The Symbolized Countryfolks in Shen Congwen＇s The Border Town

Shen Congwen is one of China＇s most renowned modem writers. The Border Town portrays the people andcustoms of a comer of Shangri-la, and humanizes, if not romanticizes nature and the country folk who are living in.The Border Town is perfect not only in subject, but in style and form as well. The complex theme of the novel isdepicted through the methods of symbolism and contrast. The current study focuses on how Shen made use ofsymbolism to portray the country folk. Although Shen used various kinds of symbolisms, natural, sexual, religious,celestial, and political, only the first two kinds will be dealt with in this paper. Symbols discussed in the paperinclude Cui Cui, Grandpa, the Border Town, river, water, ferry, bamboo, dreams, pagoda, animals, flowers, dreams,colors, etc.

The Symbolized Meaning of Voldemort in Harry Potter Series

Voldemort is the villain in the Harry Potter series,who was longing for immortality and tried to rule the world with dark magic.Does this name carry any significant meaning? This paper will focus on the analysis on the symbolized meaning of the name Voldemort.

State-Based Opacity Verification of Networked Discrete Event Systems Using Labeled Petri Nets

The opaque property plays an important role in the operation of a security-critical system,implying that pre-defined secret information of the system is not able to be inferred through partially observing its behavior.This paper addresses the verification of current-state,initial-state,infinite-step,and K-step opacity of networked discrete event systems modeled by labeled Petri nets,where communication losses and delays are considered.Based on the symbolic technique for the representation of states in Petri nets,an observer and an estimator are designed for the verification of current-state and initial-state opacity,respectively.Then,we propose a structure called an I-observer that is combined with secret states to verify whether a networked discrete event system is infinite-step opaque or K-step opaque.Due to the utilization of symbolic approaches for the state-based opacity verification,the computation of the reachability graphs of labeled Petri nets is avoided,which dramatically reduces the computational overheads stemming from networked discrete event systems.

SUMS OF DUAL TOEPLITZ PRODUCTS ON THE ORTHOGONAL COMPLEMENTS OF FOCK-SOBOLEV SPACES

We consider dual Toeplitz operators on the orthogonal complements of the FockSobolev spaces of all nonnegative real orders.First,for symbols in a certain class containing all bounded functions,we study the problem of when an operator which is finite sums of the dual Toeplitz products is compact or zero.Next,for bounded symbols,we construct a symbol map and exhibit a short exact sequence associated with the C^(*)-algebra generated by all dual Toeplitz operators with bounded symbols.

Binary Program Vulnerability Mining Based on Neural Network

Software security analysts typically only have access to the executable program and cannot directly access the source code of the program.This poses significant challenges to security analysis.While it is crucial to identify vulnerabilities in such non-source code programs,there exists a limited set of generalized tools due to the low versatility of current vulnerability mining methods.However,these tools suffer from some shortcomings.In terms of targeted fuzzing,the path searching for target points is not streamlined enough,and the completely random testing leads to an excessively large search space.Additionally,when it comes to code similarity analysis,there are issues with incomplete code feature extraction,which may result in information loss.In this paper,we propose a cross-platform and cross-architecture approach to exploit vulnerabilities using neural network obfuscation techniques.By leveraging the Angr framework,a deobfuscation technique is introduced,along with the adoption of a VEX-IR-based intermediate language conversion method.This combination allows for the unified handling of binary programs across various architectures,compilers,and compilation options.Subsequently,binary programs are processed to extract multi-level spatial features using a combination of a skip-gram model with self-attention mechanism and a bidirectional Long Short-Term Memory(LSTM)network.Finally,the graph embedding network is utilized to evaluate the similarity of program functionalities.Based on these similarity scores,a target function is determined,and symbolic execution is applied to solve the target function.The solved content serves as the initial seed for targeted fuzzing.The binary program is processed by using the de-obfuscation technique and intermediate language transformation method,and then the similarity of program functions is evaluated by using a graph embedding network,and symbolic execution is performed based on these similarity scores.This approach facilitates cross-architecture analysis of executable programs without their source codes and concurrently reduces the risk of symbolic execution path explosion.

Yeats’s Ideals:Women Old and Young

William Butler Yeats ranks among the most widely admired and intensively studied poets of the 20th century.This paper intends to explore the women who have exerted the most critical influences upon Yeats,namely Gonne,Lady Gregory,and Georgie Hyde-Lees.Even in Yeats’s poetry involved with symbolism,it is worth noting that his employment of symbols has used these women as the archetypes,and that the historical context rendered Yeats’s representations of them in his poetry all the more interesting.

Chinese New Year:A Celebration of Culture and Unity

Many countries list the Spring Festival as a national holiday,and about one-fifth of humanity celebrates this festival in various ways.THE Chinese New Year,also known as the Spring Festival,is a time-honored social and cultural tradition that has been celebrated for thousands of years.It is a festival that not only marks the inception of a new year in Chinese lunar calendar,but also acts as a symbolic bridge to connect individuals from different cultures and backgrounds.

Consumer Culture in The Great Gatsby

F.Scott Fitzgerald’s The Great Gatsby successfully portrays the“Jazz Age”.In the early 20th century,the United States transitioned from a production-based society to a consumer-based society,leading to an era of unparalleled prosperity.However,in the context of consumer culture,individuals often transition from being masters of their possessions to becoming enslaved by them.As a result,their behaviours and values become increasingly associated with extravagance and consumption.This paper uses Baudrillard’s theory of consumer society and textual analysis to explore the impact of consumer culture on human beings through the symbolization of men and objectification of women in The Great Gatsby.The meanings embedded in the novel are revealed from a different perspective.

Symbols in The Magic Barrel

The article takes the famous modern American Jewish writer Bernard Malamud’s novel The Magic Barrel as the object of study,and uses symbolism to interpret it,analyzing it one by one in terms of the magic barrel,the colors,the seasons and the windows,respectively,so as to reveal the process of getting rid of the childishness within the novel’s male protagonist,Leo Finkel,who is maturing,as well as the novel’s Jewish theme of searching for the soul of the self.

Guido Reni’s Infant Bacchus: “In vino veritas”

This article delves into the significance of Guido Reni’s Infant Bacchus,created during the Italian Baroque period.By examining historical and iconographic elements,the study aims to interpret the symbolism depicted in the painting.The historical aspects include the birth of Dionysus or Bacchus in classical and Italian Renaissance imagery and literary and visual sources that influenced Reni’s solo painting.The iconographic components encompass the infant’s nude body,the child’s bodily functions,and the attributes associated with Bacchus,the God of Agriculture,Revelry,and Wine,such as the grapevines,grapes,ivy,glass flask,kantharos(wine cup),and wine barrel.The emblematic and cosmological associations of Bacchus’s divinity are considered as well.

Design of high-performance ion-doped CoP systems for hydrogen evolution:From multi-level screening calculations to experiment

Rational design of high-performance electrocatalysts for hydrogen evolution reaction(HER)is vital for future renewable energy systems.The incorporation of foreign metal ions into catalysts can be an effective approach to optimize its performance.However,there is a lack of systematic theoretical studies to reveal the quantitative relationships at the electronic level.Here,we develop a multi-level screening methodology to search for highly stable and active dopants for CoP catalysts.The density functional theory(DFT)calculations and symbolic regression(SR)were performed to investigate the relationship between the adsorption free energy(ΔG_(H^(*)))and 10 electronic parameters.The mathematic formulas derived from SR indicate that the difference of work function(ΔΦ)between doped metal and the acceptor plays the most important role in regulatingΔG_(H^(*)),followed by the d-band center(d-BC)of doped system.The descriptor of HER can be expressed asΔG_(H^(*))=1.59×√|0.188ΔΦ+d BC+0.120|1/2-0.166 with a high determination coefficient(R^(2)=0.807).Consistent with the theoretical prediction,experimental results show that the Al-CoP delivers superior electrocatalytic HER activity with a low overpotential of75 m V to drive a current density of 10 mA cm^(-2),while the overpotentials for undoped CoP,Mo-CoP,and V-CoP are 206,134,and 83 m V,respectively.The current work proves that theΔΦis the most significant regulatory parameter ofΔG_(H^(*))for ion-doped electrocatalysts.This finding can drive the discovery of high-performance ion-doped electrocatalysts,which is crucial for electrocatalytic water splitting.

A robust symbol timing strategy for cellular systems

In cellular systems,establishing the initial symbol timing of potential preambles is the first step of a cell search.The envelope fluctuation of the downlink signal hinders the successful timing of conventional symbol timing methods.To solve this problem,a hybrid timing strategy is proposed with two novel detectors,namely the normalized replica-based detector and normalized differential detector.The strategy first detects all potential preambles via the normalized replica-based detector and then employs the normalized differential detector to verify the target preamble,which comes from the target cell and has the highest power.The strategy is unaffected by envelope fluctuation and has computational complexity comparable to that of conventional methods.Simu-lations and real-data tests show that the hybrid timing strategy is robust and practical for initial symbol timing.

The high-quality genome of lotus reveals tandem duplicate genes involved in stress response and secondary metabolites biosynthesis

Dear Editor,Lotus(Nelumbo nucifera Gaertn.),which has been domesticated and cultivated for several thousands of years and endowed with religious and cultural symbolism[1],belongs to the Nelumbo genus Nelumbonaceae family.As an early eudicot,it is not only essential for plant phylogeny but also widely used as a vegetable,a medic-inal herb,and for ornamental use.It contains abundant func-tional compounds,such as f lavonoids and benzylisoquinoline alkaloids(BIAs),which are used to treat diverse diseases.

Training-based symbol detection with temporal convolutional neural network in single-polarized optical communication system

In order to reduce the physical impairment caused by signal distortion,in this paper,we investigate symbol detection with Deep Learning(DL)methods to improve bit-error performance in the optical communication system.Many DL-based methods have been applied to such systems to improve bit-error performance.Referring to the speech-to-text method of automatic speech recognition,this paper proposes a signal-to-symbol method based on DL and designs a receiver for symbol detection on single-polarized optical communications modes.To realize this detection method,we propose a non-causal temporal convolutional network-assisted receiver to detect symbols directly from the baseband signal,which specifically integrates most modules of the receiver.Meanwhile,we adopt three training approaches for different signal-to-noise ratios.We also apply a parametric rectified linear unit to enhance the noise robustness of the proposed network.According to the simulation experiments,the biterror-rate performance of the proposed method is close to or even superior to that of the conventional receiver and better than the recurrent neural network-based receiver.

Crack Growth Rate Model Derived from Domain Knowledge-Guided Symbolic Regression

Machine learning(ML)has powerful nonlinear processing and multivariate learning capabilities,so it has been widely utilised in the fatigue field.However,most ML methods are inexplicable black-box models that are difficult to apply in engineering practice.Symbolic regression(SR)is an interpretable machine learning method for determining the optimal fitting equation for datasets.In this study,domain knowledge-guided SR was used to determine a new fatigue crack growth(FCG)rate model.Three terms of the variable subtree ofΔK,R-ratio,andΔK_(th)were obtained by analysing eight traditional semi-empirical FCG rate models.Based on the FCG rate test data from other literature,the SR model was constructed using Al-7055-T7511.It was subsequently extended to other alloys(Ti-10V-2Fe-3Al,Ti-6Al-4V,Cr-Mo-V,LC9cs,Al-6013-T651,and Al-2324-T3)using multiple linear regression.Compared with the three semi-empirical FCG rate models,the SR model yielded higher prediction accuracy.This result demonstrates the potential of domain knowledge-guided SR for building the FCG rate model.

Recognizing Ancient South Indian Language Using Opposition Based Grey Wolf Optimization

Recognizing signs and fonts of prehistoric language is a fairly difficult job that requires special tools.This stipulation make the dispensation period over-riding,difficult and tiresome to calculate.This paper present a technique for recognizing ancient south Indian languages by applying Artificial Neural Network(ANN)associated with Opposition based Grey Wolf Optimization Algorithm(OGWA).It identifies the prehistoric language,signs and fonts.It is an apparent from the ANN system that arbitrarily produced weights or neurons linking various layers play a significant role in its performance.For adaptively determining these weights,this paper applies various optimization algorithms such as Opposition based Grey Wolf Optimization,Particle Swarm Optimization and Grey Wolf Opti-mization to the ANN system.Performance results are illustrated that the proposed ANN-OGWO technique achieves superior accuracy over the other techniques.In test case 1,the accuracy value of OGWO is 94.89%and in test case 2,the accu-racy value of OGWO is 92.34%,on average,the accuracy of OGWO achieves 5.8%greater accuracy than ANN-GWO,10.1%greater accuracy than ANN-PSO and 22.1%greater accuracy over conventional ANN technique.

Application of Blank Symbols in Japanese Architecture and Indoor Designs

A symbol is an expression of meaning,while blank symbols express special meanings.By focusing on the application of blank symbols in Japanese architecture and indoor designs,we analyzed the aesthetic principles in Japanese architecture and indoor designs from the perspective of semiotics,such as“Kongji,”“Emptiness,”and“Dying out,”and their minimalist and pure design concepts.Traditional Chinese culture was also further explored,especially the profound influence of the“Chan sect”and the philosophy of“unity of heaven and mankind”on Japanese architecture and designs.This study aims to facilitate the coexistence and mutual appreciation of Chinese and Japanese architectural designs.

Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms

Radial Basis Function Neural Network(RBFNN)ensembles have long suffered from non-efficient training,where incorrect parameter settings can be computationally disastrous.This paper examines different evolutionary algorithms for training the Symbolic Radial Basis Function Neural Network(SRBFNN)through the behavior’s integration of satisfiability programming.Inspired by evolutionary algorithms,which can iteratively find the nearoptimal solution,different Evolutionary Algorithms(EAs)were designed to optimize the producer output weight of the SRBFNN that corresponds to the embedded logic programming 2Satisfiability representation(SRBFNN-2SAT).The SRBFNN’s objective function that corresponds to Satisfiability logic programming can be minimized by different algorithms,including Genetic Algorithm(GA),Evolution Strategy Algorithm(ES),Differential Evolution Algorithm(DE),and Evolutionary Programming Algorithm(EP).Each of these methods is presented in the steps in the flowchart form which can be used for its straightforward implementation in any programming language.With the use of SRBFNN-2SAT,a training method based on these algorithms has been presented,then training has been compared among algorithms,which were applied in Microsoft Visual C++software using multiple metrics of performance,including Mean Absolute Relative Error(MARE),Root Mean Square Error(RMSE),Mean Absolute Percentage Error(MAPE),Mean Bias Error(MBE),Systematic Error(SD),Schwarz Bayesian Criterion(SBC),and Central Process Unit time(CPU time).Based on the results,the EP algorithm achieved a higher training rate and simple structure compared with the rest of the algorithms.It has been confirmed that the EP algorithm is quite effective in training and obtaining the best output weight,accompanied by the slightest iteration error,which minimizes the objective function of SRBFNN-2SAT.

Inherent Features and Future Practice of Whole-Process People's Democracy from a Comparative Perspective

Democracy is a common value pursued by human society and is often viewed as an important symbol of the development level of a political civilization. However, after a review of the histories of different countries around the world。

Implications of The Gift of the Magi for Moral Education of Teenagers From the Perspective of Interaction Ritual Chains

Adolescence is a pivotal moment in shaping one’s character and holds great implications for one’s values and personal growth.The Gift of the Magi by O.Henry portrays how an ordinary young couple in difficult financial circumstances managed to show their love for each other,eulogizing truth,goodness,and beauty in humanity.We conducted a thorough examination of the significance of moral values conveyed in The Gift of the Magi for teenager education using the“situation-emotion-symbol”model that is based on Randall Collins’theory of interaction ritual chains in order to establish an interaction ritual chain model for moral education of teenagers.Our study reveals that situated cognition is useful in constructing the focus of attention for the moral education of teenagers;that shared emotion is the driving force for achieving moral education of teenagers;and that symbolic connections help teenagers put the virtues they’ve learned from The Gift of the Magi into action and provides effective measures that can significantly contribute to the cultivation and implementation of moral education among teenagers.