This response to Zongjie Wu's "Interpretation, autonomy, and interpretation" focuses on the "battle between East and West" which contextualizes Wu's proposal to counter the current Western domination of Chinese pedagogic discourse with an "authentic language" recovered from the Chinese classics. It points out that it is impossible and undesirable to reject all Western influences. The dualistic opposition between East and West over-simplifies and blinds one to the complexity of China's history and culture, and unnecessarily limits future possibilities. It challenges (...) Wu's conflation of Confucianism and Daoism and his claim that the authentic "language of Tao" recovered from the "Analects" is a language "pointing to the nameless". The response concludes with an alternative Deweyan account of how to make Chinese education authentic. (shrink)

In recent years, more and more people are applying Convolutional Neural Networks to the study of sound signals. The main reason is the translational invariance of convolution in time and space. Thereby the diversity of the sound signal can be overcome. However, in terms of sound direction recognition, there are also problems such as a microphone matrix being too large, and feature selection. This paper proposes a sound direction recognition using a simulated human head with microphones at both ears. Theoretically, (...) the two microphones cannot distinguish the front and rear directions. However, we use the original data of the two channels as the input of the convolutional neural network, and the resolution effect can reach more than 0.9. For comparison, we also chose the delay feature (GCC) for sound direction recognition. Finally, we also conducted experiments that used probability distributions to identify more directions. (shrink)

本书简要地阐明了文学本文的创造过程,文学作品的构成及其实现过程,文学的审美价值系统及其实现过程,文学的历史发展过程。.

An esssential work of this enigmatic sage, draws from the ancient traditions of Buddhism, Taosim, and Advaita Vedanta.

Boolean-valued models generalize classical two-valued models by allowing arbitrary complete Boolean algebras as value ranges. The goal of my dissertation is to study Boolean-valued models and explore their philosophical and mathematical applications.In Chapter 1, I build a robust theory of first-order Boolean-valued models that parallels the existing theory of two-valued models. I develop essential model-theoretic notions like “Boolean-valuation,” “diagram,” and “elementary diagram,” and prove a series of theorems on Boolean-valued models, including the (strengthened) Soundness and Completeness Theorem, the Löwenheim–Skolem Theorems, (...) the Elementary Chain Theorem, and many more.Chapter 2 gives an example of a philosophical application of Boolean-valued models. I apply Boolean-valued models to the language of mereology to model indeterminacy in the parthood relation. I argue that Boolean-valued semantics is the best degree-theoretic semantics for the language of mereology. In particular, it trumps the well-known alternative—fuzzy-valued semantics. I also show that, contrary to what many have argued, indeterminacy in parthood entails neither indeterminacy in existence nor indeterminacy in identity, though being compatible with both.Chapter 3 (joint work with Bokai Yao) gives an example of a mathematical application of Boolean-valued models. Scott and Solovay famously used Boolean-valued models on set theory to obtain relative consistency results. In Chapter 3, I investigate two ways of extending the Scott–Solovay construction to set theory with urelements. I argue that the standard way of extending the construction faces a serious problem, and offer a new way that is free from the problem.Abstract prepared by Xinhe Wu.E-mail: [email protected]. (shrink)

The COVID-19 pandemic has forced higher education institutions to shift their teaching activities from traditional face-to-face to online learning. This brings a great challenge to the creativity training of vocational college students, who not only learn theoretical knowledge but also cultivate technical skills. Therefore, it is very important to explore the influencing factors of online learning on students’ creativity during the epidemic. By relying on the related literature review, an extensive model is developed by integrating the expectation confirmation model, technology (...) task fit model, and the technology acceptance model to illustrate key factors that influence creativity. Based on the proposed model, theory-based hypotheses are tested through structural equation modeling employing empirical data gathered through a survey questionnaire of 229 students from different vocational colleges in China. In addition, to extend the analysis results, this paper performs a comparative analysis based on gender. The findings demonstrate that perceived ease of use and perceived usefulness significantly influence knowledge sharing; knowledge sharing significantly affects creativity. However, there is no substantial relationship between perceived usefulness and attitude, and no relationship between attitude and knowledge sharing. Moreover, a multi-group comparison shows that there is a significant gender difference between perceived ease of use and attitude. Based on the findings, theoretical and practical implications are discussed. (shrink)

In response to the COVID-19 pandemic, millions of students in China followed an emergency policy called “Suspending Classes without Stopping Learning” to continue their study online as schools across the country were closed. The present study examines how students adapted to learning online in these unprecedented circumstances. We aimed to explore the relationship between adaptability, academic emotion, and student engagement during COVID-19. 1,119 university students from 20 provinces participated in this longitudinal study (2 time points with a 2-week interval). The (...) results showed that adaptability (the ability to respond to changes) and student engagement are significantly positively correlated with positive academic emotion and negatively correlated with negative academic emotion. Furthermore, adaptability not only directly predicts student engagement, but also affects student engagement through the chain mediation of positive academic emotion and negative academic emotion. The results contribute to the gap in knowledge regarding changes in students’ learning in response to the outbreak. This study further explains the internal mechanisms mediating the relationship between adaptability and student engagement. It may provide references for educational researchers and universities in dampening the negative effects of COVID-19 on students’ learning by improving their adaptability and developing positive academic emotions. (shrink)

This study examines the role of responsible entrepreneurship among female entrepreneurs by examining how and when responsible entrepreneurship may exert a positive influence on female entrepreneurial success. Using the data collected from 337 Chinese female entrepreneurs, and by integrating responsible entrepreneurship research with a dynamic capability framework, our findings show, firstly, that responsible entrepreneurship is positively correlated to female entrepreneurial success; secondly, this relationship is mediated by female entrepreneurs’ opportunity recognition; and thirdly, the indirect effect of responsible entrepreneurship on female (...) entrepreneurial success through opportunity recognition is weaker when women entrepreneurs perceive more gender discrimination. Furthermore, using a post hoc analysis, we find that responsible entrepreneurship has a positive impact on entrepreneurial success for both male and female entrepreneurs, but that this impact is more significant for female entrepreneurs than for their male counterparts. With the contextual factor of traditional female social stereotypes inadvertently contributing to greater gender discrimination in the field of entrepreneurship, our results underscore the importance of both responsible entrepreneurship and opportunity recognition in promoting female entrepreneurial success. (shrink)

Grounded on the social exchange theory (SET), social cognitive theory (SCT), and self-determination theory (SDT), this study aims to explore the mediating role of self-efficacy (SE) and work engagement (WE) on the effect of social support (SS) on job satisfaction (JS) among Chinese ethnic minority kindergarten teachers (KTs). The results show that: (1) SS has a directly significant effect on JS; (2) WE mediates the relationship between SS and JS; and (3) SE mediates the relationship between SS and WE. Although (...) the mediation of SE on the relationship between SS and JS is not found, the posited multiple mediations of SE and WE on the relationship between SS and JS are totally accepted. The results reveal that SS mainland Chinese ethnic minority KTs received can not only have a direct effect on JS but also have an indirect impact through the one-path mediating role of WE and the chain mediating role of SE and WE. The results suggest that governments, supervisors, and sponsors should work together to provide ethnic minority KTs with more prioritized SS from both cultural psychology and financial material and opportunities for facilitating professional knowledge and skills in order to enhance their SE, inspire their WE, and eventually accumulate their JS. (shrink)

ABSTRACT We are concerned with the theorem proving in annotated logics. By using annotated polynomials to express knowledge, we develop an inference rule superposition. A proof procedure is thus presented, and an improvement named M- strategy is mainly described. This proof procedure uses single overlaps instead of multiple overlaps, and above all, both the proof procedure and M-strategy are refutationally complete.

Using a manually collected dataset on the overseas experiences of directors of Chinese listed firms, we examine the effects of returnee directors on firms’ corporate social responsibility engagement. Our results show that returnee directors significantly improve their firms’ CSR engagement. The positive relationship between the percentage of returnee directors and CSR engagement is more significant when a firm is in a competitive industry, when a firm has no government ownership, when a firm’s CEO is not politically connected, and when a (...) firm’s CEO is older. Furthermore, we find that only long-term foreign professional or academic experience matters, whereas short-term visiting experience does not. Finally, our results are robust after controlling for endogeneity. Therefore, this paper offers clear policy implications by suggesting that hiring more returnees as corporate directors is an efficient way to enhance firms’ CSR, which may be of particular interest to regulators in emerging markets. (shrink)

A new venture barely makes a profit in its initial stage, and its success depends on innovation. Innovation is related to the work environment, and the innovation behavior of employees is of great significance to the performance improvement of new venture. Based on the previous research, in this study, hypotheses on the correlation between work environment, employee innovation behavior, and corporate performance are put forward first. Then, with team cooperation, organizational incentive, leadership support, sufficient resources, and work pressure as the (...) factors of the work environment, the bosses, middle and senior managers involved in entrepreneurship, and the main members of the entrepreneurial team of 202 newly established enterprises in developed regions are surveyed online or in scene. Multivariate hierarchical regression analysis is performed to analyze the data collected from the questionnaire. The results show that the effective recovery rate of the questionnaire is 86.4%; the number of traditional enterprises is 108, and that of R&D enterprises is 68 ; teamwork, leadership support, and work pressure are all correlated with employees’ innovative behavior ; employee innovation behavior is positively correlated with enterprise performance ; the working environment and employee innovation behavior promote enterprise performance ; and the working environment affects the relationship between employee innovation behavior and enterprise performance. The study theoretically enriches the research on the relationship between innovation behavior, work environment, and enterprise performance of new ventures. In practice, it is suggested that start-up enterprises provide good working environment for employees and attach importance to innovation activities at the individual level of employees, which provides useful guidance and reference for the development of Chinese start-up enterprises. (shrink)

Previous studies of the relationship between hope and life satisfaction left the underlying mechanism of how hope predicts life satisfaction unexplored to scholars. This study thus investigates the two potential mediators in the relationship between hope and life satisfaction among a sample of Chinese shadow education institution tutors who may be under immense professional development pressure from a cross-sectional approach. The main body of the study consists of an online survey in which 221 SEI tutors reported their hope, positive coping, (...) perceived social support, and life satisfaction. The survey results were analyzed using mediation and moderation analysis via SPSS 23.0. The results indicated that positive coping improved the relationship between hope and life satisfaction, supporting the hypothesis regarding the serial mediating effect of positive coping and perceived social support. In other words, tutors with a high level of hope tend to adopt positive coping strategies, thus will receive more social support and improve life satisfaction. Our findings revealed the independent and accumulative mediating effects of positive coping and perceived social support on the relationship between hope and life satisfaction, and had implications for the psychological intervention of SEI tutors who are currently facing enormous industry pressure. (shrink)

Differential leadership as a localized leadership style gradually developed on the basis of the Pattern of Differential Sequence. It plays a dual role in stimulating “insider subordinates” and “outsider subordinates” through the dynamic transformation of the roles. Using the process of game reasoning, the study identifies the differing principles used by insider subordinates and outsider subordinates in implementing deviant innovative behaviors. The simulation graph presents the perceived benefits of employees performing or not performing deviant innovative behaviors as clues during the (...) reasoning process, and implements deviant innovative behaviors for the high risk-taking trait of insider subordinates and the high internal control personality of outsider subordinates who implement deviant innovation. The theoretical derivation of behavior provides relevant references, and provides counter measures for effectively promoting employees’ deviant innovative behavior in the context of differential leadership. (shrink)

Eye-tracking technology has become a powerful tool for biomedical-related applications due to its simplicity of operation and low requirements on patient language skills. This study aims to use the machine-learning models and deep-learning networks to identify key features of eye movements in Alzheimer's Disease (AD) under specific visual tasks, thereby facilitating computer-aided diagnosis of AD. Firstly, a three-dimensional (3D) visuospatial memory task is designed to provide participants with visual stimuli while their eye-movement data are recorded and used to build an (...) eye-tracking dataset. Then, we propose a novel deep-learning-based model for identifying patients with Alzheimer's Disease (PwAD) and healthy controls (HCs) based on the collected eye-movement data. The proposed model utilizes a nested autoencoder network to extract the eye-movement features from the generated fixation heatmaps and a weight adaptive network layer for the feature fusion, which can preserve as much useful information as possible for the final binary classification. To fully verify the performance of the proposed model, we also design two types of models based on traditional machine-learning and typical deep-learning for comparison. Furthermore, we have also done ablation experiments to verify the effectiveness of each module of the proposed network. Finally, these models are evaluated by four-fold cross-validation on the built eye-tracking dataset. The proposed model shows 85% average accuracy in AD recognition, outperforming machine-learning methods and other typical deep-learning networks. (shrink)

In this study, we examine the equity premium of seventeen nonfinancial sectors covering sample 306 firms using monthly data from January 2002 to December 2018. Two-stage least square method is applied to estimate the macro-based multifactor model. It is found that the market premium and the interest rate factors are significantly affecting the industry equity premium of all the nonfinancial sectors. However, there exists a positive effect of other macroeconomic variables such as money supply, foreign direct investment, and industrial production (...) which is different for the different sectors based on its nature of product and services they offered. The industries based on their product development which are linked to particular macroeconomic variables have more effect than others such as increase in money supply which cannot increase the sale of pharmaceutical products until needed. Similarly, an interesting insight reveals that industries producing seasonal goods, e.g., food producing, are not very much affected by macroeconomic variables but the change in seasons and similar results also revealed for tobacco industry. (shrink)

Elucidating distinct morphological atrophy patterns of Alzheimer’s disease and its prodromal stage, namely, mild cognitive impairment helps to improve early diagnosis and medical intervention of AD. On that account, we aimed to obtain distinct patterns of voxel-wise morphological atrophy and its further perturbation on structural covariance network in AD and MCI compared with healthy controls. T1-weighted anatomical images of matched AD, MCI, and HCs were included in this study. Gray matter volume was obtained using voxel-based morphometry and compared among three (...) groups. In addition, structural covariance network of identified brain regions exhibiting morphological difference was constructed and compared between pairs of three groups. Thus, patients with AD have a reduced hippocampal volume and an increased rate of atrophy compared with MCI and HCs. MCI exhibited a decreased trend in bilateral hippocampal volume compared with HCs and the accelerated right hippocampal atrophy rate than HCs. In AD, the hippocampus further exhibited increased structural covariance connected to reward related brain regions, including the anterior cingulate cortex, the putamen, the caudate, and the insula compared with HCs. In addition, the patients with AD exhibited increased structural covariance of left hippocampus with the bilateral insula, the inferior frontal gyrus, the superior temporal gyrus, and the cerebellum than MCI. These results reveal distinct patterns of morphological atrophy in AD and MCI, providing new insights into pathology of AD. (shrink)

Drawing on the social exchange theory, this study adopted a cross-level framework to investigate the influence of consumer group communication on consumer product image perception and brand memory. In addition, this paper examined the moderating role of consumer group involvement in the cross-level relationship between consumer group communication and consumer product image perception. Based on a sample of 116 groups and 530 consumers, results revealed that consumer group communication has a significant positive influence on brand memory formation across levels. Consumer (...) product image perception plays a cross-layer mediated role between consumer group communication and brand memory. Group involvement plays a cross-level negative moderating role between consumer group communication and consumer product image perception, and moderates the mediating role of consumer product image perception between consumer group communication and consumer brand memory across different levels. Finally this paper discussed implications for research and practice. (shrink)

Poverty alleviation through tourism is an important way for China to achieve targeted poverty alleviation and win the battle of poverty alleviation. As a region with deep poverty and great difficulty in poverty alleviation, whether tourism development has injected key impetus into ethnic minority areas needs to be tested by both qualitative analysis and quantitative measurement. This paper takes eight ethnic provinces in China as an example to conduct an empirical study. Based on the Data Envelopment Analysis -BCC model and (...) Malmquist index, it evaluates the tourism investment and tourism poverty alleviation efficiency of the ethnic regions in the two stages of tourism poverty alleviation, and analyzes them by classification. The results of the study show: The pure technical efficiency in the first stage is relatively high, but the total factor productivity of each region is declining; The pure technical efficiency in the second stage is also relatively high, but the scale efficiency is low, and the change rate of total factor productivity of the provinces in China has increased significantly; The “double high” type includes Guangxi, Inner Mongolia, and Guizhou, and the “double low” type includes Qinghai, Yunnan, Tibet, Xinjiang, and Ningxia. The results of the study generally show that tourism poverty alleviation has brought about the improvement of the living standards of residents and the development of local economy, but the efficiency of tourism poverty alleviation needs to be improved. On this basis, the article puts forward corresponding improvement measures, in order to further help the ethnic minority areas get rid of poverty in a comprehensive way by promoting the efficient and sustainable development of tourism. (shrink)

The optimization of high-dimensional functions is an important problem in both science and engineering. Wolf pack algorithm is a technique often used for computing the global optimum of a multivariable function. In this paper, we develop a new wolf pack algorithm that can accurately compute the optimal value of a high-dimensional function. First, chaotic opposite initialization is designed to improve the quality of initial solution. Second, the disturbance factor is added in the scouting process to enhance the searching ability of (...) wolves, and an adaptive step length is designed to enhance the global searching ability to prevent wolves from falling into the local optimum effectively. A set of standard test functions are selected to test the performance of the proposed algorithm, and the test results are compared with other algorithms. The high-dimensional and ultrahigh-dimensional functions are tested. The experimental results show that the proposed algorithm features in good global convergence, high accuracy calculation, strong robustness, and excellent performance in high-dimensional functions. (shrink)

Safeguarding GenAI models against threats and aligning them with security requirements is imperative yet challenging. This chapter provides an overview of the security landscape for generative models. It begins by elucidating common vulnerabilities and attack vectors, including adversarial attacks, model inversion, backdoors, data extraction, and algorithmic bias. The practical implications of these threats are discussed, spanning domains like finance, healthcare, and content creation. The narrative then shifts to exploring mitigation strategies and innovative security paradigms. Differential privacy, blockchain-based provenance, quantum-resistant algorithms, (...) and human-guided reinforcement learning are analyzed as potential techniques to harden generative models. Broader ethical concerns surrounding transparency, accountability, deepfakes, and model interpretability are also addressed. The chapter aims to establish a conceptual foundation encompassing both the technical and ethical dimensions of security for generative AI. It highlights open challenges and lays the groundwork for developing robust, trustworthy, and human-centric solutions. The multifaceted perspective spanning vulnerabilities, implications, and solutions is intended to further discourse on securing society’s growing reliance on generative models. Frontier model security is discussed using Anthropic proposed approach. (shrink)

Study explores the core areas that enhance the teaching ability of Chinese teachers in the Chinese+Medical learning program. The participants in the study were 150 students of Dali University and questionnaires were used to collect data from the participants. Structural Equation Modelling (SEM), Pearson correlation analysis, and ANOVA test were conducted to determine the relationship of these factors. The results of the Pearson correlation are the following findings: teaching experience (TE) has a small positive correlation with teaching ability (r = (...) 0.40,p = 0.05) while professional development training (PDT) has a strong positive correlation with the teaching ability, (r = 0.52,p = 0.01) and the pedagogical strategies (PS) (r = 0.47, p = 0.03) have the strongest positive connections with teaching ability, teacher collaboration (TC) (r = 0.30,p = 0.10 ) and educational resources (ER) (r = 0.35,p = 0.07) exhibit weaker non-significant associations. The SEM analysis findings indicate that the highest path coefficients about teaching ability areTE (C = 0.30,p = 0.02), TC (C = 0.40,p = 0.01), PDT (C = 0.45,p = 0.01),PS (C = 0.35,p = 0.01), and ER(C = 0.25,p = 0.03). The findings of the ANOVA also indicate high variation in teaching competency regarding different PDT (p = 0.03), TE (p = 0.02), ER (p = 0.01), PS (p = 0.04), and TC (p = 0.02). The results altogether suggest that the most significantkey elements that can be employed to improve the teaching ability within Chinese+Medical Education are PDT and TC. (shrink)

Lentinus edodes sticks are susceptible to mold infection during the culture process, and manual identification of infected sticks is heavy, untimely, and inaccurate. Aiming to solve this problem, this paper proposes a method for identifying infected Lentinus edodes sticks based on improved ResNeXt-50 deep transfer learning. First, a dataset of Lentinus edodes stick diseases was constructed. Second, based on the ResNeXt-50 model and the pretraining weight of the ImageNet dataset, the influence of pretraining weight parameters on recognition accuracy was studied. (...) Finally, six fine-tuning strategies of the fully connected layer were designed to modify the fully connected layer of ResNeXt-50. The experimental results show that the recognition accuracy of the method proposed in this paper can reach 94.27%, which is higher than the Vgg16, GoogLeNet, ResNet50, and MobileNet v2 models by 8.47%, 6.49%, 4.68%, and 9.38%, respectively, and the F1-score can reach 0.9422. The improved method proposed in this paper can reduce the calculation pressure and overfitting problem of the model, improve the accuracy of the model in the identification of Lentinus edodes stick mold diseases, and provide an effective solution for the selection of diseased sticks. (shrink)

With the increasing number of electric vehicles, the charging demand of EVs has brought many new research hotspots, i.e., charging path planning and charging pricing strategy of the charging stations. In this paper, an integrated framework is proposed for multiobjective EV path planning with varied charging pricing strategies, considering the driving distance, total time consumption, energy consumption, charging fee such factors, while the charging pricing strategy is designed based on the objectives of maximizing the total revenues of the charging stations (...) and balancing the profits of the charging stations. First, the energy consumption model of EVs, the M/M/S queuing model of charging stations, and the charging model of charging piles are established. A novel charging path planning algorithm is proposed based on bidirectional Martins’ algorithm, which can assist EV users to select charging stations and plan charging paths. Then, a particle swarm optimization algorithm is applied to solve the optimal solution of charging station pricing designation. Finally, the method proposed in the paper is simulated on the street map of Shenzhen to verify the efficacy of the multiobjective charging path planning for EVs and the feasibility of the charging pricing strategy. (shrink)

Based on the perspective of the regional innovation system, this study constructs an analytical framework for the influence of government R&D funding on regional innovation quality and uses 283 Chinese cities as research samples to empirically test the influence of government R&D funding methods such as subsidies and tax preferences on regional innovation quality by the spatial Durbin model. According to the study, China’s regional innovation quality has a positive spatial correlation. Subsidies can improve regional innovation quality, which is mainly (...) realized by increasing the input of innovation resources from local direct innovation subjects, attracting the inflow of innovation resources from neighboring areas, and increasing the innovation support from local indirect innovation subjects. Besides, spatial competition for subsidies makes it beneficial to improve the regional innovation quality in neighboring regions, while the promotion effect of tax preferences is not significant. When considering the heterogeneity of the city location and administrative hierarchy, it shows that the government R&D funding cannot improve the innovation quality of the Eastern cities and higher-administrative-hierarchy cities, while it can improve that of the Middle and Western cities and general-administrative-hierarchy cities. Furthermore, government R&D funding widens the gap of regional innovation quality, which may be related to the existing “insufficient intervention” and “excessive intervention” of government R&D funding. This study provides insights into the implementation of R&D funding by the government to promote the development of regional innovation quality. (shrink)

Objective: Cognitive impairment is a common neurological complication in patients with end-stage renal disease undergoing maintenance hemodialysis. Brain network analysis based on graph theory is a promising tool for studying CI. Therefore, the purpose of this study was to analyze the changes of functional brain networks in patients on MHD with and without CI by using graph theory and further explore the underlying neuropathological mechanism of CI in these patients.Methods: A total of 39 patients on MHD and 25 healthy controls (...) matched for age, sex, and years of education were enrolled in the study. Resting-state functional magnetic resonance imaging and T1-weighted high-resolution anatomical data were obtained, and functional brain networks for each subject were constructed. The brain network parameters at the global and regional levels were calculated, and a one-way analysis of covariance was used to compare the differences across the three groups. The associations between the changed graph-theory parameters and cognitive function scores in patients on MHD were evaluated using Spearman correlation analysis.Results: Compared with HCs, the global parameters [sigma, gamma, and local efficiency ] in both patient groups decreased significantly. The clustering coefficient in patients with CI was significantly lower than that in the other two groups. The regional parameters were significantly lower in the right superior frontal gyrus, dorsolateral and gyrus rectus of patients with CI than those of patients without CI; however the nodal local efficiency in the left amygdala was significantly increased. The global Cp and regional parameters in the three brain regions were significantly correlated with the cognitive function scores.Conclusion: This study confirmed that the topology of the functional brain network was disrupted in patients on MHD with and without CI and the disruption of brain network was more severe in patients with CI. The abnormal brain network parameters are closely related to cognitive function in patients on MHD. (shrink)

ABSTRACT We show that there is a polynomial over the rational number field corresponding to each propositional formula in a given many-valued logic. To decide whether a propositional formula can be deduced from a finite set of such formulas (deduction problem), we only need to decide whether a polynomial vanishes on an algebraic variety. By using Wu's method, an algorithm for this problem is presented.

EDITOR’S ABSTRACTIn this article, Huang provides a historical account of the way intellectuals have conceptualized democracy, representative assemblies, and political parties from the end of the Qing dynasty to the beginning of the Republican period. He outlines thirteen items that characterize Chinese democratic thought during this period, before tracing the historical origins of each.

The protection of cultural relics has always been an important issue in the field of museums and archaeology. With the development of Internet of Things technology, the security system of the museum is more intelligent and integrated. In order for the museum display system to keep up with the intelligent age, this article mainly studies the research and realization of the museum showcase system based on the Internet of Things technology in a smart environment. Before the start of the experiment, (...) we developed the overall design of the system, including three functional modules: temperature module, illumination module, and monitoring module. The experiment is done mainly for system testing. The performance test of the sensor module needs to sample the temperature and humidity sensor to verify the accuracy of the temperature and humidity signal collected in the instrument circuit. The light information collection test uses the ADC sampling inside the CC2530 to obtain the required data and judges whether these temperature, humidity, and light intensity values exceed the preset values. The serial port needs to be initialized to carry out data communication and transmission normally. After the receiving end finishes receiving, the sending end will clear the data buffer to prepare for the next data transmission. The experimental data show that the error between the predicted value and measured value of the temperature system is about 3°C, which is within the allowable error range of the experiment. The results show that the system has perfect functions, is safe and reliable, meets the expected requirements, and has good practicability. (shrink)

The aerial manipulator is a complex system with high coupling and instability. The motion of the robotic arm will affect the self-stabilizing accuracy of the unmanned aerial vehicles. To enhance the stability of the aerial manipulator, a composite controller combining conventional proportion integration differentiation control, fuzzy theory, and neural network algorithm is proposed. By blurring the attitude error signal of UAV as the input of the neural network, the anti-interference ability and stability of UAV is improved. At the same time, (...) a neural network model identifier based on Maxout activation function is built to realize accurate recognition of the controlled model. The simulation results show that, compared with the conventional PID controller, the composite controller combined with fuzzy neural network can improve the anti-interference ability and stability of UAV greatly. (shrink)

The original innovation talents and their achievements promote the development of natural science and are regarded as a symbol of the national comprehensive power. This study explores the process that causes original innovation talents’ personality, uses fuzzy-set qualitative comparative analysis, and explores the linkage between configurations made up of early growth experiences and personality. We took Nobel Prize winners as samples and discovered that high responsibility was inspired by high family democracy driving, high family size driving, high family function driving, (...) and high teaching democracy driving; high extroversion was inspired by high family size driving, high family democracy driving, and high family status driving; high openness was inspired by high family status driving, high family democracy driving, high family size driving, both high open teaching and educational level driving, as well as high peer support driving; high or non-high family status brought high extroversion or openness; non-high teacher accomplishments and teacher-student relationships produced high openness; non-high extroversion came with non-high teacher-student relationship. We proposed strategies for strengthening the positive effects or avoiding the negative effects of early growing-up experiences on personality. (shrink)