An experiment explored the acquisition of conscious and unconscious knowledge of semantic prosody in a second language under incidental and intentional learning conditions. Semantic prosody is the conotational coloring of the semantics of a word, largely uncaptured by dictionary definitions. Contrary to some claims in the literature, we revealed that both conscious and unconscious knowledge were involved in the acquisition of semantic prosody. Intentional learning resulted in similar unconscious but more conscious knowledge than incidental learning. The results are discussed in (...) terms of second language learning and the nature of unconscious knowledge. (shrink)

Corporate social responsibility (CSR) is becoming increasingly important in China. This paper investigates the implementation of instruments for dimensions of CSR that are relevant for the Chinese context and the challenges that Chinese companies face. Based on a survey among 109 Chinese companies, we find that formal instruments to implement CSR are rather common. Companies spend most effort in improving the economic aspects of CSR, such as competitiveness, product innovation and process innovation. Only a small minority of the companies set (...) concrete targets and report the realization of these targets for social and environmental goals. This indicates that the attention to social and environmental aspects of CSR is still rather loose. The most important challenges for improving CSR are strong competitive pressure, insufficient support from the government and/or nongovernmental organizations and high costs of CSR implementation. Multiple regression analysis shows that the use of instruments is positively related to company size and foreign ownership and negatively related to lack of resources and support for CSR by investors and consumers. (shrink)

Anxious major depressive disorder is a common subtype of major depressive disorder; however, its unique neural mechanism is not well-understood currently. Using multimodal MRI data, this study examined common and specific alterations of amygdala subregions between patients with and without anxiety. No alterations were observed in the gray matter volume or intra-region functional integration in either patient group. Compared with the controls, both patient groups showed decreased functional connectivity between the left superficial amygdala and the left putamen, and between the (...) right superficial amygdala and the bilateral anterior cingulate cortex and medial orbitofrontal cortex, while only patients with anxiety exhibited decreased activity in the bilateral laterobasal and superficial amygdala. Moreover, the decreased activity correlated negatively with the Hamilton depression scale scores in the patients with anxiety. These findings provided insights into the pathophysiologic processes of anxious major depressive disorder and may help to develop new and effective treatment programs. (shrink)

Cooperative innovation has become a critical method for freight logistics firms in supply chain management. The previous study has proved that relational embeddedness has a positive effect on service innovation performance. However, the influence of organizational learning capacity has been widely ignored. This study focuses on explaining the mechanism of OLC on the relationship between RE and innovation performance of freight logistics service. Firstly, a theoretical model is constructed based on Social Network Theory, and four research hypotheses are presented. Secondly, (...) a sample of 236 respondents from freight logistics firms in China is analyzed to test the hypotheses. Finally, several management implications and recommendations are suggested. The research results demonstrate that both RE and OLC have positive effects on IPFLS. Meanwhile, OLC partially mediates the relationship between RE and IPFLS. The findings provide practical guidance for managers to strengthen the relationship with partners and enhance OLC. (shrink)

The objective of this study is to propose a new operation method based on the universal grey number to overcome the shortcomings of typical interval operation in solving system fault trees. First, the failure probability ranges of the bottom events are described according to the conversion rules between the interval number and universal grey number. A more accurate system reliability calculation is then obtained based on the logical relationship between the AND gates and OR gates of a fault tree and (...) universal grey number arithmetic. Then, considering an aircraft landing gear retraction system as an example, the failure probability range of the top event is obtained through universal grey operation. Next, the reliability of the aircraft landing gear retraction system is evaluated despite insufficient statistical information describing failures. The example demonstrates that the proposed method provides many advantages in resolving the system reliability problem despite poor information, yielding benefits for the function of the interval operation, and overcoming the drawback of solution interval enlargement under different orders of interval operation. (shrink)

In this study, we demonstrate a previously unknown finding that mindful learning can improve an individual’s spatial cognition without regard to gender differences. Thirty-two volunteers participated in the experiment. Baselines for spatial ability were first measured for the reaction time on the mental rotation task. Next, the participants were randomly assigned to either a mindful or mindless learning condition. After learning, the mental rotation task showed that those in the mindful learning condition responded faster than those in the mindless learning (...) condition. This study provides promising evidence for applying mindful learning to education. (shrink)

Consumers may sense hypocrisy in corporate social responsibility if they note inconsistency in enterprises’ words and deeds related to CSR. This inconsistency originates from the intentional selfish actions and unintentional actions of enterprises. Studies have revealed that consumers’ perception of hypocrisy has a negative influence on enterprise operation. However, studies have not examined how corporate responses to consumers’ hypocrisy perception affect consumers’ attitude and behavior. Therefore, the present study attempted to determine the measures that should be undertaken by enterprises to (...) reduce consumers’ negative response to them when consumers perceive them to be hypocritical. We conducted a situational simulation experiment to explore the effect of the match between corporate hypocrisy manifestation and the corporate response strategy on consumers’ negative behaviors toward an enterprise and to test the mechanism influencing this effect. The results indicated that the interaction between the type of corporate hypocrisy and the corporate response strategy has a significant effect on consumers’ negative behaviors toward an enterprise. Consumers’ negative emotions have a mediating influence on the aforementioned effect. This study explored the response strategies of enterprises during a corporate hypocrisy crisis, classified corporate hypocrisy crises into two types according to the different manifestations of corporate hypocrisy, and introduced situational crisis communication theory into research on corporate hypocrisy. The present results help expand knowledge on corporate hypocrisy. (shrink)

Evidence supports predictive roles of non-social smartphone use for smartphone addiction, but the relationship of social smartphone use and smartphone addiction is unclear. This study explored whether social smartphone use has a double-edged impact on smartphone addiction. Using data from a sample of 909 Chinese undergraduates, we tested a parallel mediation model that considered online social support and realistic social support as mediators. As predicted, social smartphone use weakened smartphone addiction through realistic social support and contributed to smartphone addiction through (...) online social support. Moreover, we tested the moderating role of agreeableness in the mediation path of online social support. Agreeableness only moderated the indirect effects. Specifically, the predictive effects of online social support on smartphone addiction was greater for lower rather than higher agreeableness. The results suggest that social needs play an important role in the formation of smartphone addiction. Several limitations and implications are also discussed herein. (shrink)

Aiming at the problem of insufficient health monitoring of the elderly in the existing home care system, this paper designs a health information analysis and early warning system based on the Internet of Things technology, which can monitor the physiological data of the elderly in real time. It also can be based on the elderly real-time monitoring data, physical examination data, and other types of health data, which can be used to predict diseases, so as to achieve “early detection and (...) early treatment” of diseases. First, analyse and design the architecture and content of the home care monitoring system based on the Internet of Things. Secondly, based on the collected heart rate, blood pressure, and three-axis acceleration information of the elderly, it is analysed to determine whether the elderly are in danger of falling, and the designed system is used for early warning. Finally, this paper analyses the prediction algorithm theory of the disease prediction module in the health monitoring software of the home care system. In order to improve the accuracy of prediction, the DS evidence theory is used to optimize the traditional BP neural network algorithm and conduct experimental tests. The test results show that the health information analysis and early warning software of the home care system meet actual needs and achieve the expected goals. (shrink)

There is a growing demand for information and computational technology for surgeons help with surgical planning as well as prosthetics design. The two-dimensional images are registered to the three-dimensional model for high efficiency. To reconstruct the 3D model of knee joint including bone structure and main soft tissue structure, the evaluation and analysis of sports injury and rehabilitation treatment are detailed in this study. Mimics 10.0 was used to reconstruct the bone structure, ligament, and meniscus according to the pulse diffusion-weighted (...) imaging sequence and stir sequences of magnetic resonance imaging. Excluding congenital malformations and diseases of the skeletal muscle system, MRI scanning was performed on bilateral knee joints. Proton weighted sequence and stir pulse sequence were selected for MRI. The models were imported into Geomagic Studio 11 software for refinement and modification, and 3D registration of bone structure and main soft tissue structure was performed to construct a digital model of knee joint bone structure and accessory cartilage and ligament structure. The 3D knee joint model including bone, meniscus, and collateral ligament was established. Reconstruction and image registration based on mimics and Geomagic Studio can build a 3D model of knee joint with satisfactory morphology, which can meet the requirements of teaching, motion simulation, and biomechanical analysis. (shrink)

It is evident that, being a member of the organization, the team has to cue the influx of the green management concepts. This study focuses on the aspect of team management in green enterprises. Applying leadership theory to sample green enterprises, this paper proposes that political skills of team leadership have moderating effects on the relationship between team conflict and performance at both the individual and team levels. Empirical data were collected from 85 dyads of leaders and team members in (...) 36 green enterprises in China. It was found that the leaders’ political skills weakened the negative effects of relationship conflict on individual performance and team performance. Further, leaders’ political skills strengthened the positive effects of task conflict on individual and team performance. The results of this study deepen the cognition of two types of team conflict in theory and provide theoretical guidance for green enterprises in carrying out effective team conflict management and practical political skills training for leaders. (shrink)

Naïve sparse representation has stability problem due to its unsupervised nature, which is not preferred for classification tasks. For this problem, this paper presents a novel representation learning method named classification-oriented local representation for image recognition. The core idea of CoLR is to find the most relevant training classes and samples with test sample by taking the merits of class-wise sparseness weighting, sample locality, and label prior. The proposed representation strategy can not only promote a classification-oriented representation, but also boost (...) a locality adaptive representation within the selected training classes. The CoLR model is efficiently solved by Augmented Lagrange Multiplier scheme based on a variable splitting strategy. Then, the performance of the proposed model is evaluated on benchmark face datasets and deep object features. Specifically, the deep features of the object dataset are obtained by a well-trained convolutional neural network with five convolutional layers and three fully connected layers on the challenging ImageNet. Extensive experiments verify the superiority of CoLR in comparison with some state-of-the-art models. (shrink)

Patients with chronic obstructive pulmonary disease are characterized by attenuated pulmonary function and are frequently reported with cognitive impairments, especially memory impairments. The mechanism underlying the memory impairments still remains unclear. We applied resting-state functional magnetic resonance imaging to compare the brain local activities with static and dynamic amplitude of low-frequency fluctuations among patients with COPD and healthy controls. Compared with HC, COPD patients exhibited decreased sALFF in the right basal ganglia and increased dALFF in the bilateral parahippocampal/hippocampal gyrus. The (...) reduced the left basal ganglia was associated with lower oxygen partial pressure. Besides, the increased dALFF in the left hippocampal/parahippocampal cortex was associated with poor semantic-memory performance and the increased dALFF in the left hippocampal/parahippocampal cortex was associated the forced vital capacity. The present study revealed the abnormal static and dynamic local-neural activities in the basal ganglia and parahippocampal/hippocampal cortex in COPD patient and its relationship with poor lung function and semantic-memory impairments. (shrink)

The recent COVID-19 crisis caught many by surprise. Yet some firms were better prepared to weather the downturn than others. Using a comprehensive data set that observes over 15,000 firms in 27 countries, including several developing countries, shortly before and after the pandemic, we document that pre-crisis innovation affected firm’s survival odds and performance thereafter. The results show that innovative firms are less likely to close and perform better than non-innovators during the pandemic crisis. Innovative firms are also more optimistic (...) about the future than non-innovators. Our results further indicate that firm’s adaptability mediates the relationship between innovation and survival outcomes. The study finding shows that innovative firms are more likely to introduce new products, remote work arrangements, increase delivery, pivoting, and online activities than non-innovators during the pandemic crisis. (shrink)

Difficulty in emotional regulation is significantly correlated with depression. Depression is a psychological disease that seriously affects the physical and mental health of college students. Therefore, it is of great importance to develop diversified preventive interventions such as group impromptu music therapy. The main purpose of this study was to evaluate the effect of GIMT on the improvement of emotional regulation ability and the reduction of depressive symptoms in college students. A 71 college students were recruited to carry out randomized (...) controlled trial was used. The experimental group was intervened by GIMT. After the 4th week of intervention, follow-up and scale measurement were carried out. In the experimental group, emotional regulation difficulty scales showed significant difference before and after GIMT, implying the improvement in the emotional regulation. But there was no significant improvement in the control group. In addition, the depressive symptoms of experimental group were relieved. All findings showed that GIMT can effectively improve college students’ emotional regulation and reduce depressive symptoms. (shrink)

Although many studies have provided evidence that abstract knowledge can be acquired in artificial grammar learning, it remains unclear how abstract knowledge can be attained in sequence learning. To address this issue, we proposed a dual simple recurrent network model that includes a surface SRN encoding and predicting the surface properties of stimuli and an abstract SRN encoding and predicting the abstract properties of stimuli. The results of Simulations 1 and 2 showed that the DSRN model can account for learning (...) effects in the serial reaction time task under different conditions, and the manipulation of the contribution weight of each SRN accounted for the contribution of conscious and unconscious processes in inclusion and exclusion tests in previous studies. The results of human performance in Simulation 3 provided further evidence that people can implicitly learn both chunking and abstract knowledge in sequence learning, and the results of Simulation 3 confirmed that the DSRN model can account for how people implicitly acquire the two types of knowledge in sequence learning. These findings extend the learning ability of the SRN model and help understand how different types of knowledge can be acquired implicitly in sequence learning. (shrink)

Risk management is a key factor for smart city running. There are many risk events in a strict process like transportation management of a smart city or a medical surgery in a smart hospital, and every step may lead to one kind of risk or more. In view of the fact that the occurrence of the flow risks follows the sequence formed by each process step, this paper presents a Bayesian network under strict chain to model this situation. In this (...) model, the probabilistic reasoning formula is given according to the sequence of process steps, and the probabilities given by the model can do risk factor analysis to support the system to find an effective way to improve the process like machine manufacturing or a medical surgery. Finally, an example is analyzed based on the information given by doctors according to the situation of LC in their hospital located in Sichuan Province of China, which shows the effectiveness and rationality of the proposed BN_SC model. (shrink)

The effectiveness of trust has been extensively investigated in entrepreneurship studies. However, compared to the outcomes of trust, we still lack knowledge about the mechanisms underlying venture capitalists' initial trust in entrepreneurs. Drawing from signal theory and impression management theory, this study explores an impression management motivational explanation for the influencing factors of venture capitalists' initial trust. An empirical test is based on 202 valid questionnaires from venture capitalists, and the results indicate that the signal of five dimensions of entrepreneurial (...) orientation has a significant impact on the initial trust of venture capitalists and that a signal of entrepreneurial orientation of perseverance or passion positively influences venture capitalists' initial trust through acquired impression management strategies, while a signal of entrepreneurial orientation of risk-taking, innovation, or proactivity positively affects the initial trust of venture capitalists through defensive impression management strategies. The perceptions of entrepreneurs' hypocrisy by venture capitalists negatively moderate the relationship between acquired impression management strategies and the initial trust of venture capitalists and negatively moderate the relationship between defensive impression management strategies and the initial trust of venture capitalists. (shrink)

Recent advances in neuroscience indicate that analysis of bio-signals such as rest state electroencephalogram and eye-tracking data can provide more reliable evaluation of children autism spectrum disorder than traditional methods of behavior measurement relying on scales do. However, the effectiveness of the new approaches still lags behind the increasing requirement in clinical or educational practices as the “bio-marker” information carried by the bio-signal of a single-modality is likely insufficient or distorted. This study proposes an approach to joint analysis of EEG (...) and eye-tracking for children ASD evaluation. The approach focuses on deep fusion of the features in two modalities as no explicit correlations between the original bio-signals are available, which also limits the performance of existing methods along this direction. First, the synchronization measures, information entropy, and time-frequency features of the multi-channel EEG are derived. Then a random forest applies to the eye-tracking recordings of the same subjects to single out the most significant features. A graph convolutional network model then naturally fuses the two group of features to differentiate the children with ASD from the typically developed subjects. Experiments have been carried out on the two types of the bio-signals collected from 42 children. The results indicate that the proposed approach can achieve an accuracy of 95% in ASD detection, and strong correlations exist between the two bio-signals collected even asynchronously, in particular the EEG synchronization against the face related/joint attentions in terms of covariance. (shrink)

Positive parent-adolescent communication has been found to be negatively related to adolescent depressive symptoms; however, few studies have investigated the moderating effects of adolescent gender and age on this relationship, especially during early adolescence in China. The present study investigated the joint moderating effects of adolescent gender and age on the linkage of father-adolescent and mother-adolescent communication with adolescents’ depressive symptoms. A total of 11,455 Chinese junior high school students completed ad hoc questionnaires of parent-adolescent communication and depressive symptoms. Multiple (...) linear regression analyses were conducted. Results indicated that gender and age jointly moderated the association between parental communication and adolescent depressive symptoms. Specifically, for girls, the negative effects of both father-adolescent and mother-adolescent communication on depressive symptoms were stronger in 9th grade students than in 7th grade students, while for boys, the negative effects were not different between 7th grade students and 9th grade students. These findings suggest that in China, the protective effects of positive parent-adolescent communication on adolescents’ depressive symptoms may be most salient among senior-grade girls in junior high school. (shrink)

By investigating the status quo of the swimming training market in a certain area, we can obtain information on the current development of the swimming training market in a certain area and study the laws of the development of the market so as to provide a theoretical basis for the development of the market. This paper designs an evaluation algorithm suitable for swimming training based on the improved AlexNet network. The algorithm model uses a 3 × 3 size convolution kernel (...) to extract features, and the pooling layer uses a nonoverlapping pooling strategy. In order to accelerate the network convergence, the model introduces batch normalization technology. The algorithm uses data augmentation technology to expand the data set, including rotation and random erasure, to a certain extent alleviating the problem of overfitting. The results of the study showed that there were no significant differences in fat, minerals, protein, body mass index, basal metabolic rate, and total energy expenditure in the body composition ratios of children in the convolutional neural network assessment group and the control group, while muscle and total body water were not significantly different. However, there are significant differences in fat-free body weight and muscle strength of various segments of the body, among which there are very significant differences in muscle strength of lower limbs in each segment of the body. There were no significant differences in minerals, body mass index, basal metabolic rate, total energy expenditure, and lower limb muscle strength in the body composition ratios of men and women in the convolutional neural network assessment group. There are significant differences in body weight, upper limb muscle strength, and trunk muscle strength. There were no significant differences in the proportions of body composition between men and women in the control group, except for fat and protein. (shrink)

At present, uniform upscaling division methods are routinely used to upscale geologic model grids, resulting in overly fine grids in some areas of the model. To improve computational efficiency, we have examined the effect of model upscaling with different upscaling parameters with the goal of producing a nonuniform grid with uniform accuracy. We based our nonuniform upscaling grid method on geologic characteristics including reservoir thickness, physical properties, reservoir spacing, and water flooding. Most of the logging curves of thin reservoirs are (...) finger-like, allowing us to define the grid size according to the reservoir thickness. We use two different strategies to discretize uniform and composite reservoirs and represent reservoir thickness that exhibit bell- and funnel-shaped logging curves. Although one grid point accurately represents a uniform reservoir, we find that composite reservoirs require four or five points to accurately represent the physical properties of a composite reservoir. For the thick reservoirs with box- or composite-type logging curves, the physical properties inside the reservoir do not change much; therefore, we use a grid point to represent the reservoir thickness information. Using these metrics, we constructed alternative “moderate” and “efficient” vertical grid upscaling strategies. Taking the 15 sedimentary units with a total thickness of 72 m as an example, the statistical results show that the computational efficiency using our data-adaptive grid can be increased more than five times compared to the traditional uniform fine-grid method while retaining the same accuracy. (shrink)