Robust estimation of bacterial cell count from optical density

Optical density (OD) is widely used to estimate the density of cells in liquid culture, but cannot be compared between instruments without a standardized calibration protocol and is challenging to relate to actual cell count. We address this with an interlaboratory study comparing three simple, low-cost, and highly accessible OD calibration protocols across 244 laboratories, applied to eight strains of constitutive GFP-expressing E. coli. Based on our results, we recommend calibrating OD to estimated cell count using serial dilution of silica microspheres, which produces highly precise calibration (95.5% of residuals <1.2-fold), is easily assessed for quality control, also assesses instrument effective linear range, and can be combined with fluorescence calibration to obtain units of Molecules of Equivalent Fluorescein (MEFL) per cell, allowing direct comparison and data fusion with flow cytometry measurements: in our study, fluorescence per cell measurements showed only a 1.07-fold mean difference between plate reader and flow cytometry data

Experimental study on hydrocarbon generation and expulsion characteristics of shale with different source-reservoir structures in Lucaogou Formation, Jimsar Sag, Junggar Basin

The Permian Lucaogou Formation in the Jimusar Sag in the east of the Junggar Basin is a typical continental shale oil series in China. Employing the semi-closed thermal simulation system, an experimental study on hydrocarbon generation and expulsion of shale with different source-reservoir structures was carried out to explore the efficiency and composition characteristics of hydrocarbon generation and expulsion of shale in the Permian Lucaogou Formation with different source-reservoir structures so as to provide reference for the enrichment rule of shale hydrocarbon and the fine evaluation of "sweet spots". The experimental results show that thick reservoir interbedded with thin source rock is more conducive to hydrocarbon expulsion and features the highest hydrocarbon expulsion efficiency, while thin source rock interbedded with thin reservoir features slightly lower hydrocarbon expulsion efficiency, and thick source rock interbedded with thin reservoir features the lowest hydrocarbon expulsion efficiency. When reservoir lithology is clastic rock, the hydrocarbon expulsion efficiency of thick reservoir interbedded with thin source rock, thin source rock interbedded with thin reservoir, and thick source rock interbedded with thin reservoir are 35.6%, 30.7%, and 25.6%, respectively. When reservoir lithology is carbonate rock, the hydrocarbon expulsion efficiency of these three combinations are 27.4%, 27.5%, and 12.3%, respectively. Combined with composition of expelled hydrocarbon, received hydrocarbon in reservoir, and retained hydrocarbon in source rock, it is found that received hydrocarbon in reservoir rock is mainly supplied by neighboring sources, and the farther away from source-reservoir interface, the less relevant relationship between source rock and hydrocarbon in reservoir. Hydrocarbon in reservoir is supplied by lower adjacent source rock in thick reservoir interbedded with thin source rock, and the received hydrocarbon in upper clastic reservoir is 10.7 mg/g, while received hydrocarbon in lower clastic reservoir is only 1.4 mg/g. The thick source rock interbedded with thin reservoir is mainly self-generated and self-stored, and the content of retained hydrocarbon in source rock is high, the received hydrocarbon in upper clastic reservoir is 6.0 mg/g, while retained hydrocarbon in source rock is 21.1 mg/g. Hydrocarbon in reservoir is mainly supplied by lower adjacent source rock and partly from its own source rock in thin source rock interbedded with thin reservoir. There is no significant difference between source rock and reservoir rock in the extraction family, with the content of saturated hydrocarbon in the range of 22.8%-33.0%, aromatics in the range of 6.2%-15.1%, and non-hydrocarbon and asphaltene in the range of 28.5%-41.1% and 21.0%-30.0%. Moreover, different reservoir lithology has relatively weak influence on hydrocarbon generation and expulsion efficiency, and the hydrocarbon-bearing heterogeneity is weak in thin source rock interbedded with thin reservoir. From the perspective of hydrocarbon generation and expulsion efficiency of shale with different source-reservoir structures, thick reservoir interbedded with thin source rock and thin source rock interbedded with thin reservoir are the favorable combinations for hydrocarbon exploration in the shale of the Lucaogou Formation

Hyperspectral Unmixing with Gaussian Mixture Model and Spatial Group Sparsity

In recent years, endmember variability has received much attention in the field of hyperspectral unmixing. To solve the problem caused by the inaccuracy of the endmember signature, the endmembers are usually modeled to assume followed by a statistical distribution. However, those distribution-based methods only use the spectral information alone and do not fully exploit the possible local spatial correlation. When the pixels lie on the inhomogeneous region, the abundances of the neighboring pixels will not share the same prior constraints. Thus, in this paper, to achieve better abundance estimation performance, a method based on the Gaussian mixture model (GMM) and spatial group sparsity constraint is proposed. To fully exploit the group structure, we take the superpixel segmentation (SS) as preprocessing to generate the spatial groups. Then, we use GMM to model the endmember distribution, incorporating the spatial group sparsity as a mixed-norm regularization into the objective function. Finally, under the Bayesian framework, the conditional density function leads to a standard maximum a posteriori (MAP) problem, which can be solved using generalized expectation-maximization (GEM). Experiments on simulated and real hyperspectral data demonstrate that the proposed algorithm has higher unmixing precision compared with other state-of-the-art methods

Spectral-Spatial Attention Networks for Hyperspectral Image Classification

Many deep learning models, such as convolutional neural network (CNN) and recurrent neural network (RNN), have been successfully applied to extracting deep features for hyperspectral tasks. Hyperspectral image classification allows distinguishing the characterization of land covers by utilizing their abundant information. Motivated by the attention mechanism of the human visual system, in this study, we propose a spectral-spatial attention network for hyperspectral image classification. In our method, RNN with attention can learn inner spectral correlations within a continuous spectrum, while CNN with attention is designed to focus on saliency features and spatial relevance between neighboring pixels in the spatial dimension. Experimental results demonstrate that our method can fully utilize the spectral and spatial information to obtain competitive performance

Confined Pyrolysis for Simulating Hydrocarbon Generation from Jurassic Coaly Source Rocks in the Junggar Basin, Northwest China

Several oil and gas fields have been found in which oil and gas were mainly derived from the Jurassic coaly source rocks in the Junggar Basin, northwest China. Pyrolysis experiments were performed on two coals (J23C1 and FM1C2) and one type III kerogen of mudstone (Di9S1) from Jurassic strata in the basin at two heating rates of 20 and 2 °C/h in confined systems (gold capsules). Hydrogen indices and H/C atomic ratios of the three samples J23C1, FM1C2, and Di9S1 are 83, 197, and 226 mg/g TOC, and 0.70, 0.86, and 1.01, respectively. The measured maximum oil yields for the three samples are 59.37, 175.75, and 80.75 mg/g TOC, respectively, inconsistent with hydrogen indices and H/C atomic ratios. However, the measured maximum gas yields (∑C_1–5) for the three samples are 90.69, 157.24, and 198.15 mg/g TOC, respectively, consistent with hydrogen indices and H/C atomic ratios. This result is interpreted by kerogen Di9S1 containing mainly crossed alkane moieties with both terminals attached to aromatic rings while coals J23C1 and FM1C2 contain mainly alkane moieties with only one terminal attached to an aromatic ring based on kerogen ¹³C NMR spectra and the oil yield relative to gas yield and compositions of liquid components produced in confined pyrolysis. The crossed alkane moieties were hardly released as liquid alkanes but likely further cracked into gaseous components during pyrolysis. Jurassic strata contain some effective oil source rocks which produced enough amount of oil required for oil expulsion and formation of commercial oil reservoirs in oil generative window (Ro 0.6–1.35%). The amounts of gaseous hydrocarbons generated from the Jurassic coaly source rocks are generally low in oil generative window due to low transformation ratios. Elevated maturity (Ro > 1.35%) is a critical controlling factor to the Jurassic coaly source rocks generating sufficient gaseous hydrocarbons and forming commercial gas reservoirs