Metabolic grey early warning model for dam deformation based on wavelet denoising

Influenced by environment and human factors, the observed data of dam deformation consist of real deformation value and observation error (noise). The conventional GM(1,1) model based on nondenoised observation data is not very effective. In order to improve the prediction effect of conventional GM(1,1) model, wavelet threshold denoising method is used to eliminate the noise in the original data and improve the smoothness of the data sequence. Then, based on the conventional GM(1,1) model, the metabolic GM(1,1) model is established by eliminating the oldest information and adding the newest information. The application results show that the wavelet threshold denoising can obviously remove the noise from the original data. The predicted vertical displacement of the metabolic GM(1,1) model based on the denoised data has little difference with the measured value, and the predicted precision is obviously higher than that of the conventional GM (1,1) model. Therefore, the metabolic GM(1,1) model based on wavelet denoising can be used for prediction and early warning of dam deformation

The clinical significance of SNAIL, TWIST, and E-Cadherin expression in gastric mesentery tumor deposits of advanced gastric cancer

Objective: To explore the relationships among the epithelial to mesenchymal transition (EMT)-related factors (SNAIL, TWIST, and E-Cadherin) and clinicopathological parameters and gastric mesangial tumor deposits (TDs) in advanced gastric cancer (AGC) patients and their value in gastric cancer prognosis judgment. Materials and Methods: The data of 190 patients who underwent radical resection of ACG were analyzed retrospectively, including 75 cases of TDs (+) and 115 cases of TDs (-). The expression of EMT-related transforming factors Snail, Twist, and E-cadherin in the primary tumor, paracancerous normal tissues, and TDs was detected by immunohistochemistry. Results: SNAIL and TWIST were overexpressed in primary tumors and TDs, whereas E-Cadherin was down-expressed in primary tumors. SNAIL was correlated significantly with tumor differentiation, lymph node metastases, and TDs (P < 0.05); TWIST was correlated strongly with tumor location, lymph node metastases, and TDs (P < 0.05); E-Cadherin was correlated closely with tumor differentiation and lymph node metastases (P < 0.05). Kaplan-Meier curves showed that SNAIL expression was correlated with DFS (P < 0.05), and TWIST expression was correlated with OS (P < 0.05). Tumor differentiation, lymph node metastasis, and TWIST expression were prognostic-independent risk factors of AGC patients (P < 0.05). Conclusion: The occurrence and development of gastric cancer and the formation of TDs may be related to EMT, analyzing the expression of EMT-related transforming proteins may be helpful to judge the prognosis of gastric cancer

Reconstruction of Human Monte Carlo Geometry from Segmented Images

Human computational phantoms have been used extensively for scientific experimental analysis and experimental simulation. This article presented a method for human geometry reconstruction from a series of segmented images of a Chinese visible human dataset. The phantom geometry could actually describe detailed structure of an organ and could be converted into the input file of the Monte Carlo codes for dose calculation. A whole-body computational phantom of Chinese adult female has been established by FDS Team which is named Rad-HUMAN with about 28.8 billion voxel number. For being processed conveniently, different organs on images were segmented with different RGB colors and the voxels were assigned with positions of the dataset. For refinement, the positions were first sampled. Secondly, the large sums of voxels inside the organ were three-dimensional adjacent, however, there were not thoroughly mergence methods to reduce the cell amounts for the description of the organ. In this study, the voxels on the organ surface were taken into consideration of the mergence which could produce fewer cells for the organs. At the same time, an indexed based sorting algorithm was put forward for enhancing the mergence speed. Finally, the Rad-HUMAN which included a total of 46 organs and tissues was described by the cuboids into the Monte Carlo Monte Carlo Geometry for the simulation. The Monte Carlo geometry was constructed directly from the segmented images and the voxels was merged exhaustively. Each organ geometry model was constructed without ambiguity and self-crossing, its geometry information could represent the accuracy appearance and precise interior structure of the organs. The constructed geometry largely retaining the original shape of organs could easily be described into different Monte Carlo codes input file such as MCNP. Its universal property was testified and high-performance was experimentally verifie

Image based Monte Carlo Modeling for Computational Phantom

The evaluation on the effects of ionizing radiation and the risk of radiation exposure on human body has been becoming one of the most important issues for radiation protection and radiotherapy fields, which is helpful to avoid unnecessary radiation and decrease harm to human body. In order to accurately evaluate the dose on human body, it is necessary to construct more realistic computational phantom. However, manual description and verfication of the models for Monte carlo(MC)simulation are very tedious, error-prone and time-consuming. In addiation, it is difficult to locate and fix the geometry error, and difficult to describe material information and assign it to cells. MCAM (CAD/Image-based Automatic Modeling Program for Neutronics and Radiation Transport Simulation) was developed as an interface program to achieve both CAD- and image-based automatic modeling by FDS Team (Advanced Nuclear Energy Research Team, http://www.fds.org.c

Prediction Model of Residual Soil Shear Strength under Dry–Wet Cycles and Its Uncertainty

Granite residual soil is widely distributed in Southeast Fujian. Large-scale engineering construction leads to the exposure of residual soil slopes to the natural environment. Affected by seasonal climate factors, the soil of slopes experiences a dry–wet cycle for a long time. The repeated changes in water content seriously affect the shear strength of soil, and then affect the stability of the slope. In order to explore the influence of the dry–wet cycle on the shear strength of granite residual soil in Fujian, an indoor dry–wet cycle simulation test was carried out for shallow granite residual soil on a slope in Fuzhou, and the relationship between water content, dry–wet cycle times, and the shear strength index, including the cohesion and internal friction angle of the granite residual soil, was discussed. The results show that when the number of dry–wet cycles is constant, the cohesion and internal friction angle of the granite residual soil decrease with an increase in water content. The relationship between the cohesion, internal friction angle, and water content can be described using a power function. Meanwhile, the fitting parameters of the power function are also a function of the number of wet and dry cycles. The prediction formulas of the cohesion and internal friction angle considering the number of dry–wet cycles and water content are established, and then the prediction formula of shear strength is obtained. The ratio of the predicted value of shear strength to the test value shall be within ±15%. An error transfer analysis based on the point estimation method shows that the overall uncertainty of the predicted value of shear strength caused by the combined uncertainty of the predicted value of cohesion and the internal friction angle and the single-variable uncertainty of the predicted value of shear strength caused only by the uncertainty of the predicted value of either the cohesion or internal friction angle increases first and then decreases with an increase in the number of dry–wet cycles. All increase with an increasing water content. The maximum standard deviation of the proposed shear strength prediction model of granite residual soil is less than 9%