,the proportion of B cells in the three hyperuricemia mouse models all decreased significantly,and the proportion of CD4+ T cells,CD8+ T cells and B cells in the 600 mg/kg high-dose xanthine exposure group declined particularly significant.This study reveals the important impact of hyperuricemia on the body from the perspective of immune homeostasis,provides a reference for the construction of a hyperuricemia model,and puts forward new ideas for the pathogenesis of gout and other diseases induced by hyperuricemia.

With the increasingly severe energy problem,the design idea of converting lignocellulose,which is abundant renewable resources in nature,into second-generation fuel ethanol provides a way to solve the current energy crisis,food crisis and environmental crisis.However,microorganisms also face a number of technical problems in the process of fermentation to produce second-generation ethanol.Among them,a variety of small molecule chemicals produced by lignocellulosic degradation will not only inhibit the growth and reproduction of microorganisms,but also reduce the fermentation efficiency of microorganisms.Acetic acid is one of the main inhibitors commonly found in many degradation products of lignocellulosic materials.In order to improve the efficiency of microbial lignocellulosic ethanol fermentation,this study selected Saccharomyces cerevisiae,an ethanol fermentation strain with the greatest potential in industrial production,as the model organism,and simulated the acetylation of histone H3K9 by mutating the ninth lysine (K) of histone H3 into glutamine (Q) to investigate the tolerance of histone H3K9Q point mutants to acetic acid,a fermentation inhibitor.The results showed that H3K9Q point mutation could significantly improve the growth performance of Saccharomyces cerevisiae under acetic acid.The growth curve experiment further showed that H3K9Q point mutation could make the strain rapidly enter the exponential phase under 3.5 g /L acetic acid stress,which was shortened from 36 h to 24 h.Moreover,after 48 h of growth in medium with acetic acid,the OD600 of H3K9Q point mutant was about 1.9 times that of the control strain.These results indicated that H3K9Q point mutation significantly improved the acetic acid resistance of Saccharomyces cerevisiae,and this study provided a useful reference for strain optimization in cellulosic ethanol production.

In the power system,power lines carry the important task of conveying electric energy,and safe and reliable power lines are of great significance to the solid development of the power system.Aiming at the problems of low accuracy and poor real-time detection of hanging objects,tower cranes and other targets in power lines using deep learning algorithms,a power line safety detection and anomaly identification method based on improved YOLOv5 is proposed.The method is based on the YOLOv5s algorithm,which introduces the ECA attention mechanism in part of the C3 module of the network to enhance the feature extraction capability of the network;adds the Fast-RFB module to enhance detection speed and accuracy after the pooling layer in the backbone network;uses the decoupled head to replace the coupled detection head of the original network to improve the detection accuracy;and finally,replaces the CIoU loss function of the original model with the Wise-IoU loss function of the original model to reduce the loss of training process.Simulation experiments show that the P_mA0.5 and P_mA0.5:0.95 of the improved YOLOv5s algorithm on the power line dataset are 92.2% and 56.5%,respectively,which exceeds the original YOLOv5 model by 10.3% and 7.3%,respectively,and the detection speed is 83 frames/s,which meets the requirements of safety detection and anomaly identification of power lines in the real environment.

With the wide application of action recognition technology in the fields of risk monitoring and human-computer interaction,human action recognition based on video data has gradually become a new hotspot in the field of computer vision research.Due to the continuous improvement of graph neural network methods,deep learning methods based on graph neural network have been gradually applied to human bone data in recent years to improve the efficiency of human action recognition algorithms.Therefore,this paper introduces the related methods of human action recognition based on graph neural network,analyzes and summarizes them.Firstly,the development status of human action recognition algorithm based on graph convolutional network is introduced.Then the data sets commonly used in action recognition and their characteristics are proposed.Finally,the future research direction and trend are discussed.

Lactic acid bacteria,as a globally recognized and safe microorganism,have been widely used in various fields such as food and medicine for a long time.Traditional Chinese medicine has a history of over two thousand years in the field of skincare in China.Fermentation,as a unique process,can play a role in enhancing drug efficacy and reducing toxicity by leveraging the unique metabolic pathways of microorganisms.In recent years,traditional Chinese medicine fermented by lactic acid bacteria has gradually been applied as a raw material in various skincare products.The research and production of natural skincare raw materials have gradually become a key competitive direction for domestic and foreign cosmetics companies.The article summarizes the latest research progress on the application of lactic acid bacteria fermented traditional Chinese medicine in cosmetics,and carries out an overview of its skincare effect,effective active ingredients,and skincare mechanism,in order to provide theoretical basis for further research and subsequent production practice in this field.

With the continuous promotion of China's “Ocean Power Strategy” and the rapid development of the global “blue economy”,higher requirements have been put forward for the field of maritime communication.However,at present, most research in the maritime communication mainly focuses on channel analysis and measurement,making it difficult to directly apply it to practical maritime communication.A statistical model for evaporation duct channels has been developed based on this.This model is based on the relevant data generated by the PETOOL toolbox to establish a statistical channel model for the evaporation duct in the Beyond Line of Sight (B-LOS) scenario.The constant coefficients of the variables in the model are corrected using the least squares method to reduce errors and improve the accuracy of the statistical model.Finally,through numerical analysis,the obtained evaporation duct statistical channel model has a good fitting effect.

Self-service terminals play a key role in the modern service industry.Through the comprehensive use of face recognition,fingerprint recognition and other biometric technologies as well as various input and output devices,they can efficiently and accurately confirm customer identity and provide customers with a more efficient and convenient self-service experience.However,at present,self-service terminals generally have low face recognition accuracy,and one of the main reasons is that the shooting angle of the devices face can not adapt to customer groups of different heights,resulting in frequent face recognition failures in the process of business processing,and business processing can not be completed normally.In response to this pain point,this paper proposes an innovative solution,which combines AI technology with intelligent adjustment of camera angle,significantly improves the adaptability of self-service terminals to users of different heights,and fundamentally improves the service experience of users.Through in-depth analysis of the existing technology problems,this paper puts forward a complete set of technical solutions,including system architecture design,key technology realization and advantages and characteristics,to provide practical experience for the technical progress and innovative development of the self-service terminal industry.

Accurate wind power prediction is the basis to ensure the stable operation of wind power grid connection.In order to improve the accuracy of wind power prediction,this paper proposes a new prediction model,firstly,the chaos strategy is used to initialize the population,and the whale optimization algorithm (WOA) is optimized using the Harris Hawk strategy (HHO) with the adaptive weight strategy,and then the improved whale optimization algorithm (HHO-CAWOA) is used to optimize the long and short term memory neural network (LSTM) with the improved whale optimization algorithm (HHO-CAWOA) to optimize the number of neurons and the learning rate,and finally the model is used for wind power prediction.The model has higher prediction performance and better generalization ability and stability than other comparative models.

With the development of the economy and society,science and technology continue to progress,and human production and lifestyle have undergone tremendous changes.Many tasks have been replaced by various robots or assisted by robots to complete.Most operational robots are based on fixed bases,wheeled mobile platforms,or tracked mobile platforms,and cannot enter complex terrain environments to perform operational tasks.The quadruped robot with a single arm solves this problem effectively.This article conducts research based on the quadruped robot with a single arm.Firstly,several representative quadruped robots with a single arm,both domestically and internationally,were introduced.Then,the research status of quadruped robots with a single arm based on simulation platforms and physical experimental platforms was introduced,and the current popular research ideas were analyzed.Next,some commonly used simulation platforms were listed,and the integration and implementation of the quadruped robot system with a single arm were introduced.Finally,a summary was made and the ideas for future research work were introduced.

Trametes versicolor laccase is a copper-containing polyphenol oxidase that can oxidize a variety of phenolic and aromatic compounds.Its main product is water,and it produces almost no toxic by-products.While it has good application prospects,the low yield of Trametes versicolor laccase limits its further application.This study used Atmospheric and Room Temperature Plasma (ARTP) technology to successfully mutate a new strain,TA-03,from Trametes versicolor ATCC20869.To enhance laccase production,the paper optimized fermentation conditions through single-factor shake flask experiments and response surface analysis.The results showed that under optimized conditions,with a farnesol addition of 4.48 mmol/L,copper sulfate addition of 1.90 mmol/L,and pH maintained at 4.00,the laccase production of the mutant strain reached （283.77±8.91） U/mL.To explore the reasons for the increased laccase activity of the mutant strain TA-03,resequencing and transcriptome analysis were performed.The research results show that the mutation of amino acids in the active region of laccase and the enrichment of metabolism and other aspects lead to the improvement of laccase activity.This provides a meaningful exploration of the practical application of Trametes versicolor laccase and enhances the application of laccase in the fermentation industry.

Hydrodynamic cavitation technology is gradually gaining widespread application,and the accurate and efficient extraction of structural characteristics of cavitation clouds contributes to a better understanding of the internal mechanisms of cavitation.In this study,high-speed imaging experiments were conducted to reveal the characteristics of cavitation phenomena within a jet oscillator through grayscale value analysis.Additionally,the dynamic mode decomposition method(DMD) was employed to conduct an in-depth exploration of the transient flow field inside the oscillator,investigating the coherent structures and frequency characteristics of cavitation clouds within the oscillator.Furthermore,different dominant structures were extracted,and the overall cyclic dynamics relationship with cloud cavitation under shedding frequency was discovered.Finally,using the DMD method,this study accurately extracted the dominant frequencies and modal characteristics,revealing that the energy of the oscillator mainly concentrates in the first two modes,forming larger coherent structures,while higher-frequency modes contain less energy.These experimental results provide important experimental and theoretical foundations for further research into the mechanisms of jet cavitation flow.

Real time object detection is a very important topic in computer vision and a necessary component in computer vision systems.For the problem of urban traffic vehicle detection,the YOLO model can be used to achieve intelligent road vehicle detection.To optimize the real-time detection capability of computers for vehicles,this paper proposes an improved YOLO vehicle recognition and detection algorithm based on attention mechanism.YOLOv7 is used as the main body,and attention mechanism is introduced for the Backbone and Head modules of the YOLOv7 network model to adapt to different vehicle recognition tasks.Experimental validation is conducted using a publicly available dataset of Roboflow,demonstrating notable improvements in car detection performance compared to the original YOLOv7 model.The enhanced network achieves a P_mA value of 72.2%,marking a 0.9 percentage point increase over the baseline YOLOv7 model on the same dataset.These results underscore the efficacy of the proposed algorithm in meeting the requirements of vehicle detection applications.

Video anomaly detection has attracted much attention due to the unpredictability of surveillance video anomaly events and the complexity of the anomaly environment. Currently, video anomaly detection often utilises unsupervised methods to acquire video information, but the lack of spatio-temporal information acquisition during feature extraction leads to the problem of inconsistent spatio-temporal features. To this end, a memory-guided two-stream spatio-temporal coding network (MSTAE) model based on memory-guidance is proposed, and a two-stream spatio-temporal feature extraction network is designed to obtain the motion features of the video in spatial streams and the temporal features in temporal streams using continuous video frame sequences and optical flow graphs as inputs, respectively, and at the same time, the attention mechanism is introduced to improve the encoder and reduce the risky error due to the data redundancy. Extensive experiments are conducted on three open standard datasets (Ped2, Avenue and ShanghaiTech datasets), and the experimental results show that the AUC accuracy of the model outperforms the state-of-the-7art methods.

A rapid prototyping technology for metal alloys is introduced.The technology is based on the principle of dynamic directional solidification.The grain refinement and porosity reduction of the alloy microstructure can be achieved by high pressure water jet dynamic and rapid cooling without adding refining agent,metamorphic agent and degassing agent,and the mechanical properties of the alloy can be improved.The condensation time of A356 aluminum alloy prepared by this technology can be shortened to 15 s.The microstructure is uniform,the primary phase (α-Al) and eutectic Si phases are obviously refined,the secondary dendrite arm spacing is significantly reduced.The porosity defects are effectively improved,the porosity can be reduced to 1.1%.The tensile strength of alloy is as high as 285 MPa.

 Metal-organic framework materials (MOFs) cannot be widely used due to their powder state,which is compensated by the combination with a large number of hydroxyl sites on the surface of cellulose materials.The composites combining MOFs and cellulose (i.e.,MOFs/cellulose composites) are currently used for applications in water treatment,such as heavy metals,organic dyes,pharmaceutical wastewater,and uranium treatment.This paper reviews the progress of MOFs/cellulose composites for water treatment applications in recent years.Firstly,it adopts a visualization method to make a map of MOFs/cellulose materials in recent years,introduces the preparation methods of MOFs/cellulose composites,and analyzes the advantages and limitations of each of them;at the same time,it describes the application examples of MOFs/cellulose composites in water treatment,including adsorption,catalytic,and membrane separation;and finally looks forward to the prospect of its development.

A real-time fluorescent PCR method was developed for rapid qualitative detection of Streptococcus faecalis in PC drinking water barrels.The 23S rDNA gene sequence of Streptococcus faecalis was amplified and detected by using specific primers and probes.The specificity and repeatability of our method was evaluated based on the comparative use of our method and the national standard method to detect PC drinking water bucket samples.The results indicate that our method can quickly and qualitatively detect Streptococcus faecalis in PC drinking water barrels,effectively shorten detection time and reduce experimental operations,with high specificity and repeatability.

In this study,the formation process of humic substances (HS) and the variation of chemical structure were investigated by the tank high-temperature aerobic composting process with chicken manure and fungus residue as raw materials.The results showed that the chicken manure was treated by canned aerobic composting,the start-up speed of the composting was fast,the overall high temperature duration of the composting was long,the temperature above 50 ℃ lasted for more than 4 days,and the water content decreased rapidly to less than 25%;a large number of proteins,fats and sugars in the material were decomposed and utilized by microorganisms and then reconverted into macromolecular organic matter,composting to the 6th day,the C/N ratio reached 10.10±0.72,and the decomposition process was basically completed;3D-EEM spectrograms showed that fulvic acids were biologically oxidized to generate a more stable humic acid（HA）structure throughout the composting process,but after the 6th day,due to the decrease in the content of small-molecule organic matter,it resulted in the accumulation of fulvic acids.Therefore,the conversion of fulvic acid (FA) to HA can be further promoted by increasing the content of small molecule organic matter at the later stage of composting.

Based on a generalized derivative nonlinear Schrodinger (gDNLS) equation,this paper proves the error of the Jump matrix under time evolution about the Riemann-Hilbert problem on a straight line of the initial value problem.When the time tends to infinity,the error order of the Jump matrix and the long-term asymptotic solution changes from O(t-1/2) to O(t-1/2ln t).

Aiming at the non-linear and time-varying problem of indoor light illuminance distribution, an imporved differential evolution (IDE) and Gaussian process regression (GPR) method combined with isolation forest (iForest) is proposed to build a prediction model for indoor light illuminance.Firstly,the outliers are removed and the rest of the data is normalized by using the isolation forest algorithm.Then,an evolutionary state-based probabilistic selection strategy is proposed to overcome the premature convergence problem of the traditional DE algorithm,and the variation factor F is set to obey the normal distribution to improve the performance of the algorithm.At the same time,the IDE algorithm is used to optimize the hyperparameters of the GPR model with uncertain quantitative characteristics,so as to establish the optimal predictive model for indoor lamp illuminance.Finally,the model based on isolation forest and IDE-GPR proposed in this paper is compared with other models,and the experimental results show that the R2,δMAE,and δRMSE of this model are 0.999,0.245 lux,and 0.324 lux better than the other models,and it can more accurately predict the lighting state of the indoor light environment.

Pulp and paper industry is faced with many problems,such as difficult pollution control,less raw material supply and high energy consumption.This paper conducts experiments to study the compounding of three biological enzymes for pulping,using a combination of biological pulping and mechanical pulping.At the same time,two enzyme preparation treatments are designed to utilize agricultural waste wheat straw and improve the pulping process after pulping into paper.The paper performance was tested and it was found that compared with simple mechanical pulping and primary enzyme treatment,the secondary biological enzyme treatment improved the paper-forming effect.Compared with untreated straw,the tensile strength is nearly doubled,the tear strength is increased by 36.5%,and the water retention value is increased by 78.8%.

This paper aims to study the numerical solution of the coupled sine-Gordon equations on an unbounded domain,which is widely applied in plasma physics.The unboundedness of the physical domain and the nonlinearity of the equations make it challenging to derive the numerical solution.Employing the artificial boundary method and the operator splitting approach to overcome the unboundedness and nonlinearity,the splitting local artificial boundary method was established for the coupled sine-Gordon equations.The Cauchy problem was reduced into an initial boundary value problem on a bounded computational domain,which can be efficiently solved by the finite difference method.The accuracy and effectiveness of the proposed method were demonstrated by some numerical results,and the propagation of solitons was simulated.

The CRISPR (clustered regulatory interspersed short palindromic repeat) system has been widely used in biological gene editing research due to its high efficiency,tracelessness and simplicity.As far as microbial gene editing is concerned,the research of this system mainly focuses on the gene editing operation of haploid cells.However,for polyploid cells,which have a more complex genetic background,the lack of efficient gene editing systems is a key factor limiting the genetic modification and application of industrial strains.Therefore,in this study,a CRISPR/Cas9 gene editing system was constructed and systematically optimized for sgRNA expression driven by two promoters,RNA Pol Ⅱ (Pol Ⅱ) and RNA Pol Ⅲ (Pol Ⅲ),using a diploid industrial strain of Saccharomyces cerevisiae,and optimized the transformation conditions to improve the efficiency of multilocus gene editing.The results showed that the Pol Ⅱ promoter could achieve three pairs of alleles (six genes) to be knocked out at one time with an efficiency as high as 68%.Subsequently,preliminary explorations of multilocus knock-down of target genes were also carried out.The CRISPR/Cas gene editing system for industrial strains of S.cerevisiae established in this study provides strong technical support for rapid genetic modification of strains.

This article attempts to use the proof methods of reduction to absurdity and classification discussion to provide the strict proofs for “there are infinite primes in the form of 8k+1(k∈Z)”,“there are infinite primes in the form of 8k-1(k∈Z) ”,“there are infinite primes in the form of 8k+3(k∈Z) ”,and “there are infinite primes in the form of 8k-3(k∈Z) ”.The used knowledge is the fundamental knowledge in elementary number theory,limited to some basic properties of prime number,integer division,congruence,and Legendre symbol.To prove the main conclusions,this article first derives two very useful lemmas.

A fuzzy relation is a generalization of a classical binary relation,which is an important tool for dealing with fuzziness related problems.Aggregation of fuzzy relations has a wide range of applications in the fields of data mining,engineering design,and decision analysis.This paper focuses on the properties of fuzzy relations (reflexivity,symmetry,transitivity,connectedness,etc.)in the aggregation process,discusses the problem of preserving the properties of fuzzy relations as well as fuzzy ordinal relations by different aggregation operators.Finally,gives an example of solving a multi-criteria decision-making problem by using fuzzy ordinal relations.

The requirement of the flywheel energy storage device is to ensure a constant voltage of the bus capacitor during the charging and discharging processes.Aiming at the problems of non-linearity and poor robustness under traditional voltage outer loop PI control,an improved sliding mode voltage square control is proposed.The system achieves global linearization control,and improves the robustness of the system in a wide range of speed regulation.In addition,the sign function of the current sliding mode inner loop is changed to a relatively saturated function.On the basis of retaining excellent robustness,the system chattering and harmonic effects are reduced.The results show that the proposed control strategy has a faster response speed and better anti-interference ability than traditional voltage control.

The edema around the hematoma after hemorrhagic stroke has attracted widespread attention in recent years as a marker of secondary injury after cerebral hemorrhage.Studying the occurrence and progression of edema around hematoma in patients,early identification and prediction,is of great significance for improving patient prognosis and enhancing their quality of life.Based on real clinical data such as patient personal information,imaging information,treatment plans,and prognosis,polynomial regression models and ridge regression models are used to fit the data,and Gaussian functions are used to fit the data.The best fitting method is selected based on the calculated residual results to construct a curve of edema volume progression over time for all patients.Divide the patients into four subgroups based on age,and use the obtained best fit model to analyze the age differences in the progression pattern of edema volume over time.Finally,the change in edema volume was calculated based on known data,and a random forest and multi-layer perceptron model were used for training.The model was predicted using a test set,and the impact of different treatment methods on the progression pattern of edema volume was analyzed to determine the optimal treatment plan.

In this study,jasmine black tea leaves,whole milk powder and white sugar were used as the main raw materials,and commercially available lactic acid bacteria starter culture was used to optimize the fermentation process of jasmine black tea yogurt with sensory score as the index,and the optimal fermentation process conditions of jasmine black tea yogurt were obtained by designing response surface optimization test based on single-factor,Plackett-Burman test and steepest climb test.The physical and chemical indexes such as acidity and sugar content,microbial indexes such as lactic acid bacteria and volatile flavor substances were tested.The results showed that the optimal fermentation process for jasmine black tea yogurt was 4.1% jasmine black tea addition,14.3% milk powder addition,0.4% fermenting agent inoculation,6.2% sugar addition,9 h fermentation time and 42 ℃ fermentation temperature.Under these optimized conditions,the sensory score of the yogurt was 90 points;the acidity of jasmine black tea yogurt was 83 °T,the sugar content was 10.2%,and the lactic acid bacteria count was 2.2×10⁹ CFU/mL.28 volatile flavor substances were detected in jasmine black tea yogurt by gas chromatography tandem mass spectrometry,including three characteristic aroma substances of jasmine black tea,such as benzyl alcohol,linalool,and benzyl acetate.

The haze in reality is complex and changeable,and the data-driven image dehazing algorithm cannot establish a universal mapping model by learning the data distribution of all data sets,and only use clear images as positive samples to guide the training of the dehazing network,while the key information of negative samples(hazy images)is ignored.To solve these problems,this paper proposes an image dehazing algorithm based on the global meta attention and contrastive learning.Firstly,according to the distribution characteristics of haze in the image,a dehazing network based on multi-scale feature extraction and integration is designed.Secondly,the global meta attention module is constructed to provide the global attention optimization for the multi-scale dehazing network,and the mapping model of the network can be adaptively adjusted according to the input hazy images.Finally,self-supervised contrastive learning is introduced to draw the dehazing results closer to the positive samples and away from the negative samples.A large number of experimental results show that the algorithm achieves good dehazing performance in both synthetic haze map data sets and real haze map data sets,and is superior to the existing representative image dehazing methods in both subjective and objective evaluation.

Terpenoids,natural products formed from isopentenyl diphosphate (IPP)and dimethylallyl diphosphate (DMAPP)as precursors,are almost ubiquitous in all organisms,with medicinal plants being predominant.They find wide applications in pharmaceuticals,food,chemical,and energy industries.The extraction from plants and chemical synthesis are commonly employed methods to obtain terpenoids.However,both methods suffer from drawbacks such as low efficiency,unstable quality,and high costs.These limitations clearly cannot meet the increasing demand for terpenoids.With the rapid development of synthetic biology techniques,significant progress has been made in engineering microorganisms for the synthesis of terpenoids,particularly yeast cells.Yeast cells,owing to their similar structure to plant cells and mature genetic manipulation systems,have been utilized for the synthesis of various terpenoids,gradually showcasing the advantages of biosynthetic approaches.This article reviews the progress of metabolic engineering for efficient synthesis of important terpenoids using two model yeasts,Saccharomyces cerevisiae and Yarrowia lipolytica,as examples.Specifically,it summarizes various strategies for metabolic engineering,including the screening and expression of highly active terpenoid synthases,the supply and efficient utilization of key precursor acetyl-CoA,as well as strategies for enhancing the synthesis flux of direct precursors,IPP and DMAPP,while minimizing their consumption.Finally,the article concludes with a summary and outlook on the opportunities and challenges faced by yeast-based synthesis of terpenoids.

Using lignocellulose to produce fuel and chemicals is one of the effective ways to solve the current energy crisis.Although the pretreatment technology of lignocellulose has been widely studied,the high energy demand,high cost,and limitations of equipment corrosion resistance technology of traditional pretreatment technology have spurred the development of new pretreatment processes.The emergence of deep eutectic solvents (DES)effectively solves these problems and greatly improves the conversion efficiency of lignocellulose.At present,the application and research of binary deep eutectic solvents (BDES)is more extensive,the more efficient and targeted ternary deep eutectic solvents (TDES) are also gradually developing.In this study,TDES were systematically classified (including TDES containing alcohols and acids,TDES containing organic molecular compounds,TDES containing metal halides and TDES containing two different acids).The research progress of the above TDES in improving enzymatic hydrolysis performance after lignocellulose pretreatment was discussed;the combined pretreatment methods were reviewed.The potential application of DES in different research directions was prospected.

Magnetic coupling drive is a non-contact transmission technology that uses magnetic field interaction to achieve power transfer and has the advantages of soft starting,overload protection,vibration isolation and adaptability to harsh environments.This paper reviews the research status of magnetic seal drive system at home and abroad,and discusses its wide application in chemical industry,petroleum and other fields.In this paper,the torque,electromagnetic characteristics,eddy current,heat dissipation and application of magnetic coupler are discussed in detail,and it is pointed out that the magnetic seal transmission system with high torque,low eddy current,high efficiency and high temperature resistance will be the future development trend.

The interaction between cationic peptides and deoxyribonucleic acid(DNA)is of great significance to the basic research of biology and the pathogenesis of many diseases.The article employs optical microscopy to initially investigate the liquid-liquid phase separation(LLPS)of poly proline-arginine(Poly PR)in the presence of single-stranded salmon sperm DNA.It was found that an increase in peptide chain length and concentration promotes LLPS.Then,the effect of KCl concentration onthe LLPS of Poly PR-DNAsolution was observed,and it was found that the increase of KCl concentration inhibits LLPS.When the KCl concentration exceeds 800 mmol/L,the droplets disappear;at the same time,when the concentration of salt is constant,the increase of DNA concentration will promote the LLPS of the mixture.Secondly,the effect of KCl concentration of 100 mmol/L at the interaction between PolyPR and double-stranded salmon DNA in liquid phase separation(LLPS)was studied,and it was found that the longer double-stranded salmon DNA are more difficult to undergo LLPS compared with single-stranded salmon DNA.Finally,in order to quantitatively study the mechanism of DNA and Poly PR interaction,a single-molecule force microscopy(MT)was used to measure the change of criticality of Poly PR and DNA,and analyze its mechanism from the single-molecule level.The experimental results showed that the increase of Poly PR chain length and concentration also led to an increase in DNA cohesion;and the size of cohesion was measured after the addition of KCl solution,which showed that the cohesion decreased with the increase of salt concentration.The experimental results obtained by single molecule show good consistency with the findings obtained by optical microscopy,which led to the conclusion that longer polypeptide chains and higher concentrations can enhance the interaction between Poly PR and DNA and decrease the interaction between Poly PR and DNA due to salt ions.

A large number of membrane-free compartments within cells (collectively known as bio macromolecular condensates)are assembled through the phenomenon of liquid-liquid phase separation (LLPS).Phase-separated condensates participate in various biological activities,and abnormal phase separation may lead to a large number of complex human diseases,such as neurodegenerative diseases and cancer.Therefore,elucidating the mechanisms underlying the liquid-liquid phase separation of peptides and DNA may provide guidance for understanding and treating some severe human diseases.In this study,the regulation of LLPS was mainly explored related to a series of peptides (Poly KH)containing repeated lysine and histidine (KH)sequences.It was found that the KH-30 peptide produced LLPS with DNA through electrostatic interactions.At room temperature,the range of DNA-regulated phase separation was 6~14 μg/μL,and further increases in concentration led to the disappearance of the LLPS phenomenon.When PEG-1000 was added to a mixed solution of DNA and KH-30 peptides,its molecular crowding effect promoted the aggregation of small droplets into large droplets.As the concentration of PEG-1000 increased,the molecular crowding effect became more apparent,favoring the occurrence of the LLPS phenomenon.In addition,temperature is a convenient means to regulate LLPS in vitro.This study found that KH-30 exhibited entropy-driven LLPS behavior,meaning that an increase in temperature restrained the LLPS phenomenon between the KH-30 peptide and DNA.

Most simple four-dimensional chaotic systems produce chaotic attractors;only three different phase planes have significant chaotic attractor properties.The simple four-dimensional chaotic system constructed in this study can generate six two-dimensional attractor phase diagrams and has complex chaotic properties.The phase diagram,Lyapunov exponential spectrum,bifurcation diagram,0-1 test diagram and Poincare cross section diagram are used to verify the abundant dynamic characteristics of the system.Multisim is used to simulate the system,and the results show that the circuit simulation is in agreement with the numerical analysis,which proves the physical realization of the system.Finally,a robust synchronization control scheme is designed,which proves theoretically that the driving-response system can achieve synchronization.The synchronization controller is applied to chaotic masking secure communication,which proves that the method has good security and reliability.

 During the liquid-liquid phase separation (LLPS)process,salt ion concentration and crowding agents have significant impacts on protein interaction,folding,and aggregation.This study employed an optical inverted microscope,dynamic light scattering,and a Q5000 UV-Vis spectrophotometer to delve into the inductive effect of yttrium(Ⅲ)chloride (YCl3)on the phase behavior of bovine serum albumin (BSA),as well as the regulatory role of polyethylene glycol (PEG)on the phase separation of the BSA-YCl3 system.The research findings indicate that YCl3 effectively induces phase separation in BSA,forming an LLPS system between the lower critical salt concentration (C*)and the higher critical salt concentration (C**).The addition of PEG further enhances the LLPS phenomenon in this system.Additionally,dynamic light scattering experimental data reveal that YCl3 primarily interacts with BSA through electrostatic interactions,while spectrophotometer data suggest that PEG does not alter the LLPS range of the original system but rather promotes LLPS.