Search

Campylobacter jejuni is one of the major causative pathogens of outbreaks or sporadic cases of diarrhoeal diseases worldwide. In this study, we compared the phenotypic and genetic characteristics of C. jejuni isolates of human and food-producing animal origins in Korea and examined the genetic relatedness between these two groups of isolates. Regardless of isolation source, all C. jejuni isolates harboured four virulence genes, cadF, cdtB, ciaB and racR, whereas the wlaN and virB11 genes were more frequently observed in human isolates. Antimicrobial susceptibility testing showed that the majority of C. jejuni isolates displayed high-level resistance to fluoroquinolone (95.2%) or tetracycline (76.2%) antibiotics, and 12.4% of isolates exhibited multidrug resistance (more than three classes of antibiotics tested). Pulsed-field gel electrophoresis ( PFGE) of all Campylobacter isolates revealed 51 different SmaI- PFGE patterns and six major clusters containing both human and animal isolates. These results indicate that genetically diverse strains of C. jejuni with antimicrobial drug-resistance and virulence properties have prevailed in Incheon. Nevertheless, some particular populations continue to circulate within the community, providing the evidence for an epidemiological link of C. jejuni infections between humans and food-producing animals. Therefore, the continued monitoring and surveillance of C. jejuni isolates of human and food-producing animal origins are required for public health and food safety. [ABSTRACT FROM AUTHOR]

Growth traits, such as body weight and carcass body length, directly affect productivity and economic efficiency in the livestock industry. We performed a genome-wide linkage analysis to detect the quantitative trait loci ( QTL) that affect body weight, growth curve parameters and carcass body length in an F2 intercross between Landrace and Korean native pigs. Eight phenotypes related to growth were measured in approximately 1000 F2 progeny. All experimental animals were subjected to genotypic analysis using 173 microsatellite markers located throughout the pig genome. The least squares regression approach was used to conduct the QTL analysis. For body weight traits, we mapped 16 genome-wide significant QTL on SSC1, 3, 5, 6, 8, 9 and 12 as well as 22 suggestive QTL on SSC2, 3, 4, 5, 6, 7, 8, 9, 10, 12, 16 and 17. On SSC12, we identified a major QTL affecting body weight at 140 days of age that accounted for 4.3% of the phenotypic variance, which was the highest test statistic ( F-ratio = 45.6 under the additive model, nominal P = 2.4 × 10−11) observed in this study. We also showed that there were significant QTL on SSC2, 5, 7, 8, 9 and 12 affecting carcass body length and growth curve parameters. Interestingly, the QTL on SSC2, 3, 5, 6, 8, 9, 10, 12 and 17 influencing the growth-related traits showed an obvious trend for co-localization. In conclusion, the identified QTL may play an important role in investigating the genetic structure underlying the phenotypic variation of growth in pigs. [ABSTRACT FROM AUTHOR]

Changes affecting the status of health and robustness can bring about physiological alterations including hematological parameters in swine. To identify quantitative trait loci ( QTL) associated with eight hematological traits (one leukocyte trait, six erythrocyte traits and one platelet trait), we conducted a genome-wide association study using the Porcine SNP60K BeadChip in a resource population derived from an intercross between Landrace and Korean native pigs. A total of 36 740 SNPs from 816 F2 progeny were analyzed for each blood-related trait after filtering for quality control. Data were analyzed by the genome-wide rapid association using mixed model and regression ( GRAMMAR) approach. A total of 257 significant SNPs ( P < 1.36 × 10−6) on SSC3, 6, 8, 13 and 17 were identified for blood-related traits in this study. Interestingly, the genomic region between 17.9 and 130 Mb on SSC8 was found to be significantly associated with red blood cell, mean corpuscular volume and mean corpuscular hemoglobin. Our results include the identification of five significant SNPs within five candidate genes ( KIT, IL15, TXK, ARAP2 and ERG) for hematopoiesis. Further validation of these identified SNPs could give valuable information for understanding the variation of hematological traits in pigs. [ABSTRACT FROM AUTHOR]

Summary Haematological traits play important roles in disease resistance and defence functions. The objective of this study was to locate quantitative trait loci (QTL) and the associated positional candidate genes influencing haematological traits in an F2 intercross between Landrace and Korean native pigs. Eight blood-related traits (six erythrocyte traits, one leucocyte trait and one platelet trait) were measured in 816 F2 progeny. All experimental animals were genotyped with 173 informative microsatellite markers located throughout the pig genome. We report that nine chromosomes harboured QTL for the baseline blood parameters: genomic regions on SSC 1, 4, 5, 6, 8, 9, 11, 13 and 17. Eight of twenty identified QTL reached genome-wide significance. In addition, we evaluated the KIT locus, an obvious candidate gene locus affecting variation in blood-related traits. Using dense single nucleotide polymorphism marker data on SSC 8 and the marker-assisted association test, the strong association of the KIT locus with blood phenotypes was confirmed. In conclusion, our study identified both previously reported and novel QTL affecting baseline haematological parameters in pigs. Additionally, the positional candidate genes identified here could play an important role in elucidating the genetic architecture of haematological phenotype variation in swine and in humans. [ABSTRACT FROM AUTHOR]

Membrane fouling is the most serious problem in membrane bioreactor (MBR) process, which is restricting the widespread application of MBRs in wastewater treatment processes. In recent years, several studies on the precise diagnosis and prediction of the membrane fouling have been carried out to obtain an efficient operation of MBRs. The aims of this study are 1) to predict the membrane fouling and to determine the chemical cleaning interval of membrane using traditional mechanistic fouling model; and 2) to propose the new fouling index based on the usually obtained traditional technique. As the traditional fouling technique use an exponential fouling model, however, this method has some shortcomings, such as inadequate comprehension of the fouling mechanism and steady state assumption. Therefore, in this study, the coefficient (κ) of the exponential fouling model is proposed as a new fouling index to overcome the inadequate understanding of the fouling mechanism and steady state assumption in traditional technique. To propose the coefficient (κ) as the new fouling index, least-square (LS) method and recursive least-square (RLS) methods are applied in the exponential fouling model. The coefficient (κ) shows the similar tendency with the permeability which is another kind of fouling index. It is verified that the coefficient has been validated as the new index for diagnosis of the fouling progress as well as the prediction of membrane fouling. [ABSTRACT FROM AUTHOR]

Binding energies of positively and negatively charged magneto excitons are investigated by using the variational procedure within the single band effective mass approximation. A linear Rashba spin-orbit coupling module with the position dependent electron is included in our calculations in order to study the change in spin-orbit splitting energy. In continuation, the interband optical transition, with and without the exciton, is computed as a function of well width. The valence-band anisotropy is included in our theoretical model by using different hole masses in different spatial directions. It is observed that (i) negative trions are found to have a higher binding energy than positive trions, (ii) the exciton binding energy and the interband emission energy both increase when the well width is decreased and (iii) the effect of exciton has influence on the interband emission energy. The results of the present investigation are found to be in good agreement with the recently published results. [ABSTRACT FROM AUTHOR]

In this paper, a new systematic design methodology has been developed for the simultaneous energy and water minimization in multiple-contaminant systems that also feature maximum re-use of water. In addition to allowing re-use of water in multiple-contaminant systems, issues about heat losses and flowrate changes inside unit operations have also been incorporated in this new design method. To implement such a design, two new design aspects are introduced; new method for "Non-isothermal Mixing" point identification and new "Separate System" generation. The first aspect involves "non-isothermal mixing", which enables direct heat recovery between water streams, and therefore allows the reduction of the number of heat transfer units. The other aspect is the generation of "separate system "in heat exchanger network design. The flexibility of mixing and splitting of water streams allows separate systems to be created as a cost-effective series of heat-exchanger units between freshwater and wastewater streams. The new design aspects have been illustrated with two examples. [ABSTRACT FROM AUTHOR]

The main objective of this study was to suggest a feasible, effective process for the reduction of sewage sludge using ozone oxidation catalysed by metal ion. A series of lab-scale experiments was conducted to select a suitable catalyst and its proper dose to achieve optimum sludge reduction. Using a central composite design under response surface methodology (RSM), system optimization with respect to sludge reduction and cost-effectiveness was performed by varying the independent parameters: dosages of ozone and ions. Five metal ions, Mn2+, Fe2+, Zn2+, Cu2+, and Al3+, were tested, and the manganese ion showed the highest sludge reduction, as measured by a decrease in total suspended solids. The ozone/Mn combination achieved approximately twice as much sludge reduction as the ozonation alone. Furthermore, the Mn dose of 10 mg/g-TS (total solids) resulted in the highest sludge reduction efficiency among the different doses, which ranged from 0 to 20 mg-Mn/g-TS. The predicted efficiency of sewage sludge reduction using the RSM was found to agree well with the experimental results, and the statistical analyses predicted optimum ranges for the doses of ozone and Mn ions, taking into account the overall cost for sewage sludge treatment. [ABSTRACT FROM AUTHOR]

Wastewater treatment plants (WWTP) are notorious for poor data quality and sensor reliability due to the hostile environment in which the measurement equipment has to function. In this paper, a structured residual approach with maximum sensitivity (SRAMS) based on the redundancy of the measurements is used to detect, identify and reconstruct single and multiple sensor faults in a single reactor for high activity ammonia removal over nitrite (SHARON) process. SRAMS is based on inferences, which are insensitive to the faults in the sensor of interest and sensitive to faults in the other sensors. It is used for four types of sensor failure detection: bias, drift, complete failure and precision degradation. The application of sensor validation shows that single and multiple sensor faults can be detected and that the fault magnitude and fault type can be estimated by the reconstruction scheme. This sensor validation method is not limited by the type or application of the considered sensors. The methodology can thus easily be applied for sensor surveillance of other continuously measuring sensors and analysers. [ABSTRACT FROM AUTHOR]

This paper proposes a new process monitoring method using dynamic independent component analysis (ICA). ICA is a recently developed technique to extract the hidden factors that underlie sets of measurements, whereas principal component analysis (PCA) is a dimensionality reduction technique in terms of capturing the variance of the data. Its goal is to find a linear representation of non-Gaussian data so that the components are statistically independent. PCA aims at finding PCs that are uncorrelated and are linear combinations of the observed variables, while ICA is designed to separate the ICs that are independent and constitute the observed variables. The dynamic ICA monitoring method is applying ICA to the augmenting matrix with time-lagged variables. The dynamic monitoring method was applied to detect and monitor disturbances in a full-scale biological wastewater treatment (WWTP), which is characterized by a variety of dynamic and non-Gaussian characteristics. The dynamic ICA method showed more powerful monitoring performance on a WWTP application than the dynamic PCA method since it can extract source signals which are independent of time and cross-correlation of variables. [ABSTRACT FROM AUTHOR]

This paper proposes a new process monitoring method using dynamic independent component analysis (ICA). ICA is a recently developed technique to extract the hidden factors that underlie sets of measurements, whereas principal component analysis (PCA) is a dimensionality reduction technique in terms of capturing the variance of the data. Its goal is to find a linear representation of non-Gaussian data so that the components are statistically independent. PCA aims at finding PCs that are uncorrelated and are linear combinations of the observed variables, while ICA is designed to separate the ICs that are independent and constitute the observed variables. The dynamic ICA monitoring method is applying ICA to the augmenting matrix with time-lagged variables. The dynamic monitoring method was applied to detect and monitor disturbances in a full-scale biological wastewater treatment (WWTP), which is characterized by a variety of dynamic and non-Gaussian characteristics. The dynamic ICA method showed more powerful monitoring performance on a WWTP application than the dynamic PCA method since it can extract source signals which are independent of time and cross-correlation of variables. [ABSTRACT FROM AUTHOR]

Based on a quantitative traits locus (QTL) study using a F2 intercross between Landrace and Korean native pigs, a significant QTL affecting teat numbers in SSC7 was identified. The strong positional candidate gene, TBC1D21, was selected due to its biological function for epithelial mesenchymal cell development. Sequence analysis revealed six single nucleotide polymorphisms (SNPs) in the TBC1D21 gene. Among these, two SNP markers, one silent mutation (SNP01) for g.13,050A>G and one missense mutation (SNP04) for c.829A>T (S277C), were genotyped and they showed significant associations with teat number traits (p value = 6.38E-05 for SNP01 and p value = 1.06E-07 for SNP04 with total teat numbers). Further functional validation of these SNPs could give valuable information for understanding the teat number variation in pigs.

A new model-calibration method has been proposed to solve the problems associated with parameter subset selection and parameter estimation of the activated sludge model (ASM). We propose the use of a statistical methodology for reasonable parameter selection and parameter estimation that consists of sensitivity analysis, similarity measures, hierarchical clustering and response surface methods (RSM). The introduction of effluent quality index (EQI) can reduce all of the outputs of the ASM model into one factor. The EQI was used to calculate a sensitivity matrix. Then, the hierarchical clustering algorithm was used for parameter subset selection. This selection was based on a similarity measure using the sensitivity matrix and was used to reduce the number of model parameters by selecting only one parameter per cluster group (parameter subset selection step). Lastly, a RSM analysis was conducted in order to determine the optimal parameter values. This study was conducted in order to develop a new statistical framework that can greatly reduce the computational effort required to find the optimal solution by reducing the number of parameters. The experimental results indicated that the calibrated model can improve the prediction quality of the ASM model and the efficiency of the modeling., (Copyright © 2010 Elsevier B.V. All rights reserved.)

This paper proposes a new fault detection and isolation (FDI) method. This method monitors the distribution of process data and detects changes in this distribution, which reflect changes in the corresponding operating condition. A modified dissimilarity index and a FDI technique are defined to quantitatively evaluate the difference between data sets. This technique considers the importance of each transformed variable in the multivariate system. The FDI technique is applied to a benchmark simulation and to data from a real wastewater treatment plant. Simulation results show that it immediately detects disturbances and automatically distinguishes between serious and minor anomalies for various types of fault. The method not only detects the disturbances, but also isolates the scale of the disturbance, facilitating the interpretation of the disturbance source. The proposed monitoring technique is found to be appropriate for analyzing the biological wastewater treatment process, which is characterized by a variety of fault and disturbance sources and non-stationary characteristics.

A new rehabilitation training system, designated as a virtual cycling system, was developed to improve postural balance control by combining virtual reality (VR) technology with a bicycle. Several parameters including path deviation, path deviation velocity, cycling time, and head movement were extracted and evaluated to quantify the extent of control. The system was effective as a training device and, in addition, the technology might have a wider applicability to the rehabilitation field.