馬克思主義概念翻譯在中國1900-1949

本論文探討馬克思主義經由翻譯介紹到中國的歷史過程。馬克思主義作為中共立國的意識形態，已經成為一種權威的話語。但在本世紀初經由翻譯傳入的馬克思主義，並不是一套教條。在二十世紀初到二、三十年代間，多種思潮互相衝擊，馬克思主義在翻譯傳入的過程中，也是知識份子分析社會矛盾性質和思考社會變革的思想資源。對馬克思主義的翻譯與介紹，揭示了翻譯本身是在一定的文化政治的位置中的論述踐行。 本論文以幾個馬克思主義概念為例，將這些概念置放於其歷史脈絡中，考察這些概念在個別知識份子的著述中怎樣被理解，討論翻譯的過程中牽涉的各種閱讀策略，並嘗試說明它們如何構築各種身分。論文嘗試說明這些概念的互譯性是藉著種種論述與實踐建立起來的

Operation State Identification Method for Converter Transformers Based on Vibration Detection Technology and Deep Belief Network Optimization Algorithm

The converter transformer is a special power transformer that connects the converter bridge to the AC system in the HVDC transmission system. Due to the special structure of the converter transformer, it is necessary to test its operation state during its manufacture and processing to ensure the safety of its future connection to the grid. Numerous studies have shown that vibration signals in transformers can reflect their operating state. Therefore, in order to achieve an effective identification of the operation state of the converter transformer, this paper proposes a method for identifying the operation state of the converter transformer based on vibration detection technology and a deep belief network optimization algorithm. This paper firstly describes the background, principle and application of vibration detection technology, using vibration measurement systems with piezoelectric acceleration sensors, piezoelectric actuators and data acquisition instruments to collect vibration signals at different measurement points on the converter transformer in states of no-load and on-load. By analyzing the time-frequency characteristics of the vibration signals, fast Fourier transform (FFT), wavelet packet decomposition (WPD) and time domain indexes (TDI) are combined into a fused feature extraction method to extract the eigenvalues of the vibration signals, so that the fused eigenvectors of the signals can be constructed. Considering the excellent performance of deep learning in classification, the deep belief network is used to classify the signals’ eigenvectors. To effectively improve the network classification efficiency, the sparrow search algorithm was introduced to build a mathematical model based on the behavioral characteristics of sparrow populations and combine the model with a deep belief network, so as to achieve adaptive parameter optimization of the network and accurate classification of the signals’ eigenvectors. The proposed method is applied to a 500 kV converter transformer for experimental verification. The experimental results show that the fused feature extraction method was able to fully extract the features of the vibration signal, and the deep belief network optimization algorithm had higher classification accuracy and better operational efficiency, and was able to effectively achieve accurate identification of the operation state of the converter transformer. In addition, the method achieved a precision response to the detection results of the vibration sensors, contributing to future improvements in converter transformer manufacturing technology

Synthetic Strategies for Macrocyclic Peptides

Peptide macrocycles form an outstanding class of natural and synthetic bioactive compounds. This chapter discusses synthetic strategies for the final ring‐closing reaction by the widely employed and versatile processes of lactamization, lactonization, and disulfide bridge formation. According to the nature of the chemical bond found in the backbone, cyclic peptides can be classified in two major categories: homodetic peptides and heterodetic peptides. In principle, all methods suitable for peptide bond formation can be applied for head‐to‐tail macrocyclization of linear peptides; however the reaction usually proceeds more slowly than the corresponding bimolecular version. During synthesis design, the C‐terminal amino acid of the linear precursor and the coupling reagent should be carefully chosen to minimize epimerization at the C‐terminal residue during cyclization. In many cases, the solution‐phase strategy is the best choice for performing the macrocyclization step, especially when larger quantities of cyclic peptide are required