Numerical Analysis and Prediction of Coal Mine Methane Drainage Based on Gas–Solid Coupling Model

Methane drainage using boreholes is one of the most effective means of preventing coal mine methane disasters. However, the distributions of stress and permeability around the borehole and the effective influence radius of methane drainage are not clearly known. To solve this problem, a mathematical model of gas–solid coupling of coal rock was first established in this study based on the Kozeny–Carman equation. In this model, the coal rock was considered as a fracture–porosity dual medium. Methane’s flow was seepage in the fracture system and diffused in the pore system. Second, the finite volume method was used to discretize the coupling model. The Newton–Raphson iteration and generalized minimal residual algorithm method were used to solve the nonlinear coupling equation after diffusion. Finally, Fortran language was used to simulate the process of methane drainage using a borehole. Results showed that there was respectively stress concentration on the left and right sides of the borehole. This area was associated with the lower permeability in these zones and destroyed the borehole, which is the one of the main reasons for the low efficiency of methane drainage. The relationship between the effective influence radius and the drainage time could be described by a power function. The effective influence radius of the borehole, cumulative methane drainage volume, and residual methane content distribution obtained by simulation were well consistent with the data obtained by the actual measurements, which proves the credibility of the gas–solid coupling and solving methods. This study provides some theoretical reference for methane drainage and the solution of multi-physics field coupling model in coal mines

Acanthopagrus latus migration patterns and habitat use in Wanshan Islands, Pearl River Estuary, determined using otolith microchemical analysis

IntroductionThe waters surrounding the Wanshan Islands are important traditional fishing grounds in China, with rich habitat types. Acanthopagrus latus is an economically important species in this area; however, the distribution of its spawning grounds and habitat use patterns remain unknown.MethodsThus 100 otolith samples of A. latus were collected from three geographic areas (MW: Qi’ao Island Mangrove Water Habitat; OW: Yamen Estuary Oyster Farm Water Habitat; RW: Dong’ao-Guishan Island Reef Water Habitat), and the concentrations of Sr and Ca along the shortest axis of the vertical otolith annual or lunar rings were measured to span the entire life cycle of A. latus, with the core and edge areas corresponding to environmental characteristics at birth and capture, respectively.Results and discussionAnalysis of covariance (ANCOVA) revealed that the ratios of Sr/Ca in otolith edges of RW samples are significantly higher than those of OW and MW samples; however, both the values of Sr/Ca ratio in otolith cores collected from OW and MW are comparable with those of RW samples. Cluster analysis and non-metric multidimensional scaling (nMDS) indicated that at the juvenile stage, RW and MW individuals in the two main clusters belonged to the same cluster. There was no significant difference between the cores of the RW samples and the edges of the MW and OW samples. Therefore, the spawning area of A. latus in the Wanshan Islands is thought to have originated from low to medium-salinity waters with mangroves and oyster farm habitats in the Pearl River Estuary. A. latus from RW was found to have three distinct habitat-use patterns: 1) Marine Resident (7.2% of sampled fish) fish that remain in marine habitats for life; 2) Marine Migrant (16.4% of sampled fish) juveniles inhabit low to moderate salinity habitats and migrate to marine habitats as they grow; 3) Estuarine Visitor (76.4% of sampled fish) repeated migration between low to moderate salinity and marine habitats. This suggests widespread migration between estuarine and marine habitats throughout the ontogeny. The plasticity of this habitat use and the protection of spawning grounds should be considered in future fisheries management because A. Latus in this area has been the victim of the overexploitation of resources

Apoptosis related genes mediated molecular subtypes depict the hallmarks of the tumor microenvironment and guide immunotherapy in bladder cancer

Abstract Apoptosis has been discovered as a mechanism of cell death. The purpose of this study is to identify the diagnostic signature factors related to bladder cancer (BLCA) through apoptosis related genes (ARGs). Clinicopathological parameters and transcriptomics data of 1,440 BLCA patients were obtained from 7 datasets (GSE13507, GSE31684, GSE32548, GSE32894, GSE48075, TCGA-BLCA, and IMvigor210). We first identified prognosis-related ARGs in BLCA and used them to construct two ARGs molecular subtypes by using consensus clustering algorithm. By using principal component analysis algorithms, a ARGscore was constructed to quantify the index of individualized patient. High ARGscore correlated with progressive malignancy and poor outcomes in BLCA patients. High ARGscore was associated with higher immune cell, higher estimate scores, higher stromal scores, higher immune scores, higher immune checkpoint, and lower tumor purity, which was consistent with the “immunity tidal model theory”. Preclinically, BLCA immunotherapy cohorts confirmed patients with low ARGscore demonstrated significant therapeutic advantages and clinical benefits. These findings contribute to our understanding of ARGs and immunotherapy in BLCA. The ARGscore is a potentially useful tool to predict the prognosis and immunotherapy in BLCA

Enhancing Aboveground Biomass Estimation for Three Pinus Forests in Yunnan, SW China, Using Landsat 8

The estimation of forest aboveground biomass (AGB) using Landsat 8 operational land imagery (OLI) images has been extensively studied, but forest aboveground biomass (AGB) is often difficult to estimate accurately, in part due to the multi-level structure of forests, the heterogeneity of stands, and the diversity of tree species. In this study, a habitat dataset describing the distribution environment of forests, Landsat 8 OLI image data of spectral reflectance information, as well as a combination of the two datasets were employed to estimate the AGB of the three common pine forests (Pinus yunnanensis forests, Pinus densata forests, and Pinus kesiya forests) in Yunnan Province using a parametric model, stepwise linear regression model (SLR), and a non-parametric model, such as random forest (RF) and support vector machine (SVM). Based on the results, the following conclusions can be drawn. (1) As compared with the parametric model (SLR), the non-parametric models (RF and SVM) have a better fitting performance for estimating the AGB of the three pine forests, especially in the AGB segment of 40 to 200 Mg/ha. The non-parametric model is more sensitive to the number of data samples. In the case of the Pinus densata forest with a sample size greater than 100, RF fitting provides better fitting performance than SVM fitting, and the SVM fitting model is better suited to the AGB estimation of the Pinus yunnanensis forest with a sample size of less than 100. (2) Landsat 8 OLI images exhibit superior accuracy in estimating the AGB of the three pine forests using a single dataset. Variables, such as texture and vegetation index variables, which can reflect the comprehensive reflection information of ground objects, play a significant role in estimating AGBs, especially the texture variables. (3) By incorporating the combined dataset with characteristics of tree species distribution and ground object reflectance spectrum, the accuracy and stability of AGB estimation of the three pine forests can be improved. Moreover, the employment of a combined dataset is also effective in reducing the number of estimation errors in cases with AGB less than 100 Mg/ha or exceeding 150 Mg/ha

Reduction in Uncertainty in Forest Aboveground Biomass Estimation Using Sentinel-2 Images: A Case Study of Pinus densata Forests in Shangri-La City, China

The uncertainty from the under-estimation and over-estimation of forest aboveground biomass (AGB) is an urgent problem in optical remote sensing estimation. In order to more accurately estimate the AGB of Pinus densata forests in Shangri-La City, we mainly discuss three non-parametric models—the artificial neural network (ANN), random forests (RFs), and the quantile regression neural network (QRNN) based on 146 sample plots and Sentinel-2 images in Shangri-La City, China. Moreover, we selected the corresponding optical quartile models with the lowest mean error at each AGB segment to combine as the best QRNN (QRNNb). The results showed that: (1) for the whole biomass segment, the QRNNb has the best fitting performance compared with the ANN and RFs, the ANN has the lowest R2 (0.602) and the highest RMSE (48.180 Mg/ha), and the difference between the QRNNb and RFs is not apparent. (2) For the different biomass segments, the QRNNb has a better performance. Especially when AGB is lower than 40 Mg/ha, the QRNNb has the highest R2 of 0.961 and the lowest RMSE of 1.733 (Mg/ha). Meanwhile, when AGB is larger than 160 Mg/ha, the QRNNb has the highest R2 of 0.867 and the lowest RMSE of 18.203 Mg/ha. This indicates that the QRNNb is more robust and can improve the over-estimation and under-estimation in AGB estimation. This means that the QRNNb combined with the optimal quantile model of each biomass segment provides a method with more potential for reducing the uncertainties in AGB estimation using optical remote sensing images

The oncogenic role of microRNA-130a/301a/454 in human colorectal cancer via targeting Smad4 expression.

Transforming growth factor (TGF)-β/Smad signaling plays an important role in colon cancer development, progression and metastasis. In this study we demonstrated that the microRNA-130a/301a/454 family is up-regulated in colon cancer tissues compared to paired adjacent normal mucosa, which share the same 3'-untranslational region (3'-UTR) binding seed sequence and are predicated to target Smad4. In colorectal cancer HCT116 and SW480 cells, overexpression of miRNA-130a/301a/454 mimics enhances cell proliferation and migration, while inhibitors of these miRNAs affect cell survival. The biological function of miRNA-130a/301a/454 on colon cancer cells is likely mediated by suppression of Smad4, and the up-regulation of the miRNAs is correlated with Smad4 down-regulation in human colon cancers. Collectively, these results suggest that miRNA-130a/301a/454 are novel oncogenic miRNAs contributing to colon tumorigenesis by regulating TGF-β/Smad signaling, which may have potential application in cancer therapy

Additional file 2 of Apoptosis related genes mediated molecular subtypes depict the hallmarks of the tumor microenvironment and guide immunotherapy in bladder cancer

Additional file 2. Supplementary table 2. List of 91 apoptosis related genes used in this study