Multilabel data share important features, including label imbalance, which has a significant influence on the performance of classifiers. Because of this problem, a widely used multilabel classification algorithm, the multilabel k-nearest neighbor (ML-kNN) algorithm, has poor performance on imbalanced multilabel data. To address this problem, this study proposes an improved ML-kNN algorithm based on value and weight. In this improved algorithm, labels are divided into minority and majority, and different strategies are adopted for different labels. By considering the label of latent information carried by the nearest neighbors, a value calculation method is proposed and used to directly classify majority labels. Additionally, to address the misclassification problem caused by a lack of nearest neighbor information for minority labels, weight calculation is proposed. The proposed weight calculation converts distance information with and without label sets in the nearest neighbors into weights. The experimental results on multilabel datasets from different benchmarks demonstrate the performance of the algorithm, especially for datasets with high imbalance. Different evaluation metrics show that the results are improved by approximately 2–10%. The verified algorithm could be applied to a multilabel classification of various fields involving label imbalance, such as drug molecule identification, building identification, and text categorization.

The heat rejected by outdoor units of split A/C conditioners can impact the ambient outdoor environment of mixed-mode buildings. Nevertheless, how this environmental impact may affect the space-conditioning energy use and indoor air pollution is poorly understood. By coupling EnergyPlus and Fluent, this study examines the effects of outdoor units’ heat rejection on the building surroundings, building cooling load, and indoor PM_2.5 exposure of a six-storey mixed-mode building. The building had an open-plan room on each floor, with the outdoor unit positioned below the window. The coupled model was run for a selected day when the building was cooled by air conditioning and natural ventilation. Five mixed-mode cooling strategies were simulated, reflecting different window-opening schedules, airflow rates of outdoor units, and cooling set-points. The results indicate that compared with the always-air-conditioned mode, the mixed-mode operation could significantly mitigate the negative impact of heat rejection on space-cooling energy consumption. Increasing the airflow rate of outdoor units led to a lower increase in demand for space cooling and lower indoor PM_2.5 exposure. If one of the six rooms needs to be cooled to a lower temperature than the others; choosing the bottom-floor room helped achieve more energy savings and better indoor air quality.

Traditional gross ecosystem product (GEP) accounting methods often operate at macro scales, failing to reflect the localized and nuanced values of wetland ecosystems. This study addresses these challenges by introducing a fine-grained classification system based on a localized adaptation of international standards. The framework integrates high-precision national land surveys and remote sensing quantitative analysis while incorporating fisheries resource models, climate regulation beneficiary mapping, and visitor interpolation to address data scarcity related to human activities. This approach refines the spatial calculation methods for functional quantity accounting at fine scales. The results demonstrate that the refined classification maintains consistency with traditional methods in total value while adapting to multi-scale accounting, filling gaps at small and medium scales and providing a more accurate representation of localized wetland characteristics. Additionally, the study highlights the dominance of cultural services in GEP, emphasizing the need to balance cultural and regulatory services to ensure fairness in decision-making. Finally, a village-scale decision-support model is proposed, offering actionable guidance for wetland management and sustainable development planning.

As the substitution of natural quartz sand (QS), manufactured sand (MS) is highly demanded in the filling and reclamation of foundations in geotechnical engineering, which may be subjected to cyclic shear stresses induced by wave, seismic, and traffic loadings. One of the noticeable distinctions between MS and QS is their particle shape, which has a significant effect on their shear and liquefaction behaviors under the monotonic and cyclic shear stresses, and needs to be further investigated. In this study, the particle shapes of MS and QS were quantitatively characterized by metallurgical microscope tests and digital image processing. Their pre- and post-liquefaction behaviors were evaluated by a series of direct shear tests, cyclic simple shear tests (CSS), and post-liquefaction monotonic shear tests (PMS). The results show that in the CSS test, samples with irregular particles showed stronger liquefaction and shear resistances, indicating that MS was more stable under cyclic shear loadings. In the PMS tests, it was found that the liquefaction and shear resistances of the samples not only increased with the increasing particle irregularity but also with the increasing shear amplitude in the pre-liquefaction stage. Furthermore, quantitative relationships between the particle shape, shear history, and indexes of shear and liquefaction behaviors of the samples were proposed by regression analysis. The research findings could guide the application of MS in offshore and foundation engineering and provide a reference for the selection of MS and its foundation design.

In engineering practice, soils will inevitably experience some rotation of principal stress directions. Recent experimental evidence has highlighted how principal stress axes rotation significantly impacts clay behavior. However, most existing constitutive models accounting for this effect are essentially designed for sand and may not be applicable to clays. This paper introduces an anisotropic bounding surface model to reproduce the response of clay to principal stress axes rotation. The model’s key innovation lies in its incorporation of a secondary mapping procedure in the deviatoric stress ratio plane, which utilizes a relocatable mapping center. This step is a complement to the conventional radial mapping procedure in the meridional plane, which utilizes a fixed mapping center. This constitutive enhancement facilitates the precise modeling of plastic deformation triggered by the rotation of principal stress axes, without introducing additional loading mechanisms or incremental stress–strain nonlinearity. The performance of the model is first evaluated under various conditions and then verified through comparisons between simulation results and experimental data. The results demonstrate the effectiveness of the model and underscore the necessity of incorporating stress rotation effects into the constitutive modeling of clay.

Recycled sand from construction waste presents a promising substitute for natural sand. However, such sand typically exhibits low strength, high crushing index, and poor grading, which collectively compromise its performance in subgrade applications subjected to cyclic shear stresses caused by wave, seismic, and traffic loads. This study investigates the application of Soybean Urease-Induced Calcium Carbonate Precipitation (SICP) method to enhance the engineering properties of recycled sands. Firstly, several factors influencing the precipitation process are examined, including soybean powder concentration, cementation solution concentration and the ratio between urea and calcium chloride. Subsequently, unconfined compressive tests are conducted on sands reinforced under various conditions. Results indicate that the sample strength increases significantly with higher cementation solution concentration and grouting frequency; however, excessively high concentrations lead to a decline in sample strength, likely due to the reduced calcium carbonate precipitation efficiency under supersaturated conditions. Scanning electron microscopy reveals that the reinforcing effect can be attributed to calcium carbonate crystals formed between particles, which function as binding agents for the recycled sands.