Reordering Webpage Objects for Optimizing Quality-of-Experience

The quality of experience (QoE) perceived by users is a critical performance measure for Web browsing. “Above-The-Fold” (ATF) time has been recently recognized and widely used as a direct measure of user-end QoE by a number of studies. To reduce the ATF time, the existing works mainly focus on reducing the delay of networking. However, we observe that the webpage structures and content orders can also significantly affect theWeb QoE. In this paper, we propose a novel optimization framework that reorders the webpage objects to minimize the user-end ATF time. Our core idea is to first identify the webpage objects that consume the ATF time but have no impact on the page experience and then change the positions of these objects to achieve the minimum ATF time. We implement this framework and evaluate its performance with popular websites. The results show that the ATF time is greatly reduced compared with the existing works, especially for complex webpages

High-expression of the innate-immune related gene UNC93B1 predicts inferior outcomes in acute myeloid leukemia

Acute myeloid leukemia (AML) is a heterogeneous hematological malignancy with dismal prognosis. Identification of better biomarkers remained a priority to improve established stratification and guide therapeutic decisions. Therefore, we extracted the RNA sequence data and clinical characteristics of AML from The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression database (GTEx) to identify the key factors for prognosis. We found UNC93B1 was highly expressed in AML patients and significantly linked to poor clinical features (p < 0.05). We further validated the high expression of UNC93B1 in another independent AML cohort from GEO datasets (p < 0.001) and performed quantitative PCR of patient samples to confirm the overexpression of UNC93B1 in AML (p < 0.005). Moreover, we discovered high level of UNC93B1 was an independent prognostic factor for poorer outcome both in univariate analysis and multivariate regression (p < 0.001). Then we built a nomogram model based on UNC93B1 expression, age, FAB subtype and cytogenetic risk, the concordance index of which for predicting overall survival was 0.729 (p < 0.001). Time-dependent ROC analysis for predicting survival outcome at different time points by UNC93B1 showed the cumulative 2-year survival rate was 43.7%, and 5-year survival rate was 21.9%. The differentially expressed genes (DEGs) between two groups divided by UNC93B1 expression level were enriched in innate immune signaling and metabolic process pathway. Protein–protein interaction (PPI) network indicated four hub genes (S100A9, CCR1, MRC1 and CD1C) interacted with UNC93B1, three of which were also significantly linked to inferior outcome. Furthermore, we discovered high UNC93B1 tended to be infiltrated by innate immune cells, including Macrophages, Dendritic cells, Neutrophils, Eosinophils, and NK CD56dim cells. We also found UNC93B1 had a significantly positive correlation with CD14, CD68 and almost all Toll-like receptors. Finally, we revealed negatively correlated expression of UNC93B1 and BCL2 in AML and conjectured that high-UNC93B1 monocytic AML is more resistant to venetoclax. And we found high MCL-1 expression compensated for BCL-2 loss, thus, we proposed MCL-1 inhibitor might overcome the resistance of venetoclax in AML. Altogether, our findings demonstrated the utility of UNC93B1 as a powerful poor prognostic predictor and alternative therapeutic target

Improvement of Dielectric Breakdown Performance by Surface Modification in Polyethylene/TiO2 Nanocomposites

Dielectric breakdown is a significant property for the insulation system in high voltage power equipment. This paper is dedicated to the improvement of dielectric breakdown by surface-functionalized nanoparticles in low-density polyethylene (LDPE). Prior to the preparation of LDPE/TiO2 nanocomposites, the nanoparticles were surface modified by the silane coupling followed by the chemical reaction process. Results of Fourier transform infrared spectroscopy (FTIR) indicated that some polar groups and chemical bonding were introduced on the surface of TiO2 nanoparticles. A reduction of dielectric permittivity was observed at low nanoparticle loading (<2 wt%) samples, which responded to the restriction of the molecular chain in the interface region. High nanoparticle loadings (2 wt%, 5 wt%, 10 wt%) introduced an obvious relaxation polarization. The trap parameters detected by the thermally stimulated current (TSC) method indicated that the deep traps were introduced by small amounts of nanoparticles (≤2 wt%), while more shallow traps occurred in high loading (5 wt%, 10 wt%) samples. Meanwhile, the increase of breakdown strength at low loading samples were closely related to the deep traps, which was ascribed to the interface region by surface chemical modification

Enhanced flashover strength in polyethylene nanodielectrics by secondary electron emission modification

This work studies the correlation between secondary electron emission (SEE) characteristics and impulse surface flashover in polyethylene nanodielectrics both theoretically and experimentally, and illustrates the enhancement of flashover voltage in low-density polyethylene (LDPE) through incorporating Al2O3 nanoparticles. SEE characteristics play key roles in surface charging and gas desorption during surface flashover. This work demonstrates that the presence of Al2O3 nanoparticles decreases the SEE coefficient of LDPE and enhances the impact energy at the equilibrium state of surface charging. These changes can be explained by the increase of surface roughness and of surface ionization energy, and the strong interaction between nanoparticles and the polymer dielectric matrix. The surface charge and flashover voltage are calculated according to the secondary electron emission avalanche (SEEA) model, which reveals that the positive surface charges are reduced near the cathode triple point, while the presence of more nanoparticles in high loading samples enhances the gas desorption. Consequently, the surface flashover performance of LDPE/Al2O3 nanodielectrics is improved

Linking traps to dielectric breakdown through charge dynamics for polymer nanocomposites

Polymer nanocomposites can change the density and/or energy of traps, suppress the accumulation of space charges, and enhance dielectric breakdown strength. It is of interest to reveal the influencing mechanism of trap properties on the dielectric breakdown of polymer nanocomposites. Results of thermally stimulated depolarization current and surface potential decay were reviewed, showing that incorporating a small amount of nanoparticles into a polymer can increase the density and/or energy of deep traps. Then, the relation between traps and dc breakdown field of several polymer nanocomposites were analyzed. It was found that the increase in the density and energy of deep traps contributes to the improved dielectric breakdown performance. The modifications of traps by nanoparticles and surface treatments affect the charge dynamics in the bulk of polymer nanocomposites. Then, the accumulation of space charges, the distortion of electric field, and the energy gain of free carriers are regulated to improve the performance of dielectric breakdown

Unraveling the “U-Shaped” Dependence of Surface Flashover Performance on the Surface Trap Level

The effects of surface traps on surface flashover remain controversial. To clarify the relation between surface flashover and surface trap level, in this work, the surface trap level of epoxy composites was modified by nanoparticles incorporation, electron beam irradiation, and ozone treatment. Surface trap characteristics were analyzed by surface potential decay. Surface flashover voltages were measured in a vacuum for dc voltage and in SF6 for ac voltage. The “U-shaped” curve is founded to describe the relation between surface flashover voltage and surface deep trap level, surface flashover voltage first decreases and then increases with surface deep trap level. Enhancement of surface flashover voltage is attributed to reduced surface charge density, which was calculated by a double-trap flashover model. The simulation results indicate that the surface charge density on left side of “U-shaped” curve is controlled by surface shallow traps, whereas that on the right side is determined by surface deep traps. The effects of surface shallow and deep traps on surface charge accumulation and dissipation are used to demonstrate the reduced surface charges and improved surface flashover voltage for the “U-shaped” curve. The proposed “U-shaped” curve offers a promising way to improve surface flashover performance for high-voltage applications by tailoring surface trap characteristics with surface modifications

A Speedy Point Cloud Registration Method Based on Region Feature Extraction in Intelligent Driving Scene

The challenges of point cloud registration in intelligent vehicle driving lie in the large scale, complex distribution, high noise, and strong sparsity of lidar point cloud data. This paper proposes an efficient registration algorithm for large-scale outdoor road scenes by selecting the continuous distribution of key area laser point clouds as the registration point cloud. The algorithm extracts feature descriptions of the key point cloud and introduces local geometric features of the point cloud to complete rough and fine registration under constraints of key point clouds and point cloud features. The algorithm is verified through extensive experiments under multiple scenarios, with an average registration time of 0.5831 s and an average accuracy of 0.06996 m, showing significant improvement compared to other algorithms. The algorithm is also validated through real-vehicle experiments, demonstrating strong versatility, reliability, and efficiency. This research has the potential to improve environment perception capabilities of autonomous vehicles by solving the point cloud registration problem in large outdoor scenes