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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.

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.

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.

(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.

The remarkable efficacy of COVID-19 vaccines has established mRNA as a highly promising biomedical technology. However, the adequate application of mRNA therapeutics necessitates additional measures to mitigate the inherent immunogenicity, which is predominantly caused by dsRNA. As a byproduct of the in vitro transcription of mRNA, dsRNA was reported to be originated through several distinct mechanisms, including the extension of 3′ loop-back hairpins, the extension of hybridized abortive transcripts, and promoter-independent transcription. The intricate mechanisms involved pose a dilemma as the reduction in dsRNA results in a concomitant decrease in other critical quality attributes of mRNA. Here, we demonstrate that the promoter binding motifs of T7 RNA polymerase directly impact the production of promoter-independent transcription-based dsRNA. Specifically, the G753A mutation significantly reduces the formation of dsRNA byproducts, which can further combine with modified nucleotides to enhance the effectiveness of dsRNA mitigation and with previously reported high-integrity mutation K389A to minimize side effects. Accordingly, the present study reports a cost-effective approach to synthesize high-purity, less immunostimulatory mRNA by using an engineered T7 RNA polymerase mutant.

The power attenuation of internal combustion engines in high-altitude environments restricts the performance of unmanned aerial vehicles. Herein, a single-zone model of a hydrogen-doped high-efficiency hybrid cycle rotary engine that considers high-altitude environments was proposed. The indicated values for power, thermal efficiency, and specific fuel cost were used to evaluate the power performance, energy conversion efficiency, and economic performance of the engine, respectively. Then, the effects of adjusting the hydrogen fraction, ignition angle, and rotational speed on high-altitude performance were analyzed. The results showed that high-altitude environments prolonged combustion duration and reduced in-cylinder pressure, thereby causing power attenuation; however, increasing the hydrogen fraction can increase the indicated power. At an altitude of 6 km, the indicated power with a hydrogen fraction of 0.3 was approximately 20.7% higher than that obtained with pure gasoline. The ignition angle and hydrogen fraction corresponding to the optimal indicated thermal efficiency increased with increasing altitude. At an altitude of 6 km, the indicated thermal efficiency reached its maximum (36.4%) at an ignition angle of 340 [CA°] and a hydrogen fraction of 0.15. At high altitudes, rotational speeds below 6000 rpm and ignition angles of 340–345 [CA°] were beneficial in reducing indicated specific fuel costs.

As a new type of power device, the X-type rotary engine (XRE) is regarded as a major revolution of the internal combustion engine with its special structure and high-efficiency hybrid cycle (HEHC). A 3D CFD model of an XRE with hydrogen–gasoline fuel is firstly built in this paper. The gasoline is premixed with air in the intake of the XRE. The hydrogen is directly injected (DI) into the cylinder with four different injection positions. The effects of the hydrogen injection position on the combustion process, engine thermodynamic performance, and unburned carbon emissions and NOx emissions are investigated. The results show that, due to the interaction between the in-cylinder main flow field and the injected hydrogen gas flow, different hydrogen concentration zones are formed at different injection positions. Furthermore, a larger hydrogen distribution area and being closer to the ignition position led to a faster in-cylinder combustion rate and a higher in-cylinder temperature and pressure. When the injection position is from the front to the back of the combustion chamber such as in position 2, the hydrogen has the widest distribution area and is closest to the ignition position, resulting in its fastest combustion speed. Meanwhile, the peak in-cylinder pressure is 3.73 MPa and the peak temperature is a maximum of 1835.16 K. Especially, the highest indicated thermal efficiency of 26.56% is found in position 2, which is 10.08% higher than that of position 4 (from right to left of the combustion chamber), which was 24.13%. At the same time, due to the best overall combustion effect, position 2 presents the lowest final unburned carbon emission of 0.36 mg, while it produces the highest NOx emission of 9.15 μg. Thus, this study provides important theoretical guidelines for the hydrogen injection strategy of the XRE using hydrogen–gasoline fuel.

Effective control of the cohesive force between hydrate particles is the key to prevent their aggregation, which then causes pipeline blockage. The hydrophilic–lipophilic balance (HLB) value of surfactants was proposed as an important parameter for the evaluation and design of hydrate anti-agglomerants. A microscopic manipulation method was used to measure the cohesive forces between cyclopentane hydrate particles in the presence of Tween and Span series surfactants with different HLB values; moreover, the measured cohesive force was compared with the results of calculations based on the liquid bridge force model. Combined with the surface morphology and wettability of the hydrate particles, we analyzed the mechanism by which surfactants with different HLB values influence the cohesion between hydrate particles. The results show that for both Tween (hydrophilic, HLB > 10) and Span (hydrophobic, HLB < 10) surfactants, the cohesive force between cyclopentane hydrate particles decreased with decreasing HLB. The experimental results were in good agreement with the results of calculations based on the liquid bridge force model. The cohesive force between hydrate particles increased with increasing concentration of Tween surfactants, while in the case of the Span series, the cohesive force decreased with increasing surfactant concentration. In the formation process of cyclopentane hydrate particles, the aggregation of low-HLB surfactant molecules at the oil–water or gas–water interface increases the surface roughness and hydrophobicity of the hydrate particles and inhibits the formation of liquid bridges between particles, thus reducing the cohesion between particles. Therefore, the hydrate aggregation and the associated blockage risks can be reduced.

The balise transmission system (BTS) is an automatic identification system for vehicle–ground communication based on radio frequency identification (RFID) technology. The electromagnetic coupling characteristics of BTS have a very important effect on the transmission quality of the uplink telegram signals. However, signal transmission problems of BTS often occur due to unreasonable installation mode or parameter setting. In order to solve these problems, it is necessary to fully discuss the electromagnetic coupling characteristics of the BTS. In this paper, the transmission process of energy and data between the onboard antenna unit and the balise was analyzed using digital twin technology. A high-precision dynamic electromagnetic coupling model of the BTS was established from four aspects of three-dimensional structure, physical properties, behavior patterns, and rule restrictions. Then the accuracy of the model was verified by experiments. Finally, the influence of typical parameters on the uplink signal is calculated and analyzed quantitatively. The results showed that compared with other factors discussed in this paper, the vertical distance and the installation mode had greater effects on the uplink signal. These results can be used to guide the engineering installation and related optimization of the BTS.

For high-speed train, balise transmission module (BTM) system is easily interfered with by other equipment of the train. This could cause the train to malfunction. Studying the electromagnetic susceptibility (EMS) of the BTM is very important for the performance and efficiency of the train. In this paper, a modular, system-level modeling method is proposed to predict the EMS of BTM systems. Based on object-oriented technology and a modular method, the BTM system is disassembled into several modules according to the electromagnetic characteristics of the whole system rather than the physical structure. All the modules are mutually independent, and the total EMS could be evaluated by the output of them. The modules of three key elements of electromagnetic compatibility (EMC), i.e., sources, coupling paths, and sensitive equipment, are established by the theoretical method, full-wave simulation method, and black-box test method, respectively, and put into different layers. According to the functions of the BTM system, the EMS of BTM is given by analyzing the interrelation of input and output of modules. Results of the proposed model were verified by measurement.

Copper-based materials are common industrial products which have been broadly applied to the fields of powder metallurgy, electrical contact, and heat exchangers, etc. However, the ease of surface oxidation limits the durability and effectiveness of copper-based components. Here, we have developed a powder metallurgy process to fabricate graphene/copper composites using copper powders which were first deposited with graphene layers by thermal chemical vapor deposition (CVD). The graphene/copper composites embedded with an interconnected graphene network was then able to be obtained by vacuum hot-pressing. After thermal oxidation (up to 220 °C) in humid air for several hours, we found that the degree of surface oxidation of our samples was much less than that of their pure Cu counterpart and our samples produced a much smaller increase of interfacial contact resistance when used as electrical contact materials. As a result, our graphene/copper composites showed a significant enhancement of oxidation resistance ability (≈5.6 times) compared to their pure Cu counterpart, thus offering potential applications as novel electrical contact materials.

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.

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.

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.