This study investigates the diverse experiences of photographic and general tourists in Pingyao Ancient City, China, through the lens of the Tripartite Model of Attitudes, emphasizing sustainable heritage tourism practices. By integrating cognitive, emotional, and behavioral analyses, it unravels how these groups interact with and perceive the heritage environment. The research reveals that photographic tourists primarily focus on the city's visual, architectural and historical appeal, while general tourists show a broader engagement, encompassing practical, experiential, and cultural aspects. Sentiment analysis indicates a higher positive emotional response among photographic tourists, in line with their aesthetic interests, whereas general tourists exhibit a wider emotional range. Geographic Information Systems data analysis underscores photographic tourists' extensive exploration in visually appealing areas, contrasting with the more centralized movements of general tourists, reflecting their varied heritage interests. The findings highlight the importance of developing customized tourism strategies to cater to diverse preferences, enhancing visitor satisfaction and promoting sustainable tourism at heritage sites. This study contributes to heritage tourism management by advocating a multi-dimensional approach, ensuring a balance between visitor experience optimization and sustainable heritage preservation.

Objective Proper illuminance environment plays an important role in improving the service level of metro stations, ensuring the safety of passenger evacuation and promoting the sustainable development of public transportation. In order to promote the scientific and proper illuminance environment design in metro stations, it is necessary to study the influence of different illuminance environments on passengers′ subjective emotions and visual performance cognition. Method Based on the integration of the eye movement tracking technology, visual performance cognitive evaluation technology, and the three-dimensional emotion evaluation model, a calculation method is proposed, which consists of three evaluation categories and a total of 8 parameters, i.e. eye movement test evaluation, visual performance cognitive evaluation and subjective emotion evaluation. The test process is set up with illuminance as variable and 5 illuminance levels are selected for test research. The relationship model between different illuminances and the parameters of passengers′ subjective emotion and visual performance cognition is constructed. Test results are treated with one-way ANOVA (analysis of variance), correlation analysis and comprehensive analysis. Result & Conclusion The results show that the illuminance has significant effects on passengers′ subjective PAD (pleasantness, arousal, dominance) and visual cognitive performance. Improving passengers′ pleasure and arousal emotions can shorten their visual cognition time. When the illuminance is between 200~230 lx, the passengers′ subjective emotion and visual performance cognition will reach the optimal level.

The positioning control of the hydraulic support pushing system in the fully mechanized mining face is the key technical support to realize intelligent mining. The opening and closing of the existing support switch reversing valve will cause a sudden change in the system pressure and flow under the conditions of high pressure and large flow, which will affect the life of the components, the precision, and stability of the actuator movement. To solve the problem, the structure of a two-speed buffer valve for the hydraulic support pushing circuit is designed. Firstly, the pushing system is analyzed theoretically, and the characteristics of the flow field in the valve and the applicable working conditions are simulated. Then, an experimental platform was built to test the improvement effect of the two-speed buffer valve on the characteristics of the pushing system. Finally, the pressure, flow, and positioning characteristics of the two-valve series pushing system under different flow rates are studied by the test results. The research results show that when the two-speed buffer valve is used, the pressure and velocity change thresholds of the system are reduced, which reduces the pressure fluctuation in front of the valve and its effect on the system pressure. At the same time, under a different system flow, the downstream pressure characteristics of the valve are improved, and the steady-state pressure anti-interference is enhanced. The positioning error of the system is reduced under different flow rates. The effectiveness of the scheme is verified by the test, which provides a basis for the optimization of the downhole valve control cylinder scheme and the subsequent valve.

China's construction, energy consumption, and emissions are the world's largest, making green building (GB) crucial for sustainable development and climate action. GB policies play a crucial role in promoting sustainable development and mitigating environmental impacts. This paper presents a comprehensive analysis of China's GB policies at both central and local levels using natural language processing (NLP), Latent Dirichlet Allocation (LDA), and semantic network analysis (SNA). It also integrates three theoretical frameworks: Policy Implementation Theory, Sustainable Development Theory, and Innovation Diffusion Theory. The study aims to: (1) compare the characteristics of central and local GB policies; (2) identify problems and propose solutions to improve policy effects and impacts. The results show that both levels of policies cover various sustainability aspects but with different focuses. The SNA reveals the semantic relationships and differences within the policy documents. The study suggests several strategies to enhance GB policy effectiveness and sustainability, based on the three theoretical frameworks. These strategies include providing more specific guidance, enhancing financial support and incentives, promoting technological advancements, strengthening monitoring and evaluation, adopting a more systematic approach, democratizing policy formulation, identifying key stakeholders and influencers, and considering innovation characteristics. This study contributes to the GB policy research and practice in China. It is also the first study to use NLP, LDA, and SNA to comprehensively analyze China's GB policies, and the first study to apply the three theoretical frameworks to GB policy analysis.

As a medium to improve the environmental quality of underground space, color affects people's comfort experience. In order to quantitatively study the relationship between color and visual comfort in subway space, this study used the eye-tracking technology to discuss more comfortable color attribute matching in subway space from three aspects of color saturation, brightness and hue. The standard subway station in Taiyuan of Shanxi province was used as the research object, and the relationship model between the three attributes of color and visual comfort was established through multiple regression analysis. The results show that when the saturation was 48%–60%, the brightness was 52%–68%, or the hue was orange, yellow and green, human visual perception was more comfortable. Moreover, it was also proved that the pupillary unrest index and saccade rate in the eye movement index were significantly negatively correlated characteristics with the user's comfort, which can be served as the evaluation parameters of visual comfort. At the same time, the validity of the established model was also verified by on-site investigation of 20 subway stations in Taiyuan, Xi'an and Chengdu, China. This research can provide a valuable index reference for practitioners' design decision-making process, and offer an effective method for the objective quantification of the future spatial color design.

An ice types recognition and ice thickness detection system was designed based on capacitance and impedance double parameters. By studying the influence of electrode structure on sensor performance based on finite element simulation, the finger electrode was selected with better performance, and a planar electrode sensor was designed suitable for wing thin ice detection. After the thin ice (2.5 mm) making experiment, the capacitance and impedance spectra of three ice types (glaze ice, rime ice and mixed ice) were obtained. Among them, capacitance can reflect the growth of ice well, and the impedance spectra of different ice types are significantly different. Therefore, a capacitance-based regression model and an impedance-based classification model were built. The results of regression model show that about 90% of the calculation error of thin ice thickness is concentrated in the range of [−0.2 mm, 0.2 mm]. Finally, a field test was conducted in the ice wind tunnel to preliminarily determine the system effectiveness.

Hydraulic engineering built in the cold region, such as reservoirs and hydropower stations, is often threatened by static ice pressure from nature. Therefore, it is of vital significance to research the pressure variation in the growth and melting processes of the ice layer for the design and protection of hydraulic structures in cold regions. This paper introduces an optical fiber sensor system based on the fiber loop ring-down spectroscopy technology and field-programmable gate array (FPGA) pulse modulation technology. An electro-optic modulation scheme that relied on FPGA to generate optical pulses with adjustable pulse width and period is proposed, which is more suitable for the in-situ observation. In addition, the temperature stability and repeatability of the system are also discussed. This system was applied to the real-time detection of static ice pressure on the sidewall and bottom of the polyvinyl chloride (PVC) pipe during the ice growth and melting processes. The results indicate that the system has favorable stability and sensitivity, and the relationship obtained between the static ice pressure and temperature could provide some references for the field application in the future.

Compared with the strong background noise, the energy entropy of early fault signals of bearings are weak under actual working conditions. Therefore, extracting the bearings’ early fault features has always been a major difficulty in fault diagnosis of rotating machinery. Based on the above problems, the masking method is introduced into the Local Mean Decomposition (LMD) decomposition process, and a weak fault extraction method based on LMD and mask signal (MS) is proposed. Due to the mode mixing of the product function (PF) components decomposed by LMD in the noisy background, it is difficult to distinguish the authenticity of the fault frequency. Therefore, the MS method is introduced to deal with the PF components that are decomposed by the LMD and have strong correlation with the original signal, so as to suppress the modal aliasing phenomenon and extract the fault frequencies. In this paper, the actual fault signal of the rolling bearing is analyzed. By combining the MS method with the LMD method, the fault signal mixed with the noise is processed. The kurtosis value at the fault frequency is increased by eight-fold, and the signal-to-noise ratio (SNR) is increased by 19.1%. The fault signal is successfully extracted by the proposed composite method.