This article argues that consent must be revocable. I present two arguments for this conclusion. On the argument from informed consent, irrevocable consent lacks validity because it cannot be sufficiently informed. On the argument from bodily integrity, irrevocable consent lacks validity because we do not have the authority to deny our future selves the ability to protect our bodily integrity. I explain why the argument from bodily integrity captures unique moral problems raised by irrevocable consent and illuminates an important but (...) undertheorized distinction between autonomy and bodily integrity. (shrink)

This study examined how vocabulary, syntactic knowledge, and orthographic knowledge are related to comprehension monitoring and whether comprehension monitoring mediates the relations between these language skills and reading comprehension. Eighty-nine Chinese children were assessed on their vocabulary, syntactic knowledge, orthographic knowledge, and comprehension monitoring in Grade 1. Their reading comprehension skills were assessed in Grade 1 and Grade 3. Results showed that in Grade 1, comprehension monitoring mediated the relations between vocabulary and syntactic knowledge and reading comprehension. For Grade 3 (...) reading comprehension, syntactic knowledge in Grade 1 was the only significant predictor. These findings indicate that multiple language skills make direct and indirect contributionsviacomprehension monitoring to Chinese reading comprehension, and the relations would change as children’s reading skills develop. (shrink)

There has been much research into teacher beliefs about teaching and learning as seen in the general teacher education literature. In the field of language teacher education, this line of research has been evolving, with the recent trend being streamlined into “teacher cognition” as a generic or umbrella term. Despite increasing amounts of research output so far, research into foreign language teachers’ cognitions about their own teaching and decision-making is still insufficient, particularly with regard to university-level English-as-a-foreign-language (EFL) teachers in (...) China. Drawing on Vygotsky’s Sociocultural Theory, this qualitative research focused on EFL teachers’ cognitions about form-focused instruction in Chinese university settings. It intended to discover how teachers’ cognitions changed when they were expected to teach in actual classrooms and what factors contributed to these changes. Data collected from four teacher-participants through semi-structured interviews, classroom observations and follow-up stimulated recall interviews showed participants’ support forfocus-on-forminstruction, which means they not only paid attention to the grammatical form of the language but also to the meaning it is intended to convey. However, data also showed that the teacher-participants shifted fromfocus-on-formtofocus-on-formSinstruction in actual teaching, which suggests that they might have realized the challenges of carrying out teaching activities surroundingfocus-on-formand would like to take an easier approach by only teaching the grammar of the language byfocusing on formS. Such incongruences are interpreted with reference to a plethora of sociocultural factors including traditional Chinese thinking and institutional expectations. The implications of the findings for stakeholders in universities, including faculty members, students, and curriculum developers in similar contexts, are also discussed. (shrink)

In 2001, China’s moral education curriculum reform called for a returning to life as a radical shift from its previous empty sermonic pedagogy, hoping to cultivate its twenty-first century children into ethical humans. Accordingly, a notion of ‘human ecology’ appeared in the post-2001 textbook design, which became ‘co-being with’ in the latest 2016 textbook redesign. This paper picks up this co-being with as a philosophical, ethical, and ecological notion and scrutinizes its relevance to the discursive construction of China’s moral child (...) in two steps. First, it draws upon Heidegger’s thinking and the Chinese Daoist ecological understanding to explicate the philosophical significance of this ‘co-being with’ for moral education. Second, it unpacks the discursive embodiments of this ethical–ecological co-being with in connection with the construction of moral subjects in the post-2001 and 2016 textbooks. Through rigorous textual analysis, this paper finds that the post-2001 textbook discourses embody an instrumental trope and a subject vs object binary style of reasoning, which possibly makes egoistic rather than ethical children. The 2016 textbook discourses, especially those on the theme of co-being with, however, constrain the above instrumentality and envision cultivating ethical children. This paper argues this theorized co-being with provides some implications for moral education in China and the world, meanwhile raising some pedagogical challenges as well. (shrink)

With the increasing level of internationalization in higher education, the number of international students in mainland China is rapidly increasing. However, limited research has considered that student results may be affected by a reduced motivation to learn. Therefore, the aim of this research is to explore the effect of the learning motivation on the learning outcomes of international students and the moderating role of learning experience. A sample of 130 international students from 23 countries studying in mainland China was analyzed. (...) The study found a significant correlation between the learning motivations and international students' learning outcomes. It was also determined that learning experience has significantly enhances the relationship between learning motivation and the learning outcomes of international students. This study contributes to the higher education literature of on learning motivation by students and learning outcomes. (shrink)

This paper argues for an explanation of the mechanistic (computational) basis of consciousness that is based on the distinction between localist (symbolic) representation and distributed representation, the ideas of which have been put forth in the connectionist literature. A model is developed to substantiate and test this approach. The paper also explores the issue of the functional roles of consciousness, in relation to the proposed mechanistic explanation of consciousness. The model, embodying the representational difference, is able to account for the (...) functional role of consciousness, in the form of the synergy between the conscious and the unconscious. The fit between the model and various cognitive phenomena and data (documented in the psychological literatures) is discussed to accentuate the plausibility of the model and its explanation of consciousness. Comparisons with existing models of consciousness are made in the end. (shrink)

This paper introduces a hybrid model that unifies connectionist, symbolic, and reinforcement learning into an integrated architecture for bottom-up skill learning in reactive sequential decision tasks. The model is designed for an agent to learn continuously from on-going experience in the world, without the use of preconceived concepts and knowledge. Both procedural skills and high-level knowledge are acquired through an agent’s experience interacting with the world. Computational experiments with the model in two domains are reported.

Eye-tracking technology has become a powerful tool for biomedical-related applications due to its simplicity of operation and low requirements on patient language skills. This study aims to use the machine-learning models and deep-learning networks to identify key features of eye movements in Alzheimer's Disease (AD) under specific visual tasks, thereby facilitating computer-aided diagnosis of AD. Firstly, a three-dimensional (3D) visuospatial memory task is designed to provide participants with visual stimuli while their eye-movement data are recorded and used to build an (...) eye-tracking dataset. Then, we propose a novel deep-learning-based model for identifying patients with Alzheimer's Disease (PwAD) and healthy controls (HCs) based on the collected eye-movement data. The proposed model utilizes a nested autoencoder network to extract the eye-movement features from the generated fixation heatmaps and a weight adaptive network layer for the feature fusion, which can preserve as much useful information as possible for the final binary classification. To fully verify the performance of the proposed model, we also design two types of models based on traditional machine-learning and typical deep-learning for comparison. Furthermore, we have also done ablation experiments to verify the effectiveness of each module of the proposed network. Finally, these models are evaluated by four-fold cross-validation on the built eye-tracking dataset. The proposed model shows 85% average accuracy in AD recognition, outperforming machine-learning methods and other typical deep-learning networks. (shrink)

With the increasing proportion of the logistics industry in the economy, the study of the vehicle routing problem has practical significance for economic development. Based on the vehicle routing problem, the customer presence probability data are introduced as an uncertain random parameter, and the VRP model of uncertain customers is established. By optimizing the robust uncertainty model, combined with a data-driven kernel density estimation method, the distribution feature set of historical data samples can then be fitted, and finally, a distributed (...) robust vehicle routing model for uncertain customers is established. The Q-learning algorithm in reinforcement learning is introduced into the high-level selection strategy using the hyper-heuristic algorithm, and a hyper-heuristic algorithm based on the Q-learning algorithm is designed to solve the problem. Compared with the certain method, the distributed robust model can effectively reduce the total cost and the robust conservatism while ensuring customer satisfaction. The improved algorithm also has good performance. (shrink)

ABSTRACTUsing faces as the priming stimuli, the present study explored the influence of facial expressions on the activation of gender stereotypes using a lexical decision paradigm. Experiment 1 explored the activation of gender stereotypes when the facial primes contained only gender information. The results showed that gender stereotypes were activated. In Experiment 2, the facial primes contained both gender category and expression information. The results indicated that gender stereotypes were not activated. Experiment 3 required the participants to make emotion, gender, (...) or impression decisions concerning the facial primes before the lexical decision task. The results showed that gender stereotypes were not activated in emotion and impression decisions conditions, whereas stereotypes were activated in gender decisions condition. These finding suggest that facial expressions can inhibit automatic activation of gender stereotypes, unless the perceivers perform gender categorization processing to prime f... (shrink)

Travelling waves crossing the nervous networks at mesoscopic/macroscopic scales have been correlated with different brain functions, from long-term memory to visual stimuli. Here we investigate a feasible relationship between wave generation/propagation in recurrent nervous networks and a physical/chemical model, namely the Belousov–Zhabotinsky reaction. Since BZ’s nonlinear, chaotic chemical process generates concentric/intersecting waves that closely resemble the diffusive nonlinear/chaotic oscillatory patterns crossing the nervous tissue, we aimed to investigate whether wave propagation of brain oscillations could be described in terms of BZ (...) features. We compared experimentally detected oscillations during the spontaneous activity of the brain with BZ-like concentric waves simulated by a recently introduced artificial network. The observed overlap and agreement between simulated and measured oscillatory patterns suggests that changes in cortical areas’ neural activity might be described in terms of a recognizable diffusion pattern. We describe biological plausibility, benefits and limits of our approach and discuss the relationship among BZ-like networks, Pandemonium-like architectures and the spontaneous activity of the brain. ER -. (shrink)

The wanton dissemination of network pseudohealth information has brought great harm to people’s health, life, and property. It is important to detect and identify network pseudohealth information. Based on this, this paper defines the concepts of pseudohealth information, data block, and data block integration, designs an architecture that combines the latent Dirichlet allocation algorithm and data block update integration, and proposes the combination algorithm model. In addition, crawler technology is used to crawl the pseudohealth information transmitted on the Sina Weibo (...) platform during the “epidemic situation” from February to March 2020 for the simulation test on the experimental case dataset. The research results show that the LDA model can deeply mine the semantic information of network pseudohealth information, obtain the features of document-topic distribution, and classify and train topic features as input variables; the dataset partitioning method can effectively block data according to the text attributes and class labels of network pseudohealth information and can accurately classify and integrate the block data through the data block reintegration method; and considering that the combination model has certain limitations on the detection of network pseudohealth information, the support vector machine model can extract the granularity content of data blocks in pseudohealth information in real time, thus greatly improving the recognition performance of the combination model. (shrink)

Aiming at the problem that the embedded platform cannot meet the real-time detection of multisource images, this paper proposes a lightweight target detection network MNYOLO suitable for embedded platforms using deep separable convolution instead of standard convolution to reduce the number of model parameters and calculations; at the same time, the visible light target detection model is used as the pretraining model of the infrared target detection model and the infrared target data set collected on the spot is fine-tuned to (...) obtain the infrared target detection model. On this basis, a decision-level fusion detection model is obtained to realize the complementary information of infrared and visible light multiband information. The experimental results show that it has a more obvious advantage in detection accuracy than the single-band target detection model while the decision-level fusion target detection model meets the real-time requirements and also verifies the effectiveness of the above algorithm. (shrink)

Although substantial evidence demonstrates that directing attention to specific items is important for improving the performance of visual working memory, it is still not clear whether the attended items were better protected. The present study, thus, adopted a pre-cueing paradigm to examine the effect of attention direction and perceptual distractor on VWM. The results showed that a valid visual cue improved the individuals’ VWM performances and reduced their reaction time compared to the invalid and neutral cues. However, the VWM performances (...) in the valid and neutral cue conditions were more disrupted by a post-stimuli distractor compared to the invalid cue condition. The findings suggest that although directing attention can improve the VWM performance, it is not efficient in protecting information from being distracted. (shrink)

Computational cognitive models hypothesize internal mental processes of human cognitive activities and express such activities by computer programs Such computational models often consist of many components and aspects Claims are often made that certain aspects of the models play a key role in modeling but such claims are sometimes not well justi ed or explored In this paper we rst review some fundamental distinctions and issues in computational modeling We then discuss in principle systematic ways of identifying the source of (...) power in the models.. (shrink)

This paper explores an approach for autonomous generation of symbolic representations from an agent's subsymbolic activities within the agent-environment interaction. The paper describes a psychologically plausible general framework and its various methods for autonomously creating symbolic representations. The symbol generation is accomplished within, and is intrinsic to, a generic and comprehensive cognitive architecture for capturing a wide variety of psychological processes (namely, CLARION). This work points to ways of obtaining more psychologically/cognitively realistic symbolic and subsymbolic representations within the framework of (...) a cognitive architecture, and accentuates the relevance of such an approach to cognitive science and psychology. (shrink)

With the rapid development of contemporary social economy and the relative stability of the political situation, art has also developed rapidly. But currently, there are many unique and innovative art works in society, and the style and theme of the works are increasingly deviating from people's lives. In response to this issue, this study attempts to analyze the reflective spirit and tragic consciousness in "Scar Art" works from a realistic perspective. The research adopted comparative and image analysis methods to compare (...) the stylistic differences between Chinese scar art and other schools of art, using representative painters' oil paintings as samples to analyze the inner diameter, techniques, emotions, and visual expression of their creations. The objective was to provide reflection and inspiration for the current Chinese art community through the analysis of the realism spirit contained in the "scar art" works that bring profound value to the Chinese art community. In response to the current problem of oil painting creation being detached from people's lives, this study analyzes the artistic characteristics of scar art works and the expectations of reflecting the characteristics of the times, providing inspiration for modern art creation. The study found out that realism spirit in "scar art" is based on the principle of objectively reflecting the current era and society, paying attention to the spirit of people's lives, which is also what the current development of art needs to consider. (shrink)

Cross-sector relationship building is an important strategy in corporate social responsibility initiatives, and communicating cross-sector relationships on social media can help raise the visibility of collaborative relationships. A noticeable gap in the literature is how social media enables and constrains the formation patterns of cross-sector connections. To understand how businesses communicate their relationships with government agencies and nonprofits about social issues on social media, we propose a theoretical framework that centers public attention as a critical resource and considers different sectors' (...) interests in the COVID-19 issue. We tested this framework with a nationally representative sample of 1,980 organizations on Twitter. The analysis reveals that the increase in public attention to the COVID-19 issue was accompanied by a greater likelihood of cross-sector ties. Specifically, firms severely affected by COVID-19 were more likely to build ties with government agencies, and the increase in public attention also drove firms to build more ties with nonprofits, especially advocacy nonprofits. Our findings suggest managers of social media communication should observe the volatile public attention and design communicative strategies accordingly. (shrink)

We believe that the distinction between procedural and declarative knowledge unnecessarily confounds two issues: action-centeredness and accessibility, and can be made clearer through separating the two aspects. The work presents an integrated model of skill learning that takes into account both implicit and explicit processes and both action-centered and non-action-centered knowledge. We examine and simulate human data in the Letter Counting task. The work shows how the data may be captured using either the action-centered knowledge alone or the combined action-centered (...) and non-action-centered knowledge. The results provide a new perspective on skill learning. (shrink)

This book aims to understand human cognition and psychology through a comprehensive computational theory of the mind, namely, a "cognitive architecture.".

The Dong costume patterns in Qiandongnan have a long history and distinctive regional cultural characteristics, and their patterns contain high cultural and emotional values. Nowadays, the development of traditional patterns and cultural symbols of Dong costumes is facing many new challenges, which require expanding the application carriers of the patterns and giving them a new life. This is the value of inheritance, revitalization, and innovation of costume patterns, as well as a new direction for the development of Dong traditional costume (...) patterns. In this thesis, the origin, connotation, and cultural symbols of Dong costumes in Qiandongnan are studied in depth, aiming to explore their role in Dong's cultural inheritance. Through the historical tracing and cultural connotation analysis of Dong costumes, we find that they are not only a decorative tool but also a vivid expression of Dong culture relying on the profound historical background. Through the comprehensive study of Dong costumes, the cultural heritage of traditional patterns of Dong costumes not only provides strong support for the cultural inheritance of the Dong people but also provides useful inspiration for the protection and inheritance of other ethnic cultures. By strengthening the cognition and dissemination of cultural symbols, we are expected to promote exchanges between different cultures and realize communal development. (shrink)

In the physical sciences a rigorous theory is a hierarchy of descriptions in which causal relationships between many general types of entity at a phenomenological level can be derived from causal relationships between smaller numbers of simpler entities at more detailed levels. The hierarchy of descriptions resembles the modular hierarchy created in electronic systems in order to be able to modify a complex functionality without excessive side effects. Such a hierarchy would make it possible to establish a rigorous scientific theory (...) of consciousness. The causal relationships implicit in definitions of access consciousness and phe- nomenal consciousness are made explicit, and the corresponding causal relationships at the more detailed levels of perception, memory, and skill learning described. Extension of these causal relationships to physiological and neural levels is discussed. The general capability of a range of current consciousness models to support a modular hierarchy which could generate these causal relationships is reviewed, and the specific capabilities of two models with good general capabilities are compared in some detail. Ó 2003 Elsevier Inc. All rights reserved. (shrink)

The field of artificial intelligence (AI) can be characterized as the investigation of computational systems that exhibit intelligent behavior (including algorithms and models used in these systems). The emphasis is not so much on understanding (human) cognitive processes as on producing models, algorithms, and systems that are capable of apparently intelligent behavior by whatever means available. The idea of AI has had a long history that can be traced all the way back to, for example, Leibniz. The idea was furthered (...) through the development, early in this century, of mathematical logic, cybernetics, and information theory, all of which contributed to AI theorizing. Alan Turing's bold claim that machines can think, advanced in his famous 1950 paper, and the “Turing test” he proposed therein as a means to test the intelligence of machines predated and prompted the formation of AI. Six years later, the Dartmouth conference in 1956, the participants of which included Allen Newell, Herbert Simon, Marvin Minsky, and John McCarthy, inaugurated AI as an academic discipline. This contemporary version of AI was facilitated by the invention and rapidly widening use of digital computers. AI embodies an extremely diverse set of ideas that are often mutually conflicting (as in the case of symbolism versus connectionism), and its relationship with other fields studying cognition (such as psychology and linguistics) has been a close but uneasy one. (shrink)

This work explores the importance of similarity-based processes in human everyday reasoning, beyond purely rule-based processes prevalent in AI and cognitive science. A unified framework encompassing both rulebased and similarity-based reasoning may provide explanations for a variety of human reasoning data.

Extreme events, which are usually characterized by generalized extreme value models, can exhibit long-term memory, whose impact needs to be quantified. It was known that extreme recurrence intervals can better characterize the significant influence of long-term memory than using the GEV model. Our statistical analyses based on time series datasets following the Lévy stable distribution confirm that the stretched exponential distribution can describe a wide spectrum of memory behavior transition from exponentially distributed intervals to power-law distributed ones, extending the previous (...) evaluation of the stretched exponential function using Gaussian/exponential distributed random data. Further deviation and discussion of a historical paradox are also provided, based on the theoretical analysis of the Bayesian law and the stretched exponential distribution. (shrink)

Previous studies of the lexical psycholinguistic properties in second language production have assessed the degree of an LPP dimension of an L2 corpus by computing the mean ratings of unique content words in the corpus for that dimension, without considering the possibility that learners at different proficiency levels may perceive the degree of that dimension of the same words differently. This study extended a dynamic semantic similarity algorithm to estimate the degree of five different LPP dimensions of several sub-corpora of (...) the Education First-Cambridge Open Language Database representing L2 English learners at different proficiency levels. Our findings provide initial evidence for the validity of the algorithm for assessing the LPPs in L2 production and contribute useful insights into between-proficiency relationships and cross-proficiency differences in the LPPs in L2 production as well as the relationships among different LPP dimensions. (shrink)

The traditional understanding of corporate social responsibility (CSR) has largely been focused on its downstream performance implications, particularly its associations with firms’ customer market metrics such as customer loyalty, customer satisfaction and customer co-creation as well as financial ones such as firm value, return on assets etc. However, given the close relationship between CSR and marketing that literature has identified, it is surprising that the relationship between a focal upstream construct, i.e. the marketing function’s power within a firm and the (...) firm’s propensity toward CSR has not been addressed in the literature. Examining the link between marketing’s power (MP) in a firm’s top management team (TMT) and firm CSR levels, we investigate how this fundamental TMT configuration, i.e. the distribution of marketing power in the TMT, motivates the firm’s social endeavors. Further, we formulate this relationship in a contingency-based model that incorporates the moderating effects of firm size, firm age, service intensity, and resource slack across 1569 firms operating in 63 industries. In addition to their effect on CSR, this study shows how MP in TMT may influence corporate social irresponsibility (CSI) as well as CSR capability after controlling for industry type. The inclusion on these additional dimensions of CSR (CSI and CSR capability) complements our analyses of the effect that MP has on CSR. The research contributes to a deeper understanding of CSR’s fundamental corporate determinants as well as identifies the essential role of the marketing function in firms’ CSR strategy. In this process, it yields useful implications for multiple streams of theory as well as for business practices. (shrink)

The large scale, time varying, and diversification of physically coupled networked infrastructures such as power grid and transportation system lead to the complexity of their controller design, implementation, and expansion. For tackling these challenges, we suggest an online distributed reinforcement learning control algorithm with the one-layer neural network for each subsystem or called agents to adapt the variation of the networked infrastructures. Each controller includes a critic network and action network for approximating strategy utility function and desired control law, respectively. (...) For avoiding a large number of trials and improving the stability, the training of action network introduces supervised learning mechanisms into reduction of long-term cost. The stability of the control system with learning algorithm is analyzed; the upper bound of the tracking error and neural network weights are also estimated. The effectiveness of our proposed controller is illustrated in the simulation; the results indicate the stability under communication delay and disturbances as well. (shrink)

Live commerce is a phenomenally innovative form of social commerce in China. In this paper, the authors aim to explore the authenticity of live commerce. By employing a qualitative approach using in-depth interviews and grounded theory, 21 initial categories are classified into six core categories. Among them, authenticity-associated concepts are classified into explicit concepts and implicit concepts. Explicit concepts of authenticity are associated with objectively authentic cues, while implicit concepts of authenticity are associated with subjectively authentic experiences. Moreover, the study (...) explores the relationship between explicit concepts of authenticity and product commitment, as well as the relationship between implicit concepts of authenticity and affective commitment. Both of these paths are found to influence consumers' shopping-related behaviors. Although consumers can more easily perceive explicitly authentic cues than implicitly authentic experiences, this study suggests that the latter may be more effective in inducing shopping behaviors. In addition, the effect of streamer attractiveness on opinion leader building is addressed, while authenticity is found to be an alternative approach to attract consumers both for attractive and nonattractive streamers. Finally, the study addresses theoretical implications and practical implications as well as suggestions for future research. (shrink)

In order to improve the integrity of the social network behavior feature extraction results for sports college students, this study proposes to be based on the clustering algorithm. This study analyzes the social network information dissemination mechanism in the field of college students’ sports, obtains the real-time social behavior data in the network environment combined with the analysis results, and processes the obtained social network behavior data from two aspects of data cleaning and de-duplication. Using clustering algorithm to determine the (...) type of social network user behavior, setting the characteristics of social network behavior attributes, and finally through quantitative and standardized processing, get the results of college students’ sports field social network behavior characteristics extraction. The experimental results showed that the completeness of the method feature extraction results improved to 9.93%, and the average extraction time cost was 0.344 s, with high result integrity and obvious advantages in the extraction speed. (shrink)

We believe that when assessing the likelihood of uncertain events, statistically unsophisticated people utilize a coarse internal scale that only has a limited number of categories. The success of the nested sets hypothesis may lie in its ability to provide an appropriate set structure of the problem by reducing the computational demands.