Evolutionary Patterns of the Proviral gp90 V3 to V5 Regions of Equine Infectious Anemia Virus Associated with Immune Selection in Progressors and Nonprogressors

The aim of this study was to determine the genomic evolutionary pattern of virulent equine infectious anemia virus （EIAV） during persistent infection. The evolutionary dynamics of proviral genomes were examined by challenging an EIAV seronegative equine （pony 1） and three EIAV vaccinated equines （ponies 4, 7, and 8） with the Chinese virulent strain EIAV- L. Ponies 1 and 7 succumbed to disease and were called progressors, while ponies 4 and 8 lacked clinical symptoms and were considered nonprogressors. Sequences spanning the V3, V4, and V5 hyper-variable regions of the EIAV-L envelope gp90 gene were sequenced from each pony as evolutionary markers of the provirus. The proviral genome of the EIAV-L inoculum evolved during persistent infection and displayed different patterns between EIA progressors and nonprogressors. Inoculum-like variants were isolated from nonprogressors during persistent infection, but only from progressors during acute infection. Variant mutations from nonprogressors were dispersed throughout the sequenced region, while those from progressors were predominantly localized to V3. Humoral immunity and virus variant population selection analyses indicated that immune selection was positive in chronically infected progressors and weak in nonprogressors. In-frame stop codons were frequently localized to a defect ＂hot spot＂. The high number of defective variants in nonprogressors may promote disease survival.

OPTIMIZATION OF AIRPORT TAXIING PLANNING DURING CONGESTED HOURS BASED ON IMMUNE CLONAL SELECTION ALGORITHM

In order to ease congestion and ground delays in major hub airports, an aircraft taxiing scheduling optimization model is proposed with schedule time as the object function. In the new model, the idea of a classical job shop-schedule problem is adopted and three types of special aircraft-taxi conflicts are considered in the constraints. To solve such nondeterministic polynomial time-complex problems, the immune clonal selection algorithm（ICSA） is introduced. The simulation results in a congested hour of Beijing Capital International Airport show that, compared with the first-come-first-served（FCFS） strategy, the optimization-planning strategy reduces the total scheduling time by 13.6 min and the taxiing time per aircraft by 45.3 s, which improves the capacity of the runway and the efficiency of airport operations.

Directional Filter for SAR Images Based on Nonsubsampled Contourlet Transform and Immune Clonal Selection

A directional filter algorithm for intensity synthetic aperture radar （SAR） image based on nonsubsampled contourlet transform （NSCT） and immune clonal selection （ICS） is presented. The proposed filter mainly focuses on exploiting different features of edges and noises by NSCT. Furthermore, ICS strategy is introduced to optimize threshold parameter and amplify parameter adaptively. Numerical experiments on real SAR images show that there are improvements in both visual effects and objective indexes.

An Improved Immune Clone Selection Algorithm for Parameters Optimization of Marine Electric Power System Stabilizer

In themarine electric power system,the marine generators will be disturbed by the large change of loads or the fault of the power system.The marine generators usually installed power system stabilizers to damp power system oscillations through the excitation control.This paper proposes a novel method to obtain optimal parameter values for Power System Stabilizer(PSS)to suppress low-frequency oscillations in the marine electric power system.In this paper,a newly developed immune clone selection algorithm was improved from the three aspects of the adaptive incentive degree,vaccination,and adaptive mutation strategies.Firstly,the typical PSS implementation type of leader-lag structure was adopted and the objective function was set in the optimization process.The performance of PSS tuned by improved immune clone selection algorithm was compared with PSS tuned by basic immune clone selection algorithm(ICSA)under various operating conditions and disturbances.Then,an improved immune clone selection algorithm(IICSA)optimization technique was implemented on two test systems for test purposes.Based on the simulations,it is found that an improved immune clone selection algorithm demonstrates superiority over the basic immune clone selection algorithm in getting a smaller number of iterations and fast convergence rates to achieve the optimal parameters of the power system stabilizers.Moreover,the proposed approach improves the stability and dynamic performance under various loads conditions and disturbances of the marine electric power system.

An optimization algorithm for locomotive secondary spring load adjustment based on artificial immune

In order to control the locomotive wheel(axle) load distribution, a shimming process to adjust the locomotive secondary spring loads was heretofore developed. An immune dominance clonal selection multi-objective algorithm based on the artificial immune system was presented to further improve the performance of the optimization algorithm for locomotive secondary spring load adjustment, especially to solve the lack of control on the output shim quantity. The algorithm was designed into a two-level optimization structure according to the preferences of the problem, and the priori knowledge of the problem was used as the immune dominance. Experiments on various types of locomotives show that owing to the novel algorithm, the shim quantity is cut down by 30% 60% and the calculation time is about 90% less while the secondary spring load distribution is controlled on the same level as before. The application of this optimization algorithm can significantly improve the availability and efficiency of the secondary spring adjustment process.

Evaluation of fatty acid metabolism and innate immunity interactions between commercial broiler, F1 layer × broiler cross and commercial layer strains selected for different growth potentials

Background： The broiler industry has undergone intense genetic selection over the past 50 yr. resulting in improvements for growth and feed efficiency, however, significant variation remains for performance and growth traits. Production improvements have been coupled with unfavourable metabolic consequences, including immunological trade-offs for growth, and excess fat deposition. To determine whether interactions between fatty acid（FA） metabolism and innate immunity may be associated with performance variations commonly seen within commercial broiler flocks, total carcass lipid %, carcass and blood FA composition, as wel as genes involved with FA metabolism, immunity and cel ular stress were investigated in male birds of a broiler strain, layer strain and F1 layer × broiler cross at d 14 post hatch. Heterophil：lymphocyte ratios, relative organ weights and bodyweight data were also compared.Results： Broiler bodyweight（n = 12） was four times that of layers（n = 12） by d 14 and had significantly higher carcass fat percentage compared to the cross（n = 6; P = 0.002） and layers（P = 0.017） which were not significantly different from each other（P = 0.523）. The carcass and whole blood FA analysis revealed differences in the FA composition between the three groups indicating altered FA metabolism, despite al being raised on the same diet. Genes associated with FA synthesis andβ-oxidation were upregulated in the broilers compared to the layers indicating a net overal increase in FA metabolism,which may be driven by the larger relative liver size as a percentage of bodyweight in the broilers. Genes involved in innate immunity such as TLR2 and TLR4, as wel as organel e stress indicators ERN1 and XBP1 were found to be nonsignificant, with the exception of high expression levels of XBP1 in layers compared to the cross and broilers. Additional y there was no difference in heterophil： lymphocytes between any of the birds.Conclusions： The results provide evidence that genetic selection may be associated with altered metabolic processes between broilers, layers and their F1 cross. Whilst there is no evidence of interactions between FA metabolism, innate immunity or cel ular stress, further investigations at later time points as growth and fat deposition increase would provide useful information as to the effects of divergent selection on key metabolic and immunological processes.

CLUSTERING VIA DIMENSIONAL REDUCTION METHOD FOR THE PROJECTION PURSUIT BASED ON THE ICSA

The performance of the classical clustering algorithm is not always satisfied with the high-dimensional datasets, which make clustering method limited in many application. To solve this problem, clustering method with Projection Pursuit dimension reduction based on Immune Clonal Selection Algorithm (ICSA-PP) is proposed in this paper. Projection pursuit strategy can maintain consistent Euclidean distances between points in the low-dimensional embeddings where the ICSA is used to search optimizing projection direction. The proposed algorithm can converge quickly with less iteration to reduce dimension of some high-dimensional datasets, and in which space, K-mean clustering algorithm is used to partition the reduced data. The experiment results on UCI data show that the presented method can search quicker to optimize projection direction than Genetic Algorithm (GA) and it has better clustering results compared with traditional linear dimension reduction method for Principle Component Analysis (PCA).

Epitope variation in the Newcastle disease virus HN gene under antibody immune selective pressure in cell culture

The influence of antibody immune selective pressure on Newcastle disease virus (NDV) HN and F gene mutations was studied in cell cultures.NDV field strain TZ060107 was inoculated into chicken embryo fibroblast cells and continuously passaged with (group A) or without (group B) anti-NDV monospecific serum.Each group contained three independent passage series.HN and F genes were amplified and sequenced for the 10th,20th,30th,40th and 50th generations of each serial passage,and compared with the original strain.The results demonstrated that increased HN gene mutations were observed in group A with the antibody than in group B without the antibody.The nonsynonymous (NS) to synonymous (S) mutations ratio was 6 for group A,significantly higher than 3.4 in group B.In group A with the antibody,there were five stable NS mutations in HN gene,three of which (related to aa#353,521 and 568) were related to known epitopes.There were two stable NS mutations in F gene in group A,but no stable NS mutations in group B.The NS/S ratios of F gene were less than 2.5 for both groups A and B.Our results suggested that the antibody strongly influenced HN gene mutations,while the F gene was less influenced by the same antibody.

GLOBAL STABILITY FOR A TWO-STRAIN VIRUS INFECTION MODEL WITH INTRA-CELLULAR DELAY AND IMMUNE RESPONSE

Considering the immune response and intracellular delay, we propose a two-strain virus model and investigate dynamics of this mathematical model. The global dynamics of the model are completely determined by introducing suitable Lyapunov functionals. We show that if the basic reproduction number is less than one, then both strains die out; but when the number is greater than one, at least one of the strains become endemic depending on the parameter values. The theoretical results provide some useful information on the dynamics of the two strains virus.

Clonal Strategy Algorithm Based on the Immune Memory

Based on the clonal selection theory and immune memory mechanism in the natural immune system, a novel artificial immune system algorithm, Clonal Strategy Algorithm based on the Immune Memory （CSAIM）, is proposed in this paper. The algorithm realizes the evolution of antibody population and the evolution of memory unit at the same time, and by using clonal selection operator, the global optimal computation can be combined with the local searching. According to antibody-antibody （Ab-Ab） affinity and antibody-antigen （Ab-Ag） affinity, the algorithm can allot adaptively the scales of memory unit and antibody population. It is proved theoretically that CSAIM is convergent with probability 1. And with the computer simulations of eight benchmark functions and one instance of traveling salesman problem （TSP）, it is shown that CSAIM has strong abilities in having high convergence speed, enhancing the diversity of the population and avoiding the premature convergence to some extent.