Search

The molecular structure of lubricating oil affects its lubrication properties, catalytic and hydrolytic stability, and anti-wear properties. Based on the idea of material genomics, researchers are trying to find the correlation between structural characteristics and functional performances of lubricating oil, but the correlation can only explore the influence weight of structural parameters on performance, it is also very important to research the influence mechanism. In this study, through quantum mechanics/molecular mechanics calculations, (i) the spatial configurations of four typical ester lubricants with different chain length structures were studied, (ii) effects of active functional groups and charge distribution on the properties of the ester lubricants were discussed, and (iii) electronic transition and molecular orbital contributions were compared. The calculated results are expected to provide considerable support for theoretical research on the anti-wear and anti-oxidation mechanisms of ester lubricants and assist the rapid design, development and application of lubricating materials.

Ultrahigh molecular weight polyethylene (UHMWPE) is suitable for tribological applications in various environments because of its advantageous characteristics, including its high‐impact strength, excellent resistance against wear and corrosion, and self‐lubricating properties. However, the tribological behavior of UHMWPE under seawater lubrication is still poorly understood. In this study, the wear mechanisms of UHMWPE in seawater environment were elucidated by examining its morphology and structural evolution during sliding friction. The tribological properties of UHMWPE were significantly affected by the sliding speed in seawater. At low sliding speeds, no long‐strip structures were observed on the worn UHMWPE surface. However, as the sliding speed was increased, prominent convex long‐strip structures appeared and became more densely distributed with time. The molecular chains in the amorphous region of UHMWPE stretched along the sliding direction under stress. In the crystalline region, molecular orientation, and lamellar slip were accompanied by molecular conformational transformations. During the initial stage of sliding friction, UHMWPE mainly exhibited adhesive wear caused by plastic deformation. Subsequently, the wear mechanism of UHMWPE gradually changed from adhesive wear to a combination of adhesive and abrasive wear, and its wear intensified over time. [ABSTRACT FROM AUTHOR]

Abstract Background Transcervical resection of adhesions (TCRA) is the standard treatment for intrauterine adhesion (IUA). Previous studies have shown that postoperative oral estrogen or an intrauterine physical barrier could reduce the recurrence of IUA by promoting the proliferation of the endometrium or inhibiting the reformation of adhesions. Our team designed an intrauterine stent that can release estrogen within the uterine cavity slowly. In this study, we aimed to investigate the efficacy and safety of the estrogen-releasing intrauterine system in preventing the recurrence of moderate to severe IUA. Methods This was a multicenter prospective randomized controlled 2-arm parallel trial that included patients who were diagnosed with moderate to severe IUA and who received TCRA. A total of 250 patients were randomly assigned, at a 1:1 ratio, to receive the intrauterine estrogen-releasing system or a Foley catheter balloon combined with oral estrogen therapy after surgery. The primary outcome was the rate of adhesion reduction in the two groups. The secondary outcomes included endometrial thickness at the ovulation period, menstrual improvement rates, and other reported adverse events during follow-up. Results The average daily drug release amount for all the tested stents was 0.21 mg/day. At 60 days postoperatively, the rate of adhesion reduction was significantly greater in the experimental group than in the control group (93.33% vs. 58.56%, p

Rutin has a variety of pharmacological activities, in order to solve the application defects caused by its poor water solubility. In this paper, rutin/hydroxypropyl-β-cyclodextrin (HPCD) inclusion complexes were prepared by solvent evaporation method and analysed for structure, solubility, antioxidant activity and stability. The analysis of the inclusion complex showed that HPCD could effectively encapsulate rutin in a molar ratio of 1:1, and its encapsulation efficiency and drug loading rate were 89.33% and 26.67%, respectively. The solubility of the inclusion complex in water was 51 times higher than that of rutin. After complexation, the crystal diffraction peaks of rutin disappeared and the temperature of the maximum weight loss increased from 266 ℃ to 318 ℃ and solid inclusion complex forms showed an irregular sheet-like structures indicating a successful complexation of rutin by HPCD. The IC50 of the inclusion complex for scavenging DPPH radicals and ABTS cationic radicals was significantly lower than that of rutin (P

Abstract Scenario‐based test methods are employed to assess the safety and performance of autonomous vehicles. The analytic hierarchy process (AHP) method is a common assessment method for determining the criticality of test scenarios. However, the AHP method is subjective and less reproducible when performed by different persons, as the elements of pairwise comparison values that are directly linked to the outcome must be assigned by the person involved. This paper proposes a novel AHP method that automatically generates pairwise comparison values by optimizing the correlation between performance metrics and risk of test scenarios by simulation. Performance metrics are defined as the minimum relative distances and corresponding relative velocities between vehicles, and the risk of the test scenario is determined by the pairwise comparison values of AHP. The novel AHP method was evaluated using a cut‐in scenario. The results showed that the minimum relative distance and the risk determined by the novel AHP method achieved a better correlation coefficient of −0.96, which is better than the conventional AHP of −0.828 and Fuzzy AHP of −0.824. These results suggest that the criticality of the test scenarios determined by the novel AHP method can more accurately reflect real‐world driving environments.

Objective In July 2022(Beijing time), the glacier survey group and mountaineering group of the China University of Geosciences (Wuhan) performed the "Second University Students' Scientific Expedition to the Yangtze River" in the Geladandong Snow Mountain area. Methods To analyse the spatial and temporal characteristics of glaciers in this region, scientific research data were combined with optical remote sensing image interpretation, InSAR deformation information extraction, LiDAR altimetry measurements, and high-precision geodetic survey data to conduct multisource remote sensing image fusion processing research. Aerial triangulation encryption, frequency domain image matching, the waveband ratio method, and visual interpretation were used to extract DOM, DSM, glacier area and number distribution information from high-resolution satellite GF1, GF6, GF7, ZY3, and Landsat 7 remote sensing images of Geladandong Snow Mountain and typical glaciers.Sentinel-1A and ICESat-2 images were used, supported by the cross-correlation offset tracking method in the SAR image space domain, to extract glacier surface velocity and elevation changes, respectively. The 3D spatial coordinates and elevation outliers of all the control points were calculated for the BDS CORS station in Qinghai Province using the Gamit/Globk double difference ionospheric combination model, real-time extended (RTX), and real-time kinematic (RTK) techniques. Results The results revealed 512 glaciers in the Geladandong Snow Mountain area, with an average annual growth rate of 3.12%, an area of 1 111.96 km2, and an average annual retreat rate of 0.63%.The average daily maximum velocity of the Jianggen (gu) Diru glacier is 0.25 cm/d, and the average annual maximum velocity is 91.25 cm/a. The maximum retreat value, accumulation value and annual change rate of Jianggen (gu) Diru glacier on the south side and north side are -74.63 m, 38.44 m, -5.29 m/a to 3.09 m/a, -39.17 m, 35.74 m, -3.02 m/a to 2.85 m/a, respectively. The precision of the regional quasigeoid refinement model and the errors at all control sites both attained mm levels. Conclusion The aforementioned findings can provide data support for subsequent research on glaciers in this region.

This research investigates precision enhancement in regional quasi-geoid refinement through ADS80 tri-linear array scanning stereoscopic imagery for aerial triangulation coupled with GNSS gravity-potential modeling. By acquiring stereoscopic imagery and analyzing triangulation accuracy using an ADS80 camera, we performed this study over the Qinghai–Tibet Plateau’s elevated, desolate terrain, collecting 593 GNSS points following high-precision stereoscopic imagery modeling. By utilizing 12 gravity satellite models, we computed geoid heights and China’s 1985 Yellow Sea elevations for 28 benchmarks and GNSS points, thereby refining the Qinghai Province Quasi-Geoid Model (QPQM) using geometric techniques. The findings reveal that POS-assisted ADS80 stereoscopic imagery yields high-precision triangulation with maximal horizontal and elevation accuracies of 0.083/0.116 cm and 0.053/0.09 cm, respectively, across five control point arrangements. The RMSE of normal heights for 1985, processed via these GNSS points, achieved decimeter precision. By applying error corrections from benchmarks to the 1985 elevation data from gravity satellites and performing weighted averaging, the precision of EGM2008, SGG-UGM-2, and SGG-UGM-1 models improved to 8.61 cm, 9.09 cm, and 9.38 cm, respectively, surpassing the QPQM by 9.22 cm to 9.99 cm. This research demonstrates that the proposed methods can significantly enhance the precision of regional quasi-geoid surfaces. Additionally, these methods offer a novel approach for rapidly establishing regional quasi-geoid models in the uninhabited areas of the Qinghai–Tibet Plateau.

AbstractAs an alpine area, surface fires significantly affect the fragile ecosystems of the Qinghai-Tibetan Plateau (QTP). However, no studies on the accuracy of any remote sensing burned area (BA) products on the QTP has not been evaluated, resulting in higher uncertainties in BA mapping. To address this, we used 56-view medium-resolution Landsat images of the QTP from 2001 to 2020 to verify the MCD64A1 and FireCCI51 products by stratified sampling. The results showed that MCD64A1 was more accurate than FireCCI51 for identifying small-scale (5 km2) BAs. Additionally, MCD64A1 was more accurate than FireCCI51 for identifying BAs in forests, FireCCI51 was more accurate than MCD64A1 for identifying BAs in grasslands, shrublands, and wetlands. These results can aid fire risk assessment in the region to improve ecosystem stewardship and inform further improvements in BA products.

Guangdong-Hong Kong-Macao Greater Bay Area (GBA) is an important space carrier for China to build a world-class city group and to participate in global competition. Since the 1980s, large-scale reclamation and cultivation activities have been carried out in order to accelerate the urbanization construction. Consequently, large area of natural shoreline, beach and muddy beach and other important coastal wetlands disappeared. Mangroves, coral reefs, seagrass beds and other important typical coastal wetland ecosystems have also been greatly damaged, and some specific areas even harder to play their normal ecological functions due to the serious damage of reclamation projects. In order to strictly control the reclamation projects, China has issued a series of relevant policies since 2016, which require to speed up the handling of the historical problems of reclamation projects and to gradually restore the degraded coastal wetlands by means of ecological protection and restoration strategies based on the concept of "natural restoration as the main and artificial restoration as the auxiliary". Based on several actual design cases in GBA, this paper discussed the ecological protection and restoration measures from three different perspectives of management, science and technology, aiming at the loss of coastline, degradation of coastal wetland function, damage of hydrodynamics and loss of biological resources caused by reclamation project. This paper can provide a reference for the overall planning and marine ecosystem management in GBA.

Rheumatoid arthritis (RA) has a high prevalence in patients with non-alcoholic fatty liver disease (NAFLD); however, the underlying mechanism is unclear. To address this, our study established a rat model with both NAFLD and RA by feeding a high-fat diet (HFD) and administering intradermal injection of Freund’s complete adjuvant (FCA) with bovine type II collagen. Collagen-induced RA (CIA) was confirmed by hind paw swelling and histological examination. The histomorphological characteristics of NAFLD were evaluated by Masson’s trichrome and hematoxylin-eosin staining. The development of NAFLD was further evaluated by measuring serum concentrations of triglyceride (TG), total cholesterol (T-CHO), alanine aminotransferase (ALT), aspartate aminotransferase (AST), and lipopolysaccharide (LPS). The results showed that HFD feeding exacerbated secondary inflammation in CIA rats, whereas FCA/bovine type II collagen injection increased serum levels of ALT, AST, TG, T-CHO, and LPS and exacerbated hepatic fibrosis in both normal and NAFLD rats. Interestingly, NAFLD + CIA significantly promoted the expression of PTRF, a caveolae structure protein involved in hepatic lipid metabolism and affecting downstream signaling of Toll-like receptor 4 (TLR4) and PI3K/Akt activation. High resolution confocal microscopy revealed increased PTRF and TLR4 co-localization in hepatic small vessels of NAFLD + CIA rats. AAV9-mediated PTRF knockdown inhibited TLR4 signaling and alleviated hepatic fibrosis in NAFLD + CIA rats. Together, these findings indicate that NAFLD combined with CIA causes synovial injury and enhances non-alcoholic fatty liver fibrosis in rats. PTRF could attenuate the symptoms of NAFLD + CIA likely by affecting TLR4/PTRF co-expression and downstream signaling.

Background and Aims: Levonorgestrel-releasing intrauterine system (LNG-IUS) is an effective and long-term treatment for adenomyosis, especially for patients who have severe dysmenorrhea symptoms but a strong desire to preserve their uterus. However, expulsion of the device for patients with an enlarged uterus remains a problem. In this study, an LNG-IUS was stitched on the posterior wall of the uterus under hysteroscopy, which can be an alternative method to this problem. Methods: 21 patients with adenomyosis who had previously been treated with the LNG-IUS and experienced expulsion for at least one time were enrolled. The fixation of the LNG-IUD on the posterior wall of the uterus was performed with a 4-0 Ethicon polypropylene non-absorbable suture through an endoscopic needle driver and a knot-pushing device. Results: During the postoperative follow-up, all patients experienced complete remission of their symptoms: a significant decrease in menstrual flow, relief of dysmenorrhea, and improvement in quality of life. No expulsion of device and other compilations were found. Conclusions: In patients with adenomyosis suffering from dysmenorrhea or heavy menstrual blood loss, suture fixation of an LNG-IUS using the hysteroscopic cold knife surgery system is a minimally invasive and effective alternative treatment for patients with an enlarged uterus and decreases the risk of LNG-IUS expulsion.

Hidden Markov models (HMMs) have been recently used for fault detection and prediction in continuous industrial processes; however, the expected maximum (EM) algorithm in the HMM has local optimality problems and cannot accurately find the fault root cause variables in complex industrial processes with high-dimensional data and strong variable coupling. To alleviate this problem, a hidden Markov model-Bayesian network (HMM-BN) hybrid model is proposed to alleviate the local optimum problem in the EM algorithm and diagnose the fault root cause variable. Firstly, the model introduces expert empirical knowledge for constructing BN to accurately diagnose the fault root cause variable. Then, the EM algorithm is improved by sequential and parallel learning to alleviate the initial sensitivity and local optimum problems. Finally, the log-likelihood estimates (LL) calculated by the improved hidden Markov model provide empirical evidence for the BN and give fault detection, prediction, and root cause variable detection results based on information about the similar increasing and decreasing patterns of LL for the training data and the online data. Combining the Tennessee Eastman (TE) process and the continuously stirred tank reactor (CSTR) process, the feasibility and effectiveness of the model are verified. The results show that the model can not only find the fault in time but also find the cause of the fault accurately.

Traditional onefold data-driven methods for fault detection in complex process industrial systems with high-dimensional, linear, nonlinear, Gaussian, and non-Gaussian coexistence often have less than satisfactory monitoring performance because only a single distribution of process variables is considered. To address this problem, a hybrid fault detection model based on PCA-KPCA-ICA-KICA-BI (Bayesian inference) is proposed, taking into account the advantages of principal component analysis (PCA), kernel principal component analysis (KPCA), independent component analysis (ICA), and kernel independent component analysis (KICA) in terms of dimensionality reduction and feature extraction. Foremost, this paper proposed a nonlinear evaluation method and divided the feature variables into Gaussian linear blocks, Gaussian nonlinear blocks, non-Gaussian linear blocks, and non-Gaussian nonlinear blocks by using the Jarque–Bera (JB) test and nonlinear discrimination method. Each division was monitored by the PCA-KPCA-ICA-KICA model, and finally the Bayesian fusion strategy proposed in this study is used to synthesize the detection results for each block. The hybrid model helps in evaluating variable features and bettering detection performance. Ultimately, the superiority of this hybrid model was verified through the Tennessee Eastman (TE) process and the Continuous Stirred Tank Reactor (CSTR) process, and the fault monitoring results showed an average accuracy of 85.91% for this hybrid model.

Qinghai Province is situated deep in inland China, on the Qinghai-Tibet plateau, and it has unique climate change characteristics. Therefore, understanding the temporal and spatial distributions of water vapor in this region can be of great significance. The present study applied global navigation satellite system (GNSS) technology to retrieve precipitable water vapor (PWV) in Qinghai and analyzed its relationship with rainfall and drought. Firstly, radiosonde (RS) data is used to verify the precision of the surface pressure (P) and temperature (T) from the fifth-generation atmosphere reanalysis data set (ERA5) of the European Centre for Medium-Range Weather Forecasts (ECMWF), as well as the zenith troposphere delay (ZTD), calculated based on the data from continuously operating reference stations (CORS) in Qinghai. Secondly, a regional atmospheric weighted mean temperature (Tm) (QH-Tm) model was developed for Qinghai based on P, T, and relative humidity, as well as the consideration of the influence of seasonal changes in Tm. Finally, the PWV of each CORS in Qinghai was calculated using the GNSS-derived ZTD and ERA5-derived meteorological data, and its relationship with rainfall and drought was evaluated. The results show that the ERA5-derived P and T have high precision, and their average root mean square (RMS), mean absolute error (MAE) and bias were 1.06/0.85/0.01 hPa and 2.98/2.42/0.03 K, respectively. The RMS, MAE and bias of GNSS-derived ZTD were 13.2 mm, 10.3 mm and −1.8 mm, respectively. The theoretical error for PWV was 1.98 mm; compared with that of RS- and ERA5-derived PWV, the actual error was 2.69 mm and 2.16 mm, respectively. In addition, the changing trend of GNSS-derived PWV was consistent with that of rainfall events, and it closely and negatively correlated with the standardized precipitation evapotranspiration index. Therefore, the PWV retrieved from GNSS data in this study offers high precision and good feasibility for practical applications; thus, it can serve as a crucial tool for investigating water vapor distribution and climate change in Qinghai.

Soil moisture (SM), an important variable in water conversion between the atmosphere and terrestrial ecosystems, plays a crucial role in ecological processes and the evolution of terrestrial ecosystems. Analyzing and exploring SM’s processes and influencing factors in different permafrost regions of the Qinghai-Tibet Plateau (QTP) can better serve the regional ecological security, disaster warning, water management, etc. However, the changes and future trends of SM on the QTP in recent decades are uncertain, and the main factors affecting SM are not fully understood. The study used SM observations, the Global Land Evapotranspiration Amsterdam Model (GLEAM) SM products, meteorological and vegetation data, Mann–Kendall test, Theil–Sen estimation, Ensemble Empirical Mode Decomposition (EEMD), and correlation methods to analyze and explore the characteristics and influencing factors of SM change in different permafrost regions of the QTP. The results show that: (1) At the pixel scale, GLEAM SM products can better reflect SM changes in the QTP in the warm season. The seasonal permafrost region is closer to the real SM than the permanent region, with a median correlation coefficient (R) of 0.738, median bias of 0.043 m3 m−3, and median unbiased root mean square errors (ubRMSE) of 0.031 m3 m−3. (2) The average SM in the QTP warm season increased at a rate of 0.573 × 10−3 m3 m−3 yr−1 over the recent 40 years, and the trend accelerated from 2005–2020. In 64.31% of the region, the soil was significantly wetted, mainly distributed in the permafrost region, which showed that the wetting rate in the dry region was faster than in the wet region. However, the wetting trend does not have a long-term continuity and has a pattern of “wetting–drying-wetting” on interannual and decadal levels, especially in the seasonal permafrost region. (3) More than 65% of the SM wetting trend on the QTP is caused by temperature, precipitation, and vegetation. However, there is apparent spatial heterogeneity in the different permafrost regions and vegetation cover conditions, and the three factors have a more substantial explanatory power for SM changes in the seasonal permafrost region. With the global climate change, the synergistic SM–Climate–Vegetation effect on the QTP tends to be more evident in the seasonal permafrost region.

Abundant evidence has illustrated that long non-coding RNA (lncRNA) plays a vital role in the regulation of tumor development and progression. Most lncRNAs have been proven to have biological and clinical significance in acute myeloid leukemia (AML), but further investigation remains necessary. In this study, we investigated lncRNA NR-104098 in AML and its specific mechanism. The microarray analysis was performed on NB4 cells. Based on the related analysis results, we identified that lncRNA NR-104098 is a suppressor gene that is significantly upregulated in AML cells. LncRNA NR-104098 could inhibit proliferation and induce differentiation in AML cells in vitro and also play main role in the mouse xenografts. Mechanically, it was confirmed that lncRNA NR-104098 may effectively inhibit EZH2 transcription by directly binding to E2F1 and recruiting E2F1 to the EZH2 promoter. In addition, ATPR can significantly increase the expression of lncRNA NR-104098, whereas knocking down NR104098 can inhibit the inhibitory effect of ATPR on the proliferation and induction differentiation of AML cells. Taken together, these results lead to deeper insight into the mechanism of ATPR-induced AML differentiation and prevent proliferation by inhibiting EZH2 on the transcriptional level.

The latest gravity survey of the gravity base network in Qinghai Province, China, was conducted with six Scintrex CG gravimeters and this gravity survey was tied to existed gravity reference stations. In this gravity network with long segments and very rugged topography, the calibration of scale factors is a time-consuming progress and its accuracy may be affected by many uncertainties, and the change in drift rates of the relative gravimeters are complex over time in this long-term survey. The reasonable calculation of scale factors and drift rates plays an important role in improving the gravity estimation accuracy. In this paper, based on the least squares, robust least squares, and Bayesian methods, various parameter calculation methods were employed to process this gravity network. The performance and practicality of each method were analyzed in terms of internal and external accuracy. The results indicated that the scale factors calibrated in the baseline field had poor applicability due to insufficient gravity difference, in this case, the scale factors estimated by the adjustment models were more accurate, which weakened the correlation between gravity differences and mutual differences. The drift rates estimated by the Bayesian method were relatively smooth over time, while drift rates estimated using symmetric observations were more practical for the gravimeter with highly variable drift. The weight constraints of observations can be optimized by the robust least squares method, the gravity values obtained by it were more consistent with absolute gravity values than those obtained by the least squares method, and the robust least squares method was recommended to process gravity data in plateau areas.