Theoretical Analysis of Rock Blasting Damage in Construction of Tunnels Closely Under-Passing Sewage Box Culverts

With the large-scale construction of urban traffic tunnels in China, it has become common to underpass existing buildings and structures such as sewage box culverts and pipelines using the drilling-blasting method. How to analyze accurately the blasting damage of surrounding rock and reasonably determine the safe distance between tunnel and box culvert or pipelines is an urgent issue to be solved. In this paper, the Cowper-Symonds plastic kinetic hardening model was improved using both rock initial damage degree and damage modification coefficient considering rock residual strength. The proposed model was implemented into LS-DYNA. The proposed damage model was used to evaluate the blasting construction of rock tunnels closely under-passing sewage box culverts. The results of numerical simulation using the proposed damage model shows that the blasting damage range of rock with a damage degree of more than 0.5 very significantly reduces from 1.0 m to 0.3 m as the spacing between the box culvert and the tunnel increases from 1.0 m to 4.0 m, and the evolution process of rock blasting damage can be well-presented. Moreover, the safe distance between tunnel and box culvert in blasting construction can be reasonably determined to be no less than 4.0 m. The findings in this paper could be significant for guiding the blasting construction of rock tunnels closely under-passing sewage box culverts

Dynamic Stress of Subgrade Bed Layers Subjected to Train Vehicles with Large Axle Loads

The dynamic responses of subgrade bed layers are the key factors affecting the service performance of a heavy-haul railway. A 3D train-track-subgrade interaction finite element (FE) model was constructed using the ABAQUS code, where different vertical irregular track spectra were simulated by modifying the vertical node coordinates of the FE mesh of the rail. Then, the dynamic stresses in the subgrade bed layers subjected to heavy-haul trains were studied in detail. The results showed the following: (1) the transverse distribution of the dynamic stress transformed from a bimodal pattern to a unimodal pattern with increasing depth; (2) the pass of adjacent bogies of adjacent carriages can be simplified once loaded on the subgrade since the dynamic stresses are maintained around the peak value during the pass of the adjacent bogies; (3) the dynamic stress at the bottom of the subgrade bed surface layer was more sensitive to the train axle load compared with that at the subgrade surface because the dynamic stresses induced by the two rails were gradually overlaid with increasing depth; (4) the maximum dynamic stress at the subgrade bed bottom was reduced by approximately 70% compared with that at the subgrade surface; (5) the vertical track irregularities intensified the vertical excitation between the train vehicle wheels and rails, and the maximum dynamic stress at the subgrade surface under the action of the irregular heavy-haul track spectrum increased by 23% compared with the smooth rail condition; and (6) the possible maximum dynamic stress (σdm) at the subgrade surface under the action of irregular track spectra can be predicted using the triple standard deviation principle of a normally distributed random variable, i.e., σdm = μ + 3σ (where μ and σ are the expectation and standard deviation of σdm, respectively)

dMXP: A <i>De Novo</i> Small-Molecule 3D Structure Predictor with Graph Attention Networks

Generating the three-dimensional (3D) structure of small molecules is crucial in both structure- and ligand-based drug design. Structure-based drug design needs bioactive conformations of compounds for lead identification and optimization. Ligand-based drug design techniques, such as 3D shape similarity search, 3D pharmacophore model, 3D-QSAR, etc., all require high-quality small-molecule ligand conformations to obtain reliable results. Although predicting a small molecular bioactive conformer requires information from the receptor, a crystal structure of the molecule is a proper approximation to its bioactive conformer in a specific receptor because the binding pose of a small molecule in its receptor’s binding pockets should be energetically close to the crystal structures. This study presents a de novo small molecular structure predictor (dMXP) with graph attention networks based on crystal data derived from the Cambridge Structural Database (CSD) combined with molecular electrostatic information calculated by density-functional theory (DFT). Two featuring strategies (topological and atomic partial change features) were employed to explore the relation between these features and the 3D crystal structure of a small molecule. These features were then assembled to construct the holistic 3D crystal structure of a molecule. Molecular graphs were encoded using a graph attention mechanism to deal with the issues of the inconsistencies of local substructures contributing to the entire molecular structure. The root-mean-square deviation (RMSDs) of approximately 80% dMXP predicted structures and the native binding poses within receptors are less than 2.0 Å

Chemical constituents of industrial hemp roots and their anti-inflammatory activities

Abstract Objective Although the chemical constituents of the aerial parts of Cannabis have been extensively studied, phytochemicals of Cannabis roots are not well characterized. Herein, we investigated the chemical constituents of industrial hemp (Cannabis sativa L.) roots and evaluated the anti-inflammatory activities of phytochemicals isolated from the hemp roots extract. Methods An ethyl acetate extract of hemp roots was subjected to a combination of chromatographic columns to isolate phytochemicals. The chemical structures of the isolates were elucidated based on spectroscopic analyses (by nuclear magnetic resonance and mass spectrometry). The anti-inflammatory effects of phytochemicals from hemp roots were evaluated in an anti-inflammasome assay using human monocyte THP-1 cells. Results Phytochemical investigation of hemp roots extract led to the identification of 32 structurally diverse compounds including six cannabinoids (1–6), three phytosterols (26–28), four triterpenoids (22–25), five lignans (17–21), and 10 hydroxyl contained compounds (7–16), three fatty acids (29–31), and an unsaturated chain hydrocarbon (32). Compounds 14–21, 23, 27, and 32 were identified from the Cannabis species for the first time. Cannabinoids (1–5) reduced the level of cytokine tumor necrosis-alpha (by 38.2, 58.4, 47.7, 52.2, and 56.1%, respectively) and 2 and 5 also decreased the interleukin-1β production (by 42.2 and 92.4%, respectively) in a cell-based inflammasome model. In addition, non-cannabinoids including 11, 13, 20, 25, 29, and 32 also showed selective inhibition of interleukin-1β production (by 23.7, 22.5, 25.6, 78.0, 24.1, 46.6, and 25.4%, respectively) in THP-1 cells. Conclusion The phytochemical constituent of a hemp roots extract was characterized and compounds from hemp roots exerted promising anti-inflammatory effects

Crystallization and preliminary crystallographic analysis of the second RRM of Pub1 from Saccharomyces cerevisiae

The second RRM of Pub1 from S. cerevisiae was overexpressed, purified and crystallized. Diffraction data were collected to 1.69 Å resolution

Rotating Stall Inception Prediction Using an Eigenvalue-Based Global Instability Analysis Method

The accurate prediction of rotating stall inception is critical for determining the stable operating regime of a compressor. Among the two widely accepted pathways to stall, namely, modal and spike, the former is plausibly believed to originate from a global linear instability, and experiments have partially confirmed it. As for the latter, recent computational and experimental findings have shown it to exhibit itself as a rapidly amplified flow perturbation. However, rigorous analysis has yet to be performed to prove that this is due to global linear instability. In this work, an eigenanalysis approach is used to investigate the rotating stall inception of a transonic annular cascade. Steady analyses were performed to compute the performance characteristics at a given rotational speed. A numerical stall boundary was first estimated based on the residual convergence behavior of the steady solver. Eigenanalyses were then performed for flow solutions at a few near-stall points to determine their global linear stability. Once the relevant unstable modes were identified according to the signs of real parts of eigenvalues, they were examined in detail to understand the flow destabilizing mechanism. Furthermore, time-accurate unsteady simulations were performed to verify the obtained eigenvalues and eigenvectors. The eigenanalysis results reveal that at the rotating stall inception condition, multiple unstable modes appear almost simultaneously with a leading mode that grows most rapidly. In addition, it was found that the unstable modes are continuous in their nodal diameters, and are members of a particular family of modes typical of a dynamic system with cyclic symmetries. This is the first time such an interesting structure of the unstable modes is found numerically, which to some extent explains the rich and complex results constantly observed from experiments but have never been consistently explained. The verified eigenanalysis method can be used to predict the onset of a rotating stall with a CPU time cost orders of magnitude lower than time-accurate simulations, thus making compressor stall onset prediction based on the global linear instability approach feasible in engineering practice

Systematic Studies on the Protocol and Criteria for Selecting a Covalent Docking Tool

With the resurgence of drugs with covalent binding mechanisms, much attention has been paid to docking methods for the discovery of targeted covalent inhibitors. The existence of many available covalent docking tools has inspired development of a systematic and objective procedure and criteria with which to evaluate these programs. In order to find a tool appropriate to studies of a covalently binding system, protocols and criteria are proposed for protein&ndash;ligand covalent docking studies. This paper consists of three sections: (1) curating a standard data set to evaluate covalent docking tools objectively; (2) establishing criteria to measure the performance of a tool applied for docking ligands into a complex system; and (3) creating a protocol to evaluate and select covalent binding tools. The protocols were applied to evaluate four covalent docking tools (MOE, GOLD, CovDock, and ICM-Pro) and parameters affecting covalent docking performance were investigated