Machinery degradation assessment can offer meaningful prognosis and health management in-formation. Although numerous machine prediction models based on artificial intelligence have emerged in recent years, they still face a series of challenges: (1) Many models continue to rely on manual feature extraction. (2) Deep learning models still struggle with long sequence prediction tasks. (3) Health indicators are inefficient for remaining useful life (RUL) prediction with cross-operational environments when dealing with high-dimensional datasets as inputs. This research proposes a health indicator construction methodology based on a transformer self-attention transfer network (TSTN). This methodology can directly deal with the high-dimensional raw dataset and keep all the information without missing when the signals are taken as the input of the diagnosis and prognosis model. First, we design an encoder with a long-term and short-term self-attention mechanism to capture crucial time-varying information from a high-dimensional dataset. Second, we propose an estimator that can map the embedding from the encoder output to the estimated degradation trends. Then, we present a domain dis-criminator to extract invariant features from different machine operating conditions. The case studies with the FEMTO-ST bearing dataset and the Monte Carlo method for RUL prediction during the degradation process are conducted. The experiment results fully exhibited the signif-icant advantages of the proposed method compared to other state-of-the-art techniques.

Transit-oriented development (TOD), such as metro depot and over-track building complexes, has expanded rapidly in China. Over-track building construction has the advantage of comprehensive utilization of land resources, ease of commuting to work, and provide funds for subway construction. However, there still has a pending problem, disturbance of railway vibration, for TOD. Excessive noise and vibration seriously affect people’s life. To address this challenge, field measurements are used to obtain the vibration source characteristics and vibration propagation of the ground and the superstructure in this study. And the typical metro depot with over-track building in Wuhan was selected. The effects of vibration on the surrounding ground and adjacent buildings caused by the operation of trains have been measured, and the propagation law of train-induced ground vibration acceleration in the time and frequency domains has been analyzed. The distribution and propagation laws of vibration noise, structural noise and secondary structure noise in sensitive areas such as the throat area, depot area, test section and access section of the over-track buildings and their impact laws on the over-track buildings are obtained. And the effectiveness of the vibration and noise reduction methods used were evaluated. Results show that within 43 m from the train running track, the train running induced vertical vibration acceleration level in the high-rise building peak size of 58.8 dB, the average value of 55.62 dB; vibration frequency components are mainly 40-60 Hz. The findings might provide useful insight for designing vibration mitigation systems in new metro depots with over-track buildings.

Based on the analysis of the working principle, circuit design and working loss of the common charger DC/DC converter, this paper designs a ZVS half-bridge three-level DC/DC converter based on non-phase-shift control mode, and proposes a multi-stage constant current and voltage limiting charging control strategy based on modulation wave selection control. The simulation results show that the proposed method and control strategy have faster voltage regulation ability and wider stability margin, and can achieve stable current sharing control in the charging process.

Chrysanthemum tea, a typical health tea with the same origin as medicine and food, is famous for its unique health benefits and flavor. To clarify the influence of metabolites of different varieties of chrysanthemum tea on the formation of taste and quality differences, nontargeted metabolomics combined with electronic tongue analysis were used to characterize the correlation between metabolites profiles and taste characteristics of different quality chrysanthemum tea. Thirteen metabolites were identified as the key metabolites of the sensory quality difference between Huangju and Jinsi Huangju tea. Kaempferol, luteolin, genistein, and some quinic acid derivatives were correlated with the ‘astringent’ and taste attributes. In contrast, l-(-)-3 phenyllactic acid and L-malic acid were found to be the ‘bitterness’ and ‘umami’ in chrysanthemum tea. KEGG pathway enrichment analysis showed that the flavonoid and flavonol biosynthesis pathway had important effects on the sensory quality of chrysanthemum tea.

As a new plant slope protection technology, living stumps can effectively improve slope stability. The current study attemptes to investigate the mechanical characteristics of the root system of living stumps and their reinforcement mechanism on slopes by carrying out a three-dimensional living stump slope modeling test. Using ABS materials, a 3D model of a living elm stump was created by 3D printing and a slope model test was carried out. The reinforcement mechanism of the living stump was studied through a combination of model testing and numerical simulation. The results indicate that, due to the presence of living stumps in the lower and middle parts of the slope, the maximum shear stress area of the soil moved to a deeper direction. The stress state of the soil around the living stump was effectively improved due to the existence of the lateral root system.Living stumps in the lower part of the slope cross the potential sliding surface and transferred the soil shear stress gradually to the root system through root-soil interaction. Moreover, the tap roots and lateral roots of living stumps form a robust spatial structure that bears the shear stress of soil together, thus increasing the stability of the slope.

The combination of encryption and digital watermarking technologies is a trend to achieve full lifecycle data protection. Recently, reversible data hiding in encrypted domain (RDHED) has greatly aroused the interests of many scholars. But the fixed order of first encryption and then watermarking makes this kind of algorithms unsuitable to many applications. Commutative encryption and watermarking (CEW) technology realizes the flexible combination of encryption and watermarking, and suits more applications. However, most existing CEW schemes for vector maps are not reversible and unsuitable to high precision maps. To solve this problem, here we propose a commutative encryption and reversible watermarking (CERW) algorithm for vector maps based on virtual coordinates which are uniformly distributed on the number axis. The CERW algorithm consists of virtual interval step based encryption scheme and coordinate difference based reversible watermarking scheme. In the encryption scheme, the map coordinates are moved randomly by multiples of virtual interval step defined as distance between two adjacent virtual coordinates. In the reversible watermarking scheme, difference expansion (DE) technique is used to embed the watermark bit into the coordinate difference computed based on the relative position of a map coordinate in a virtual interval. Since the relative position of a map coordinate in a virtual interval keeps unchanged during the coordinate scrambling encryption process, the watermarking operation and the encryption operation don’t interfere with each other and the commutativity between encryption and watermarking achieves. Results show that: proposed method has high security, high capacity and good invisibility. In addition, the algorithm is not only applicable to polyline and polygon vector data, but also can be applied to sparsely distributed point data which the traditional DE watermarking algorithm often fails to watermark.