Global Neural Network Potential with Explicit Many-Body Functions for Improved Descriptions of Complex Potential Energy Surface.

The high dimensional machine learning potential (MLP) that has developed rapidly in the past decade represents a giant step forward in large-scale atomic simulation for complex systems. The long-range interaction and the poor description of chemical reactions are typical problems of high dimensional MLP, which are mainly caused by the poor structure discrimination of the atom-centered ML model. Herein, we propose a low-cost neural-network-based MLP architecture for fitting global potential energy surface data, namely, G-MBNN, that can offer improved energy and force resolution on a complex potential energy surface. In G-MBNN, a set of many-body energy terms based on the local atomic environment are explicitly included in computing the total energy─the total energy of the system is written as the sum of atomic energy and many-body energy contributions. These extra many-body energy terms are computationally low-cost and, importantly, can provide easy access to delicate energy terms in complex systems such as very short repulsion, long-range attractions, and sensitive angular-dependent covalent interactions. We implement G-MBNN in the LASP code and demonstrate the improved accuracy of the new framework in representative systems, including ternary-element energy materials LiCoOx, TiO2 with defects, and a series of organic reactions.

Fault severity assessment of rolling bearing based on optimized multi-dictionaries matching pursuit and Lempel-Ziv complexity.

For the safe working of rolling bearing, this paper presents a fault severity assessment method through optimized multi-dictionaries matching pursuit (OMMP) and Lempel-Ziv (LZ) complexity. To solve the redundancy problem of over-complete dictionary, the OMMP is proposed by introducing the quantum particle swarm optimization into matching pursuit for best representing the original vibration signal. And then, LZ complexity is calculated as an index of fault severity assessment by reconstructed signal. The performance of assessment method is verified through the measured signals of three bearing tests, and the comparisons with various methods are specifically described. The results indicate that the OMMP method averagely takes the shortest running time for the vibration signal decomposition. The assessment method is able to effectively evaluate different fault sizes of rolling bearing, and has a great applicability to in the condition-based maintenance of rotating machineries.

[Effects of SiRNA-EGFR on the expression of hyaluronidase gene EGFR in human breast cancer cells].

OBJECTIVE: To study the effect of SiRNA-EGFR on the expression of hyaluronidase gene in human breast cancer cells. METHODS: Reverse transcription-polymerse chain reaction was used to detect the changes in the expression of EGFR mRNA in human breast cancer cell lines MDA-MB-231, MDA-MB-435S, ZR-75 and ZR-75-30 after transfection by SiRNA-EGFR. RESULTS: After transfection with SiRNA-EGFR, the expression levels of EGFR were significantly inhibited in MDA-MB-231, MDA-MB-435S, ZR-75 and ZR-75-30 cells (P<0.05). CONCLUSION: Transfection by SiRNA-EGFR can inhibit the expression of EGFR mRNA in human breast cancer cells.

[Effects of RNA interference on epidermal growth factor receptor expression in breast cancer cells: a study in tumor-bearing nude mice].

OBJECTIVE: To investigate the effect of cationic liposome-mediated RNA interference (RNAi) in silencing epidermal growth factor (EGF) receptor (EGFR) gene in breast cancer cells in vivo. METHODS: A small interfering RNA (siRNA) targeting EGFR gene was constructed and transfected into human breast cancer cell in vitro via cationic liposome. The transfected cells were inoculated into nude mice, and the tumor growth inhibition rate was calculated. The tumors were then removed for immunohistochemistry and Western blotting to examine the expression of EGFR protein. Quantitative RT-PCR was used to detect the mRNA expression of the EGF receptor gene, and enzyme-linked immunosorbent assay (ELISA) performed to assess the EGF level in both the serum and tumor extraction. RESULTS: In athymic nude mice, MDA-MB-231 cells had obviously lower tumor formation rate than ZR-75 cells (30.00% and 88.89%). Transfection of the cells with EGFR siRNA significantly inhibited tumor formation capacity of the cells in vivo as compared with the cells transfected with empty vector or irrelevant siRNA. The results of ELISA demonstrated that in mice bearing the tumors grown from EGFR siRNA-transfected cells, the EGF levels in the serum and tumor extraction were lowered by 16.77% and 12.59%, respectively. Real-time RT-PCR showed that EGFR siRNA transfection caused a specific downregulation of EGFR mRNA expression by 21.05% in the tumor. CONCLUSION: Chemically synthesized 21-nucleotide siRNA duplexes can be effectively delivered via lipofectamine 2000 into breast cancer cells in vivo to induce a longer-lasting gene silencing effect than in vitro transfection. RNAi of EGFR gene may indicate a promising approach for management of lung cancers, especially those nodular ones with easy access.