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Possible Epithelial Ovarian Cancer Association with HPV18 or HPV33 Infection
Zhang, Pei-Pei,Zhou, Lei,Cao, Jia-Shi,Li, Yi-Ping,Zeng, Zhi,Sun, Ni,Shen, Li,Zhu, Hao-Yue,Ruan, Yang,Zha, Wen-Ting,Wang, Xin-Yu,Zhang, Ke-Qiang,Zhang, Ran Asian Pacific Journal of Cancer Prevention 2016 Asian Pacific journal of cancer prevention Vol.17 No.6
The present study was conducted to investigate the prevalence of HPV infection in epithelial ovarian cancer (EOC) in Hunan province. DNA samples were collected from paraffin embedded ovarian tissue from 322 patients with EOC, 99 with ovarian benign tumors and 199 normal persons. The polymerase chain reaction and direct sequencing were used to identify the HPV types in the samples. The relationship between the infection of human papillomavirus (HPV) and the epithelial ovarian carcinoma (EOC) was investigated combined with clinical data. The prevalence of HPV18 and HPV33 in EOC group and benign group was higher than in the normal group. HPV18 and HPV33 may play a role in the development of both EOC and ovarian benign tumor and may participate in the development of EOC with traditional risk factors, family history and abortion, possibly exerting synergistic effects.
A Improved Algorithm of Quantum Particle Swarm with Fast Convergence
Zhang Chun-na,Li Yi-ran,Li Jun-feng 보안공학연구지원센터 2015 International Journal of Hybrid Information Techno Vol.8 No.6
An improved algorithm of quantum particle swarm with chaos is presented to solve the problem that the traditional particle swarm algorithm is easy to fall into local optimum and converges very slowly. Through analysis the current state of particles in the iteration, to determine and deal with the particle of poor performance, and keep the normal state continue to complete the search optimal solution, which effectively inhibit premature phenomenon of the particles, and improve the overall search ability of particle swarm. At the same time, in order to improve the performance of the algorithm, introducing chaos mechanism, further enhance the search ability of particle. The experiments of benchmark function show that the improved algorithm has obvious advantages compared with the other two algorithms, it has higher stability and accuracy and faster convergence speed at the same time.
Application of a Hybrid Intelligent Optimization Algorithm in Cloud Computing Resources Scheduling
Zhang Chun-na,Li Yi-ran 보안공학연구지원센터 2016 International Journal of Multimedia and Ubiquitous Vol.11 No.10
The resource scheduling imbalance is a multi-objective optimization problem in cloud computing environment, this paper introduced the particle swarm optimization algorithm in cloud computing, a simulated annealing ideas is proposed in view of the prematurity of the algorithm, on the premise of performance determination, the position of the particle is determined by the probability choice, which helps the particle to escape. In order to enhance the global searching ability of the particle, the algorithm is combined with the chaotic mechanism to improve the accuracy of the algorithm. The inertia weight is adjusted dynamically according to the current state of the particle, accordingly, at the same time to obtain the optimal solution to ensure the convergence. Analysis of the experimental results show that the improved algorithm has a significant improvement in the ability of optimization and convergence speed, compared with other algorithms, the benchmark functions comparison is better, the different resource task proportion spent the shortest time and load balancing is the highest.
Yi, Wei-Min,Wang, Feige,Wu, Xue-Bing,Yang, Jinyi,Bai, Jin-Ming,Fan, Xiaohui,Brandt, William N.,Ho, Luis C.,Zuo, Wenwen,Kim, Minjin,Wang, Ran,Yang, Qian,Zhang, Ju-jia,Wang, Fang,Wang, Jian-Guo,Ai, Yanl IOP Publishing 2014 ASTROPHYSICAL JOURNAL LETTERS - Vol.795 No.2
<P>Very few of the z > 5 quasars discovered to date have been radio-loud, with radio-to-optical flux ratios (radio-loudness parameters) higher than 10. Here we report the discovery of an optically luminous radio-loud quasar, SDSS J013127.34-032100.1 (J0131-0321 in short), at z = 5.18 +/- 0.01 using the Lijiang 2.4 m and Magellan telescopes. J0131-0321 has a spectral energy distribution consistent with that of radio-loud quasars. With an i-band magnitude of 18.47 and a radio flux density of 33 mJy, its radio-loudness parameter is similar to 100. The optical and near-infrared spectra taken by Magellan enable us to estimate its bolometric luminosity to be L-bol similar to 1.1 x 10(48) erg s(-1), approximately 4.5 times greater than that of the most distant quasar known to date. The black hole mass of J0131-0321 is estimated to be 2.7 x 10(9) M-circle dot, with an uncertainty up to 0.4 dex. Detailed physical properties of this high-redshift, radio-loud, potentially super-Eddington quasar can be probed in the future with more dedicated and intensive follow-up observations using multi-wavelength facilities.</P>
Liu, Yi-Qing,Zhang, Guo-An,Zhang, Bing-Chang,Wang, Yong,Liu, Zheng,Jiao, Yu-Lian,Liu, Ning,Zhao, Yue-Ran Asian Pacific Journal of Cancer Prevention 2015 Asian Pacific journal of cancer prevention Vol.16 No.3
Background: Prostate cancer is one of the main causes of cancer death, and drug resistance is the leading reason for therapy failure. However, how this occurs is largely unknown. We therrfore aimed to study the response of DU145 cells to cisplatin. Materials and Methods: Du145 prostate cancer cells were treated with a low dose of cisplatin for 24 h and cell viability and number were determined by MTT assay and trypan blue exclusion assay, respectively. The real time polymerase chain reaction (PCR) was used to assess responses to cisplatin treatment. Results: After 24h $2{\mu}g/ml$ treatment did not result in significant reduction in cell viability or number. However, it led to enhanced cancer cell invasiveness. E-cadherin mRNA was reduced, and vimentin, Snail, Slug, metalloproteinase 9 (MMP9) mRNA expression increased significantly, a feature of epithelial-mesenchymal transition (EMT). Conclusions: Short time low concentration cisplatin treatment leads to elevated invasiveness of DU145 cancer cells and this is possibly due to EMT.
A Hybrid Intelligent Optimization Algorithm of Fast Convergence
Li Yi-ran,Zhang Chun-na 보안공학연구지원센터 2015 International Journal of Hybrid Information Techno Vol.8 No.1
A hybrid intelligent optimization algorithm based on quantum particle swarm is presented to solve the problem that the local search ability of traditional SFLA is poor and converges very slowly. The particle is quantized and introduced chaos mechanism in the algorithm in order to enhance the global search ability, using the escape strategy, the group is divided into three clusters and mutation operation on the cluster within individuals, not only improves the convergence speed and ensure the performance of the algorithm. Experiments show that the improved algorithm has the characteristics of strong optimization capability and performance is improved greatly in whether comparison of the baseline function or analysis of universal database, compared with the other two algorithms have obvious advantages.
A New Clustering Algorithm of Hybrid Strategy Optimization
Li Yi-ran,Zhang Chun-na 보안공학연구지원센터 2015 International Journal of Hybrid Information Techno Vol.8 No.7
Normally, improving the performance of clustering depends on improvement of the algorithm. On the basis, this paper presents a hybrid strategy optimization algorithm that K-means algorithm effectively combined with PSO algorithm, which not only has played their respective advantages, but also reflected a hybrid performance. First of all, combined with a semi-supervised clustering idea, to optimize the clustering center of particle by K - means in the iteration of algorithm, enhanced the searching capability of the particles. Secondly, improved the traditional K - means enhance the ability of the algorithm to deal with the concave and convex points. Finally, the algorithm is introduced into the particle state determination mechanism, on implementing mutation for unstable particles, so that the algorithm to obtain stable performance. Experimental results show that the hybrid algorithm optimization ability is outstanding, and the convergence and stability can be effectively improved.
Markov Prediction based on Semi-supervised Kernel Fuzzy Clustering
Li Yi-ran,Zhang Chun-na,Guo Sheng-xing 보안공학연구지원센터 2016 International Journal of Database Theory and Appli Vol.9 No.2
This paper proposes an improved Markov prediction, according to the temperature control problem of hot blast stove alternate supply air in the operation of blast furnace operation, namely, implement clustering for waiting to be processed data, used kernel fuzzy c-means clustering based on the pairwise constraints. The supply air temperature of hot blast stove is seen as without aftereffect things in this method, introduce semi-supervised learning mechanism in traditional fuzzy clustering to deal with the basic data, and using the kernel effectiveness index improved the FCM algorithm. Experiments show that the improved clustering algorithm is superior to other algorithms in accuracy and performance, at the same time, the improved prediction model comparison with the traditional values of temperature prediction, which has obvious advantages in defined temperature range and the fit of the temperature value, the guiding significance was significantly enhanced in industrial field.
( Luo Yi ),( Guo Yi Zhang ),( Zhen Zhu ),( Xiao Hui Wang ),( Wei Ran ),( Qi Rong Shen ) 한국미생물생명공학회(구 한국산업미생물학회) 2013 한국미생물·생명공학회지 Vol.41 No.1
The nutritional requirements for the maximum production of lipopeptides by Bacillus subtilis N7 (B. subtilis N7) were investigated and optimized using response surface methodology (RSM) under shake flask fermentation. A one-factor-at-a time experimental setup was used to screen carbon and nitrogen sources. A Plackett?Burman design (PBD) was employed to screen the most critical variables for lipopeptides production amongst ten nutritional elements. The central composite experimental design (CCD) was finally adopted to elucidate the composition of the fermentation medium. Statistical analyses (analysis of variance, ANOVA) of the results showed that KCl, MnSO4 and FeSO4·6H2O were important components and that their interactions were strong. Lipopeptide production was predicted to reach 709.87 mg/L after a 60 h incubation using an optimum fermentation medium composed of glucose 7.5 g/L, peanut oil 1.25 g/L, MgSO4 0.37 g/L, KH2PO4 0.75 g/L, monosodium glutamate 6.75 g/L, yeast extract and NH4Cl (5:3 w/w) 10 g/L, KCl 0.16 g/L, FeSO4·6H2O 0.24 mg/L, MnSO4 0.76 mg/L, and an initial pH of 7.0. Lipopeptide production (706.57 ± 3.70 mg/L) in the optimized medium confirmed the validity of the predicted model.