• Korean Journal of Agricultural and Forest Meteorology
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• v.6 no.2
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• pp.71-84
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• 2004

There is a growing demand for agrometeorological information that end-users can use and not just interesting information. lo achieve this, each region/community needs to develop and provide localized climate and weather information for growers. Additionally, provide tools to help local users interpret climate forecasts issued by the National Weather Service in the country. Real time information should be provided for farmers, including some basic data. An ideal agrometeorological information system includes several components: an efficient data measuring and collection system; a modern telecommunication system; a standard data management processing and analysis system; and an advanced technological information dissemination system. While it is conventional wisdom that, Internet is and will play a major role in the delivery and dissemination of agrometeorological information, there are large gaps between the "information rich" and the "information poor" countries. Rural communities represent the "last mile of connectivity". For some time to come, TV broadcast, radio, phone, newspaper and fax will be used in many countries for communication. The differences in achieving this among countries arise from the human and financial resources available to implement this information and the methods of information dissemination. These differences must be considered in designing any information dissemination system. Experience shows that easy across to information more tailored to user needs would substantially increase use of climate information. Opportunities remain unexplored for applications of geographical information systems and remote sensing in agro meteorology.e sensing in agro meteorology.

• Journal of Life Science
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• v.26 no.1
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• pp.34-41
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• 2016

Black chokeberries (scientific name Aronia melanocarpa) have been reported to have major effects due to anti-oxidant, anti-inflammatory, and anti-cancer capabilities. In this study, we investigated the anti- wrinkle effects of A. melanocarpa, including collagenase inhibition effects and their molecular biological mechanisms, such as oxidative stress-induced matrix metalloproteinase (MMP), mitogen-activated protein (MAP) kinase, and activator protein (AP)-1 expression and/or phosphorylation. In collagenase inhibition activity, the ethyl acetate fraction of black chokeberry (AE) was 77.2% at a concentration of 500 μg/ml, which was a significant result compared to that of Epigallocatechin gallate (positive control, 83.9% in 500 μg/ml). In the reactive oxygen species (ROS) assay, the AE produced 78% of ROS in 10 μg/ml and 70% of ROS in 75 μg/ml, which was a much lower percentage than the ROS production of H₂O₂-induced CCRF S-180II cells. In the MTT assay, cell viability was increased dose-dependently with AE in H₂O₂-induced cells. In protein expression by western blot assay, the AE suppressed the expression and phosphorylation of MMPs (MMP-1, -3, -9), MAPK (ERK, JNK, and p38), and AP-1 (c-Fos and c-Jun), and expressed the pro-collagen type I in H₂O₂-induced cells. These results suggest that black chokeberries have anti-wrinkle and collagen-production effects, and they may be used in applications for material development in the functional food and cosmetic industries.

• Journal of Dairy Science and Biotechnology
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• v.33 no.2
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• pp.111-118
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• 2015

Probiotic, prebiotic, and synbiotic substances as well as microorganisms were added to infant formula in an attempt to influence the intestinal microflora with an aim to stimulate the growth of lactic acid bacteria, especially bifidobacteria and lactobacilli. Over the last 10 years, new synbiotic infant formulas containing probiotics and prebiotics have been proposed in order to simulate the effect of breast-feeding on the intestinal microflora. Owing to their synergistic effect, the new synbiotics are expected to be more helpful than using probiotics and prebiotics individually. Maintenance of the viability of the probiotics during food processing and the passage through the gastrointestinal tract should be the most important consideration, since a sufficient number of bacteria ($10^8cfu/g$) should reach the intended location to have a positive effect on the host. Storage conditions and the processing technology used for the manufacture of products such as infant formula adversely affect the viability of the probiotics. When an appropriate and cost-effective microencapsulation methodology using the generally recognized as safe (GRAS) status and substances with high biological value are developed, the quality of infant formulas would improve. The effect of probiotics may be called a double-effect, where one is an immunomodulatory effect, induced by live probiotics that advantageously alter the gastrointestinal microflora, and the other comprises anti-inflammatory responses elicited by dead cells. At present, a new terminology is required to define the dead microorganisms or crude microbial fractions that positively affect health. The term "paraprobiotics" (or ghost probiotics) has been proposed to define dead microbial cells (not damaged or broken) or crude cell extracts (i.e., cell extracts with complex chemical composition) that are beneficial to humans and animals when a sufficient amount is orally or topically administered. The fecal microflora of bottle-fed infants is altered when the milk-based infant formula is supplemented with probiotics or prebiotics. Thus, by increasing the proportion of beneficial bacteria such as bifidobacteria and lactobacilli, prebiotics modify the fecal microbial composition and accordingly regulate the activity of the immune system. Therefore, considerable attention has been focused on the improvement of infant formula quality such that its beneficial effects are comparable to those of human milk, using prebiotics such as inulin and oligosaccharides and potential specific probiotics such as bifidobacteria, which selectively stimulate the proliferation of beneficial bacteria in the microflora and the indigenous intestinal metabolic activity of the microflora.

• Journal of Life Science
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• v.31 no.9
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• pp.818-826
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• 2021

5-Aminolevulinic acid phosphate (5-ALA-p) is a substance obtained by eluting 5-ALA (a natural delta amino acid) with aqueous ammonia, adding phosphoric acid to the eluate, and then adding acetone to confer properties suitable for use in photodynamic therapy applications. However, its pharmacological efficacy, including potential mechanisms of antioxidant and anti-inflammatory reactions, remains unclear. This study aimed to investigate the effects of 5-ALA-p on oxidative and inflammatory stresses in lipopolysaccharide (LPS)-stimulated RAW 264.7 cells. Our data showed that 5-ALA-p significantly inhibited excessive phagocytic activity via LPS and attenuated oxidative stress in LPS-treated RAW 264.7 cells. Furthermore, 5-ALA-p improved mitochondrial biogenesis reduced by LPS, suggesting that 5-ALA-p restores mitochondrial damage caused by LPS. Additionally, 5-ALA-p significantly suppressed the release of nitric oxide (NO) and pro-inflammatory cytokines, such as tumor necrosis factor α (TNF-α), interleukin (IL)-1β, and IL-6, which are associated with the inhibition of inducible NO synthase and respective cytokine expression. Furthermore, 5-ALA-p reduced the nuclear translocation of nuclear factor-kappa B (NF-κB) and inhibited phosphorylation of mitogen-activated protein kinases (MAPKs), indicating that the anti-inflammatory effect of 5-ALA-p is mediated through the suppression of NF-κB and MAPK signaling pathways. Based on these results, 5-ALA-p may serve as a potential candidate to reduce inflammation and oxidative stress.

• Korean Chemical Engineering Research
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• v.61 no.4
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• pp.555-560
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• 2023

Conventional aqueous amine-based CO₂ capture has a problem in that a large amount of renewable energy is required for CO₂ stripping and solvent regeneration in its industrial applications. This work proposes a water-lean absorbent that can reduce regeneration energy by lowering the water content in the absorbent with high absorption capacity for CO₂. To this purpose, this water-lean solvent introduced NMP (N-methyl-2-pyrrolidone), which has a higher physical solubility in CO₂ and a low specific heat capacity comparing to water, along with 3-methylaminopropylamine (MAPA), a diamine, into the absorbent. The circulating absorption capacity and absorption rate for CO₂ of this water-lean solvent were measured using a packed tower. When NMP was added to the absorbent, the absorption rate was improved. In the case of the absorbent containing 2.5M MAPA was used, the maximum circulating absorption capacity was obtained when 10 wt% of NMP was included in absorbent. The overall mass transfer coefficient increased as the concentration of NMP increased. However, at loading values higher than 0.5, the increment in mass transfer coefficient decreased as the concentration of NMP increased. When the lean loading value is low, the mass transfer resistance due to viscosity of the absorbent is low, so the overall mass transfer coefficient increases with the addition of NMP. However, as the lean loading value increases, the viscosity of the absorbent increases, and the diffusivity of CO₂ and MAPA decreases, resulting in sharply decreasing of the overall mass transfer coefficient.

• Journal of Life Science
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• v.34 no.5
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• pp.339-355
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• 2024

The pulmonary system is a highly complex system that can only be understood by integrating its functional and structural aspects. Hence, in vivo animal models are generally used for pathological studies of pulmonary diseases and the evaluation of inhalation toxicity. However, to reduce the number of animals used in experimentation and with the consideration of animal welfare, alternative methods have been extensively developed. Notably, the Organization for Economic Co-operation and Development (OECD) and the United States Environmental Protection Agency (USEPA) have agreed to prohibit animal testing after 2030. Therefore, the latest advances in biotechnology are revolutionizing the approach to developing in vitro inhalation models. For example, lung organ-on-a-chip (OoC) and organoid models have been intensively studied alongside advancements in three-dimensional (3D) bioprinting and microfluidic systems. These modeling systems can more precisely imitate the complex biological environment compared to traditional in vivo animal experiments. This review paper addresses multiple aspects of the recent in vitro modeling systems of lung OoC and organoids. It includes discussions on the use of endothelial cells, epithelial cells, and fibroblasts composed of lung alveoli generated from pluripotent stem cells or cancer cells. Moreover, it covers lung air-liquid interface (ALI) systems, transwell membrane materials, and in silico models using artificial intelligence (AI) for the establishment and evaluation of in vitro pulmonary systems.

• Information Systems Review
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• v.16 no.3
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• pp.161-177
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• 2014

Corporate credit rating assessment consists of complicated processes in which various factors describing a company are taken into consideration. Such assessment is known to be very expensive since domain experts should be employed to assess the ratings. As a result, the data-driven corporate credit rating prediction using statistical and artificial intelligence (AI) techniques has received considerable attention from researchers and practitioners. In particular, statistical methods such as multiple discriminant analysis (MDA) and multinomial logistic regression analysis (MLOGIT), and AI methods including case-based reasoning (CBR), artificial neural network (ANN), and multiclass support vector machine (MSVM) have been applied to corporate credit rating.2) Among them, MSVM has recently become popular because of its robustness and high prediction accuracy. In this study, we propose a novel optimized MSVM model, and appy it to corporate credit rating prediction in order to enhance the accuracy. Our model, named 'GAMSVM (Genetic Algorithm-optimized Multiclass Support Vector Machine),' is designed to simultaneously optimize the kernel parameters and the feature subset selection. Prior studies like Lorena and de Carvalho (2008), and Chatterjee (2013) show that proper kernel parameters may improve the performance of MSVMs. Also, the results from the studies such as Shieh and Yang (2008) and Chatterjee (2013) imply that appropriate feature selection may lead to higher prediction accuracy. Based on these prior studies, we propose to apply GAMSVM to corporate credit rating prediction. As a tool for optimizing the kernel parameters and the feature subset selection, we suggest genetic algorithm (GA). GA is known as an efficient and effective search method that attempts to simulate the biological evolution phenomenon. By applying genetic operations such as selection, crossover, and mutation, it is designed to gradually improve the search results. Especially, mutation operator prevents GA from falling into the local optima, thus we can find the globally optimal or near-optimal solution using it. GA has popularly been applied to search optimal parameters or feature subset selections of AI techniques including MSVM. With these reasons, we also adopt GA as an optimization tool. To empirically validate the usefulness of GAMSVM, we applied it to a real-world case of credit rating in Korea. Our application is in bond rating, which is the most frequently studied area of credit rating for specific debt issues or other financial obligations. The experimental dataset was collected from a large credit rating company in South Korea. It contained 39 financial ratios of 1,295 companies in the manufacturing industry, and their credit ratings. Using various statistical methods including the one-way ANOVA and the stepwise MDA, we selected 14 financial ratios as the candidate independent variables. The dependent variable, i.e. credit rating, was labeled as four classes: 1(A1); 2(A2); 3(A3); 4(B and C). 80 percent of total data for each class was used for training, and remaining 20 percent was used for validation. And, to overcome small sample size, we applied five-fold cross validation to our dataset. In order to examine the competitiveness of the proposed model, we also experimented several comparative models including MDA, MLOGIT, CBR, ANN and MSVM. In case of MSVM, we adopted One-Against-One (OAO) and DAGSVM (Directed Acyclic Graph SVM) approaches because they are known to be the most accurate approaches among various MSVM approaches. GAMSVM was implemented using LIBSVM-an open-source software, and Evolver 5.5-a commercial software enables GA. Other comparative models were experimented using various statistical and AI packages such as SPSS for Windows, Neuroshell, and Microsoft Excel VBA (Visual Basic for Applications). Experimental results showed that the proposed model-GAMSVM-outperformed all the competitive models. In addition, the model was found to use less independent variables, but to show higher accuracy. In our experiments, five variables such as X7 (total debt), X9 (sales per employee), X13 (years after founded), X15 (accumulated earning to total asset), and X39 (the index related to the cash flows from operating activity) were found to be the most important factors in predicting the corporate credit ratings. However, the values of the finally selected kernel parameters were found to be almost same among the data subsets. To examine whether the predictive performance of GAMSVM was significantly greater than those of other models, we used the McNemar test. As a result, we found that GAMSVM was better than MDA, MLOGIT, CBR, and ANN at the 1% significance level, and better than OAO and DAGSVM at the 5% significance level.