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.

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.

At present,multi-modal neuroimaging data is widely used in Alzheimer’s disease (AD) classification research.However,these research methods have certain limitations.Firstly,the original feature dimension is high,and it contains a large amount of redundant information,requiring a large amount of computational resources for processing and analysing.Secondly,it is difficult to obtain complete multi-modal data from the same patient,resulting in a small sample size,which is not conducive to training reliable classification models.To address these issues,this paper proposes an AD classification method based on maximum relevance-minimum redundancy (mRMR) and canonical correlation analysis (CCA).Specifically,the mRMR algorithm is first used to select discriminative features that are most relevant to the classification label from each modality data.Then,the CCA algorithm is used to explore the inherent connections among multi-modal data,and finally,classification is performed.This paper conducted experiments by using data from the Alzheimer’s Disease Neuroimaging Initiative database,and the results demonstrated the effectiveness of the proposed method in AD classification.

With the rapid development of modern intelligence and automation,mobile AGVs are beginning to play an important role.This paper is devoted to the study of trajectory tracking control method of McNamee wheel AGV (Automated Guided Vehicle),which adopts adaptive sliding mode control in order to improve the performance of its application in the field of automated logistics and manufacturing.Firstly,the McNamee wheel AGV is mathematically modelled to establish its kinematic and dynamic models while considering external disturbances.Secondly,an adaptive sliding mode trajectory tracking controller is designed on the basis of the dynamics model,which realizes the control of the system state by introducing the sliding mode surface,and then the stability of the control method is analyzed by using Lyapunov theory.Finally,the controller is verified through matlab simulation experiments to improve the trajectory accuracy as well as the effectiveness of the AGV.

In this paper,we study the test problem of a class of variable coefficient models with panel data interaction effects.Based on the empirical likelihood method,the empirical likelihood ratio test statistic of the coefficient function is constructed.Under some regular conditions,the asymptotic theory of the statistic is established,and its asymptotic distribution is analyzed theoretically,including their consistency,convergence speed and asymptotic distribution.Based on this,the rejection region at a certain confidence level is constructed.Based on the regularization test method, the test statistics are obtained by optimizing the empirical likelihood ratio function of the constraints. The whole process is robust and efficient. The asymptotic theory of the empirical likelihood test of the interactive fixed effect variable coefficient model is studied, which provides some theoretical support and method guarantee for the statistical modeling of panel data.

Aiming at the problem of online measurement of flotation concentrate grade that needs to be solved urgently in the process of beneficiation production,a non-negative garrote (NNG) algorithm is embedded in an online sequential extreme learning machine (OS-ELM) and a new method is proposed based on online soft sensing algorithm for concentrate grade selected by OS-ELM and its input variables.First,the trained OS-ELM network model is obtained through parameter optimization and its excellent online learning ability is used to recursively update the network output weights by adding new samples or sample blocks in the incremental learning process;the input weights of the OS-ELM network model are sparsely optimized,redundant variables are eliminated and the prediction accuracy of the model is improved;finally,the online model is applied to the soft sensing modeling of copper concentrate grade in the flotation process of a copper mine in a mining enterprise and is combined with other advanced algorithms and comparison of the measurement results of the on-site current-carrying X-ray fluorescence grade analyzer.The experimental results show that the proposed algorithm can effectively eliminate redundant variables,improve the accuracy of concentrate grade measurement and realize real-time accurate soft measurement of flotation concentrate grade.

“Polyphenols” is a class of bioactive natural substances that widely exist in plants.Sugarcane contains a large number of polyphenols with high antioxidant activity,which play an important role in controlling blood glucose levels and regulating immunity.By optimizing the ratio of water and ethanol and realizing sugarcane polyphenols without organic residues with ultrasound-assisted extraction,the sugarcane polyphenols extraction process was optimized through one-factor experimental method and response surface design.The test results show that the best extraction process of sugarcane polyphenols is ethanol concentration 58%,liquid ratio 11∶1（mL·g^-1）,water bath temperature 49 ℃,ultrasonic power 103 W,ultrasonic time 35 min,the yield of sugarcane polyphenols 18.87 mg·g-1,and the predicted value is 19.10 mg·g^-1.The prediction accuracy of this model is 98.8%.

A robust soft sensor algorithm based on gate recurrent unit (GRU)is proposed to address the issues of multi-variability,nonlinearity,time delay,and measurement outliers in modern process industrial process variables.Firstly,an initial model of GRU is trained by historical data.Secondly,an improved least absolute Lp penalized solution (ILAPPS)algorithm is proposed,which incorporates median absolute deviation into the capped mean absolute error loss,making it more resistant to outliers;and embeds an adaptive operator based on permutation importance ranking design of random forest into Lp-regularization term to improve the accuracy of input variable selection.In addition,ILAPPS is embedded in the GRU input and recurrent layers to achieve sparse optimization of the network.Finally,the proposed algorithm is applied to artificial datasets and actual industrial copper ore flotation processes,and its performance is compared with other advanced algorithms.The experimental results show that the proposed algorithm has higher prediction accuracy and robustness.

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.

Information entropy is commonly used to measure the uncertainty of random variables and plays a significant role in various fields such as physics,statistics,and information theory,aiding in our understanding and explanation of diverse phenomena.Unlike the entropy in thermodynamics,information entropy exhibits a certain degree of orderliness,which stands in stark contrast to the disorder and complexity represented by entropy.Using a binary statistical model as an example,this article explores the connection between information entropy and random events,quantitatively describes the evolution process of information entropy,and reveals the fundamental principles underlying the orderliness of information entropy.

CoCrNi medium entropy alloy was produced by laser melting deposition process,and the influence of laser power on microstructure and properties was studied.The findings show that when the power is 800~1 600 W,the metallurgical bonding between the deposition layer and the substrate is good,and the fusion line is clearly visible.The structure along the building direction of the deposition layer is planar crystal,columnar crystal and equiaxed crystal.With the increase of power,the breadth of the deposition layer increases,the microstructure coarsens,and the microhardness gradually decreases.The laser power is P=800 W,the performance is optimal,and the microhardness of the fusion zone,middle and top of the deposited layer is 393,435 and 496 HV.

How to shorten the patient's clinic time and improve the service efficiency and quality has become an important problem to be solved in the emergency department.Based on Flexsim software modeling,this study simulates and optimizes the emergency department treatment process.First,the input data required by the simulation model is processed by the Kolmogorov-Smirnov goodness-of-fit test together with other statistics methods.Second,through Flexsim software modeling and simulation,the resource bottleneck of emergency department treatment process is found out.Third,an optimization and improvement scheme is proposed to eliminate the resource bottleneck.And based on the Flexsim simulation model,the rationality of the optimized scheme is verified.Through optimization and improvement,the resource bottleneck of the emergency department system was eliminated,the patient crowding was effectively reduced,the patient's clinic time was shortened,and the treatment efficiency and patient satisfaction were improved.

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.

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.

There is a natural demand for integration between the cultural industry and the tourism industry;however,digital technology has become a driving force for the high-quality development of the cultural tourism industry.Based on the industrial characteristics of cultural industry and tourism industry and the interaction mechanism between them,index system of cultural and tourism industry was constructed from four dimensions:industrial scale,industrial reception,industrial strength and industrial efficiency in this paper.The coupling coordination model was introduced to measure the development level and coupling coordination degree of the two major industries in Shandong Province from 2010 to 2020,and the time series changes were analyzed.The results of the study showed that in addition to the impact of the epidemic in 2020,the overall development level of cultural industry and tourism industry in Shandong Province has been improving year by year,however,the development of the cultural industry generally lagged behind the development of the tourism industry;the coupling coordination degree showed a steady upward trend,increased from 0.390 8 to 0.900 6,coordination level was upgraded from mild dysregulation to excellent coordination.Based on this,from the aspects of cultivating cultural tourism industry to enhance the new momentum of integrated development of cultural tourism,building digital cultural tourism platform to improve the value co-creation mechanism,expanding the transmission channels of technology and product innovation,and training new digital cultural tourism talents,a path was put forward to promote the digital economy to empower the high-quality development of cultural tourism integration.

In order to solve the problem of low feedback accuracy of channel state information feedback method in frequency-division duplex massive multi-input multi-output system,a CSI feedback network named CDTransformer based on Transformer and convolutional decomposition (CD)is proposed.CDTransformer incorporates convolutional decomposition into an improved Transformer network architecture to improve network performance without adding computational complexity,and enables lightweight deployment by binarizing the full connectivity layer of the network.A MixedTransformer network model is proposed for the limited power of the client.The encoder adopts a single layer convolutional neural network with low computational cost and simple structure,while the decoder adopts the same structure as the CDTransformer model.The CDTransformer model incorporates the Transformer structure and convolutional decomposition to improve CSI feedback accuracy and enable lightweight deployment.In addition,the MixedTransformer model was introduced,combining the advantages of CDTransformer and convolutional neural networks to provide better performance in power limited situations.The results show that compared with the CsiTransformer network model,the normalized mean square error and cosine similarity of CDTransformer network model are improved by 37.7% and 0.2%,respectively.

Blue is one of the three primary colors and is now widely used in many fields such as food,medicine and cosmetics.Most of the blue pigments currently used in food processing are synthetic blue pigments,and natural blue pigments are extremely rare in commercial applications.The study first found that Quambalaria cyanescens QY229 can metabolize to produce extracellular watersoluble blue pigment under liquid shake flask culture conditions,and the response surface optimization of its fermentation conditions was carried out.The results showed that when the peptone content was 34.61 g/L,the temperature was 31.67 ℃,and the bottling volume was 72.33 mL/250 mL,the color value of blue fermentation liquid could reach 348.2 U/mL,which was 2.1 times of that before optimization..Therefore,the production of blue pigment by liquid fermentation of Quambalaria cyanescens,QY229 as another new source of rare natural blue pigment,has a broad application prospect.

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).

Magnetic coal gasification slag (MCGS) was prepared by acid leaching and chemical coprecipitation process,and further characterized by scanning electron microscopy (SEM),Fourier transform infrared spectroscopy (FTIR) and X-ray diffraction (XRD).The results showed that the coal gasification slag had a rough and porous structure,and the surface and pores were loaded with Fe₃O₄ particles with reverse spinel structure,which indicated that the magnetic coal gasification slag had been successfully prepared.Then,RhB was taken as the target pollutant to study its adsorption performance.The removal efficiency and adsorption capacity of RhB were 90.66% and 90.66 mg/g under the optimal conditions of pH 3.0,the adsorption time 200 min,the initial concentration of RhB 200 mg/L,and the dosage of magnetic coal gasification slag 2.0 g/L.Moreover,the adsorption isotherm and adsorption kinetics results demonstrated that the adsorption process of RhB by MCGS was in agreement with pseudo second-order kinetic and Langmuir isotherm,indicating that the process was a single molecular layer adsorption dominated by chemisorption.The research provides a new technique and method for the resource utilization of coal gasification slag.

Based on the environmental data before and after the establishment of Saihanba Forest Farm,the environmental evaluation index was given and the comprehensive evaluation model of TOPSIS environmental status based on entropy weight method was established.The outstanding contribution of the construction of the ecological protection zone of Saihanba Forest Farm to the improvement of the local and surrounding environment was studied,and the quantitative evaluation model was used to analyze its role in Beijings resistance to dust storms.Then,in order to explain more accurately the importance of the construction of Saihanba Forest Farm,a TOPSIS comprehensive evaluation model of environmental conditions based on analytic hierarchy process was established.The simulation results show that the conclusions of the two models are consistent.In order to study the ecological situation in China,the environmental data of thirtyone provinces were collected,and the environmental index evaluation system was established by principal component analysis.The environmental conditions of each province were scored,and the threshold was set through the environmental conditions of typical areas.The provinces with scores below the threshold need to establish ecological protection areas.Finally,in order to put forward a more reasonable construction plan for provinces that need to establish ecological protection zones,the economic level and land area of the province should be considered,and the construction area of each ecological protection zone and its impact on national carbon neutrality are given by quantitative comparison.

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.

This paper establishes a half-vehicle 7 degree-of-freedom rigid-flexible coupling dynamic model and simplifies using the Euler-Bernoulli beam model.Given the limitations associated with the traditional PSO algorithm,which include susceptibility to being stuck in local optima and so on.Three methods,namely chaotic initialization,dynamic inertia weight,and adaptive learning factor,are introduced to optimize the algorithm.Accordingly,a refined variant of the PSO algorithm,namely the Adaptive Inertia Weight PSO,has been introduced.Ultimately,by using MATLAB simulation modeling,the outcomes of three scenarios are meticulously compared:the absence of optimization,optimization via the conventional PSO algorithm,and optimization through the enhanced PSO algorithm.These scenarios are evaluated based on four distinct performance aspects.The findings clearly indicate that the refined PSO algorithm surpasses the other two approaches in all metrics,thereby confirming the effectiveness of the proposed algorithm in greatly enhancing the fluidity of vehicle movement and driving stability.

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.

Microalgae,the third generation biomass raw material,has been used to produce biodiesel for its advantages of high production capacity and high lipids content.In order to increase the production and separation efficiency of microalgae,foam flotation can be applied in the harvest of microalgae.Protein as a natural nitrogen source and a bio-surfactant can play a role of a bridge in coupling the cultivation process with the separation process.The application of the recovered whey soy protein from the soy whey wastewater is cost-effective to the production of Chlorella.The addition of whey soy protein was beneficial to the growth of Chlorella in BBM.In foam flotation,a high enrichment ration 18.7 and a high recovery percentage 96.4% of Chlorella were obtained by adding the optimal whey soy protein concentration of 0.163 g/L at pH 7.0.

 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.

Bi₂Se₃ and Bi₂Te₃,which are topological insulators,show excellent thermoelectric properties.As a new class of topological Weyl semimetals,whether TaAs possesses excellent thermoelectric properties has attracted much attention.In this work,the effect of electron-phonon coupling on the electronic transport properties of TaAs was studied using first-principles calculations and Boltzmann transport theory.Compared with previous studies,when the electron-phonon coupling effect is considered,the maximum ZT value in TaAs at 900 K is found to be much lower with the value of merely 0.078.The results contribute to further understanding of the transport properties of Weyl semimetallic TaAs.

Fungi can form mycelial pellets with hollow inside and dense surface under submerged cultivation.These mycelial pellets have advantages of good flocculation performance,uneasily settling at the reaction tank bottom,broad growth conditions,and easy cultivation.Researchers have widely studied on the formation mechanism and cultivation conditions of mycelial pellets.Recently,the focus of researchers has gradually shifted to their application.At present,mycelial pellets have been applied in the fields of wastewater treatment and recovery of resource and energy.This review mainly introduces the self-assembly mechanism and the influencing factors of nutrient and culture conditions on the formation fungal mycelial pellets under submerged cultivation.Also,the study of fungal mycelial pellets carrying nanoparticles,microorganisms,biochar to treat wastewater and the potential and challenges for these types of complexes were summarized.Furthermore,the cases of fungal mycelial pellets treating various kinds of sewage and the running characteristics and application of the matching reactors were introduced.The application of fungal mycelial pellets should focus on the diversified and collaborative development,coupling their own advantages with heterologous substances to play a synergistic role and to promote the improvement in wastewater treatment and environmental remediation.This review can provide guidance and reference for the application of fungal mycelial pellets in wastewater treatment.

With the continuous development of big data, the personalized recommendation of users is widely used. The existing recommendation algorithms ignore the community structure composed of various social relations between users. Relationships can be used well in recommendation systems. Based on the multi-subnet complex network model, this paper proposes a community partitioning probability matrix recommendation algorithm based on multiple social relationships by using the community structure characteristics composed of multiple social relationships. By comparing with the existing recommendation algorithms on the real data set Epinions, the accuracy evaluation indicators δ_MAE and δ_RMSE have been improved by 30% and 20% respectively. It can be proved that the community division probability matrix recommendation algorithm based on multiple social relations can effectively improve the recommended accuracy.

The adaptive filter algorithm is the core of active control systems (ACS).To further improve the performance of the normalized variable step size filter-x least mean square (NVSS-FxLMS)algorithm,the signal interpolation concept is introduced in this research,and the algorithm combining the signal interpolation with normalized variable step size concept (INVSS-FxLMS algorithm)is proposed to improve the control performance and convergence rate of the NVSS-FxLMS algorithm,then the effect of the number of signal interpolation on the performance of the algorithm is explored.The results show that the signal interpolation can improve the control performance and convergence rate of the NVSS-FxLMS algorithm.Besides,the optimal range of the number of signal interpolation exists.When the number is about 10,the control performance and convergence rate of the algorithm is relatively better,and the total sound pressure level or acceleration level in the frequency domain is reduced by about 18%,while the computational time increases by 9.6%.The research provides a new idea for the improvement of the NVSS-FxLMS algorithm,and lays the foundation for the development of the ACS.

To study the water migration law of cucumber slices during hot-air drying,this paper takes cucumber slices as the research object and explores the influences of different temperatures and slice thicknesses on the water ratio and drying rate of cucumber slices.Firstly,a mathematical model for describing the water migration law of cucumber slices during hot-air drying is established,and numerical simulation analysis is carried out based on the numerical simulation software COMSOL.The results show that the Page model is more suitable for describing the water change law of cucumber slices during hot-air drying.Under the experimental conditions set,the coefficient of determination R² of the Page model reaches 0.99,and the corresponding residual sum of squares RSS and chi-square χ² are less than 0.017 16 and 0.000 953 351,respectively.Meanwhile,the experimental data is fitted,and the effective diffusion coefficient of cucumber slices in the temperature range of 50～80 ℃ is calculated to be between 0.173 5×10^-9~4.189×10^-9.The higher the hot-air temperature and the greater the thickness,the larger the effective diffusion coefficient.The numerical simulation process visually describes the water migration process of cucumber slices.The water concentration of cucumber slices gradually decreases from the edge to the interior.The water concentration at the edge position decreases rapidly,while the water concentration at the core position decreases slowly.By comparing and analyzing the change processes of dry basis moisture content in the numerical simulation and experimental processes,it is found that their change trends are the same,but the dry basis moisture content decreases faster in the experimental process.This model can provide a reference for the simulation study of other materials in hot-air drying technology.

During the plastic stress wave velocity stage of the workpiece material,brittle cutting of the workpiece can avoid problems such as difficult chip breaking,strain hardening,and tool sticking caused by the high soft viscosity of the material.In this paper,carbide tools,ceramic tools and cubic boron nitride (PCBN)tools are used to cut pure iron at high speed (linear speed up to 8 000 m/min),and the wear,cutting force and machined surface quality of the tools after cutting are observed.The results show that among the three kinds of tools,the carbide tools wear is the most serious,followed by the PCBN tools wear,ceramic tool wear is the least.Severe abrasive wear occurs on the flank face of carbide tool,and the rake face of PCBN tool shows crescent depression wear,which is full of high temperature melts and brittle fracture fragments.Ceramic tools have no obvious wear characteristics,but there is a lot of workpiece material adhesion on the rake face and flank faces.Compared with carbide and PCBN tools,ceramic tool machining workpiece machining surface has less defects,minimal lateral flow,minimum roughness and hardening layer,the ceramic tool is an ideal tool material for high-speed cutting of pure iron.

Accurate power load forecasting is the basis to ensure the stable operation of the power grid,and is also an important basis for power planning.In order to improve the accuracy of power load forecasting,a new forecasting model is proposed in this paper.First,the Harris Hawk algorithm is optimized by using chaos strategy and sine and cosine perturbation strategy,and then the weight and threshold of the limit learning machine are optimized by using the improved Harris Hawk algorithm.Finally,the model is used for short-term power load forecasting.Compared with other prediction models,the prediction effect of this model is greatly improved,and it has better generalization ability and stability.

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.

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.

The transcription factor Ask10p of Saccharomyces cerevisiae,also known as Rgc2p,not only plays an important role in cell wall biosynthesis,but also participates in the regulation of oxidative stress as a component of the RNA polymerase II holoenzyme,and also participates in the regulation of osmotic balance as a positive regulator of the aquaglyceroporin Fps1p. In recent years,with the deepening of research,Ask10p has been confirmed to play an important regulatory role in oxidative stress,osmotic stress,acetate and toxic metal ion stress,and xylose metabolism. In this review,the biological functions and current research advances of Ask10p in Saccharomyces cerevisiae were presented,and the research directions were also prospected in order to provide reference for future research directions.

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 corrosion resistance of EH40 steel in simulated seawater solution is studied through immersion and electrochemical methods in this paper.The soaking test results show that within 1 400 hours,as the corrosion time progresses,the number of corrosion pores on the surface of the sample continues to increase.At 360 hours,the number of corrosion pores is the highest,and after 840 hours,corrosion products gradually form on the surface,resulting in an insignificant increase in the number of corrosion pores.The electrochemical test results show that as the soaking time increases,the corrosion resistance first weakens and then enhances,and the corrosion resistance is the worst at 360 hours.The research on the corrosion behavior of EH40 steel in simulated seawater solution has important engineering practice and theoretical research value，which is helpful to promote the development and application of marine engineering materials.

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.

This study established an efficient,accurate,and sensitive detection method for sodium azide based on liquid chromatography.This study innovatively used a chromatography column system consisting of octadecylsilane bonded silica gel column and ion exchange chromatography column connected in series through a six way valve,combined with a dual pump infusion system of gradient pump and constant flow pump,to achieve efficient separation and accurate detection of sodium azide.In addition,this study also optimized key parameters such as detection wavelength,column temperature,and valve switching time,further improving the sensitivity and accuracy of the method.The results showed that this method had a good linear relationship (R=0.999 9) in the range of 0.397 8~1.989 μg/mL under the conditions of detection wavelength of 210 nm,column temperature of 60 ℃,and valve switching time of 4 minutes and 6 minutes.The recovery rate was 81.2%～96.6%,δ_RSD≤2.8%,and the detection limit of the method was 0.039 78 μg/mL.This method has the advantages of strong specificity,high sensitivity and accuracy,good repeatability,and low detection cost,providing a reliable technical means for the detection of sodium azide in moxifloxacin sodium.

Industrial pollution is an important factor affecting ecological protection and high-quality development in the Yellow River Basin.To assess the impact of environmental regulation on promoting green industrial development,56 prefecture-level cities in the basin were selected for study.Using panel data from 2011-2020,the Super-SBM model was employed to measure green industrial development.System GMM and threshold models were applied to explore the relationship between environmental regulation and industrial green development.The results indicate:Environmental regulation has an inverted U-shaped effect on green industrial development.Green finance positively moderates this relationship;the higher the green finance level,the stronger the impact of environmental regulation.The nonlinear effect of environmental regulation shows spatial heterogeneity.