Accurate prediction of ground surface settlement (GSS) adjacent to an excavation is important to prevent potential damage to the surrounding environment. Previous studies have extensively delved into this topic but all under the limitations of either imprecise theories or insufficient data. In the present study, we proposed a physics-constrained neural network (PhyNN) for predicting excavation-induced GSS to fully integrate the theory of elasticity with observations and make full use of the strong fitting ability of neural networks (NNs). This model incorporates an analytical solution as an additional regularization term in the loss function to guide the training of NN. Moreover, we introduced three trainable parameters into the analytical solution so that it can be adaptively modified during the training process. The performance of the proposed PhyNN model is verified using data from a case study project. Results show that our PhyNN model achieves higher prediction accuracy, better generalization ability, and robustness than the purely data-driven NN model when confronted with data containing noise and outliers. Remarkably, by incorporating physical constraints, the admissible solution space of PhyNN is significantly narrowed, leading to a substantial reduction in the need for the amount of training data. The proposed PhyNN can be utilized as a general framework for integrating physical constraints into data-driven machine-learning models. (c) 2025 Institute of Rock and Soil Mechanics, Chinese Academy of Sciences. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/ 4.0/).

Two new structure-specific scalar intensity measures for plane steel frames under far-field earthquakes are proposed. These intensity measures of the spectral acceleration and spectral displacement type are multi-modal as they take into account the effect of the first four natural periods and multi-level as they are defined for four performance levels and consider inelasticity and period elongation up to the collapse prevention level. This is accomplished with the aid of the equivalent modal damping ratios of a structure previously developed by the authors for performance-based seismic design purposes. These modal damping ratios are period, soil type and deformation dependent and associate the equivalent linear structure to the original nonlinear one. The proposed intensity measures are conceptually simple, elegant and include all the aforementioned features in a rational way without artificially combining terms, defining period ranges and adding coefficients to be determined by optimization procedures as it is the case for all the existing measures, which try to take into account more than one mode and inelasticity. Comparison of the proposed intensity measures against some of the most popular ones existing in the literature, with respect to efficiency (beta), practicality (b), proficiency (zeta), sufficiency in terms of seismic magnitude (M) and source-to-site distance (R), scaling robustness and the range of their values at any damage or performance level demonstrates their very good performance as indicators of the destructive power of an earthquake.

Carbon neutrality is an important goal for addressing global warming. It can be achieved by increasing carbon storage and reducing carbon emissions. Vegetation plays a key role in storing carbon, but it is often lost or damaged, especially in areas affected by desertification. Therefore, restoring vegetation in these areas is crucial. Using advanced techniques to improve ecosystem structure can support ecological processes, and enhance soil and environmental conditions, encourage vegetation growth, and boost carbon storage effectively. This study focuses on optimizing Ecological Spatial Networks (ESNs) for revitalization and regional development, employing advanced techniques such as the MCR model for corridor construction, spatial analysis, and Gephi for mapping topological attributes. Various ecological and topological metrics were used to evaluate network performance, while the EFCT model was applied to optimize the ESN and maximize carbon sinks. In the Thal Desert, ecological source patches (ESPs) were divided into four modularity levels (15.6% to 49.54%) and five communities. The northeastern and southwestern regions showed higher ecological functionality but lower connectivity, while the central region exhibited the reverse. To enhance the ESN structure, 27 patches and 51 corridors were added to 76 existing patches, including 56 forest and 20 water/wetland patches, using the EFCT model. The optimized ESN resulted in a 14.97% improvement in carbon sink capacity compared to the unoptimized structure, primarily due to better functioning of forest and wetland areas. Enhanced connectivity between components contributed to a more resilient and stable ESN, supporting both ecological sustainability and carbon sequestration.

Integrating environmental robustness, energy-efficient recoatability and multi-scenario applicability into a single durable coating that can resist the accumulation of liquid, solid, and mold contaminants is critical for the sustainable development of the coatings industry, yet remains a significant challenge. Here, this issue is addressed by developing a novel hydrophilic-hydrophobic conversion strategy to engineer an environmentally robust organic/inorganic hybrid superhydrophobic coating with remarkable anti-soiling properties and pH-induced recoatability. This conversion, achieved through surface chemistry regulation incorporating hydrophobic hydrocarbon chains and aminopropyl functional groups, yields a coating with a high water contact angle (WCA) of 155.4 degrees and a low sliding angle (SA) of 1.3 degrees. Notably, the WCA can reversibly transition to 0 degrees within 15 s under pH adjustment. The wide range of the surface energy variations enables effective recoatability and restores surface wettability in damaged coatings, with an adhesion strength up to 5.34 MPa, allowing for the in-situ reuse of old coatings. The uniform distribution of modified silica nanoparticles within semi-cured epoxy matrix imparts satisfactory environmental durability, allowing the composite coating to retain its superhydrophobicity after enduring various harsh conditions, including 100 cycles of sandpaper abrasion, 70 cycles of tape-peeling, 120 h of water immersion, and 168 h of heat and humidity exposure. Additionally, the coating demonstrates enhanced anti-mold performance, achieving a grade 1 rating. This work introduces a novel design and fabrication method for multifunctional pH-triggered recoatable superhydrophobic coatings with enhanced environmental robustness that significantly extends their lifespan and adaptability.

Fall armyworm (FAW), Spodoptera frugiperda (Smith) (Lepidoptera: Noctuidae), invasion in Africa has threatened food security. Optimization of plant tolerance and post-infestation recovery are among the management tactics that are being promoted for the integrated management of this pest, but these techniques are poorly studied in sub-Saharan Africa. Our study examined the efficacy of enriched compost, split-NPK fertilization, conventional fertilization, and bioinsecticides on FAW infestation rates, maize plant resilience, natural enemy presence, and grain yield. We found that split-NPK fertilization significantly improved maize plant robustness and reduced FAW incidence and leaf damage in a phenology-dependent manner, leading to higher grain yields. A synergistic effect was observed when split-NPK was coupled with bioinsecticides, resulting in increased populations of natural predators, and specifically the egg endoparasitoid, Telenomus remus (Nixon) (Hymenoptera: Scelionidae). Multivariate analyses confirmed that factors like split-NPK fertilization, bioinsecticide usage, stem circumference, and overall plant robustness are major determinants of maize grain yield. Our results endorse soil fertility management via split-NPK fertilization as an effective cultural control measure against FAW, providing an alternative to synthetic insecticides. These insights set the stage for future research focused on assessing the economic viability of this integrated approach, exploring the integration of split-NPK with alternative insecticides, evaluating environmental impacts, and examining the underlying resilience mechanisms to FAW, among other avenues.