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Accurate prediction of reservoir landslide displacements is crucial for early warning and hazard prevention. Current machine learning (ML) paradigms for predicting landslide displacement demonstrate superior performance, while often relying on various feature engineering techniques, such as decomposing into different temporal lags and feature selection. This study investigates the impact of various feature selection techniques on the performance of ML algorithms for landslide displacement prediction. The Shuping and Baishuihe landslides in China’s Three Gorges Reservoir Area are used to comprehensively benchmark four prevalent ML algorithms. Both static ML models, including backpropagation neural network (BPNN), support vector machine (SVM), and dynamic models, such as long short-term memory (LSTM), and gated recurrent unit (GRU), are included. Each ML model is evaluated under three feature engineering techniques: raw multivariate time series, and feature selection under maximal information coefficient-partial autocorrelation function (MIC-PACF), or grey relational analysis-PACF (GRA-PACF). The results demonstrate that appropriate feature selection methods could significantly improve the performance of static ML models. In contrast, dynamic models effectively leverage inherent capabilities in capturing temporal dynamics within raw multivariate time series, seeing marginal gains with extensive feature engineering compared to no feature selection strategy. The optimal feature selection approach varies based on the ML model and specific landslide, highlighting the importance of case-specific assessments. The findings in this study offer guidance on integrating feature selection techniques with different machine learning models to maximize the robustness and generalizability of data-driven landslide displacement prediction frameworks.

This paper established a numerical model for the structure system in a soil–structure interaction using MATLAB 23.2 and ANSYS 24.1 software and validated the effectiveness and accuracy of a simplified nonlinear calculation model for soil–structure interaction through the numerical simulation results. Meanwhile, a list of key parameters was identified according to their influence on the simplified model, including the free field area, site soil parameters, equivalent soil area, superstructure size and number of stories, and input seismic waves. On this basis, a series of parametric investigations were carried out with the validated simplified model, by varying the selected key parameters. The research findings demonstrated that the simplified calculation model exhibited excellent accuracy and efficiency, and was capable of reflecting the nonlinear response of the structural system. It is applicable to the field of dynamic response analysis of the superstructure, considering soil–structure interaction.

An improved Penzien model is proposed in this paper as a simplified model of soil–pile–structure interaction. The dynamic nonlinearity of soil under earthquake excitation is simulated by ANSYS in a free-field model and added to the original Penzien model. The improved Penzien model uses the finite element software ANSYS 2021 to simulate the dynamic nonlinearity of soil. The improved Penzien model is then used as a simplified calculation model of the numerical substructure. A substructure pseudo-dynamic test based on the improved Penzien model is carried out. The realization of the substructure pseudo-dynamic test verifies the feasibility and effectiveness of this method, which provides a convenient test method for the study of soil–pile–structure interaction in general laboratories. Soil and structure interaction reduces the acceleration of the structure, and the response exhibited a hysteresis phenomenon because of the nonlinear characteristics of the soil. The influences of soil–pile–structure interaction on velocity and displacement are very complex. The conclusions are reasonable, which proves that the substructure pseudo-dynamic test method of soil–pile–structure dynamic interaction using the improved Penzien model is feasible.

Aluminum dross (AD) is a waste product produced during aluminum processing and can be used to prepare mullite ceramic materials. However, the research on the preparation of mullite porous ceramics entirely from solid waste is still in the development stage. In this paper, porous mullite ceramics were successfully fabricated using a solid-phase sintering process with AD and different silicon sources (fly ash, silica dust, and gangue) as raw materials. The bulk density, apparent porosity, and compressive strength of the specimens were obtained, and the phase compositions and microstructures of the sintered specimens were measured using XRD and SEM, respectively. The average activation energy of the phase transition of fly ash, silica dust, and gangue as silicon sources were 984 kJ/mol, 1113 kJ/mol, and 741 kJ/mol, respectively. The microstructures of the mullite in the specimens were prisms, random aggregates, and needle-shaped, respectively. The formation of needle-shaped mullite combined with the substrate enhanced the mechanical strength of the porous mullite ceramics. The apparent porosity, density, and compressive strength of the specimens with gangue as the silicon source were 33.13%, 1.98 g/cm3, and 147.84 MPa, respectively, when sintered at 1300 °C for 2 h.

Epoxy resin insulation materials are mainly derived from petrochemical materials which have the disadvantages of resource consumption and environmental pollution. In order to cure bisphenol A epoxy resin, a maleopimaric anhydride (MPA) curing agent was prepared from rosin, a renewable resource, and blended with a petroleum-based curing agent (methylhexahy-drophthalic anhydride). The influence of maleopimaric anhydride content on the initiation and growth characteristics of electrical trees was studied and analyzed in this paper using molecular dynamics simulation (MD) and electrical tree tests at an 18-kilovolt power frequency voltage. When the MPA content used was ≤10%, the free volume percentage of the curing system increased with MPA content, and thus the initiation voltage became lower; when the MPA content was ≥20%, the hydrogenated phenanthrene ring structure content increased significantly with increasing MPA content, and the rigidity of the curing system increased significantly; thus, the initiation voltage gradually increased. MPA4 had an 11.11% higher initiation voltage than the petroleum-based control group. The effect of the polar rigid structure within the curing system significantly inhibited the growth rate and length of electrical trees as MPA content increased. Electrical trees developed into light-colored, thin, and narrow dendritic structures when the MPA content reached 40%. The results show that curing epoxy resin with the rosin-based curing agent maleopimaric anhydride (MPA), in place of a petroleum-based curing agent, can produce environmentally friendly resins with excellent electrical tree resistance and potential application prospects.

Si3N4 ceramics with a microscale rice leaf structure (MRLS) and titanium alloy were connected via brazing, and the influence of the surface microstructure on the ceramic connection was analyzed. MRLS fabrication is an efficient and high-degree-of-freedom method that can be used to change a material’s surface morphology and wettability. The MRLS was obtained at a laser power of 110 W, with line spacings of 100 and 50 μm. The laser-treated surface included nanoparticles and micro particles, exhibiting a coral-like structure after agglomeration. When the MRLS was used to braze the titanium alloy, no defects were observed at the brazing interface, and the formation was excellent. Throughout the brazed joint, the MRLS remained intact and formed a strong metallurgical bond with the brazing filler metal. A finite element analysis was performed to study the cross-sectional morphology after joint fracture; from the load-time curve, it was found that the MRLS on the surface not only helped improve the mechanical occlusion and brazing area at the interface, but also helped generate compressive stress on the Si3N4 side. Crack propagation was hindered, thereby increasing the joint strength.

In this study, the hydrolysis behavior and kinetics of AlN in aluminum dross (AD) were investigated in order to better identify the steps controlling the AlN hydrolysis reaction and the factors influencing the hydrolysis rate to enhance the removal efficiency of AlN. The hydrolysis behavior of AlN, including AlN content, phase composition, chemical composition, microstructure, and element distribution, was determined by a leaching test, X-ray diffraction, X-ray fluorescence, scanning electron microscopy, and energy dispersive spectroscopy, respectively. The results showed that increasing the leaching liquid–solid ratio as well as the temperature was helpful for the removal efficiency of AlN. When the liquid-–solid ratio was 4:1, temperature was 90 °C, and leaching time was 300 min, the removal efficiency of AlN reached 89.05%. The kinetics were described using the unreacted core model, and when the temperature was 30–40, 50–70, and 80–90 °C, the hydrolysis reaction rate of AlN was controlled by boundary layer diffusion, chemical reaction control, and product layer diffusion control, respectively.

Melanin has been reported to have potential applications in industries such as cosmetics and food due to its anti-UV and antioxidative qualities. However, the corresponding data on its safety evaluation or biological consequences are fairly limited; such data are critical given its widespread use. The effect of different concentrations (1, 2, 3, and 4%) of melanin on growth status (larvae length and weight, cocoon weight, and morphology), the microstructure of the various tissues (fat body, silk gland, and midgut), and silk properties was studied by using the silkworm (bombyx mori) as the model organism. The weight and length of silkworm larvae fed with melanin were lower than the control, indicating that melanin appears to have a negative effect on the growth status of silkworms; however, the histophysiology analysis indicates that the cell morphologies are not changed, the XRD and FTIR spectra indicate that the secondary and crystalline structures of silks are also well preserved, and the thermogravimetric analysis and tensile test indicate that the thermal stability and mechanical properties are well maintained and even improved to some extent. Generally, it indicates that melanin has a certain inhibitory effect on the growth of silkworm larva but causes no harm to the cell microstructures or silk properties; this demonstrates that the safety of melanin as a food addictive should be considered seriously. The increase of thermal stability and mechanical properties shows that melanin may be a good chemical modifier in textile industries.

In the case of earthquake and rockfall disasters, it is proposed to replace part of sand with geofoam material to form sand–EPS and sand–EPE composite cushions to improve the ability of structures to resist disasters. The shear performance of the sand–EPS beads mixture material with different moisture contents, the impact resistance of sand–EPS beads and sand–flocculent-EPE layered composite materials with different cushion thicknesses and different mass ratios were studied by direct shear tests and multi-impact tests. The results showed that with the increase in the moisture content, the shear strength of the sand–EPS beads decreased, the internal friction angle of sand–EPS decreased first and then increased, and the cohesion of sand–EPS increased first and then decreased. The sand–geofoam layered cushion had better buffering performance. Sand–EPE has better durability than Sand–EPS.

Rocking shallow foundations can be used as an effective seismic isolation means to reduce earthquake-induced damage to structures by utilizing nonlinearities arising from base uplifting and soil yielding. A number of studies have been devoted to the proposal of inelastic displacement ratios for estimating the maximum inelastic displacement demands on yielding structures on rocking shallow foundations for seismic evaluation purposes. However, there is a lack of methods for estimating structural deformations associated with damage to structures, which are usually measured using structural drift ratios. Since drift ratios of structures on rocking foundations consist of contributions due to foundation rocking, it is necessary to figure out whether these rocking rotations should be removed from structural drift ratios to obtain effective structural drift ratios related solely to structural straining. A comprehensive parametric analysis is carried out in this study to quantify the contribution of foundation rocking. Based on the results, a structural displacement ratio is proposed to estimate effective structural drift ratios excluding foundation rocking rotation, and an empirical expression is provided so that effective structural drift ratios can be directly obtained using available expressions for the inelastic displacement ratios of rocking shallow foundations.

Tricholoma matsutake is an edible fungus that contains various bioactive substances, some of them with immunostimulatory properties. Presently, there is limited knowledge about the functional components of T. matsutake. Our aim was to evaluate the protective effects and molecular mechanisms of two T. matsutake-derived peptides, SDLKHFPF and SDIKHFPF, on lipopolysaccharide (LPS)-induced mitochondrial dysfunction and inflammation in RAW264.7 macrophages. Tricholoma matsutake peptides significantly ameliorated the production of inflammatory cytokines and inhibited the expression of COX-2, iNOS, IKKβ, p-IκB-α, and p-NF-κB. Immunofluorescence assays confirmed the inhibitory effect of T. matsutake peptides on NF-κB/p65 nuclear translocation. Furthermore, the treatment with T. matsutake peptides prevented the accumulation of reactive oxygen species, increased the Bcl-2/Bax ratio, reversed the loss of mitochondrial membrane potential, and rescued abnormalities in cellular energy metabolism. These findings indicate that T. matsutake peptides can effectively inhibit the activation of NF-κB/COX-2 and may confer an overall protective effect against LPS-induced cell damage.

Hydrodynamic pressure is often a crucial factor in the evaluation of slope stability analysis, especially for many rainfall-triggered landslides. Nevertheless, hydrodynamic pressure is rarely considered in the traditional limit equilibrium slice method of slope stability analysis since effective and reliable hydrodynamic pressure data are often lacking in practice. Moreover, efficient methods to involve these data in slope stability analysis are an urgent need. To overcome these concerns, the flow velocity and direction system (FVDS) is employed to measure the groundwater flow velocity, which can be used to generate hydrodynamic pressure samples at different monitoring points. Based on these samples, the hydrodynamic pressure of each soil strip is estimated using artificial neural networks (ANNs). Afterward, an improved Bishop method that considers hydrodynamic pressure is proposed. The effectiveness and significance of the proposed method are illustrated with a case study, the Fanshantou landslide in Zhejiang Province, China. The safety factor before and after taking drainage countermeasures is also calculated and compared. The results indicate that hydrodynamic pressure plays an important role in the stability analysis of the Fanshantou landslide. Compared with the classical Bishop method, the improved method is shown to agree better with the actual deformation characteristics of the landslide.

In laser systems, beam pointing usually drifts as a consequence of various disturbances, e.g., inherent drift, airflow, transmission medium variation, mechanical vibration, and elastic deformation. In this paper, we develop a laser beam pointing control system with Fast Steering Mirrors (FSMs) and Position Sensitive Devices (PSDs), which is capable of stabilizing both the position and angle of a laser beam. Specifically, using the ABCD matrix, we analyze the kinematic model governing the relationship between the rotation angles of two FSMs and the four degree-of-freedom (DOF) beam vector. Then, we design a Jacobian matrix feedback controller, which can be conveniently calibrated. Since disturbances vary significantly in terms of inconsistent physical characteristics and temporal patterns, great challenges are imposed to control strategies. In order to improve beam pointing control performance under a variety of disturbances, we propose a data-driven disturbance classification method by using a Recurrent Neural Network (RNN). The trained RNN model can classify the disturbance type in real time, and the corresponding type can be subsequently used to select suitable control parameters. This approach can realize the universality of the beam stabilization pointing system under various disturbances. Experiments on beam pointing control under several typical external disturbances are carried out to verify the effectiveness of the proposed control system.

(1) Background: Growing evidence suggests that electroencephalography (EEG), recording the brain’s electrical activity, can be a promising diagnostic tool for Alzheimer’s disease (AD). The diagnostic biomarkers based on quantitative EEG (qEEG) have been extensively explored, but few of them helped clinicians in their everyday practice, and reliable qEEG markers are still lacking. The study aims to find robust EEG biomarkers and propose a systematic discrimination framework based on signal processing and computer-aided techniques to distinguish AD patients from normal elderly controls (NC). (2) Methods: In the proposed study, EEG signals were preprocessed firstly and Maximal overlap discrete wavelet transform (MODWT) was applied to the preprocessed signals. Variance, Pearson correlation coefficient, interquartile range, Hoeffding’s D measure, and Permutation entropy were extracted as the input of the candidate classifiers. The AD vs. NC discriminant performance of each model was evaluated and an automatic diagnostic framework was eventually developed. (3) Results: A classification procedure based on the extracted EEG features and linear discriminant analysis based classifier achieved the accuracy of 93.18 ± 3.65 (%), the AUC of 97.92 ± 1.66 (%), the F-measure of 94.06 ± 4.04 (%), separately. (4) Conclusions: The developed discrimination framework can identify AD from NC with high performance in a systematic routine.

In this paper, Au nanoshell arrays, serving as a photo-activated material, are fabricated via the combination of self-assembled nanosphere lithography and the thermal decomposing polymer method. The intensity and position of surface plasmonic resonance can be tuned from the visible region to the near-infrared region by changing the size of Au nanoshell arrays. When resonance absorption peaks of metal nanoparticles are matched with emission wavelengths of core-shell CdSe/CdS quantum dots, fluorescent intensity of CdSe/CdS quantum dots can be strongly enhanced. The physical mechanism of fluorescent enhancement is explained.