With the increasing demand for wood in the wood market and the frequent trade of high-value wood, the accurate identification of wood varieties has become essential. This study employs two hyperspectral imaging systems—visible and near-infrared spectroscopy (VNIR) and short-wave infrared spectroscopy (SWIR)—in combination with a deep learning model to propose a method for wood species identification. Spectral data from wood samples were obtained through hyperspectral imaging technology, and classification was performed using a combination of convolutional neural networks (CNNs) and Transformer models. Multiple spectral preprocessing and feature extraction techniques were applied to enhance data quality and model performance. The experimental results show that the full-band modeling is significantly better than the feature-band modeling in terms of classification accuracy and robustness. Among them, the classification accuracy of SWIR reaches 100%, the number of model parameters is 1,286,228, the total size of the model is 4.93 MB, and the Floating Point Operations (FLOPs) is 1.29 M. Additionally, the Shapley Additive Explanation (SHAP) technique was utilized for model interpretability, revealing key spectral bands and feature regions that the model emphasizes during classification. Compared with other models, CNN-Transformer is more effective in capturing the key features. This method provides an efficient and reliable tool for the wood industry, particularly in wood processing and trade, offering broad application potential and significant economic benefits.

As society develops, the aging population issue is becoming more serious and gaining global attention. Meanwhile, the building industry worldwide is focusing on making buildings more convenient for the elderly. This study focuses on a health care building, analyzing its aging-friendly design. It examines issues related to walking situations and activity spaces and proposes optimization strategies based on relevant codes and actual needs. Through optimization and transformation, the walking distance to the nearest exit for the elderly in the building has been reduced by 36.8%, the walking distance to activity space for the elderly has been reduced by 8.4%, and the average public activity space of each elderly person has been increased by about 23.5%. In addition, the handrails of the accessible stairway have been changed to double handrails, which is more suitable for the different needs of the elderly, and the space of the wheelchair-accessible elevator has been expanded, which is more convenient for the elderly’s activities in elevators. This paper explores the feasibility and design direction of the aging-friendly architecture, and it aims to provide a valuable reference for the renovation of aging buildings.

Natural convection in cavity plays a significant role in energy-related field, including the indoor heat transfer analysis in greenhouse with integrated PV roof. In this study, mathematical model is established for two-dimensional heat transfer analysis in greenhouse air cavity, with numerical simulation through computational fluid dynamics (CFD). Main natural convection impact factors, such as system configuration parameters (tilting angle and PV panel unit number) and fluid thermalphysical properties, are investigated with indoor temperature distribution and streamline comparison by finite-volume method (FVD). Preliminary results show that with rising Rayleigh number (Ra), natural convection is enhanced with growing Nusselt number (Nu). Moreover, panel slope tilting angle (θ) highly determines inside heat transfer subregions in terms of the vertical temperature gradient declines with rising θ, improving the temperature distribution uniformity inside. The solar greenhouse example illustrates that with the increasing numbers of panel group numbers (n), the air temperature gradient differences decrease, improving the temperature distribution uniformity inside, which is preferable to built environment accurate control for greenhouse in the practical engineering. This work can provide modeling method support and reference for natural heat convection applications.

The Gansu–Qinghai–Ningxia region is a major area of concentrated Hui settlement in northwestern China, characterized by significant cultural interaction and integration. In response to the limited regional-scale research on how multiple cultural and geographical factors jointly shape settlement spatial forms, this study adopts a cultural integration perspective and develops an analytical framework of “field investigation–settlement morphology–historical tracing–cultural interpretation.” Eleven representative traditional Hui settlements and historical residential areas in Gansu, Qinghai, and Ningxia are selected as case studies. Based on field surveys, spatial mapping, and an examination of local gazetteers and historical documents, the study identifies the spatial characteristics of these settlements and traces their historical and cultural origins. Four major spatial types are identified: settlements organized around mosques, differentiated hierarchical settlements, fortress-based settlements, and settlements shaped by commercial activities. The study argues that the long-term interaction among the distinctive frontier environment, multicultural integration, shared religious beliefs, and transregional trade networks has jointly produced the multilayered spatial patterns of Hui settlements in the region. This research establishes an analytical approach that integrates geographical, religious, commercial, and ethnic-cultural factors, providing a useful reference for the study and conservation of traditional settlements and cultural heritage in the multiethnic regions of northwestern China.

The industrial heritage of the Third Front construction (hereafter referred to as Third Front industrial heritage) serves as a significant physical manifestation of China’s urban society, economy, and culture during a unique historical period. Its widespread abandonment not only constitutes a waste of social resources but also accelerates the erosion of collective memory surrounding the Third Front initiative. As one of Sichuan Province’s (including present-day Chongqing) key Third Front construction regions during that era, Guangyuan City possesses a substantial legacy of Third Front industrial heritage sites. These sites are predominantly idle and face ongoing risks of deterioration, necessitating comprehensive and systematic research into their classification, protection, and regeneration. This paper focuses on 39 Third Front industrial heritage sites in Guangyuan City, employing architectural typology to construct a ‘type-medium-value’ research framework integrating field research with strategic distribution analysis at the urban level, spatial form analysis at the settlement level, and spatial combination analysis at the building level to quantitatively identify and qualitatively deconstruct the spatial logic of these sites. This enables the analysis of the functional characteristics, structural logic, and spatial intent embodied by different types, thereby exploring the multidimensional value implications of Third Front industrial heritage through this value medium. Ultimately, this research proposes targeted adaptive mechanisms and revitalisation pathways for Third Front industrial heritage. It aims to promote the cultural legacy of this heritage and perpetuate the Third Front spirit within the context of strengthening the Chinese national community consciousness in the new era, while aligning with the Party and state’s development strategies. This approach aims to provide a reference for revitalising and utilising Third Front industrial heritage in other underdeveloped regions.