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The construction process of asphalt pavement in highway construction projects is a key link in energy consumption and emissions, and the production of asphalt mixing stations is the main energy consumption link of asphalt pavement. Currently, targeted energy consumption evaluation and monitoring of asphalt mixing stations still lack systematic research. This article first determines the evaluation indicators for energy conservation and emission reduction of asphalt pavement. By decomposing the energy consumption composition of the asphalt mixing station, a energy consumption evaluation system for the asphalt mixing station consisting of three parts: heating drum, asphalt heating and insulation system, and power system is established. After calculation, the predicted natural gas conversion rates for each ton of SMA-13 asphalt mixture in the upper layer, AC-20 asphalt mixture in the middle layer, and AC-25 asphalt mixture in the lower layer are 8.07, 7.41, and 6.87 m3, respectively. The predicted results fit well with the measured data. Finally, through the development of hardware and software, the energy consumption evaluation and monitoring of asphalt mixing stations based on the Internet of Things were achieved, which played a promoting role in the environmental protection evaluation of highway pavement construction.

With the development of society and economy, land subsidence in soft soil areas has become a prominent geological disaster in our country’s coastal area. Land subsidence has the characteristics of irreversibility, wide influence range, long aging, etc., and these characteristics are closely related to the characteristics of soft soil, such as physical and mechanical parameters, microstructure characteristics, etc. The Nansha District of Guangzhou was taken as the study area in this paper. Through the collection of preliminary data, two-dimensional scanning electron microscopy, and three-dimensional Computed Tomography (CT), the micro-structure characteristics of soft soil are expounded and its plugging characteristics are further analyzed. The results show that the study area’s soft soil has a honeycomb, granular, and flocculent structure. From the perspective of pore scale distribution, the number of macropores and ultramicro pores is small, and the continuity is poor. In most small and medium pores, namely the aggregate and granular pores. The siltation of soft soil is closely related to the microstructure of soil and can be treated according to the effect of siltation characteristics on the consolidation settlement of soft soil. The research results of this paper can provide targeted prevention and control suggestions for the soft land subsidence disaster in the Nansha area, and also provide a reference for other similar research.

Based on the methods of literature survey, interview survey and questionnaire survey, this paper selects Xiaojin, Danba, Kangding, Luding, Puge and Butuo County as the survey sites of multi-ethnic areas in Sichuan Province. After obtaining the first-hand data and data of local dialect usage, family language habits and family economic conditions, it empirically analyzes the relationship between dialect diversity and economic income and comes to a conclusion that in the multi-ethnic areas of Sichuan Province, dialect diversity has a significant negative impact on the level of economic income. On the basis of deepening the understanding of the relevance between language and economy, this paper provides some reference for the government to carry out reasonable language planning in ethnic areas.

There is a relatively new economic growth theory that culture is a deeper force to explain economic growth. This paper will establish an economic growth model based on Solow model, and discuss the economic growth of multi-ethnic areas from the perspective of language economics. On the basis of literature research, this paper first puts forward the conjecture that dialect diversity has a negative impact on the economic income level of multi-ethnic areas. In order to verify this conjecture, this paper selects Xiaojin County, Danba County, Puge county and Butuo County of Sichuan Province as the investigation objects. After screening more than 200 effective data, the least square linear regression model is used to carry out empirical analysis. Through White Heteroscedasticity Test and WLS Heteroscedasticity Test, the hypothesis that dialect diversity has a negative impact on economic income level in multi-ethnic areas is verified.

At present, clinical psychologists at home and abroad have applied artificial intelligence to the treatment of mental illness and have achieved certain results. Artificial intelligence has tried to be applied to various fields of mental health and hygiene. This article reviews the application of artificial intelligencerelated technologies in mental health, including the application of artificial intelligence to mental illness identification and early warning intervention, and the application of artificial intelligence to the mental level of the elderly, and discusses its advantages, disadvantages and prospects.

The spatial high-resolution synthetic aperture radar (SAR) for ocean exploration puts forward higher requirement for output power and amplitude-phase consistency of the pulsed TWT amplifier. The kW class pulsed TWT amplifier based on broadband power combining is the key technology for space SAR applications. In this paper, the factors affecting the amplitude and phase consistency of MPM are studied, and a phase consistency compensation circuit was designed to improve the phase consistency of multiple sets of products. A microwave power model (MPM) with dual TWTs output integrated architecture was proposed which consists of two short travelling wave tubes (TWT), two solid-state power amplifiers (SSPA), and an electronic power conditioner (EPC). More than 45% efficiency is achieved in 15% duty cycle within 600 MHz bandwidth, and the phase consistency was less than ± 5 degrees.With the improvement of synthesis efficiency, higher synthesis power and higher sensitivity of ocean wide scanning and detection can be obtained

Energy efficiency is one of our most economical sources of new energy. When it comes to efficient building design, the computation of the heating load (HL) and cooling load (CL) is required to determine the specifications of the heating and cooling equipment. The objective of this paper is to model heating load and cooling load buildings using neural networks in order to predict HL load and CL load. Rprop with genetic algorithm was proposed to increase the global convergence capability of Rprop by modifying a corresponding weight. Comparison results show that Rprop with GA can successfully improve the global convergence capability of Rprop and achieve lower MSE than other perceptron training algorithms, such as Back-Propagation or original Rprop. In addition, the trained network has better generalization ability and stabilization performance.