Urbanization is causing profound changes in ecosystem functions at local and regional scales. The net primary productivity is an important indicator of global change, rapid urbanization and climate change will have a significant impact on NPP, and urban expansion and climate change in different regions have different impacts on NPP, especially in densely populated areas. However, to date, efforts to quantify urban expansion and climate change have been limited, and the impact of long-term continuous changes in NPP has not been (...) well understood. Based on land use data, night light data, NPP data, climate data, and a series of social and economic data, we performed a comprehensive analysis of land use change in terms of type and intensity and explored the pattern of urban expansion and its relationship with NPP and climate change for the period of 2000–2015, taking Zhengzhou, China, as an example. The results show that the major form of land use change was cropland to built-up land during the 2000–2015 period, with a total area of 367.51 km2 converted. The NPP exhibited a generally increasing trend in the study area except for built-up land and water area. The average correlation coefficients between temperature and NPP and precipitation and NPP were 0.267 and 0.020, respectively, indicating that an increase in temperature and precipitation can promote NPP despite significant spatial differences. During the examined period, most expansion areas exhibited an increasing NPP trend, indicating that the influence of urban expansion on NPP is mainly characterized by an evident influence of the expansion area. The study can provide a reference for Zhengzhou and even the world's practical research to improve land use efficiency, increase agricultural productivity and natural carbon sinks, and maintain low-carbon development. (shrink)

This article examines the mediation effect of brand identification and the moderating effect of service quality (SQ) on the effects of corporate social responsibility (CSR) association on service brand performance. A survey of customers of mobile telecommunications services was conducted. The study finds, first, that both CSR and SQ have direct effects on brand identification and customer satisfaction and indirect effects on customer satisfaction (via brand identification) and on service brand loyalty (via customer satisfaction and via "brand identification/customer satisfaction"). Second, (...) SQ enhances the effect of CSR on brand identification. This study contributes to the literature by incorporating three perspectives of service brand performance — CSR association, SQ, and brand identification - into one general framework that stresses (a) the mediating role of brand identification in predicting customer satisfaction and service brand loyalty; and (b) the interactive effect of CSR and SQ in predicting brand identification. (shrink)

In this study, an accurate convergence time of the supertwisting algorithm is proposed to build up a framework for nonaffine nonlinear systems’ finite-time control. The convergence time of the STA is provided by calculating the solution of a differential equation instead of constructing Lyapunov function. Therefore, precise convergence time is presented instead of estimation of the upper bound of the algorithm’s reaching time. Regardless of affine or nonaffine nonlinear systems, supertwisting control provides a general solution based on virtual control law (...) skill ensuring the output of the systems converges to the origin point at exact time. Benchmark tests are simulated to demonstrate the effectiveness and efficiency of the algorithm. (shrink)

As an imitation of the biological nervous systems, neural networks, which have been characterized as powerful learning tools, are employed in a wide range of applications, such as control of complex nonlinear systems, optimization, system identification, and patterns recognition. This article aims to bring a brief review of the state-of-the-art NNs for the complex nonlinear systems by summarizing recent progress of NNs in both theory and practical applications. Specifically, this survey also reviews a number of NN based robot control algorithms, (...) including NN based manipulator control, NN based human-robot interaction, and NN based cognitive control. (shrink)

In situ stress has an important influence on coal reservoir permeability, fracturing, and production capacity. In this paper, fracturing testing, imaging logging, and 3D finite-element simulation were used to study the current in situ stress field of a coal reservoir with a high coal rank. The results indicated that the horizontal stress field within the coal reservoir is controlled by the burial depth, folding, and faulting. The [Formula: see text] and [Formula: see text] values within the coal reservoir are 1–2.5 (...) MPa higher than those within the clastic rocks of the roof and floor. The [Formula: see text]–[Formula: see text] values of the coal reservoir are generally between 2 and 6 MPa and increase with burial depth. When the [Formula: see text]–[Formula: see text] value is less than 5 MPa, production from a single well is high, but when the [Formula: see text]–[Formula: see text] value is greater than 5 MPa, production from a single well is low. In addition, the accumulated water production is high when the [Formula: see text]–[Formula: see text] value is greater than 5 MPa, demonstrating that a higher [Formula: see text]–[Formula: see text] value allows the hydraulic fractures to more easily penetrate the roof and floor of the coal seam. In coal-bed methane development regions with high [Formula: see text]–[Formula: see text] values, repeated fracturing using the small-scale plug removal method — which is a fracturing method that uses a small volume of liquid, small displacement, and low sand concentration — is suggested. (shrink)

In situ stress has an important influence on coal reservoir permeability, fracturing, and production capacity. In this paper, fracturing testing, imaging logging, and 3D finite-element simulation were used to study the current in situ stress field of a coal reservoir with a high coal rank. The results indicated that the horizontal stress field within the coal reservoir is controlled by the burial depth, folding, and faulting. The [Formula: see text] and [Formula: see text] values within the coal reservoir are 1–2.5 (...) MPa higher than those within the clastic rocks of the roof and floor. The [Formula: see text]–[Formula: see text] values of the coal reservoir are generally between 2 and 6 MPa and increase with burial depth. When the [Formula: see text]–[Formula: see text] value is less than 5 MPa, production from a single well is high, but when the [Formula: see text]–[Formula: see text] value is greater than 5 MPa, production from a single well is low. In addition, the accumulated water production is high when the [Formula: see text]–[Formula: see text] value is greater than 5 MPa, demonstrating that a higher [Formula: see text]–[Formula: see text] value allows the hydraulic fractures to more easily penetrate the roof and floor of the coal seam. In coal-bed methane development regions with high [Formula: see text]–[Formula: see text] values, repeated fracturing using the small-scale plug removal method — which is a fracturing method that uses a small volume of liquid, small displacement, and low sand concentration — is suggested. (shrink)

On the basis of PM2.5 data of the national air quality monitoring sites, local population data, and baseline all-cause mortality rate, PM2.5-related health economic benefits of the Air Improvement Action Plan implemented in Wuhan in 2013–2017 were investigated using health-impact and valuation functions. Annual avoided premature deaths driven by the average concentration of PM2.5 decrease were evaluated, and the economic benefits were computed by using the value of statistical life (VSL) method. Results showed that the number of avoided premature deaths (...) in Wuhan are 21,384 (95% confidence interval (CI): 15,004 to 27,255) during 2013–2017, due to the implementation of the Air Improvement Action Plan. According to the VSL method, the obtained economic benefits of Huangpi, Wuchang, Hongshan, Xinzhou, Jiang’an, Hanyang, Jiangxia, Qiaokou, Jianghan, Qingshan, Caidian, Dongxihu, and Hannan District were 8.55, 8.19, 8.04, 7.39, 5.78, 4.84, 4.37, 4.04, 3.90, 3.30, 2.87, 2.42, and 0.66 billion RMB (1 RMB = 0.1417 USD On 14 October 2019), respectively. These economic benefits added up to 64.35 billion RMB (95% CI: 45.15 to 82.02 billion RMB), accounting for 4.80% (95% CI: 3.37% to 6.12%) of the total GDP of Wuhan in 2017. Therefore, in the process of formulating a regional air quality improvement scheme, apart from establishing hierarchical emission-reduction standards and policies, policy makers should give integrated consideration to the relationship between regional economic development, environmental protection and residents’ health benefits. Furthermore, for improving air quality, air quality compensation mechanisms can be established on the basis of the status quo and trends of air quality, population distribution, and economic development factors. (shrink)

In this paper, we give an alternative semantics to the non-normal logic of knowing how proposed by Fervari et al., based on a class of Kripke neighborhood models with both the epistemic relations and neighborhood structures. This alternative semantics is inspired by the same quantifier alternation pattern of ∃∀\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\exists \forall $$\end{document} in the semantics of the know-how modality and the neighborhood semantics for the standard modality. We show that this new semantics (...) is equivalent to the original Kripke semantics in terms of the validities. A key result is a representation theorem showing that the more abstract Kripke neighborhood models can be represented by the concrete Kripke models with action transitions modulo the valid formulas. We prove the completeness of the logic for the neighborhood semantics. The neighborhood semantics can be adapted to other variants of logics of knowing how. It provides us a powerful technical tool to study these logics while preserving the basic semantic intuition. (shrink)

We have analyzed vertical seismic profile data acquired across a Marcellus Shale prospect and found that SV-P reflections could be extracted from far-offset VSP data generated by a vertical-vibrator source using time-variant receiver rotations. Optimal receiver rotation angles were determined by a dynamic steering of geophones to the time-varying approach directions of upgoing SV-P reflections. These SV-P reflections were then imaged using a VSP common-depth-point transformation based on ray tracing. Comparisons of our SV-P image with P-P and P-SV images derived (...) from the same offset VSP data found that for deep targets, SV-P data created an image that extended farther from the receiver well than P-P and P-SV images and that spanned a wider offset range than P-P and P-SV images do. A comparison of our VSP SV-P image with a surface-based P-SV profile that traversed the VSP well demonstrated that SV-P data were equivalent to P-SV data for characterizing geology and that a VSP-derived SV-P image could be used to calibrate surface-recorded SV-P data that were generated by P-wave sources. (shrink)

A technoeconomic optimization problem for a domestic grid-connected PV-battery hybrid energy system is investigated. It incorporates the appliance time scheduling with appliance-specific power dispatch. The optimization is aimed at minimizing energy cost, maximizing renewable energy penetration, and increasing user satisfaction over a finite horizon. Nonlinear objective functions and constraints, as well as discrete and continuous decision variables, are involved. To solve the proposed mixed-integer nonlinear programming problem at a large scale, a competitive swarm optimizer-based numerical solver is designed and employed. (...) The effectiveness of the proposed approach is verified by simulation results. (shrink)

While an increasing number of organizations have introduced artificial intelligence as an important facilitating tool for learning online, the application of artificial intelligence in e-learning has become a hot topic for research in recent years. Over the past few decades, the importance of online learning has also been a concern in many fields, such as technological education, STEAM, AR/VR apps, online learning, amongst others. To effectively explore research trends in this area, the current state of online learning should be understood. (...) Systematic bibliometric analysis can address this problem by providing information on publishing trends and their relevance in various topics. In this study, the literary application of artificial intelligence combined with online learning from 2010 to 2021 was analyzed. In total, 64 articles were collected to analyze the most productive countries, universities, authors, journals and publications in the field of artificial intelligence combined with online learning using VOSviewer through WOS data collection. In addition, the mapping of co-citation and co-occurrence was explored by analyzing a knowledge map. The main objective of this study is to provide an overview of the trends and pathways in artificial intelligence and online learning to help researchers understand global trends and future research directions. (shrink)

This study provided a content analysis of studies aiming to disclose how artificial intelligence has been applied to the education sector and explore the potential research trends and challenges of AI in education. A total of 100 papers including 63 empirical papers and 37 analytic papers were selected from the education and educational research category of Social Sciences Citation Index database from 2010 to 2020. The content analysis showed that the research questions could be classified into development layer, application layer, (...) and integration layer. Moreover, four research trends, including Internet of Things, swarm intelligence, deep learning, and neuroscience, as well as an assessment of AI in education, were suggested for further investigation. However, we also proposed the challenges in education may be caused by AI with regard to inappropriate use of AI techniques, changing roles of teachers and students, as well as social and ethical issues. The results provide insights into an overview of the AI used for education domain, which helps to strengthen the theoretical foundation of AI in education and provides a promising channel for educators and AI engineers to carry out further collaborative research. (shrink)

This study examines the impact of corporate social responsibility activities on insider trading. While opponents of insider trading claim that the buying or selling of a security by insiders who have access to non-public information is illegal, proponents argue that insider trading improves economic efficiency and fairness when corporate insiders buy and sell stock in their own companies. Based on extensive U.S. data of insider trading and CSR engagement, we find that both the number of insider transactions and the volume (...) of insider trading are positively associated with CSR activities.We also find that legal insider transactions are positively related to CSR engagement even after controlling for potential endogeneitybias and various firm characteristics. Furthermore, our evidence suggests that firms perceive adjustment to CSR dimension of product as being efficient, while adjustment to diversity and environmental CSR as being inefficient. Our results of bad and illegal insider trading proxies are consistent with the interpretation that firms with high CSR ratings do not attempt to engage in unethical or bad insider trading in a significant fashion. Combined together, we consider our empirical evidence supportive of the fairness and efficiency explanation, but not the unfairness and inefficiency hypothesis. (shrink)

Atmospheric pollution is deteriorating, which has affected the evolution of respiratory disease for the exposed human worldwide. Thus, exploring the influence of air pollution on the evolution of disease transmission dynamics is a significant issue. In this article, a stochastic susceptible-infective epidemic model in a polluted atmospheric environment is investigated. The existence and uniqueness of the global positive solution are established. In virtue of the aggregation methods and Lyapunov function, the sufficient conditions of disease extinction, persistence, and existence of the (...) stationary distribution are established, respectively. TakingPM2.5concentration as the air pollutant index, numerical simulations are carried out to support these results. Our results indicated that the disease transmission dynamics are significantly associated with the environmental atmospheric pollution and fluctuation. (shrink)

Frequent pattern mining is an effective approach for spatiotemporal association analysis of mobile trajectory big data in data-driven intelligent transportation systems. While existing parallel algorithms have been successfully applied to frequent pattern mining of large-scale trajectory data, two major challenges are how to overcome the inherent defects of Hadoop to cope with taxi trajectory big data including massive small files and how to discover the implicitly spatiotemporal frequent patterns with MapReduce. To conquer these challenges, this paper presents a MapReduce-based Parallel (...) Frequent Pattern growth algorithm to analyze the spatiotemporal characteristics of taxi operating using large-scale taxi trajectories with massive small file processing strategies on a Hadoop platform. More specifically, we first implement three methods, that is, Hadoop Archives, CombineFileInputFormat, and Sequence Files, to overcome the existing defects of Hadoop and then propose two strategies based on their performance evaluations. Next, we incorporate SF into Frequent Pattern growth algorithm and then implement the optimized FP-growth algorithm on a MapReduce framework. Finally, we analyze the characteristics of taxi operating in both spatial and temporal dimensions by MR-PFP in parallel. The results demonstrate that MR-PFP is superior to existing Parallel FP-growth algorithm in efficiency and scalability. (shrink)

Good balance between product and service is the key in the innovative design of product service systems. In this study, the evolution route of the PSS based on Teoriya Resheniya Izobretatelskikh Zadatch ideal final result was provided. The function model of the PSS was constructed according to the service blueprint and function system diagrams. On this basis, an innovation design method of the PSS based on function incentive was established. The function incentive strategies included function synergy, function supplement, and function (...) substitution. Finally, the PSS design process of agricultural machinery based on computer-aided innovation platform was analyzed to verify this method. (shrink)

The diversities in the natural, social, and human environment of various regions often lead to the differences in their regional economic development level and industrial structure and layout; moderate regional differences can mobilize economic vitality and improve development efficiency, but excessive differences may lead to social instability or even turbulence. Intelligent algorithms or their improved and hybrid algorithms can recently achieve more suitable solutions to practical problems of nonlinear, discrete, nondifferentiable, and multiple constraints. Therefore, this paper's main point is on (...) the analysis of regional economic development differences based on intelligent hybrid algorithms. On the basis of summarizing and analyzing previous research works, this paper expounded the research status and significance of regional economic development differences analysis, elaborated the development background, current status, and future challenges of intelligent hybrid algorithms, introduced the methods and principles of principal component distance weighting algorithm and sequential quadratic programming algorithm, constructed a basic model for regional economic development differences based on intelligent hybrid algorithm, conducted the construction of analysis index system and the hybrid of intelligence algorithm, analyzed the regional economic development differences based on intelligent hybrid algorithm, performed the principal component analysis and time-space change analysis of regional economic development, and finally carried out a simulation experiment and its result analysis. The study results show that the intelligent hybrid algorithm can simulate the intelligent behavior of certain groups in nature when analyzing the differences in regional economic development, so that it has essentially parallelism, high accuracy, and convergence speed. The study results of this paper provide a reference for further researches on the regional economic development differences analysis based on intelligent hybrid algorithm. (shrink)

We have developed an example of hydrocarbon detection for an Ordovician cavern carbonate reservoir in western China with a burial depth exceeding 6600 m using amplitude variation with offset and spectral decomposition. We selected six production wells, three prolific oil wells, and three brine wells to test the hydrocarbon detection method. The three oil wells have been producing for more than three years, and the three water wells only produce brine. We performed spectral decomposition to the angle gathers and analyzed (...) amplitude variation patterns with incidence angles for different spectral components. Specifically, we compared the time corresponding to the peak spectral amplitude for different spectral components for the oil- and brine-saturated carbonate reservoirs. The main findings are as follows: Oil-saturated cavern carbonate reservoirs show decreasing peak time with increasing frequency; i.e., the high-frequency components travel faster than do the low-frequency components. The maximum time difference between the 10 and 50 Hz spectral components could reach 35 ms. In contrast, the brine-saturated carbonate reservoirs do not exhibit conspicuous variation in the peak time, AVO attributes extracted from the low-frequency spectral gathers are more robust than those extracted from the original seismic gathers, oil-saturated cavern carbonate reservoirs cause strong energies in the low-frequency spectral components and severe attenuation to the high-frequency spectral components at large incidence angles. In contrast, the brine-saturated carbonate reservoirs do not produce such phenomenon. Rock physics analysis for carbonate reservoirs under different saturation conditions was conducted. The synthetic gathers were generated for carbonate reservoirs under oil- and brine-saturated conditions. The spectrally decomposed synthetic gathers are in agreement with the real gathers. The results indicate that AVO analysis of spectrally decomposed prestack gathers could be used as an effective hydrocarbon detection method for carbonate reservoirs. (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)

Lamina-induced fractures are abundant in lacustrine formations, playing an important role in tight oil resource exploration. There is a lack of research on the dynamic mechanisms of LF propagation in heterogeneous formations characterized by complex combinations of lamina and surrounding rock. For this reason, we conducted triaxial compressive tests of 28 long column samples and Brazil split tests of 37 short column samples using six core samples with different lithologies, including nine column samples tested using a CT scanner and an (...) acoustic emission apparatus. We designed this experiment to study the LF propagation process and its dynamic mechanisms within different lithologies. Our results show that we classified three mechanical LF types based on the relationship between stress state and lamina angle: tensile LF, shear LF, and hybrid LF ; H-LF only propagated in the middle lamina angle range ; T-LF was inclined to propagate in the low lamina angles; and S-LF was inclined to propagate in the high lamina angles; and in the Ordos Basin, T-LF, TF, and SF propagated mutually in outcrops with low confining pressures. T-LF, H-LF, and SF propagated mutually in the Yanchang Formation, an outcrop that greatly contributes to tight oil sweet spot exploration. Furthermore, unlike the in situ accumulation theory, we find that it is possible for hydrocarbon migration to occur in tight reservoir formations, in which the LF acts as a hydrocarbon migration pathway during the tectonic phase. (shrink)

Geologic studies indicate that the platform-margin reef-shallow facies in Permo-Triassic marine strata in the Micang-Dabashan foothill belt in the Sichuan Basin are favorable exploration targets for oil and gas exploration. However, the typical dual-complexity problem brings a great challenge for seismic technology targeting of those potential oil and gas reservoirs. To overcome this problem, varieties of advanced seismic acquisition and processing methods have been used to improve the imaging quality of piedmont seismic data since 2000. Some improvements have been achieved: (...) The reflection waves from the far offset and deep layer can be acquired in shot gathers from limestone outcropped areas, and the signal-to-noise ratio of reflection and diffraction waves in the stack section has been enhanced significantly so as to reveal amounts of valuable geologic information. The resolution and the S/N of seismic migration imaging for the strong fold zone in marine strata have been improved partially, so that the structure of the step-fault zone and the enveloping of gypsum rock are clearer than those revealed by the old seismic section. Even so, actual drilling data demonstrate that the subsurface structures of the foothill belt are far more complex than those revealed by the current seismic imaging results. Therefore, postdrilling evaluation for the validity of seismic techniques implemented in the Nanjiang and Zhenba piedmont zone has been carried out. The results indicate that the current acquisition scheme and processing workflow cannot completely fulfill the requirements of high-precision velocity modeling and migration imaging of complex structures in the piedmont zone, especially when the rugged surface and the widespread limestone outcrop appear simultaneously. Finally, we have developed some potential needs of seismic theories and techniques in the foothill belt, including seismic wave propagation, acquisition, and processing technology. (shrink)

In today’s knowledge economy, knowledge and knowledge sharing are fundamental for organizations to achieve competitiveness and for individuals to strengthen their innovation capabilities. Knowledge sharing is a complex language-based activity; language affects how individuals communicate and relate. The growth in international collaborations and the increasing number of diverse teams affect knowledge sharing because individuals engage in daily knowledge activities in a language they are not native speakers. Understanding the challenges they face, and how they manage the emerging difficulties is the (...) main aim of this manuscript. For this purpose, an explorative case study was conducted in an international university research project, namely the TED project. Both interviews and direct observations were employed to understand the phenomenon better and deliberately triangulate data and improve validity. Results show that non-native language use determines the emergence of different language proficiency, depending on the nature of the knowledge domain–job-related vs. non-job-related. Within non-job-related knowledge domains, the lack of linguistic abilities, summed to the perceived cultural diversities, mainly affects people’s propensity to engage in personal and more intense social relationships. Under such circumstances, tacit knowledge sharing is reduced with negative consequences on the project’s long-term innovative performance. Since the project is still running, detecting language challenges will allow the partners to design and apply effective measures to support cooperation with language and cultural barriers. Among them, code switching, adopted by “bridge” actors, already emerges as tool supporting communication and knowledge exchange. (shrink)

The coronavirus disease 2019 pandemic has severely damaged the global industrial supply chain and accelerated the digital transformation of the global economy. In such rapidly changing environments, multinational corporations should encourage employees to be more innovative in various fields than ever before. With the onset of the COVID-19 pandemic, employees have become psychologically anxious, their working conditions have deteriorated, and they are in danger of losing their jobs. In this study, we aim to address the question of whether servant leadership (...) facilitates the innovative behavior of employees working in emerging-market MNCs when servant leadership is adopted within the firms. In addition, we explore the mediating roles of work–life balance and psychological stability perceived by employees, and the moderating role of organizational climate in the relationship between servant leadership and MNC employees' innovative behavior. In doing so, we collected data from a sample of 307 Chinese employees who are employed by five different Chinese MNCs from the Internet, information technology, electronics, and e-commerce industries. Based on a sample of survey data collected from employees of Chinese MNCs, we empirically test these ideas by specifically examining how servant leadership may shape the innovation behavior of employees in these MNCs. The results suggest that servant leadership positively influences employees' innovative behavior, and that the contribution of servant leadership to employees' innovative behavior is mediated by work–life balance and psychological stability as well as moderated by the degree of organizational climate. Moreover, the different organizational climates of these MNC employees are also expected to significantly shape the relationship between servant leadership and employees' innovative behavior. This study enriches our understanding of the importance of servant leadership in driving the innovative behaviors of employees in emerging-market MNCs and provides new insights into the mechanisms through which emerging-market MNCs can motivate their employees to be more innovative in their jobs. Thus, this study contributes to the research on human resource management by offering important implications vis-à-vis how MNCs manage their employees more effectively in addressing and responding to the dramatically changing global landscape in the post COVID-19 era. (shrink)

As a new form of online reviews, Q&A reviews have been recently used by many e-commerce platforms to compensate for the weaknesses and problems related to trust and helpfulness found in traditional online reviews. This research documents what motivates people to share products or purchasing knowledge with others through Q&A reviews and why e-commerce platforms should place an emphasis on Q&A reviews. Importantly, our results provide evidence that, when receiving feedback, people are more likely willing to share knowledge with others (...) and will have a higher level of loyalty. We believe that this study contributes to knowledge sharing and the e-commerce literature, and also has practical implications. (shrink)

The predominant use of junk food in our societies is continuously held responsible for the obese body physiques and overweight among the kids and adolescents. The current supportive environments where organic foods are limited, and new processed foods have been brought to the market with more variant tastes and acceptability for the kids and adolescents that have diverged their eating patterns. It has significantly contributed to the health issues and growth discrepancies of the users. However, the awareness of the food (...) contents is an important milestone for understanding the risks associated with the usage of junk foods. A quantitative approach has been used in this study to measure the effect of perceived severity, vulnerability and fear on the junk food eating behaviors and ultimately on the obesity. The moderating role of product knowledge hiding has also been measured on the relationship of junk food eating and obesity. Structural equation modeling is used using the software Smart-PLS for measuring the hypothesis with a sample size of 228 selected through purposive sampling. The sample consisted of kids and adolescents who were reached on purpose for data collection. The current study has explored the role of perceived severity, vulnerability and the fear of using junk foods which have been found as a negative effect on junk food eating behavior which is positively associated with obesity among the kids and adolescents. The result of study shows that perceived threat has a negative effect on the junk food eating behavior of the adolescents. However, the positive relationship of junk food eating behavior with obesity can be decreased if the information about the products is not hidden. This study will be useful for making the consumers aware of the product knowledge hiding of the junk food usage. Moreover, it will help the users in creating understanding of risks allied with the use of junk food which may be addressed in order to avoid obesity issues in the kids and adolescents globally. (shrink)

Research productivity is an important criterion for the university to assess teachers. Studies about factors that affect teachers’ research productivity are increasing nowadays. It is generally agreed that academics’ research productivity depends on how much mentorship is provided to them and how the current working environment is mediated by their research motivation and self-efficacy. Despite the increasing amount of the literature along this line, we know little about what kinds of situations that Chinese university English as a foreign language teachers (...) are in and how they regard the importance of mentorship and what roles their working environments would play in affecting their research productivity. To fill the research gap, we utilized the snowball method to collect the survey data from 546 Chinese EFL tertiary teachers. The results show that mentorship is not correlated with research productivity while the working environment has a positive direct correlation with it. Both motivation and self-efficacy mediate the working environment and research productivity significantly. Specifically, only extrinsic motivation has a negative mediation influence on teachers’ research productivity; teachers’ intrinsic motivation and self-efficacy play a positive mediation role in affecting their research productivity. (shrink)

本书收《论小农社会主义对我国社会主义事业的影响》、《论人的目的》、《论共产主义运动的失败》等20多篇文章。.

In this paper, we study the evolution of knowledge in multi-agent conformant planning over transition systems. We propose a dynamic epistemic logical framework with modalities of distributed knowledge to handle the epistemic reasoning in such scenarios, and we reduce a problem of multi-agent conformant planning to a model checking problem. We prove that multi-agent conformant planning is Pspace-complete on the size of the dynamic epistemic model.

© The Author, 2017. Published by Oxford University Press. All rights reserved. In this article, we introduce a lightweight dynamic epistemic logical framework for automated planning under initial uncertainty. We generalize the standard conformant planning problem in AI in two crucial aspects: first, the planning goal can be any formula expressed in an epistemic propositional dynamic logic ; second, procedural constraints of the desired plan specified by regular expressions can be imposed. We then reduce the problem of generalized conformant planning (...) to the model checking problem of our logic. Although our conformant planning problem is much more general than the standard one with Boolean goals and no procedural constraints, the complexity is still PSPACE-complete which is equally hard as standard conformant planning over explicit transition systems. (shrink)

Previous studies have demonstrated that lying can undermine memory and that its memory-undermining effects could be modulated by the cognitive resources required to tell lies. We extended the investigation of the memory-undermining effect by using a daily life setting in which participants were highly involved in a mock shopping task. Participants were randomly assigned to truth-telling, denying or mixed lying conditions. After finishing the shopping task, participants were told that two people wanted to know about their shopping lists and would (...) ask them some questions in an interview. During the interview, participants were asked whether each of ten items were on the shopping list, five of which were randomly selected from the shopping list, while the other five were not sold in the store. In answering the interview questions, the truth-telling group was asked to respond honestly, the denying group was asked to give denial responses, and the mixed lying group was asked to respond deceptively. Thus, the denying group told five lies and the mixed lying group told ten lies in the interview. The item memory test, source memory test and destination memory test were given in an orderly manner 48 h after the interview. We found that the mixed lying group, rather than the denying group, forgot the lies they told in the interview and mistakenly believed they had lied about something that they had not lied about. Moreover, the mixed lying group retained fewer memories about the person they responded to than the honest group. In addition, participants in the mixed lying group had more non-believed memories than those in the truth-telling group in both item and source memory tests. We conclude that more lies could result in more memory disruptions in daily life. (shrink)

The purpose of this study was to understand the influence mechanism of college students’ entrepreneurial intention in view of the increasing number of college students at present to alleviate college students’ employment competition. The psychological factors that influence the entrepreneurial tendency of art graduates were analyzed and studied. First, venture capital and factors affecting entrepreneurial performance were analyzed. Second, the coefficient calculation is carried out for college students majoring in art through the regression analysis of the logistic model. Finally, a (...) team entrepreneurial performance questionnaire was designed, and team reward levels were discussed. The results show that the logistic model can well reflect the real situation of the respondents. The significance level of the entrepreneurial team was 0.02, which was correlated. Additionally, corresponding suggestions were put forward according to the questionnaire results. Clear team goals, assignment of tasks to members, good pressure resistance, and psychological quality of members are necessary qualities for successful entrepreneurship. This conclusion provides a certain theoretical basis for the current college students’ entrepreneurial learning and a reliable inspiration for helping college students to successfully start a business. (shrink)