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Truck platooning has been identified as an emerging and promising operational technology with the advantages of fuel consumption savings and carbon emissions reductions. We formulate the truck platooning routing optimization problem as a multi-commodity network flow problem from a transportation optimization and scheduling perspective. Based on fuel consumption savings generated through the reduction of aerodynamic drag by the formation of truck platooning, the route of each truck is also set to be a decision variable needing settlement to facilitate the formation of truck platooning to maximize fuel consumption savings. Considering fuel consumption and detour costs, we construct a truck platooning routing optimization model with minimum overall system fuel consumption as the optimization objective. The output of the routing optimization model could both reflect the composition of each truck platooning on each link and directly show the routings of each truck. To explore the impact of the restrictions on the number of trucks in truck platooning on overall fuel consumption savings, road networks are constructed and the truck platooning routing optimization model is solved by the commercial solver CPLEX. Compared to individual trucks, 8% or 12% fuel consumption savings are achieved, respectively, with the number of trucks being restricted or not restricted in truck platooning. Considering the different fuel reduction rates of the following trucks in platooning on the system performance in terms of the total fuel cost, a sensitivity analysis is also conducted. The results also show that the ideal truck platooning routing plan can be obtained by the proposed model, and the study provides a theoretical reference for the promotion and application of truck platooning.

In this study, a green and efficient extraction methodology was developed by leveraging the unique properties of chitosan—namely its non-toxicity, biocompatibility, and adhesive nature—to enhance the recovery of bioactive ingredients from Forsythia suspensa leaves. The core mechanism involves the formation of complexes between chitosan and the target bioactive ingredients, which significantly boosts their extraction efficiency. To substantiate this mechanism, comprehensive characterization was performed using Powder X-ray Diffraction (PXRD), Fourier Transform Infrared Spectroscopy (FT-IR), Differential Scanning Calorimetry (DSC), Scanning Electron Microscopy (SEM), and molecular docking analyses. The results provided robust evidence of a strong interaction between chitosan and the bioactive ingredients, leading to a marked enhancement in both the stability and aqueous solubility of the target compounds. For process optimization, a multi-objective approach was implemented using the Non-dominated Sorting Genetic Algorithm II (NSGA-II) to simultaneously maximize the extraction yields of phillyrin and forsythoside A. The algorithm identified the optimal parameters as a leaf-to-chitosan mass ratio of 10:11.75, a solid-to-liquid ratio of 1:52 g/mL, a temperature of 80 °C, and a duration of 120 min. Under these optimized conditions, the corresponding extraction yields for phillyrin and forsythoside A were 1.68 ± 0.16% and 3.23 ± 0.27%, respectively. These findings collectively indicate that chitosan-assisted extraction represents a highly promising and advanced technology for the sustainable and effective extraction of bioactive ingredients from botanical sources.

Background Discipline competitions play an important role in higher education, as they drive innovation. Despite recognition of their educational value, little is known about the psychological mechanisms that determine students’ efficacy in these settings. The relationship between internal cognitive effects and outside help needs further study. Methods This study developed the model based on an extended Unified Theory of Acceptance and Use of Technology 2 framework with self-efficacy theory. Perceived instructor support and self-efficacy were included in the model as key predictors. An online questionnaire was administered to 506 Chinese university students with competition experience. The model was tested using Covariance-Based Structural Equation Modeling. Fuzzy-set Qualitative Comparative Analysis was used to identify pathways within the complex set of causes leading to high effectiveness. Results The results of the CB-SEM analysis indicate that performance expectancy, effort expectancy, social influence, and facilitating conditions significantly enhanced competition intention. In addition, competition intention had a strong positive impact on competition effectiveness (β = 0.429, p  < 0.001). Self-efficacy and perceived instructor support also proved direct, significant positive predictors of effectiveness (β = 0.227, p  < 0.001; β = 0.131, p  = 0.013). The fsQCA revealed three distinct yet equal paths to high effectiveness: the Motivation-Support pathway, the Social-Driven pathway, and the Resource-Guided pathway. Conclusions As per the findings, competition intention acts as a mediator for self-efficacy, which is a vital resource of the mind. Their results show that effectiveness is not the product of one variable, but rather specific combinations of motivational, social, and resource-based conditions. This research offers a sophisticated psychological understanding of competitive performance outcomes based on evidence from successful competitors. Its completion has implications for educators to tailor mechanisms of support and develops agency. Competitors, the bid team, and their tailor have implications for a wide range of students.

Distance is crucial to inbound tourism for islands that depend heavily on external connectivity. While the concept of distance has expanded into a multidimensional construct, its complex dynamic effects across multiple dimensions remain underexplored, particularly in island contexts. This study investigates how multidimensional distance influences inbound tourism volume (ITV) to Hainan Island, China. We innovatively integrate the cultural, administrative, geographic, and economic distance framework with the cross-sectionally augmented autoregressive distributed lag model. Using panel data from 22 countries covering 2008–2023, we estimate short-run dynamics and long-run effects. The results reveal substantial heterogeneity: Cultural distance exerts a significant positive long-run effect, indicating cultural novelty attracts international tourists. Conversely, economic, administrative, and geographic distances show significant inhibitory effects, reflecting persistent market, institutional, and spatial barriers. Short-run effects broadly mirror long-run dynamics, with ITV showing path dependence. This study introduces an integrated framework for island tourism research and provides a policy matrix for destination management.

In order to solve the problem that the railway passenger volume data are abnormal due to holidays and major events interfering with the prediction accuracy, the spline interpolation method is introduced to replace the abnormal passenger volume data. In addition, an improved particle swarm optimization (IPSO) is proposed to optimize the gradient difference acceleration law to combine and improve the predicted value and further improve the prediction accuracy of the railway passenger traffic. Finally, taking Beijing as the research object, the Holt exponential smoothing method and the BP neural network are selected to verify the effect of spline interpolation and IPSO-gradient difference acceleration law on prediction accuracy. The research results show that the spline interpolation method has a better prediction effect after processing abnormal passenger traffic data, and the improved particle swarm algorithm also shows better optimization ability and convergence speed when solving the double difference postulate. In comparison with the BP neural network, Holt exponential smoothing, simple averaging, and conventional redifference approaches, the IPSO-redifference acceleration method achieves a superior prediction performance, and the absolute values of the forecast error are reduced by 3.320%, 1.518%, 2.419%, and 0.602%.

Ground-based synthetic aperture radar (GB-SAR) is a highly effective technique that is widely used in landslide and bridge deformation monitoring. GB-SAR based on multiple input multiple output (MIMO) technology can achieve high accuracy and real-time detection performance. In this paper, a novel method is proposed to design transmitting and receiving array elements, which increases the minimum spacing of the antenna by sacrificing several equivalent phase centers. In MIMO arrays, the minimum antenna spacing in the azimuth direction is doubled, which increases the variety of antenna options for this design. To improve the accuracy of the system, a new method is proposed to estimate channel phase errors, amplitude errors, and position errors. The position error is decomposed into three directions with one compensated by the phase error and two estimated by the strong point. Finally, we validate the accuracy of the system and our error estimation method through simulations and experiments. The results prove that the GB-SAR system performs well in bridge deformation and vibration monitoring with the proposed method.

The pavilion is a time-honored architectural form in the Chinese silhouette with strong regional characteristics. Its appearance and technical means are often adaptively combined according to the characteristics of local architecture. The “kiln–house isomorphism” is a unique construction technology of the Shanxi construction type in China. Therefore, the “kiln–house isomorphism” is generally adopted for the construction of pavilions in Shanxi. This study focuses on Xiaonanzhuang Village, Yuci District, Jinzhong City, Shanxi Province. Taking the Xiang-ming Pavilion, the core building of the village, as an example, we analyze the architectural characteristics of the “kiln–house isomorphism” in the pavilion in this area, describe the general construction rules of the region, and conduct a deep investigation of the five “cultural isomerism” factors of the pavilions in the region, namely, geomancy, etiquette and music, beliefs, clans, and cultivation and study. The results of this research will enrich the regional knowledge of such pavilions and add new objects for the protection of local architectural heritage, providing a theoretical basis for the contemporary adaptive reuse of pavilions in the Yuci area from a cultural perspective.

Three-dimensional biofilm electrode reactors (3D-BERs) exhibit efficacy in the removal of refractory wastewater of pharmaceuticals due to the resistance of pharmaceutical wastewater to biodegradation. In this paper, a new 3D-BER with a polyurethane sponge carrier was applied to the treatment of pharmaceutical wastewater containing tetrahydrofuran (THF) with an objective of exploring the removal efficiency, degradation pathway and main functions of microorganisms of 3D-BERs for wastewater containing THF. The results indicate that when the voltage is 10 V, the highest CODCr removal efficiency is (95.9 ± 1.6)%. Compared to the control group, the removal rate was increased by 21.97 ± 4.69%. The main intermediates of THF, γ-butyrolactone and 4-hydroxybutyric acid, were detected, respectively, by Gas Chromatography–Mass Spectrometry (GC–MS), indicating that 3D-BERs contribute to the degradation of THF with electro-oxidation as well as microbial synergism. Microorganisms, such as Proteobacteria with extracellular electron transfer capacity, Bacteroidetes capable of degrading complex carbon sources and parthenogenic anaerobic bacteria Firmicutes, were found to be enriched by high-throughput sequencing analysis in 3D-BERs, which were conducive to the degradation of refractory pollutants. At the genus level, Chryseobacterium, Brevundimonas, Erysipelothrix, and Desulfovibrio were the main functional genera, whose degradation of THF intermediates was found by functional prediction, mainly through chemoheterotrophy, aerobic chemoheterotrophy, etc. It is to be hoped that this study will provide a solution to the practical treatment of pharmaceutical wastewater containing THF via this new 3D-BER system with a polyurethane sponge carrier.

Ground-Based Synthetic Aperture Radar (GB-SAR), due to its high precision, high resolution, and real-time capabilities, is widely used in the detection of slope deformations. However, the weak scattering coefficient in low-coherence areas poses a great challenge to the observation point selection accuracy. This paper introduces a selection process for reliable observation points that integrates phase and spatial information. First, for various observation points with differentiated stability, we propose to utilize maximum likelihood estimation (MLE) methods to achieve stability assessment. Second, a phase correction approach is proposed to address unwrapped phase errors encountered at less stable points. Third, adaptive filtering for deformation information at observation points is achieved using estimated variance combined with wavelet filtering thresholds. Finally, in dealing with unknown deformation trends, we propose utilizing a clustering method to accurately identify these trends, thereby enhancing the precision in identifying reliable observation points (ROPs). The experimental results demonstrate that this method enhances the accuracy of observation point selection in low-coherence areas, providing a broader observational field for deformation detection.

Cool-season plant growth and development are impacted by high temperatures. As a biostimulant, glycine betaine is responsible for inducing tolerance to both biotic and abiotic stressors. However, the mechanism by which glycine betaine protects cool-season crops against high-temperature stress is not clear. In the present study, under the conditions of high temperatures (35 °C/30 °C day/night), cherry radishes (Raphanus sativus var. radicula Pers.) (Brassicaceae) were cultured for 9, 18, and 27 days, and different concentrations (0, 0.067, 8.79, 11.72, 14.65, and 17.58 mg L−1) of glycine betaine were applied to investigate the influence of glycine betaine on cherry radish biomass, quality, net photosynthetic rate, chlorophyll content, antioxidant enzyme activity, and endogenous hormone content under high-temperature stress. The results showed that, under high-temperature conditions, cherry radishes grew best with the 17.58 mg L−1 glycine betaine treatment. At day 27, comparing the 17.58 mg L−1 glycine betaine treatment with 0 mg L−1 glycine betaine under high-temperature stress, the cherry radish biomass increased by 44.7%, while the soluble protein and vitamin C content increased by 14.4% and 21.6%, respectively, the net photosynthetic rate and chlorophyll a content increased by 7.8% and 44.1%, respectively, and the peroxidase and catalase levels increased by 81.0% and 146.3%, respectively. On day 9, the auxin, abscisic acid, and glycine betaine contents significantly increased by 67.4%, 6.8%, and 32.9%, respectively, in comparing the 17.58 mg L−1 glycine betaine treatment with 0 mg L−1 glycine betaine under high-temperature stress. Therefore, the application of 17.58 mg L−1 betaine to cherry radishes grown under high-temperature stress had positive effects. The appropriate concentration of glycine betaine can improve the resistance of cherry radish to high temperatures and maintain yield.