A Novel Double Cluster and Principal Component Analysis-Based Optimization Method for the Orbit Design of Earth Observation Satellites

The weighted sum and genetic algorithm-based hybrid method (WSGA-based HM), which has been applied to multiobjective orbit optimizations, is negatively influenced by human factors through the artificial choice of the weight coefficients in weighted sum method and the slow convergence of GA. To address these two problems, a cluster and principal component analysis-based optimization method (CPC-based OM) is proposed, in which many candidate orbits are gradually randomly generated until the optimal orbit is obtained using a data mining method, that is, cluster analysis based on principal components. Then, the second cluster analysis of the orbital elements is introduced into CPC-based OM to improve the convergence, developing a novel double cluster and principal component analysis-based optimization method (DCPC-based OM). In DCPC-based OM, the cluster analysis based on principal components has the advantage of reducing the human influences, and the cluster analysis based on six orbital elements can reduce the search space to effectively accelerate convergence. The test results from a multiobjective numerical benchmark function and the orbit design results of an Earth observation satellite show that DCPC-based OM converges more efficiently than WSGA-based HM. And DCPC-based OM, to some degree, reduces the influence of human factors presented in WSGA-based HM

Machinery, Materials Science and Engineering Applications: Proceedings of the 6th International Conference on Machinery, Materials Science and Engineering Applications (MMSE 2016)

This conference proceeding contains papers presented at the 6th International Conference on Machinery, Materials Science and Engineering Applications (MMSE 2016), held 28-30 October, 2016 in Wuhan, China. The conference proceeding contributions cover a large number of topics, both theoretical and applied, including Material science, Electrical Engineering and Automation Control, Electronic Engineering, Applied Mechanics, Mechanical Engineering, Aerospace Science and Technology, Computer Science and Information technology and other related engineering topics. MMSE provides a perfect platform for scientists and engineering researchers to exchange ideas, build cooperative relationships and discuss the latest scientific achievements. MMSE will be of interest for academics and professionals working in a wide range of industrial, governmental and academic sectors, including Material Science, Electrical and Electronic Engineering, Information Technology and Telecommunications, Civil Engineering, Energy Production, Manufacturing, Mechanical Engineering, Nuclear Engineering, Transportation and Aerospace Science and Technolog

A Novel Double Cluster and Principal Component Analysis-Based Optimization Method for the Orbit Design of Earth Observation Satellites

The weighted sum and genetic algorithm-based hybrid method (WSGA-based HM), which has been applied to multiobjective orbit optimizations, is negatively influenced by human factors through the artificial choice of the weight coefficients in weighted sum method and the slow convergence of GA. To address these two problems, a cluster and principal component analysis-based optimization method (CPC-based OM) is proposed, in which many candidate orbits are gradually randomly generated until the optimal orbit is obtained using a data mining method, that is, cluster analysis based on principal components. Then, the second cluster analysis of the orbital elements is introduced into CPC-based OM to improve the convergence, developing a novel double cluster and principal component analysis-based optimization method (DCPC-based OM). In DCPC-based OM, the cluster analysis based on principal components has the advantage of reducing the human influences, and the cluster analysis based on six orbital elements can reduce the search space to effectively accelerate convergence. The test results from a multiobjective numerical benchmark function and the orbit design results of an Earth observation satellite show that DCPC-based OM converges more efficiently than WSGA-based HM. And DCPC-based OM, to some degree, reduces the influence of human factors presented in WSGA-based HM

Serum Golgi Protein 73 as a Potential Biomarker for Hepatic Necroinflammation in Population with Nonalcoholic Steatohepatitis

Aims. Persistent hepatic necroinflammatory damage almost always results in fibrosis/cirrhosis or even hepatocellular carcinoma. Therefore, the presence of active necroinflammation in the liver suggests that nonalcoholic fatty liver disease (NAFLD) patients are in urgent need of treatment. Unfortunately, alanine transaminase (ALT), a routine indicator of liver inflammatory damage, showed a poor performance in nonalcoholic steatohepatitis (NASH) patients. Thus, it will be valuable to find an alternative indicator to identify patients with hepatic necroinflammatory damage. In this study, we evaluated the diagnostic value of serum Golgi protein 73 (GP73) for hepatic necroinflammatory damage in patients with NASH. Methods. The clinical data of 201 patients with NASH diagnosed by liver biopsy according to the Brunt staging system were collected retrospectively. The in situ expression of GP73 protein was measured by immunohistochemistry. The receiver operating characteristic (ROC) curve was used to calculate the area under the ROC curve (AUROC) of serum GP73 for diagnosing hepatic necroinflammatory damage. Results. The serum GP73 levels of NASH patients increased with the aggravation of liver necroinflammation. The median levels significantly increased from 49.98 ng/ml (31.49, 75.05) for G0-1 to 76.61 ng/ml (48.68, 110.03) for G2 and to 116.44 ng/ml (103.41, 162.17) for G3 patients (G0-1 vs. G2, P<0.0001; G2 vs. G3, P=0.0228). In consistent, the gradual increase of GP73 protein expression in situ was also observed in liver tissue, in parallel with the increasing severity of necroinflammatory activity. Therefore, serum GP73 correlated well with the intensity of protein expression in liver tissue. The AUROCs of serum GP73 for G2 and G3 inflammatory activity were 0.742 (0.676 to 0.801) and 0.891 (0.840 to 0.931), respectively. Conclusions. GP73 is a valuable alternative serum marker reflecting the severity of hepatic necroinflammation in NASH patients

Effect of Combined Application of Slow-Release and Conventional Urea on Yield and Nitrogen Use Efficiency of Rice and Wheat under Full Straw Return

The effects of one-time basal application of different mixtures of slow-release urea (SRU) and conventional urea (CU) on yield and nitrogen use efficiency (NUE) of rice and wheat were investigated to determine the appropriate ratios of SRU to CU for one-time basal fertilization in a rice&ndash;wheat rotation farmland under full residue incorporation. A field plot experiment was used in this study. Six treatments were established as follows: CK (no nitrogen fertilizer applied), T0 (100% CU, 50% applied as basal fertilizer and 50% applied as jointing fertilizer), T3 (one-time basal application of SRU and CU mixture with 30% SRU), T5 (one-time basal application of SRU and CU mixture with 50% SRU), T7 (one-time basal application of SRU and CU mixture with 70% SRU), and T10 (one-time basal application of 100% SRU). The results showed that the combined application of SRU and CU increased the yields of rice and wheat. Treatment T7 resulted in the highest rice yield, and T3 resulted in the highest wheat yield, which were 25.6% and 29.4% higher, than those of treatment T0, respectively. Compared with treatment T0 (application of CU alone), the combined application of SRU and CU resulted in 27.4&ndash;96.5% and 22.8&ndash;57.1% higher NUE in rice and wheat, respectively

Effect of Combined Application of Slow-Release and Conventional Urea on Yield and Nitrogen Use Efficiency of Rice and Wheat under Full Straw Return

The effects of one-time basal application of different mixtures of slow-release urea (SRU) and conventional urea (CU) on yield and nitrogen use efficiency (NUE) of rice and wheat were investigated to determine the appropriate ratios of SRU to CU for one-time basal fertilization in a rice–wheat rotation farmland under full residue incorporation. A field plot experiment was used in this study. Six treatments were established as follows: CK (no nitrogen fertilizer applied), T0 (100% CU, 50% applied as basal fertilizer and 50% applied as jointing fertilizer), T3 (one-time basal application of SRU and CU mixture with 30% SRU), T5 (one-time basal application of SRU and CU mixture with 50% SRU), T7 (one-time basal application of SRU and CU mixture with 70% SRU), and T10 (one-time basal application of 100% SRU). The results showed that the combined application of SRU and CU increased the yields of rice and wheat. Treatment T7 resulted in the highest rice yield, and T3 resulted in the highest wheat yield, which were 25.6% and 29.4% higher, than those of treatment T0, respectively. Compared with treatment T0 (application of CU alone), the combined application of SRU and CU resulted in 27.4–96.5% and 22.8–57.1% higher NUE in rice and wheat, respectively