• Proceedings of the KSME Conference
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• 2008.11b
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• pp.2816-2821
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• 2008

This paper investigates the flow field and organism concentration in a UV disinfection channel in which vertical ultraviolet lamps are arranged in a staggered configuration. Turbulence is described by low Reynolds number ${\kappa}-{\varepsilon}$ turbulence model and standard ${\kappa}-{\varepsilon}$ turbulence model, respectively. P-1 method has been employed to solve the radiative transfer equation. The obtained incident radiation is used to compute the inactivation term in the species equation. The CFD results are in good agreement with the existing experimental data for the UV channel. For the flow field, the low-Reynolds number ${\kappa}-{\varepsilon}$ model is superior to the standard ${\kappa}-{\varepsilon}$ model. The approach velocity has a significant effect on the disinfection efficiency. The organism concentration at the outlet decreases fast to a low inlet velocity.

• BMB Reports
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• v.37 no.1
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• pp.83-92
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• 2004

As a result of the enormous amount of information that has been collected with E. coli over the past half century (e.g. genome sequence, mutant phenotypes, metabolic and regulatory networks, etc.), we now have detailed knowledge about gene regulation, protein activity, several hundred enzyme reactions, metabolic pathways, macromolecular machines, and regulatory interactions for this model organism. However, understanding how all these processes interact to form a living cell will require further characterization, quantification, data integration, and mathematical modeling, systems biology. No organism can rival E. coli with respect to the amount of available basic information and experimental tractability for the technologies needed for this undertaking. A focused, systematic effort to understand the E. coli cell will accelerate the development of new post-genomic technologies, including both experimental and computational tools. It will also lead to new technologies that will be applicable to other organisms, from microbes to plants, animals, and humans. E. coli is not only the best studied free-living model organism, but is also an extensively used microbe for industrial applications, especially for the production of small molecules of interest. It is an excellent representative of Gram-negative commensal bacteria. E. coli may represent a perfect model organism for systems biology that is aimed at elucidating both its free-living and commensal life-styles, which should open the door to whole-cell modeling and simulation.

• Korean System Dynamics Review
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• v.7 no.2
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• pp.215-226
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• 2006

A conceptual system dynamics model is developed to represent the dynamic mechanism between the number of hepatitis B virus and the defense system of the body. The simulation results shows that the model behaves within the reasonable ranges. The developed conceptual model is a first attempt to quantify the dynamic mechanisms of the hepatitis B virus, where only feedback structures are considered without bio-organism data. The next step would be to incorporate the model with bio-organism theory and to carry out case studies to identify personal characteristics. Since the current model is a conceptual model where quantitative results are not based on the sound background, the usage is limited only within the qualitative basis. It could be a effective educational tool for the patients. It also shows what-to-do lists in order to be used for forecast purposes.

• BMB Reports
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• v.52 no.4
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• pp.250-258
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• 2019

Parkinson's disease (PD) is a common neurodegenerative disorder characterized by selective and progressive loss of dopaminergic neurons. Genetic and environmental risk factors are associated with this disease. The genetic factors are composed of approximately 20 genes, such as SNCA, parkin, PTEN-induced kinase1 (pink1), leucine-rich repeat kinase 2 (LRRK2), ATP13A2, MAPT, VPS35, and DJ-1, whereas the environmental factors consist of oxidative stress-induced toxins such as 1-methyl-4-phenyl-1, 2, 3, 6-tetrahydropyridine (MPTP), rotenone, and paraquat. The analyses of their functions and mechanisms have provided important insights into the disease process, which has demonstrated that these factors cause oxidative damage and mitochondrial dysfunction. The most invaluable studies have been performed using disease model organisms, such as mice, fruit flies, and worms. Among them, Drosophila melanogaster has emerged as an excellent model organism to study both environmental and genetic factors and provide insights to the pathways relevant for PD pathogenesis, facilitating development of therapeutic strategies. In this review, we have focused on the fly model organism to summarize recent progress, including pathogenesis, neuroprotective compounds, and newer approaches.

• Proceedings of the Korea Society of Environmental Toocicology Conference
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• 2003.05a
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• pp.146-147
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• 2003

The free-living nematode, Caenorhabditis elegans (C. elegans) has been adopted as a multicellular biosensor of biological toxicity for alkylphenol, organotin compounds and heavy metals. To adopt as a biosensor, suitability to assess must be fulfilledthrough several criteria; the organism must be sensitive to the testing toxicants, easy to manage in the laboratory and available throughout the year. C. elegans widely used as a simple multicellular organism in developmental biology studies and satisfies all these criteria, and its culture conditions, developmental staging, anatomy and genetic properties are well defined. In addition, researchers can take advantage of the worm's short life cycle, low cost and little individual variation. Moreover, genomic sequencing of C. elegans has recently been completed. With these aspectsof the organism, C. elegans become a more potent model organism for basic and applied bioassays.

• Korea Journal of Hospital Management
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• v.19 no.4
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• pp.21-33
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• 2014

This study was conducted to propose an insight into the appropriateness of hospital length of stay(LOS) by developing a severity-adjusted LOS model for patients with pneumonia, organism unspecified. The pneumonia risk-adjustment model developed in this paper is based upon the 2006-2010 the Korean National Hospital Discharge in-depth Injury Survey. Decision tree analysis revealed that age, admission type, insurance type, and the presence of additional disorders(pleural effusion, respiratory failure, sepsis, congestive heart failure etc.) were major factors affecting the severity-adjusted model using the Clinical Classifications Software(CCS). Also there was a difference in LOS among the regional hospitals, especially the hospital LOS has not been efficiently managed in Gyeongsangbuk-do, Jeollanam-do, Jeollabuk-do, Daejeon, and Busan. To appropriately manage hospital LOS, reliable statistical information about severity-adjusted LOS should be generated on a national level to make sure that hospitals voluntarily reduce excessive LOS and manage main causes of delayed discharge.

• The KIPS Transactions:PartB
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• v.12B no.3 s.99
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• pp.349-356
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• 2005

Artificial Organism-used application areas are expanding at a break-neck speed with a view to getting things done in a dynamic and Informal environment. A use of general programming or traditional hi methods as the representation of Artificial Organism behavior knowledge in these areas can cause problems related to frequent modifications and bad response in an unpredictable situation. Strategies aimed at solving these problems in a machine-learning fashion includes Genetic Programming and Evolving Neural Networks. But the learning method of Artificial-Organism is not good yet, and can't represent life in the environment. With this in mind, this research is designed to come up with a new behavior evolution model. The model represents behavior knowledge with Classification Rules and Enhanced Backpropation Neural Networks and discriminate the denomination. To evaluate the model, the researcher applied it to problems with the competition of Artificial-Organism in the Simulator and compared with other system. The survey shows that the model prevails in terms of the speed and Qualify of learning. The model is characterized by the simultaneous learning of classification rules and neural networks represented on chromosomes with the help of Genetic Algorithm and the consolidation of learning ability caused by the hybrid processing of the classification rules and Enhanced Backpropagation Neural Network.

• Toxicological Research
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• v.24 no.4
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• pp.235-243
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• 2008

While in some instances, loss of diversity results from acute toxicity (e.g. major pollution incidents), in most cases it results from long-term sub-lethal effects that alter the relative competitive ability and fitness of certain organisms. In such cases the sub-lethal effects will cause a physiological response in the organism that ultimately leads to community level changes. Very sensitive tools are now available to study sub-lethal responses at the molecular level. However, relating such laboratory measurements to ecological effects represents a substantial challenge that can only be met by investigation at all scales (molecular, individual organism and community level) with an appropriate group of organisms. Among the various in vertebrates which can be used as model organisms in such a way, the soil nematode, Caenorhabditis elegans appear to be a promising biological model to diagnose environmental quality. This paper reviews the current status of multilevel biomarkers in environmental toxicology, and C. elegans as promising organisms for this approach.

• Asia pacific journal of information systems
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• v.22 no.4
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• pp.51-73
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• 2012

Social network services based on openness, connectedness, and mass participation are reshaping many aspects of how companies conduct business and create value for their customers. For instance, Facebook and Twitter are expected to play a pivotal role as a new communication channel through which companies-forge close relationships with their customers for co-creation of value for mutual benefits. Given the potential of social network services, it is not surprising that many companies have strategically invested in social network services to reach out to customers. Despite the growing interest in social network services as a platform to connect companies and their customers, few guidelines exist about how managers can effectively utilize social network services in forging relationships with their customers. As such, scholars should pay greater attention to how firms can successfully develop relationships with their customers on social network services. In particular, this study employs the S-O-R (stimulus-organism-response) framework as a theoretical lens to develop a research model that explains customers' participation in the value co-creation platform that companies opened on Twitter. According to the S-O-R framework, certain types of individuals' behaviors can be best understood based on a causal link from environmental stimulus to organism, and response. We apply the S-O-R framework to understand how ubiquitous connectivity (stimuli) can influence customers' experience (organism) with companies on Twitter, which in turn influence their participation behavior (response). Two steps have been undertaken to empirically test the research model. First, we conducted a content analysis of tweets written by customers who follow companies on Twitter. As a result, we found event/promotion participation, company support, and giving feedback as three specific types of customer participation behavior. Second, we conducted a web-based survey to test research hypotheses in the research model. Participations in the survey were solicited to customers who followed companies on Twitter. As a result, a total of 115 respondents have completed the survey. Data were analyzed using the partial least square (PLS) technique. The results of data analysis suggest that ubiquitous connectivity (stimuli) had strong positive effects on perceive usefulness, perceived enjoyment, and perceived intimacy (organism). Perceived intimacy showed positive effects on customer participation behavior (response), such as event participation, company support, and giving feedback. Perceived enjoyment was found to have strong positive effects on company support and giving feedback. On the other hand, perceived usefulness did not have significant impacts on the three types of customer participation behavior.

• Journal of Distribution Science
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• v.20 no.4
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• pp.33-50
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• 2022

Purpose: This pilot study aims to conceptualize a new green marketing mix for retail consumers based on Stimulus-Organism-Response (SOR) model. Moreover, it also aims to conceptualize a testable research model of new green marketing mix with consumers' green purchasing behavior, and to validate the measurement model with traditional as well as modern suggested validating techniques. Research design, data and methodology: A pilot test data from 75 respondents of retail buyers of energy-efficient electric appliances in Pakistan were tested for the confirmatory factor analysis (CFA) by examining a measurement model of the construct through different validation techniques (like Composite Reliability, McDonald's Omega (ω), rho (ρA), HTMT, etc.) as heretofore these scales were not validated through these modern methods. Results: The results revealed that the instrument has a certain degree of reliability and validity through different validating techniques. All the measurement items reach the suggested threshold values. Conclusions: Therefore, this study conceptualized an integrated framework of all the three stakeholders of the environment (government, companies, and public or consumers) to achieve environmental sustainability. Hence, future studies can extend these findings and conduct a full-scale study to establish an empirical relationship between the 5G's of green marketing for retailing businesses and consumers' green purchase behavior.