Field Composition and Development Trend of Research Hotspots of Translation Technology in China—Based on Co-word Visualization Analysis of Relevant Academic Journals from CNKI Published from 1999 to 2017

With the rapid development of computer technology and deep integration of disciplines, translation technology has gradually become an important research direction and a new focus of translation studies. In order to reveal the present situation of research on translation technology, we take the academic journals on translation technology from CNKI published between 1999 and 2017 as our data sample for analysis. The results show that the main research hotspots of translation technology cover four areas, i.e. computer-aided translation, human-computer interaction, translation technology teaching and talent training, as well as terminologies of the field. Through analysis of the current situation and existing problems in the above mentioned areas, some thoughts and prospects are put forward to provide guidance and illumination to scholars in this research field and promote further and deeper studies into the subject

A Probe Into the Sustainable Development of Petty Loan Companies

The petty loan companies in China have been in good performance since taken the pilot demonstration, which effectively relieves the rural funds and financing difficulties of SMEs. However, the petty loan companies in the business development also face many problems, such as the unreasonable legal status, the limited sources of funding, the heavy tax burden, high cost, and operational risks, and so on. These issues will be restricted to the sustainable development of petty loan companies. This thesis is in-depth analysis of the problems of petty loan companies in terms of sustainable development, and puts forward suggestions to promote the sustainable development of petty loan companies

Connections Between Ideals Of Semisimple Emv-algebras And Set-theoretic Filters

In this paper, we mainly study connections between ideals of the semisimple EMV-algebra M and filters on some nonempty set Ω. We show that there is a bijection between the set of all closed ideals of M and the set of all filters on Ω. We prove that the topological space of all closed prime ideals of M and the topological space of all weak ultrafilters on Ω are homeomorphic

Thermopower and Nernst measurements in a half-filled lowest Landau level

Motivated by recent proposal by Potter et al. [Phys. Rev. X 6, 031026 (2016)] concerning possible thermoelectric signatures of Dirac composite fermions, we perform a systematic experimental study of thermoelectric transport of an ultrahigh-mobility GaAs/AlxGa1-xAs two dimensional electron system at filling factor v = 1/2. We demonstrate that the thermopower Sxx and Nernst Sxy are symmetric and anti-symmetric with respect to B = 0 T, respectively. The measured properties of thermopower Sxx at v = 1/2 are consistent with previous experimental results. The Nernst signals Sxy of v = 1/2, which have not been reported previously, are non-zero and show a power law relation with temperature in the phonon-drag dominant region. In the electron-diffusion dominant region, the Nernst signals Sxy of v = 1/2 are found to be significantly smaller than the linear temperature dependent values predicted by Potter et al., and decreasing with temperature faster than linear dependence.Comment: 23 pages, 5 figure

Carbon Emission Prediction and Clean Industry Transformation Based on Machine Learning: A Case Study of Sichuan Province

This study preprocessed 2000-2019 energy consumption data for 46 key Sichuan industries using matrix normalization. DBSCAN clustering identified 16 feature classes to objectively group industries. Penalized regression models were then applied for their advantages in overfitting control, high-dimensional data processing, and feature selection - well-suited for the complex energy data. Results showed the second cluster around coal had highest emissions due to production needs. Emissions from gasoline-focused and coke-focused clusters were also significant. Based on this, emission reduction suggestions included clean coal technologies, transportation management, coal-electricity replacement in steel, and industry standardization. The research introduced unsupervised learning to objectively select factors and aimed to explore new emission reduction avenues. In summary, the study identified industry groupings, assessed emissions drivers, and proposed scientific reduction strategies to better inform decision-making using algorithms like DBSCAN and penalized regression models.Comment: 21 pages,19 figure