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At present, data-driven fault diagnosis has made significant achievements. However, in actual industrial environments, labeled fault data are difficult to obtain, making the industrial application of intelligent fault diagnosis models very challenging. This limitation even prevents intelligent fault diagnosis algorithms from being applicable in real-world industrial settings. In light of this, this paper proposes a Collaborative Domain Adversarial Network (CDAN) method for the fault diagnosis of rolling bearings using unlabeled data. First, two types of feature extractors are employed to extract features from both the source and target domain samples, reducing signal redundancy and avoiding the loss of critical signal features. Second, the multi-kernel clustering algorithm is used to compute the differences in input feature values, create pseudo-labels for the target domain samples, and update the CDAN network parameters through backpropagation, enabling the network to extract domain-invariant features. Finally, to ensure that unlabeled target domain data can participate in network training, a pseudo-label strategy using the maximum probability label as the true label is employed, addressing the issue of unlabeled target domain data not being trainable and enhancing the model's ability to acquire reliable diagnostic knowledge. This paper validates the CDAN using two publicly available datasets, CWRU and PU. Compared with four other advanced methods, the CDAN method improved the average recognition accuracy by 7.85% and 5.22%, respectively. This indirectly proves the effectiveness and superiority of the CDAN in identifying unlabeled bearing faults. [ABSTRACT FROM AUTHOR]

The planetary boundary layer (PBL) over the Tibetan Plateau (TP) exerts a significant influence on regional and global climate, while its vertical structures of turbulence and evolution features remain poorly understood, largely due to the scarcity of observations. This study examines the vertical profile of and daytime variation in the turbulence dissipation rate (ε) in the PBL and free troposphere over the TP using the high-resolution (6 min and 120 m) measurements from a radar wind profiler (RWP) network, combined with hourly data from ERA5 during the period from 1 September 2022 to 31 October 2023. Observational analyses show that the magnitude of ε below 3 km under all-sky conditions exhibits a large spatial discrepancy over the six RWP stations over the TP. Particularly, the values of ε at Minfeng and Jiuquan over the northern TP and at Dingri (alternately Tingri) over the southern TP are roughly an order of magnitude greater than those at Lijiang, Ganzi (alternately Garzê), and Hongyuan over the eastern TP. This could be partially attributed to the difference in land cover across the six RWP stations. In terms of the diurnal variation, ε rapidly intensifies from 09:00 local standard time (LST) to 14:00 LST and then gradually levels off in the late afternoon. Under clear-sky conditions, both ε and the planetary boundary layer height (zi) are greater compared with cloudy-sky conditions, which could be due to the cooling effect of clouds, which reduces the solar irradiation reaching the surface. In the lower PBL (0.3 ≤ z/zi ≤ 0.5), where z is the height above ground level, the dominant influential factor in the development of turbulence is the surface–air temperature difference (Ts-Ta). By comparison, in the upper PBL (0.6 ≤ z/zi ≤ 1.0), both Ts-Ta and vertical wind shear (VWS) affect the development of turbulence. Above the PBL (1.0 < z/zi ≤ 2.0), the shear production resulting from VWS dominates the variation in turbulence. Under cloudy-sky conditions, the reduced Ts-Ta and weakened surface sensible heat flux tend to inhibit the turbulent motion in the PBL. On the other hand, the strong VWS induced by clouds enhances the turbulence above the PBL. The findings obtained here underscore the importance of the RWP network in revealing the fine-scale structures of the PBL over the TP and gaining new insight into the PBL evolution. [ABSTRACT FROM AUTHOR]

Given the important role of Atmospheric River precipitation (ARP) in the global hydrological cycle, accurate representation of ARP is significant. However, general circulation models (GCMs) demonstrate bias in simulating ARP. The target of this study is to quantify the performance of ARP intensity/frequency for CMIP6 simulations, and further to improve ARP estimation of CMIP6 using Cycle‐Consistent Generative Adversarial Networks (CycleGAN) with highlighting the more accurate ARP features under the global warming background. The findings of this study are as follows: (a) although ARP intensity/frequency in reserved‐optimal CMIP6 overall reproduces the observation, it is still underestimated at the stronger Atmospheric river (AR) scales, particularly for the AR highly active mid‐latitude regions. (b) The CycleGAN‐based bias correction approach markedly diminishes the bias of the CMIP6 simulations within most of the AR scales among both global and the four AR highly active regions. Moreover, the performance of the ARP in AR highly active regions is significant improvement, which is mainly due to the reduction of the bias at the strongest scale. (c) Relative to reference period (1986–2005), ARP intensity/frequency at the strongest scale increase notably under 3°C warming level, with an average value of 373.3% in intensity and 415.9% in frequency for global and the four key regions before correction, and the value is 451.9% and 492.5% after bias correction. The results illustrate that CycleGAN can effectively improve the ARP simulations of GCMs, and an early warning implies that future strong extreme ARP should potentially surpass the current expected. Plain Language Summary: Despite the important role of Atmospheric River precipitation (ARP) in global hydrological cycle, accurately simulating global ARP remains a great challenge. Here, the content of our study consists of three main parts. Firstly, we quantify the performance of CMIP6 general circulation models (GCMs) on ARP intensity/frequency simulations and find that CMIP6 GCMs underestimates ARP at the Atmospheric river (AR) highly active regions, especially in the strongest AR intensity scale. Secondly, we utilize a deep learning method named CycleGAN to improve global ARP intensity/frequency simulations of CMIP6 GCMs. The results indicate that CycleGAN effectively corrects the ARP intensity/frequency bias within most of the AR intensity scales among both global and the AR highly active regions. Moreover, the performance of ARP in the AR highly active regions is significant improvement, which is mainly due to the reduction of the bias in the strongest scale. Finally, the trained CycleGAN model is used to evaluate ARP under global warming of 1.5, 2, and 3°. The bias correction results show that ARP in the strongest AR intensity scale surpasses the current expected, especially under 3° warming level. Key Points: CMIP6 models underestimates Atmospheric River precipitation (ARP) at the Atmospheric river (AR) highly active regions, especially in the strongest AR scaleThe CycleGAN‐based deep learning method reduces model bias notably for ARP intensity and frequency, respectivelyARP in the strongest AR scale potentially surpasses the current GCM‐based projections expected in different degrees of warming after bias correction [ABSTRACT FROM AUTHOR]

Two distinct categories of weather patterns, denoted as Type 1 and Type 2, which show higher-than-expected frequency of summer heavy rainfall days (HRDs) over North China (NC), are selected from nine weather patterns categorized by the self-organizing map algorithm during 1979–2019. The respective HRDs over NC exhibit dissimilar characteristics, with Type 1 showing a northern distribution and Type 2 a southern distribution. The quantitative disparities in terms of moisture content and vertical motion are discussed in reactions to the synoptic-scale patterns associated with HRDs. The outcomes of a 20-day backward tracking, using the so-called Water Accounting Model-2layers, reveal noteworthy contrasts in moisture sources. Type 1 predominantly receives moisture from the western North Pacific, while Type 2 relies more on contributions from the Arabian Sea, Bay of Bengal, and Eurasia. However, the major moisture sources with grid cells contributing more than 0.01 mm show a consistent cumulative contribution of 77% for Type 1 and 80% for Type 2. The finding suggests that the discrepancy between the two types cannot be solely attributed to moisture supply. Further examination of the transverse and shearwise Q-vector components provides insights into how these distinct weather patterns influence HRDs by the alteration of vertical motion. In Type 1, an upper-level jet entrance induces a thermally direct secondary circulation that enhances vertical motion, while a baroclinic trough plays a dominant role in generating vertical motion in Type 2. Moreover, these unique configurations for each type of weather pattern are not only pre-existing but also intensified during HRDs. [ABSTRACT FROM AUTHOR]

To further comprehensively study the intramolecular weak interaction of the gaseous TKX‐50 molecule, the two conformations of the TKX‐50 molecule were analyzed via the Independent Gradient Model based on the Hirshfeld Partition (IGMH) method based on the B3LYP/6‐311 g (d,p) level for geometry optimization and for single point energy. The conclusions manifest that the weak interactions between these fragments are mainly composed of hydrogen bonds and van der Waals interactions. From the strength of inter‐fragment interactions formed by contributing atomic pairs and their percentage contributions, these H bonds, together with dispersion‐dominated weak interactions provided by non‐direct facing atomic pairs near these H bonds, dominate the inter‐fragment interaction resulting in the stability of the molecular structure. Meanwhile, the weak interactions enclosed by end‐atoms of two fragments not only include the contributions provided by inter‐fragment atomic pairs of two fragments but also include the contributions provided by intra‐fragment atomic pairs of fragment 1. For conformation II, due to the H transfer between fragments, a pair of symmetric H bonds at the corresponding regions are extremely strong to reach the level of covalent bond while the two groups −OH at the other end become looser, resulting in conformation II own lower energy. Differences in inter‐fragment interactions between two conformations were essentially brought by the stronger electron‐withdrawing ability of atom O than that of atom N. [ABSTRACT FROM AUTHOR]

There are many influencing factors of bubble curtain clipping technology. In order to obtain the optimal combination of bubble curtain in engineering applications, AUTODYN software was used to design a three factor and three level orthogonal test. The average reduction rate of shock wave peak pressure was used as an evaluation index to study the influence and sensitivity of the number of bubble curtain layers, the burst distance of the bubble curtain and the charge depth on the bubble curtain clipping effect. The results indicate that the clipping ability of the bubble curtain has a great value, and there will be a negative effect if the number of bubble curtain layers continues to increase. The number of bubble curtain layers has the greatest effect on the clipping ability, followed by the charge depth, and the effect of bubble curtain explosion center distance is the smallest. The smaller the burst center distance and the greater the depth of the packet, the better the bubble curtain chipping effect. When the number of bubble curtain layers is 2, the bubble curtain burst distance is 1 m, and the charge depth is 10.5 m, the clipping effect is the best. [ABSTRACT FROM AUTHOR]

In this study, we analyze the diurnal variations and formation mechanisms of low clouds at different elevations. We further discuss whether there exists a triggering mechanism for convection over the Tibetan Plateau (TP) and whether there is an association among low air density, strong turbulence, and ubiquitous "popcorn-like" cumulus clouds. The buoyancy term (BT) and shear term (ST) over the TP are significantly greater than those at low elevations, which is favorable for the formation of an increasing planetary boundary layer height (PBLH) and also plays a key role in the convective activities in the lower troposphere. From the viewpoint of global effects, the triggering of convection by boundary layer dynamics is analyzed over the TP, but also in the Northern Hemisphere over the Rocky Mountains. It is found that ST and BT are strong over both high-elevation regions. The strong thermal turbulence and large-scale ascending motion jointly result in obvious positive values of PBLH–LCL (lifting condensation level) under low relative humidity (RH) conditions over the TP. The obvious large-scale subsidence on both sides of the Rocky Mountains, especially the western side, leads to inversion above the PBL and lower RH within the PBL, which further leads to negative values of PBLH–LCL and decreased low cloud cover (LCC) in most parts of the Rocky Mountains. The slightly greater-than-zero PBLH–LCL corresponds spatially to increased LCC in the partial regions of the central Rocky Mountains. Thus, less LCC is generated at the Rocky Mountains compared to the TP. [ABSTRACT FROM AUTHOR]