Tourism experiences are inherently multisensory, engaging visitors’ senses of sight, sound, smell, taste, and touch. This study addresses the gap in literature by investigating the impact of visual and auditory landscapes on tourist emotions and behaviors within coastal tourism settings, using the Stimulus-Organism-Response (SOR) model. Data collected from tourists in Sanya, China, were analyzed using structural equation modeling. The results indicate that both visualscape and soundscape significantly influence tourist emotions (pleasure and arousal) and subsequent loyalty. Pleasure and arousal mediate the relationships between environmental stimuli and tourist loyalty, emphasizing their roles as emotional bridges between the environment and behaviors. These findings highlight the importance of integrating local cultural and community elements into tourism to enhance socio-economic benefits and ensure sustainable development. By fostering a deep connection between tourists and the local environment, these sensory experiences support the preservation of cultural heritage and promote sustainable tourism practices, aligning with the goals of economic development and public policy. The study contributes to the theoretical understanding of multisensory tourism by integrating the SOR model in coastal tourism and emphasizes the roles of visual and auditory stimuli. Practically, it provides insights for tourism managers to improve tourist experiences and loyalty through careful management of sensory elements. This has implications for infrastructure development, particularly in enhancing the quality of soft infrastructure such as cultural and social systems, which are crucial for sustainable tourism and community well-being. Future research could include additional sensory dimensions and diverse destinations for a comprehensive understanding of sensory influences on tourist behaviors and emotions. This research aligns with the broader goals of the policy and development by addressing critical aspects of infrastructure and socio-economic development within the tourism sector.

High-quality development in China requires higher vocational education, scientific and technological innovation, and sustainable economic development. The spatial distribution patterns of these factors show higher levels in the east and coastal areas compared to the west and inland regions, emphasizing the need for coupling coordination with the social economy. This study examines the impact of sustainable economic development on the coupling coordination degree using the spatial Durbin model. The results show a positive promotion and spillover effect, with regional variations. The main factors affecting the difference in coupling coordination are the amount of technology market contracts, fiscal expenditure on science and technology, patent application authorizations, tertiary industry output value, and the number of R&D institutions. According to the grey prediction model, the coupling coordination degree is expected to increase from 2022 to 2025, but achieving primary coordination may still be challenging in some areas. Therefore, strategies that utilize regional characteristics for coordinated development should be developed to improve the level of coupling coordination and create a mutually beneficial environment.

This paper analyzes the characteristics and influence mechanisms of financial support for China’s strategic emerging industries. Using a sample of 356 listed companies across nine major industries, we conduct an in-depth analysis of the efficiency of financial support and its influencing factors. In addition, this paper analyzes the influence mechanism of financial support for strategic emerging industries based on the relevant theory of financial support for industry development. It clarifies the internal and external influencing factors. Based on the theoretical analysis, a two-stage empirical investigation was conducted: The data of 356 listed companies in strategic emerging industries from 2010 to 2022 were selected as a sample, and the data envelopment analysis (DEA) method was applied to measure efficiency. The influencing factors were then analyzed using a Tobit regression and an intermediate effects test.

This paper concerns a miniature gasifier fed with a constant ambient-pressure flow of air to study the pyrolysis and subsequent combustion stage of a single wood pellet at T = 800 ℃. The alkali release and the concentration of simple gases were recorded simultaneously using an improved alkali surface ionisation detector and a mass spectrometer in time steps of 1 s and 1.2 s, respectively. It showed alkali release during both stages. During combustion, the MS data showed almost complete oxidation of the charred pellet to CO₂. The derived alkali release, “O₂ consumed”, and “CO₂ produced” conversion rates all indicated very similar temporal growth and coalescence features with respect to the varying char pore surface area underlying the original random pore model of Bhatia and Perlmutter. But, also large, rapid signal accelerations near the end and marked peak-tails with O₂ and CO₂ after that, but not with the alkali release data. The latter features appear indicative of alkali–deprived char attributable to the preceding pyrolysis with flowing air. Except for the peak-tails, all other features were reproduced well with the modified model equations of Struis et al. and the parameter values resembled closely those reported for fir charcoal gasified with CO₂ at T = 800 ℃.