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Prefabricated H-section steel composite wall columns (PHSWCs) are crucial for advancing modular steel construction, yet their elastic buckling performance lacks a universally accurate predictive model due to the complex interplay between section interaction and semi-rigid bolted connections. To address this, a comprehensive theoretical framework for elastic buckling analysis is developed in this study. The model integrates Euler–Bernoulli beam theory for the H-sections, a three-dimensional spring system to represent the stiffness of bolted connections, and the Green strain tensor to account for geometric nonlinearity. Validation against ABAQUS (2020) and ANSYS (2021 R1) shows high accuracy (average errors: 1.0% and 1.2%, respectively). Furthermore, a unified formula for the normalized slenderness ratio is derived via stepwise regression, which elegantly degenerates to the classical Euler solution under limiting conditions. The main conclusion is that this framework enables rapid and precise buckling analysis, reducing parametric study time by 95% compared to detailed finite element modeling. It establishes a bolt density coefficient threshold of η = 0.5 that separates composite from independent section behavior, with an optimal design range of η = 0.2 to 0.25, thereby offering a robust theoretical basis for PHSWC design.

Historic and cultural heritage districts, as physical carriers of a city’s cultural identity, have become key issues in urban development. Architectural color, as a core visual element of district character, is an important symbol of regional identity recognition. However, further exploration is needed regarding how to integrate architectural color quantification metrics and evaluation techniques into the urban characteristics management framework. In this paper, taking Tianjin’s historic cultural heritage districts as a case study, street view data were utilized, and deep learning along with clustering analysis methods were employed to extract architectural colors. Based on the “point-line-surface” protection strategy, a multi-scale architectural color identification and evaluation method spanning “buildings-streets-districts” was established. This methodology enables the recognition of dominant building colors in heritage zones at the district scale and the assessment of street color harmony and richness at the street scale. By analyzing these two levels, this research interprets the role of architectural color as a visual attribute in defining urban character and enhancing urban distinctiveness. It provides technical support for refining urban characteristics management systems and achieving precise control over the preservation and development of distinctive urban features.

In order to investigate the internal curing effect of recycled brick aggregate (RBA) in recycled aggregate concrete (RAC) and calculate its contribution to the final compressive strength, two RAC groups with different recycled aggregates and 6 replacement ratios (r) under 4 curing ages were tested. Results show that the compressive strengths of RACI and RACII decrease steadily with the increase of r when below 40%, and that there is a significant drop once the r is higher than 60%. The internal curing effect for RAC with a low RBA ratio is mainly reflected during the curing age of 14–21 days, while for RAC with a high RBA ratio, this internal curing effect appears earlier, during 7–14 days, and becomes very obvious after 14 days. In addition, the actual tested compressive strength of RAC replaced by 100% RBA exceeds around 40% of the expected compressive strength at the age of 28 days. When the age of RAC entirely with RBA is 28 days, the compressive strength caused by the internal curing effect accounts for around 28% of the actual tested compressive strength. The most appropriate r of RBA for RAC production is between 40% to 60%. Finally, the equations for calculating the compressive strength of RAC are presented considering the curing ages, the replacement ratios and the internal curing effect of RBA. Further, a unified equation is suggested for convenience in calculation.

Continuous global warming and frequent extreme high temperatures keep the urban climate health risk increasing, seriously threatening residents’ emotional health. Therefore, analysis on spatial distribution of the health risk that the urban heat island (UHI) effect imposes on emotional health as well as basic research on the characteristics of vulnerable populations need to be conducted. This study, with Tianjin city as the case, analyzed data from Landsat remote-sensing images, meteorological stations, and digital maps, explored the influence of summer UHI effect on distress (a typical negative emotion factor) and its spatiotemporal evolution, and conducted difference analysis on the age groups, genders, family state, and distress levels of vulnerable populations. The results show: (1) During the period of 1992–2020, the level and area of UHI influence on residents’ distress drastically increased–influence level elevated from level 2–4 to level 4–7, and highlevel influence areas were concentrated in six districts of central Tianjin. (2) Influence of the UHI effect on distress varied in different age groups–generally dropping with fluctuations as residents got older, especially residents aged 50–59. (3) Men experienced a W-shaped pattern in distress and were more irritable and unsteady emotionally; while women were more sensitive to distress in the beginning, but they became more placid as temperature got higher. (4) Studies on family status show that couples living together showed sound heat resistance in the face of heat stress, while middle-aged and elderly people living alone or with children were relatively weak in adjusting to high ambient temperature.

In response to the current issue of poor modeling performance of Building Information Modeling for building models, a new Building Information Modeling based on an improved region growth algorithm is proposed. This method improves the region growth algorithm by introducing machine learning technology, and utilizes the improved algorithm to perfect the building model, thereby improving the efficiency of Building Information Modeling. The performance comparison experiment of the improved algorithm shows that its accuracy is 92.3%, respectively, which are lower than the comparison algorithm. Subsequent empirical analysis found that the robustness rating of the renovated building with the new Building Information Modeling was 94.06, significantly higher than the traditional model. The above results indicate that the new Building Information Modeling proposed in the study has high efficiency and accuracy in building reinforcement and renovation. This method can provide a new solution and idea for the field of building reinforcement and renovation.

An SRC-RC column is a vertical hybrid of a steel reinforced concrete (SRC) column and a reinforced concrete (RC) column. To propose the capacity and stiffness calculation method of SRC-RC columns, 768 column models have been simulated using fiber FEM (finite element method) with lateral static loading. These models have different parameters, including: Concrete strength, steel strength, steel sections, steel length and column concrete ratio. Based on simulation results and using a linear regression method, the equations of the secant stiffness and bearing capacity of the SRC-RC hybrid columns are calculated, proposed and verified using the residual analyzing method, ensuring that these calculate equations are accurate.

Two columns of thin-walled concrete-filled steel tubes (CFSTs), in which tube seams are connected by self-tapping screws, are axial compression tested and FEM simulated; the influence of local buckling on the column compression bearing capacity is discussed. Failure modes of square thin-wall CFST columns are, first, steel tube plate buckling and then the collapse of steel and concrete in some corner edge areas. Interaction between concrete and steel makes the column continue to withstand higher forces after buckling appears. A large deflection analysis for tube elastic buckling reflects that equivalent uniform stress of the steel plate in the buckling area can reach yield stress and that steel can supply enough designing stress. Aiming at failure modes of square thin-walled CFST columns, a B-type section is proposed as an improvement scheme. Comparing the analysis results, the B-type section can address both the problems of corner collapse and steel plate buckling. This new type section can better make full use of the stress of the concrete material and the steel material; this type section can also increase the compression bearing capacity of the column.

Traditional villages are a valuable cultural asset that occupy an important position in Chinese traditional culture. This study focuses on 206 traditional villages in Hebei Province and aims to explore their spatial distribution characteristics and influencing factors using ArcGIS spatial analysis. The analysis shows that traditional villages in Hebei Province were distributed in clusters during different historical periods, and eventually formed three core clusters in Shijiazhuang, Zhangjiakou and Xingtai-Handan after different historical periods. Moreover, the overall distribution of traditional villages in Hebei Province is very uneven, with clear regional differences, and most of them are concentrated in the eastern foothills of the Taihang Mountains. To identify the factors influencing traditional villages, natural environmental factors, socio-economic factors, and historical and cultural factors are considered. The study finds that socio-economic and natural environmental factors alternate in the spatial distribution of traditional villages in Hebei Province. The influence of the interaction of these factors increases significantly, and socio-economic factors have a stronger influence on the spatial distribution. Specifically, the spatial distribution of traditional villages in Hebei Province is influenced by natural environmental factors, while socio-economic factors act as drivers of spatial distribution. Historical and cultural factors act as catalysts of spatial distribution, and policy directions are external forces of spatial distribution. Overall, this study provides valuable insights into the spatial distribution characteristics and influencing factors of traditional villages in Hebei Province, which can be used to develop effective strategies for rural revitalisation in China.

Although surface-enhanced Raman scattering (SERS) technology has been widely explored nowadays in various fields, the fabrication of practical SERS-active substrates with prominent recognition ability for various analyte molecules is still defective. Natural Fulfora candelaria wing (FCW) with three-dimensional (3D) hierarchical reticular nanostructure was selected as a new bioscaffold for rough silver (Ag) nanoislands to be assembled on to prepare a practical SERS substrate (Ag/FCW substrate). By adjusting the sputtering time of metal Ag, the morphology of the substrates could be easily tuned to control the formation and distribution of “hot spots”. Three-dimensional finite-difference time-domain (3D-FDTD) simulation indicated that the excellent SERS performance under optimal morphology was ascribed to the local enhanced electric field in rough Ag surface and effective “hot spot” areas. The SERS measurement results show that the optimal Ag/FCW substrates had high SERS performance in terms of Raman signal sensitivity, reproducibility, uniformity and recognition ability for various analyte molecules. Coupled with flexibility of the biological substrates and the cost effectiveness, the sensitive SERS detection of varied analytes based on Ag/FCW substrates offered great potential for practical applications.

This research adds to the body of knowledge by examining the asymmetric link between rural development and pro-environmental behavior in rural China. Rural development is assessed via rural income and digital financial inclusion. We use linear and nonlinear autoregressive distributed lag (ARDL) models to assess short- and long-term effects. The linear analysis suggests that a rise in rural income and digital financial inclusion encourages long-term access to clean fuels and technologies (CFT) in rural areas, while they do not have any significant impact in the short run. On the other side, the nonlinear framework illustrates that a positive shock in rural income and digital financial inclusion encourages long-term access to CFT in rural areas. A negative shock in rural income reduces long-term access to CFT in rural areas, and a negative shock in digital financial inclusion does not significantly impact access to CFT. However, in the short run, only the estimates of rural income are significant, while the estimates attached to digital financial inclusion are insignificant, implying that a rise in rural income increases access to CFT and a fall in rural income reduces access to CFT. Thus, government should encourage collaboration between private sector and civil society organizations to promote sustainable rural development and pro-environmental behavior.