Xuzhou Institute of Technology

About: Xuzhou Institute of Technology is a education organization based out in Xuzhou, China. It is known for research contribution in the topics: Catalysis & Computer science. The organization has 1696 authors who have published 1521 publications receiving 13541 citations.

High-pressure synthesis, characterization, and equation of state of double perovskite Sr 2 CoFeO 6

Abstract: Double perovskite oxide Sr2CoFeO6 (SCFO) has been obtained using a high-pressure and high-temperature (HPHT) synthesis method. Valence states of Fe and Co and their distributions in SCFO were examined with X-ray photoelectron spectroscopy. The electric transport behavior of SCFO showed a semiconductor behavior that can be well described by Mott?s law for variable-range hopping conduction. The structural stability of SCFO was investigated at pressures up to 31 GPa with no pressure-induced phase transition found. Bulk modulus B0 was determined to be 163(2) GPa by fitting the pressure?volume data to the Birch?Murnaghan equation of state.

Exploiting Quality-Guided Adaptive Optimization for Fusing Multimodal Medical Images

Abstract: Multimodal medical image fusion (MMIF) plays critical roles in image-guided clinical diagnostics and treatment. Pulse coupled neural network (PCNN) has been applied in image fusion for several years. In the schemes of image fusion based on PCNN, the authors have adjusted variables manually, so that it is difficult to get satisfying effects which limit in dealing with medical images with different modalities. This paper presents a quality-guided adaptive optimization method for MMIF, which is based on PCNN optimized by multi-swarm fruit fly optimization algorithm (MFOA). To reduce the implementation cost and improve the performance of the MFOA, quality assessment for multimodal medical image fusion was chosen to be the hybrid fitness function. Guided by such quality measurement, the adaptive PCNN using the MFOA (PCNN-MFOA) is proposed, which could automatically fit the optimal variables to the source images and enhance the fusion effect. The experimental results visually and quantitatively show that the proposed fusion strategy is more effective than the state-of-the-art methods and it is more effective in processing medical images with different modalities.

C M ⊗C N D-computable state

Abstract: The notions of D-computable state and D-concurrence are generalized to the C M ⊗ C N system. A class of D-computable state on C M ⊗ C N is given and the calculating method of the lower bound of D-concurrence is provided. The obvious expression of the lower bound of D-concurrence for the state mixed by two D-pure states is derived.

PID parameter optimization using improved genetic algorithm

Abstract: In order to improve the problem of premature and performance of optimization,a hybrid algorithm of particle swarm optimization and genetic algorithm is proposed for parameters optimization of PID controller by applying particle swarm optimization to the mutation operation of genetic algorithm.The simulation and experimental results show that the novel algorithm is superior to simple genetic algorithm,can overcome premature phenomena,reduce the influence of random initial population,and improve the convergence precision,which demonstrates the proposed method has better performance of convergence and fine ability of global optimization.

Characterization of γ-glutamyltranspeptidases from dormant garlic and onion bulbs.

Abstract: This study investigated the characteristics of γ-glutamyltranspeptidases (GGTs) isolated from dormant garlic (Allium sativum L.) and onion (Allium cepa L. var. agrogatum Don) bulbs. GGTs were isolated using (NH 4)2 SO 4 precipitation and hydrophobic interaction chromatography (phenyl-Sepharose column). The optimal temperature, optimal pH of extraction, and the effects of metal ions and organic compounds on the activity of GGTs were investigated. The optimal pH of the GGTs of garlic and onion was 5 and 7, respectively; the optimal temperatures were 70 and 50°C, respectively. Garlic's GGT had a major band at 53 kDa, whereas onion's GGT had two bands at 55 and 22 kDa. Cu2+, Mn2+, Fe2+, Mg2+, glucose, aspartic acid, and cysteine significantly enhanced the activity of garlic's GGT. Lysine and proline remarkably promoted the activity of onion's GGT, whereas Cu2+, glucose, and aspartic acid repress its activity. These results may deepen our understanding of allium GGTs and promote the commercial production of bioactive allium compounds.