Biodegradation Kinetics for Pre-treatment of Klebsiella pneumoniae Waste with Autothermal Thermophilic Aerobic Digestion

Biodegradation parameters and kinetic characteristics for pre-treating waste strains of Klebsiella pneu-moniae were studied in laboratory scale with an insulated reactor by an innovative technique,autothermal thermo-philic aerobic digestion(ATAD) . Based on an Arrhenius-type equation,an empirical model was developed to corre-late the removal of total suspended solid(TSS) with the initial TSS concentration,influent reaction temperature,aeration rate and stirring rate. The reaction temperatures of the ATAD system could be raised from the ambient temperatures of 25 °C to a maximum temperature of 65 °C. The exponentials for the initial TSS concentration,aeration rate and stirring rate were 1.579,-0.8175 and-0.6549,respectively,and the apparent activation energy was 6.8774 kJ·mol-1. The correlation coefficient for the pre-exponential factor was 0.9223. The TSS removal effi-ciency predicted by the model was validated with an actual test,showing a maximum relative deviation of 10.79%. The new model has a good practicability.

Decomposition Reaction of Zn-MPA(3-Mercaptopropionic Acid) Complex Under Microwave Irradiation

The thermal decomposition of Zn-MPA complex was investigated under microwave irradiation. ZnO and ZnS nanocrystals could be obtained by decomposing Zn-MPA（3-mercaptopropionic acid） complex under different reaction conditions. It was found that both the pH value of the solution and the molar ratio of Zn2＋ and MPA can play an important role in the formation of ZnO and ZnS nanocrystals. MPA mainly acts as an S source or as a complexing agent. This study provides a new route for the controllable preparation of semiconductor nanocrystals.

Generalized Irreducible α-Matrices and Its Applications

The class of generalized α-matrices is presented by Cvetkovi?, L. (2006), and proved to be a subclass of H-matrices. In this paper, we present a new class of matrices-generalized irreducible α-matrices, and prove that a generalized irreducible α-matrix is an H-matrix. Furthermore, using the generalized arithmetic-geometric mean inequality, we obtain two new classes of H-matrices. As applications of the obtained results, three regions including all the eigenvalues of a matrix are given.

Thermal Fatigue Behavior and Cracking Characteristics of High Si-Mo Nodular Cast Iron for Exhaust Manifolds

The thermal fatigue cracking behavior of high Si-Mo nodular cast iron （NCI） is investigated by means of optical microscope （OM）, scanning electron microscope （SEM） and energy dispersive spectroscope （EDS）, in order to find a new material used in exhaust manifolds in First Automotive Works （FAW） .Nodular cast irons with silicon content about 4.7% , in combination with up to 1.1% molybdenum , were produced by Jilin University and FAW. The repeated heating / cooling test was performed under cyclic heating at various maximum heating temperatures （Tmax） ranging from 800to 900℃.Experimental results indicate that the thermal fatigue cracking resistance of high Si-Mo NCI decreases with increasing the maximum heating temperature.The periods for crack initiation are 24-36 , 40-50and 70-90times associated with heating temperature of 900 , 850and 800℃ , respectively , when the holding time is about 10min at Tmax.When thermal fatigue cracking occurs , the cracking always initiates at the bigger surface of specimen.The major positions of cracks propagation are generally at the eutectic oxide boundary region and the region of the graphite disappearance.At the same time , the oxidation may accelerate crack initiation and propagation.On the other hand , micro-crack number varied from large to little because of shielding effect.As exhaust manifolds , the reasonable working temperature of high Si-Mo NCI is no more than 840℃ by test and analysis.

Feature Selection with Fluid Mechanics Inspired Particle Swarm Optimization for Microarray Data

Deoxyribonucleic acid（ DNA） microarray gene expression data has been widely utilized in the field of functional genomics,since it is helpful to study cancer,cells,tissues,organisms etc.But the sample sizes are relatively small compared to the number of genes,so feature selection is very necessary to reduce complexity and increase the classification accuracy of samples. In this paper,a completely newimprovement over particle swarm optimization（ PSO） based on fluid mechanics is proposed for the feature selection. This newimprovement simulates the spontaneous process of the air from high pressure to lowpressure,therefore it allows for a search through all possible solution spaces and prevents particles from getting trapped in a local optimum. The experiment shows that,this newimproved algorithm had an elaborate feature simplification which achieved a very precise and significant accuracy in the classification of 8 among the 11 datasets,and it is much better in comparison with other methods for feature selection.

Hybrid Optimization Algorithm Based on Wolf Pack Search and Local Search for Solving Traveling Salesman Problem

Traveling salesman problem(TSP) is one of the typical NP-hard problems, and it has been used in many engineering applications. However, the previous swarm intelligence(SI) based algorithms for TSP cannot coordinate with the exploration and exploitation abilities and are easily trapped into local optimum. In order to deal with this situation, a new hybrid optimization algorithm based on wolf pack search and local search(WPS-LS)is proposed for TSP. The new method firstly simulates the predatory process of wolf pack from the broad field to a specific place so that it allows for a search through all possible solution spaces and prevents wolf individuals from getting trapped into local optimum. Then, local search operation is used in the algorithm to improve the speed of solving and the accuracy of solution. The test of benchmarks selected from TSPLIB shows that the results obtained by this algorithm are better and closer to the theoretical optimal values with better robustness than those obtained by other methods.