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Yifei Wang,Kaiyu Sun,Jingxian Shen,Bin Li,Ming Kuang,Qinghua Cao,Sui Peng 대한암학회 2019 Cancer Research and Treatment Vol.51 No.4
Purpose Hepatocellular carcinoma (HCC) is an aggressive disease with high recurrence rate. However, current staging systems were lack of predictive capacity for HCC recurrence. We aimed to develop prognostic nomograms based on inflammation-related markers for HCC patients underwent hepatectomy. Materials and Methods We recruited 889 surgically treated patients from two medical centers. Independent prognostic factors were identified by cox regression analyses. Nomograms for recurrence-free survival (RFS) and overall survival (OS) were established and validated internally and externally. The performance, discrimination, and calibration of nomograms were assessed and compared with existed staging systems. Results Neutrophil to lymphocyte ratio (NLR) and gamma-glutamyl transpeptidase to platelet ratio (GPR) were the two inflammation-related factor that independently correlated with survival. NLR, GPR, international normalized ratio (INR), microvascular invasion, satellite lesions, tumor number, tumor diameter, and macrovascular invasion were used to construct nomogram for RFS while GPR, total bilirubin, INR, -fetoprotein, microvascular invasion, satellite lesions, tumor diameter, and macrovascular invasion were for OS. In the training cohort, the C-index of nomogram was 0.701 (95% confidence interval [CI], 0.669 to 0.732) for RFS and 0.761 (95% CI, 0.728 to 0.795) for OS. These results received both internal and external validation with C-index of 0.701 (95% CI, 0.647 to 0.755) and 0.707 (95% CI, 0.657 to 0.756) for RFS, and 0.706 (95% CI, 0.640 to 0.772) and 0.708 (95%CI, 0.646 to 0.771) for OS, respectively. The nomograms showed superior accuracy to conventional staging systems (p < 0.001). Conclusion The nomograms based on inflammation-related markers are of high efficacy in predicting survival of HCC patients after hepatectomy, which will be valuable in guiding postoperative interventions and follow-ups.
Ma, Yifei,Jang, Haegyu,Kim, Sun Jung,Pang, Changhyun,Chae, Heeyeop Springer US 2015 NANOSCALE RESEARCH LETTERS Vol.10 No.1
<P>Vertical graphene (VG) nanosheets are directly grown below 500 °C on glass substrates by a one-step copper-assisted plasma-enhanced chemical vapour deposition (PECVD) process. A piece of copper foil is located around a glass substrate as a catalyst in the process. The effect of the copper catalyst on the vertical graphene is evaluated in terms of film morphology, growth rate, carbon density in the plasma and film resistance. The growth rate of the vertical graphene is enhanced by a factor of 5.6 with the copper catalyst with denser vertical graphene. The analysis of optical emission spectra suggests that the carbon radical density is increased with the copper catalyst. Highly conductive VG films having 800 Ω/□ are grown on glass substrates with Cu catalyst at a relatively low temperature.</P><P><B>Electronic supplementary material</B></P><P>The online version of this article (doi:10.1186/s11671-015-1019-8) contains supplementary material, which is available to authorized users.</P>
Coral‑Like NiFe2O4/C Composite as the High‑Performance Anode Material for Lithium‑Ion Batteries
Shanshan Bao,Yifei Xiao,Junfeng Li,Bo Yue,Yanjun Li,Wenxian Sun,Lei Liu,Yi Huang,Li Wang,Peicong Zhang,Xuefei Lai 대한금속·재료학회 2020 ELECTRONIC MATERIALS LETTERS Vol.16 No.3
In this work, we fabricated NiFe2O4/C composite with a coral-like structure through co-precipitation approach followed bythermal decomposition. The composite with a large surface area of 162.1 m2 g−1 and an average pore size of 11.8 nm wasobtained. The porous structure in the composite derived from oxalate can Effectively accommodate the volume changesof NiFe2O4 during the cycling processes. When used as anode materials, the initial charge and discharge capacities of thecomposite were 926.7 and 1277.7 mAh g−1 at 100 mA g−1. After 50 cycles, the reversible capacity of NiFe2O4/C could stillremain at 892.4 mAh g−1. Even at a current density of 2000 mA g−1, the reversible capacity still reached 523.3 mAh g−1. The results showed that the synergy between NiFe2O4 and carbon improved the electrochemical performance, and the porouscomposite could stabilize the structure of the electrode.
Multi-step model predictive current control of permanent-magnet synchronous motor
Xu, Yanping,Sun, Yifei,Hou, Yongle The Korean Institute of Power Electronics 2020 JOURNAL OF POWER ELECTRONICS Vol.20 No.1
The traditional model predictive current control (MPCC) strategy has the advantages of a fast dynamic response and flexible constraint conditions. However, this strategy only determines the optimal voltage vector in a period rather than in multiple periods, which may result in a large current ripple. To solve the above problem, this paper proposes a multi-step MPCC strategy of permanent-magnet synchronous motor. In the proposed multi-step MPCC strategy, the optimal voltage vector and the sub-optimal voltage vector are considered simultaneously. The current response in the next period is predicted on the basis of the optimal and the sub-optimal voltage vectors, respectively. To ensure the optimality of the selected voltage vector in two control periods, the current responses of the two control periods are contrasted. Compared with the traditional MPCC strategy, simulation and experimental results show that the proposed multi-step MPCC strategy can effectively reduce the current ripple and improve the steady-state performance without increasing the switching frequency.
Qiannan Wu,Yifei Sun,Xuefeng Yan,Lihua Lv 제어·로봇·시스템학회 2023 International Journal of Control, Automation, and Vol.21 No.11
The selective ensemble aims to search the optimal subset balanced accuracy and diversity from the original base classifier set to construct an ensemble classifier with strong generalization performance. A selective ensemble classifier named BRFS-APCSC is proposed in this paper, which realizes the generation and selection of a set of accurate and diverse base classifiers respectively. In the first step, a multimodal perturbation method is introduced to train distinct base classifiers. The method perturbs the sample space by Bootstrap and disturbs the feature space under a newly proposed semi-random feature selection, which is a combination of the core attribute theory and the improved maximum relevance minimum redundancy algorithm. Then, to search the optimal classifier subset, affinity propagation clustering is added to cluster base classifiers in the first step, then the base classifiers are regarded as features so that the improved maximum relevance minimum redundancy algorithm is applied to select parts of base classifiers from each cluster for integration. UCI datasets and an actual dataset of semi-decarbonization are employed to verify the performance of BRFS-APCSC. The experimental results demonstrate that BRFS-APCSC has significantly difference with other selective ensemble methods and improve the classification accuracy.
HUI WANG,YIFEI YU,YUBIN SUN,QIANWANG CHEN 성균관대학교(자연과학캠퍼스) 성균나노과학기술원 2011 NANO Vol.6 No.1
One-dimensional (1D) chain-like structures are of special significance because of their interparticle magnetic interactions and potential applications in various fields, such as micromechanical sensors. This paper attempts to review the field of research into magnetic chains including monatomic chains and nanoparticle chains. The synthesis methods used mostly belong to one of the following categories: magnetosome chains in magnetotactic bacteria, zero-field self-assembly, magnetic field induced (MFI) assembly, template-directed synthesis, and gas phase synthesis. The potential applications of nanoparticle chains, mainly in the field of magnetic recording media, sensor, biomedicine and magnetic-field tunable photonic crystal are discussed.