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Integration of Shift-and-Invert Parallel Spectral Transformation (SIPs) eigensolver (as implemented in the SLEPc library) into an ab initio molecular dynamics package, SIESTA, is described. The effectiveness of the code is demonstrated on applications to polyethylene chains, boron nitride sheets, and bulk water clusters. For problems with the same number of orbitals, the performance of the SLEPc eigensolver depends on the sparsity of the matrices involved, favoring reduced dimensional systems such as polyethylene or boron nitride sheets in comparison to bulk systems like water clusters. For all problems investigated, performance of SIESTA-SIPs exceeds the performance of SIESTA with default solver (ScaLAPACK) at the larger number of cores and the larger number of orbitals. A method that improves the load-balance with each iteration in the self-consistency cycle by exploiting the emerging knowledge of the eigenvalue spectrum is demonstrated. © 2018 Wiley Periodicals, Inc.

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With continued increasing construction of both electrified facilities and buried high‐strength pipelines in China, stray current corrosion defects have become an nonignorable threat for these pipelines. A comprehensive investigation on a new failure pressure prediction model for high‐strength pipes with stray current corrosion defects was conducted in this study. The mechanism of stray current corrosion in steel pipes was firstly elaborated in brief. After that, a parameterized finite element model for stress analysis of pipes with external corrosion defects was programmed by APDL code developed by general software ANSYS. By comparing numerical results with full‐scale experimental results, both the numerical model and the failure criteria for pipe burst were proven to be reasonable. Based on the finite element model, parametric analysis was performed using a calculation matrix set by orthogonal testing method to investigate the effects of three main dimensionless factors, that is, ratio of pipe diameter to wall thickness, nondimensional corrosion defect length, and nondimensional corrosion defect depth on pipe's failure pressure. Utilizing the parametric analysis results as database, a multilayer feed‐forward artificial neural network (ANN) was developed for failure pressure prediction. By comparison with experimental burst test results and results of previous failure pressure estimation model, the ANN model results were proven to have both high accuracy and efficiency, which could be referenced in residual strength or safety assessment of high‐strength pipes with corrosion defects.

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Tumor necrosis factor α-induced protein 8 (TNFAIP8)-like protein 1 (TIPE1) was a member of TNFAIP8 family. Previous studies have shown that TIPE1 could induce apoptosis in hepatocellular carcinoma. In this study, we attempted to predict its potential structure. Bioinformatic analysis of TIPE1 was performed to predict its potential structure using the bioinfomatic web services or softwares. The results showed that the amino acid sequences of TIPE1 were well conserved in mammals. No signal peptide and no transmembrane domain existed in human TIPE1. The aliphatic index of TIPE1 was 100.75 and the theoretical pI was 9.57. TIPE1 was a kind of stable protein and its grand average of hydropathicity was -0.108. Various post-translational modifications were also speculated to exist in TIPE1. In addition, the results of Swiss-Model Server and Swiss-Pdb Viewer program revealed that the predicted three-dimensional structure of TIPE1 protein was stable and it may accord with the rule of stereochemistry. TIPE1 was predicted to interact with FBXW5, caspase8 and so on. In conclusion, TIPE1 may be a stable protein with no signal peptide and no transmembrane domain. The bioinformatic analysis of TIPE1 will provide the basis for the further study on the function of TIPE1.