Inversion using a new low-dimensional representation of complex binary geological media based on a deep neural network

Efficient and high-fidelity prior sampling and inversion for complex geological media is still a largely unsolved challenge. Here, we use a deep neural network of the variational autoencoder type to construct a parametric low-dimensional base model parameterization of complex binary geological media. For inversion purposes, it has the attractive feature that random draws from an uncorrelated standard normal distribution yield model realizations with spatial characteristics that are in agreement with the training set. In comparison with the most commonly used parametric representations in probabilistic inversion, we find that our dimensionality reduction (DR) approach outperforms principle component analysis (PCA), optimization-PCA (OPCA) and discrete cosine transform (DCT) DR techniques for unconditional geostatistical simulation of a channelized prior model. For the considered examples, important compression ratios (200 - 500) are achieved. Given that the construction of our parameterization requires a training set of several tens of thousands of prior model realizations, our DR approach is more suited for probabilistic (or deterministic) inversion than for unconditional (or point-conditioned) geostatistical simulation. Probabilistic inversions of 2D steady-state and 3D transient hydraulic tomography data are used to demonstrate the DR-based inversion. For the 2D case study, the performance is superior compared to current state-of-the-art multiple-point statistics inversion by sequential geostatistical resampling (SGR). Inversion results for the 3D application are also encouraging

Effects of Vitexin on tumor necrosis factor (TNF)-α (A), interleukin (IL)-1β (B), IL-6 (C), and maleic dialdehyde (MDA) production (D) in lipopolysaccharide (LPS)-treated mice.

Data was expressed as means ± SEM (n = 6–10 per group). * p #p p < 0.05, versus LPS+Vitexin treated WT mice. Nrf2-/-, nuclear factor erythroid-2-related factor 2 gene knockout mice.</p

Effects of Vitexin on pulmonary histopathological analysis, lung injury score, lung permeability, and lung water content in lipopolysaccharide (LPS)-treated mice.

<p>Representative haematoxylin-eosin staining images of pulmonary section (A): a, control group (wild type (WT) mice treated with sterile phosphate-buffered saline (PBS)+vehicle); b, WT mice treated with PBS+Vitexin; c, nuclear factor erythroid-2-related factor 2 (Nrf2) gene knockout (Nrf2-/-) mice treated with LPS+vehicle; d, WT mice treated with LPS+vehicle; e, WT mice treated with LPS+Vitexin; f, Nrf2-/- mice treated with LPS+Vitexin. All photographs were taken at 100×magnification. Lung injury score (B). Protein concentrations in bronchoalveolar lavage fluid (BALF) (C). Pulmonary wet to dry (W/D) weight ratio (D). Data was expressed as means ± SEM (n = 6–10 per group). * <i>p</i> < 0.05, versus control group; ^#<i>p</i> < 0.05, versus LPS+vehicle group; ** <i>p</i> < 0.05, versus LPS+Vitexin treated WT mice.</p

Vitexin attenuates lipopolysaccharide-induced acute lung injury by controlling the Nrf2 pathway

<div><p>Background</p><p>A major feature of acute lung injury (ALI) is excessive inflammation in the lung. Vitexin is an active component from medicinal plants which has antioxidant and anti-inflammatory activities. Oxidative stress and inflammation play important roles in the pathophysiological processes in ALI. In the current study, we investigate the effect and potential mechanisms of Vitexin on lipopolysaccharide (LPS)-induced ALI.</p><p>Methods</p><p>ALI was induced by LPS intratracheal instillation in C57BL/6 wild-type mice and Nrf2 gene knocked down (Nrf2-/-) mice. One hour before LPS challenge, Vitexin or vehicle intraperitoneal injection was performed. Bronchoalveolar lavage fluid and lung tissues were examined for lung inflammation and injury at 24 h after LPS challenge.</p><p>Results</p><p>Our animal study’s results showed that LPS-induced recruitment of neutrophils and elevation of proinflammatory cytokine levels were attenuated by Vitexin treatment. Vitexin decreased lung edema and alveolar protein content. Moreover, Vitexin activated nuclear factor erythroid-2-related factor 2 (Nrf2), and increased the activity of its target gene heme oxygenase (HO)-1. The LPS-induced reactive oxygen species were inhibited by Vitexin. In addition, the activation of the nucleotide-binding domain and leucine-rich repeat PYD-containing protein 3 (NLRP3) inflammasome was suppressed by Vitexin. However, these effects of Vitexin were abolished in the Nrf2-/- mice. Our cell studies showed that Vitexin enhanced the expression of Nrf2 and HO-1 activity. Moreover, reactive oxygen species (ROS) and IL-1β productions were reduced in Vitexin-treated cells. However, knockdown of Nrf2 by siRNA in RAW cells reversed the benefit of Vitexin.</p><p>Conclusions</p><p>Vitexin suppresses LPS-induced ALI by controlling Nrf2 pathway.</p></div

Effects of Vitexin on cell viability (A), the expressions of nuclear factor erythroid-2-related factor 2 (Nrf2) (B), heme oxygenase (HO)-1 activity (C), reactive oxygen species (ROS) levels (D), and interleukin (IL)-1β levels (E) in lipopolysaccharide (LPS)-activated RAW cells.

<p>TBP, TATA box binding protein. Data was expressed as means ± SEM of three independent experiments. * <i>p</i> < 0.05.</p

Effects of Vitexin on nuclear factor erythroid-2-related factor 2 (Nrf2) activity (A), heme oxygenase (HO)-1 activity (B), and the nucleotide-binding domain and leucine-rich repeat PYD-containing protein 3 (NLRP3) inflammasome (C) in lipopolysaccharide (LPS)-treated mice.

<p>Data was expressed as means ± SEM (n = 6–10 per group). * <i>p</i> < 0.05, versus control group (wild type (WT) mice treated with PBS+vehicle); ^#<i>p</i> < 0.05, versus LPS+vehicle group; ** <i>p</i> < 0.05, versus LPS+Vitexin treated WT mice. Nrf2-/-, Nrf2 gene knockout mice.</p

Goodness of fit test table of the number of vehicle-bicycle conflicts.

Goodness of fit test table of the number of vehicle-bicycle conflicts.</p

Spearman correlation analysis.

In order to further study the expansion characteristics of left-turning non-motorized vehicles at intersections and the relationship between expansion characteristics and vehicle-bicycle conflicts, the trajectory point data of left-turning non-motorized vehicles are extracted using video trajectory tracking technology, and construct the cubic curve expansion envelope equation with the highest fitting degree. For the purpose of quantifying the expansion degree of non-motor vehicles after starting, two intersections in Guangxi Zhuang Autonomous Region were selected for case analysis, and the numerical range of expansion degree of the intersection with a left-turn waiting area and the intersection without a left-turn waiting area was obtained. Study the mathematical relationship between the expansion degree and its influencing factors, and establish the multivariate nonlinear regression equation between the expansion degree and the left-turn non-motorized vehicle flow, the number of parallel non-motorized vehicles, and the left-turn green light time. Analyze the vehicle-bicycle conflicts caused by the expansion of left-turning non-motorized vehicles, determine the essential factors affecting the number of non-motorized vehicles, and establish the multiple linear regression equation between the number of non-motorized vehicles and the number of left-turning non-motorized vehicles, the expansion degree, and the number of parallel non-motorized vehicles, the results show that the model has high accuracy. By analyzing the expansion characteristics of left-turning non-motorized vehicles at intersections, the relationship between different influencing factors and the expansion degree is obtained. Then the vehicle-bicycle conflicts under the influence of expansion characteristics is analyzed, providing theoretical ideas for improving traffic efficiency and optimizing traffic organization at intersections.</div

Survey location characteristic parameters.

In order to further study the expansion characteristics of left-turning non-motorized vehicles at intersections and the relationship between expansion characteristics and vehicle-bicycle conflicts, the trajectory point data of left-turning non-motorized vehicles are extracted using video trajectory tracking technology, and construct the cubic curve expansion envelope equation with the highest fitting degree. For the purpose of quantifying the expansion degree of non-motor vehicles after starting, two intersections in Guangxi Zhuang Autonomous Region were selected for case analysis, and the numerical range of expansion degree of the intersection with a left-turn waiting area and the intersection without a left-turn waiting area was obtained. Study the mathematical relationship between the expansion degree and its influencing factors, and establish the multivariate nonlinear regression equation between the expansion degree and the left-turn non-motorized vehicle flow, the number of parallel non-motorized vehicles, and the left-turn green light time. Analyze the vehicle-bicycle conflicts caused by the expansion of left-turning non-motorized vehicles, determine the essential factors affecting the number of non-motorized vehicles, and establish the multiple linear regression equation between the number of non-motorized vehicles and the number of left-turning non-motorized vehicles, the expansion degree, and the number of parallel non-motorized vehicles, the results show that the model has high accuracy. By analyzing the expansion characteristics of left-turning non-motorized vehicles at intersections, the relationship between different influencing factors and the expansion degree is obtained. Then the vehicle-bicycle conflicts under the influence of expansion characteristics is analyzed, providing theoretical ideas for improving traffic efficiency and optimizing traffic organization at intersections.</div

Curve fitting diagram of D2 at the intersection of Daxuedong Road and Luban Road.

Curve fitting diagram of D2 at the intersection of Daxuedong Road and Luban Road.</p