This paper argues that current pragmatic theories fail to describe common ground in its complexity because they usually retain a communication-as-transfer-between-minds view of language, and disregard the fact that disagreement and egocentrism of speaker-hearers are as fundamental parts of communication as agreement and cooperation. On the other hand, current cognitive research has overestimated the egocentric behavior of the dyads and argued for the dynamic emergent property of common ground while devaluing the overall significance of cooperation in the process of verbal (...) communication. The paper attempts to eliminate this conflict and proposes to combine the two views into an integrated concept of common ground, in which both core common ground and emergent common ground converge to construct a dialectical socio-cultural background for communication.Both cognitive and pragmatic considerations are central to this issue. While attention explains why emergent property unfolds, intention explains why presumed shared knowledge is needed. Based on this, common ground is perceived as an effort to converge the mental representation of shared knowledge present as memory that we can activate, shared knowledge that we can seek, and rapport, as well as knowledge that we can create in the communicative process. The socio-cognitive approach emphasizes that common ground is a dynamic construct that is mutually constructed by interlocutors throughout the communicative process. The core and emergent components join in the construction of common ground in all stages, although they may contribute to the construction process in different ways, to different extents, and in different phases of the communicative process. (shrink)

This paper argues that current pragmatic theories fail to describe common ground in its complexity because they usually retain a communication-as-transfer-between-minds view of language, and disregard the fact that disagreement and egocentrism of speaker-hearers are as fundamental parts of communication as agreement and cooperation. On the other hand, current cognitive research has overestimated the egocentric behavior of the dyads and argued for the dynamic emergent property of common ground while devaluing the overall significance of cooperation in the process of verbal (...) communication. The paper attempts to eliminate this conflict and proposes to combine the two views into an integrated concept of common ground, in which both core common ground and emergent common ground converge to construct a dialectical socio-cultural background for communication.Both cognitive and pragmatic considerations are central to this issue. While attention explains why emergent property unfolds, intention explains why presumed shared knowledge is needed. Based on this, common ground is perceived as an effort to converge the mental representation of shared knowledge present as memory that we can activate, shared knowledge that we can seek, and rapport, as well as knowledge that we can create in the communicative process. The socio-cognitive approach emphasizes that common ground is a dynamic construct that is mutually constructed by interlocutors throughout the communicative process. The core and emergent components join in the construction of common ground in all stages, although they may contribute to the construction process in different ways, to different extents, and in different phases of the communicative process. (shrink)

Socioeconomic status refers to the social position or class according to their material and non-material social resources. We conducted a study with 60 college students to explore whether SES affects past self-evaluation and used event-related potentials in a self-reference task that required participants to judge whether the trait adjectives describing themselves 5 years ago were appropriate for them. Behavioral data showed that individuals’ positive past self-evaluations were significantly higher than individuals’ negative past self-evaluations, regardless of high or low SES. Individuals (...) with high SES had significantly higher positive past self-evaluations than those with low SES. ERP data showed that in the low SES group, negative adjectives elicited a marginally greater N400 amplitude than positive adjectives; in the high SES group, negative adjectives elicited a greater late positive potential amplitude than positive adjectives. N400 is an index of the accessibility of semantic processing, and a larger N400 amplitude reflects less fluent semantic processing. LPP is an index of continuous attention during late processing; the larger LPP amplitude is elicited, the more attention resources are invested. Our results indicated that compared with college students with low SES, the past self-evaluations of college students with high SES were more positive; college students with high SES paid more attention to negative adjectives. However, college students with low SES were marginally less fluent in processing negative adjectives. (shrink)

Host‐pathogen arms race is a universal, central aspect of the evolution of life. Most organisms evolved several distinct yet interacting strategies of anti‐pathogen defense including resistance to parasite invasion, innate and adaptive immunity, and programmed cell death (PCD). The PCD is the means of last resort, a suicidal response to infection that is activated when resistance and immunity fail. An infected cell faces a decision between active defense and altruistic suicide or dormancy induction, depending on whether immunity is “deemed” capable (...) of preventing parasite reproduction and consequent infection of other cells. In bacteria and archaea, immunity genes typically colocalize with PCD modules, such as toxins‐antitoxins, suggestive of immunity‐PCD coupling, likely mediated by shared proteins that sense damage and “predict” the outcome of infections. In type VI CRISPR‐Cas systems, the same enzyme that inactivates the target RNA might execute cell suicide, in a case of ultimate integration of immunity and PCD. (shrink)

The objective of this study is to propose a new operation method based on the universal grey number to overcome the shortcomings of typical interval operation in solving system fault trees. First, the failure probability ranges of the bottom events are described according to the conversion rules between the interval number and universal grey number. A more accurate system reliability calculation is then obtained based on the logical relationship between the AND gates and OR gates of a fault tree and (...) universal grey number arithmetic. Then, considering an aircraft landing gear retraction system as an example, the failure probability range of the top event is obtained through universal grey operation. Next, the reliability of the aircraft landing gear retraction system is evaluated despite insufficient statistical information describing failures. The example demonstrates that the proposed method provides many advantages in resolving the system reliability problem despite poor information, yielding benefits for the function of the interval operation, and overcoming the drawback of solution interval enlargement under different orders of interval operation. (shrink)

Using the promulgation of Green Credit Guidelines in China as the research setting, this paper exploits a quasi-natural experiment to examine the impact of green credit policy on the stock price crash risk of heavy-polluting firms. The results show that green credit policy significantly increases the risk of stock price crash of heavy-polluting firms. Such impact is transmitted through increased financial constraints and reduced information transparency. In addition, we find that the impact of green credit policy on the stock price (...) crash risk is more pronounced in firms with weak external governance and a small size. Our findings provide policy implications for mitigating corporate risks and promoting corporate sustainability. (shrink)

In the course of consumer behavior, it is necessary to study the relationship between the characteristics of psychological activities and the laws of behavior when consumers acquire and use products or services. With the development of the Internet and mobile terminals, electronic commerce has become an important form of consumption for people. In order to conduct experiential education in E-commerce combined with consumer behavior, courses to understand consumer satisfaction. From the perspective of E-commerce companies, this study proposes to use artificial (...) intelligence image recognition technology to recognize and analyze consumer facial expressions. First, it analyzes the way of human–computer interaction in the context of E-commerce and obtains consumer satisfaction with the product through HCI technology. Then, a deep neural network is used to predict the psychological behavior and consumer psychology of consumers to realize personalized product recommendations. In the course education of consumer behavior, it helps to understand consumer satisfaction and make a reasonable design. The experimental results show that consumers are highly satisfied with the products recommended by the system, and the degree of sanctification reaches 93.2%. It is found that the DNN model can learn consumer behavior rules during evaluation, and its prediction effect is increased by 10% compared with the traditional model, which confirms the effectiveness of the recommendation system under the DNN model. This study provides a reference for consumer psychological behavior analysis based on HCI in the context of AI, which is of great significance to help understand consumer satisfaction in consumer behavior education in the context of E-commerce. (shrink)

Brittleness index, usually calculated by compressional and shear wave velocities, is an important parameter used to optimize the sweet pots of shale oil. The empirical relationships or artificial intelligence networks can predict sonic logs based on conventional logging data, but the accuracy is limited by the formation types and properties, such as shale sandstone interbedded. Therefore, we propose a hybrid CNN-LSTM deep learning model that combines convolutional neural network and long short-term memory for the prediction of the compressional and shear (...) travel times. The new model can extract nonlinear features as well as fluctuating trends of log response features with depth, which is different from most machine learning methods that only consider extracting spatial features between logs or only consider extracting time-series features of log datasets.We conclude that the new CNN-LSTM network has the highest prediction accuracy and advantages in predicting curve mutation points compared with other machine learning models. We apply the predicted compressional and shear sonic times for evaluating brittleness to reduce the risk of exploration in shale oil reservoirs. (shrink)

More and more schools begin to design simulation technology based on virtual imaging technology and virtual reality in their course contents. In particular, among these technical courses, there is a need to first strengthen the Film and Television Production education in higher institutions. This article aims to study the impact of VRT, VR, and Internet of things technology on FTP courses and audience psychology in higher institutions under the era of intelligent multimedia. How to use emerging VR technology to promote (...) the psychological wellbeing of students or patients has become a new research direction, the exploration of which has a far-reaching significance for the applications of the related technologies. First, the principle and applications of VR and IoT technology are described. Thereon, the deep learning -based training model is used to analyze the postproduction of VR-based Sand Table game, and the function and effect of the designed game model are discussed. Subsequently, VR-based Sand Play Therapy is applied to mentally ill patients to obtain its therapeutic effect. The results show that the designed VR-based Sand Table game model can be used to treat mentally ill patients and alleviate their negative psychological states. Meanwhile, the Test Anxiety Scale scores prove the significant therapeutic effect of the designed game model on the mental problems of patients. Therefore, VR-based psychological SPT can be applied in the stress relief of students and the treatment of mentally ill patients, as well as alleviate their mental health problems. This research provides a new direction and some theoretical support for the application field of VR technology. (shrink)

This study combines the discovery methods and training of innovative talents, China’s requirements for improving talent training capabilities, and analyses the relationship between the number of professional enrollments in colleges and universities and the demand for skills in specific places. The research learns the characteristics and training models of innovative talents, deep learning, neural networks, and related concepts of the seasonal difference Autoregressive Moving Average Model. These concepts are used to propose seasonal autoregressive integrated moving average back propagation. Firstly, the (...) SARIMA-BP artificially sets the weight parameter values and analyzes the model’s convergence speed, superiority, and versatility. Then, particle swarm optimization algorithm is used to pre-process the model and test its independence. The accuracy of the model is checked to ensure its proper performance. Secondly, the model analyzes and predicts the relationship between the number of professional enrollments of 10 colleges and universities in a specific place and the talent demand of local related enterprises. Moreover, the established model is optimized and tested by wavelet denoising. Independent testing is done to ensure the best possible performance of the model. Finally, the weight value will not significantly affect the model’s versatility obtained by experiments. The prediction results of professional settings and corporate needs reveal that: there is a moderate correlation between professional locations and corporate needs; colleges and universities should train professional talents for local enterprises and eliminate the practical education concepts. (shrink)

This study aims to explore new educational strategies suitable for the mental health education of college students. Big data and artificial intelligence are combined to evaluate the mental health education of college students in sports majors. First, the research status on the mental health education of college students is introduced. The internet of things on mental health education, a structure based on big data and convolutional neural network, is constructed. Next, the survey design and questionnaire survey are carried out. Finally, (...) the questionnaire data are analyzed and compared with the mental health status under traditional education. The results show that the CNN model has good accuracy and ability to distinguish symptoms, so it can be applied to the existing psychological work in colleges. In the symptom comparison survey, under the traditional education and big data network, the number of college students with mild mental health problems is found to be 158 and 170, respectively. It indicates that the number of college students with moderate mental health problems decreases significantly. In the comparative investigation of the severity of mental problems, the number of students with normal mental health, subhealth, and serious mental health problems under the background of traditional mental health education is 125, 56, and 5, respectively. The mental health status of college students under the influence of big data networks on mental health education is better than that of traditional mental health education. There are 140 students with normal mental health, a year-on-year increase of 16.7%. In the comparative survey of specific mental disorders, students with obsessive-compulsive symptoms under traditional mental health education account for 22.0% of the total sample, having the largest proportion. In the subhealth psychological group under the big data network on mental health education, the number of hostile students decreases by 7, which is the psychological factor with the most obvious improvement. Hence, the proposed path of mental health education is feasible. (shrink)

The study expects to find a better way to improve the teaching quality of the education of college students' outlook on life, based on the theory of educational psychology. First, the relevant theories of positive psychology are introduced and expounded, and the importance of the education of college students' outlook on life is analyzed. Second, the current situations of college students' outlook on life and the education of their outlook on life are investigated through a questionnaire survey, and the problems (...) presented in the questionnaire are analyzed. Then, the correlation between positive psychology and the education of college students' outlook on life is explored, and their mutual connection is analyzed. The results are as follows: 77.4% of the college students have periodical aims and work hard for them; 80.8% of the students think that the realization of life goals rely on hard work, accounting for the largest proportion; when they encounter setbacks, more than 80% of the students choose to work hard to overcome them; 69.2% students think that their outlook on life comes from self-learning and exploration. According to college students' outlook on life in China and other countries, there are many problems in the education of college students' outlook on life, and the teaching quality of the education of college students' outlook on life is backward. The combination of positive psychology and college students' education of college students' outlook on life under the theory of educational psychology provides new ideas and ways for college students' education of college students' outlook on life. The conclusion of this study promotes the innovation of the education of college students' outlook on life. (shrink)

This study aims to explore the current situation and strategy formulation of sports psychology teaching in colleges and universities following adaptive learning and deep learning under information education. The informatization in physical education, teaching methods, and teaching processes make psychological education more scientific and efficient. First, the relevant theories of adaptive learning and deep learning are introduced, and an adaptive learning analysis model is implemented. Second, based on the deep learning automatic encoder, college students’ sports psychology is investigated and the (...) test results are predicted. Finally, the current situation and development strategy of physical education in colleges and universities are analyzed. The results show that when the learning rate is 1, 0.1, and 0.01, there is no significant change in the analysis factors of recall, ndcg, item_coverage, and sps. When the learning rate is 1, their analysis factors change obviously, and it is calculated that the optimal learning rate of the model is 1. And the difficulty of the recommended test questions by using the sports psychology teaching method based on adaptive learning and deep learning is relatively stable. The test questions include various language points of sports psychology. Compared with others methods, adaptive learning and deep learning can provide comprehensive test questions for sports psychology teaching. This study provides technical support for the reform of sports psychology teaching in colleges and universities and contributes to optimizing the information-based teaching mode. (shrink)

The artificial neural network is employed to study children’s psychological emotion recognition to fully reflect the psychological status of preschool children and promote the healthy growth of preschool children. Specifically, the ANN model is used to construct the human physiological signal measurement platform and emotion recognition platform to measure the human physiological signals in different psychological and emotional states. Finally, the parameter values are analyzed on the emotion recognition platform to identify the children’s psychological and emotional states accurately. The experimental (...) results demonstrate that the recognition ability of children aged 4–6 to recognize the three basic emotions of happiness, calm, and fear increases with age. Besides, there are significant age differences in children’s recognition of happiness, calm, and fear. In addition, the effect of 4-year-old children on the theory of mind tasks is less than that of 5- to 6-year-old children, which may be related to more complex cognitive processes. Preschool children are experiencing a stage of rapid emotional development. If children cannot be guided to reasonably identify and deal with emotions at this stage, their education level and social ability development will be significantly affected. Therefore, this study has significant reference value for preschool children’s emotional recognition and guidance and can promote children’s emotional processing and mental health. (shrink)

Globalization and informatization are reshaping human life and social behaviors. The purpose is to explore the worldwide strategies to cultivate international talents with a global vision. As a global language with the largest population, English, and especially its learning effect, have always been the major concerns of scholars and educators. This work innovatively studies the combination of immersion-based English teaching with virtual reality technology. Then, based on the experimental design mode, 106 students from a Chinese school were selected for a (...) quasi-experimental study for 16 weeks. The collected data were analyzed by computer statistical software, and hypotheses are verified. The results showed that there is a significantly positive correlation between VR and immersion-based language teaching. There is a significantly positive correlation between immersion-based language teaching and academic achievement, and VR is positively correlated with learning outcome. Compared with other state-of-art research methods, this work modifies the students’ oral test through the analysis and comparison with the system database, and the students’ learning effect is greatly improved. Finally, some suggestions are put forward according to the research results to provide an experimental reference for English teachers and future linguistics teaching. (shrink)

Educational psychology focuses on the laws of change in the knowledge, skills, and individual psychology of the educatees in the process of education and teaching. Writing teaching is a key and difficult point in literature teaching. Nowadays, it is common for students to be afraid and tired of writing in school literature education. In view of these problems, the present work optimizes the teaching mode of writing from the perspective of reconstructing the writing subject. Through literature research and interdisciplinary analysis, (...) a questionnaire is designed to analyze the literary situation and the reconstruction of writing subjects in literary education. The questionnaire is aimed at three aspects, namely the hidden educational effect of teachers’ personality charm, the influencing factors of students’ psychology and students’ learning effect, and the influencing factors of psychology of the communication between teachers and students and teachers’ teaching effect. Then, the changes of students’ performance in literary class in these three aspects before and after using the teaching strategy of writing subject reconstruction are analyzed. Finally, the changes of students’ grades in the literary course are investigated. In this experiment, a total of 400 questionnaires were distributed, and a total of 389 questionnaires were collected. The survey results show that the number of students who feel the classroom atmosphere is active increases by 10%, the number of students who listen carefully and take notes increases by 7%, and 45% of students have improved their grades. Besides, after the implementation of the teaching strategy, most students change their attitude to the literature course, become more active, and significantly improve their motivation for learning. This study has a certain reference value for the analysis of literary situations and the reconstruction of writing subjects in literary education from the perspective of educational psychology. (shrink)

With the rapid emergence of the technology of deep learning, it was successfully used in different fields such as the aquatic product. New opportunities in addition to challenges can be created according to this change for helping data processing in the smart fish farm. This study focuses on deep learning applications and how to support different activities in aquatic like identification of the fish, species classification, feeding decision, behavior analysis, estimation size, and prediction of water quality. Power and performance of (...) computing with the analyzed given data are applied in the proposed DL method within fish farming. Results of the proposed method show the significance of contributions in deep learning and how automatic features are extracted. Still, there is a big challenge of using deep learning in an era of artificial intelligence. Training of the proposed method used a large number of labeled images got from the Fish4Knowledge dataset. The proposed method based on suitable feature extracted from the fish achieved good results in terms of recognition rate and accuracy. (shrink)

Brittleness index, usually calculated by P- and S-wave velocities, is an important parameter used to optimize the sweet spots of shale oil. Empirical relationships or artificial intelligence networks can predict sonic logs based on conventional logging data, but accuracy is limited by the formation types and properties, such as shale sandstone interbeds. Therefore, we propose a hybrid convolutional neural network long short-term memory deep learning model for the prediction of compressional and shear traveltimes. The new model can extract nonlinear features (...) as well as fluctuating trends of log response features with depth, which is different from most machine learning methods that only consider extracting spatial features between logs or only time-series features of log data sets. We conclude that the new CNN-LSTM network has the highest prediction accuracy and advantages in predicting curve mutation points compared with other machine learning models. We apply the predicted compressional and shear sonic times for evaluating brittleness to reduce the risk of exploration in shale oil reservoirs. (shrink)

Accumulating evidence has shown that win-win is necessary for both individuals and the society. This research, including two studies, aimed to develop and validate a measurement of the win-win scale. In the first study, we screened the items by item analysis and extracted common factors using exploratory factor analysis, thus determining a total of 25 items in the initial scale consisted of five dimensions including integrity, advancement, altruism, harmoniousness, and coordination. In the second study, we used first- and second-order confirmatory (...) factor analysis to test the scale’s construct validity. The results indicated a good fit between the five-factor model and the data. Based on our results, we have formed a win-win scale by keeping 16 items from the original project pool. (shrink)

Using Shanghai Tennis Masters as an example, this study seeks to explore the psychic income associated with major sports events hosting and whether the psychic income would predict the attitudes of local residents toward events hosting. In addition, the moderating effect of sport involvement on the relationship between psychic income and attitude is also tested. In this study, a questionnaire survey is adopted. The structured questionnaire was developed based on 4 parts, including the demographics of the residents, involvement in the (...) sport event, psychic income from the sport event, and their attitudes toward the sports event, there were 47 items in total. Data were collected from the local residents of Shanghai, as a result, 1,302 valid questionnaires were collected. A series of statistical analyses were conducted by using SPSS25.0 and AMOS 24.0 to examine the reliability and validity of the scales and to test the hypotheses. The results showed that the event has brought a significant level of psychic income to the local community, and the perceived psychic income would predict the attitudes of the residents toward the event hosting. The moderating effect of sports involvement on the relationship between psychic income and attitude is also confirmed. (shrink)

: The study of German Begriffsgeschichte by scholars such as Koselleck focuses on historiography, but its basic hypotheses are highly philosophical. One of its tasks is to explore modernity from the perspective of language, hence can be understood as the “linguistic approach” in the study of modernity. As for the origin of the theory, the conceptual evolution of Verzeitlichung, Demokratisierung, Politisierung, and Ideologisierbarkeit proposed by Koselleck was not only largely affected by Gadamer’s hermeneutics and Heidegger’s existential phenomenology but also deeply (...) influenced by Carl Schmitt’s political philosophy. In Koselleck’s view, conceptual upheaval in the revolutionary era from 1750 to 1850 was, essentially, a semantic struggle in which old and new forces competed fiercely. (shrink)

The purpose is to strengthen the life education of contemporary college students and give better play to the vital role of life education in preventing college students’ mental diseases. Specifically, it discusses the role of dance therapy in College Students’ Life Education. Firstly, based on educational psychology, this manuscript analyzes the relevant theoretical concepts of EP and life education and discusses the importance of life education to contemporary college students. Secondly, following a Questionnaire Survey and using deep learning Convolutional Neural (...) Network and Facial Emotion Recognition, this manuscript reviews and examines the CSLE’s current situation and the DT effect. Research findings are summarized combined with the QS results and scores of 20 subjects before and after five activities in 3 months. After DT intervention, the positive dimensions of college students’ life values have improved, especially self-development and dedication, and their quality of life is refined. Thus, DT group counseling proves the positive role of DT in CSLE. After DT intervention, 96.5% of the members think DT is effective. Therefore, EP-based DT is more effective and scientific in CSLE. The research findings provide a DT-based teaching concept for CSLE, explore the feasibility and effectiveness of life education, and enrich the DT scheme of CSLE. The research provides a practical reference for further applying DT in college students’ psychological education. (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)

The quality of Innovation and Entrepreneurship Education in higher institutions is closely related to the degree to which the undergraduates absorb relevant innovation and entrepreneurship knowledge and their entrepreneurial motivation. Thus, an effective Evaluation of Educational Quality is essential. In particular, fault tree analysis, a common EEQ approach, has some disadvantages, such as fault data reliance and insufficient uncertainties handleability. Thereupon, this article first puts forward a theoretical model based on the deep learning method to analyze the factors of IEE (...) quality; consequently, based on the traditional FTA, fuzzy fault tree analysis is proposed to evaluate the reliability of IEE classroom teaching for college teachers and students. Finally, based on the top event of entrepreneurial teaching failure, the hyper-ellipsoid model is implemented to restrict the interval probability of basic events and describe the deviation of uncertain events. Furthermore, the model accuracy is verified by a questionnaire survey, based upon which the factors of IEE quality are analyzed. The results show that the designed QS has good reliability, validity, and fitness; the path coefficients of cooperative ability to critical thinking and innovative thinking are 0.9 and 0.66, respectively, indicating that the students’ cooperative ability plays a vital role in the classroom teaching. By calculation, the probability of “teaching failure” in entrepreneurial classroom teaching is 0.395, 3, 0.462, and 5. To sum up, the proposed method can effectively and quantitatively evaluate the quality of IEE in higher institutions, thus providing a certain basis for formulating relevant improvement strategies. The purpose is to provide important technical support for improving the IEE quality. (shrink)

The study of German Begriffsgeschichte by scholars such as Koselleck focuses on historiography, but its basic hypotheses are highly philosophical. One of its tasks is to explore modernity from the perspective of language, hence can be understood as the “linguistic approach” in the study of modernity. As for the origin of the theory, the conceptual evolution of Verzeitlichung, Demokratisierung, Politisierung, and Ideologisierbarkeit proposed by Koselleck was not only largely affected by Gadamer’s hermeneutics and Heidegger’s existential phenomenology but also deeply influenced (...) by Carl Schmitt’s political philosophy. In Koselleck’s view, conceptual upheaval in the revolutionary era from 1750 to 1850 was, essentially, a semantic struggle in which old and new forces competed fiercely. (shrink)

The Lower Silurian shale-gas formation in the south of Sichuan Basin represents strong VTI feature. Successful characterization of shale-gas formation requires handling the great influence of anisotropy in the seismic wave propagation. Seismic AVO inversion for VTI media using PP-waves only is a difficult issue because more than three parameters need to be estimated and such an inverse problem is highly ill-posed. We have applied an AVO inversion method for VTI media based on a modified approximation of the PP-wave reflection (...) coefficient. This approximation consists of only three model parameters: the acoustic impedance, shear modulus proportional to the anellipticity parameter, and the approximated horizontal P-wave velocity, which can be well-inverted and have great interpretation capability in shale-gas reservoir characterization. A statistical-rock-physics method was then applied to the inverted attributes for quantitative interpretation of shale-gas reservoir. Markov random field is combined with Bayesian rule to improve the continuity and accuracy of the interpretation results. Shales can be successfully discriminated from surrounding formations by using the attribute pair A-C, and the organic-rich gas-bearing shale can be successfully identified by using the attribute pair C-B. Comparison between the prediction results and well logs demonstrates the feasibility of the inversion and quantitative interpretation approaches. (shrink)

Associated credit risk is a kind of credit risk among the associated credit entities formed by credit-related entities. Focusing on this hot topic of associated credit risk and the relevant contagion and considering the latent entities and their incubatory period, this paper builds an infectious dynamic model to describe the associated credit risk contagion of associated credit entities based on the mean-field theory of complex networks. Firstly, this paper analyzes the stable state of the associated credit risk contagion in the (...) associated entity network, considering the latent entities and their incubatory period. Secondly, from the perspective of complex network and considering the incubatory period, a SHIS model is built to reveal how the incubatory period influences associated credit risk contagion. Finally, the sensitivity of some parameters is analyzed in the Barabási–Albert scale-free network. The results show the following: the contagion threshold of associated credit risk is related to the incubatory period of latent entities, the recovery rate and infectivity of infected entities, and the newborn rate of credit entities; the infectious rate of infected entities, the mortality rate of credit entities, and the important factors stated in are all significantly correlated with the density of infected entities. (shrink)

The Lower Silurian shale-gas formation in the south of the Sichuan Basin represents a strong transverse isotropy with vertical axis of symmetry feature. Successful characterization of shale-gas formation requires handling the great influence of anisotropy in the seismic wave propagation. Seismic amplitude variation with offset inversion for VTI media using PP-waves only is a difficult issue because more than three parameters need to be estimated and such an inverse problem is highly ill posed. We have applied an AVO inversion method (...) for VTI media based on a modified approximation of the PP-wave reflection coefficient. This approximation consists of only three model parameters: the acoustic impedance, shear modulus proportional to the anellipticity parameter, and the approximated horizontal P-wave velocity, which can be well-inverted and have great interpretation capability in shale-gas reservoir characterization. A statistical-rock-physics method was then applied to the inverted attributes for quantitative interpretation of the shale-gas reservoir. A Markov random field is combined with Bayesian rule to improve the continuity and accuracy of the interpretation results. Shales can be successfully discriminated from surrounding formations by using the attribute pair [Formula: see text]-[Formula: see text], and the organic-rich gas-bearing shale can be successfully identified by using the attribute pair [Formula: see text]-[Formula: see text]. Comparison between the prediction results and well logs demonstrates the feasibility of the inversion and quantitative interpretation approaches. (shrink)

As the first stage of the formation of a collaborative new product innovation team, member selection is crucial for the effective operation of the CNPI team and the achievement of new product innovation goals. Considering comprehensively the individual and collaborative attributions, the individual knowledge competence, knowledge complementarity, and collaborative performance among candidates are chosen as the criteria to select CNPI team members in this paper. Moreover, using the fuzzy set and social network analysis method, the quantitative methods of the above (...) criteria are proposed correspondingly. Then, by integrating the above criteria, a novel multiobjective decision model for member selection of the CNPI team is built from the view of individual and collaborative attributions. Since the proposed model is NP-hard, a double-population adaptive genetic algorithm is further developed to solve it. Finally, a real case is provided to illustrate the application and effectiveness of the proposed model and method in this paper. (shrink)