Unified strength model of asphalt mixture under various loading modes

Although the rutting resistance, fatigue cracking, and the resistance to water and frost are important for the asphalt pavement, the strength of asphalt mixture is also an important factor for the asphalt mixture design. The strength of asphalt mixture is directly associated with the overall performance of asphalt mixture. As a top layer material of asphalt pavement, the strength of asphalt mixture plays an indispensable role in the top structural bearing layer. In the present design system, the strength of asphalt pavement is usually achieved via the laboratory tests. The stress states are usually different for the different laboratory approaches. Even at the same stress level, the laboratory strengths of asphalt mixture obtained are significantly different, which leads to misunderstanding of the asphalt mixtures used in asphalt pavement structure design. The arbitrariness of strength determinations affects the effectiveness of the asphalt pavement structure design in civil engineering. Therefore, in order to overcome the design deviation caused by the randomness of the laboratory strength of asphalt mixtures, in this study, the direct tension, indirect tension, and unconfined compression tests were implemented on the specimens under different loading rates. The strength model of asphalt mixture under different loading modes was established. The relationship between the strength ratio and loading rate of direct tension, indirect tension, and unconfined compression tests was adopted separately. Then, one unified strength model of asphalt mixture with different loading modes was established. The preliminary results show that the proposed unified strength model could be applied to improve the accurate degree of laboratory strength. The effectiveness of laboratory-based asphalt pavement structure design can therefore be promoted

Panax Quinquefolius Saponin of Stem and Leaf Attenuates Intermittent High Glucose-Induced Oxidative Stress Injury in Cultured Human Umbilical Vein Endothelial Cells via PI3K/Akt/GSK-3 β

Panax quinquefolius saponin of stem and leaf (PQS), the effective parts of American ginseng, is widely used in China as a folk medicine for diabetes and cardiovascular diseases treatment. In our previous studies, we have demonstrated that PQS could improve the endothelial function of type II diabetes mellitus (T2DM) rats with high glucose fluctuation. In the present study, we investigated the protective effects of PQS against intermittent high glucose-induced oxidative damage on human umbilical vein endothelial cells (HUVECs) and the role of phosphatidylinositol 3-kinase kinase (PI3K)/Akt/GSK-3β pathway involved. Our results suggested that exposure of HUVECs to a high glucose concentration for 8 days showed a great decrease in cell viability accompanied by marked MDA content increase and SOD activity decrease. Moreover, high glucose significantly reduced the phosphorylation of Akt and GSK-3β. More importantly, these effects were even more evident in intermittent high glucose condition. PQS treatment significantly attenuated intermittent high glucose-induced oxidative damage on HUVECs and meanwhile increased cell viability and phosphorylation of Akt and GSK-3β of HUVECs. Interestingly, all these reverse effects of PQS on intermittent high glucose-cultured HUVECs were inhibited by PI3K inhibitor LY294002. These findings suggest that PQS attenuates intermittent-high-glucose-induced oxidative stress injury in HUVECs by PI3K/Akt/GSK-3β pathway

PIK3C2A is a prognostic biomarker that is linked to immune infiltrates in kidney renal clear cell carcinoma

BackgroundPhosphoinositide 3-kinases (PI3Ks) are lipid enzymes that regulate a wide range of intracellular functions. In contrast to Class I and Class III PI3K, which have more detailed descriptions, Class II PI3K has only recently become the focus of functional research. PIK3C2A is a classical member of the PI3Ks class II. However, the role of PIK3C2A in cancer prognosis and progression remains unknown.MethodsThe expression pattern and prognostic significance of PIK3C2A in human malignancies were investigated using multiple datasets and scRNA-seq data. The PIK3C2A expression in renal clear cell carcinoma (KIRC) was then validated utilizing Western blot. The functional role of PIK3C2A in KIRC was assessed using combined function loss experiments with in vitro experiments. Furthermore, the correlation of PIK3C2A expression with tumor immunity was investigated in KIRC. The TCGA database was employed to investigate PIK3C2A functional networks.ResultsSignificant decrease in PIK3C2A expression in KIRC, demonstrated that it potentially influences the prognosis of diverse tumors, particularly KIRC. In addition, PIK3C2A was significantly correlated with the T stage, M stage, pathologic stage, and histologic grade of KIRC. Nomogram models were constructed and used to predict patient survival based on the results of multivariate Cox regression analysis. PIK3C2A knockdown resulted in significantly increased KIRC cell proliferation. Of note, PIK3C2A expression demonstrated a significant correlation with the infiltrating levels of primary immune cells in KIRC.ConclusionThese findings support the hypothesis that PIK3C2A is a novel biomarker for tumor progression and indicates dynamic shifts in immune infiltration in KIRC. Furthermore, aberrant PIK3C2A expression can influence the biological activity of cancer cells

Fatigue equation for asphalt mixture under low temperature and low loading frequency conditions

© 2019 Elsevier Ltd In order to reveal the thermal fatigue behavior of asphalt mixtures under low temperature conditions, the four-point bending beam tests of strength and fatigue were carried out. The asphalt mixtures are typical viscoelastic materials whose fatigue properties are significantly influenced by low loading frequency. Thus, the fatigue tests under low loading frequency were used to simulate the thermal fatigue of asphalt mixtures. Based on the nominal stress ratio (not considering the effect of loading rate on the strength value) and the real stress ratio (the strength value corresponding to the loading rate of fatigue test), the fatigue equations of asphalt mixtures under low temperature and low frequency conditions were established. The flexural strengths of the four-point bending beam tests at different loading rates at 0 °C, −10 °C and −20 °C were studied. The results show that the flexural strength of asphalt mixtures expresses a power function on the pattern of variation with the loading rates. The intersection of fatigue curve characterized by the nominal stress ratio and the abscissa axis is much larger than 1. The fatigue curve based on the nominal stress ratio cannot be extended to fatigue failure point (1,1). But the fatigue curve characterized by the real stress ratio can be extended to the strength failure point, whose fatigue life is 1. So, the behavior of strength failure and fatigue failure was integrated. The uniform characterization model of fatigue equations for asphalt mixture under low temperature and low loading frequency conditions was realized, which means that the fatigue equations and curves under different loading frequencies could be characterized by one equation and one curve. The results can provide a theoretical basis for predicting the thermal fatigue performance of asphalt mixtures under low temperature conditions more accurately

Adaptive Aggregated Attention Network for Pulmonary Nodule Classification

Lung cancer has one of the highest cancer mortality rates in the world and threatens people’s health. Timely and accurate diagnosis can greatly reduce the number of deaths. Therefore, an accurate diagnosis system is extremely important. The existing methods have achieved significant performances on lung cancer diagnosis, but they are insufficient in fine-grained representations. In this paper, we propose a novel attentive method to differentiate malignant and benign pulmonary nodules. Firstly, the residual attention network (RAN) and squeeze-and-excitation network (SEN) were utilized to extract spatial and contextual features. Secondly, a novel multi-scale attention network (MSAN) was proposed to capture multi-scale attention features automatically, and the MSAN integrated the advantages of the spatial attention mechanism and contextual attention mechanism, which are very important for capturing the salient features of nodules. Finally, the gradient boosting machine (GBM) algorithm was used to differentiate malignant and benign nodules. We conducted a series of experiments on the Lung Image Database Consortium image collection (LIDC-IDRI) database, achieving an accuracy of 91.9%, a sensitivity of 91.3%, a false positive rate of 8.0%, and an F1-score of 91.0%. The experimental results demonstrate that our proposed method outperforms the state-of-the-art methods with respect to accuracy, false positive rate, and F1-Score

Effects of loads and speeds on friction and wear properties of Cu–Ti alloys processed by combination aging treatments

The friction-wear properties of conductive elastic connectors are rarely reported but are important. The Cu–8Ti-0.4Cr-0.4 Mg, Cu–8Ti-0.4Cr-0.4Mg-0.3Al, Cu–8Ti-0.4Cr-0.4Mg-0.3Fe (in atom%) were fabricated and studied, and after treated by CR 60% + 450 °C/30min + CR 50% + 400 °C/120 min + 400 °C/1 min their hardness achieved to 447 HV, 446 HV, and 437 HV, respectively. The effects of loads and speeds on the friction and wear behavior of the studied Cu–Ti alloys were investigated by friction and wear testing machines. The wear mechanism of the alloy is mainly abrasive wear, as tested at a load of 50 N and a speed of 121 mm/s. While the wear mechanisms of the alloy are mainly oxidation wear, adhesive wear, and abrasive wear, as tested at a load of 100 N and a speed of 363 r/min. These findings bring an extended understanding of the friction and wear application of ultra-high strength conductive Cu–Ti alloys

Characterization of Asphalt Mixture Moduli under Different Stress States

Modulus testing methods under various test conditions have a large influence on modulus test results, which hinders the accurate evaluation of the stiffness of asphalt mixtures. In order to decrease the uncertainty in the stiffness characteristics of asphalt mixtures under various stress states, the traditional unconfined compression test, direct tensile test, and the synchronous test method, based on the indirect tension and four-point bending tests, were carried out for different loading frequencies. Results showed that modulus test results were highly sensitive to the shape, size, and stress state of the specimen. Additionally, existing modulus characteristics did not reduce these differences. There is a certain correlation between the elastic modulus ratio and the frequency ratio for asphalt under multiple stress states. The modulus, under multiple stress states, was processed using min⁻max normalization. Then, the standardization model for tensile and compressive characteristics of asphalt under diverse stress states was established based on the sample preparation, modulus ratio variations, and loading frequency ratio. A method for deriving other moduli from one modulus was realized. It is difficult to evaluate the stiffness performance in diverse stress states for asphalt by only using conventional compressive and tensile tests. However, taking into account the effects of stress states and loading frequencies, standardized models can be used to reduce or even eliminate these effects. The model realizes the unification of different modulus test results, and provides a theoretical, methodological, and technical basis for objectively evaluating moduli

With impatient customers and repairman multiple delay vacations of two parts parallel repairable queuing system(具有不耐烦顾客且修理工多重延误休假的两部件并联的可修排队系统)

从具有不耐烦顾客和修理工多重延误休假的角度，利用马尔可夫过程理论、稳态平衡方程、母函数方程的方法，研究两部件（服务台）并联的可修排队系统，并求出稳态平均队长，从而检测该模型的可行性

Adaptive Aggregated Attention Network for Pulmonary Nodule Classification

Lung cancer has one of the highest cancer mortality rates in the world and threatens people’s health. Timely and accurate diagnosis can greatly reduce the number of deaths. Therefore, an accurate diagnosis system is extremely important. The existing methods have achieved significant performances on lung cancer diagnosis, but they are insufficient in fine-grained representations. In this paper, we propose a novel attentive method to differentiate malignant and benign pulmonary nodules. Firstly, the residual attention network (RAN) and squeeze-and-excitation network (SEN) were utilized to extract spatial and contextual features. Secondly, a novel multi-scale attention network (MSAN) was proposed to capture multi-scale attention features automatically, and the MSAN integrated the advantages of the spatial attention mechanism and contextual attention mechanism, which are very important for capturing the salient features of nodules. Finally, the gradient boosting machine (GBM) algorithm was used to differentiate malignant and benign nodules. We conducted a series of experiments on the Lung Image Database Consortium image collection (LIDC-IDRI) database, achieving an accuracy of 91.9%, a sensitivity of 91.3%, a false positive rate of 8.0%, and an F1-score of 91.0%. The experimental results demonstrate that our proposed method outperforms the state-of-the-art methods with respect to accuracy, false positive rate, and F1-Score