• Journal of Veterinary Science
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• v.25 no.4
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• pp.42.1-42.12
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• 2024

Importance: Bovine mastitis, predominantly associated with gram-positive Staphylococcus aureus, poses a significant threat to dairy cows, leading to a decline in milk quality and volume with substantial economic implications. Objective: This study investigated the incidence, virulence, and antibiotic resistance of S. aureus associated with mastitis in dairy cows. Methods: Fifty milk-productive cows underwent a subclinical mastitis diagnosis, and the S. aureus strains were isolated. Genomic DNA extraction, sequencing, and bioinformatic analysis were performed, supplemented by including 124 S. aureus genomes from cows with subclinical mastitis to enhance the overall analysis. Results: The results revealed a 42% prevalence of subclinical mastitis among the cows tested. Genomic analysis identified 26 sequence types (STs) for all isolates, with Mexican STs belonging primarily to CC1 and CC97. The analyzed genomes exhibited multidrug resistance to phenicol, fluoroquinolone, tetracycline, and cephalosporine, which are commonly used as the first line of treatment. Furthermore, a similar genomic virulence repertoire was observed across the genomes, encompassing the genes related to invasion, survival, pathogenesis, and iron uptake. In particular, the toxic shock syndrome toxin (tss-1) was found predominantly in the genomes isolated in this study, posing potential health risks, particularly in children. Conclusion and Relevance: These findings underscore the broad capacity for antibiotic resistance and pathogenicity by S. aureus, compromising the integrity of milk and dairy products. The study emphasizes the need to evaluate the effectiveness of antibiotics in combating S. aureus infections.

• Annals of Hepato-Biliary-Pancreatic Surgery
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• v.26 no.1
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• pp.69-75
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• 2022

Backgrounds/Aims: Progressive familial intrahepatic cholestasis (PFIC) is an autosomal recessive inherited disease requiring liver transplantation (LT). The objective of this study was to investigate the clinicopathological features and posttransplant courses of seven LT recipients with PFIC. Methods: This was a retrospective single-center study of patients with PFIC who underwent LT from January 2013 to June 2020. Results: Two and five patients were diagnosed with PFIC type 1 and type 2, respectively. For all seven patients, age of PFIC onset was at birth. Jaundice was present in all cases. Mean pretransplant total and direct bilirubin levels were 16.1 ± 8.1 mg/dL and 12.4 ± 6.2 mg/dL, respectively. Median patient age and body weight at LT were 10 months and 7 kg, respectively. Types of donors were mothers of patients in four and deceased donors in three. All five patients with PFIC type 2 recovered uneventfully. One patient each with PFIC type 1 underwent retransplantation due to graft failure or died due to multi-organ failure. Overall graft and patient survival rates at five years were 66.7% and 83.3%, respectively. Bile salt export pump immunohistochemical staining showed normal canalicular expression in two patients with PFIC type 1, focal loss in two patients with PFIC type 2, and total loss in three patients with PFIC type 2. Conclusions: LT is currently the only effective treatment for PFIC-associated end-stage liver diseases. It is mandatory to perform regular follow-up due to the risk of complications including steatohepatitis, especially for patients with PFIC type 1.

• Journal of Veterinary Science
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• v.25 no.5
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• pp.62.1-62.13
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• 2024

Importance: Antimicrobial resistance (AMR) is a serious public health threat. AMR bacteria and their resistance determinants in food can be transmitted to humans through the food chain and by direct contact and disseminate directly to the environment. Objective: This study examined the AMR characteristics and transferable R plasmids in Escherichia coli isolated from meat ducks raised in an open-house system. Methods: One hundred seventy-seven (n = 177) commensal E. coli were examined for their antimicrobial susceptibilities and horizontal resistance transfer. The plasmids were examined by PCR-based plasmid replicon typing (PBRT) and plasmid multi-locus sequence typing (pMLST). Results: The highest resistance rate was found against ampicillin (AMP, 83.0%) and tetracycline (TET, 81.9%), and most isolates exhibited multidrug resistance (MDR) (86.4%). The R plasmids were conjugally transferred when TET (n = 4), AMP (n = 3), and chloramphenicol (n = 3) were used as a selective pressure. The three isolates transferred resistance genes either in AMP or TET. The blaCTX-M1 gene resided on conjugative plasmids. Five replicon types were identified, of which Inc FrepB was most common in the donors (n = 13, 38.4%) and transconjugants (n = 16, 31.2%). Subtyping F plasmids revealed five distinct replicons combinations, including F47:A-:B- (n = 2), F29:A-:B23 (n = 1), F29:A-:B- (n = 1), F18:A-B:- (n = 1), and F4:A-:B- (n = 1). The chloramphenicol resistance was significantly correlated with the other AMR phenotypes (p < 0.05). Conclusions and Relevance: The meat ducks harbored MDR E. coli and played an important role in the environmental dissemination of AMR bacteria and its determinants. This confirms AMR as a health issue, highlighting the need for routine AMR monitoring and surveillance of meat ducks.

• Journal of Veterinary Science
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• v.25 no.5
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• pp.67.1-67.8
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• 2024

Importance: Carbapenem-resistant Enterobacteriaceae are emerging as a global public health risk. Therefore, assessing the prevalence of carbapenem-resistant Escherichia coli (CRE) in both humans and animals is important. Objective: We aimed to ascertain the occurrence and characteristics of CRE isolated from companion animals, dogs and cats. Methods: E. coli strains were tested for antimicrobial susceptibility using the broth microdilution technique. Antimicrobial resistance genes were detected by polymerase chain reaction and sequencing analysis. The molecular characteristics of CRE were determined using multi-locus sequence typing, replicon typing, and pulsed-field gel electrophoresis (PFGE). Results: In total, 13 CRE isolates (0.13%) were identified from dogs possessing bla_NDM-5 along with β-lactamase genes, mostly blaCMY-2 (92.2%) and blaTEM-1 (53.8%). The commonly observed mutations were S83L and D87N in gyrA, S80I in parC, and S458A in parE. CRE carried non-beta-lactam resistance genes, with the majority being tet(B) (100%), sul (84.6%), and aac(3)-II (53.8%). Nine different PFGE patterns (P1-P9), IncX3-type plasmids (69.2%), and ST410 (84.6%) were predominantly detected. Conclusions and Relevance: This investigation provides significant insight into the prevalence and molecular characteristics of bla_NDM-5-carrying E. coli in dogs. The co-existence of bla_NDM-5 and other antimicrobial resistance genes in E. coli potentially poses severe health hazards to humans.

• Journal of Korea Water Resources Association
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• v.40 no.10
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• pp.769-781
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• 2007

Factor analysis has been usually employed in reducing quantity of data and summarizing information on a system or phenomenon. In this analysis methodology, variables are grouped into several factors by consideration of statistic characteristics, and the results are used for dropping variables which have lower weight than others. In this study, factor analysis was applied for extracting primary factors influencing multi-dam system operation in the Han River basin, where there are two multi-purpose dams such as Soyanggang Dam and Chungju Dam, and water has been supplied by integrating two dams in water use season. In order to fulfill factor analysis, first the variables related to two dams operation were gathered and divided into five groups (Soyanggang Dam: inflow, hydropower product, storage management, storage, and operation results of the past; Chungju Dam: inflow, hydropower product, water demand, storage, and operation results of the past). And then, considering statistic properties, in the gathered variables, some variables were chosen and grouped into five factors; hydrological condition, dam operation of the past, dam operation at normal season, water demand, and downstream dam operation. In order to check the appropriateness and applicability of factors, a multiple regression equation was newly constructed using factors as description variables, and those factors were compared with terms of objective function used in operation water resources optimally in a river basin. Reviewing the results through two check processes, it was revealed that the suggested approach provided satisfactory results. And, it was expected for extracted primary factors to be useful for making dam operation schedule considering the future situation and previous results.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.4 no.1
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• pp.11-26
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• 1984

The aim of this study is to establish a synthetical optimal method that simultaneously analyze and design reinforced concrete flat slab-column structures involving multi-constraints and multi-design variables. The variables adopted in this mathematical models consist of design variables including sectional sizes and steel areas of frames, and analysis variable of the ratio of bending moment redistribution. The cost function is taken as the objective function in the formulation of optimal problems. A number of constraint equations, involving the ultimate limit state and the serviceability limit state, is derived in accordance with BSI CP110 requirements on the basis of limit state design theory. Both objective function and constraint equations derived from design variables and an analysis variable generally become high degree nonlinear problems. Using SLP as an analytical method of nonlinear optimal problems, an optimal algorithm is developed so as to analyze and design the structures considered in this study. The developed algorithm is directly applied to a few reinforced concrete flat slab-column structures to assure the validity of it and the possibility of optimization From the research it is found that the algorithm developed in this study is applicable to the optimization of reinforced concrete flat slab column structures and it converges to a optimal solution with 4 to 6 iterations regardless of initial variables. The result shows that an economical design can be possible when compared with conventional designs. It is also found that considering the ratio of bending moment redistribution as a variable is reasonable. It has a great effect on the composition of optimal sections and the economy of structures.

• Journal of Korean Society of Forest Science
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• v.112 no.4
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• pp.561-573
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• 2023

National forests have an advantage over private forests in terms of higher investment in capital, technology, and labor, allowing for more intensive management. As such, national forests are expected to serve not only as a strategic reserve of forest resources to address the long-term demand for timber but also to stably perform various essential forest functions demanded by society. However, most forest stands in the current national forests belong to the fourth age class or above, indicating an imminent timber harvesting period amid an imbalanced age class structure. Therefore, if timber harvesting is not conducted based on systematic management planning, it will become difficult to ensure the continuity of the national forests' diverse functions. This study was conducted to determine the optimal volume of timber production in the national forests to improve the age-class structure while sustainably maintaining their economic and public functions. To achieve this, the study first identified areas within the national forests suitable for timber production. Subsequently, a forest management planning model was developed using multi-objective linear programming, taking into account both the national forests' economic role and their public benefits. The findings suggest that approximately 488,000 hectares within the national forests are suitable for timber production. By focusing on management of these areas, it is possible to not only improve the age-class distribution but also to sustainably uphold the forests' public benefits. Furthermore, the potential volume of timber production from the national forests for the next 100 years would be around 2 million m³ per year, constituting about 44% of the annual domestic timber supply.

• Journal of Intelligence and Information Systems
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• v.26 no.2
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• pp.57-78
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• 2020

With the development of the Internet, consumers have had an opportunity to check product information easily through E-Commerce. Product reviews used in the process of purchasing goods are based on user experience, allowing consumers to engage as producers of information as well as refer to information. This can be a way to increase the efficiency of purchasing decisions from the perspective of consumers, and from the seller's point of view, it can help develop products and strengthen their competitiveness. However, it takes a lot of time and effort to understand the overall assessment and assessment dimensions of the products that I think are important in reading the vast amount of product reviews offered by E-Commerce for the products consumers want to compare. This is because product reviews are unstructured information and it is difficult to read sentiment of reviews and assessment dimension immediately. For example, consumers who want to purchase a laptop would like to check the assessment of comparative products at each dimension, such as performance, weight, delivery, speed, and design. Therefore, in this paper, we would like to propose a method to automatically generate multi-dimensional product assessment scores in product reviews that we would like to compare. The methods presented in this study consist largely of two phases. One is the pre-preparation phase and the second is the individual product scoring phase. In the pre-preparation phase, a dimensioned classification model and a sentiment analysis model are created based on a review of the large category product group review. By combining word embedding and association analysis, the dimensioned classification model complements the limitation that word embedding methods for finding relevance between dimensions and words in existing studies see only the distance of words in sentences. Sentiment analysis models generate CNN models by organizing learning data tagged with positives and negatives on a phrase unit for accurate polarity detection. Through this, the individual product scoring phase applies the models pre-prepared for the phrase unit review. Multi-dimensional assessment scores can be obtained by aggregating them by assessment dimension according to the proportion of reviews organized like this, which are grouped among those that are judged to describe a specific dimension for each phrase. In the experiment of this paper, approximately 260,000 reviews of the large category product group are collected to form a dimensioned classification model and a sentiment analysis model. In addition, reviews of the laptops of S and L companies selling at E-Commerce are collected and used as experimental data, respectively. The dimensioned classification model classified individual product reviews broken down into phrases into six assessment dimensions and combined the existing word embedding method with an association analysis indicating frequency between words and dimensions. As a result of combining word embedding and association analysis, the accuracy of the model increased by 13.7%. The sentiment analysis models could be seen to closely analyze the assessment when they were taught in a phrase unit rather than in sentences. As a result, it was confirmed that the accuracy was 29.4% higher than the sentence-based model. Through this study, both sellers and consumers can expect efficient decision making in purchasing and product development, given that they can make multi-dimensional comparisons of products. In addition, text reviews, which are unstructured data, were transformed into objective values such as frequency and morpheme, and they were analysed together using word embedding and association analysis to improve the objectivity aspects of more precise multi-dimensional analysis and research. This will be an attractive analysis model in terms of not only enabling more effective service deployment during the evolving E-Commerce market and fierce competition, but also satisfying both customers.

• Journal of Korean Association for Spatial Structures
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• v.4 no.2 s.12
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• pp.89-97
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• 2004

The objective of this study is the development of a scheme and discrete optimum design algorithm, which is based on the genetic algorithm. The algorithm can perform both scheme and size optimum designs of plane trusses. The developed Scheme genetic algorithm was implemented in a computer program. For the optimum design, the objective function is the weight of structures and the constraints are limits on loads and serviceability. The basic search method for the optimum design is the genetic algorithm. The algorithm is known to be very efficient for the discrete optimization. However, its application to the complicated structures has been limited because of the extreme time need for a number of structural analyses. This study solves the problem by introducing the size & scheme genetic algorithm operators into the genetic algorithm. The genetic process virtually takes no time. However, the evolutionary process requires a tremendous amount of time for a number of structural analyses. Therefore, the application of the genetic algorithm to the complicated structures is extremely difficult, if not impossible. The scheme genetic algorithm operators was introduced to overcome the problem and to complement the evolutionary process. It is very efficient in the approximate analyses and scheme and size optimization of plane trusses structures and considerably reduces structural analysis time. Scheme and size discrete optimum combined into the genetic algorithm is what makes the practical discrete optimum design of plane fusses structures possible. The efficiency and validity of the developed discrete optimum design algorithm was verified by applying the algorithm to various optimum design examples: plane pratt, howe and warren truss.

• Archives of design research
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• v.20 no.3 s.71
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• pp.61-72
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• 2007

Having started with "Space War", the first game produced by MIT in the 1960's, the gaming industry expanded rapidly and grew to a large size over a short period of time: the brand new games being launched on the market are found to contain many different elements making up a single content in that it is often called the 'the most comprehensive ultimate fruits' of the design technologies. This also translates into a large increase in the number of things which need to be considered in developing games, complicating the plans on the financial budget, the work force, and the time to be committed. Therefore, an approach for analyzing the elements which make up a game, computing the importance of each of them, and assessing those games to be developed in the future, is the key to a successful development of games. Many decision-making activities are often required under such a planning process. The decision-making task involves many difficulties which are outlined as follows: the multi-factor problem; the uncertainty problem impeding the elements from being "quantified" the complex multi-purpose problem for which the outcome aims confusion among decision-makers and the problem with determining the priority order of multi-stages leading to the decision-making process. In this study we plan to suggest AHP (Analytic Hierarchy Process) so that these problems can be worked out comprehensively, and logical and rational alternative plan can be proposed through the quantification of the "uncertain" data. The analysis was conducted by taking FPS (First Person Shooting) which is currently dominating the gaming industry, as subjects for this study. The most important consideration in conducting AHP analysis is to accurately group the elements of the subjects to be analyzed objectively, and arrange them hierarchically, and to analyze the importance through pair-wise comparison between the elements. The study is composed of 2 parts of analyzing these elements and computing the importance between them, and choosing an alternative plan. Among these this paper is particularly focused on the Delphi technique-based objective element analyzing and hierarchy of the FPS games.