Failure mechanisms and dynamic process control measures of deep buried tunnels in tectonic fracture zones under high in-situ stresses—a case study in Southwestern China

Squeezing deformation in tectonic fracture zones under high in-situ stresses has created great difficulties to deep tunnel construction in Southwestern China. This study reports an investigation on large deformation and failure mechanisms of the Wanhe tunnel on the China-Laos Railway through several field tests including the in-situ stress, loosened zone, deformation monitoring, and internal stresses of steel arches. The dynamic process control method is proposed following the combination principle of stress releasing and support resistance. Further, the dynamic process control measures including the advanced and primary supports, the deep-shallow coupled delayed grouting method, and the double steel arches method were applied on site to resist the deformation development. The results of this study indicate that the rapid growth of the tunnel deformation in the early stage was caused by the squeezing effect, and later the loosening effect led to another growing trend of the vault settlement. The dynamic process control method allows to release the deformation of the surrounding rock in the rapid growth stage. Then, it requires to control the deformation within the reserved range by reinforcing the surrounding rock and increasing the stiffness of supports in the later stage. From the feedback of monitoring results, large deformation of Wanhe tunnel was well released and effectively controlled within the deformation allowance. Thus these countermeasures based on the dynamic process control method can guarantee the construction safety of deep buried tunnels in tectonic fracture zones under high in-situ stresses

A Novel Adaptive Level Set Segmentation Method

The adaptive distance preserving level set (ADPLS) method is fast and not dependent on the initial contour for the segmentation of images with intensity inhomogeneity, but it often leads to segmentation with compromised accuracy. And the local binary fitting model (LBF) method can achieve segmentation with higher accuracy but with low speed and sensitivity to initial contour placements. In this paper, a novel and adaptive fusing level set method has been presented to combine the desirable properties of these two methods, respectively. In the proposed method, the weights of the ADPLS and LBF are automatically adjusted according to the spatial information of the image. Experimental results show that the comprehensive performance indicators, such as accuracy, speed, and stability, can be significantly improved by using this improved method

The changing face of floodplains in the Mississippi River Basin detected by a 60-year land use change dataset

Floodplains provide essential ecosystem functions, yet \u3e80% of European and North American floodplains are substantially modified. Despite floodplain changes over the past century, comprehensive, long-term land use change data within large river basin floodplains are limited. Long-term land use data can be used to quantify floodplain functions and provide spatially explicit information for management, restoration, and flood-risk mitigation. We present a comprehensive dataset quantifying floodplain land use change along the 3.3 million km2 Mississippi River Basin (MRB) covering 60 years (1941–2000) at 250-m resolution. We developed four unique products as part of this work, a(n): (i) Google Earth Engine interactive map visualization interface, (ii) Python code that runs in any internet browser, (iii) online tutorial with visualizations facilitating classroom code application, and (iv) instructional video demonstrating code application and database reproduction. Our data show that MRB’s natural floodplain ecosystems have been substantially altered to agricultural and developed land uses. These products will support MRB resilience and sustainability goals by advancing data-driven decision making on floodplain restoration, buyout, and conservation scenarios

Effect of dietary Ginkgo biloba leaf on the growth performance and nonspecific immunity of red swamp crayfish Procambarus clarkii

This trial investigated the effect of dietary Ginkgo biloba leaf (GBL) on the growth performance and nonspecific immunity of red swamp crayfish Procambarus clarkii. 180 Crayfishes were randomly divided into three groups. One group was fed with basic diet, whereas the other two groups were fed with diets containing 1% and 3% GBL. After 32 days of feeding, GBL addition tended to increase the body weight gain rate compared with control. In 3% GBL group, the bodyweight gain rate of male crayfish was higher than that of female crayfish. While female crayfish were advantageous in terms of meat yield. Liver-related indexes were influenced by GBL addition and 3% GBL could reduce glutamic pyruvic transaminase and glutamic oxaloacetic transaminase as well as total cholesterol in male crayfish, showing its function in liver protection. Moreover, GBL addition effects on liver protection was better in male crayfish than female crayfish

The Therapeutic and Pathogenic Role of Autophagy in Autoimmune Diseases

Autophagy is a complicated cellular mechanism that maintains cellular and tissue homeostasis and integrity via degradation of senescent, defective subcellular organelles, infectious agents, and misfolded proteins. Accumulating evidence has shown that autophagy is involved in numerous immune processes, such as removal of intracellular bacteria, cytokine production, autoantigen presentation, and survival of lymphocytes, indicating an apparent and important role in innate and adaptive immune responses. Indeed, in genome-wide association studies, autophagy-related gene polymorphisms have been suggested to be associated with the pathogenesis of several autoimmune and inflammatory disorders, such as systemic lupus erythematosus, psoriasis, rheumatoid arthritis, inflammatory bowel disease, and multiple sclerosis. In addition, conditional knockdown of autophagy-related genes in mice displayed therapeutic effects on several autoimmune disease models by reducing levels of inflammatory cytokines and autoreactive immune cells. However, the inhibition of autophagy accelerates the progress of some inflammatory and autoimmune diseases via promotion of inflammatory cytokine production. Therefore, this review will summarize the current knowledge of autophagy in immune regulation and discuss the therapeutic and pathogenic role of autophagy in autoimmune diseases to broaden our understanding of the etiopathogenesis of autoimmune diseases and shed light on autophagy-mediated therapies

Molecular Control of Follicular Helper T cell Development and Differentiation

Follicular helper T cells (Tfh) are specialized helper T cells that are predominantly located in germinal centers and provide help to B cells. The development and differentiation of Tfh cells has been shown to be regulated by transcription factors, such as B-cell lymphoma 6 protein (Bcl-6), signal transducer and activator of transcription 3 (STAT3) and B lymphocyte-induced maturation protein-1 (Blimp-1). In addition, cytokines, including IL-21, have been found to be important for Tfh cell development. Moreover, several epigenetic modifications have also been reported to be involved in the determination of Tfh cell fate. The regulatory network is complicated, and the number of novel molecules demonstrated to control the fate of Tfh cells is increasing. Therefore, this review aims to summarize the current knowledge regarding the molecular regulation of Tfh cell development and differentiation at the protein level and at the epigenetic level to elucidate Tfh cell biology and provide potential targets for clinical interventions in the future

Automatic segmentation of myocardium from black-blood MR images using entropy and local neighborhood information.

By using entropy and local neighborhood information, we present in this study a robust adaptive Gaussian regularizing Chan-Vese (CV) model to segment the myocardium from magnetic resonance images with intensity inhomogeneity. By utilizing the circular Hough transformation (CHT) our model is able to detect epicardial and endocardial contours of the left ventricle (LV) as circles automatically, and the circles are used as the initialization. In the cost functional of our model, the interior and exterior energies are weighted by the entropy to improve the robustness of the evolving curve. Local neighborhood information is used to evolve the level set function to reduce the impact of the heterogeneity inside the regions and to improve the segmentation accuracy. An adaptive window is utilized to reduce the sensitivity to initialization. The Gaussian kernel is used to regularize the level set function, which can not only ensure the smoothness and stability of the level set function, but also eliminate the traditional Euclidean length term and re-initialization. Extensive validation of the proposed method on patient data demonstrates its superior performance over other state-of-the-art methods