Abstract:Cholesteryl ester transfer protein(CETP)plays a critical regulatory role in the pathogenesis of hyperlipidemia.It facilitates the transfer of cholesteryl esters from high-density lipoprotein(HDL)to very-low-density lipoprotein(VLDL)and low-density lipoprotein(LDL),thereby reducing cardioprotective HDL cholesterol levels and elevating pro-atherogenic LDL cholesterol levels,which ultimately promotes the development of hyperlipidemia.To enable prokaryotic expression,the coding sequence(CDS)of CETP was retrieved from the GenBank database.Following bioinformatic analysis and codon optimization,a pCold-CETP prokaryotic expression vector was constructed,and the target protein was purified via nickel-affinity chromatography.Bioinformatic analysis revealed that the CETP gene CDS encodes a 493-amino acid protein with a predicted molecular weight of approximately 54 ku.The protein was predicted to be stable(instability index:32.68)and hydrophilic.After codon optimization,the average guanine and cytosine(GC)content of the CETP gene was reduced from 54.7%to 51.3%,and unfavorable secondary structures were eliminated,significantly enhancing its expression efficiency in Escherichia coli.Under induction conditions of 37℃and 10 mmol/L isopropyl β-D-1-thiogalactopyranoside(IPTG)overnight,the CETP protein was predominantly expressed in inclusion bodies.The purified protein showed a distinct band on SDS-PAGE,with a final concentration of 13.48 mg/mL.In conclusion,this study successfully achieved high-yield expression of the CETP protein in a prokaryotic system.The significant improvement in protein production,accomplished through codon optimization and induction condition refinement,provides a solid foundation for future functional studies of CETP and the development of its inhibitors.

Abstract:No-reference image quality assessment(NRIQA)has always been an important research direction in the fields of image processing and computer vision,with the goal of estimating image quality through objective assessment.In recent years,no-reference image quality assessment methods based on convolutional neural network(CNN)and Transformers have received extensive attention.However,due to the complex structure of the Transformer,most existing algorithms have the problem of high computational complexity.To this end,this paper proposes a multi-level convolutional neural network based on Transformer(TBMCNN),which only extracts features from the horizontal and vertical axis of the Transformer,significantly improving the network performance.The multi-level convolutional neural network based on Transformer consists of four core modules:the shallow feature extraction module(SFEM),the parameter sharing module(PSM),the multi-level Transformer feature extraction module(MTFEM),and the fully connected network module(FCNM).Among them,the multi-level Transformer feature extraction module is designed with parallel branches,which are respectively used for adaptive multi-scale convolution and axis attention Transformer.This not only enables more effective extraction and fusion of features but also significantly enhances the computing speed of the network.The experimental results show that the multi-level convolutional neural network based on Transformer has better performance and generalization ability without consuming excessive resources.

Abstract:Aiming at the problems of missed detection and false detection caused by the uneven distribution of small targets and indistinct feature information,a lightweight UAV small target detection algorithm named BEW-YOLO is proposed.The original loss function is replaced with the GWD(Gaussian Wasserstein Distance)Loss function based on Gaussian Wasserstein distance to optimize the problem of discontinuous target boundaries.A 160×160 detection head for small target detection is embedded to enhance the ability of detecting small targets.The efficient channel attention(ECA)module and dynamic sparse attention mechanism(BiFormer)are introduced to strengthen the model's ability to extract feature information of targets and improve detection accuracy.Experimental results on the VisDrone2019 dataset show that compared with the baseline algorithm YOLOv8n,the mAP@0.5 and mAP@0.5:0.9 are increased by 6.9%and 4.3%respectively,while the Precision and Recall are simultaneously improved by 5.8%and 7.3%.Generalization experiments are conducted on the RSOD and NWPU VHR-10 datasets,and the mAP@0.5(%)is increased by 2.1%and 3.5%respectively.Moreover,the total number of parameters of the model is only 3.2M,which indicates that the proposed BEW-YOLO algorithm can effectively accomplish the task of small object detection.

Abstract:There exists a dual relationship between the one-dimensional steady-state equations in quantum mechanics,which can be extended to any system where two potentials are located.The problem of solving the one-dimensional steady-state Schrödinger equation using the extended dual relationship can be transformed into a problem of finding the dual transformation between the equation to be solved and the equation with a known solution.This provides a new method for solving the one-dimensional steady-state Schrödinger equation.Starting from a one-dimensional harmonic oscillator system with known solutions,a solution to the one-dimensional steady-state Schrödinger equation under an unsolved periodic potential can be obtained using the dual relationship.And it can provide the conditions that the coefficient satisfies when the energy eigenvalue belongs to the bandgap or conduction band.

Abstract:The performance degradation of silicon anodes caused by volume expansion during lithium storage is closely associated with the limited mechanical strength and conductivity of conventional binders and conductive additives.To address this challenge,we employ aramid-modified Ti3C2Tx MXene as a novel multifunctional binder for silicon-based anodes.This novel binder,combining high electrical conductivity with excellent mechanical strength,effectively mitigates stress during lithiation/delithiation,prevents large-scale electrode cracking,and thereby significantly enhances the cycling stability(maintaining 1 127 mA•h/g after 100 cycles at 0.2 A/g)and rate capability(maintaining 927.8 mA•h/g at 2 A/g)of the silicon anode.This design strategy for an aramid-modified Ti3C2Tx MXene binder offers a novel approach to enhancing the performance of lithium-ion batteries and other energy storage materials.

Abstract:The current research status of electromagnetic vibration and noise suppression methods of automotive permanent magnet synchronous machine at home and abroad is reviewed,focusing on three aspects of reducing motor vibration and noise,namely,the amplitude of motor electromagnetic force,the structural modulus and intrinsic frequency of the stator system,and the introduction of carrier vibration and noise in the inverter.Reliable methods for reducing motor vibration and noise are reviewed,followed by examples of acoustic and psychoacoustic factors for evaluating motor vibration noise,and future development trends are summarized to provide references for subsequent research on vibration noise suppression of automotive permanent magnet synchronous motors.

Abstract:In the traditional soybean processing,the problems of soybean residue,wastewater discharge and whey reuse have been troubling the development of soybean products industry.The whole soybean processing can achieve zero emission of soybean residue and whey,but the whole soybean products still have the problems of decreased gel strength,poor elasticity,loose structure and fragility due to the rich fibre content.Therefore,using ultra-micron crushed soybean powder as raw material,dynamic high-pressure micro-jet technology for pretreatment of soybean powder emulsion,GDL,CaCl2 and MgCl2 as coagulants,soybean powder emulsion gels were prepared,and the effects of different homogenising pressures and number of homogenisations on the gel properties,moisture distribution and rheological properties of soybean powder were investigated.The results showed that the particle size of soybean powder emulsion was the smallest when the homogenising pressure was 150 MPa and the number of homogenising times was 6 times.The gel strength,water holding capacity,equilibrium water content,energy storage modulus,elasticity and deformation resistance of soybean whole powder emulsion gel were the best when the homogenising pressure was 120 MPa and the number of homogenising was 4 times.

Abstract:Multi-particle cluster states,which have received much attention recently for their maximum connectivity,persistent entanglement and robustness to decoherence.How to prepare multi-particle cluster states has become one of the hot issues in the field of quantum information.This work introduces superadiabatic shortcut scheme for quantum phase gates and prepare 4-particle cluster states.The traditional adiabatic channel scheme requires two steps,and may be ineffective due to the long evolution time of the system.The scheme in this work takes only one step,which greatly reduces the difficulty of experimental realization and various losses in the experimental process.Numerical simulations show that the superadiabatic shortcut scheme is robust to the decoherence effects caused by spontaneous atomic emission and cavity decay in the cavity system,and takes less time than the traditional adiabatic channel scheme.

Abstract:Halide orthorhombic perovskite CsPbX3(X=Cl,Br,I)has received much attention for its excellent photoelectric properties.In order to investigate its electrical transport properties,the longitudinal acoustic phonon(LAP)and polar optical phonon(POP)models are used to predict its carrier mobility.The results obtained by POP model are lower than those obtained by LAP model and in agreement with the experimental values,which indicates that POPs are the main scattering source.Moreover,the carrier mobility of orthorhombic CsPbX3 shows significant anisotropic behavior,in which CsPbI3 has the highest mobility in the z direction,reaching 125 cm2·V-1·s-1.It is found that the top of the valence band is mainly determined by the p orbital of the halogen atom and the bottom of the conduction band is mainly determined by the p orbital of the Pb atom.In addition,the phonon dispersion curve of CsPbX3 is calculated by first principles,and its kinetic stability is verified.

Abstract:This paper presents a composite pseudospectral method for solving a class of optimal control problems with piecewise smooth differential equations and inequality constraints.The system's operating interval to be optimized is divided into multiple sub-intervals with unequal spacing based on the non-smooth time points of the function.Within each sub-interval,segmented interpolation polynomials are constructed through transformed Legendre-Gauss-Radau nodes.The weak differential representation method is used to derive the corresponding derivative operation matrix.The Legendre-Gauss quadrature formula and the obtained derivative operation matrix are used to discretize the optimal control problem into a nonlinear programming problem,where the non-smooth points of the state function and control function are unknown parameters.The obtained discretized nonlinear programming problem can be solved using Matlab nonlinear solver.Due to the fact that the elements and structures in the derivative operation matrix establish connections between adjacent sub-interval systems states,this method can be used to handle optimal control problems for non-smooth ordinary differential equations.Numerical examples have verified the effectiveness of the proposed method.

Abstract:Excited-state proton transfer(ESPT),a fundamental photochemical reaction,plays a crucial role in numerous photochemical and photobiological processes.Its significant practical value in applications like fluorescent probes and organic light-emitting diodes(OLEDs)has attracted growing research attention in recent decades.The characteristic spectroscopic signature of ESPT is dual fluorescence in emission spectra,exhibiting distinct"normal"and"anomalous"bands corresponding to the excited-state reactant and product,respectively.Despite extensive studies through diverse experimental and theoretical methods,conventional quantum chemical approaches relying solely on vertical excitation energies for spectral simulation are demonstrated to be inadequate for elucidating complex photochemical reaction mechanisms.Consequently,methods simulating vibrationally resolved electronic spectra based on Franck-Condon factors are increasingly employed for investigating such mechanisms and the luminescence of novel materials.However,challenges in solution-phase Franck-Condon simulations have restricted the reporting of vibrationally resolved spectra in this context.To overcome this limitation,we recently introduced damped Franck-Condon factors within the mass-weighted Cartesian coordinate framework.This methodology models solute-solvent interactions and interprets solvent enhanced absorption and fluorescence.Implementing these solution-phase Franck-Condon simulations to ESPT reactions yields deeper mechanistic insights,enabling us to propose novel mechanistic perspectives on several ESPT reaction mechanisms from the viewpoint of electronic spectral simulation.

Abstract:In this study,the effects of gelatin(GE)and polyethylene glycol(PEG)on the characteristics of high inner phase lotion(HIPEs)prepared from soybean soluble polysaccharide(SSPS)/soybean protein isolate(SPI)hybrid particles(SSHPs)were investigated.The results show that the average particle size,microstructure and rheological properties of HIPEs with GE and PEG additions are significantly different.The average particle size and microscopic results showed that the droplets of HIPEs with GE were smaller and more uniformly distributed,which was further confirmed by SEM images.In addition,rheological measurements showed shear-thinning behavior and good viscoelasticity,and the elastic modulus(>500 Pa)of the sample was always greater than the viscous modulus(<500 Pa).In addition,the endogenous fluorescence spectrum shows that GE-SSHPS have a lower absorption intensity and a blue shift compared with PEG-SSHPS,indicating that GE binds more strongly to SSHPS.The above results confirm that the addition of GE renders SSHPS stabilized HIPEs more homogeneous and more favorable for strengthening robust glycoprotein stabilized HIPEs than PEG.This provides a certain theoretical basis for the preparation of more robust raw HIPEs.

Abstract:This paper studies the numerical solution of a class of weakly degenerate parabolic equations with Neumann boundary conditions.To address the singularity problem caused by degenerate boundaries,a novel Galerkin method with self-defined basis functions adapted to the degenerate characteristics is innovatively constructed.By introducing the first term of the basis functions,the computational accuracy of the numerical solution at the degenerate boundary is significantly enhanced.Numerical experiments show that compared with the finite difference method based on the conservation principle(with a maximum error of 1.998 8)and the traditional polynomial basis Galerkin method(with a maximum error of 0.205 01),this method reduces the maximum absolute error to the order with only 4 basis functions,and also greatly reduces the computational time.It is significantly superior to the comparison methods in both accuracy and efficiency,providing an efficient and high-precision tool for solving complex degenerate equations.

Abstract:With the acceleration of the global green and low-carbon transformation,the new energy vehicle industry is developing at an unprecedented pace,and the development and substitutability of electric vehicles and fuel vehicles have become the focus of public attention.This study is based on Weibo data mining,and through the crawling and analysis of relevant Weibo posts and comments under the hot topic"Can Electric Cars Replace Fuel Cars",it aims to thoroughly discuss the future development trend of whether electric cars can replace fuel cars.By using LDA sentiment topic analysis,it was determined that the best three topic factors are environmental impact,economic factors,and technical factors.Social network analysis was conducted to identify the most influential Weibo users,namely Auto Home,Xiaoyang brother-Dongchedi,etc.,who usually play a core role in the network and have a significant impact on the dissemination of information,the flow of resources,or the influence of group behavior.The results of the study not only provide a scientific basis for the government to formulate new energy automobile policies but also help enterprises to grasp the market pulse,adjust product strategies and marketing strategies,and further promote the prosperous development of the electric car market.

Abstract:Accurate and efficient assessment of strawberry ripeness is crucial for improving fruit quality and standardizing harvesting in modern agriculture.However,traditional manual inspection methods suffer from strong subjectivity and low efficiency.This study proposes an enhanced lightweight object detection model based on YOLOv11n,specifically designed for real-time strawberry ripeness classification in complex greenhouse environments.The model integrates the LightGhostConv module,LightCA attention mechanism,and an optimized C2f module to improve small object feature extraction,reduce computational complexity,and enhance robustness to occlusion and illumination changes.A custom dataset containing different ripeness grades of"Benihoppe"strawberries was collected in Jinzhou,China,under various lighting and occlusion conditions.Experimental results show that the improved model achieves an average precision of 92.6%,with an inference speed of 49 FPS and only 2.24 M parameters,outperforming the original YOLOv11n and other mainstream models such as YOLOv5n,YOLOv8n,and YOLOv10n.Based on this model,a web-based detection system was further developed,which supports image upload,classification,and visualization operations,providing practical support for intelligent harvesting applications.This work offers a feasible solution for lightweight deployment on mobile terminals and has broad application prospects in the fields of smart agriculture and precise fruit harvesting.

Abstract:Echo state network(ESN)represent a relatively novel class of recurrent neural networks that have demonstrated significant potential in chaotic time series prediction.However,the random generation of ESN'connectivity and weight structures may lead to suboptimal reservoir performance during task execution.Additionally,the input weight matrix may exhibit substantial fluctuations during random initialization.To address these limitations,we have developed a novel architecture termed sine-circle echo state network(SCESN),which features a deterministic reservoir structure and an input weight matrix with autocorrelation properties.The SCESN employs a sinusoidal distribution for the input weight matrix to ensure both sparse connectivity of the reservoir and autocorrelation of input weights.Furthermore,the reservoir structure is designed based on the Newman-Watts small-world network topology.Comparative experiments across multiple datasets demonstrate that the SCESN outperforms traditional ESN in prediction accuracy while maintaining lower network complexity.

Abstract:Echo state networks are widely used in chaotic time series prediction due to their superior performance.However,in practice,the complex topology and random reservoir of echo state networks are difficult to implement.An echo state network model based on sulfur hexafluoride octahedral topology is proposed to address this issue.The model has the following characteristics:the fixed connection between neurons in the reservoir improves the internal stability of the reservoir while reducing the randomness and blindness between neurons,and increases the efficiency of information transmission.Simulation tests were conducted using sunspot time series for prediction,and validated with Indian stock data.The experimental results showed that the improved model has higher prediction accuracy.

Abstract:In high-energy heavy-ion collisions at HIRFL-CSR energies,the quark-gluon plasma may be generated.By utilizing K mesons as probes,early-stage evolution information of the particle emission source can be inferred.We model the expansion dynamics of the particle emission source at HIRFL-CSR energies using(2+1)-dimensional hydrodynamic equations derived from conservation laws.To generalize the framework,the original three conservation equations are reformulated into five equations through the introduction of the metric tensor and Christoffel symbols.These equations are numerically solved via the operator-splitting method.For the evolution of the source,three scenarios are investigated:the chemical freeze-out,partial chemical equilibrium,and thermal freeze-out models.Each model is tested with distinct initial configurations of transverse and longitudinal radii,including cases where the transverse radius equals,exceeds,or is smaller than the longitudinal radius.We analyze the energy density profiles and transverse/longitudinal velocity distributions across all models.Our results demonstrate that when the initial transverse radius is larger than the longitudinal radius,the central density of the source undergoes the most rapid evolution.

Abstract:In this study,a porous metal-organic framework {(CH3)2H2N+[Zn(btc)]·(H2O)(DMA)}n(Zn-MOFs)was synthesized via a solvothermal method using zinc nitrate and 1,3,5-benzenetricarboxylic acid(H3btc)as precursors.Subsequently,the as-synthesized Zn-MOFs were immersed in a 0.01 mol/L silver nitrate solution,magnetically stirred for 6 hours to achieve homogeneous impregnation,and then allowed to stand for phase separation.The resulting product was centrifuged,thoroughly washed,and dried under vacuum to obtain the Ag-loaded Zn-MOFs material.The synthesized materials were systematically characterized by XRD,SEM,TEM,and EDS to investigate their compositional,structural,and morphological properties.These analyses revealed a well-defined rod-like morphology with longitudinal dimensions exceeding 10 μm.The photocatalytic degradation performance of Ag-loaded Zn-MOFs toward Methyl Orange,Methylene Blue,and Congo Red was systematically investigated.A comparative analysis with pristine Zn-MOFs revealed that the Ag-functionalized material demonstrated a remarkable enhancement factor exceeding 30-fold in photodegradation efficiency under identical experimental conditions.The Ag-loaded Zn-MOFs exhibited exceptional stability during three consecutive cycling experiments,with negligible variation in their photocatalytic degradation performance.Notably,the material achieved over 95％photodegradation efficiency for Congo Red and Methylene Blue within 15 minutes under optimized conditions.These findings collectively demonstrate that Ag-impregnated MOFs exhibit superior photocatalytic performance in the degradation of azo dye-containing wastewater.The significant enhancement in degradation efficiency underscores the pivotal role of Ag functionalization in optimizing MOFs' catalytic activity,thereby providing a robust theoretical framework for advancing functional modifications of porous MOFs and guiding their practical implementation in industrial wastewater remediation.

Abstract:Traffic congestion is a major challenge faced by many cities around the world.This paper aims to reduce vehicle waiting times and improve traffic flow by optimizing traffic signal control using Deep Q-Networks(DQN).The method includes modeling the traffic signal control problem as a reinforcement learning problem and using the DQN algorithm to adaptively learn and optimize the strategy.The experimental results show that the improved DQN algorithm performs excellently in reducing vehicle waiting times and improving traffic efficiency,with an overall efficiency improvement of more than 20％.The validity of the improved algorithm was verified through simulation experiments,providing a new solution for urban traffic management.