Identification of bacterial community composition in freshwater aquaculture system farming of Litopenaeus vannamei reveals distinct temperature-driven patterns

Change in temperature is often a major environmental factor in triggering waterborne disease outbreaks. Previous research has revealed temporal and spatial patterns of bacterial population in several aquatic ecosystems. To date, very little information is available on aquaculture environment. Here, we assessed environmental temperature effects on bacterial community composition in freshwater aquaculture system farming of Litopenaeus vannamei (FASFL). Water samples were collected over a one-year period, and aquatic bacteria were characterized by polymerase chain reaction-denaturing gradient gel electrophoresis (PCR-DGGE) and 16S rDNA pyrosequencing. Resulting DGGE fingerprints revealed a specific and dynamic bacterial population structure with considerable variation over the seasonal change, suggesting that environmental temperature was a key driver of bacterial population in the FASFL. Pyrosequencing data further demonstrated substantial difference in bacterial community composition between the water at higher (WHT) and at lower (WLT) temperatures in the FASFL. Actinobacteria, Proteobacteria and Bacteroidetes were the highest abundant phyla in the FASFL, however, a large number of unclassified bacteria contributed the most to the observed variation in phylogenetic diversity. The WHT harbored remarkably higher diversity and richness in bacterial composition at genus and species levels when compared to the WLT. Some potential pathogenenic species were identified in both WHT and WLT, providing data in support of aquatic animal health management in the aquaculture industry.

A new approach for fault location identification in transmission system using stability analysis and SVMs

This paper presents a new approach to the location of fault in the high voltage power transmission system using Support Vector Machines (SVMs). A knowledge base is developed using transient stability studies for apparent impedance swing trajectory in the R-X plane. SVM technique is applied to identify the fault location in the system. Results are presented on sample 3-power station, a 9-bus system illustrate the implementation of the proposed method.

Identification of coherent synchronous generators in a multi- machine power system using support vector clustering

This paper illustrates the application of a new technique, based on Support Vector Clustering (SVC) for the direct identification of coherent synchronous generators in a large interconnected Multi-Machine Power Systems. The clustering is based on coherency measures, obtained from the time domain responses of the generators following system disturbances. The proposed clustering algorithm could be integrated into a wide-area measurement system that enables fast identification of coherent clusters of generators for the construction of dynamic equivalent models. An application of the proposed method is demonstrated on a practical 15 generators 72-bus system, an equivalent of Indian Southern grid in an attempt to show the effectiveness of this clustering approach. The effects of short circuit fault locations on coherency are also investigated.

Identification of fault location in power distribution system with distributed generation using support vector machines

This paper presents a multi-class support vector machine (SVMs) approach for locating and diagnosing faults in electric power distribution feeders with the penetration of Distributed Generations (DGs). The proposed approach is based on the three phase voltage and current measurements which are available at all the sources i.e. substation and at the connection points of DG. To illustrate the proposed methodology, a practical distribution feeder emanating from 132/11kV-grid substation in India with loads and suitable number of DGs at different locations is considered. To show the effectiveness of the proposed methodology, practical situations in distribution systems (DS) such as all types of faults with a wide range of varying fault locations, source short circuit (SSC) levels and fault impedances are considered for studies. The proposed fault location scheme is capable of accurately identify the fault type, location of faulted feeder section and the fault impedance. The results demonstrate the feasibility of applying the proposed method in practical in smart grid distribution automation (DA) for fault diagnosis.

Support vector clustering-based direct coherency identification of generators in a multi-machine power system

This study investigates the application of support vector clustering (SVC) for the direct identification of coherent synchronous generators in large interconnected multi-machine power systems. The clustering is based on coherency measure, which indicates the degree of coherency between any pair of generators. The proposed SVC algorithm processes the coherency measure matrix that is formulated using the generator rotor measurements to cluster the coherent generators. The proposed approach is demonstrated on IEEE 10 generator 39-bus system and an equivalent 35 generators, 246-bus system of practical Indian southern grid. The effect of number of data samples and fault locations are also examined for determining the accuracy of the proposed approach. An extended comparison with other clustering techniques is also included, to show the effectiveness of the proposed approach in grouping the data into coherent groups of generators. This effectiveness of the coherent clusters obtained with the proposed approach is compared in terms of a set of clustering validity indicators and in terms of statistical assessment that is based on the coherency degree of a generator pair.

Architecture research and hardware implementation on simplified neural computing system for face identification

This paper describes a special-purpose neural computing system for face identification. The system architecture and hardware implementation are introduced in detail. An algorithm based on biomimetic pattern recognition has been embedded. For the total 1200 tests for face identification, the false rejection rate is 3.7% and the false acceptance rate is 0.7%.

Identification and characterization of the AcrR/AcrAB system of a pathogenic Edwardsiella tarda strain

Edwardsielia tarda is one of the leading marine pathogens that can infect a wide range of cultured marine species. In this study, the acrR-acrAB cluster was cloned from TX1, a pathogenic E. tarda strain isolated from diseased fish. AcrR and AcrAB were found to be involved in resistance against acriflavine and methyl viologen, which positively regulate the expression of acrAB. AcrR negatively regulates its own expression and the expression of the acrAB operon, most likely by interacting with a 24-bp operator site that overlaps the putative promoter of acrA (PacrA). The repressive effect of AcrR on PacrA could be relieved by acriflavine, methyl viologen, and ethidium bromide, the presence of each of which enhanced transcription from PacrA. Interruption of the regulated expression of acrR by introducing into TX1 a plasmid that overexpresses acrR affected growth under stress conditions, AI-2 production, and bacterial virulence. In addition, mutational analyses identified a constitutively active AcrR mutant (named N215), which exhibits full repressor activity but is impaired in its ability to interact with the inducer. Overexpression of N215 produced the same kind of but moderately stronger effect on TX1 compared to that produced by overexpression of the wild-type acrR.

Construction and characterization of two bacterial artificial chromosome libraries of Zhikong scallop, Chlamys farreri Jones et Preston, and identification of BAC clones containing the genes involved in its innate immune system

Large-insert bacterial artificial chromosome (BAC) libraries are necessary for advanced genetics and genomics research. To facilitate gene cloning and characterization, genome analysis, and physical mapping of scallop, two BAC libraries were constructed from nuclear DNA of Zhikong scallop, Chlamys farreri Jones et Preston. The libraries were constructed in the BamHI and MboI sites of the vector pECBAC1, respectively. The BamHI library consists of 73,728 clones, and approximately 99% of the clones contain scallop nuclear DNA inserts with an average size of 110 kb, covering 8.0x haploid genome equivalents. Similarly, the MboI library consists of 7680 clones, with an average insert of 145 kb and no insert-empty clones, thus providing a genome coverage of 1.1x. The combined libraries collectively contain a total of 81,408 BAC clones arrayed in 212 384-well microtiter plates, representing 9.1x haploid genome equivalents and having a probability of greater than 99% of discovering at least one positive clone with a single-copy sequence. High-density clone filters prepared from a subset of the two libraries were screened with nine pairs of Overgos designed from the cDNA or DNA sequences of six genes involved in the innate immune system of mollusks. Positive clones were identified for every gene, with an average of 5.3 BAC clones per gene probe. These results suggest that the two scallop BAC libraries provide useful tools for gene cloning, genome physical mapping, and large-scale sequencing in the species.

A drive-by inspection system via vehicle moving force identification

This paper presents a novel method to carry out monitoring of transport infrastructure such as pavements and bridges through the analysis of vehicle accelerations. An algorithm is developed for the identification of dynamic vehicle-bridge interaction forces using the vehicle response. Moving force identification theory is applied to a vehicle model in order to identify these dynamic forces between the vehicle and the road and/or bridge. A coupled half-car vehicle-bridge interaction model is used in theoretical simulations to test the effectiveness of the approach in identifying the forces. The potential of the method to identify the global bending stiffness of the bridge and to predict the pavement roughness is presented. The method is tested for a range of bridge spans using theoretical simulations and the influences of road roughness and signal noise on the accuracy of the results are investigated.

Identification of the Flagellin Glycosylation System in Burkholderia cenocepacia and the Contribution of Glycosylated Flagellin to Evasion of Human Innate Immune Responses

Burkholderia cenocepacia is an opportunistic pathogen threatening patients with cystic fibrosis. Flagella are required for biofilm formation, as well as adhesion to and invasion of epithelial cells. Recognition of flagellin via the Toll-like receptor 5 (TLR5) contributes to exacerbate B. cenocepacia-induced lung epithelial inflammatory responses. In this study, we report that B. cenocepacia flagellin is glycosylated on at least 10 different sites with a single sugar, 4,6-dideoxy-4-(3-hydroxybutanoylamino)-d-glucose. We have identified key genes that are required for flagellin glycosylation, including a predicted glycosyltransferase gene that is linked to the flagellin biosynthesis cluster and a putative acetyltransferase gene located within the O-antigen lipopolysaccharide cluster. Another O-antigen cluster gene, rmlB, which is required for flagellin glycan and O-antigen biosynthesis, was essential for bacterial viability, uncovering a novel target against Burkholderia infections. Using glycosylated and nonglycosylated purified flagellin and a cell reporter system to assess TLR5-mediated responses, we also show that the presence of glycan in flagellin significantly impairs the inflammatory response of epithelial cells. We therefore suggest that flagellin glycosylation reduces recognition of flagellin by host TLR5, providing an evasive strategy to infecting bacteria.