Children with autism spectrum disorder show marked difficulties in reading comprehension, a complex cognitive skill fundamental to successful daily functioning that is associated with core executive functions. However, the neurophysiological mechanisms underlying reading comprehension deficits in these children remain elusive. Twenty-one right-handed males with high-functioning ASD and 23 age-, IQ-, educational level-, sex- and handedness-matched typically developing individuals underwent a reading comprehension test and the semantic verbal fluency test that tapped core executive functions underlying reading comprehension during concurrent prefrontal functional (...) near-infrared spectroscopy measurement. Participants’ information processing efficiency was also assessed. High-functioning ASD children exhibited general reading comprehension [main effect of group: F = 7.58, p = 0.009], selective verbal fluency deficits [Group × category interaction: F = 4.90, p = 0.032] and slower processing speed. Regarding the hemodynamics of the prefrontal cortex, although ASD individuals showed comparable patterns of PFC brain activation to their healthy counterparts, lower PFC intrahemispheric [main effect of group: F = 11.36, p = 0.002] and interhemispheric [main effect of group: F = 7.79, p = 0.008] functional connectivity were evident during the semantic verbal fluency test. At the whole-group level, poorer reading comprehension performance was associated with poorer performance in the semantic verbal fluency test. Moreover, poorer semantic verbal fluency test performance was associated with slower information processing speed, which is associated with reduced left medial PFC functional connectivity. Abnormal intrahemispheric and interhemispheric prefrontal hypoconnectivity is associated with deficits in executive processes essential for reading comprehension in ASD. Our study has provided important implications for the neuropsychological and neurophysiological mechanisms underlying reading comprehension deficits in ASD. (shrink)

According to the essence of industrial civilization, wilderness is bound to disenchantment. However, in the ecological civilization era, based on the demands of ecological balance, we must reserve a certain degree of wilderness in urban environment. Therefore, we need to bring back enchantment to aesthetic appreciation of wilderness. On the surface, the re-enchantment of wilderness seems to be a regression of agricultural civilization; however, in fact, it is a transcendental development of agricultural civilization. In recent years, there have been some (...) deviations in the application of “garden urbanism” and “landscape urbanism” have existed in contemporary Chinese urban landscaping. To some extent, the recovery of wilderness is a major mission in Chinese urban construction. (shrink)

本书是王蒙先生用自己的人生历练, 用自己的体悟感受, 用自己的政治经历, 社会经历, 人生经历, 文学经历, 也用自己的知识与智商去与庄生对话, 与庄生共舞, 揣摩逼近庄生的鱼, 兔, 意图, 意念, 雄辩与才华, 对"庄子"进行解说与阐释, 交映生辉.

本书就文化哲学的核心问题文明论,对法兰克福学派理论研究,强调其学派文明论的重要性,论述其学派对启蒙精神、文化工业、合法化危机的批判等。.

本书着眼于人与文化,运用马克思人学理论和文化类型理论对中国传统走向现代的社会变革和人的存在进行了深入的理论分析,不仅从人的活动及其目的、人的自我及其实现、现代人的自我实现之路三大层在展开对中国现代化过 程的探讨.

Self-serving leadership is a form of unethical leadership behavior that has destructive effect on its targets and the overall organization. Adopting a social cognition perspective, this study expands our knowledge of its adverse effect and the way to mitigate the effect. Integrating two sub-theories of social cognition, we propose a theoretical model wherein self-serving leadership hinders team creativity through psychological safety as well as knowledge hiding, with task interdependence acting as a contextual condition. Results from a sample of 107 R&D (...) teams revealed that self-serving leadership not only reduced team psychological safety, but also induced team knowledge hiding, both of which ultimately affected team creativity. The presence of high task interdependence buffered the destructive effect of self-serving leadership on team creativity via team psychological safety as well as the indirect effect via knowledge hiding. (shrink)

The popularization of intelligent machines such as service robot and industrial robot will make human–machine interaction, an essential work mode. This requires employees to adapt to the new work content through learning. However, the research involved human–machine interaction that how influences the employee’s learning is still rarely. This paper was to reveal the relationship between human–machine interaction and employee’s learning from the perspective of job characteristics and competence perception of employees. We sent questionnaire to 500 employees from 100 artificial intelligence (...) companies in China and received 319 valid and complete responses. Then, we adopted a hierarchical regression for the test. Empirical results show that human–machine interaction has a U-shaped curvilinear relationship with employee learning, and employee’s vitality mediates the curvilinear relationship. In addition, job characteristics moderate the U-shaped curvilinear relationship between human–machine interaction and employee’s vitality, especially the results of moderating effects varying with employee’s competence perception. Exploring the mechanism of the effect of human–machine interaction on employee’s learning enriches the socially embedded model. Moreover, it provides managerial implications how to enhance individual adaptability with the introduction of AI into firms. However, our research focuses more on the impact of human–machine interaction on employees at the initial stage of AI development, and the level of machine intelligence in various industries will reach a high degree of autonomy in the future. The future research can explore the impact of human–machine interaction on individual’s behavior at different stages, and the results may vary depending on the technologies mastered by different individuals. The study has theoretical and practical significance to human–machine interaction literature by underscoring the important of individual’s behavior among individuals with different skills. (shrink)

人学思想是儒家思想的价值核心。本书以殷周至春秋时期人学思想发展的萌芽阶段为铺垫,重点探讨了孔孟荀学庸易的人学思想特征。.

Punishment is fundamental to the evolution of cooperative norms in teams, organizations, and societies. Based on findings that people are faster when punishing others (relative to when withholding punishment), dual-process theories of punishment assert that humans have an intuitive tendency to punish, which requires effortful deliberation to overcome. Here, we propose an alternative single-process theory that models punishment decisions as a sequential sampling process. We provide supporting evidence for this theory using a public goods game experiment that experimentally manipulates the (...) cost–benefit tradeoff across the game. We show that people are not systematically faster when punishing (versus withholding) across tradeoffs. We also find an inverted-U-shaped relationship between response times and the strength of preferences for punishing, and a negative association between punishment rates and the relative speed of punishment across individuals. Further computational analysis using the drift–diffusion model (DDM) reveals that, on average, people exhibit a pre-disposition to withhold punishment. Our study provides a unified single-process framework for studying the micro-foundations of punishment and integrating process measures to better describe and predict behavior. (shrink)

The demand for ethical fashion products has grown in recent years, with consumers caring more about how the product is made. Based on the deontological underpinnings of ethical fashion, the present research provides recommendations to ethical fashion brands by leveraging the emotion of awe through visual representations. This research examines 5362 Instagram posts of five ethical fashion brands and shows that the presence of awe-inspiring visual elements increases consumer engagement on social media for ethical fashion brands. Further, this research identifies (...) the moderating roles of the color green and the size of the visual elements in this context. Two follow-up experiments provide causal evidence for these relationships. Experimental evidence for the role of deontological beliefs as a mediator of the relationship between feelings of awe and social media engagement with ethical fashion brands is also provided. Overall, the findings offer a more nuanced understanding of how ethical fashion brands can develop effective visual advertising campaigns on social media and the underlying process driving the effect, which is consistent with deontological ethics. (shrink)

Ethical decision-making is central to the practice of construction engineering and management. This is no more evident than in the twenty-first century, when the construction industry must function in very diverse organizational contexts. Whilst construction companies pursue projects in international markets, many investors are buying or forming joint ventures with domestic companies. New and varied professional attitudes have recently arrived in western markets such as the United States and Australia because construction companies are increasingly employing managers from developing nations to (...) undertake commercial and infrastructure engineering projects. In many developing countries the construction industry is vulnerable to unethical behavior or corruption – vulnerability in part because of differences in culture and managerial systems across countries; and this diversity is manifest in the different perspectives of professional ethics and professional practice. Importantly, professionals in construction engineering must be aware of these differences; however current ethics education for engineering professionals generally lacks global components. In this chapter, emphasis is placed upon professional registration, including mandatory awareness of professional ethics, as an imperative for the welfare of world citizens; discussion on the nature of the construction industry and globalized trends emphasizes why ethics and professional education must be integrated within civil and construction engineering and management curricula. Only then we can anticipate an appropriate educational foundation for professional registration of the international engineer. (shrink)

The innovation of the deep learning modeling scheme plays an important role in promoting the research of complex problems handled with artificial intelligence in smart cities and the development of the next generation of information technology. With the widespread use of smart interactive devices and systems, the exponential growth of data volume and the complex modeling requirements increase the difficulty of deep learning modeling, and the classical centralized deep learning modeling scheme has encountered bottlenecks in the improvement of model performance (...) and the diversification of smart application scenarios. The parallel processing system in deep learning links the virtual information space with the physical world, although the distributed deep learning research has become a crucial concern with its unique advantages in training efficiency, and improving the availability of trained models and preventing privacy disclosure are still the main challenges faced by related research. To address these above issues in distributed deep learning, this research developed a clonal selective optimization system based on the federated learning framework for the model training process involving large-scale data. This system adopts the heuristic clonal selective strategy in local model optimization and optimizes the effect of federated training. First of all, this process enhances the adaptability and robustness of the federated learning scheme and improves the modeling performance and training efficiency. Furthermore, this research attempts to improve the privacy security defense capability of the federated learning scheme for big data through differential privacy preprocessing. The simulation results show that the proposed clonal selection optimization system based on federated learning has significant optimization ability on model basic performance, stability, and privacy. (shrink)

Patients requiring deep brain stimulation due to intracerebral metallic foreign substances have not been reported elsewhere in the world. Additionally, the long-term effects of metallic foreign bodies on deep brain stimulation are unknown. A 79-year-old man with a 5-year history of Parkinson's disease reported that, 40 years ago, while playing with a pistol, a metallic bullet was accidentally discharged into the left brain through the edge of the left eye, causing no discomfort other than blurry vision in the left eye. (...) DBS was performed due to the short duration of efficacy for oral medication. Because the bullet was on the left subthalamic nucleus electrode trajectory and the patient's right limb was primarily stiff, the patient received globus pallidus interna -DBS implantation in the left hemisphere and STN-DBS implantation in the right hemisphere. During a 6-month postoperative follow-up, the patient's PD symptoms were effectively managed with no noticeable discomfort. (shrink)

Bayesian networks can be employed to cognitive diagnostic assessment. Most of the existing researches on the BNs for CDA utilized the MCMC algorithm to estimate parameters of BNs. When EM algorithm and gradient descending learning method are adopted to estimate the parameters of BNs, some challenges may emerge in educational assessment due to the monotonic constraints cannot be satisfied in the above two methods. This paper proposed to train the BN first based on the ideal response pattern data contained in (...) every CDA and continue to estimate the parameters of BN based on the EM or the GD algorithm regarding the parameters based on the IRP training method as informative priors. Both the simulation study and realistic data analysis demonstrated the validity and feasibility of the new method. The BN based on the new parameter estimating method exhibits promising statistical classification performance and even outperforms the G-DINA model in some conditions. (shrink)

With a focus in the financial market, stock market dynamics forecasting has received much attention. Predicting stock market fluctuations is usually challenging due to the nonlinear and nonstationary time series of stock prices. The Elman recurrent network is renowned for its capability of dealing with dynamic information, which has made it a successful application to predicting. We developed a hybrid approach which combined Elman recurrent network with factorization machine technique, i.e., the FM-Elman neural network, to predict stock market volatility. In (...) this paper, the Standard & Poor’s 500 Composite Stock Price index, the Dow Jones industrial average index, the Shanghai Stock Exchange Composite index, and the Shenzhen Securities Component Index were used to demonstrate the validity of our proposed FM-Elman model in time-series prediction. The results were compared with predictions obtained from the other two models which are basic BP neural network and the Elman neural network. Some experiments showed that the FM-Elman model outperforms others through different accuracy measures. Furthermore, the effects of volatility degree on prediction performance from different stock indexes were investigated. An interesting phenomenon had been found through some numerical experiments on the effects of different user-specified dimensions on the proposed FM-Elman neural network. (shrink)

This paper presents an active fault-tolerant control strategy for quadrotor helicopters to simultaneously accommodate sensor faults and external disturbances. Unlike most of the existing fault diagnosis and fault-tolerant control schemes for quadrotor helicopters, the proposed fault diagnosis scheme is able to estimate sensor faults while eliminating the effect of external disturbances. Moreover, the proposed fault-tolerant control scheme is capable to eliminate the adverse effect of external disturbances as well by designing a disturbance observer to effectively estimate the unknown external disturbances (...) and integrating with the designed integral sliding-mode controller. In this case, the continuous operation of the quadrotor helicopter is ensured while avoiding the unexpected control chattering. In addition, the stability of the closed-loop system is theoretically proved. Finally, the effectiveness and advantages of the proposed scheme are validated and demonstrated through comparative numerical simulations of the quadrotor helicopter under different faulty and uncertain scenarios. (shrink)

Bastin and colleagues present an integrative model of how recollection- and familiarity-based memories are represented in the brain. While they emphasize the role of attribution mechanisms in shaping memory retrieval, prior work examining implicit memory suggests that memory deficits may be better understood by separating attributional biases from the underlying memory traces.

阐述人作为主体和自然作为客体的认同,人与自然之间在形体结构、情感意志、伦理道德有一种相通和类似的关系的美学观点和源流。.