Optimal selection of time functions for describing coal mining-induced dynamic subsidence at single surface point using AIC criterion

The time function method is one of the most commonly used methods for predicting surface dynamic displacements in coal mine areas. In which, the accuracy and reliability of the predicted displacements, to a large extent, depends on the selected mathematical functions for describing the “S”-typed dynamic subsidence at a single surface point (referred to as time functions). Nearly all of the existing studies primarily improve or introduce “S”-shaped growth functions with a single object to minimizing the fitting residuals between the in-situ monitored and the model-fitted subsidence. Such a strategy, however, would result in “overfitting” (or over-parameterization), thereby increasing the complexity of the constructed time function model and the difficulty of model parameter inversion. To this end, the optimal selection of time functions was analyzed in this paper using two indicators of fitting residual and model complexity, rather than the former one in existing studies. More specifically, time-series subsidence observations at 103 field points in seven coal mining areas with different geological mining conditions were selected to be observation samples for ensuring the applicability of the optimal time function. Then, 12 common “S-shaped” growth models were chosen to candidates, and the theoretical analysis and Akaike information criterion (AIC) were further used to analyze the optimal selection of time function from the chosen 12 “S”-shaped models. The results show that: ① Among the 12 selected models, the mean mis-fitting error of the five four-parameter models is about 3.51 cm, which is obviously smaller than that of the two-parameter Knothe model (14.10 cm), but just slightly smaller than the six three-parameter models (4.78 cm); ② In the view of making a trade-off between fitting residuals and model complexity (assessing by the AIC), the AICs of the six three-parameter models are smaller than those of the four-parameter and two-parameter models.This indicates that the three-parameters models are preferrable to describe the temporal evolution of subsidence at a single point, and the four-parameter and two-parameters models may be over-fitted and under-fitted, respectively; ③ Among the six selected models, the optimal selection of time function is related to the lithology of the overburden rock strata; that is, Hossfeld model, which has not been introduced into the time function method, is preferrable under soft and medium-hard overburden strata, whereas Weibull model is preferrable under hard overburden strata

Tip60 Suppresses Cholangiocarcinoma Proliferation and Metastasis via PI3k-AKT

Background/Aims: Aberrant expression of Tip60 is associated with progression in many cancers. However, the role of Tip60 in cancer progression remains contradictory. The aim of this study was to investigate the clinical significance, biological functions and underlying mechanisms of Tip60 deregulation in cholangiocarcinoma (CCA) for the first time. Methods: Quantitative real-time PCR (QRT-PCR), western blotting and immunohistochemistry staining (IHC) were carried out to measure Tip60 expression in CCA tissues and cell lines. Kaplan–Meier analysis and the log-rank test were used for survival analysis. In vitro, cell proliferation was evaluated by flow cytometry and CCK-8, colony formation, and EDU assays. Migration/ invasion was evaluated by trans-well assays. Phosphokinase array was used to confirm the dominant signal regulated by Tip60. Tumor growth and metastasis were demonstrated in vivo using a mouse model. Results: Tip60 was notably downregulated in CCA tissues, which was associated with greater tumor size, venous invasion, and TNM stage. Down-regulation of Tip60 was associated with tumor progression and poorer survival in CCA patients. In vitro and in vivo studies demonstrated that Tip60 suppressed growth and metastasis throughout the progression of CCA. We further identified the PI3K/AKT pathway as a dominant signal of Tip60 and suggested that Tip60 regulated CCA cell proliferation and metastasis via PT3K-AKT pathway. Pearson analysis revealed that PTEN was positively correlated with the Tip60 level in CCA tissues. Conclusion: Tip60, as a tumor suppressor in CCA via the PI3K/AKT pathway, might be a promising therapeutic target or prognostic marker for CCA

Analyzing the Error Pattern of InSAR-Based Mining Subsidence Estimation Caused by Neglecting Horizontal Movements

It is common to estimate underground mining-induced subsidence from interferometric synthetic aperture radar (InSAR) displacement observations by Neglecting hOrizontal moVements (NOV). Such a strategy would cause large errors in the NOV-estimated subsidence. This issue was proven and the theoretical equation of the resulting errors has been deduced before. However, the systematic analysis of the error pattern (e.g., spatial distribution) and its relationship between some critical influence factors (e.g., lithology of overlying rock strata) is lacking to date. To circumvent this, a method was first presented to assess the errors of the NOV-estimated mining subsidence in this study. Then, the error pattern and the influence factors of the NOV-estimated mining subsidence were discussed. The results suggest that the errors of the NOV-estimated mining subsidence spatially follow a “peak-to-valley” shape, with an absolute “peak-to-valley angle” of 5–15°. In addition, for the same underground mining geometry, the error magnitudes of the NOV-estimated mining subsidence under hard lithology of overlying rock strata are smaller than those under soft lithology, and vice versa. These results would be beneficial to guide the scientific use of the NOV method for understanding the deformation mechanism and controlling the geohazards associated with underground mining and other similar anthropogenic activities

Analyzing the Error Pattern of InSAR-Based Mining Subsidence Estimation Caused by Neglecting Horizontal Movements

It is common to estimate underground mining-induced subsidence from interferometric synthetic aperture radar (InSAR) displacement observations by Neglecting hOrizontal moVements (NOV). Such a strategy would cause large errors in the NOV-estimated subsidence. This issue was proven and the theoretical equation of the resulting errors has been deduced before. However, the systematic analysis of the error pattern (e.g., spatial distribution) and its relationship between some critical influence factors (e.g., lithology of overlying rock strata) is lacking to date. To circumvent this, a method was first presented to assess the errors of the NOV-estimated mining subsidence in this study. Then, the error pattern and the influence factors of the NOV-estimated mining subsidence were discussed. The results suggest that the errors of the NOV-estimated mining subsidence spatially follow a “peak-to-valley” shape, with an absolute “peak-to-valley angle” of 5–15°. In addition, for the same underground mining geometry, the error magnitudes of the NOV-estimated mining subsidence under hard lithology of overlying rock strata are smaller than those under soft lithology, and vice versa. These results would be beneficial to guide the scientific use of the NOV method for understanding the deformation mechanism and controlling the geohazards associated with underground mining and other similar anthropogenic activities

Recent progress in retrieving and predicting mining-induced 3D displace-ments using InSAR

This paper firstly presents the basic principle of InSAR techniques in monitoring surface deformations. Then, the existing InSAR-based approaches for retrieving mining-induced 3D displacements are classified, and their technique features and application scopes are also analyzed. Subsequently, the research progress of InSAR-based 3D deformation prediction of mining areas is demonstrated. Finally, some potential research topics in retrieving and predicting mining-induced 3-D displacements using InSAR, such as integrating multi-source data and the analysis of mining subsidence mechanism, are demonstrated

Improving the Robustness of the MTI-Estimated Mining-Induced 3D Time-Series Displacements with a Logistic Model

The previous multi-track InSAR (MTI) method can be used to retrieve mining-induced three-dimensional (3D) surface displacements with high spatial–temporal resolution by incorporating multi-track interferometric synthetic aperture radar (InSAR) observations with a prior model. However, due to the track-by-track strategy used in the previous MTI method, no redundant observations are provided to estimate 3D displacements, causing poor robustness and further degrading the accuracy of the 3D displacement estimation. This study presents an improved MTI method to significantly improve the robustness of the 3D mining displacements derived by the previous MTI method. In this new method, a fused-track strategy, instead of the previous track-by-track one, is proposed to process the multi-track InSAR measurements by introducing a logistic model. In doing so, redundant observations are generated and further incorporated into the prior model to solve 3D displacements. The improved MTI method was tested on the Datong coal mining area, China, with Sentinel-1 InSAR datasets from three tracks. The results show that the 3D mining displacements estimated by the improved MTI method had the same spatial–temporal resolution as those estimated by the previous MTI method and about 33.5% better accuracy. The more accurate 3D displacements retrieved from the improved MTI method can offer better data for scientifically understanding the mechanism of mining deformation and assessing mining-related geohazards

Deriving Dynamic Subsidence of Coal Mining Areas Using InSAR and Logistic Model

The seasonal variation of land cover and the large deformation gradients in coal mining areas often give rise to severe temporal and geometrical decorrelation in interferometric synthetic aperture radar (InSAR) interferograms. Consequently, it is common that the available InSAR pairs do not cover the entire time period of SAR acquisitions, i.e., temporal gaps exist in the multi-temporal InSAR observations. In this case, it is very difficult to accurately estimate mining-induced dynamic subsidence using the traditional time-series InSAR techniques. In this investigation, we employ a logistic model which has been widely applied to describe mining-related dynamic subsidence, to bridge the temporal gaps in multi-temporal InSAR observations. More specifically, we first construct a functional relationship between the InSAR observations and the logistic model, and we then develop a method to estimate the model parameters of the logistic model from the InSAR observations with temporal gaps. Having obtained these model parameters, the dynamic subsidence can be estimated with the logistic model. Simulated and real data experiments in the Datong coal mining area, China, were carried out in this study, in order to test the proposed method. The results show that the maximum subsidence in the Datong coal mining area reached about 1.26 m between 1 July 2007 and 28 February 2009, and the accuracy of the estimated dynamic subsidence is about 0.017 m. Compared with the linear and cubic polynomial models of the traditional time-series InSAR techniques, the accuracy of dynamic subsidence derived by the logistic model is increased by about 50.0% and 45.2%, respectively

Pointwise Modelling and Prediction for Ground Surface Uplifts in Abandoned Coal Mines from InSAR Observations

Interferometric synthetic aperture radar (InSAR) is a useful tool for monitoring surface uplifts due to groundwater rebound in abandoned coal mines. However, InSAR-based prediction for surface uplifts has rarely been focused on so far, hindering the scientifical assessment and controlling of uplift-related geohazards in a wide area. In this study, we firstly revealed that the temporal evolution of surface uplifts caused by groundwater rebound at a surface point approximately followed an exponential distribution. Following the result, a varied cumulative distribution function (CDF) of the Weibull distribution was then used to model the temporal evolution of surface uplifts on a point-by-point basis. Finally, the parameters of the varied Weibull CDF were inverted from historical InSAR observations of surface uplifts and were forward used to predict uplift trends. Two abandoned coal mines in Beipiao city, China, were chosen to test the presented method. The results suggest that the varied Weibull CDF is able to well describe the processing of time-series uplifts, and the root mean square errors of the predicted uplifts were about 1.2 mm. The presented pointwise method predicts surface uplifts based on historical uplift observations and a mathematical function (i.e., the varied Weibull CDF), without the requirement of in situ geological and hydrological information about the focused abandoned coal mines. Therefore, it offers a new tool for predicting surface uplifts in abandoned mines, especially in case they lack in situ geological and hydrological information