本书系统地分析和探讨了清教伦理思想、启蒙伦理思想、先验主义伦理思想、实用主义伦理思想、唯心主义伦理思想、自然主义伦理思想、元伦理学、应用伦理学在美国的发展状况,展现了美国伦理思潮演变的历史脉络,勾画了 其中比较清晰的三条线索:重个人的倾向;重实用的倾向;与宗教捆绑的倾向。.

Few previous studies have investigated the relationship between global perspective and willingness to communicate in English. Hence, more studies are needed to validate their correlation. Furthermore, hardly any pertaining studies have been conducted at English Medium Instruction universities. As such, the current study aimed to fill these gaps in the context of an EMI university in China, by investigating whether GP correlates with second language WTC and what factors impact the two variables. Data were collected from students via an online (...) questionnaire and follow-up interviews. The questionnaire findings confirmed a moderate positive correlation between GP and L2 WTC. The interview data unraveled that several factors influenced students’ L2 WTC, including needs and motivations driving L2 WTC, concerns constraining L2 WTC, and intercultural cognition facilitating L2 WTC. These findings suggest that: students could be more determined to practice their English if they realize the significance of the role of English in their life; teachers could foster students’ WTC by creating a non-threatening English-speaking environment and encouraging students to communicate in English in and outside the classroom; and teachers could educate students about GP and L2 WTC, which might help to expand students’ horizon and stimulate their interests in foreign cultures and global affairs, so as to facilitate the sustainable growth of their English learning. (shrink)

We present a novel method, called graph sparse nonnegative matrix factorization, for dimensionality reduction. The affinity graph and sparse constraint are further taken into consideration in nonnegative matrix factorization and it is shown that the proposed matrix factorization method can respect the intrinsic graph structure and provide the sparse representation. Different from some existing traditional methods, the inertial neural network was developed, which can be used to optimize our proposed matrix factorization problem. By adopting one parameter in the neural network, (...) the global optimal solution can be searched. Finally, simulations on numerical examples and clustering in real-world data illustrate the effectiveness and performance of the proposed method. (shrink)

According to the dual-system theories, the decisions in an ultimatum game are governed by the automatic System 1 and the controlled System 2. The former drives the preference for fairness, whereas the latter drives the self-interest motive. However, the association between the contributions of the two systems in UG and the cognitive process needs more direct evidence. In the present study, we used the process dissociation procedure to estimate the contributions of the two systems and recorded participants eye movements to (...) examine the cognitive processes underlying UG decisions. Results showed that the estimated contributions of the two systems are uncorrelated and that they demonstrate a dissociated pattern of associations with third variables, such as reaction time and mean fixation duration. Furthermore, the relative time advantage and the transitions between the two payoffs can predict the final UG decisions. Our findings provide evidence for the independent contributions of preference for fairness and self-interest maximizing inclinations to UG and shed light on the underlying processes. (shrink)

ObjectivePrevious studies have demonstrated altered brain activity in strabismic amblyopia. In this study, low-frequency repetitive transcranial magnetic stimulation was applied in children with strabismic amblyopia after they had undergone strabismus surgery. The effect of rTMS was investigated by measuring the changes of brain features using the amplitude of low-frequency fluctuation.Materials and MethodsIn this study, 21 SA patients were recruited based on their age, weight, and sex. They all had SA in their left eyes and they received rTMS treatment one month (...) after strabismus surgery. Their vision before and after surgery were categorized as pre-rTMS and post-rTMS. All participants received rTMS treatment, underwent magnetic resonance imaging, and their data were analyzed using the repeated measures t-test. The team used correlation analysis to explore the relationship between logMAR visual acuity and ALFF.ResultsPre- versus post-rTMS values of ALFF were significantly different within individuals. In the POT group, ALFF values were significantly decreased in the Angular_R, Parietal_Inf_L, and Cingulum_Mid_R while ALFF values were significantly increased in the Fusiform_R and Frontal_Inf_Orb_L compared to the PRT stage.ConclusionOur data showed that ALFF recorded from some brain regions was changed significantly after rTMS in strabismic amblyopes. The results may infer the pathological basis of SA and demonstrate that visual function may be improved using rTMS in strabismic amblyopic patients. (shrink)

More and more studies showed that strabismus is not simply an ocular disease, but a neuro-ophthalmology disease. To analyze potential changes in brain activity and their relationship to behavioral performance in comitant strabismus patients and healthy controls. Our study recruited 28 patients with comitant strabismus and 28 people with matched weight, age range, and sex ratio as healthy controls. Using resting-state functional magnetic resonance imaging, we evaluated fALFF to compare spontaneous brain activity between comitant strabismus and healthy controls. We did (...) hospital anxiety and depression scale questionnaires for these patients. We found significantly lower fALFF value in comitant strabismus patients compared with controls in the left frontal superior medial gyrus and the right middle cingulum. In the latter region, fALFF was significantly negatively correlated with the hospital anxiety and depression scale, as well as the duration of disease. Receiver operating characteristic curve analysis indicated that the fALFF method has clear potential for the diagnosis of comitant strabismus patients. These results revealed abnormal spontaneous activity in two brain regions of comitant strabismus patients, which may indicate underlying pathologic mechanisms and may help to advance clinical treatment. (shrink)

In recent years government publicity was extensively used to convey environmental issues; therefore, it is important to explore the role of green government publicity influencing people’s pro-environmental behaviors. This study is to uncover the impact of China’s green government publicity on people’s willingness to use green packaging. This research collected data from Guangzhou of China, we used convenient sampling and online questionnaire survey to gather data, and there were 584 effective samples. Using the statistical software Amos17.0, the results reveal that (...) green government publicity has a significant effect on environmental concerns and moral obligation. Environmental concerns and moral obligation both have positive effects on PEBs. In addition, Environmental concerns and moral obligation all have mediating effects in the relationship between green government publicity and people’s PEBs. (shrink)

Ben shu jie he shi dai fa zhan de yao qiu,Cong pi pan ji cheng you xiu chuan tong wen hua de shi jiao,Dui xian qin ru jia"he"zheng zhi lun li si xiang jin xing le bi jiao quan mian de si kao.

Research has independently highlighted the roles of semantic memory and associative abilities in creative thinking. However, it remains unclear how these two capacities relate to each other, nor ho...

Time preference reversals refers to systematic inconsistencies between preferences and valuations in intertemporal choice. When faced with a pair of intertemporal options, people preferred the smaller-sooner option but assign a higher price to the larger-later one. Different hypotheses postulate that the differences in evaluation scale or output format between the choice and the bid tasks cause the preference reversal. However, these hypotheses have not been distinguished. In the present study, we conducted a hybrid task, which shares the same evaluation scale (...) with the bid task and shares the same output format with the choice task. By comparing these three tasks, we can figure out the key reason for time preference reversal. The eye-tracking measures reflecting attention allocation, cognitive effort and information search pattern were examined. Results showed that participants' time preference and eye-tracking measures in the hybrid task were similar to those in the choice task, but different from those in the bid task. Our findings suggest that the output format is the core reason for time preference reversal and may deepen our understanding of the mechanisms that underlie time preference reversal. (shrink)

PurposeTo investigate spontaneous brain activity in patients with dry eye and healthy control using the fractional amplitude of low frequency fluctuation technique with the aim of elucidating the relationship between the clinical symptoms of DE and changes in brain function.Material and MethodsA total of 28 patients with DE and 28 matched healthy volunteers were enrolled. Resting-state functional magnetic resonance imaging scans were performed in both groups. Then all subjects were required to complete a comprehensive Hospital Anxiety and Depression Scale. Receiver (...) operating characteristic curve analysis was used to evaluate the differences in fALFF values between the two groups and their diagnostic value. Linear correlations between HADS and fALFF values in different brain regions of DE patients were analyzed using the Pearson correlation coefficient.ResultsPatients with DE had significantly higher fALFF values in the left calcarine sulcus than the HC group, while fALFF values in the bilateral middle frontal gyrus and right MFG/right inferior frontal gyrus were significantly lower in DE patients than in HC group. fALFF values had a high diagnostic value for differentiating patients with DE from the HC group. Right MFG and right MFG/IFG were significantly correlated with HADS values.ConclusionOur study found that DE mainly involved functional disorders in the brain areas of the left CS, bilateral MFG and right MFG/right IFG, which helped us to find possible clinical features of DE disease and reflected the potential pathological mechanism of DE. (shrink)

ObjectivesTo simulate hemodynamic changes after extraluminal compression in pulsatile tinnitus patients with a prominent transverse-sigmoid sinus junction.MethodsOne patient-specific case was reconstructed based on computed tomography venography images of a PT patient. The compression degree served as a new index in this study. Cases with 10, 20, 30, 40, 50, 60, 70, 80, and 90% of the compression degree of the control subject were constructed. Steady-state computational fluid dynamics were assessed. The wall pressure distribution, wall maximum pressure and flow pattern of (...) the PTSJ were calculated to evaluate hemodynamic differences among all cases.ResultsWith increasing compression, the wall pressure at the compression point and downstream of the PTSJ decreased but increased upstream. When the compression degree exceeded 70%, the upstream pressure increased significantly. Above 50% compression, the blood flow pattern downstream of the sigmoid sinus tended to spiral, especially after 80% compression. Beyond 60% compression, the blood flow pattern under the compression axis became more medial.ConclusionMechanical compression of PTSJ changes wall pressure and blood flow patterns. The degree of compression should be carefully observed to avoid possible complications or reoccurrence. (shrink)

Objective: To investigate the prevalence of and risk factors associated with mental health symptoms in psychiatric outpatients and their family members in China during the COVID-19 pandemic.Methods: This cross-sectional, survey-based, region-stratified study collected demographic data and mental health measurements for depression, anxiety and acute stress from 269 psychiatric patients and 231 family members in the Second Xiangya Hospital in China from April 27, 2020 to May 8, 2020. Binary logistic regression analysis was performed to identify risk factors associated with mental (...) health outcomes.Result: The results of this survey revealed that symptoms of depression, anxiety, and acute stress were highly prevalent symptoms in the psychiatric patient group. Respondents who were female, unmarried or highly educated were significantly more likely to have the above symptoms. In the family member group, more than half of them felt that the burden of nursing had increased during the epidemic. Subjects with a high degree of burden of care were significantly more likely to exhibit the above mental health symptoms, while females were significantly more likely to have acute stress.Conclusions: The results of this survey revealed a high prevalence of mental health disorder symptoms among psychiatric patients and an increased burden of nursing among their family members after the COVID-19 outbreak in China. Understanding the risk factors in those particular groups of people help improve the public health service system for mental health problems during public health events. For further study, exploration of the needs of mental health services and dynamic change tracking will be needed. (shrink)

Emotional design is an important development trend of interaction design. Emotional design in products plays a key role in enhancing user experience and inducing user emotional resonance. In recent years, based on the user's emotional experience, the design concept of strengthening product emotional design has become a new direction for most designers to improve their design thinking. In the emotional interaction design, the machine needs to capture the user's key information in real time, recognize the user's emotional state, and use (...) a variety of clues to finally determine the appropriate user model. Based on this background, this research uses a deep learning mechanism for more accurate and effective emotion recognition, thereby optimizing the design of the interactive system and improving the user experience. First of all, this research discusses how to use user characteristics such as speech, facial expression, video, heartbeat, etc., to make machines more accurately recognize human emotions. Through the analysis of various characteristics, the speech is selected as the experimental material. Second, a speech-based emotion recognition method is proposed. The mel-Frequency cepstral coefficient of the speech signal is used as the input of the improved long and short-term memory network. To ensure the integrity of the information and the accuracy of the output at the next moment, ILSTM makes peephole connections in the forget gate and input gate of LSTM, and adds the unit state as input data to the threshold layer. The emotional features obtained by ILSTM are input into the attention layer, and the self-attention mechanism is used to calculate the weight of each frame of speech signal. The speech features with higher weights are used to distinguish different emotions and complete the emotion recognition of the speech signal. Experiments on the EMO-DB and CASIA datasets verify the effectiveness of the model for emotion recognition. Finally, the feasibility of emotional interaction system design is discussed. (shrink)

With the outbreak of the COVID-19 crisis, the public keeps getting epidemic-related information on the media. News reports on the increasing number of fatalities have exposed individuals to death, which causes negative emotional experiences such as tension, anxiety, and fear. This study aimed to investigate whether creativity could serve as an anxiety-buffer when mortality is salient. Based on previous findings, the present study utilized type of creative task and personal search for meaning as moderators. In Study 1, a 2 × (...) 2 between-subject design was utilized, and 168 subjects were randomly assigned to four experimental conditions. In Study 2, 221 subjects were recruited. The experimental procedure was similar to Study 1, except that the priming paradigm of mortality was changed and search for meaning was included as an additional moderating variable. State anxiety was measured as the dependent variable in both studies. Results of Study 1 showed that, while the benevolent creative task could buffer anxiety in the mortality salience condition, the malevolent creative task did not have the same effect. Furthermore, there was a significant interaction between mortality salience, type of creative task, and search for meaning in life on anxiety. In Study 2, the buffering function of benevolent creativity was more intense for participants with a higher level of search for meaning. Together, these findings reveal the influence of different types of creative tasks on individual anxiety levels under death priming conditions and the moderating effect of search for meaning in this relationship. Further, they suggest the need to focus on the role of creativity in terror management. (shrink)

Emotion recognition plays an important role in intelligent human–computer interaction, but the related research still faces the problems of low accuracy and subject dependence. In this paper, an open-source software toolbox called MindLink-Eumpy is developed to recognize emotions by integrating electroencephalogram and facial expression information. MindLink-Eumpy first applies a series of tools to automatically obtain physiological data from subjects and then analyzes the obtained facial expression data and EEG data, respectively, and finally fuses the two different signals at a decision (...) level. In the detection of facial expressions, the algorithm used by MindLink-Eumpy is a multitask convolutional neural network based on transfer learning technique. In the detection of EEG, MindLink-Eumpy provides two algorithms, including a subject-dependent model based on support vector machine and a subject-independent model based on long short-term memory network. In the decision-level fusion, weight enumerator and AdaBoost technique are applied to combine the predictions of SVM and CNN. We conducted two offline experiments on the Database for Emotion Analysis Using Physiological Signals dataset and the Multimodal Database for Affect Recognition and Implicit Tagging dataset, respectively, and conducted an online experiment on 15 healthy subjects. The results show that multimodal methods outperform single-modal methods in both offline and online experiments. In the subject-dependent condition, the multimodal method achieved an accuracy of 71.00% in the valence dimension and an accuracy of 72.14% in the arousal dimension. In the subject-independent condition, the LSTM-based method achieved an accuracy of 78.56% in the valence dimension and an accuracy of 77.22% in the arousal dimension. The feasibility and efficiency of MindLink-Eumpy for emotion recognition is thus demonstrated. (shrink)

In the automatic detection of epileptic seizures, the monitoring of critically ill patients with time varying EEG signals is an essential procedure in intensive care units. There is an increasing interest in using EEG analysis to detect seizure, and in this study we aim to get a better understanding of how to visualize the information in the EEG time-frequency feature, and design and train a novel random forest algorithm for EEG decoding, especially for multiple-levels of illness. Here, we propose an (...) automatic detection framework for epileptic seizure based on multiple time-frequency analysis approaches; it involves a novel random forest model combined with grid search optimization. The short-time Fourier transformation visualizes seizure features after normalization. The dimensionality of features is reduced through principal component analysis before feeding them into the classification model. The training parameters are optimized using grid search optimization to improve detection performance and diagnostic accuracy by in the recognition of three different levels epileptic of conditions (healthy subjects, seizure-free intervals, seizure activity). Our proposed model was used to classify 500 samples of raw EEG data, and multiple cross-validations were adopted to boost the modeling accuracy. Experimental results were evaluated by an accuracy, a confusion matrix, a receiver operating characteristic curve and an area under the curve. The evaluations indicated that our model achieved the more effective classification than some previous typical methods. Such a scheme for computer-assisted clinical diagnosis of seizures has a potential guiding significance, which not only relieves the suffering of patient with epilepsy to improve quality of life, but also helps neurologists reduce their workload. (shrink)

Aiming to improve the commercialization efficiency of scientific innovative achievements, this paper utilizes the time series visualization method to construct the time series network of each subsystem. After that, the network similarity is calculated by the cosine similarity theorem. On this basis, a new multilayer network adjacency matrix is obtained. With the adoption of k-core technology, the critical nodes can be identified to study the transformation efficiency of the innovation value in the network. Finally, according to the provincial innovation value (...) transformation data of China from 1998 to 2016, an empirical study was carried out to calculate and analyze the transformation efficiency of innovation achievements in 30 provinces. The results indicate that the transformation efficiency of innovation value can be expressed by the structure of the time series network constructed by the input-output vectors; the mapping relationship of the value transformation vectors could be reflected by the cosine similarity of the time series network, while the transformation efficiency of innovation value could be identified using the k-core; and the transformation efficiency of innovation value in three coastal provinces is relatively higher, while that of the rest of the provinces is roughly the same among the 30 provinces. (shrink)