College students often face challenges in maintaining healthy lifestyles, including poor dietary habits, low physical activity levels, and insufficient sleep. To understand the factors that influence health behaviors in this population, we conducted a survey based on the Theory of Planned Behavior (TPB). Using data collected from 282 valid questionnaires, we employed structural equation modeling (SEM) to examine the effects of attitudes, subjective norms, perceived behavioral control, and peer effects on students’ motivation to adopt healthier behaviors. The results revealed that peer effects significantly influence motivation, with a standardized path coefficient of 0.639, alongside the established TPB constructs. This study emphasizes the need to consider social influences when designing interventions to improve the health behaviors of college students.

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In this study, we analyzed 1,629 tourists' comments on Ctrip and other platforms through ROST CM6 text analysis and ROST EA sentiment analysis to explore the sustainable consumption preference of traditional village architecture in Qiandongnan. The study found that tourists have a high preference for the cultural authenticity and ecological adaptability of iconic architectural elements such as drum towers, footstools and wind and rain bridges, but strongly resist the erosion of the “original ecological” landscape by “commercialization”. Sentiment analysis showed that 69.71% of the comments were positive, mainly due to the preservation of the architectural features, while 29.62% of the negative sentiments were focused on the separation of form and spirit caused by excessive remodeling. Based on this, we propose to construct a diversified financing mechanism based on tourists' value perception, and guide the upgrading of consumption preferences by optimizing the tourism experience, so as to provide a practical path for the sustainable inheritance of traditional village architecture.

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As modern office spaces become more airtight, the challenges associated with indoor air quality and thermal comfort increase, directly affecting employee health and productivity. Traditional centralized ventilation systems often fail to meet individual thermal preferences and local environmental needs. In this context, this study proposes and validates a personalized desktop living wall (DLW) system that combines greenery with mechanical ventilation to improve the microenvironment of office workstations. A series of controlled experiments were conducted to evaluate the environmental performance of the DLW system through continuous monitoring of temperature, relative humidity, carbon dioxide concentration and airflow. The results showed that the DLW system reduced the average temperature by 1.79℃, reduced the carbon dioxide concentration by 18.32 per cent and increased the relative humidity by 1.74 per cent. The results of the study show that the personalized green wall system has good potential for improving the office microenvironment and can effectively support the comfort enhancement and green design of office space in the future.

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In this study, we aimed to consider an energy conservation plan for subway stations by analyzing the actual conditions of cooling load and air-conditioning operation. Since the structural characteristics and usage patterns of subway stations differ from station to station, a uniform energy-saving plan is difficult to apply. Therefore, we surveyed lighting, equipment, and passenger numbers at each station, and the actual cooling load was calculated. The study analyzed (1) the breakdown of cooling load, (2) differences in cooling load characteristics among stations, and (3) the relationship between cooling load, air-conditioning operation data, and platform temperature. The results clarified that train heat release and ventilation loads dominated the total cooling load, and that differences in train specifications significantly affected the thermal characteristics of each station. Furthermore, a correlation was found between the discrepancy of thermal load and supply quantity and platform temperature, indicating that optimizing the control of thermal supply is important for stable and energy-efficient operation. The findings of this study provide practical insights for formulating station-specific energy conservation plans.

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This study aims to develop an external energy management system (EMS) that supports the optimal operation of thermal storage heat source systems by utilizing data from the building energy management systems (BEMS) of existing buildings. The objective for FY2024 is to verify the energy conservation benefits achieved through the use of automated optimal operation support software. First, the accuracy of the heat load predictions generated by the operation support software during operation plan creation was evaluated, confirming a low error rate. Next, an operation support simulation for FY2024 was conducted using the operation support software and performance data from the demonstration building’s BEMS to evaluate the software’s long-term effectiveness. As a result, the virtual coefficient of performance (COP) generated by the software exceeded the actual COP on most days, demonstrating the software’s effectiveness.

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This community implements demand-side energy management via the Energy Center (EC) and Community Energy Management System (CEMS) to optimize energy use by controlling consumers' air conditioning setpoints. This advanced initiative, where the supply side of a District Heating and Cooling (DHC) plant manages the indoor environment, reduces consumer heat demand, prevents the installation of additional heat sources, shortens boiler operation time, and lowers operational costs. A summer demonstration in two hospital buildings validated the approach: supply air temperature was relaxed by up to 7℃, indoor temperatures by 0.2–1.6℃ in Medical A and 0.3–0.9℃ in Medical B, resulting in heat demand reductions of 14.8% and 8.4%, respectively. These results confirm the method's effectiveness in reducing energy consumption while maintaining thermal comfort.

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Garden greening is used as a common form of greening in traditional Japanese houses. Existing studies have shown that garden greening can have an impact on the outdoor thermal environment. However, the existing research is insufficient for the thermal comfort of human beings for different seasons of garden greening. This study examines the seasonal influence of courtyard greening complexity on outdoor human thermal comfort in traditional Japanese garden settings. Through a combination of field observations, the results demonstrate that in summer, higher greening complexity—characterized by increased vegetation diversity and multilayered canopy structures—significantly enhances outdoor thermal comfort. The complex greening mitigates thermal stress by providing extensive shading, reducing surface and air temperatures, and enhancing evaporative cooling effects. In contrast, during winter, increased greening complexity exerts a detrimental impact on thermal comfort. Dense vegetation impedes solar radiation access, leading to lower ambient temperatures and diminishing the benefits of passive solar heating, which is crucial for maintaining outdoor thermal comfort in colder conditions. These findings underscore the importance of seasonally responsive greening strategies in garden design, emphasizing the need to balance the cooling benefits during summer against the warming requirements in winter to optimize year-round outdoor thermal comfort in Japanese gardens.

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Existing strategies for Mars development are largely dominated by engineering paradigms centered on survival, with an emphasis on closed habitats, resource shielding, and environmental isolation. While technically essential, these approaches often overlook broader ecological and systemic dimensions of planetary habitation. To address this conceptual gap, the present study introduces a capsule-based developmental framework grounded in the principles of ecological succession. In this framework, functional capsules—modular and semi-autonomous units capable of operating with in-situ Martian resources—are deployed incrementally. Each capsule supports essential life functions while generating environmental byproducts such as thermal energy, moisture, and oxygen. Over time, these capsules evolve from isolated survival units into interconnected ecological nodes capable of influencing local environmental conditions and forming distributed, feedback-regulated systems. This study outlines a six-phase evolutionary trajectory, ranging from initial deployment to the formation of synthetic ecological zones, thereby reframing terraforming as a bottom-up, temporally staged process of ecological activation rather than conventional top-down planetary engineering. This framework provides a new theoretical foundation for long-term Mars settlement, offering strategic insights into system design, resource planning, and planetary stewardship.

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This study presents a data-driven method for predicting heat load variations to support the optimal operation of building heat source systems. The proposed method does not rely on weather data or physical models; instead, it utilizes actual operational data from building energy management systems (BEMS). Instead of forecasting absolute values, the method estimates load fluctuations, defined as the difference between consecutive time intervals, using a similarity-based analysis of historical trends. By selecting historical days with similar patterns and calculating weighted average changes, the method enables hourly prediction of heat load variations. To evaluate the effectiveness of the proposed approach, we applied it to a large-scale office-commercial complex in Tokyo, using two years of hourly BEMS data. The prediction accuracy was assessed with the Expected Error Percentage (EEP) index, and results confirmed that the method maintains higher precision during cooling and heating peak periods. These findings demonstrate the method’s potential to enhance real-time control and energy efficiency in air-conditioning systems.

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This article introduces a course, which is aimed for the fourth-year’s undergraduate architecture students in the School of Architecture, Chang’an University. This course aims to teach architecture students using digital (BIM+XR) means, to analyze and protect vernacular dwellings. Overall, this article first introduces the situation and development of the relevant research, and then elaborates on the research content of this course, including the collection of data in the early stage and the implementation of the teaching in the later stage. Secondly, the feasibility analysis of the course design and implementation was expounded to ensure the effectiveness of the later offering. Finally, the case teaching of this course was introduced in detail: This course takes the digital mapping data of several typical traditional residences in the Guanzhong area as teaching materials and is targeted at the fourth-year undergraduate students of Chang 'an University, School of Architecture. The aim of this course is to enable architecture students to master the digital methods and approaches of reconstructing and protecting vernacular dwellings in the Guanzhong area, and ultimately provide relevant talents and ideas for the protection of architectural heritage in the western region of China.

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This study investigates the mechanical and durability performance of concrete incorporating blast furnace slag (BS) and MSWI molten slag (MS) as fine aggregate replacements, with supplementary use of fly ash (FA) as a partial cement substitute. Six mix proportions were prepared: three mixtures with 30% FA and BS replacement ratios of 25%, 50%, and 100%, and three mixtures with BS and MS at 50% each, with FA contents of 0%, 15%, and 30%. The experimental evaluation focused on compressive strength, drying shrinkage, creep, and pore structure. The results indicated that replacing sand with BS generally improved compressive strength, whereas the inclusion of MS tended to reduce it. Drying shrinkage strain was reduced in concretes with combined MS and BS compared to those with BS alone, indicating a shrinkage-mitigating effect of MS. For creep, mixes with higher BS content exhibited lower creep strain, whereas MS-BS mixtures showed increased creep strain with higher FA replacement levels. Pore structure analysis revealed that water curing promoted the pozzolanic reaction, resulting in reduced total pore volume. Overall, BS and MS had little influence on the total pore volume, whereas higher FA replacement increased the volume of pores smaller than 0.01 µm. These findings provide insights into the potential of BS and MSWI molten slag as sustainable fine aggregate alternatives.

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This study takes the pocket park on the east side of Yuehui, Chongqing South Road, Shibei District, Qingdao as the research object, aiming to explore its thermal comfort environment characteristics in summer and verify the applicability of parametric simulation tools. The research comprehensively uses field measurement and numerical simulation methods to monitor the microclimate of three types of functional spaces in the park in typical summer days, and uses Ladybug Tools to build a refined model for UTCI simulation. The results show that there is significant spatial differentiation in thermal comfort of park, the green shade area has the best effect, and the thermal stress of hard pavement square is prominent. The simulated data are in good agreement with the measured data (error 0.3-2.5 ℃), which verifies the reliability of the method. However, the research is limited to a single sunny day in summer, and the simulation accuracy of complex vegetation ecological process is still insufficient. In the future, it is necessary to carry out long-term research on multiple seasons and cases, and integrate users' subjective perception to deepen relevant conclusions.

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Since the emergence of COVID-19 in the United States, all aspects of the entire country have been greatly affected. Everyone felt sad for the death of lots of people who appeared in the virus. Is virus product of environmental impact? A virus from the environment has caused such large casualties to humans. From another perspective, will COVID-19 have an impact on the environment? It is not just COVID-19. When any epidemic occurs, will it have an impact on the environment? My project took Chicago as an example to research the air environmental quality in Chicago in recent year. In what ways has COVID-19 affected Chicago’s air quality? In other words, is there any social connection between them? Can the quality of the air influence people to have a higher chance of getting COVID-19? Many papers prove that long-term air pollution will cause more respiratory diseases because people’s respiratory systems have damaged. What levels of environmental pollution people stay are exposed to leads to higher infection rates. The emergence of COVID-19 is a warning. Whether our environment is also affecting people’s chances of getting sick. Is there any connection between the impact on Chicago’s air quality during the pandemic and the explosive increase in the number of patients? And how to deal with the impact of the pandemic on air quality in the future. The pandemic is not only one, but we should also prevent any future simultaneous attacks of environmental problems and diseases that may arise.

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Building-scale rainwater harvesting (RWH) systems increasingly face operational stress under intensifying short-duration rainfall, yet most installations continue to rely on passive rule-based control with limited ability to adjust storage ahead of storm events. This study develops a forward-looking operational framework that incorporates short-term rainfall forecasts into a standard hourly water-balance model through a predictive pre-release mechanism. The method evaluates potential exceedance of storage capacity over a seven-day horizon and adjusts release volumes based on projected inflow–storage interactions while maintaining physical constraints and supply reliability. The framework was applied to the campus RWH tank at the Kitakyushu Science and Research Park using hourly rainfall and non-potable water demand data for 2022. Comparative simulations using identical inflow and demand sequences show that predictive adjustment alters the temporal structure of discharge by lowering storage levels in advance of high-inflow periods, thereby reducing peak overflow without affecting annual rainwater use or municipal supplementation. Sensitivity analysis across multiple storage capacities indicates that the operational benefits of predictive control depend on the interaction between tank size and anticipated inflow pressure, with diminishing marginal improvements once structural capacity exceeds a threshold. The results indicate that forecast-informed operation can enhance the adaptability of decentralized RWH systems under non-stationary rainfall regimes and may complement structural design measures in future system planning.

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