Generating Subsurface Earth Models using Discrete Representation Learning and Deep Autoregressive Network

Subsurface earth models (referred to as geo-models) are crucial for characterizing complex subsurface systems. Multiple-point statistics are commonly used to generate geo-models. In this paper, a deep-learning-based generative method is developed as an alternative to the traditional Geomodel generation procedure. The generative method comprises two deep-learning models, namely the hierarchical vector-quantized variational autoencoder (VQ-VAE-2) and PixelSNAIL autoregressive model. Based on the principle of neural discrete representation learning, the VQ-VAE-2 learns to massively compress the Geomodels to extract the low-dimensional, discrete latent representation corresponding to each Geomodel. Following that, PixelSNAIL uses the deep autoregressive network to learn the prior distribution of the latent codes. For the purpose of Geomodel generation, PixelSNAIL samples from the newly learned prior distribution of latent codes, and then the decoder of the VQ-VAE-2 converts the newly sampled latent code to a newly constructed geo-model. PixelSNAIL can be used for unconditional or conditional geo-model generation. In an unconditional generation, the generative workflow generates an ensemble of geo-models without any constraint. On the other hand, in the conditional geo-model generation, the generative workflow generates an ensemble of geo-models similar to a user-defined source image, which ultimately facilitates the control and manipulation of the generated geo-models. To better construct the fluvial channels in the geo-models, the perceptual loss is implemented in the VQ-VAE-2 model instead of the traditional mean squared error loss. At a specific compression ratio, the quality of multi-attribute geo-model generation is better than that of single-attribute geo-model generation

Characterization and health risk assessment of airborne pollutants in commercial restaurants in northwestern China: Under a low ventilation condition in wintertime

Impacts on indoor air quality of dining areas from cooking activities were investigated in eight categories of commercial restaurants including Szechwan Hotpot, Hunan, Shaanxi Noodle, Chinese Barbecue, Chinese Vegetarian, Korean Barbecue, Italian, and Indian, in Northwestern China during December 2011 to January 2012. Chemical characterization and health risk assessment for airborne carbonyls, and particulate-bound polycyclic aromatic hydrocarbons (PAHs) and heavy metals were conducted under low ventilation conditions in wintertime. The highest total quantified carbonyls (Sigma(carbonyls)) concentration of 313.6 mu g m(-3) was found in the Chinese Barbecue, followed by the Szechwan Hotpot (222.6 mu g m(-3)) and Indian (221.9 mu g m(-3)) restaurants. However, the highest Sigma(carbonyls) per capita was found at the Indian restaurant (4500 mu g capita(-1)), suggesting that cooking methods such as stir-fly and bake for spices ingredients released more carbonyls from thermal cooking processes. Formaldehyde, acetaldehyde, and acetone were the three most abundant species, totally accounting for >60% of mass concentrations of the Sigma(carbonyls). Phenanthrene, chrysene, and benzo[a]anthracene were the three most abundant PAHs. Low molecular weight fraction (Sigma PAHs(<= 178)) had the highest contributions accounting for 40.6%-65.7%, much greater than their heaver counterparts. Diagnostic PAHs ratios suggest that cooking fuel and environmental tobacco smoke (ETS) contribute to the indoor PAHs profiles. Lead was the most abundant heavy metal in all sampled restaurants. High quantity of nickel was also found in samples due to the emissions from stainless-steel made kitchen utensils and cookware and ETS. Cancer risk assessments on the toxic substances demonstrate that the working environment of dining areas were hazard to health. Formation of reactive organic species (ROS) from the cooking activities was evidenced by measurement of hydroxyl radical (center dot OH) formed from simulating particulate matter (PM) react with surrogate lung fluid. The highest center dot OH concentration of 294.4 ng m(-3) was detected in Chinese Barbecue. In addition, the elevation of the concentrations of PM and center dot OH after non-dining periods implies that the significance of formation of oxidizing-active species indoor at poor ventilation environments. (c) 2018 Elsevier B.V. All rights reserved

Nonlinear Optical Microscopy for Histology of Fresh Normal and Cancerous Pancreatic Tissues

BACKGROUND: Pancreatic cancer is a lethal disease with a 5-year survival rate of only 1-5%. The acceleration of intraoperative histological examination would be beneficial for better management of pancreatic cancer, suggesting an improved survival. Nonlinear optical methods based on two-photon excited fluorescence (TPEF) and second harmonic generation (SHG) of intrinsic optical biomarkers show the ability to visualize the morphology of fresh tissues associated with histology, which is promising for real-time intraoperative evaluation of pancreatic cancer. METHODOLOGY/PRINCIPAL FINDINGS: In order to investigate whether the nonlinear optical imaging methods have the ability to characterize pancreatic histology at cellular resolution, we studied different types of pancreatic tissues by using label-free TPEF and SHG. Compared with other routine methods for the preparation of specimens, fresh tissues without processing were found to be most suitable for nonlinear optical imaging of pancreatic tissues. The detailed morphology of the normal rat pancreas was observed and related with the standard histological images. Comparatively speaking, the preliminary images of a small number of chemical-induced pancreatic cancer tissues showed visible neoplastic differences in the morphology of cells and extracellular matrix. The subcutaneous pancreatic tumor xenografts were further observed using the nonlinear optical microscopy, showing that most cells are leucocytes at 5 days after implantation, the tumor cells begin to proliferate at 10 days after implantation, and the extracellular collagen fibers become disordered as the xenografts grow. CONCLUSIONS/SIGNIFICANCE: In this study, nonlinear optical imaging was used to characterize the morphological details of fresh pancreatic tissues for the first time. We demonstrate that it is possible to provide real-time histological evaluation of pancreatic cancer by the nonlinear optical methods, which present an opportunity for the characterization of the progress of spontaneous pancreatic cancer and further application in a non-invasive manner

Spontaneous optical fractals in linear & nonlinear systems

This thesis concerns the generation and characterisation of optical fractals. Chapter 1 presents a brief introduction to fractals and fractal dimensions, and then a review of contexts where fractal concepts have arisen in optics. These contexts are classified in terms of whether the fractal-generating mechanisms at work are linear or nonlinear.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Spontaneous optical fractals in linear & nonlinear systems

This thesis concerns the generation and characterisation of optical fractals. Chapter 1 presents a brief introduction to fractals and fractal dimensions, and then a review of contexts where fractal concepts have arisen in optics. These contexts are classified in terms of whether the fractal-generating mechanisms at work are linear or nonlinear.EThOS - Electronic Theses Online ServiceGBUnited Kingdo