The classification accuracy of training set and test set for SVM was 90.63 and 90.00%, respectively. The total accuracy for SVM was 90.48%, which was higher than that of LDA (77.78%). Comparison of the two methods shows that the performance of SVM was better than that of LDA, which implies that the SVM method is an effective tool in evaluating the risk of drugs when experimental M/P ratios have not been investigated.
Ethyl tert-butyl ether (ETBE) is an alternative fuel oxygenate that can be produced in the liquid phase by addition of ethanol to isobutene catalyzed by sulfonic acid ion exchange resins. A generalized Langmuir-Hinshelwood rate expression is formulated in terms of the liquid phase activities of the reactants that is quasi-autocatalytic due to ethanol. This microkinetic model is combined with the generalized Maxwell-Stefan equations for a detailed investigation of the influence of multicomponent mass transfer limitations inside the macropores of the heterogeneous catalyst. The model is used for revision of experimental rate data for ETBE synthesis in the literature. The analysis reveals that reverse diffusion of isobutene can occur by strong interaction with ethanol and the catalyst effectiveness factor can exceed unity.
Abstract. The aim of the present study was to investigate the incremental value of resting three-dimensional speckle-tracking echocardiography (3D-STE) in the detection of early-stage left ventricular dysfunction in patients with coronary artery disease (CAD). A total of 110 patients suspected of having CAD were recruited. All patients underwent 3D-STE and coronary artery angiography (CAG). They were divided to a CAD group and a normal group according to the results of CAG. Using 3D-STE software, the peak values of longitudinal strain (LS), circumferential strain (CS), radial strain (RS) and area strain (AS) and the time to peak value of these strains (T-LS, T-CS, T-RS and T-AS) were measured. A receiver operator characteristic curve (ROC) was used to analyze the sensitivity of these strains for the diagnosis of CAD. ROC analysis indicated that T-LS and composite indices combining the peak strain value and time to peak of LS, CS and AS have diagnostic value for the early detection of CAD; the area under the curve (AUC) values were 0.667, 0.692, 0.621 and 0.672 respectively (P<0.005). The composite index of longitudinal strain demonstrated the highest diagnostic value for CAD with 62% sensitivity and 76% specificity. These results indicate that 3D-STE has incremental value for the diagnosis of CAD in patients at rest.
Our results showed that in a Chinese population with CKD, CKD-EPI GFR, CysC GFR and CysC-Scr GFR of bias and overall accuracy of 30% were very similar. There was little advantage in adding Asian coefficient to modifying the CKD-EPI equation. CysC GFR overestimated GFR in patients with CKD stages 4 and 5.
Community detection is of great significance in understanding the structure of the network. Label propagation algorithm (LPA) is a classical and effective method, but it has the problems of randomness and instability. An improved label propagation algorithm named LPA-MNI is proposed in this study by combining the modularity function and node importance with the original LPA. LPA-MNI first identify the initial communities according to the value of modularity. Subsequently, the label propagation is used to cluster the remaining nodes that have not been assigned to initial communities. Meanwhile, node importance is used to improve the node order of label updating and the mechanism of label selecting when multiple labels are contained by the maximum number of nodes. Extensive experiments are performed on twelve real-world networks and eight groups of synthetic networks, and the results show that LPA-MNI has better accuracy, higher modularity, and more reasonable community numbers when compared with other six algorithms. In addition, LPA-MNI is shown to be more robust than the traditional LPA algorithm.
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