Prognostic value of N-terminal Pro–B-Type natriuretic peptide in patients with intermediate coronary lesions

BackgroundThe optimal treatment strategy for patients with coronary intermediate lesions, defined as diameter stenosis of 50–70%, remains a great challenge for cardiologists. Identification of potential biomarkers predictive of major adverse cardiovascular events (MACEs) risk may assist in risk stratification and clinical decision.MethodsA total of 1,187 patients with intermediate coronary lesions and available N-terminal pro-brain natriuretic peptide (NT-proBNP) levels were enrolled in the current study. A baseline NT-proBNP level was obtained. The primary endpoint was defined as MACEs, the composite endpoint of all-cause death and non-fatal myocardial infarction. A multivariate Cox regression model was used to explore the association between NT-proBNP level and MACE risk.ResultsThe mean age of the study cohort was 59.2 years. A total of 68 patients experienced MACE during a median follow-up of 6.1 years. Restricted cubic spline analysis delineated a linear relationship between the baseline NT-proBNP level and MACE risk. Both univariate and multivariate analyses demonstrated that an increased NT-proBNP level was associated with an increased risk of MACE [adjusted hazard ratio (HR) per doubling: 1.412, 95% confidence interval (CI): 1.022–1.952, p = 0.0365]. This association remains consistent in clinical meaningful subgroups according to age, sex, body mass index (BMI), and diabetes.ConclusionAn increased NT-proBNP level is associated with an increased risk of MACE in patients with intermediate coronary lesions and may serve as the potential biomarker for risk stratification and treatment decision guidance

The Overseeing Mother: Revisiting the Frontal-Pose Lady in the Wu Family Shrines in Second Century China

Located in present-day Jiaxiang in Shandong province, the Wu family shrines built during the second century in the Eastern Han dynasty (25–220) were among the best-known works in Chinese art history. Although for centuries scholars have exhaustively studied the pictorial programs, the frontal-pose female image situated on the second floor of the central pavilion carved at the rear wall of the shrines has remained a question. Beginning with the woman’s eyes, this article demonstrates that the image is more than a generic portrait (“hard motif ”), but rather represents “feminine overseeing from above” (“soft motif ”). This synthetic motif combines three different earlier motifs – the frontal-pose hostess enjoying entertainment, the elevated spectator, and the Queen Mother of the West. By creatively fusing the three motifs into one unity, the Jiaxiang artists lent to the frontal-pose lady a unique power: she not only dominated the center of the composition, but also, like a divine being, commanded a unified view of the surroundings on the lofty building, hence echoing the political reality of the empress mother’s “overseeing the court” in the second century during Eastern Han dynasty

Improved the Wear Resistance of Ti/Cu Multilayer Film by Nitriding

In this study, Ti/Cu multilayer film was deposited by magnetron sputtering and then nitrided at 800 and 900 °C in N2. The microstructure and wear performance were studied. The deposited Ti/Cu multilayer film mainly consisted of Ti and Cu phases. After nitriding, the film mainly consisted of Cu4Ti3, CuTi, and TiN phases, indicating the interface reaction and nitriding reaction occurring. The surface microstructure of the Ti/Cu multilayer film became denser after nitridation. The wear resistance of the Ti/Cu multilayer film improved after nitriding. After nitriding at 900 °C for 2 h, the maximum wear track depth of the multilayer film was ~0.73 μm, which is just 65% of the deposited Ti/Cu multilayer film. The wear mechanism of the Ti/Cu multilayer film before and after nitriding was abrasive and adhesive wear

Evolutionary Game Model of Integrating Health and Care Services for Elder People

With the background of aging, ensuring the deep integration of pension and medical services and effectively integrating pension resources and medical resources are hot issues that must be addressed in the current mode of integrating health and care services for older people. Thus, we use game theory to construct the utility model of resource allocation between pension and medical institutions. We apply this model to explore how pension institutions and medical institutions invest resources into the integration of health and care services, analysis of influencing factors, and conducting incentive mechanism research by using MATLAB 2016b software. Through theoretical deduction and experimental analysis, the following conclusions are drawn. First, the income distribution coefficient of pension institutions is positively correlated with the level of labor input, and its growth rate has a marginal diminishing effect on the level of labor. Second, in early investment, the income distribution coefficient of pension institutions is positively correlated with fixed asset investment regardless of the different effort coefficients between medical institutions and pension institutions. With a high income distribution coefficient, pension institutions are negatively correlated and marginally decrease. Third, in early investment, the income distribution coefficient of pension institutions is positively correlated with medical institutions’ labor input level. When the income distribution coefficient of pension institutions reaches a certain value, it is negatively correlated with the labor input level of medical institutions, thereby showing a marginal diminishing effect

Experimental Research on Bearing Characteristics of the Asphalt Pavement Containing Buried Pipeline

The bearing characteristics of the asphalt pavement structure are greatly influenced by buried pipelines. Improper treatment of buried pipelines would cause early damage to pavement structure. By the digital speckle correlation method (DSCM), the experimental research on bearing characteristics of the asphalt pavement containing buried pipe was carried out. The mechanical characteristics of the asphalt pavement structure are studied under four different pipeline burial conditions. The vertical displacement and strain values of each layer of the asphalt pavement structure are obtained under four operating conditions. The results showed that (1) the digital speckle observation test method can accurately obtain the displacement and strain values of each layer of asphalt pavement structure containing buried pipeline, and the application effect is good. Compared with the traditional contact strain measurement method, this method is simple and accurate and can provide effective analysis data for experimental research. (2) There exists an interlayer effect of the asphalt pavement structure. The vertical displacement value and the strain value are discontinuities and can suddenly change between two adjacent layers. At the same time, the vertical strain and the shear strain concentration phenomenon appear at the bottom of each layer, especially at the bottom of the upper layer and the subbase layer of asphalt. (3) Affected by the buried pipelines, the vertical displacement value of the asphalt pavement structure reduces, and the tensile and shear strain values of asphalt pavement structure increase. The subbase layer of asphalt is most affected by the buried pipelines, which accelerated the destruction of the asphalt pavement structure

H3PMo12O40 Immobilized on Amine Functionalized SBA-15 as a Catalyst for Aldose Epimerization

In this work various amount of phosphomolybdic acid (PMo) were immobilized on amine functionalized SBA-15 and used as heterogeneous catalysts in the epimerization of glucose in aqueous solution. 13.3PMo/NH2-SBA-15 exhibited the best catalytic performance with a glucose conversion of 34.8% and mannose selectivity of 85.6% within two hours at 120 °C. The activation energy of 80.1 ± 0.1 kJ·mol−1 was lower than that of 96 kJ·mol−1 over the homogeneous H3PMo12O40 catalyst. The catalytic activities of 13.3PMo/NH2-SBA-15 for the transformation of some other aldoses including mannose, arabinose and xylose were also investigated

Studies on Nanocrystalline TiN Coatings Prepared by Reactive Plasma Spraying

Titanium nitride (TiN) coatings with nanostructure were prepared on the surface of 45 steel (Fe-0.45%C) via reactive plasma spraying (denoted as RPS) Ti powders using spraying gun with self-made reactive chamber. The microstructural characterization, phases constitute, grain size, microhardness, and wear resistance of TiN coatings were systematically investigated. The grain size was obtained through calculation using the Scherrer formula and observed by TEM. The results of X-ray diffraction and electron diffraction indicated that the TiN is main phase of the TiN coating. The forming mechanism of the nano-TiN was characterized by analyzing the SEM morphologies of surface of TiN coating and TiN drops sprayed on the surface of glass, and observing the temperature and velocity of plasma jet using Spray Watch. The tribological properties of the coating under nonlubricated condition were tested and compared with those of the AISI M2 high-speed steel and Al2O3 coating. The results have shown that the RPS TiN coating presents better wear resistance than the M2 high-speed steel and Al2O3 coating under nonlubricated condition. The microhardness of the cross-section and longitudinal section of the TiN coating was tested. The highest hardness of the cross-section of TiN coating is 1735.43HV100 g

Inter-Comparison of Four Models for Detecting Forest Fire Disturbance from MOD13A2 Time Series

Many models for change point detection from time series remote sensing images have been developed to date. For forest ecosystems, fire disturbance detection models have always been an important topic. However, due to a lack of benchmark datasets, it is difficult to determine which model is appropriate. Therefore, we collected and generated a benchmark dataset specifically for forest fire disturbance detection, named CUG-FFireMCD1. The CUG-FFireMCD1 contains a total of 132 pieces of MODIS MOD13A2 time series, and each time series contains at least one fire disturbance. The occurrence time for a forest fire disturbance was determined using the National Cryosphere DesertDataCenter(NCDC) website, and the precise latitude and longitude coordinates were determined using the FireCCI51 dataset. In addition, we selected four commonly used time series change detection models and validate the advantages and limitations of the four models through dataset analysis. Finally, we use the detection results of the models and their applicable scenarios to label the additional change points. The four models we used are breaks for additive season and trend (BFAST), Prophet, continuous change detection and classification (CCDC), and Landsat-based detection of trends in disturbance and recovery (LandTrendR). The experiments show that the BFAST outperformed the other three models in forest fire disturbance detection from MOD13A2 time series, with the successful-detection-proportion rate of 96.2% with the benchmark dataset. The detection effect of the Prophet model is not as good as that of BFAST, but it also performs well, with the successful-detection-proportion rate of 87.9%. The detection results of CCDC and LandTrendR are similar, and the detection success rate is lower than that of BFAST and Prophet, but their detection results can be used as data support for labeling work. However, to apply them perfectly to MOD13A2 time series change detection, it is best to do some model adaptation. In summary, the CUG-FFireMCD1 data were verified using different types of time series change detection models, and the change points we marked are credible. The CUG-FFireMCD1 will surely provide a reliable benchmark for model optimization and the accuracy verification of remote sensing time series change detection

Remote Sensing Time Series Classification Based on Self-Attention Mechanism and Time Sequence Enhancement

Nowadays, in the field of data mining, time series data analysis is a very important and challenging subject. This is especially true for time series remote sensing classification. The classification of remote sensing images is an important source of information for land resource planning and management, rational development, and protection. Many experts and scholars have proposed various methods to classify time series data, but when these methods are applied to real remote sensing time series data, there are some deficiencies in classification accuracy. Based on previous experience and the processing methods of time series in other fields, we propose a neural network model based on a self-attention mechanism and time sequence enhancement to classify real remote sensing time series data. The model is mainly divided into five parts: (1) memory feature extraction in subsequence blocks; (2) self-attention layer among blocks; (3) time sequence enhancement; (4) spectral sequence relationship extraction; and (5) a simplified ResNet neural network. The model can simultaneously consider the three characteristics of time series local information, global information, and spectral series relationship information to realize the classification of remote sensing time series. Good experimental results have been obtained by using our model

TITANIUM CARBONITRIDE COATINGS PREPARED BY REACTIVE PLASMA SPRAYING Ti POWDERS

Titanium Carbonitride (TiCN), a new high hardness and wear-resistant material, has been applied widely in many fields. TiCN coating was first fabricated using reactive plasma spraying (RPS) technology in the reactive chamber that was filled with nitrogen and acetylene (N2 and C2H2) in this study. The microstructure and the phase composition of the coatings were analyzed by SEM and XRD. More chemical information of surface was analyzed by XPS. The Vickers microhardness of TiCN coating is 1659.11 HV100g, and the cross-section of the coating shows a conspicuous phenomenon of indentation size effect.TiCN, reactive plasma spraying, coating, microhardness