Calculation Method of Probability Integration Method Parameters Based on MIV-GP-BP Model

In order to guarantee the precision of the parameters of the probability integral method (PIM), starting from optimizing input and improving algorithm an algorithm integrating the genetic algorithm (GA) and particle swarm optimization (PSO) was put forward to optimize the prediction model of BP neural network and the mean impact value algorithm (MIV) was applied to optimize the input of BP neural network. The mean impact value algorithm (MIV) was applied to optimize the input of BP neural network. The measured data of 50 working faces were chosen as the training and testing sets to build the MIV-GP-BP model. The results showed that among the five parameters, the RMSE was between 0.0058 and 1.1575, the MaxRE of q, tanβ, b and θ was less than 5.42%, and the MeaRE was less than 2.81%. The RMSE of s/H did not exceed 0.0058, the MaxRE was less than 9.66% and the MeaRE was less than 4.31% (the parameters themselves were small). The optimized neural network model had higher prediction accuracy and stability

A Markov Process Inspired Cellular Automata Model of Road Traffic

To provide a more accurate description of the driving behaviors in vehicle queues, a namely Markov-Gap cellular automata model is proposed in this paper. It views the variation of the gap between two consequent vehicles as a Markov process whose stationary distribution corresponds to the observed distribution of practical gaps. The multiformity of this Markov process provides the model enough flexibility to describe various driving behaviors. Two examples are given to show how to specialize it for different scenarios: usually mentioned flows on freeways and start-up flows at signalized intersections. The agreement between the empirical observations and the simulation results suggests the soundness of this new approach.Comment: revised according to the helpful comments from the anonymous reviewer

Co-reductive fabrication of carbon nanodots with high quantum yield for bioimaging of bacteria

A simple and straightforward synthetic approach for carbon nanodots (C-dots) is proposed. The strategy is based on a one-step hydrothermal chemical reduction with thiourea and urea, leading to high quantum yield C-dots. The obtained C-dots are well-dispersed with a uniform size and a graphite-like structure. A synergistic reduction mechanism was investigated using Fourier transform infrared spectroscopy and X-ray photoelectron spectroscopy. The findings show that using both thiourea and urea during the one-pot synthesis enhances the luminescence of the generated C-dots. Moreover, the prepared C-dots have a high distribution of functional groups on their surface. In this work, C-dots proved to be a suitable nanomaterial for imaging of bacteria and exhibit potential for application in bioimaging thanks to their low cytotoxicity

Hyper-IL-15 suppresses metastatic and autochthonous liver cancer by promoting tumour-specific CD8+ T cell responses

Liver cancer has a very dismal prognosis due to lack of effective therapy. Here, we studied the therapeutic effects of hyper-interleukin15 (hyper-IL-15), which is composed of IL-15 and the sushi domain of the IL-15 receptor α chain, on metastatic and autochthonous liver cancers

Retrieving 3D Large Gradient Deformation Induced to Mining Subsidence Based on Fusion of Boltzmann Prediction Model and Single-Track InSAR Earth Observation Technology

Surface deformation of mining area caused by mining subsidence can be divided into three stages: the initial stage, the active stage and the decline stage. At the active stage, D-InSAR technology could be easily affected by the incoherence of large-gradient deformation, thus leading to the failure of conventional D-InSAR technology in monitoring mining subsidence.In order to solve the problem, this paper developed a 3D surface deformation prediction method of mining subsidence by integrating dynamic Boltzmann prediction model with D-InSAR. It was firstly to monitor the surface movement and deformation by D-InSAR technology during the decline stage and obtain the surface LOS deformation field data. Then, on the basis of Boltzmann model, the geometric equation between LOS deformation by D-InSAR monitored and 3D deformation was established. Next, the geometric equation was solved based on the GA theory, and the parameters of Boltzmann prior model were obtained. On the basis, the 3D deformation of mining area were obtained, proving that D-InSAR technology was effective to get 3D deformation of mining subsidence. Through simulation experiments, the effectiveness of the proposed method is verified. The surface deformation of 1613 working face in Guqiaonan coal mine was monitored by D-InSAR during the decline stage, and the LOS deformation values were obtained. The 3D deformation was obtained from the initial stage to the decline stage by using the method of DB-InSAR. The monitoring results showed that the fitting errors in the LOS deformation were mostly within 3 mm, the RMSES was ±2.37 mm, shown that the fitting accuracy was high. The RMSE of subsidence were ±120 mm. The results showed that the method of DB-InSAR has engineering application values

Stability-Level Evaluation of the Construction Site above the Goaf Based on Combination Weighting and Cloud Model

Mineral resource-based cities have formed a large number of goafs due to the long-term mining of coal. It is of great significance to make full use of the abandoned land resources above the goaf to promote the transformation and development of resource-based cities. In order to avoid the threat of surface residual deformation to the proposed construction project, it is an urgent problem to obtain the stability results of the construction site accurately. First of all, based on the principles of relevance, hierarchy, representativeness and feasibility of index selection, 10 indexes are selected to construct the stability evaluation index system. Then the subjective weight and objective weight of evaluation indexes are determined based on improved AHP, rough set and CRITIC methods, which improves the accuracy of the determination of the index weights. In addition, the membership degree of each index is determined using the cloud model. Finally, the stability grade can be obtained according to the maximum membership degree theory. The above researches are applied to evaluate the stability of the Mianluan expressway construction site, and the results show that the stability level of the study area is not uniform and that there are two states: stable and basically stable. Finally, a sensitivity analysis of the subjective weight of each index is carried out, the index stopping time has the highest sensitivity to weight (12.44%), which is far lower than the corresponding weight change rate of 100%, indicating that the determination of weight is scientific and reasonable. These things considered, the reliability of the evaluation result is indirectly verified according to the field leveling. This research can provide a reference for the effective utilization of land resources above an old goaf