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In the context of globalization, the reconstruction of material spaces and the evolution of social relations have accelerated the loss of emotions in traditional villages. Intangible heritage can play an important role in the emotional maintenance of traditional villages as an emotional carrier for its residents. Previous studies have been less involved in the synergistic relationship between the interactive game of power subjects and the evolution of emotions in the practice of intangible heritage. Particularly, research on the evolution of the emotional exchange mode is insufficient. Taking the Dong minority chorus of Huangdu Village as an example, this study adopts qualitative research methods, such as semi-structured interviews and participant observation, to construct an analytical framework of "daily life practice-emotional exchange", and to deeply explore the evolution process and motivational mechanism of the emotional exchange mode in the daily life practice of traditional village residents. The study found that: 1) According to the changes in the subject and relationship, motive and mode, resource and situation, perception and experience of emotional exchange in the natural, livelihood, institutional, and spiritual dimensions, the daily life practice of Huangdu Village can be divided into four stages: primitive equilibrium, passive compromising, active resisting, and regenerating. 2) In the process of intangible cultural heritage practices, the manipulation of capital and the suppression of power have broken the original balance of Huangdu Village, and the division of power and status among subjects has squeezed the living spaces of local residents, forcing them to become involved in power struggles. They resist the control of the "other" by means of physical empowerment and restatement of the local subjectivity, and ultimately strike a balance of power within the village. In the daily practice of intangible cultural heritage, the mode of residents' emotional exchange changes from reciprocity to general negotiation and production modes. 3) Emotional exchanges in traditional villages are produced during power struggles between residents and other subjects. When power is balanced, residents master the discourse of intangible cultural heritage and produce positive emotions such as attachment and belonging. When residents are suppressed by power and capital, they gradually lose discourse and produce negative emotions, such as a sense of crisis and separation. 4) The evolution of emotional exchange modes in the daily practices of traditional village residents is systematic. The evolution of the outer system pushes the kernel system to adapt, and the driving, pulling, and supporting forces promote the synergistic evolution of "daily life―emotional exchange―intangible cultural heritage practice" in Huangdu village. The evolution of emotional exchange patterns during the practice of the Dong minority chorus in Huangdu Village was an inevitable process for reconstructing the cultural subjectivity of local residents in the context of tourism development. Exploring emotional exchange patterns at different stages of daily life practices can help understand the developmental law of traditional villages and provide useful references for its emotional governance and sustainable development.

By reviewing and studying relevant historical materials, this study presents the advanced and fruitful clinical teaching in Peking Union Medical College Hospital(PUMCH) nearly a hundred years ago. It proved that the clinical teaching of PUMCH had reached the internationally advanced level in 1925. The bed-side teaching, case discussion, multidisciplinary joint ward round, interdisciplinary teaching, and resident training system still have practical significance presently. As it turns out, many of the teachers who were passionate about teaching and students who were actively involved in teaching went on to become medical masters. The spirit of taking teaching as an honor, responsibility and mission has been passed on and deeply rooted in the spirit of PUMCH and has remained unchanged for a century.

To better predict the lateral displacements of diaphragm walls during deep excavation, a long short-term memory (LSTM) multi-step prediction model is developed in this paper based on the LSTM algorithm. First, the multi-output strategy of multi-step prediction model is discussed. Then, the construction method of the LSTM multi-step prediction model is introduced in detail, and the two hyperparameters, i.e., the space and time dimensions of the model input set, are explored to improve the prediction accuracy of the model. Finally, the errors between the predicted values and the field monitoring data are analyzed based on an excavation project buried in water-rich sandy strata. The analysis results of three typical monitoring points indicate that the LSTM prediction model is characterized by solid generalization ability, and the relevant algorithm is practically helpful for improving and optimizing deformation prediction methods of deep excavation.

Conforms to: doi:10.34847/cocoon.49aefa90-8c1f-3ba8-a099-0ebefc6a2aa7 Enregistrement des interactions de base en chinois

The soil unloading effect caused by the adjacent excavation will influence both the uplift and the deformation of the adjacent existing tunnel, and even interfere with the normal operation of the tunnel. A simplified calculation method for the longitudinal deformation of the underlying tunnel caused by foundation pit excavation is proposed. The tunnel is simplified into an infinitely long Euler-Bernoulli beam resting on a three-parameter Kerr foundation model. The difference method is combined with the boundary conditions at both ends of the tunnel to obtain the longitudinal deformation difference decomposition of the tunnel. The accuracy of the proposed method is proved by comparing it with the finite element simulation method and some cases study. Compared with the tunnel simplified as the Euler-Bernoulli beam which is placed upon the existing Pasternak foundation model, the Kerr foundation model has more advantages. As the elastic modulus of soil mass and the depth of tunnel axis increase, the longitudinal deflection and the inner force of the tunnel will decrease. The inner force of the tunnel will increase with the increment of the stiffness of the tunnel.

Control of the disturbed displacement of adjacent tunnel during excavation is a significant issue for design and construction. Based on the multi-objective optimization method, the multi-type monitoring data in the excavation of the excavation are integrated, the key soil parameters are inverted and identified, and the time effect of the tunnel displacement is quantified and corrected. A dynamic multi-objective optimization method with adaptive infill criterion (DMO-AIC) is proposed to improve the updating efficiency of dynamic surrogate models. The proposed method takes into account the computational redundancy of dynamic surrogate models in engineering optimization, and designs an adaptive point-adding discrimination strategy, which can autonomously identify invalid updates of surrogate models on the optimization path. The results show that the proposed DMO-AIC significantly reduces the invocations of the black-box model during optimization while ensuring the good search performance and the convergence speed of the algorithm. The improved computational efficiency of DMO-AIC is helpful for the application of dynamic surrogate models in engineering optimization. The results of the virtual numerical example show that DMO-AIC can predict and update multiple model responses during excavation, such as wall deflections and tunnel displacements. The engineering practice of Shanghai Bund 596 excavation indicates that the time effect is properly updated, and the staged vertical displacements of the adjacent tunnel are accurately predicted.

[Purpose/Significance] By jointly mining multiple diaries related to National South-west Associated University (NSAU), a social network graph of NSAU that integrates information from multiple sources is constructed. The aim is to discover more potential social relationships through joint mining of multiple diaries, and break through the limitations of single diary social network mining. [Method/Process] Using multiple diaries related to NSAU from 1938 to 1941 as corpus, Python program is used to count co-occurrence relationships of characters, and Gephi is used to construct multi-diary social network graph. Through social network analysis methods, the network topology features, character centrality features and character group features based on modularity and K-core are analyzed and discussed. [Result/Conclusion] Compared with independent diary mining, multi-diary social network joint mining showed more obvious network structure features, more decentralized and rich social relationship information, which can reveal more hidden social relationships, and has good application value in the field of digital humanities.

It is an era of "heritage" that we live in. After nearly two decades of practice and exploration, the social and academic circles have accumulated rich experience in the protection of intangible cultural heritage, especially the scholars of ethnology and art, who have made outstanding contributions to the development of intangible cultural heritage (ICH) protection system with local characteristics. However, comprehensive and critical geographical studies have paid less attention to this topic with less contribution. Firstly, this paper reviews the practice of intangible cultural heritage protection since 2003, starting from the birth of the concept of "intangible cultural heritage" and the revival of Chinese traditional folklore culture. The research progress of China's intangible cultural heritage is analyzed through the database of CNKI. And it is found that the intangible cultural heritage research has experienced two periods－rapid prosperity and steady growth, but relatively few papers have been published in high-quality and geographical journals. Due to the large number of related papers, it is impossible or unnecessary to exhaust all research topics. Therefore, based on the research and practical experience, three key topics in the academic research of intangible cultural heritage are summarized: "characteristics and the construction of meaning", "transmission and the reflection on systems", and "development and community initiative". And Section 3.1 focuses on the basic characteristics of intangible cultural heritage, the importance of intangible cultural heritage as social construction, and the significance of "making" intangible cultural heritage. The current basic laws and regulations for the protection and transmission of China's intangible cultural heritage－representative projects and representative transmitters of intangible cultural heritage are re-examined. It is called for respect for the views and opinions of community group when turning to the "community" in intangible cultural heritage. And it is believed that Chinese scholars have formed a new method and new theoretical system of intangible cultural heritage research with local Chinese characteristics, by actively learning from the academic achievements of western critical heritage research. Secondly, intangible cultural heritage has been incorporated into the national political system as an important cultural resource to promote the implementation of major national strategies. Rethinking the significance and role of intangible cultural heritage under the three geographical national strategies of rural revitalization, urban development and cultural nation, it is found that as a unique cultural resource, intangible cultural heritage plays an important role in promoting the implementation of major national strategies and urban and rural development. And it is believed that the social significance and academic value of intangible cultural heritage should be further explored continuously. Finally, five possible topics for geographers to study intangible cultural heritage are proposed in this paper－transmitters' daily life, social justice, mobility, natural and cultural interaction and international communication, so as to encourage and inspire the geographical research of intangible cultural heritage in the future.

This study introduced the development history and current research status of large language model (LLM), data query robot (DQR). Meanwhile, through empirical analyses, the practical application effect of LLM-based DQR and its role in dealing with the complex tasks of medical data querying and analysis in the field of digital medicine was explored, and it was confirmed that LLM-based DQR could provide non-technical people with an intuitive and convenient tool to significantly improve the querying efficiency and analysis capability of medical data. In addition, this paper discusses the limitations and potential of future development of LLM and DQR techniques in current applications, providing reference for further research and applications.

In response to the difficulty of existing attack detection methods in dealing with advanced persistent threat (APT) with longer durations, complex and covert attack methods, a model for APT attack detection based on attention mechanisms and provenance graphs was proposed.Firstly, provenance graphs that described system behavior based on system audit logs were constructed.Then, an optimization algorithm was designed to reduce the scale of provenance graphs without sacrificing key semantics.Afterward, a deep neural network (DNN) was utilized to convert the original attack sequence into a semantically enhanced feature vector sequence.Finally, an APT attack detection model named DAGCN was designed.An attention mechanism was applied to the traceback graph sequence.By allocating different weights to different positions in the input sequence and performing weight calculations, sequence feature information of sustained attacks could be extracted over a longer period of time, which effectively identified malicious nodes and reconstructs the attack process.The proposed model outperforms existing models in terms of recognition accuracy and other metrics.Experimental results on public APT attack datasets show that, compared with existing APT attack detection models, the accuracy of the proposed model in APT attack detection reaches 93.18%.