Drawing on social exchange theory, we examine the conditions under which employees’ good intentions motivate them to engage in unethical pro-organizational behavior (UPB) and the psychological mechanism behind this behavioral decision. Findings from a time-lagged field study and a scenario study indicate (1) an interactive effect between perceived organizational support and employee performance on UPB; (2) that low performers who perceive high levels of organizational support are more likely to engage in UPB; and (3) that feelings of indebtedness to the (...) organization mediate the interactive effect on UPB. Therefore, the paper highlights the importance of conditional factors in motivating UPB by combining employee ‘good intentions’ and ‘disadvantageous situations’ to understand the UPB decision process. The paper concludes with theoretical and practical implications. (shrink)

Mandarin speakers, like most other language speakers around the world, use spatial terms to talk about time. However, the direction of their mental temporal representation along the front-back axis remains controversial because they use the spatial term “front” to refer to both earlier times and the future. Although the linguistic distinction between time- and ego-reference-point spatiotemporal metaphors in Mandarin suggests a promising clarification of the above controversy, there is little empirical evidence verifying this distinction. In this study, Mandarin speakers’ time- (...) and ego-reference-point temporal representations on three axes were separately examined through two tasks. In a time-reference-point task, Mandarin speakers judged whether the time point of the second picture was earlier or later than the time point of the first picture, while in an ego-reference-point task, they judged whether an event or phase had happened in the past or would happen in the future. The results indicate that Mandarin speakers construe an earlier-times-in-front-of-later-times temporal sequence and adopt the front-to-the-future orientation. (shrink)

The COVID-19 pandemic has caused tremendous loss starting from early this year. This article aims to investigate the change of anxiety severity and prevalence among non-graduating undergraduate students in the new semester of online learning during COVID-19 in China and also to evaluate a machine learning model based on the XGBoost model. A total of 1172 non-graduating undergraduate students aged between 18 and 22 from 34 provincial-level administrative units and 260 cities in China were enrolled onto this study and asked (...) to fill in a sociodemographic questionnaire and the Self-Rating Anxiety Scale twice, respectively, during February 15 to 17, 2020, before the new semester started, and March 15 to 17, 2020, 1 month after the new semester based on online learning had started. SPSS 22.0 was used to conduct t-test and single factor analysis. XGBoost models were implemented to predict the anxiety level of students 1 month after the start of the new semester. There were 184 and 221 students who met the cut-off of 50 and were screened as positive for anxiety, respectively, in the two investigations. The mean SAS scores in the second test was significantly higher than those in the first test. Significant differences were also found among all males, females, and students majoring in arts and sciences between the two studies. The results also showed students from Hubei province, where most cases of COVID-19 were confirmed, had a higher percentage of participants meeting the cut-off of being anxious. This article applied machine learning to establish XGBoost models to successfully predict the anxiety level and changes of anxiety levels 4 weeks later based on the SAS scores of the students in the first test. It was concluded that, during COVID-19, Chinese non-graduating undergraduate students showed higher anxiety in the new semester based on online learning than before the new semester started. More students from Hubei province had a different level of anxiety than other provinces. Families, universities, and society as a whole should pay attention to the psychological health of non-graduating undergraduate students and take measures accordingly. It also confirmed that the XGBoost model had better prediction accuracy compared to the traditional multiple stepwise regression model on the anxiety status of university students. (shrink)

Coronavirus disease 2019 has not only resulted in immeasurable life and property losses worldwide but has also impacted individuals’ development, especially teenagers. After the COVID-19 pandemic, individual rumination as an important cognitive process should be given more attention because of its close associations with physical and mental health. Previous studies have shown that creativity as an antecedent variable can predict people’s mental health or adaptation. However, few studies have focused on the relationship between creativity and individual cognitive rumination after traumatic (...) events, and the mechanism underlying this relationship remains unclear. By using the Runco Ideational Behavior Scale, the Event Related Rumination Inventory, and the Questionnaire of Adolescent Emotional Resilience, the current study explored the relationship between creativity and intrusive rumination among 1488 Chinese teenagers during the COVID-19 pandemic and analyzed the moderating effect of emotional resilience on the relationship. The results showed that creativity, as assessed by the RIBS, was positively related to teenagers’ intrusive rumination, which implied that a higher level of creative performance could predict more intrusive rumination. Moreover, emotional resilience acted as a moderator in the relationship between creativity and intrusive rumination; the correlation was stronger when emotional resilience was low. These findings provide more evidence of the relationship between creativity and mental health and show the effect of this traumatic event on teenagers. (shrink)

This study aimed to explore the influence the value modularity and a firm’s innovation performance, directly and indirectly, using knowledge management as mediating variable. Moreover, in this study, we used the resource integration ability as a moderator between the relationship value modularity and firm innovation performance. We collected data from the Chinese state-owned and state-controlled high-tech firms from 2011 to 2018. In this study, we used the gray comprehensive evaluation method to test the degree of value modularity, and hierarchical regression (...) analysis is used to analyze the relationship among variables. The outcomes of this study indicate that value modularity and firm innovation performance has inverted U-shaped and significant association. Similarly, results also confirm that knowledge acquisition and knowledge internalization mediate the relationship between value modularity and firm innovation performance. The finding of this research also confirms that resource integration ability negatively affects the relationship between value modularity and firm innovation performance. This paper enriches the research of the value modularity and gives certain inspiration to knowledge management. At the end of this study, we also suggest some significant practical implications. (shrink)

From the end of 2018 in China, the Big-data Driven Price Discrimination (BDPD) of online consumption raised public debate on social media. To study the consumers’ attitude about the BDPD, this study constructed a semantic recognition frame to deconstruct the Affection-Behavior-Cognition (ABC) consumer attitude theory using machine learning models inclusive of the Labeled Latent Dirichlet Allocation (LDA), Long Short-Term Memory (LSTM), and Snow Natural Language Processing (NLP), based on social media comments text dataset. Similar to the questionnaires published results, this (...) article verified that 61% of consumers expressed negative sentiment toward BDPD in general. Differently, on a finer scale, this study further measured the negative sentiments that differ significantly among different topics. The measurement results show that the topics “Regular Customers Priced High” (69%) and “Usage Intention” (67%) occupy the top two places of negative sentiment among consumers, and the topic “Precision Marketing” (42%) is at the bottom. Moreover, semantic recognition results that 49% of consumers’ comments involve multiple topics, indicating that consumers have a pretty clear cognition of the complex status of the BDPD. Importantly, this study found some topics that had not been focused on in previous studies, such as more than 8% of consumers calling for government and legal departments to regulate BDPD behavior, which indicates that quite enough consumers are losing confidence in the self-discipline of the platform enterprises. Another interesting result is that consumers who pursue solutions to the BDPD belong to two mutually exclusive groups: government protection and self-protection. The significance of this study is that it reminds the e-commerce platforms to pay attention to the potential harm for consumers’ psychology while bringing additional profits through the BDPD. Otherwise, the negative consumer attitudes may cause damage to brand image, business reputation, and the sustainable development of the platforms themselves. It also provides the government supervision departments an advanced analysis method reference for more effective administration to protect social fairness. (shrink)

Person reidentification aims to recognize a specific pedestrian from uncrossed surveillance camera views. Most re-id methods perform the retrieval task by comparing the similarity of pedestrian features extracted from deep learning models. Therefore, learning a discriminative feature is critical for person reidentification. Many works supervise the model learning with one or more loss functions to obtain the discriminability of features. Softmax loss is one of the widely used loss functions in re-id. However, traditional softmax loss inherently focuses on the feature (...) separability and fails to consider the compactness of within-class features. To further improve the accuracy of re-id, many efforts are conducted to shrink within-class discrepancy as well as between-class similarity. In this paper, we propose a circle-based ratio loss for person re-identification. Concretely, we normalize the learned features and classification weights to map these vectors in the hypersphere. Then we take the ratio of the maximal intraclass distance and the minimal interclass distance as an objective loss, so the between-class separability and within-class compactness can be optimized simultaneously during the training stage. Finally, with the joint training of an improved softmax loss and the ratio loss, the deep model could mine discriminative pedestrian information and learn robust features for the re-id task. Comprehensive experiments on three re-id benchmark datasets are carried out to illustrate the effectiveness of the proposed method. Specially, 83.12% mAP on Market-1501, 71.66% mAP on DukeMTMC-reID, and 66.26%/63.24% mAP on CUHK03 labeled/detected are achieved, respectively. (shrink)

In a complex network, each edge has different functions on controllability of the whole network. A network may be out of control due to failure or attack of some specific edges. Bridges are a kind of key edges whose removal will disconnect a network and increase connected components. Here, we investigate the effects of removing bridges on controllability of network. Various strategies, including random deletion of edges, deletion based on betweenness centrality, and deletion based on degree of source or target (...) nodes, are used to compare with the effect of removing bridges. It is found that the removing bridges strategy is more efficient on reducing controllability than the other strategies of removing edges for ER networks and scale-free networks. In addition, we also found the controllability robustness under edge attack is related to the average degree of complex networks. Therefore, we propose two optimization strategies based on bridges to improve the controllability robustness of complex networks against attacks. The effectiveness of the proposed strategies is demonstrated by simulation results of some model networks. These results are helpful for people to understand and control spreading processes of epidemic across different paths. (shrink)

In order to highlight the role of music teaching in the teaching of ideological and political courses, this study puts forward research on the integration of music teaching and ideological and political teaching. This study analyzes the promotion and necessity of college music teaching to ideological and political work, constructs a fusion model of college music teaching and ideological and political work, introduces deep learning methods, and weakens the influence of errors in the data of college music teaching and ideological (...) and political work. This study also optimized the integration mode of college music teaching and ideological and political work and realized the model research of college music teaching and ideological and political work. The experimental results show that the resource output amplitude controlled by the deep learning method has the best stability, and there is no large amplitude fluctuation during the experiment. The output amplitude and control time of the fusion resource are guaranteed and the fusion path of music teaching and ideological and political education is clearer. The maximum control time of the fusion resource of this method is 23.55 ms. (shrink)

Mobile English learning has multiple advantages and brings enormous benefits to EFL learners. However, not everyone adopts it, and the determinants of learners’ adoption intention have not yet been investigated fully. This study aimed to better understand learners’ adoption by employing the theory of planned behaviour in conjunction with the influences of technostress and compatibility. Based on existing literature, a research model was proposed and verified with a sample of 409 undergraduates from a Chinese university. The results indicated that in (...) the context of mobile English learning: Individuals with higher adoption intention are more likely to engage in mobile English learning with higher frequency. Practical implications related to mobile English learning were discussed. (shrink)

System security is essential for the operation of the island microgrid. However, the system security is generally threatened due to the presence of physical uncertainties and cyber attacks. In this article, a novel sliding mode load control strategy is proposed for the microgrid to mitigate cyber attacks and physical uncertainties. Firstly, a high-order disturbance observer is designed to estimate the unmeasurable factors in the microgrid. Secondly, a HODO-based sliding mode control strategy is proposed where the estimated value observed by the (...) HODO is applied to the sliding mode surface and control law. It can better guarantee the security of the isolated microgrid. Then, the stability of the HODO-based SMC is demonstrated by Lyapunov stability theory. Finally, simulation results show that the proposed control strategy has excellent control performance. (shrink)

Common spatial pattern is an effective algorithm for extracting electroencephalogram features of motor imagery ; however, CSP mainly aims at multichannel EEG signals, and its effect in extracting EEG features with fewer channels is poor—even worse than before using CSP. To solve the above problem, a new combined feature extraction method has been proposed in this study. For EEG signals from fewer channels, wavelet packet transform, fast ensemble empirical mode decomposition, and local mean decomposition were used to decompose the band-pass (...) filtered EEG into multiple time–frequency components, and the corresponding components were selected according to the frequency characteristics of MI or the correlation coefficient between its time–frequency components and the original EEG signal. Furthermore, phase space reconstruction was performed on the selected components after the three time-frequency decompositions, the maximum Lyapunov index was calculated, and the features were reconstructed; then, CSP projection mapping was used for the reconstructed features. The support vector machine probability output model was trained by the obtained three mappings. Probability outputs by three different support vector machines were then obtained. Finally, the classification of test samples was determined by the fusion of the Dempster–Shafer evidence theory at the decision level. The results showed that the accuracy of the proposed method was 95.71% on data set III of BCI competition II, which was 2.88% higher than the existing methods. On data set IIb of BCI competition IV, the average accuracy was 86.60%, which was 2.3% higher than the existing methods. This study verified the effectiveness of the proposed method and provided an approach for the research and development of the MI-BCI system based on fewer channels. (shrink)

The KNN algorithm is one of the most famous algorithms in machine learning and data mining. It does not preprocess the data before classification, which leads to longer time and more errors. To solve the problems, this paper first proposes a PK-means++ algorithm, which can better ensure the stability of a random experiment. Then, based on it and spherical region division, an improved KNNPK+ is proposed. The algorithm can select the center of the spherical region appropriately and then construct an (...) initial classifier for the training set to improve the accuracy and time of classification. (shrink)

In this paper, we propose to incorporate the local attention in WaveNet-CTC to improve the performance of Tibetan speech recognition in multitask learning. With an increase in task number, such as simultaneous Tibetan speech content recognition, dialect identification, and speaker recognition, the accuracy rate of a single WaveNet-CTC decreases on speech recognition. Inspired by the attention mechanism, we introduce the local attention to automatically tune the weights of feature frames in a window and pay different attention on context information for (...) multitask learning. The experimental results show that our method improves the accuracies of speech recognition for all Tibetan dialects in three-task learning, compared with the baseline model. Furthermore, our method significantly improves the accuracy for low-resource dialect by 5.11% against the specific-dialect model. (shrink)

Based on the existing financial system risk models, a set of time-lag financial system risk models is established considering the influence brought by time-lag factors on the financial risk system, and the dynamical behavior of this system is analyzed by using chaos theory. Through Matlab simulation, the bifurcation diagram and phase diagram of time-lag risk intensity and control intensity are plotted. The analysis shows that this kind of time-lag financial system risk model has complex dynamic behavior, different motion states will (...) appear when different parameter values are selected, and the time-lag risk intensity parameter also has a very strong influence on the system motion. To ensure the operation of the financial system in a stable state, measures with certain delay effects must be taken to control the risk and to choose the appropriate time-lag control intensity, and too much or too little time-lag control intensity is not conducive to the benign operation of the system. (shrink)

The problem of generalizing the power option-pricing model to incorporate more empirical features becomes an urgent and necessary event. A new power option pricing method is designed for the financial market uncertainty that simultaneously involves randomness and fuzziness. The randomness in market uncertainty is modeled by a time-fractional diffusion model, which describes trend memory in underlying asset prices. The fuzziness in market uncertainty is characterized by a triangular interval type-2 fuzzy numbers, which better captures the fuzziness of underlying asset prices. (...) Considering the decision-maker’s subjective judgment, we show the price mean value with the possibility-necessity weight and pessimistic-optimistic index under the type-2 fuzzy environment. We develop the power option pricing model with the time-fractional diffusion model and the triangular interval type-2 fuzzy numbers. Furthermore, the analytic solutions of pricing call power option and put power option are obtained and verified by the variational iterative reconstruction method. Our study shows that power option pricing, which adopts the time-fractional model and the triangular interval type-2 fuzzy numbers, can better capture the trend memory and double fuzziness of the real market. In addition, a numerical example is provided to illustrate that the power option means the value is decreasing with respect to the pessimistic-optimistic index and is fluctuating with respect to the possibility-necessity weight index. (shrink)

As we all know, the Silk Road, as a famous ancient transportation route, was a trade line cross-Eurasian continent in history. Its name was from the delivery of silk. However, no Chinese ancient documents mentioned the name of “Silk Road”. German F. V. Richthofen (1933-1905) firstly used the term “Silk Road” in his book China, published in 1877. Afterwards, the name of “Silk Road” has been accepted universally and used by the world widely. The Silk Road was an ancient business (...) channel, acrossing the middle of China and countries in Central Asia, gradually forming after Qian Zhang visited Western Regions twice, two thousand and one hundred years ago. The north-west land Silk Road started from Chinese ancient Capital Chang’an (now Xi’an), acrossing Central Asia, and reaching ancient Rome in Europe. It was a bridge for communication of politics, economy, and culture between ancient China and the Western. Before 11 Century, the Sino-Western silk trade mainly depended on the land transportation. During Han Dynasty, it was a competition between the Huns and the Hans for occupy the Silk road. The silk as a kind of material culture was a sort of intermediary for making people to know how to get along together.This article attempts to describe the Sino-Western silk trade conditions before and after the two missions of Qian Zhang to Western Regions (Xiyu), including archaeological evidences, kinds of silk and trade scale, transportation routes, trade participants, and so on. (shrink)

Supply chain financing guaranteed by third-party logistics firms is an effective way to solve the financing difficulties of small and medium-sized enterprises. Studies have explored factors that affect the willingness of supply chain financial credit providers under guarantee of 3PL firms. However, whether the scale of 3PL firms will affect the bank’s credit decision has not been studied, as well as the neural processing of credit decisions. To clarify these issues, this study extracted behavioral and event-related potentials data when participants (...) performed a selection task of judging whether to grant credit to guaranteed financing-seeking enterprises according to the large or small scale of the 3PL guaranteeing firms. The behavioral results showed that under the condition of a large-scale 3PL guaranteeing firm, the willingness to provide credit to SMEs was higher than that under the condition of a small-scale 3PL guaranteeing firm. This finding indicates there was credit scale discrimination against 3PL guaranteeing firms in supply chain finance. The ERP results showed that compared with the condition of a large-scale 3PL guaranteeing firm, a greater N2 amplitude was induced under the condition of a small-scale 3PL guaranteeing firm, which indicated that credit decision makers experienced greater perceived risk and more decision-making conflict. In contrast, a larger LPP amplitude was detected under the condition of a large-scale 3PL guaranteeing firm, which indicated that large-scale 3PL guaranteeing firms received more positive comments and more positive emotions from credit decision makers than small-scale 3PL guaranteeing firms. Based on these results, this study reveals the cognition process of credit decision makers regarding the impact of the 3PL guaranteeing firm scale on the willingness to provide credit in supply chain finance and explains the theory of credit scale discrimination from the perspective of decision neuroscience. (shrink)

Positioning accuracy of micropositioning stage in scanning ion conductance microscopy is the key to obtain high-precision scanning model. Most piezoelectric ceramic micromotion platforms are used for that, and hysteresis characteristics are the main reason for the nonlinear characteristics of piezoelectric ceramics and the influence on the control accuracy. In order to solve this problem, backpropagation algorithm based on whale optimization algorithm is used to model the hysteresis, which is directly used as a feedforward controller to compensate the hysteresis effect, and (...) the robust adaptive moving average control method is used for feedback control. The results show that the hysteresis model of backpropagation algorithm based on the whale optimization algorithm can fit the hysteresis curve well, and the maximum fitting error is 0.2050 μm, only 0.256%. By adopting feedforward and feedback, feedforward robust adaptive moving average control algorithm decreases the hysteresis from 17.64% to 2.51%, which enables the output of the piezoelectric ceramic controller to track the expected displacement well and makes it possible to improve the scanning accuracy. (shrink)

This paper explores whether a Student’s choice of major leads to certain personality traits and the reasons for this phenomenon. Specifically, we look at evidence from two Chinese universities, both of which specialize in agricultural studies. Using the Sixteen Personality Factor questionnaire and the Neuroticism Extraversion Openness Five-Factor Inventory questionnaire, we collected data from two groups of students: those who study agriculture-related majors, and those who study non-agriculture-related majors. The surveys all showed no significant change in personality traits during Students’ (...) freshman year. However, after 3 years of university study, significant personality trait changes were noted between seniors in the ARM and NARM groups. Whereas ARM seniors tended to be socially shy and lower in communicative competence, NARM seniors were better at expressing themselves and communicating with others. Although a Student’s choice of profession has an influence on their personality traits, it is not the only factor. The differences between ARM and NARM training models and curricula are also undoubtedly significant. Moreover, the bias against ARM in Chinese society further magnifies the differences in personality traits among students with different majors. (shrink)

Aesthetic education plays an important role in people's education and training. Guided by Marxist aesthetic education view, studying the construction of aesthetic education in the new era is not only an important condition for shaping a sound personality and an inevitable requirement for guiding people's better life in the new era, but also a theoretical basis for guiding the cultivation of innovative talents in the new era, and a realistic need for dealing with the misunderstanding of aesthetic education in the (...) new era. As an important part of socialist cultural construction, aesthetic education can cultivate people's perception, acceptance and creativity of beauty, shape individual's lofty ideals and sentiments by purifying the soul and casting the soul, transform the objective world and beautify the subjective world according to the law of beauty, establish a beautiful world outlook, outlook on life and values, and promote people's quality promotion and all-round development. From the perspective of aesthetic education, we media's own characteristics enable it to become a platform for teachers' teaching and students' learning at the same time, and with the new changes shown by the relationship between the media and the audience, we media can become an effective carrier to enhance college students' aesthetic education, providing us with a good opportunity to effectively enhance college students' aesthetic education. (shrink)

儒家思想向來於以封建禮教為核心的西周文化備加推崇，認為這套思想是平治天下的基本原則，如果世局動盪不安，必然是由於人們棄絕封建禮教之故。 儒家思想代表人物孔子，終其一生的志業就是重振禮教以匡正時局。 墨子出身於庶民階級，卻主張封建禮教本身就是動亂的根源，封建一日不除，天下無一日太平。 雄辯滔滔的墨子，以「兼愛」為武器向儒家陣營發動猛烈攻擊，反覆衝撞層層壁壘，批判封建禮教支持者言行不一、矛盾可笑。 墨家不是只會辯論，他們同樣重視身體力行，墨子提出「非攻」主張，也親自帶領門徒為實踐信念而奔走於國際之間，用行動證明，在那樣的亂世中，墨家的主張確實有其合理性，也深具價值。 拋開冷硬的課文題解，穿過層層的過度解讀， 楊照經典講堂以最貼近歷史真實的讀法， 帶你一次讀懂兩千年前的漢語經典！ 最平易的語言、最扎實的分析 打破時空限制，直接從原典文句汲取千年智慧 提供最立即的知識趣味 楊照全程領讀、解讀，漢語經典完全解碼 台灣新品種文庫版，隨身伴讀.

在連續不斷、無區隔、無裂隙的世界觀中，天地與我並生，萬物與我為一。 周文化的主流，講求階級身分之責任義務、嚴守人我是非之限界秩序。 非主流的莊子卻說，窮盡智識分辨事物其實不智，只是勞神而無功。 如果能夠拋開成心和偏好，立於無彼無此的道之樞紐上看待萬事萬物， 世上的一切就都有了道理，都有了自身之常、自身之用，這就是通達。 楊照讀莊子， 引入傳統中國哲學裡被忽視的邏輯分析， 將前人難以理解的細密哲思一一梳理清晰， 為我們展示出莊子開闊混同的精神世界。 拋開冷硬的課文題解，穿過層層的過度解讀， 楊照經典講堂以最貼近歷史真實的讀法， 帶你一次讀懂兩千年前的漢語經典！ 最平易的語言、最扎實的分析 打破時空限制，直接從原典文句汲取千年智慧 提供最立即的知識趣味 楊照全程領讀、解讀，漢語經典完全解碼 台灣新品種文庫版，隨身伴讀.

Humans can understand thousands of abstract words, even when they do not have clearly perceivable referents. Recent views highlight an important role of social experience in grounding of abstract concepts and sub-kinds of abstract concepts, but empirical work in this area is still in its early stages. In the present study, a picture-word semantic priming paradigm was employed to investigate the contribution effect of social experience that is provided by real-life pictures to social abstract concepts and emotional abstract concepts. Using (...) a lexical decision task, we examined responses to picture-SA word pairs and picture-EA word pairs in social/emotional semantically related and unrelated conditions. All pairs shared either positive or negative valence. The results showed quicker responses to positive SA and EA words that were preceded by related vs. unrelated prime pictures. Specifically, positive SA words were facilitated by the corresponding social scene pictures, whereas positive EA words were facilitated by pictures depict the corresponding facial expressions and gestures. However, such facilitatory effect was not observed in negative picture-SA/EA word conditions. This pattern of results suggests that a facilitatory effect of social experience on abstract concepts varies with different sub-kinds of abstract concepts, that seems to be limited to positive SA concepts. Overall, our findings confirm the crucial role of social experience for abstract concepts and further suggest that not all abstract concepts can benefit from social experience, at least in the semantic priming. (shrink)

With the rapid development of China's economy in recent decades, and the decentralization of the country's economic regulation and legal support, private financing has developed rapidly due to its simple, flexible and unique advantages. Some SMEs can solve it to some extent through private financing. The company's own financing issues have also helped the local financial market's effectiveness. Based on the “Yantai Private Financing Interest Rate Index,” this paper constructs a private financial risk index model from three perspectives of interest (...) rate risk, scale risk and credit risk, and conducts a case simulation analysis of the private financing risk index. The characteristic indicators of the early warning system are screened from the macro, micro and stability dimensions, and subjective and objective adjustment coefficients are set for each indicator from both subjective and objective perspectives. This article takes the Yantai Index as the representative of China's private financing interest rate index. Based on the term structure of Yantai's private lending rate, this paper studies its response to macroeconomic shocks and analyzes the information value it contains. And use the private financing interest rate index to build a financial risk monitoring model. Through the system transformation model, the article finds that there is a significant asymmetry in the response of private lending to macroeconomic shocks. When private lending rates are higher, inflation has a greater effect on interest rates; when private lending rates are lower, monetary policy has a stronger regulatory effect on private lending rates. In the data processing, the principal component analysis method and the Bayesian vector autoregressive model were established. Through the study of this article, it is concluded that the interest rate decreases with the increase of the term, and the risk comparison is performed for the 1-month period, 3-month period, June period, 1-year period, and more than 1-year. The risks in the previous period are greater, and the risks in the March and June periods are relatively small. This model can be used to calculate the comprehensive evaluation value and its fluctuation in the historical risk market and historical equilibrium market, so as to determine the risk range of the comprehensive evaluation value. Thus, the early warning system is verified to be feasible. (shrink)

Post‐transcriptional regulation faces a distinctive challenge in gametes. Transcription is limited when the germ cells enter the division phase due to condensed chromatin, while gene expression during gamete maturation, fertilization, and early cleavage depends on existing mRNA post‐transcriptional coordination. The dynamics of the 3ʹ‐poly(A) tail play crucial roles in defining mRNA fate. The 3ʹ‐poly(A) tail is covered with poly(A)‐binding proteins (PABPs) that help to mediate mRNA metabolism and recent work has shed light on the number and function of germ cell‐specific (...) expressed PABPs. There are two structurally different PABP groups distinguished by their cytoplasmic and nuclear localization. Both lack catalytic activity but are coupled with various roles through their interaction with multifunctional partners during mRNA metabolism. Here, we present a synopsis of PABP function during gametogenesis and early embryogenesis and describe both conventional and current models of the functions and regulation of PABPs, with an emphasis on the physiological significance of how germ cell‐specific PABPs potentially affect human fertility. (shrink)

At present, a series of economic structural changes created by the network economy have brought challenges to the entire economy and society. Traditional social commerce has also suffered severe tests under the background of network economy and global integration, and the rise and development of network commercial activities lack legal constraints. Based on the Big Data technology, in view of the characteristics of data mining services, this paper expands and changes the traditional model and proposes the Big Data alliance data (...) mining service process model. Moreover, this paper uses intelligent decision-making theory and knowledge reasoning methods to construct a fast-responding, service-reusable, and intelligent service model to realize the scalability of data mining services. In addition, this paper constructs system function modules according to the requirements of Internet commercial judicial data mining and verifies the performance of the system constructed in this paper through experimental analysis. The research results show that the system constructed in this paper has certain practical effects. (shrink)

This paper presents an overall view of the Philosophy of Tian-xia, a particular form of neo-universalism developed by its author and very much debated in the last years. The system of Tian-xia, or ‘all-under-heaven’, is a philosophical re-elaboration of an ancient form of Chinese universalism. The world is constituted as a global unity and a basic concept of political philosophy. It aims at a world institution as a way to rethink all problems in the world as problems of the world. (...) Zhao Tingyang has analytically developed this view in some recent publications in Chinese. This article represents the most recent attempt to provide a synthetic view of his philosophy of ‘all-under-heaven’. (shrink)