In April 2023, the government of Changshu City, in Jiangsu Province, China, announced that it would officially use digital Chinese Yuan (E-CNY) as a method of wage payment to the government and state-owned enterprises staff starting in May. With the gradual improvement and application of E-CNY technologies, such as no electricity, no internet payment (offline payment), and the programmability of smart contracts, E-CNY will be officially used in China. CNN said China is on the verge of a cashless society. The advantages of E-CNY have a positive role in promoting the Chinese government’s implementation of the development goals of a low-carbon and sustainable economy. However, artificial intelligence (AI) trust concerns are the primary bottleneck in the current development based on intelligent algorithms and digital information technology. AI trust concerns are affecting the scope of use of E-CNY, and it may need to achieve effective scale-use, making it promote low-carbon and sustainable development. From the industry perspective, this article selects the housing rental enterprises, which are challenging to develop and energy-intensive, to analyze the theoretical approach and practical impact of E-CNY in promoting the low-carbon and sustainable development of China’s rental housing economy. Meanwhile, from the perspective of Chinese consumers, the impact of AI trust concerns on E-CNY in promoting low-carbon and sustainable development is analyzed in this article.

In the era of rapid information technology development, artificial intelligence (AI) and virtual reality (VR) technologies have gradually infiltrated the field of university English teaching, brought significant applications and impacted to English language learning in listening, speaking, writing, translation, and personalized learning. AI plays a vital role as an auxiliary teaching method in university English instruction, and the integration of VR technology further enhances teaching efficiency. This research will propose relevant recommendations to provide theoretical references for university English education in the age of AI, while also offering insights and guidance to educators in the education industry during the informatization reform of education.

Based on the characteristics of liquid lens sparse aperture imaging, a radiative multiplet array structure is proposed; a simplified model of sparse aperture imaging is given, and the analytical expression of the modulation transfer function is derived from the optical pupil function of the multiplet array structure; the specific distribution form of this multiplet array structure is given, and the structure parameters are approximated by the dimensionless method; the two types of radiative multiplet array structures are discussed, and the filling factor, redundancy, modulation transfer function and other characteristic parameters are calculated. The physical phenomena exhibited by the parametric scan are discussed, and the structural features and imaging characteristics of these two arrays are compared. The results show that the type-II structure with larger actual equivalent aperture and actual cutoff frequency and lower redundancy is selected when the average modulation transfer function and the IF characteristics of the modulation transfer function of the two structures are close to each other; the type-II structure has certain advantages in imaging; the conclusion is suitable for arbitrary enclosing circle size because the liquid lens-based multiplet array structure adopts dimensionless approximation parameters; compared with the composite toroidal structure, the radiative multiplet mirror structure has a larger actual cut-off frequency and actual equivalent aperture when the filling factor is the same.

With the development of social economy, the current urban traffic problem is more prominent. In order to solve this problem very well, the idea of establishing intelligent traffic management came into being. The establishment of intelligent traffic management, cannot do without the signal launch and reception. Therefore, how to set up some wireless signal transmitting device in time to travel on the road motor vehicles to send traffic information and how to achieve full coverage of the signal and signal stability is our article to discuss the issue. For the first question, we must separate the motorway and non-motorway from all roads. Motorway lanes are usually straight and long. While the bends are usually just sidewalks or bike lanes (non-motorized lanes). So the 121 road can be clustered analysis, clustering of the two indicators for each road length (the distance between the adjacent points) and the collection point of density (by drawing, you can observe the more curved the denser the road collection point, so the road curvature into the collection point of the intensity), the result of clustering can get 48 motor lanes. And then through regress function regression and data fitting to achieve an approximate description of each type of motor vehicle description model, so that each road in a given latitude (latitude) coordinates to determine the latitude (longitude) coordinates and the corresponding altitude. For the problem of two, according to the meaning of the road to know the signal strength is only related to the distance between the sampling point and the launch device, so you can 'the motor vehicle between the signal reception is relatively close to' this indicator into ' The average of the distance between all the sampling points and the transmitting device is close to '. By reading the data will be latitude and longitude conversion distance length, so that the maximum value as small as possible. The position of the launcher can be obtained by programming by MATLAB. When considering the altitude, only the position of the transmitting device can be changed. (9.7824,56.7720), and the position coordinates when considering the altitude are D (9.7459, 56.7586, 73.5645), and the position coordinate of the signal device is B (9.7824, 56.7720). For question three, note the effect of the original signal device A on the result. We still use the average of the distance between all the sampling points of the road and the launcher to characterize the stability of the signal reception. The average distance of all non-motorized trains to the original signal device A is first determined, and then the average distance of all non-motorized lanes from the new signal device B is set, and the signal acceptance strength of the non-motorized lane can be used to characterize. And then use the same method in question two to determine the location of the new signal transmitter. Finally, the coordinates of the position of the new signal device are E (9.7459,56.7586,73.5645).