Exploration of the Teaching Reform of Computer Composition Principles with Ideological and Political Education at Anqing Normal University

The teaching mode of the Computer Composition Principles includes theoretical and practical teaching.At present,there is a problem of inconsistency in the teaching content of the two methods in our school.To this end,this paper conducts online and offline hybrid teaching based on the learning platform and the virtual simulation experiment platform,and cleverly applies ideological and political elements to theoretical and practical teaching to practice ideological and political education.Finally,the combination of theoretical and practical teaching modes can further help students firmly grasp the core knowledge points and improve the teaching quality and level of this course.

Construction of Ideological and Political Education in English Teacher Education Courses in Local Normal Universities:Objectives,Connotations,and Implementation Paths

The integration of ideological and political education into university curricula represents a new trend in holistic,comprehensive,and all-around education.The concept of“ideological and political education in English teacher education courses”embodies an interdisciplinary approach to curriculum reform.Grounded in the principle of fostering moral integrity,it aims to create high-quality courses by seamlessly integrating the transmission of knowledge and skills with the guidance of ideological values.This study explores the status quo,significance,and implementation pathways for integrating ideological and political education into English teacher education courses,providing valuable insights for future curricular development.

Robust autofocusing propagation in turbulence

Turbulence in complex environments such as the atmosphere and biological media has always been a great challenge to the application of beam propagation in optical communication, optical trapping and manipulation. To overcome this challenge, this study comprehensively investigates the robust propagation of traditional Gaussian and autofocusing beams in turbulent environments. In order to select stable beams that exhibit high intensity and high field gradient at the focal position in complex environments, Kolmogorov turbulence theory is used to simulate the propagation of beams in atmospheric turbulence based on the multi-phase screen method. We systematically analyze the intensity fluctuations, the variation of the coherence factor and the change in the scintillation index with propagation distance. The analysis reveals that the intensity fluctuations of autofocusing beams are significantly smaller than those of Gaussian beams, and the coherence of autofocusing beams is better than that of Gaussian beams under turbulence. Moreover, autofocusing beams exhibit less oscillation than Gaussian beams, indicating that autofocusing beams propagate in complex environments with less distortion and intensity fluctuation. Overall, this work clearly demonstrates that autofocusing beams exhibit higher stability in propagation compared with Gaussian beams, showing great promise for applications such as optical trapping and manipulation in complex environments.

Experimental confirmation of the linear relation between plasma current and external vertical magnetic field in EXL-50 spherical torus energetic electron plasmas

A three-fluid equilibrium plasma with bulk plasma and energetic electrons has been observed on the Xuanlong-50(EXL-50) spherical torus, where the energetic electrons play a crucial role in sustaining the plasma current and pressure. In this study, the equilibrium of a multi-fluid plasma was investigated by analyzing the relationship between the external vertical magnetic field(B_(V)),plasma current(I_(p)), the poloidal ratio(β_(p)) and the Shafranov formula. Remarkably, our research demonstrates some validity of the Shafranov formula in the presence of multi-fluid plasma in EXL-50 spherical torus. This finding holds significant importance for future reactors as it allows for differentiation between alpha particles and background plasma. The study of multi-fluid plasma provides a significant reference value for the equilibrium reconstruction of burning plasma involving alpha particles.

Identification of Mulberry Bacterial Blight Caused by Klebsiella oxytoca in Bazhong,Sichuan,China

To provide a scientific basis for controlling mulberry bacterial blight in Bazhong,Sichuan,China(BSC),this study aimed to isolate and purify pathogenic bacteria from diseased branches of mulberry trees in the region and to clarify their taxonomic status using morphological observation,physiological and biochemical detection,molecular-level identification,and the construction of a phylogenetic tree.A total of 218 bacterial strains were isolated from samples of diseased mulberry branches.Of these,7 strains were identified as pathogenic bacteria based on pathogenicity tests conducted in accordance with Koch’s postulates.Preliminary findings from the analysis of the 16S rRNA sequence indicated that the 7 pathogenic bacteria are members of Klebsiella spp.Morphological observation revealed that the pathogenic bacteria were oval-shaped and had capsules but no spores.They could secrete pectinase,cellulase,and protease and were able to utilize D-glucose,D-mannose,D-maltose,and D-Cellobiose.The 7 strains of pathogenic bacteria exhibited the highest homology with Klebsiella oxytoca.This study identifies Klebsiella oxytoca as the causative agent of mulberry bacterial blight in BSC,laying the foundation for the prevention and control of this pathogen and further investigation into its pathogenic mechanism.

Preparation for CSST:Star-galaxy Classification using a Rotationally Invariant Supervised Machine Learning Method

Most existing star-galaxy classifiers depend on the reduced information from catalogs,necessitating careful data processing and feature extraction.In this study,we employ a supervised machine learning method(GoogLeNet)to automatically classify stars and galaxies in the COSMOS field.Unlike traditional machine learning methods,we introduce several preprocessing techniques,including noise reduction and the unwrapping of denoised images in polar coordinates,applied to our carefully selected samples of stars and galaxies.By dividing the selected samples into training and validation sets in an 8:2 ratio,we evaluate the performance of the GoogLeNet model in distinguishing between stars and galaxies.The results indicate that the GoogLeNet model is highly effective,achieving accuracies of 99.6% and 99.9% for stars and galaxies,respectively.Furthermore,by comparing the results with and without preprocessing,we find that preprocessing can significantly improve classification accuracy(by approximately 2.0% to 6.0%)when the images are rotated.In preparation for the future launch of the China Space Station Telescope(CSST),we also evaluate the performance of the GoogLeNet model on the CSST simulation data.These results demonstrate a high level of accuracy(approximately 99.8%),indicating that this model can be effectively utilized for future observations with the CSST.

Discussion on the Construction and Application of Virtual Reality-Based Curriculum Resources for Kindergarten Education

The construction of early childhood curriculum resources serves as a vital vehicle and precondition for the implementation of collective teaching activities in kindergartens.However,traditional curriculum resources based on graphic language or the linguistic descriptions of early childhood educators often fail to provide children with an immersive experience during collective teaching activities,leading to a lack of initiative and interest in learning.This paper discusses the methods for building a kindergarten curriculum resource library and,based on this foundation,employs virtual reality technology for three-dimensional modeling of the library to enrich the curriculum resources in kindergartens.Furthermore,this paper proposes to train early childhood educators in virtual reality technology to enhance their abilities to operate and utilize virtual reality equipment,which can emphasize the children’s central role in the learning process,better achieve educational goals,and improve teaching outcomes.

Teaching Reform and Practice of “Mathematical Analysis” under the New Engineering Education Paradigm

With the advent and promotion of the new engineering education paradigm,university mathematics courses face new challenges and opportunities.As a fundamental course for engineering majors,the reform of“Mathematical Analysis”is particularly crucial.This paper explores the necessity,specific practices,and outcomes of teaching reform in“Mathematical Analysis”within the context of the new engineering education.By reforming teaching content,methods,and assessment approaches,this study aims to enhance students’mathematical literacy and comprehensive abilities to meet the demands of the new engineering education development.

Research on the Integration Path of Postgraduate Professional Courses into the Construction of Curriculum Ideology and Politics

The curriculum ideology and politics play an important role in cultivating students’correct worldview,outlook on life,and values.In recent years,universities and colleges have begun to pay attention to the cultivation of postgraduates’moral education and the construction of postgraduates’curriculum ideology and politics.This paper takes the course“Theory of Software Engineering”of Anqing Normal University as an example,discusses the paths of integrating postgraduate professional courses into the construction of curriculum ideology and politics,and puts forward the paths of feeding back from scientific research,connecting with practice and summarizing and condensing,which are aimed at improving postgraduates’comprehensive quality and innovation ability,and have positive significance for cultivating high-level applied scientific and technological talents who are both moral and talented.

Deep Reinforcement Learning for IRS-Assisted UAV Covert Communications

Covert communications can hide the existence of a transmission from the transmitter to receiver.This paper considers an intelligent reflecting surface(IRS)assisted unmanned aerial vehicle(UAV)covert communication system.It was inspired by the high-dimensional data processing and decisionmaking capabilities of the deep reinforcement learning(DRL)algorithm.In order to improve the covert communication performance,an UAV 3D trajectory and IRS phase optimization algorithm based on double deep Q network(TAP-DDQN)is proposed.The simulations show that TAP-DDQN can significantly improve the covert performance of the IRS-assisted UAV covert communication system,compared with benchmark solutions.

Turing/Turing-like patterns:Products of random aggregation of spatial components

Turing patterns are typical spatiotemporal ordered structures in various systems driven far from thermodynamic equilibrium.Turing’s reaction-diffusion theory,containing a long-range inhibiting agent and a local catalytic agent,has provided an explanation for the formation of some patterns in nature.Numerical,experimental and theoretical studies about Turing/Turing-like patterns have been generally focused on systems driven far from thermodynamic equilibrium.The local dynamics of these systems are commonly very complex,which brings great difficulties to understanding of formation of patterns.Here,we investigate a type of Turing-like patterns in a near-equilibrium thermodynamic system experimentally and theoretically,and put forward a new formation mechanism and a quantitative method for Turing/Turing-like patterns.Specifically,we observe a type of Turing-like patterns in starch solutions,and study the effect of concentration on the structure of patterns.The experimental results show that,with the increase of concentration,patterns change from spots to inverse spots,and labyrinthine stripe patterns appear in the region of intermediate concentration.We analyze and model the formation mechanism of these patterns observed in experiments,and the simulation results agree with the experimental results.Our conclusion indicates that the random aggregation of spatial components leads to formation of these patterns,and the proportion of spatial components determines the structures.Our findings shed light on the formation mechanism for Turing/Turing-like patterns.

Effect of polytetrafluoroethylene hollow fiber microstructure on formaldehyde carbonylation performance in membrane contactor

Membrane contactor is regarded as a promising method for reaction and process intensification. The feasibility of formaldehyde carbonylation to synthesize glycolic acid using polytetrafluoroethylene(PTFE)membrane contactor has been proved in our previous study. In this paper, the effect of membrane microstructure on process performance was further investigated. Three porous PTFE hollow fibers with different pore sizes and one polydimethylsiloxane(PDMS)/PTFE composite membrane with dense layer were fabricated for comparison. The physical and chemical properties of four membranes, including chemical composition, morphology, contact angle, liquid entry pressure, thermodynamic analysis and gas permeability, were systemically characterized. Experiments of formaldehyde carbonylation under different reaction conditions were conducted. The results indicated that the yield of glycolic acid increased with decreasing pore size for porous membranes, which was due to the improvement of wetting behavior. The dense layer of PDMS in composite hollow fiber could effectively prevent the solvent from entering membrane pores, thus the membrane exhibited the best performance. At reaction temperature of 120℃ and operation pressure of 3.0 MPa, the yield of glycolic acid was always higher than 90% as the mass ratio of trioxane and phosphotungstic acid increased from 0.2:1 to 0.8:1. The highest turnover frequency was up to 26.37 mol·g^(-1)·h^(-1). This study provided a reference for the understanding and optimization of membrane contactors for the synthesis of glycolic acid using solvent with low surface tension.

Revising the H_(2)^(16)O line-shape parameters around 1.1μm based on the speed-dependent Nelkin–Ghatak profile and the Hartmann–Tran profile

Accurate spectroscopic data for H_(2)^(16)O in the 1.1μm region are particularly important for the study of Earth's atmosphere.The pure water vapor molecular spectra were measured based on direct laser absorption spectroscopy using a narrow line-width external cavity diode laser combined with a high-precision Fabry-Pérot etalon.A total of 31 H_(2)^(16)O transitions were studied for the first time by using the speed-dependent Nelkin-Ghatak profile and the Hartmann-Tran profile.From an accurate line-shape analysis,we obtained the line intensities and the self-broadening coefficients,and they are compared with the available data reported in the HITRAN 2016 database and the HITRAN 2020 database.Finally,we obtained information on the influence of Dicke narrowing,as well as the correlations between Dicke narrowing and speed dependence,and of speed-dependent effects.

Four-stage cascaded variable optical attenuator with large attenuation range for quantum key distribution

A four-stage cascaded variable optical attenuator(VOA)with a large attenuation range is presented.The VOA is based on a Mach–Zehnder interferometer(MZI)and fabricated in a silica-based planar lightwave circuit(PLC)platform.The thermo-optic effect is used to achieve intensity modulation.The measured maximum attenuation of the four-stage cascaded VOA is 88.38 d B.The chip is also tested in a quantum key distribution(QKD)system to generate signal and decoy states.The mean photon number after attenuation of the four-stage cascaded VOA is less than 0.1,which can meet the requirement of QKD.

Application of Mind Mapping in General Zoology Teaching

Against the background of the new curriculum reform,teachers are no longer just expected to impart knowledge exclusively,but they also carry the responsibility to encourage students to think independently,improve students’thinking skills,and cultivate good learning and thinking habits among students,so as to enable students to use knowledge in a flexible manner and improve their thinking skills.General zoology is a highly specialized discipline,with scattered knowledge points and various concepts.Since the traditional teaching mode limits students’mastery of knowledge points,teachers need to find a teaching method that can help students understand knowledge points and exercise independent thinking.Mind mapping is a concrete thinking tool that helps students exercise their thinking skills.The introduction of mind mapping in the teaching of general zoology allows students to have a clearer understanding of the overall framework of this discipline.The application of mind mapping can be divided into four parts:pre-class preview,classroom study,after-class review,and zoology experiment.The application of mind mapping to teaching not only improves students’learning efficiency,but also enhances students’comprehensive ability and stimulates their interest in general zoology.In this paper,the 17th chapter of“Fish”in general zoology is taken as an example to elaborate the application of mind mapping in the teaching of general zoology.

From Big Data to Intelligent Tutoring: Exploring the Application of Big Data Technology in the Ideological and Political Education for College Counselors

This paper explores the application of big data technology in ideological and political education for college counselors.Big data-driven personalized counseling for students,social network analysis,and public opinion monitoring can optimize the efficiency of counselor work.However,there are still challenges concerning data privacy protection,technical support,and training.By scientifically evaluating and addressing these challenges,big data technology is expected to enhance the effectiveness of college counselors and improve the quality of ideological and political education.In the future,with technological advancements,big data technology will become an essential tool for higher education management.

Research on the Teaching Reform of Radio-Frequency Identification Course Based on the Educational Philosophy of Outcome-Based Education

In order to improve the teaching effect and quality of the course Radio-Frequency Identification,we investigated the characteristics of the course and problems in its teaching practice.Based on the educational philosophy of outcome-based education(OBE),we carried out teaching reforms,which included the use of flipped classroom,the organic combination of theoretical and practical teaching,school-enterprise cooperation and collaborative education,as well as other measures.The results showed that the improved teaching method can effectively stimulate students’interest in learning,enhance students’learning initiative,improve students’ability to solve complex engineering problems in the field of radio-frequency identification,cultivate the spirit of teamwork among students,and nurture their innovative practical ability.

Remolding Software Engineering Course Based on Engineering Education Concepts

The core of the engineering education concepts is student-centered teaching,result-oriented teaching,and continuous improvement.It is necessary to carry out course remolding of software engineering course guided by engineering education concepts.This paper first analyzes the pain points of teaching the course of software engineering,and then introduces how to remold the course based on engineering education concepts,including reformulating the teaching objectives,teaching modes,and assessment methods.Through teaching practice,we find that the improved course has achieved a better teaching result,which reflects the advantages of the engineering education concepts.

Predicting stability of integrated circuit test equipment using upper side boundary values of normal distribution

In response to the growing complexity and performance of integrated circuit(IC),there is an urgent need to enhance the testing and stability of IC test equipment.A method was proposed to predict equipment stability using the upper side boundary value of normal distribution.Initially,the K-means clustering algorithm classifies and analyzes sample data.The accuracy of this boundary value is compared under two common confidence levels to select the optimal threshold.A range is then defined to categorize unqualified test data.Through experimental verification,the method achieves the purpose of measuring the stability of qualitative IC equipment through a deterministic threshold value and judging the stability of the equipment by comparing the number of unqualified data with the threshold value,which realizes the goal of long-term operation monitoring and stability analysis of IC test equipment.

Leaf N and P stoichiometry of 57 plant species in the Karamori Mountain Ungulate Nature Reserve,Xinjiang,China

Nitrogen （N） and phosphorus （P） are the major nutrients that constrain plant growth and development, as well as the structure and function of ecosystems. Hence, leaf N and P patterns can contribute to a deep understanding of plant nutrient status, nutrient limitation type of ecosystems, plant life-history strategy and differentiation of functional groups. However, the status and pattern of leaf N and P stoichiometry in N-deficiency desert ecosystems remain unclear. Under this context, the leaf samples from 57 plant species in the Karamori Mountain Ungulate Nature Reserve, eastern Junggar Desert, China were investigated and the patterns and interrelations of leaf N and P were comparatively analyzed. The results showed that the average leaf N concentration, P concentration, and N：P ratio were 30.81 mg/g, 1.77 mg/g and 17.72, respectively. This study found that the leaf N concentration and N：P ratio were significantly higher than those of studies conducted at global, national and regional scales; however, the leaf P concentration was at moderate level. Leaf N concentration was allometrically correlated with leaf P and N：P ratio across all species. Leaf N, P concentrations and N：P ratio differed to a certain extent among plant functional groups. C4 plants and shrubs, particularly shrubs with assimilative branches, showed an obviously lower P concentration than those of C3 plants, herbs and shrubs without assimilative branches. Shrubs with assimilative branches also had lower N concentration. Fabaceae plants had the highest leaf N, P concentrations （as well as Asteraceae） and N：P ratio; other families had a similar N, P-stoichiometry. The soil in this study was characterized by a lack of N （total N：P ratio was 0.605）, but had high N availability compared with P （i.e. the available N：P ratio was 1.86）. This might explain why plant leaves had high N concentration （leaf N：P ratio〉16）. In conclusion, the desert plants in the extreme environment in this study have formed their intrinsic and special stoichiometric characteristics in relation to their life-history strategy.