Much of the current work on AI ethics has lost its connection to the real-world impact by making AI ethics operable. There exist significant limitations of hyper-focusing on the identification of abstract ethical principles, lacking effective collaboration among stakeholders, and lacking the communication of ethical principles to real-world applications. This position paper presents challenges in making AI ethics operable and highlights key obstacles to AI ethics impact. A preliminary practice example is provided to initiate practical implementations of AI ethics. We (...) aim to inspire discussions on making AI ethics operable and focus on its impact on real-world applications. (shrink)

Pseudo-clefts are the building blocks of coherent discourse progression and serve as a rhetorical toolkit to construct an authorial stance in the academic discourse. Despite an increasing interest in grammatical constructions in the academic discourse, researchers have not treated pseudo-clefts in much detail. This paper explores the features of pseudo-clefts in the corpus of academic discourse in the field of applied linguistics. Here, we take the textual and the interpersonal perspectives, focusing on the use of pseudo-clefts in terms of their (...) distribution in generic structure, discourse functions with reference to clefted constituents, and evaluative meaning. The results show that pseudo-clefts were more frequently used in “Results and Discussion” and Literature Review, performing the functions such as the specification of key terms, generalization of the literature, the description and explanation of findings, etc. They are facilitative in creating information gaps and establishing a logic-semantic expansive relationship between the clauses. The findings also suggest that the pseudo-clefts are evaluative devices and are involved in the construction of authorial identities. (shrink)

Registration of a series of the two-dimensional electron microscope images of the brain tissue into volumetric form is an important technique that can be used for neuronal circuit reconstruction. However, complex appearance changes of neuronal morphology in adjacent sections bring difficulty in finding correct correspondences, making serial section neural image registration challenging. To solve this problem, we consider whether there are such stable "markers" in the neural images to alleviate registration difficulty. In this paper, we employ the spherical deformation model (...) to simulate the local neuron structure and analyze the relationship between registration accuracy and neuronal structure shapes in two adjacent sections. The relevant analysis proves that regular circular structures in the section images are instrumental in seeking robust corresponding relationships. Then, we design a new serial section image registration framework driven by this neuronal morphological model, fully utilizing the characteristics of the anatomical structure of nerve tissue and obtaining more reasonable corresponding relationships. Specifically, we leverage a deep membrane segmentation network and neural morphological physical selection model to select the stable rounded regions in neural images. Then, we combine feature extraction and global optimization of correspondence position to obtain the deformation field of multiple images. Experiments on real and synthetic serial EM section neural image datasets have demonstrated that our proposed method could achieve more reasonable and reliable registration results, outperforming the state-of-the-art approaches in qualitative and quantitative analysis. (shrink)

Happiness is the eternal pursuit of mankind and is also the ultimate goal of social governance and national development. Based on data from the Chinese General Social Survey, this study used a structural equation model to analyze the influence of social class identity and public service satisfaction on the happiness of residents. The effect of public service satisfaction and social trust between social class identity and residents’ happiness was tested using the Monte Carlo method. The empirical results show that social (...) class identity, social trust, and public service satisfaction all had a significant positive impact on residents’ happiness. The influence coefficients of social class identity on the happiness of residents and on the satisfaction degree of public service for those born in the1970s group were greater than the 1980s and 1990s groups. The influence coefficients of social class identity on the happiness and public service satisfaction of non-agricultural household residents were greater than those of agricultural household residents. Therefore, to improve the happiness of residents, we should make new breakthroughs in the equality of quality and the quality of public services, promote the integration of urban and rural areas, highlight key areas of rural development, and increase the construction of basic public services for agricultural household residents. (shrink)

The social network in the organizational learning process is a critical knowledge source to realize superior performance. The purpose of this study is to examine the relationship between relational memory, relational embeddedness, and absorptive capacity, and their impact on the relational performance of small and middle enterprises. This study empirically verifies the research framework from 223 Chinese internationalized SMEs. The results confirm previous studies that indicate positive correlations among relational embeddedness, relational memory, and absorptive capacity. The results also indicate that (...) relational embeddedness and relational memory have positive effects on relational performance. The findings show that relational memory plays a mediating role in the relationship between relational embeddedness, absorptive capacity, and relational performance. (shrink)

The aim of this study was to explore the influence of different intensities of acute aerobic exercise on brain activation in male methamphetamine -dependent patients during exercise. Twenty MA-dependent patients were divided randomly into two groups participating in 35 min of either moderate- or high-intensity aerobic exercise. Functional near-infrared spectral imaging was used to detect hemodynamic changes in prefrontal cortex during the main 25-min exercise stage. The results revealed that high-intensity acute aerobic exercise aroused more cerebral oxygenation changes in the (...) prefrontal cortex and left dorsolateral prefrontal cortex during exercise as compared with moderate-intensity exercise. Furthermore, there was a stronger positive connection observed between orbital frontal cortex and left dorsolateral prefrontal cortex in the high-intensity group than in the moderate-intensity group. Together these results suggest that for submaximal exercise intensities, high-intensity exercise may bring more benefits to male MA-dependent patients than moderate-intensity. (shrink)

ObjectiveThe correlation between the performance of coordination movement and brain activity is still not fully understood. The current study aimed to identify activated brain regions and brain network connectivity changes for several coordinated finger movements with different difficulty levels and to correlate the brain hemodynamics and connectivity with kinematic performance.MethodsTwenty-one right-dominant-handed subjects were recruited and asked to complete circular motions of single and bilateral fingers in the same direction and in opposite directions on a plane. Kinematic data including radius and (...) angular velocity at each task and synchronized blood oxygen concentration data using functional near-infrared spectroscopy were recorded covering six brain regions including the prefrontal cortex, motor cortex, and occipital lobes. A general linear model was used to locate activated brain regions, and changes compared with baseline in blood oxygen concentration were used to evaluate the degree of brain region activation. Small-world properties, clustering coefficients, and efficiency were used to measure information interaction in brain activity during the movement.ResultIt was found that the radius error of the dominant hand was significantly lower than that of the non-dominant hand in both clockwise and counterclockwise movements. The fNIRS results confirmed that the contralateral brain region was activated during single finger movement and the dominant motor area was activated in IP movement, while both motor areas were activated simultaneously in AP movement. The Δhbo were weakly correlated with radius errors. Brain information interaction in IP movement was significantly larger than that from AP movement in the brain network in the right prefrontal cortex. Brain activity in the right motor cortex reduces motor performance, while the right prefrontal cortex region promotes it.ConclusionOur results suggest there was a significant correlation between motion performance and brain activation level, as well as between motion deviation and brain functional connectivity. The findings may provide a basis for further exploration of the operation of complex brain networks. (shrink)

Previous research on the detrimental consequences of employees' unethical pro-organizational behaviors (UPB) has been based mainly on cognitive dissonance theory. The authors suggest that moral disengagement theory and cognitive dissonance theory can be used to explain the negative effects of UPB. We conducted two studies, including a scenario experiment and a survey, to test the mediating roles of moral identity and moral disengagement and the moderating role of performance pressure in the relationship between UPB and organizational deviance. The results revealed (...) that UPB impacts organizational deviance through moral identity and moral disengagement and that distinct psychological reactions are differentially moderated by performance pressure. Employees who face low levels of performance pressure are more receptive to the effects of moral identity; in contrast, employees who face high levels of performance pressure are more receptive to the effects of moral disengagement. The theoretical and managerial implications of this research are discussed. (shrink)

ObjectiveThe studies showed the benefits of virtual reality training for functional mobility and balance in older adults. However, a large variance in the study design and results is presented. We, thus, completed a systematic review and meta-analysis to quantitatively examine the effects of VRT on functional mobility and balance in healthy older adults.MethodsWe systematically reviewed the publications in five databases. Studies that examine the effects of VRT on the measures of functional mobility and balance in healthy older adults were screened (...) and included if eligible. Subgroup analyses were completed to explore the effects of different metrics of the intervention design on those outcomes related to functional mobility and balance.ResultsFifteen studies of 704 participants were included. The quality of these studies was good. Compared to traditional physical therapy, VRT induced greater improvement in TUG and one-leg stance with open eyes. Subgroup analyses revealed that immersive VRT with more than 800 min of total intervention time over 8 weeks and at least 120 min per week and/or designed by the two motor-learning principles was optimal for functional mobility and balance.ConclusionVirtual reality training can significantly improve functional mobility and balance in healthy older adults compared to TPT, and the findings provided critical knowledge of the optimized design of VRT that can inform future studies with more rigorous designs.Systematic Review Registration[https://www.crd.york.ac.uk/PROSPERO/], identifier [CRD42021297085]. (shrink)

This research aims to analyze the influencing factors of migrant children’s education integration based on the convolutional neural network algorithm. The attention mechanism, LSTM, and GRU are introduced based on the CNN algorithm, to establish an ALGCNN model for text classification. Film and television review data set, Stanford sentiment data set, and news opinion data set are used to analyze the classification accuracy, loss value, Hamming loss, precision, recall, and micro-F1 of the ALGCNN model. Then, on the big data platform, (...) data in the Comprehensive Management System of Floating Population and Rental Housing, Student Status Information Management System, and Student Information Management System of Beijing city are taken as samples. The ALGCNN model is used to classify and compare related data. It is found that in the MR, STT, and MPQA data sets, the classification accuracy and loss value of the ALGCNN model are better than other algorithms. HL is the lowest, the Pre is second only to the BERT algorithm, and the Re and F1 are both higher than other algorithms. From 2015 to 2019, the number of migrant children in different grades of elementary school shows a gradual increase. Among migrant children, the number of migrant children from other counties in this province is evidently higher than the number of migrant children from other provinces. Among children of migrant workers, the number of immigrants from other counties in this province is also notably higher than the number of immigrants from other provinces. With the gradual increase in the years, the proportion of township-level expenses shows a gradual decrease, whereas the proportion of district and county-level expenses shows a gradual increase. Moreover, the accuracy of the ALGCNN model in migrant children and local children data classification is 98.6 and 98.9%, respectively. The proportion of migrant children in the first and second grades of a primary school in Beijing city is obviously higher than that of local children. The average final score of local children was greatly higher than that of migrant children, whereas the scores of migrant children’s listening methods, learning skills, and learning environment adaptability are lower, which shows that an effective text classification model is established based on the CNN algorithm. In short, the children’s education costs, listening methods, learning skills, and learning environment adaptability are the main factors affecting migrant children’s educational integration, and this work provides a reference for the analysis of migrant children’s educational integration. (shrink)

E-commerce conceivable future trade, consumption, and service is a new digital employer mode. Therefore, in order to decorate the customary natural environment of operation, it is quintessential to get rid of the preferred desktop in the true field, create a social logistics and transportation administration computing device with commodity agents and distributors as the key features, and mix freight logistics, business enterprise approach waft and data waft advertising and marketing, and advertising and marketing organically. The notion of e-commerce logistics looks (...) alongside the enchantment vogue of neighborhood technological knowledge and social demand. It is an integral part of ending e-commerce authentic economic value. All kinds of cell networks clear up the problem of data flow communication; in the technological know-how of telephone network, digital cost solves the bother of capital flow; at present, logistics is however a long-standing problem of e-commerce. Logistics has grown to be the last and entirely bottleneck of e-commerce. If logistics cannot adapt to the enchantment of e-commerce, it may also additionally lead to the slow enchantment of e-commerce. The purpose of this paper is to supply an Internet of things e-commerce logistics cloud provider platform based totally absolutely on cell communication, which can be combined with e-commerce and beautify the transport tempo of e-commerce. This paper moreover optimizes the e-commerce logistics system, so that it can combine with e-commerce to increase out the distribution of goods, the distribution tempo of e-commerce is doubled, and e-commerce can in a similar fashion develop rapidly. (shrink)

Since the outbreak of the novel coronavirus disease at the beginning of December 2019, there have been more than 28.69 million cumulative confirmed cases worldwide as of 12th September 2020, affecting over 200 countries and regions with more than 920,463 deaths. The COVID-19 pandemic has been sweeping worldwide with unexpected rapidity. In this paper, a hybrid modelling strategy based on tessellation structure- configured SEIR model is adopted to estimate the scale of the pandemic spread. Building on the data pertaining to (...) the global pandemic transmission over the last six months around the world, key impact factors in the transmission and control procedure have been analysed, including isolation rate, number of the infected cases before taking prevention measures, degree of contact scope, and medical level, so as to capture the fundamental factor influencing the pandemic. The quantitative evaluation allowed us to illustrate the magnitude of risks of pandemic and to recommend appropriate national health policy of prevention measures for effectively controlling both intra- and interregional pandemic spread. Our modelling results clearly indicate that the early-stage preventive measures are the most effective action to be taken to contain the pandemic spread of the highly contagious nature of the COVID-19. (shrink)

Evidences are important proofs to support judicial trials. Automatically extracting evidences from judgement documents can be used to assess the trial quality and support “Intelligent Court”. Current evidence extraction is primarily depended on sequence labelling models. Despite their success, they can only assign a label to a token, which is difficult to recognize nested evidence entities in judgment documents, where a token may belong to several evidences at the same time. In this paper, we present a novel evidence extraction architecture (...) called ATT-MRC, in which extracting evidence entities is formalized as a question answer problem, where all evidence spans are screened out as possible correct answers. Furthermore, to address the data imbalance problem in the judgement documents, we revised the loss function and combined it with a data enhancement technique. Experimental results demonstrate that our model has better performance than related works in evidence extraction. (shrink)

Background: It has been reported that type 2 diabetes is associated with olfactory identification impairments and cognitive decline. However, the relationship between OI impairments and cognitive decline is largely unknown in T2DM patients.Methods: Sixty-eight T2DM patients and 68 healthy controls underwent 3D-T1 MRI scans, olfactory and cognitive assessments. The cortical thickness of olfaction-related brain regions, olfactory and cognitive scores were compared between groups. Correlation analyses were carried out among cognition, olfaction, and cortical thickness of olfaction-related brain regions.Results: First, the cognitive (...) and olfactory test scores of T2DM patients were lower than healthy subjects. Second, higher olfactory scores were associated with increased cortical thickness in the left parahippocampal gyrus and bilateral insula in T2DM. Third, higher olfactory scores were associated with higher cognitive performance in T2DM. Fourth, some cognitive performances were related to cortical thickness in the left parahippocampal gyrus and left insula in T2DM.Conclusion: These findings indicated that olfactory dysfunction may be useful for future applications that attempt to predict cognitive decline or develop tailored therapies in T2DM patients. (shrink)

The interpretability of AI is just as important as its performance. In the LegalAI field, there have been efforts to enhance the interpretability of models, but a trade-off between interpretability and prediction accuracy remains inevitable. In this paper, we introduce a novel framework called LK-IB for compulsory measure prediction (CMP), one of the critical tasks in LegalAI. LK-IB leverages Legal Knowledge and combines an Interpretable model and a Black-box model to balance interpretability and prediction performance. Specifically, LK-IB involves three steps: (...) (1) inputting cases into the first module, where first-order logic (FOL) rules are used to make predictions and output them directly if possible; (2) sending cases to the second module if FOL rules are not applicable, where a case distributor categorizes them as either “simple” or “complex“; and (3) sending simple cases to an interpretable model with strong interpretability and complex cases to a black-box model with outstanding performance. Experimental results demonstrate that the LK-IB framework provides more interpretable and accurate predictions than other state-of-the-art models. Given that the majority of cases in LegalAI are simple, the idea of model combination has significant potential for practical applications. (shrink)

Governments have adopted strict home quarantine measures during the COVID-19 pandemic. A monotonous, barren, and under-stimulating environment can cause state boredom, and people often deal with boredom via novelty-seeking behavior. Novelty-seeking behavior can be divided into “novelty input” and “novelty output.” The former refers to obtaining novel information such as browsing the Web; the latter refers to engaging in creative behavior such as literary creation. This study explores the relationship between two types of novelty-seeking behavior and individual state boredom during (...) home quarantine, along with the moderation effect of trait creativity. The study sample consists of 582 Chinese college students who were quarantined at home during the COVID-19 pandemic. Participants completed the Multidimensional State Boredom Scale, the Williams Creativity Aptitude Test, and self-compiled questionnaires of novelty input and novelty output. The results show that there is no significant relationship between novelty input or novelty output and boredom during the COVID-19 quarantine. Trait creativity is found to negatively moderate the relationship between the two means of novelty seeking and boredom. Specifically, novelty output negatively predicts the state boredom of individuals with high creativity, while novelty input positively predicts the state boredom of individuals with low creativity. Our findings suggest that different novelty-seeking behaviors may have different effects on the boredom level of individuals with high versus low creativity during quarantine. During a quarantine period, individuals should avoid excessively engaging in novelty input behaviors aimed at escaping boring situations. (shrink)

There is a growing consensus that the mental lexicon contains both abstract and word-specific acoustic information. To investigate their relative importance for word recognition, we tested to what extent perceptual learning is word specific or generalizable to other words. In an exposure phase, participants were divided into two groups; each group was semantically biased to interpret an ambiguous Mandarin tone contour as either tone1 or tone2. In a subsequent test phase, the perception of ambiguous contours was dependent on the exposure (...) phase: Participants who heard ambiguous contours as tone1 during exposure were more likely to perceive ambiguous contours as tone1 than participants who heard ambiguous contours as tone2 during exposure. This learning effect was only slightly larger for previously encountered than for not previously encountered words. The results speak for an architecture with prelexical analysis of phonological categories to achieve both lexical access and episodic storage of exemplars. (shrink)

Based on social cognitive theory, we theorize that collective efficacy plays a mediating role in the relationship between paternalistic leadership and organizational commitment and that this mediating role depends on team cohesion. The empirical results from a study of 238 employees from 52 teams at manufacturing companies show that benevolent leadership and moral leadership, both components of paternalistic leadership, are positively related to organizational commitment and further that collective efficacy mediates the moral leadership–organizational commitment relationship. We did not find a (...) relationship between authoritarian leadership and organizational commitment. Besides, it was found that team cohesion negatively moderates the relationship between moral leadership and collective efficacy and positively moderates the relationship between collective efficacy and organizational commitment. Explanations and directions for future research are discussed. (shrink)

A new theory of the neuropsychological underpinnings of phenomenal consciousness, “asynchronous introspection theory,” is proposed that emphasizes asynchrony between different neurocognitive processes. We provide a detailed explanation of how a mind might arrive at a cognitive structure isomorphic to the cognitive structure that would emerge from experiential qualia. The theory suggests that a temporal illusion is created because of the mismatch between the real physical timeline and the neurally constructed timeline composed inside a person’s brain. This temporal illusion leads to (...) the origination of a thought that one has had a certain experience wherein the thought and the feeling seem synchronous to the person but, in fact, are not. This leads to the thought, “I had a feeling.” The theory is elaborated via a metaphorical “robot supervisor model” and is shown to explain many current problems of phenomenal consciousness. (shrink)

Leveraging the staggered introduction of specialized bankruptcy courts across China as an exogenous shock, this study examines the impact of specialized bankruptcy courts on corporate ESG performance. Using listed firms in China from 2015 to 2021, we find that the introduction of specialized bankruptcy courts leads to an increase in corporate ESG performance. Our main results remain robust after considering endogeneity concerns and TWFE bias. The underlying mechanism is that these courts strengthen creditor protection, thereby enhancing access to bank loans (...) for local firms. Moreover, this effect is more pronounced in firms with limited access to bank financing and in cities with more efficient legal and financial environments. Collectively, our study contributes a novel perspective to the discourse in law and finance, underscoring the broader implications of judicial reforms on corporate ethical behavior. (shrink)

As the labeling costs in legal artificial intelligence tasks are expensive. Therefore, it becomes a challenge to utilize low cost to train a robust model. In this paper, we propose a LAIAugment approach, which aims to enhance the few-shot learning capability in legal artificial intelligence tasks. Specifically, we first use the self-training approach to label the amount of unlabelled data to enhance the feature learning capability of the model. Moreover, we also search for datasets that are similar to the training (...) set by improving the text similarity function. We conducted experimental analyses for three legal artificial intelligence tasks, including evidence extraction, legal element extraction, and case multi-label prediction, which composed of 3500 judgement documents. The experimental results show that the proposed LAIAugment method has an average F1-score of 72.3% on the three legal AI tasks, which is 1.93% higher than the baseline model. At the same time, it shows a huge improvement in few-shot learning. (shrink)

In this article, we point out the problem on Stanley and Williamson’s reconstruction of Ryle’s regress argument to refute their critique toward Ryle’s argument. We identify the object of Ryle’s criticism through analysing some intellectualisms which try to solve the regress argument. To reconcile the contradiction of intellectualism and anti-intellectualism, we propose a moderate version of intellectualism – Intellectual Explanation Thesis – which does not lead to infinite regress while maintains the necessary connection between knowledge-how and knowledge-that. This alternative thesis (...) introduces a criterion for judging whether an action is intellectual or not, therefore offers a new perspective on the complex relationship between intellectual action and knowledge. (shrink)

Acid fracturing is the most important stimulation method in the carbonate reservoir. Due to the high cost and high risk of acid fracturing, it is necessary to predict the reservoir productivity before acid fracturing, which can provide support to optimize the parameters of acid fracturing. However, the productivity of a single well is affected by various construction parameters and geological conditions. Overfitting can occur when performing productivity prediction tasks on the high-dimension, small-sized reservoir, and acid fracturing dataset. Therefore, this study (...) developed a stacking heterogeneous ensemble model with a hybrid wrapper-based feature selection strategy to forecast reservoir productivity, resolve the overfitting problem, and improve productivity prediction. Compared to other baseline models, the proposed model was found to have the best predictive performances on the test set and effectively deal with the overfitting. The results proved that the hybrid wrapper-based feature selection strategy introduced in this study reduced data acquisition costs and improved model comprehensibility without reducing model performance. (shrink)

Understanding personality effects and their role in influencing relationship quality, varied according to gender and relationship duration, could help us better understand close relationships. Participants were Chinese dating dyads and were asked to complete both the Big Five Inventory and Perceived Relationship Quality Component scales. Males and those who had a long-term relationship perceived better relationship quality; individuals who scored higher on agreeableness, conscientiousness, openness, and emotional stability enjoyed better relationship quality; gender and/or relationship duration moderated the actor effect of (...) extraversion and the partner effects of conscientiousness, emotional stability, and openness on relationship quality. Regarding the profile similarity, those couples who were more dissimilar in their profile personality had better relationship quality, especially when they were in a relatively long-term relationship. Meanwhile, with an increase in profile similarity, the males’ perceived relationship quality decreased. (shrink)

WeChat is not only a mobile application with many innovative features but is also representative of China’s electronic revolution. It is compatible with more than 90% of smart phones and has become an indispensable tool for daily use. People are captivated by various types of WeChat voting and canvassing activities, but little research has investigated whether such voting is based on guanxi or justice. Are people truly willing to vote on WeChat? Is WeChat voting an effective means of acquaintance marketing? (...) In this research, three studies were conducted. First, 656 respondents were surveyed, and the results showed that more than 90% of WeChat users have participated in WeChat voting and that their voting behaviour is based on guanxi. Second, an online questionnaire was administered to 731 subjects, and the results were statistically analysed to determine whether voting behaviour is motivated by guanxi or by justice. The results showed that people’s behaviour deviates from their intention. Third, 676 subjects were investigated, and logistic regression was used to model and analyse the characteristics of voting participants. The many interesting findings reveal that men show more ‘empathy’ than women and that men are more likely to vote on WeChat based on reciprocity and intimacy. In addition, older people emphasize emotion, whereas students are more interested in fostering connections for the future. Inappropriate WeChat voting behaviour does not facilitate promotional marketing, damages the reputation of the company and reduces customer loyalty. These findings provide theoretical, methodological, and practical contributions to strategies for effective acquaintance marketing. (shrink)