Towards Highly Accurate and Stable Face Alignment for High-Resolution Videos

In recent years, heatmap regression based models have shown their effectiveness in face alignment and pose estimation. However, Conventional Heatmap Regression (CHR) is not accurate nor stable when dealing with high-resolution facial videos, since it finds the maximum activated location in heatmaps which are generated from rounding coordinates, and thus leads to quantization errors when scaling back to the original high-resolution space. In this paper, we propose a Fractional Heatmap Regression (FHR) for high-resolution video-based face alignment. The proposed FHR can accurately estimate the fractional part according to the 2D Gaussian function by sampling three points in heatmaps. To further stabilize the landmarks among continuous video frames while maintaining the precise at the same time, we propose a novel stabilization loss that contains two terms to address time delay and non-smooth issues, respectively. Experiments on 300W, 300-VW and Talking Face datasets clearly demonstrate that the proposed method is more accurate and stable than the state-of-the-art models.Comment: Accepted to AAAI 2019. 8 pages, 7 figure

A novel gaussian particle swarms optimized particle filter algorithm for the state of charge estimation of lithium-ion batteries.

A gaussian particle swarm optimized particle filter estimation method, along with the second-order resistance-capacitance model, is proposed for the state of charge estimation of lithium-ion battery in electric vehicles. Based on the particle filter method, it exploits the strong optimality-seeking ability of the particle swarm algorithm, suppressing algorithm degradation and particle impoverishment by improving the importance distribution. This method also introduces normally distributed decay inertia weights to enhance the global search capability of the particle swarm optimization algorithm, which improves the convergence of this estimation method. As can be known from the experimental results that the proposed method has stronger robustness and higher filter efficiency with the estimation error steadily maintained within 0.89% in the constant current discharge experiment. This method is insensitive to the initial amount and distribution of particles, achieving adaptive and stable tracking in the state of charge for lithium-ion batteries

Microstructure，mechanical property and oxidation behavior of HfZrTiTaBx HEAs

The unique structural and thermal features of high-entropy alloys (HEAs) conduce to their excellent stability and mechanical properties. Recent researches have suggested that the high-entropy alloys composed of refractory metals exhibit competitive phase-stability and strength at elevated temperatures, which made them the promising candidate materials for high-temperature structural applications at even higher temperatures compared with the Ni-based superalloys. However, the alloys barely consisting of refractory metal elements are usually oxidized easily in oxidizing environment at high temperatures. This work aims to prepare a refractory HEA with both excellent mechanical properties and outstanding oxidation resistance by alloying of B element. In this study, an equimolar quaternary HfZrTiTa alloy and three kinds of HfZrTiTaBx(x=1.1, 2.3, 4.7) alloys with different amounts of B-addition were produced by vacuum arc melting technique in argon atmosphere. The structures of the prepared alloys were characterized via X-Ray diffraction and TEM. The oxidation behaviors of these alloys were investigated by differential scanning calorimeter (DSC)from 25℃ to 1300℃ in air. Their mechanical properties at room temperature and phase-stability at different annealing temperatures from 800℃ to 1600℃ were also examined. The results show that the HfZrTiTa alloy consists of a fully disordered body-centered cubic (BCC) solid solution phase due to the high mixing entropy, while the alloys with B addition have some nano particles uniformly distributed in the BCC solid solution matrix. The lattice parameters and Vicker hardness of the B-containing alloys increase with increasing B content due to the interstitial solid solution strengthening of B element and nanoprecipitation strengthening. The BCC structure of all alloy samples remains stable up to 1200℃. The quaternary HfZrTiTa alloy has a flexural strength of 2.3GPa with a typical dimple fracture morphology, indicating that the alloy shows ductile to some extent. The oxidation rates of the HfZrTiTaBx (x=1.1, 2.3, 4.7) alloys at 1300℃ were about 0.13~0.15g•mm-2•h-1, obviously lower than that of the HfZrTiTa alloy (0.454g•mm-2•h-1)

Key Technology of Real-Time Road Navigation Method Based on Intelligent Data Research

The effect of traffic flow prediction plays an important role in routing selection. Traditional traffic flow forecasting methods mainly include linear, nonlinear, neural network, and Time Series Analysis method. However, all of them have some shortcomings. This paper analyzes the existing algorithms on traffic flow prediction and characteristics of city traffic flow and proposes a road traffic flow prediction method based on transfer probability. This method first analyzes the transfer probability of upstream of the target road and then makes the prediction of the traffic flow at the next time by using the traffic flow equation. Newton Interior-Point Method is used to obtain the optimal value of parameters. Finally, it uses the proposed model to predict the traffic flow at the next time. By comparing the existing prediction methods, the proposed model has proven to have good performance. It can fast get the optimal value of parameters faster and has higher prediction accuracy, which can be used to make real-time traffic flow prediction

Brain image data processing using collaborative data workflows on Texera.

In the realm of neuroscience, mapping the three-dimensional (3D) neural circuitry and architecture of the brain is important for advancing our understanding of neural circuit organization and function. This study presents a novel pipeline that transforms mouse brain samples into detailed 3D brain models using a collaborative data analytics platform called Texera. The user-friendly Texera platform allows for effective interdisciplinary collaboration between team members in neuroscience, computer vision, and data processing. Our pipeline utilizes the tile images from a serial two-photon tomography/TissueCyte system, then stitches tile images into brain section images, and constructs 3D whole-brain image datasets. The resulting 3D data supports downstream analyses, including 3D whole-brain registration, atlas-based segmentation, cell counting, and high-resolution volumetric visualization. Using this platform, we implemented specialized optimization methods and obtained significant performance enhancement in workflow operations. We expect the neuroscience community can adopt our approach for large-scale image-based data processing and analysis

Sexually Dimorphic Adaptation of Cardiac Function: Roles of Epoxyeicosatrienoic Acid and Peroxisome Proliferator-Activated Receptors

Epoxyeicosatrienoic acids (EETs) are cardioprotective mediators metabolized by soluble epoxide hydrolase (sEH) to form corresponding diols (DHETs). As a sex-susceptible target, sEH is involved in the sexually dimorphic regulation of cardiovascular function. Thus, we hypothesized that the female sex favors EET-mediated potentiation of cardiac function via downregulation of sEH expression, followed by upregulation of peroxisome proliferator-activated receptors (PPARs). Hearts were isolated from male (M) and female (F) wild-type (WT) and sEH-KO mice, and perfused with constant flow at different preloads. Basal coronary flow required to maintain the perfusion pressure at 100 mmHg was significantly greater in females than males, and sEH-KO than WT mice. All hearts displayed a dose-dependent decrease in coronary resistance and increase in cardiac contractility, represented as developed tension in response to increases in preload. These responses were also significantly greater in females than males, and sEH-KO than WT 14,15-EEZE abolished the sex-induced (F vs. M) and transgenic model-dependent (KO vs. WT) differences in the cardiac contractility, confirming an EET-driven response. Compared with M-WT controls, F-WT hearts expressed downregulation of sEH, associated with increased EETs and reduced DHETs, a pattern comparable to that observed in sEH-KO hearts. Coincidentally, F-WT and sEH-KO hearts exhibited increased PPARα expression, but comparable expression of eNOS, PPARβ, and EET synthases. In conclusion, female-specific downregulation of sEH initiates an EET-dependent adaptation of cardiac function, characterized by increased coronary flow via reduction in vascular resistance, and promotion of cardiac contractility, a response that could be further intensified by PPARα