: Confucianism is often valued as a doctrine that highlights both the individual and social dimensions of the ideal person, for it indeed puts special emphasis on such lofty goals as loving all humanity and cultivating the self. Through a close and critical analysis of the texts of the Analects and the Mencius, however, it is attempted to demonstrate that because Confucius and Mencius always take filial piety, or, more generally, consanguineous affection, as not only the foundation but also the (...) supreme principle of human life, the individual and social dimensions are inevitably subordinated to and substantially negated by the filial precisely within the Confucian framework, with the result that Confucianism in essence is neither collectivism nor individualism, but "consanguinitism.". (shrink)

A fresh, graceful translation of one of the most important and timeless classics-the foundational work of Daoism-by award-winning novelist Ken Liu, who contextualizes and demystifies this famously enigmatic text. Laozi's Dao De Jing was written around 400 BC by a compassionate soul in a world torn by hatred and ambition, dominated by those that yearned for apocalyptic confrontations and prized ideology over experience. By speaking out against the cleverness of elites and the arrogance of the learned, Laozi upheld the wisdom (...) of the concrete, the humble, the quotidian, the everyday individual dismissed by the great powers of the world. Earthy, playful, and defiant, Laozi's words gave solace to souls back then, and offer comfort today. Now, this beautifully designed new edition serves as both an accessible new translation of an ancient Chinese classic and a fascinating account of renowned novelist Ken Liu's transformative experience while wrestling with the classic text. Throughout this translation, Liu takes us through his own struggles to capture the meaning in Laozi's text in a series of thoughtful and provocative interstitial entries. Unlike traditional notes that purport to be objective, these entries are explicitly personal and unapologetically subjective. Gradually, as Liu learns that true wisdom cannot be pinned down in words, the notes grow sparser until they fade away entirely. His journey suggests the only way out of struggle is to engage with texts that have survived the millennia, wrestling with ideas that gesture at something eternal, in hopes that we might eventually reach that moment of transcendent joy. Liu's translation, by eschewing cleverness, paradoxically reveals the slipperiness of Laozi's original. The Dao De Jing has been translated countless times and will be translated countless times in the future. In that constant change and flow, we finally find our home in Dao, the eternal principle that allows us, finite beings in time and space, to reckon and reconcile with the infinite. (shrink)

Smart grids are rolling out internationally, with the United States nearing completion of a significant USD4-plus-billion federal program funded under the American Recovery and Reinvestment Act. The emergence of smart grids is widespread across developed countries. Multiple approaches to analyzing the benefits of smart grids have emerged. The goals of this white paper are to review these approaches and analyze examples of each to highlight their differences, advantages, and disadvantages. This work was conducted under the auspices of a joint U.S.-China (...) research effort, the Climate Change Working Group Implementation Plan, Smart Grid. We present comparative benefits assessments of smart grid demonstrations in the U.S. and China along with a BA of a pilot project in Europe. In the U.S., we assess projects at two sites: the University of California, Irvine campus, which consists of two distinct demonstrations: Southern California Edison’s Irvine Smart Grid Demonstration Project and the UCI campus itself; and the Navy Yard area in Philadelphia, which has been repurposed as a mixed commercial-industrial, and possibly residential, development. In China, we cover several smart-grid aspects of the Sino-Singapore Tianjin Eco-city and the Shenzhen Bay Technology and Ecology City. In Europe, we look at a BA of a pilot smart grid project in the Malagrotta area west of Rome, Italy, contributed by the Joint Research Centre of the European Commission. The Irvine sub-project BAs use the U.S. Department of Energy Smart Grid Computational Tool, which is built on methods developed by the Electric Power Research Institute. The TEC sub-project BAs apply Smart Grid Multi-Criteria Analysis developed by the State Grid Corporation of China based on the analytic hierarchy process with fuzzy logic. The B-TEC and TNY sub-project BAs are evaluated using new approaches developed by those project teams. JRC has adopted an approach similar to EPRI’s but tailored to the Malagrotta distribution grid. (shrink)

Sensibility theory claims that, for any object x, x is good/right if and only if x is such as to make a certain sentiment appropriate. A realist position, sensibility theory claims conceptual and explanatory advantages over alternative metaethical theories. Sensibility theory, while revealing, presents a problem of its own: its central thesis involves an explanatory circularity. Here, a Mencius-Hume solution to that problem is offered.

Putnam and Burge have been viewed as launching a joint attack on individualism, the view that the content of one's psychological state is determined by what is in the head . Putnam argues that meanings are not in the head while Burge argues that beliefs are not in the head either, and both have come up with convincing arguments against individualism. It is generally conceived that Putnam's view is a version of physical externalism, which argues that factors in the physical (...) environment play a role in determining the meanings of natural kind terms. Burge, on the other hand, is regarded as following up Putnam's argument to bring in factors in the social environment for the determination of belief. Burge's view has been commonly referred to as 'social externalism.' The general consensus in the field is that physical externalism and social externalism are compatible views. Furthermore, both Putnam and Burge seem to endorse each other’s position for the most part. In this paper, however, I shall argue against this general view to show that the two theories are deep down incompatible. (shrink)

Rice is a staple food in China, and, thus, its security has drawn much attention. The Chinese government proactively fuels the application of biotechnology in agriculture and food to cope with increasingly severe food security issues. However, most consumers resist the commercialization of genetically modified rice. One of the important reasons is the consumer perception of its various risks. Conversely, trust in the government, scientists, and media can stimulate consumer purchase. On the basis of the dual perspectives of perceived risks (...) and trust, this study establishes a model of purchase intention for GM rice to explore the structural relationship between variables. Perceived risks explore how exclusion can weaken the purchase intention from the consumer perspective; trust examines the benefits that support can provide. Based on the structural equation model, online survey results of 564 consumers in eight provinces and cities are analyzed. The following observations are offered: health risks, moral risks, and purchase intention are negatively correlated; environmental, functional, and economic risks have no significant correlation with purchase intention; and trust and purchase intention have a significant positive correlation. (shrink)

In order to better understand the individual-level motives for ticket-splitting, Taiwan's Election and Democratization Study has since 2001 included a question aimed at measuring respondents’ preferences for checks and balances. We argue that this set of questions, designed to measure a combination of Fiorina's policy-balancing hypothesis and Ladd's cognitive Madisonianism, is inconsistent with principles of survey methodology and thus produces data that are suboptimal. Following a method developed by Carsey and Layman, we propose an alternative concept, the policy-balancing index derived (...) from the perceived ideological distance between respondent and political parties, which both avoids methodological violations and provides us with a more precise concept to work with. We test the index and find it to be a significant determinant of ticket-splitting behavior. (shrink)

The role of other-directed moral emotions (e.g. anger) in constructing leadership ethics is well-discussed, yet the effects of leaders expressing self-directed moral emotions remain under-explored. This paper focuses on guilt, a typical self-conscious moral emotion, to investigate the interpersonal prosocial impact of a leader’s guilt expression. Drawing from the emotion as social information theory, we propose that a leader’s guilt expression can enhance followers’ forgiveness and organizational citizen behaviors by evoking followers’ moved emotions and delivering the leader’s benevolence information. Additionally, (...) we examine the moderating role of the quality of leader–member exchange in these effects. Our results, obtained through a two-wave field survey (Study 1), a critical incident technique experiment (Study 2), and a scenario experiment (Study 3), provide support for most of our hypotheses. Our research contributes to the EASI theory and literature on emotions and provides practical guidance on leader emotional management. (shrink)

The rapid worldwide spread of COVID-19 forced many countries to enforce complete lockdown and strict quarantine policies. The strict lockdown and quarantine affect the psychological state of people toward cryptocurrency. The current research aims to examine the effect of COVID-19 on Bitcoin prices concerning cumulative deaths and confirmed cases. The research comprises daily data from January 20, 2020, to April 30, 2020, during the initial worldwide breakout of COVID-19. This research employed the augmented Dickey-Fuller test to check the stationarity of (...) data, the co-integration test for the interdependency of variables, and the vector error correction model for identifying the direction and long or short-run relationship between Bitcoin prices and COVID-19. The research results show that Bitcoin prices are negatively significant and related to COVID-19 in the short-run. A unidirectional relationship between Bitcoin prices and cumulative deaths is also observed. Investors and the public’s psychological state were positively significant to Bitcoin prices in the long-term because of cashless transactions, unbanked, and less risky virus traveling. The second reason behind the positive psychological relation is un-centralization and easy-to-make payments by Bitcoin. This study’s finding provides timely evidence to decision-makers on Bitcoin price volatility and its impacts on the public’s psychological states regarding COVID-19. (shrink)

Educational assessments tests are often constructed using testlets because of the flexibility to test various aspects of the cognitive activities and broad content sampling. However, the violation of the local item independence assumption is inevitable when tests are built using testlet items. In this study, simulations are conducted to evaluate the performance of item response theory models and testlet response theory models for both the dichotomous and polytomous items in the context of equating tests composed of testlets. We also examine (...) the impact of testlet effect, length of testlet items, and sample size on estimating item and person parameters. The results show that more accurate performance of testlet response theory models over item response theory models was consistently observed across the studies, which supports the benefits of using the testlet response theory models in equating for tests composed of testlets. Further, results of the study indicate that when sample size is large, item response theory models performed similarly to testlet response theory models across all studies. (shrink)

Partner selection is an important aspect of the customer collaborative product innovation process and aims to select innovative customer partners from huge numbers of customers, fast and accurately. The purpose of this article is to present a quantitative partner selection method based on the complex network theory. In this method, the complex network model of the Online Community Customer Network is constructed, and network centrality is used as the initial index of customer partner selection. Then, network efficiency and delta centrality (...) are used to evaluate the effect of the index. An example is presented to reflect the feasibility and efficiency of the proposed method. Results validate the small-world and scale-free properties of the OCCN and show that betweenness centrality is the most appropriate index for partner selection in the OCCN. (shrink)

陈沛霖(1934~ ),湖南株洲人,华中师范大学教育系心理学副教授、基础心理学教研室主任,湖北省心理学会副理事长、省社科联委员.

Sven-Ove Hansson and Erik Olsson studied in Hansson and Olsson, 103–119 1995) the logical properties of an operation of contraction first proposed by Isaac Levi in Levi. They provided a completeness result for the simplest version of contraction that they call Levi-contraction but left open the problem of characterizing axiomatically the more complex operation of value-based contraction or saturatable contraction. In this paper we propose an axiomatization for this operation and prove a completeness result for it. We argue that the (...) resulting operation is better behaved than various rival operations of contraction defined in recent years. (shrink)

AimsAlcohol consumption could lead to a series of health problems and social issues. In the current study, we investigated the resting-state functional brain networks of healthy volunteers before and after drinking through graph-theory analysis, aiming to ascertain the effects of acute alcohol intake on topology and information processing mode of the functional brain networks.Materials and methodsThirty-three healthy volunteers were enrolled in this experiment. Each volunteer accepted alcohol breathalyzer tests followed by resting-state magnetic resonance imaging at three time points: before drinking, (...) 0.5 h after drinking, and 1 h after drinking. The data obtained were grouped based on scanning time into control group, 0.5-h group and 1-h group, and post-drinking data were regrouped according to breath alcohol concentration (BrAC) into relative low BrAC group (A group; 0.5-h data, n = 17; 1-h data, n = 16) and relative high BrAC group (B group; 0.5-h data, n = 16; 1-h data, n = 17). The graph-theory approach was adopted to construct whole-brain functional networks and identify the differences of network topological properties among all the groups.ResultsThe network topology of most groups was altered after drinking, with the B group presenting the most alterations. For global network measures, B group exhibited increased global efficiency, Synchronization, and decreased local efficiency, clustering coefficient, normalized clustering coefficient, characteristic path length, normalized characteristic path length, as compared to control group. Regarding nodal network measures, nodal clustering coefficient and nodal local efficiency of some nodes were lower in B group than control group. These changes suggested that the network integration ability and synchrony improved, while the segregation ability diminished.ConclusionThis study revealed the effects of acute alcohol intake on the topology and information processing mode of resting-state functional brain networks, providing new perceptions and insights into the effects of alcohol on the brain. (shrink)

Guiding core enterprises to participate in supply chain work safety governance is an innovative mode of work safety control, which has an important impact on improving the work safety level of small and medium-sized enterprises in the supply chain. Through in-depth interviews, the grounded theory is adopted to explore the driving factors of work safety management behaviors of core enterprise. It is found that the work safety management behavior of the core enterprise is driven by both internal and external factors. (...) External driving factors are the main category of institutional pressure composed of regulatory pressure, normative pressure, and cognitive pressure. Internal driving factors are divided into the main category of behavioral awareness and the behavioral capability of the core enterprises. The behavioral awareness is composed of responsibility sense, problem cognition and behavioral effect perception. The behavioral capability is composed of safety management strength and safety coordination capability. Institutional pressure, behavioral awareness, and behavioral capability all influence the work safety management behavior of core enterprise in supply chain significantly, but with different ways and paths. On this basis, the driving mechanism model of the above three main categories on the work safety management behavior in core enterprise supply chain is explored. The research can provide targeted policy ideas and implementation paths for the government to formulate effective guiding policies to promote the work safety management behavior of core enterprise. (shrink)

BackgroundAdolescents’ engagement in daily physical activity brings multiple benefits, including reduction in obesity, improvement of mental health, and enhancement of cognitive function. While prior studies have examined the link between physical activity and cognitive function, little is known regarding the extent to which this relationship is shaped by health and wellbeing factors. This study examines how subjective wellbeing and general health mediate the relationship between adolescents’ physical activity and cognitive function.MethodsThis study estimates a parallel structural equation model using the Program (...) for International Student Assessment 2018 dataset. Specifically, a total of 63,228 15-year-old subjects in nine countries/economies satisfied the study inclusion criteria, including in Bulgaria, Georgia, Hong Kong, Ireland, Mexico, Panama, Serbia, Spain, and United Arab Emirates. Frequency of moderate physical activity was reported weekly; SWB and GH were assessed using an internationally validated multi-item standardized questionnaire. SWB was measured by students’ self-evaluated satisfaction with their health, life, and schooling. GH was measured by students’ physical health and mental health status. Cognitive function was modeled as a latent function consisting of plausible values derived using item response theory on reading, mathematics, and science achievement tests.ResultsFindings indicated that increase in weekly MPA was positively associated with higher levels of SWB, GH, and CF among the study subjects. Parallel mediation analyses revealed that more frequent weekly MPA had relatively large direct effects on CF, and indirect effects channeling through improvements in SWB and GH were non-trivial. Heterogeneity results showed that boosts to CF, associated with MPA, were larger for mathematics and science than for reading.ConclusionThis study used a large-scale international dataset to show that the positive relationship observed between MPA and CF among adolescents was robust, and that SWB and GH were two critical mediators through which physical activity positively bolster CF. (shrink)

This paper describes the investigations performed to better understand two-stage rotor speed matching in a contrarotating fan. In addition, this study develops a comprehensive measuring and communication system for a contrarotating fan using ZigBee network. The investigation method is based on three-dimensional RANS simulations; the RANS equations are solved by the numerical method in conjunction with a SST turbulence model. A wireless measurement system using big data method is first designed, and then a comparison is done with experimental measurements to (...) outline the capacity of the numerical method. The results show that when contrarotating fan worked under designed speed, performance of two-stages rotors could not be matched as the designed working condition was deviated. Rotor 1 had huge influences on flow rate characteristics of a contrarotating fan. Rotor 2 was influenced by flow rates significantly. Under large flow rate condition, the power capability of rotor 2 became very weak; under working small flow rate condition, overloading would take place to class II motor. In order to solve the performance mismatch between two stages of CRF under nondesigned working conditions, under small flow rate condition, the priority shall be given to increase of the speed of rotor 1, while the speed of rotor 2 shall be reduced appropriately; under large flow rate condition, the speed of rotor 1 shall be reduced and the speed of rotor 2 shall be increased at the same time. (shrink)

This study examines the relationship among the employees–organization pro-environmental values fit, supervisors’ PEVs and employees’ pro-environmental behaviors. Informed by the PEB, organizational values and employee–organization fit literature, we propose and test hypotheses that under egoistic, altruistic and biosphere-value orientations, E–O PEVs fit versus non-fit have significant effects on employees’ private-sphere PEB and public-sphere PEB, identifying supervisors’ PEVs as a moderator. An empirical investigation indicates that the effect of E–O PEVs fit on employees’ private-sphere PEB and public-sphere PEB varies as the (...) value orientation differs. More specifically, under the context of altruistic and biosphere-value orientations, if the organizational PEVs do not match the employees’ PEVs, especially when the former exceeds the latter, employees’ PEB will rise as the organizational PEVs increase. As for egoistic value orientation, when organizational PEVs exceed employees’ PEVs, not only will public-sphere PEB stop decreasing and tend to stabilize, but also private-sphere PEB will rise to a slight degree. Furthermore, compared with altruistic and biospheric values dimensions, supervisors who promote egoistic PEVs will have a more significant effect on the relationship between global E–O PEVs fit and employees’ PEB. Finally, we suggest that the goals of an organization and its supervisors need to be combined within the actual situation of Chinese corporations to truly implement corporate green practices by balancing the profit goal and the environmental goal. (shrink)

This paper further extends the existing GARCH-MIDAS model to deal with the effect of microstructure noise in mixed frequency data. This paper has two highlights. First, according to the estimation of the long-term volatility components of the GARCH-MIDAS model, rAVGRV is adopted to substitute for the RV estimator. rAVGRV uses the rich data sources in tick-by-tick data and significantly corrects the impact of the microstructure noise on volatility estimation. Second, besides introducing macroeconomic variables, deposits in financial institutions, industrial value-added, and (...) M2), Chinese Economic Policy Uncertainty index and Infectious Disease Equity Market Volatility Tracker are introduced in the long-run volatility component of the GARCH-MIDAS model. As indicated by the results of this paper, the rAVGRV-based GARCH-MIDAS is slightly better than the RV model-based GARCH-MIDAS. In addition to the common macroeconomic variables significantly impacting stock market volatility, CEPU also substantially impacts stock market volatility. Nevertheless, the effect of EMV on the stock market is insignificant. (shrink)

Complex adaptation systems are the main development direction of China’s current green innovation research. New material industry is one of the key entry points to accelerate the construction of modern industrial system and promote innovation, green, and efficient development. Under the requirements of China’s current low-carbon development, China’s green innovation system is developing rapidly. Green innovation complicates traditional innovation models and their functions and improves economic development. The purpose of this paper is to study the theoretical analysis framework of applying (...) complex adaptive systems and to analyze and calculate the characteristics of the current status of green innovation systems in multiple industries in China’s manufacturing industry. Analysis is as follows. The experimental group and the control group are set for comparison, and the data are organized by applying complex adaptive system theory and data analysis methods. Experimental data show that the coordinated development of the green innovation systems in various industries in China is not balanced, with a difference of more than three times; the parameters of the various green innovation systems within the industry are unbalanced, and the difference is more than five times. The experimental results show that the green innovation subject can strategically interact by adjusting the ratio of resource allocation through the constructed green innovation system model. The green innovation system with complex adaptive system theory is conducive to the development of the green system. It can save about 23% of green innovation time and improve efficiency by about 15%, to promote the development of green innovation in China. (shrink)

This research synthesizes social exchange, organizational culture, and social identity theories to explore the boundary conditions of the relationship between high-performance work systems and employee organizational citizenship behavior. In particular, it draws on the China-specific management context. In this country, in spite of the wide use of a long-term-oriented and loose-control-focused Western-styled strategic human resource management model, a short-term-focused and tight-control-oriented error aversion culture is still popular. The study uses multi-source individual-level survey data in a large state-owned enterprise to test (...) the hypotheses. It is found that employee-experienced, Western-styled high-performance work systems positively impact a China-specific employee’s organizational citizenship behavior, and the—joint—moderation effects of employee-perceived error aversion culture and organizational identification are significant. The research findings deepen the understanding of the HRM-OCB relationship by demonstrating that culture and identity can jointly adjust the effects of HRM on OCB. The findings also challenge an established argument in the HRM-OCB literature that compatibility between employees’ personalities and organizational values – organizational identification – can enhance OCB. (shrink)

Research on the relationship between emotions and job performance is ubiquitous, yet few scholars have examined the combined effects of different emotions. Drawing on the broaden-and-build theory and conservation of resources theory, we propose that employees’ daily emotion fluctuations will affect their service performance in opposite directions. Furthermore, we propose these effects will be moderated by psychological [i.e., regulatory emotional self-efficacy ] and physiological characteristics of the employees. Based on the experience sampling method, data obtained from 187 frontline employees of (...) 35 bank branches over 18 consecutive days supports our hypotheses. (shrink)

ObjectiveThis paper studies the mediating and interactive effects of social capital on psychological capital and the feeling of happiness from the impact of COVID-19. Since its emergence, the COVID-19 pandemic has taken a toll on people’s mental health and affected their hopes for the future. Lifestyle and economic conditions have also been affected and have subsequently impacted people’s sense of confidence in life. This could increase the likelihood of many people developing mental health issues, such as anxiety or depression. Therefore, (...) it is vital to study the influence of psychological capital and social capital on people’s subjective psychology and happiness experiences.Materials and MethodsUsing an ordered probit model, this paper studied the independent influence and interaction between psychological capital and social capital on people’s happiness. The ordered probit model was chosen because subjective well-being is an ordered variable. We further used structural equation modeling to study the mediating effects of social capital on psychological capital and happiness.ResultsThe regression results showed that both psychological capital and social capital were significantly positively correlated with happiness when controlling for other factors. In addition, psychological and social capital significantly interacted, in which the psychological capital promotes the effect of social capital on happiness. Moreover, the effect of psychological capital on happiness was greater than that of social capital, demonstrating that happiness is more greatly influenced by subjective psychological experience. The interaction coefficient of psychological and social capital was also significant, showing that the two have mutually reinforcing effects on happiness. Finally, health, income class, real estate, stranger trust, age, and urban household registration had significant positive effects on happiness, while the view of money, being female, education had a negative relationship with happiness. The SEM results showed that the mediating effect of psychological capital on happiness was partly transmitted through social capital: the total effect of psychological capital on happiness was highly significant, as was the total effect of social capital on happiness ; however, the coefficient for psychological capital was greater than that for social capital. Through heterogeneity analysis, we found that the relationship between psychological capital, social capital, and happiness was significantly positive in each sub-sample group. There was also a significant interaction between psychological and social capital for men, women, urban and rural residents, and higher education background sample groups. However, the interaction was not significant in the sample group without higher education. In addition, the relationship between the happiness of rural residents and their educational background and gender was not significant.ConclusionWe found that psychological and social capital have significant positive relationships and effects on happiness. Psychological capital demonstrated both direct and indirect influences on happiness, and further strengthens the influence of social capital on happiness. These results support a scheme to emphasize psychological support during the COVID-19 pandemic period to enhance the mental health of citizens. (shrink)

With the rapid growth of online product reviews, many users refer to others’ opinions before deciding to purchase any product. However, unfortunately, this fact has promoted the constant use of fake reviews, resulting in many wrong purchase decisions. The effective identification of deceptive reviews becomes a crucial yet challenging task in this research field. The existing supervised learning methods require a large number of labeled examples of deceptive and truthful opinions by domain experts, while the available unsupervised learning methods are (...) inefficient because they depend on the features of reviewers to detect each fake review. Therefore, by focusing on the detection efficiency problem and the limitation of large amount of labeled examples dependence, in this paper, we proposed an effective semisupervised learning approach for detecting spam reviews. Firstly, a time series model of all the reviews of a product is constructed, and then the suspected time intervals are captured based on the burst review increases in these intervals. Secondly, a co-training two-view semisupervised learning algorithm was performed in each captured interval, in which linguistic cues, metadata, and user purchase behaviors were synthetically employed to classify the reviews and check whether they are spam ones or not. A series of numerical experiments on a real dataset acquired from Taobao.com have confirmed the effectiveness of the proposed model, not only reaping benefits in terms of time efficiency and high accuracy but also overcoming the shortcomings of supervised learning methods, which depend on large amounts of labeled examples. And a trade-off balance was obtained between accuracy and efficiency. (shrink)

In the process of communication between people, everyone will have emotions, and different emotions will have different effects on communication. With the help of external performance information accompanied by emotional expression, such as emotional speech signals or facial expressions, people can easily communicate with each other and understand each other. Emotion recognition is an important network of affective computers and research centers for signal processing, pattern detection, artificial intelligence, and human-computer interaction. Emotions convey important information in human communication and communication. (...) Since the end of the last century, people have started the research on emotion recognition, especially how to correctly judge the emotion type has invested a lot of time and energy. In this paper, multi-modal emotion recognition is introduced to recognize facial expressions and speech, and conduct research on adaptive higher education management. Language and expression are the most direct ways for people to express their emotions. After obtaining the framework of the dual-modal emotion recognition system, the BOW model is used to identify the characteristic movement of local areas or key points. The recognition rates of emotion recognition for 1,000 audios of anger, disgust, fear, happiness, sadness and surprise are: 97.3, 83.75, 64.87, 89.87, 84.12, and 86.68%, respectively. (shrink)

Numerous studies have produced contradictory findings about whether static or animated format is the better instructional tool. With a comparison between graphs and animations that has a genuine impact on learning and teaching, this review provides a comprehensive examination of the theoretical foundations of visualized learning, influencing factors, and prospective future studies.

Greed is one of the most common features of human nature, and it has recently attracted increasing research interest. The aims of this paper are to provide one of the first empirical investigations of the effects of greed on job performance and to explore the mediating role of the need for social status and perceived distributive justice. Using a working sample (N = 315) from China, the current study found that greed promoted both task and contextual performance through the intermediary (...) effect of the need for social status. At the same time, greed inhibited both types of performance through perceived distributive justice. These results confirmed our hypothesis that greed is a double-edged sword with opposite effects on one’s performance. The findings suggest that organizations should both address greedy employees’ social status concerns and ensure that they are treated fairly so that organizations can fully utilize the talents of greedy people and channel their energy in a beneficial direction. (shrink)

Advances in artificial intelligence have raised a basic question about human intelligence: Is human reasoning best emulated by applying task‐specific knowledge acquired from a wealth of prior experience, or is it based on the domain‐general manipulation and comparison of mental representations? We address this question for the case of visual analogical reasoning. Using realistic images of familiar three‐dimensional objects (cars and their parts), we systematically manipulated viewpoints, part relations, and entity properties in visual analogy problems. We compared human performance to (...) that of two recent deep learning models (Siamese Network and Relation Network) that were directly trained to solve these problems and to apply their task‐specific knowledge to analogical reasoning. We also developed a new model using part‐based comparison (PCM) by applying a domain‐general mapping procedure to learned representations of cars and their component parts. Across four‐term analogies (Experiment 1) and open‐ended analogies (Experiment 2), the domain‐general PCM model, but not the task‐specific deep learning models, generated performance similar in key aspects to that of human reasoners. These findings provide evidence that human‐like analogical reasoning is unlikely to be achieved by applying deep learning with big data to a specific type of analogy problem. Rather, humans do (and machines might) achieve analogical reasoning by learning representations that encode structural information useful for multiple tasks, coupled with efficient computation of relational similarity. (shrink)

As a way of human-computer interaction, game-based assessment is more suitable for young children because it is situational, interesting, and effective. National identity is an important factor affecting the overall development of young children and the future development of a country, which has attracted extensive attention from researchers. Nevertheless, the assessment of young children's national identity is still based on traditional evaluation, including questionnaires and interviews, which have the limitations of being inaccurate, dull, and time-consuming. To understand the characteristics of (...) children's national identity, it is necessary to use scientific and interactive assessment methods. The present study investigated whether the game-based assessment we developed specifically would be an appropriate tool to measure young children's national identity. The results show that the game-based assessment had good item discrimination. Exploratory factor analysis demonstrated the game covered three aspects: national cognition mastery, national emotion engagement, and national behavior tendency. The confirmatory factor analysis suggested that the model with three factors fit the data well. The internal consistency, the split-half reliability, and the test-retest reliability meet standards. Overall, the results indicated that this game can be successfully used to assess young children's national identity with acceptable validity and reliability. Our study provides strong evidence for the use of human-computer interaction in child measurement. These findings are the first to demonstrate the promise of game-based assessment in assessing children's national identity reliably and effectively. (shrink)

With the rapid development of science and technology, UAVs have become a new type of weapon in the informatization battlefield by their advantages of low loss and zero casualty rate. In recent years, UAV navigation electromagnetic decoy and electromagnetic interference crashes have activated widespread international attention. The UAV LiDAR detection system is susceptible to electromagnetic interference in a complex electromagnetic environment, which results in inaccurate detection and causes the mission to fail. Therefore, it is very necessary to predict the effects (...) of the electromagnetic environment. Traditional electromagnetic environment effect prediction methods mostly use a single model of mathematical model and machine learning, but the traditional prediction method has poor processing nonlinear ability and weak generalization ability. Therefore, this paper uses the Stacking fusion model algorithm in machine learning to study the electromagnetic environment effect prediction. This paper proposes a Stacking fusion model based on machine learning to predict electromagnetic environment effects. The method consists of Extreme Gradient Boosting algorithm, Gradient Boosting Decision Tree algorithm, K Nearest Neighbor algorithm, and Decision Tree algorithm. Experimental results show that, comprising with the other seven machine learning algorithms, the Stacking fusion model has a better classification prediction accuracy of 0.9762, a lower Hamming code distance of 0.0336, and a higher Kappa coefficient of 0.955. The fusion model proposed in this paper has a better predictive effect on electromagnetic environment effects and is of great significance for improving the accuracy and safety of UAV LiDAR detection systems under the complex electromagnetic environment on the battlefield. (shrink)

ObjectiveThis study aimed to develop a diagnostic model of multi-kinematic parameters for patients with amnestic mild cognitive impairment (aMCI).MethodIn this cross-sectional study, 94 older adults were included (33 cognitively normal, CN; and 61 aMCI). We conducted neuropsychological battery tests, such as global cognition and cognitive domains, and collected gait parameters by an inertial-sensor gait analysis system. Multivariable regression models were used to identify the potential diagnostic variables for aMCI. Receiver operating characteristic (ROC) curves were applied to assess the diagnostic accuracy (...) of kinematic parameters in discriminating aMCI from healthy subjects.ResultsMultivariable regression showed that multi-kinematic parameters were the potential diagnostic variables for aMCI. The multi-kinematic parameter model, developed using Timed Up and Go (TUG) time, stride length, toe-off/heel stride angles, one-leg standing (OLS) time, and braking force, showed areas under ROC (AUC), 0.96 [95% confidence interval (CI), 0.905–0.857]; sensitivity, 0.90; and specificity, 0.91. In contrast, a single kinematic parameter’s sensitivity was 0.26–0.95 and specificity was 0.21–0.90. Notably, the separating capacity of multi-kinematic parameters was highly similar to Montreal Cognitive Assessment (MoCA; AUC: 0.96 vs. 0.95). Compared to cognitive domain tests, the separating ability was comparable to Auditory Verbal Learning Test (AVLT) and Boston Naming Test (BNT; AUC: 0.96 vs. 0.97; AUC: 0.96 vs. 0.94).ConclusionWe developed one diagnostic model of multi-kinematic parameters for patients with aMCI in Foshan. (shrink)

In the big data era, sequencing technology has produced a large number of biological sequencing data. Different views of the cancer genome data provide sufficient complementary information to explore genetic activity. The identification of differentially expressed genes from multiview cancer gene data is of great importance in cancer diagnosis and treatment. In this paper, we propose a novel method for identifying differentially expressed genes based on tensor robust principal component analysis, which extends the matrix method to the processing of multiway (...) data. To identify differentially expressed genes, the plan is carried out as follows. First, multiview data containing cancer gene expression data from different sources are prepared. Second, the original tensor is decomposed into a sum of a low-rank tensor and a sparse tensor using TRPCA. Third, the differentially expressed genes are considered to be sparse perturbed signals and then identified based on the sparse tensor. Fourth, the differentially expressed genes are evaluated using Gene Ontology and Gene Cards tools. The validity of the TRPCA method was tested using two sets of multiview data. The experimental results showed that our method is superior to the representative methods in efficiency and accuracy aspects. (shrink)

Every scientific or intellectual movement rests on central premises and assumptions that shape its philosophy. The purpose of this study is to review a brief account of the main philosophical bases of grey systems theory (GST) and the paradigm governing its principles. So, the recent studies on the philosophical foundations of GST have been reviewed and tried to pay attention to some key ambiguities in the previous studies and give more and clearer explanations in this paper. Also, this paper tries (...) to fill the gap among the previous studies and to provide a purposeful connection between them by expressing two key concepts: complete information and imbalance knowledge. Primarily, the study addresses the theoretical foundations of uncertainty and the concept of greyness. Next, it focuses on the notion of “complete information” and challenges to it. Then, it reviews such processes as perception, cognition, and understanding, as well as their dynamic nature. It explains how knowledge is produced through understanding and interpreting information/data and the dynamics governing the whole process. Also, the study describes any dataset, no matter how large it may be, will remain incomplete, imperfect, and grey, so humans only rely on incomplete datasets to interpret the world. As such, information and knowledge are always grey and uncertain because they are basically contingent on subjective understandings and interpretations and imperfect inputs and data. Finally, as a key development, this study also demonstrates that human grey knowledge remains imbalanced across different disciplines and spheres. In the end, a brief overview of the philosophical paradigm of GST is also provided. GST is depicted as an anti-realistic, anti-positivistic, and non-deterministic approach, which is inherently pluralistic and ideographic. According to GST principles, dynamicity and change are essential parts of human narratives of the world and systems, and human knowledge is constantly reproduced through collecting new information. As a result, knowledge, theories, narratives, and scientific laws dynamically change. Given this premise, one could argue that GST is considerably compatible with the postulates of post-modern thinking. (shrink)