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Accurate and fast rolling bearing fault diagnosis is required for the normal operation of rotating machinery and equipment. Although deep learning methods have achieved excellent results for rolling bearing fault diagnosis, the performance of most methods declines sharply when the working conditions change. To address this issue, we propose a one-dimensional lightweight deep subdomain adaptation network (1D-LDSAN) for faster and more accurate rolling bearing fault diagnosis. The framework uses a one-dimensional lightweight convolutional neural network backbone for the rapid extraction of advanced features from raw vibration signals. The local maximum mean discrepancy (LMMD) is employed to match the probability distribution between the source domain and the target domain data, and a fully connected neural network is used to identify the fault classes. Bearing data from the Case Western Reserve University (CWRU) datasets were used to validate the performance of the proposed framework under different working conditions. The experimental results show that the classification accuracy for 12 tasks was higher for the 1D-LDSAN than for mainstream transfer learning methods. Moreover, the proposed framework provides satisfactory results when a small proportion of the unlabeled target domain data is used for training.

Understanding the driving mechanisms of vegetation development is critical for maintaining terrestrial ecosystem function in mountain areas, especially under the background of climate change. The Qinba Mountains (QBM), a critical north–south transition zone in China, is an environmentally fragile area that is vulnerable to climate change. It is essential to characterize how its ecological environment has changed. Currently, such a characterization remains unclear in the spatiotemporal patterns of the nonlinear effects and interactions between environmental factors and vegetation changes in the QBM. Here, we utilized the Normalized Difference Vegetation Index (NDVI), obtained from Google Earth Engine (GEE) platform, as an indicator of terrestrial ecosystem conditions. Then, we measured the spatiotemporal heterogeneity for vegetation variation in the QBM from 2003 to 2018. Specifically, the Geodetector method, a new geographically statistical method without linear assumptions, was employed to detect the interaction between vegetation and environmental driving factors. The results indicated that there is a trend of a general increase in vegetation growth amplitude (the average NDVI increased from 0.810 to 0.858). The areas with an NDVI greater than 0.8 are mainly distributed in the Qinling Mountains and the Daba Mountains, which account for more than 76.39% of the QBM area. For the entire region, the global Moran’s index of the NDVI is greater than 0.95, indicating that vegetation is highly concentrated in the spatial domain. The Geodetector identified that landform type was the primary factor in controlling vegetation changes, contributing 24.19% to the total variation, while the explanatory powers of the aridity index and the wetness index for vegetation changes were 22.49% and 21.47%, respectively. Furthermore, the interaction effects between any two factors outperformed the influence of a single environmental variable. The interaction between air temperature and the aridity index was the most significant element, contributing to 47.10% of the vegetation variation. These findings can not only improve our understanding in the interactive effects of environmental forces on vegetation change, but also be a valuable reference for ecosystem management in the QBM area, such as ecological conservation planning and the assessment of ecosystem functions.

Cirrhosis is a common endpoint in various chronic liver diseases, and often causes hepatocellular carcinoma. Studies have revealed the significant role of disulfidptosis in the occurrence and development of hepatocellular carcinoma; however, our understanding of this role is limited. Therefore, we aimed to identify potential disulfidptosis-related biomarkers for cirrhosis. We obtained the gene expression data of patients with cirrhosis from the Gene Expression Omnibus (GEO) database. Subsequently, weighted gene co-expression network analysis was performed, and the “limma” package was used to screen for differentially expressed genes (DEGs) associated with disulfidptosis. Significantly altered biological pathways were identified using Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), Gene Set Enrichment Analysis (GSEA), and Gene Set Variation Analysis (GSVA). We constructed protein–protein interaction (PPI) networks using GeneMANIA and generated receiver operating characteristic (ROC) curves to identify hub-shared genes. Additionally, we assessed the distribution of immune cell populations in cirrhotic and control specimens using single-sample GSEA (ssGSEA) and explored their relationship with hub genes. Six hub genes ( CXCL12, COL1A1, CXCR4, COL1A2, CCR7, and CXCL8 ) were closely associated with disulfidptosis-related DEGs. Further immunohistochemical experiments confirmed the potential of CCR7, CXCL12, CXCR4, and CXCL8 as novel diagnostic biomarkers and suggested their potential as new therapeutic targets. These genes mainly promote the development of liver cirrhosis through the oxidative metabolism and cytokine pathways. Furthermore, we observed positive correlations among 23 of the 28 types of immune cells. This study highlights the potential utility of immune cell infiltration and efficient disulfidptosis-related early diagnostic biomarkers in cirrhosis, and highlights its strong useful as a therapeutic target, offering potential clinical application value.

Astragalus polysaccharide (APS) is an important bioactive component of Astragalus membranaceus which is used as an anti-diabetes herb in traditional Chinese medicine. The objective of this study was to investigate the effects and mechanisms of APS on insulin-sensitizing of adipocytes. Mouse 3T3-L1 preadipocytes were used as a model. The results showed that APS increased preadipocytes proliferation in a dose dependent manner, and 0.1 μg/mL APS sufficiently increased Proliferating Cell Nuclear Antigen (PCNA) content (p < 0.01). Moreover, APS enhanced intracellular lipid accumulation and mRNA expression of proliferator-activated receptor γ (PPARγ, p < 0.01), CCAAT/enhancer binding protein α (C/EBPα, p < 0.01) and fatty acid binding protein (aP2, p < 0.01). As expected, corresponding protein contents were elevated. Importantly, APS increased 2-(N-(7-Nitrobenz-2-oxa-1,3-diazol-4-yl)Amino)-2-Deoxyglucose (2-NBDG) uptake (p < 0.01). Meanwhile, both mRNA and protein content of glucose transporter 4 (Glut4) were elevated by APS (p < 0.01). The APS treatment enhanced tyrosine phosphorylation of insulin receptor substrate 1 (IRS1, p < 0.05) and phosphor-Akt content (p < 0.01). Besides, phosphorylated AMP-activated protein kinase (AMPK) content was increased in the APS treated cells (p < 0.01). Taken together, APS improved insulin sensitivity by enhancing glucose uptake, possibly through AMPK activation. These results suggested that APS might be a therapeutic candidate for insulin resistance.

Because an open-pit mine is an open operating environment, mining and stripping equipment inevitably pollutes the environment to some extent during the operation process. Therefore, the current dust concentration monitoring methods and technologies are relatively simple, and the dust distribution characteristics and diffusion laws of each production link in open-pit mines are not clear. Taking the transportation link of the Anjialing open-pit mine as the research object, a set of integrated monitoring methods combining ground and space and fixed and mobile technology is proposed. First, aiming at the complex transportation system of an open-pit mine, a physical model of dump truck movement in an open pit mine was constructed. On the basis of the principle of gas‒solid two-phase flow, a starting model of dust particles under impact and a dynamic model of dust particles under wind pressure were constructed, and the dusting, movement and diffusion mechanisms of dust particles were defined. Second, in view of the missing data and noise caused by the stability of the acquisition system and the coverage of the mining area signal, a method of dust concentration prediction based on time series and sample data correction processing of background noise was proposed. To fully restore and characterize the characteristics of the induction and influence of mining trucks on dust particles under different environmental conditions, a simulation method based on fluid mechanics, which effectively reveals the characteristics of air flow field migration and dust diffusion during the driving of mining trucks, was . Finally, on the basis of field monitoring data and numerical simulation data, the law of dust diffusion and migration of mining trucks under different speed conditions was revealed, and the characteristics of dust diffusion and migration prediction models were constructed. The relative error of the model prediction accuracy was 1.2% ~ 10.6%. The mean square error in the z-axis direction was 13.8%, whereas in the x-axis direction, it was 52.0%. The research results provide data support and a theoretical basis for follow-up dust concentration prediction in open-pit mines and the formulation of dust control programs.

Dust pollution is one of the most severe environmental issues in open pit mines, hindering green mining development. Open pit mine dust has characteristics of multiple dust-generating points, is irregular, influenced by climatic conditions, and has a high degree of distribution with a wide dispersion range in three dimensions. Consequently, evaluating the quantity of dust dispersion and controlling environmental pollution are crucial for supporting green mining. In this paper, dust monitoring above the open pit mine was carried out with an unmanned aerial vehicle (UAV) on board. The dust distribution patterns above the open pit mine were studied in different vertical and horizontal directions at different heights. The results show that the temperature changes less in the morning and more at noon in winter. At the same time, the isothermal layer becomes thinner and thinner as the temperature rises, which makes it easy for dust to spread. The horizontal dust is mainly concentrated at 1300 and 1550 elevations. The dust concentration is polarized at 1350–1450 elevation. The most serious exceedance is at 1400 elevation, with TSP (the concentration of total suspended particulate), PM10 (particulates with aerodynamic diameter < 10 μm), and PM2.5 (particulates with aerodynamic diameter < 2.5 μm) accounting for 188.8%, 139.5%, and 113.8%, respectively. The height is 1350–1450 elevation. Dust monitoring technology carried out by UAV can be applied to the study of dust distribution in the mining field, and the research results can provide reference for other open pit mines. It can also provide a basis for law enforcement part to carry out law enforcement, which has expanded and wide practical application value.

The coronavirus disease 2019 (COVID-19) pandemic, along with the implementation of public health and social measures (PHSMs), have markedly reshaped infectious disease transmission dynamics. We analysed the impact of PHSMs on 24 notifiable infectious diseases (NIDs) in the Chinese mainland, using time series models to forecast transmission trends without PHSMs or pandemic. Our findings revealed distinct seasonal patterns in NID incidence, with respiratory diseases showing the greatest response to PHSMs, while bloodborne and sexually transmitted diseases responded more moderately. 8 NIDs were identified as susceptible to PHSMs, including hand, foot, and mouth disease, dengue fever, rubella, scarlet fever, pertussis, mumps, malaria, and Japanese encephalitis. The termination of PHSMs did not cause NIDs resurgence immediately, except for pertussis, which experienced its highest peak in December 2023 since January 2008. Our findings highlight the varied impact of PHSMs on different NIDs and the importance of sustainable, long-term strategies, like vaccine development. Public health and social measures for COVID-19 also impacted the incidence of other infectious diseases. In this study, the authors characterise the impacts of these measures on 24 notifiable infectious diseases in China until December 2023.

Atrial fibrillation (AF) is a common arrhythmia often treated with cryoballoon ablation. The impact of Metabolic-associated fatty liver disease (MASLD), a condition newly defined by a fatty liver index ≥ 60, on AF recurrence post-ablation is unclear. We analyzed 303 patients undergoing cryoballoon ablation for AF. Cox proportional hazards models were used to assess the relationship between MASLD and AF recurrence. Paroxysmal atrial fibrillation was present in 61.1% of patients and 63% were male. Among the patients, 23.4% had MASLD. These patients exhibited larger left atrial diameter and left ventricular end-diastolic dimension. During a median follow-up of 14 months, AF recurrence was more frequent in MASLD patients (45.1% vs. 20.7%). MASLD independently predicted AF recurrence (HR, 2.24 [95% CI 1.35–3.74], P  = 0.002), alongside persistent AF, longer AF duration, and larger left atrial diameter. MASLD consistently demonstrated a significant association with an increased risk of AF recurrence in both paroxysmal (HR, 2.38 [95% CI, 1.08–5.23], P  = 0.031) and persistent AF (HR, 2.55 [95% CI, 1.23–5.26], P  = 0.011). MASLD significantly increases the risk of AF recurrence after cryoballoon ablation, highlighting the importance of supporting targeted interventions of MASLD in the periprocedural management of AF.

The potential role of metasomatism‐induced hydrated layers, such as amphibole, in causing the mid‐lithospheric discontinuities (MLDs) has been widely debated. To determine whether amphibole is the compositional cause of the MLDs, we measured the electrical conductivity of mixtures of olivine and various proportions of amphiboles under high pressures and temperatures. Our results showed that the amphibole reacted with the olivine at >1,023–1,173 K. Comparison of the geophysical observations with the electrical structure profiles calculated from this study constrained the amphibole contents of 20%–29% in MLDs in North China and South Australia, which may induce a 2.2%–3.1% reduction in seismic velocity. Plain Language Summary Whether amphibole is the contributing component of mid‐lithospheric discontinuities (MLDs) has been widely debated. We measured the conductivity of olivine–amphibole mixtures with various proportions at 3.0 GPa and 573–1,273 K. We found that the amphibole decomposed at 1,023–1,173 K, which is colder than those of most MLDs. The high conductivity in North China and South Australia indicated the amphibole contents of 20%–29%, resulting in a 2.2%–3.1% reduction in velocity. Thus, amphibole decomposition may be one of the potential contributors to the simultaneously low velocity and high conductivity anomalies in the MLDs in young tectonic settings. Key Points Electrical conductivities of the mixtures of olivine and amphibole with different compositions were measured at 3.0 GPa and 573–1,273 K Conductivities of olivine‐amphibole aggregates were mainly controlled by iron content and fluid before and after breakdown, respectively Dehydration of 5%–10% amphibole might produce high‐conductivity anomalies relevant to mid‐lithospheric discontinuities

Objectives The study aims to assess the effect of baseline glycated hemoglobin (HbA1c) levels on atrial fibrillation (AF) recurrence following cryoballoon ablation in patients with and without diabetes. Methods Consecutive AF patients receiving first cryoballoon ablation between April 2018 and April 2021 were included. AF recurrence and other clinical outcomes were recorded for a minimum of 12 months post-ablation, with regular assessments at 3, 6, and 12 months, followed by annual check-ups. The primary outcome was AF recurrence after ablation at longest follow-up. Multivariate Cox proportional hazards regression models were utilized to calculate the hazard ratio (HR) and 95% CI per standard deviation (SD) increase of baseline HbA1c level. Results 335 patients were included in the analysis. The mean age was 61.7 years, 61.8% were male. 12.8% had type 2 diabetes, and 81.7% of patients had paroxysmal AF. The median level of HbA1c was 5.3%, and the mean CHA 2 DS 2 -VAS c score was 1.8. All cryoballoon ablation procedures, utilizing a 28-mm balloon, achieved successful pulmonary vein isolation. Over a median follow-up of 18 months, 105 patients (31.3%) experienced AF recurrence. In multivariate Cox proportional hazards analysis, a higher HbA1c level, persistent AF (HR 1.91, 95% CI 1.08 to 3.39, P  = 0.026), alcohol consumption (HR 2.67, 95% CI 1.33 to 5.37, P  = 0.006), and Nadir RSPV (HR 1.04, 95% CI 1.00 to 1.08, P  = 0.005) were significant predictors of AF recurrence. Per-SD increase of HbA1c was associated with a 1.75-fold increase risk of AF recurrence (HR 1.75, 95% CI 1.39 to 2.21, P  < 0.001). Subgroup analysis revealed that a higher HbA1c level was associated with a higher risk of AF recurrence in patients with and without diabetes, and in patients with paroxysmal and persistent AF. Conclusion Baseline HbA1c level was an independent predictor of AF recurrence following cryoablation, both in patients with and without diabetes.