Yidali si xiang jia Weike de "Xin ke xue" de zhong yao xing bu xia yu Daerwen de "Wu zhong qi yuan", shi mei xue jia Zhu Guangqian wan nian tou ru zui duo jing li wan cheng de yi bu zhong liang ji yi zuo. Zhu Guangqian zai fan yi de tong shi, hai dui "Xin ke xue" jin xing le shen ru yan jiu. zai ben shu zhong, Zhu Guangqian xian shi e yao jie shao le "Xin ke (...) xue" de jing sui, ren wei Weike yan jiu li shi shi qiang diao qiong ben qiu yuan, yi bu luo zi ran fa wei qi dian, lun zheng ren lei ji she hui zhi du de fa zhan; hou you tou shi Weike de shi xue he mei xue, fen xi le wei ke dui xi fang zhe xue de ge xin he Zhongguo mei xue de ju da ying xiang, bing dai chu le Zhu Guangqian zi ji dui zi you ji ren dao zhu yi de zhui qiu. (shrink)

本書以20世紀80年代震動一時的“潘曉討論”為中心，為當代文學研究——特別是關於80年代文學的研究——帶入新的“問題意識”，一方面挑戰既有的線性文學史描述、豐富我們的文學研究範式；一方面將廣闊的社會、 文化“大本文”引入對於80年代具有代表性的文學“小文本”的解讀之中，以從方法上賦予當代文學研究以新質。.

本书分为两个部分，上篇是儒道情感哲学本论，下设三个独立章，分别探讨了儒家哲学和道家哲学注重情感的特点、儒家与道家情感哲学的义理诠释、儒道情感教育与情感实践。下篇论述儒道情感哲学的现代价值，研究了儒情与 道情理论与现当代中国的人格建构及人的精神健康而和谐的发展。.

This study investigates whether and how the intensity of social distancing from the Coronavirus disease 2019 (COVID-19) pandemic influences the corporate social responsibility (CSR) disclosure index. An empirical examination is carried out based on data from the Shanghai Stock Exchange from 2020 to 2022. CSR disclosure index is measured by the percentage of CSR-related press releases from the total press releases published on a certain day. The intensity of the COVID-19 pandemic is measured by the daily confirmed cases among the (...) population in China. This research uses the two-stage least squares regression model to alleviate the endogeneity issues. Findings reveal a reverse correlation between the intensity of the COVID-19 pandemic and the CSR disclosure. The results are consistent and robust to endogeneity tests and sensitivity analyses. Findings support the stakeholder–agency theory and indicate that Chinese managers tend to satisfy the shareholders' interests rather than those of other broad stakeholders. Moreover, Chinese managers tend to choose short-term survival rather than long-term development in times of social distancing. (shrink)

Ben shu jie shao le gong zi zhen, wei yuan, yan fu, kang you wei, tan si tong, liang qi chao, chen tian hua, zhang bing lin deng wan qing si xiang jia de zhe xue si xiang.

Depression is a common mental health illness worldwide that affects our quality of life and ability to work. Although prior research has used EEG signals to increase the accuracy to identify depression, the rates of underdiagnosis remain high, and novel methods are required to identify depression. In this study, we built a model based on single-channel, dry-electrode EEG sensor technology to detect state depression, which measures the intensity of depressive feelings and cognitions at a particular time. To test the accuracy (...) of our model, we compared the results of our model with other commonly used methods for depression diagnosis, including the PHQ-9, Hamilton Depression Rating Scale, and House-Tree-Person drawing test, in three different studies. In study 1, we compared the results of our model with PHQ-9 in a sample of 158 senior high students. The results showed that the consistency rate of the two methods was 61.4%. In study 2, the results of our model were compared with HAM-D among 71 adults. We found that the consistency rate of state-depression identification by the two methods was 63.38% when a HAM-D score above 7 was considered depression, while the consistency rate increased to 83.10% when subjects showed at least one depressive symptom. In study 3, 68 adults participated in the study, and the results revealed that the consistency rate of our model and HTP drawing test was 91.2%. The results showed that our model is an effective means to identify state depression. Our study demonstrates that using our model, people with state depression could be identified in a timely manner and receive interventions or treatments, which may be helpful for the early detection of depression. (shrink)

本书内容包括:导论、生命与智慧的根源、逻辑启蒙与熏习西方哲学、站在西方哲学巨人的肩上、复归中国哲学继承儒学衣钵等。.

ObjectiveThis study explores the relationship between physical exercise and school adaptation of junior middle school students and constructs a chain intermediary model through the intermediary role of psychological resilience and sports learning motivation.MethodsUsing the stratified cluster sampling method, 930 junior middle school students in Anhui Province were measured in group psychology by using the physical exercise rating scale, adolescent psychological resilience scale, physical learning motivation scale and school adaptation scale. The statistical software SPSS 23.0 and process plug-in were used for (...) statistical processing, and the common method deviation test was carried out by Harman single-factor control method. Finally, the bootstrap sampling test method and process plug-in were used to test the significance of intermediary effect.Results The direct prediction effect of physical exercise on school adaptation is remarkable ; psychological resilience and sports learning motivation are the intermediary variables of the relationship between physical exercise and school adaptation; psychological resilience and sports learning motivation play a chain mediation role in the relationship between physical exercise and school adaptation. The intermediary effect is composed of three indirect effects: physical exercise → psychological resilience → school adaptation, physical exercise → physical learning motivation → school adaptation, physical exercise → psychological resilience → physical learning motivation → school adaptation.ConclusionsPhysical exercise can directly improve the school adaptation of junior middle school students, which can also affect junior middle school students’ school adaptation indirectly through psychological resilience or sports learning motivation, and it can influence school adaptation through the chain mediation of psychological resilience and sports learning motivation. (shrink)

This study investigates the influence of chief executive officers' (CEOs) career horizon on the adoption of Global Reporting Initiative (GRI) standards for corporate social responsibility (CSR) reporting. Using data from A-share Chinese listed firms on the Shanghai and Shenzhen stock exchanges from 2010 to 2020, we employ logistic regression analysis to examine the empirical relationship. Our findings indicate that companies led by CEOs with shorter career horizons (older CEOs) are less inclined to adopt GRI reporting standards for CSR reporting. This (...) association is particularly pronounced in non-state-owned enterprises compared to state-owned enterprises. Additionally, we observe a weaker relationship between CEO career horizon and GRI adoption when the CEO possesses foreign experience. These results remain robust across various measures of CEO career horizons and econometric methodologies as well. The implications of our findings are significant for understanding the development and implementation of GRI standards for CSR reporting, particularly within the context of China. (shrink)

Conventional wisdom suggests mid-task rest as a potential approach to relieve the time-on-task (TOT) effect while accumulating evidence indicated that acute exercise might also effectively restore mental fatigue. However, few studies have explored the neural mechanism underlying these different break types, and the results were scattered. This study provided one of the first looks at how different types of fatigue-recovery break exerted influence on the cognitive processes by evaluating the corresponding behavioral improvement and neural response (EEG power spectral) in a (...) sustained attention task. Specifically, 19 participants performed three sessions of psychomotor vigilance tasks (PVT), with one session including a continuous 30-min PVT while the other two sessions additionally inserted a 15-min mid-task cycling and rest break, respectively. For behavioral performance, both types of break could restore objective vigilance transiently, while subjective feeling was only maintained after mid-task rest. Moreover, divergent patterns of EEG change were observed during post-break improvement. In detail, relative theta decreased and delta increased immediately after mid-task exercise, while decreased delta was found near the end of the rest-inserted task. Meanwhile, theta and delta could serve as neurological indicators to predict the reaction time change for exercise and rest intervention, respectively. In sum, our findings provided novel evidence to demonstrate divergent neural patterns following the mid-task exercise and rest intervention to counter TOT effects, which might lead to new insights into the nascent field of neuroergonomics for mental fatigue restoration. (shrink)

This paper aims to explore coevolution of emotional contagion and behavior for microblog sentiment analysis. Accordingly, a deep learning architecture is proposed for the target microblog. Firstly, the coevolution of emotional contagion and behavior is described by the tie strength between microblogs, that is, with the spread of emotional contagion, user behavior such as emotional expression will be affected. Then, based on user interaction and the correlation with target microblog, the Hawkes process is adopted to quantify the tie strength between (...) microblogs so as to build the corresponding weighted network. Secondly, in the weighted network, the Deepwalk algorithm is used to build the sequence representation of microblogs which are similar to the target microblog. Next, a CNN-BiLSTM-Attention network is designed to analyze the sentiment analysis of target and similar microblogs. Finally, the experimental results on two real Twitter datasets demonstrate that the proposed MSA-UITC has advanced performance compared with the existing state-of-the-art methods. (shrink)

To explore the change of brain connectivity in schizophrenics, the resting-state EEG source functional connections of SCZ and healthy control were investigated in this paper. Different band single-layer networks, multilayer networks, and improved multilayer networks were constructed and their topological attributes were extracted. The topological attributes of SCZ and HC were automatically distinguished using ensemble learning methods called Ensemble Learning based on Trees and Soft voting method, and the effectiveness of different network construction methods was compared based on the classification (...) accuracy. The results showed that the classification accuracy was 89.38% for α band network, 82.5% for multilayer network, and 86.88% for improved multilayer network. Comparing patients with SCZ to those with Alzheimer’s disease, the classification accuracy of improved multilayer network was the highest, which was 88.12%. The power spectrum in the α band of SCZ was significantly lower than HC, whereas there was no significant difference between SCZ and AD. This indicated that the improved multilayer network can effectively distinguish SCZ and other groups not only when their power spectrum was significantly different. The results also suggested that the improved multilayer topological attributes were regarded as biological markers in the clinical diagnosis of patients with schizophrenia and even other mental disorders. (shrink)

In recent years, self-paced learning has attracted much attention due to its improvement to nonconvex optimization based machine learning algorithms. As a methodology introduced from human learning, SPL dynamically evaluates the learning difficulty of each sample and provides the weighted learning model against the negative effects from hard-learning samples. In this study, we proposed a cognitive driven SPL method, i.e., retrospective robust self-paced learning, which is inspired by the following two issues in human learning process: the misclassified samples are more (...) impressive in upcoming learning, and the model of the follow-up learning process based on large number of samples can be used to reduce the risk of poor generalization in initial learning phase. We simultaneously estimated the degrees of learning-difficulty and misclassified in each step of SPL and proposed a framework to construct multilevel SPL for improving the robustness of the initial learning phase of SPL. The proposed method can be viewed as a multilayer model and the output of the previous layer can guide constructing robust initialization model of the next layer. The experimental results show that the R2SPL outperforms the conventional self-paced learning models in classification task. (shrink)

Two kinds of probability expressions, verbal and numerical, have been used to characterize the uncertainty that people face. However, the question of whether verbal and numerical probabilities are cognitively processed in a similar manner remains unresolved. From a levels-of-processing perspective, verbal and numerical probabilities may be processed differently during early sensory processing but similarly in later semantic-associated operations. This event-related potential (ERP) study investigated the neural processing of verbal and numerical probabilities in risky choices. The results showed that verbal probability (...) and numerical probability elicited different N1 amplitudes but that verbal and numerical probabilities elicited similar N2 and P3 waveforms in response to different levels of probability (high to low). These results were consistent with a level-of-processing framework and suggest some internal consistency between the cognitive processing of verbal and numerical probabilities in risky choices. Our findings shed light on possible mechanism underlying probability expression and may provide the neural evidence to support the translation of verbal to numerical probabilities (or vice versa). (shrink)

Dry port construction can reduce the cost of container transportation, and its location is the focus of existing research. Considering dry port capacity limitations and scale advantages, this study calculates the costs associated with dry port construction and operations, transportation, time, and the environment and constructs a joint optimization model of the dry port location and transportation scheme to minimize the total cost. Taking 35 prefecture-level cities in Northeast China as the source of container goods and Dalian port as the (...) destination, this study conducts an empirical analysis using the Gurobi 9.0.2 optimizer of the AMPL software to solve the problem and takes the minimum total cost as the goal to select the best dry port and container transshipment scheme. The research draws the following conclusions. Seven dry ports also need to be built in the road-rail mode, which shares 82.76% of the container transshipment volume, to reduce the total transportation cost by approximately 21.67%. Although multimodal transport through dry ports increases the time cost slightly, it can significantly reduce the economic and environmental costs of container transportation. (shrink)

Data heterogeneity is the obstacle for the resource sharing on Semantic Web, and ontology is regarded as a solution to this problem. However, since different ontologies are constructed and maintained independently, there also exists the heterogeneity problem between ontologies. Ontology matching is able to identify the semantic correspondences of entities in different ontologies, which is an effective method to address the ontology heterogeneity problem. Due to huge memory consumption and long runtime, the performance of the existing ontology matching techniques requires (...) further improvement. In this work, an extended compact genetic algorithm-based ontology entity matching technique is proposed, which uses both the compact encoding mechanism and linkage learning approach to match the ontologies efficiently. Compact encoding mechanism does not need to store and maintain the whole population in the memory during the evolving process, and the utilization of linkage learning protects the chromosome’s building blocks, which is able to reduce the algorithm’s running time and ensure the alignment’s quality. In the experiment, ECGA-OEM is compared with the participants of ontology alignment evaluation initiative and the state-of-the-art ontology matching techniques, and the experimental results show that ECGA-OEM is both effective and efficient. (shrink)