A Method of Domain Dictionary Construction for Electric Vehicles Disassembly

Currently, there is no domain dictionary in the field of electric vehicles disassembly and other domain dictionary construction algorithms do not accurately extract terminology from disassembly text, because the terminology is complex and variable. Herein, the construction of a domain dictionary for the disassembly of electric vehicles is a research work that has important research significance. Extracting high-quality keywords from text and categorizing them widely uses information mining, which is the basis of named entity recognition, relation extraction, knowledge questions and answers and other disassembly domain information recognition and extraction. In this paper, we propose a supervised learning dictionary construction algorithm based on multi-dimensional features that combines different features of extraction candidate keywords from the text of each scientific study. Keywords recognition is regarded as a binary classification problem using the LightGBM model to filter each keyword, and then expand the domain dictionary based on the pointwise mutual information value between keywords and its category. Here, we make use of Chinese disassembly manuals, patents and papers in order to establish a general corpus about the disassembly information and then use our model to mine the disassembly parts, disassembly tools, disassembly methods, disassembly process, and other categories of disassembly keywords. The experiment evidenced that our algorithms can significantly improve extraction and category performance better than traditional algorithms in the disassembly domain. We also investigated the performance algorithms and attempts to describe them. Our work sets a benchmark for domain dictionary construction in the field of disassembly of electric vehicles that is based on the newly developed dataset using a multi-class terminology classification.     

Production of Atosiban’s Key Intermediate Pentapeptide: Synthetic Approaches to the Development of a Peptide Synthesis with Less Racemization and Simplifier Purification Process

The key intermediate NH₂-Ile-Thr(Bzl)-Asn-Cys(Bzl)-Pro-COOH of Atosiban was prepared from N-Boc-S-Bzl-cysteine by the stepwise lengthening of the chain according to the repetitive N,O-bis(trimethylsilyl)acetamide/N-hydroxysuccinimide ester (BSA/NHS) strategy. This synthetic route required no chromatography purification and can be readily performed, yielding a highly pure pentapeptide compound.     

Identification of Biomarker Volatile Organic Compounds Released by Three Stored-Grain Insect Pests in Wheat

Monitoring and early detection of stored-grain insect infestation is essential to implement timely and effective pest management decisions to protect stored grains. We report a reliable analytical procedure based on headspace solid-phase microextraction coupled with gas chromatography–mass spectrometry (HS-SPME-GC-MS) to assess stored-grain infestation through the detection of volatile compounds emitted by insects. Four different fibre coatings were assessed; 85 µm CAR/PDMS had optimal efficiency in the extraction of analytes from wheat. The headspace profiles of volatile compounds produced by Tribolium castaneum (Herbst), Rhyzopertha dominica (Fabricius), and Sitophilus granarius (Linnaeus), either alone or with wheat, were compared with those of non-infested wheat grains. Qualitative analysis of chromatograms showed the presence of different volatile compound profiles in wheat with pest infestation compared with the wheat controls. Wheat-specific and insect-specific volatile compounds were identified, including the aggregation pheromones, dominicalure-1 and dominicalure-2, from R. dominica, and benzoquinones homologs from T. castaneum. For the first time, the presence of 3-hydroxy-2-butanone was reported from S. granarius, which might function as an alarm pheromone. These identified candidate biomarker compounds can be utilized in insect surveillance and monitoring in stored grain to safeguard our grain products in future.     

GDP vs. LDP: A Survey from the Perspective of Information-Theoretic Channel

The existing work has conducted in-depth research and analysis on global differential privacy (GDP) and local differential privacy (LDP) based on information theory. However, the data privacy preserving community does not systematically review and analyze GDP and LDP based on the information-theoretic channel model. To this end, we systematically reviewed GDP and LDP from the perspective of the information-theoretic channel in this survey. First, we presented the privacy threat model under information-theoretic channel. Second, we described and compared the information-theoretic channel models of GDP and LDP. Third, we summarized and analyzed definitions, privacy-utility metrics, properties, and mechanisms of GDP and LDP under their channel models. Finally, we discussed the open problems of GDP and LDP based on different types of information-theoretic channel models according to the above systematic review. Our main contribution provides a systematic survey of channel models, definitions, privacy-utility metrics, properties, and mechanisms for GDP and LDP from the perspective of information-theoretic channel and surveys the differential privacy synthetic data generation application using generative adversarial network and federated learning, respectively. Our work is helpful for systematically understanding the privacy threat model, definitions, privacy-utility metrics, properties, and mechanisms of GDP and LDP from the perspective of information-theoretic channel and promotes in-depth research and analysis of GDP and LDP based on different types of information-theoretic channel models.     

氮掺杂改性二氧化钛光催化剂的研究进展

综述了近年来国内外利用氮掺杂改性二氧化钛的光催化剂性能、提高可见光的利用效率的最新研究进展;分析和讨论了氮掺杂二氧化钛的制备方法、理论计算和结构模型、掺杂机理等;总结了氮掺杂改性二氧化钛存在的问题,同时讨论了今后的研究方向.     

Dynamic crossover in [VIO~(2+)][Tf_2N~-]_2 ionic liquid

Ionic liquids usually behave as fragile liquids,and the temperature dependence of their dynamic properties obeys supper-Arrhenius law.In this work,a dynamic crossover is observed in([VIO²⁺][Tf₂N-]₂) ionic liquid at the temperature of 240-800 K.The diffusion coefficient does not obey a single Arrhenius law or a Vogel-Fulcher-Tammann(VFT) relation,but can be well fitted by three Arrhenius laws or a combination of a VFT relation and an Arrhenius law.The origin of the dynamic crossover is analyzed from correlation,structure,and thermodynamics.Ion gets a stronger backward correlation at a lower temperature,as shown by the fractal dimension of the random walk.The temperature dependence function of fractal dimension,heterogeneity order parameter,and thermodynamic data can be separated into three regions similar to that observed in the diffusion coefficient.The two crossover temperatures observed in the three types of data are almost the same as that in diffusion coefficient fitted by three Arrhenius laws.The results indicate that the dynamic crossover of[VIO2+][Tf2 N-]2 is attributed to the heterogeneous structure when it undergoes cooling.     

ICP-AES测定Ni-Cr合金在人工唾液中析出的Ni离子

在模拟口腔环境下用人工唾液浸泡Ni-Cr桥,150h后采用ICP-AES测定Ni-Cr桥在人工唾液中的Ni离子析出量.镍在0.01-7.5μg/mL内有良好的线性关系,相关系数为0.9998;方法检出限为0.0059μg/mL;标准加入法测定镍的回收率为92.3%-99.8%.     

Phases of supersymmetric gauge theories with flavors

We explore the phases of supersymmetric U(N) gauge theories with fundamental matter that arise as deformations of SQCD by the addition of a superpotential for the adjoint chiral multiplet. As the parameters in the superpotential are varied, the vacua of this theory sweep out various branches, which in some cases have multiple semiclassical limits. In such limits, we recover the vacua of various product gauge group theories, with flavors charged under some group factors. We describe in detail the structure of the vacua in both classical and quantum regimes, and develop general techniques such as an addition and a multiplication map which relate vacua of different gauge theories. We also consider possible indices characterizing different branches and potential relationships with matrix models.