Shanxi Transportation Research Institute

China’s rapid urbanization has generated substantial low-strength demolition waste, creating significant environmental and disposal challenges. Recycling this waste as subgrade filler provides a viable solution given the subgrade’s lower strength requirements and high consumption capacity. This study systematically evaluated the feasibility of using unsorted rural demolition waste (URDW) as subgrade filler without separation to improve recycling efficiency. Three gradations (FF20, MF40, and CF80) with maximum particle sizes of 20, 40, and 80 mm were designed based on the characteristics of the raw materials. The composition, compaction behavior, particle breakage mechanisms, and mechanical properties of these fillers were analyzed. The experimental road subgrade employed FF20, with model tests assessing long-term performance under wet–dry (WD) cycles and field evaluations combining quality tests with settlement monitoring. Results showed that increased particle size reduced the combined content of bricks and mortar (CCBM) while raising that of concrete and stones (CCCS) in the raw materials, demonstrating particle size effects on material strength. This explains the decreasing CCBM and increasing CCCS from FF20 to CF80. Heavy compaction produced elevated particle breakage rates (Br) and irregular compaction curves, whereas surface vibration compaction generated standard curves with significantly reduced Br. Although filler compositions varied, particle size and coarse content primarily controlled Br variation during compaction. The FF20 subgrade model exhibited minimal compressive deformation under WD cycling, with transitional deformation progressively diminishing as cycling enhanced the model’s deformation resistance. After cycling, the saturated FF20 model maintained a resilient modulus (MR) above regulatory requirements. Field tests confirmed FF20-filled subgrade complies with specifications for compaction degree, deflection, and MR in both dry and saturated conditions. Forty-month monitoring recorded only 1.64 mm centerline compression, validating satisfactory deformation resistance. This study broadens potential applications for URDW and provides practical guidelines for similar projects.

• A local pattern interaction (LPI) model is developed to examine spatial association and interaction. • Compared with traditional models, LPI model improves explanatory power of local patterns of variables. • LPI integrates geocomplexity, locally stratified power, and interaction effects to uncover localized mechanisms of urbanization drivers. • LPI identifies local interactions of economic variables and patterns as key drivers of urbanization. Spatial association and spatial interaction are fundamental to understanding geographical phenomena and regional development disparities, with broad applicability across disciplines. Existing spatial heterogeneity analysis face significant challenges in capturing pattern interactions and local variability. This study develops a local pattern interaction (LPI) model that integrates local complexity patterns or geocomplexity of spatial data, the interaction of patterns, and their locally varied power of determinants (PD). LPI is implemented in assessing the PD of local variables and pattern interactions on the spatial distributions of urbanization using statistical data, remote sensing imagery, and open geospatial data. The results show that LPI effectively identifies the local PD of interactions involving the geocomplexity patterns of urbanization-related explanatory variables. Model performance is evaluated by comparison with the optimal-parameters geographical detector (OPGD), a widely used spatial heterogeneity–based PD identification model. The model validation shows that LPI provides advantages over OPGD by capturing spatially varying interaction patterns and local effects, whereas OPGD assesses only global interaction effects. For example, the LPI-derived PD for the interaction between total retail sales and the geocomplexity pattern of tertiary-industry output averages 0.610 [0.336,0.783], indicating critical spatial variation in both local PD values and their significance, while the OPGD-derived PD yields a single global estimate of 0.537 (p < 0.01). This research advances theoretical understanding of spatial association and interaction, while providing an innovative analytical tool and decision-support capability for regional development, urban planning, and resource allocation.

IntroductionThis randomized controlled trial aimed to compare the acute and sustained effects of tissue flossing (TF) versus dynamic stretching (DS) on hamstring muscle stiffness and flexibility in light volleyball (LVB) enthusiasts.MethodsThirty-seven participants were randomly assigned to TF, DS, or placebo groups. Muscle stiffness was evaluated using shear-wave elastography, measuring Young’s modulus at the distal and proximal regions of the biceps femoris long head and semitendinosus. Flexibility was assessed via passive knee extension (KE), straight leg raise (SLR), and forward flexion distance (FFD) at baseline, immediately post-intervention, and 30 min post-intervention.ResultsThe results demonstrated that TF significantly reduced muscle stiffness compared to DS at the 30-min mark, particularly in the semitendinosus [distal: mean difference = −43.40 kPa, 95% CI (–80.65, −6.16), p = 0.007; proximal: −51.13 kPa, (–101.20, −1.05), p = 0.040]. However, no significant differences were observed between the TF and DS groups in flexibility outcomes (KE, SLR, or FFD) at any time point.DiscussionThese findings indicate that while TF offers a prolonged reduction in hamstring stiffness—suggesting potential benefits in injury prevention and prolonged performance—its effect on functional flexibility remains comparable to that of dynamic stretching. TF may serve as an effective warm-up intervention for athletes requiring sustained decreases in muscle stiffness during activities.