• The Korean Journal of Pesticide Science
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• v.5 no.4
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• pp.27-32
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• 2001

Methanol extracts from 43 materials of 17 fruit trees were tested for their insecticidal activities toward five agricultural and four stored-product anthropod pests. Efficacy varied with insect species, plant species, and tissue sampled. At a concentration of 2,500 ppm, strong activity was observed with extracts of Chaenomeles sinensis and Punica granatum seeds against Myzus persicae adult females, Vitis vinifera seeds against Nilaparvata lugens adults, Citrus junos, Citrus paradisi, Cucumis melo Linne var. reticulatus, Diospyros kaki, Malus pumila var. dulcissima, Prunug persica, and V. vinifera seeds against Plutella xylostella, Citrus sinensis seeds against Spedoptera litura larvae, and Ch. sinensis and V. vinifera against Tetranychus urticae adults. Against four stored-product insect pests at 50 ppm, seed extracts of Ch. sinensis and V. vinifera against Sitophilus oryzae adults, and Ch. sinensis, C. junos, D. kaki, and V. vinifera against Callosobruchus chinensis adults gave over 80% mortality. Extracts of all samples exhibited little and no activity against Lasioderma serricorne adults and Plodia interpunctella larvae.

• Korean Journal of Environment and Ecology
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• v.33 no.5
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• pp.565-577
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• 2019

The purpose of this study was to understand the factors influencing the decline and the patterns of changes in Abies nephrolepis populations on Mt. Seorak. We installed permanent quadrats in the areas of the Gwittagicheongbong (peak), Gwanmoneungseon (ridge), and the Seorak Falls and have monitored the community structure, population dynamics, radial growth, and vitality in the quadrats since 2009. Excluding the Seorak Falls, the three research sites showed a three-layer structure in which the low-tree layer forms the canopy. Major tree species were Khingan fir, Korean arborvitae, Mongolian oak, Erman's birch, and Korean maple. The significance of Khingan fir in Seorak Falls decreased from 45.3% in 2009 to 36.8% in 2018. The number of shoots ($DBH{\geq}5cm$) was highest at 1,800 individuals/ha and 1,700 individuals/ha at the Gwittagicheongbong 2 and the Gwanmoneungseon, respectively. The mortality rates over the past 10 years were very high, at 38.3% and 35.3%, respectively, in the Gwittagicheongbong 1 and Seorak Falls. The most stable inverse J-shaped distribution in the Gwittagicheongbong 1 area was shown in the size-frequency distribution of the Khingan fir populations. The average annual ring growth of the Khingan fir was 0.96 ~ 1.73 mm/year, and the ring growth tended to decrease in the areas of Gwittagicheongbong 1, Gwanmoneungseon, and Seorak Falls, where the vitality was low. If the monitoring process continues, it will be possible to obtain basic data for the conservation and management of subalpine vegetation.

• Korean Journal of Environmental Biology
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• v.41 no.1
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• pp.18-30
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• 2023

Forest destruction is an inevitable result of the development processes. According to the environmental impact assessment, over 10% of the destroyed trees need to be recycled and transplanted to minimize the impact of forest destruction. However, the rate of successful transplantation is low, leading to a high rate of tree death. This is attributable to a lack of consideration for environmental factors when choosing a temporary site for transplantation and inadequate management. To monitor transplanted trees, a field survey is essential; however, the spatio-temporal aspect is limited. This study evaluated the applicability of remote sensing for the effective monitoring of transplanted trees. Vegetation indices based on satellite remote sensing were derived to detect time-series changes in the status of the transplanted trees at three temporary transplantation sites. The mortality rate and vitality of transplanted trees before and after the transplant have a similar tendency to the changes in the vegetation indicators. The findings of this study showed that vegetation indices increased after transplantation of trees and decreased as the death rate increased and vitality decreased over time. This study presents a method for assessing newly transplanted trees using satellite images. The approach of utilizing satellite photos and the vegetation index is expected to detect changes in trees that have been transplanted across the country and help to manage tree transplantation for the environmental impact assessment.

• Natural Product Sciences
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• v.12 no.4
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• pp.247-253
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• 2006

The antitumor activity of crude saponin mixture obtained from Luffa tuberosa (Roxb.) (Fam; Cucurbitaceae) hairy roots (CSLT) in mice transplanted with Ehrlich ascites carcinoma (EAC) was investigated. The EAC-bearing mice receiving 150 and $300{\mu}g/kg$ body weight, (i.p) of CSLT have shown a dose dependent elevation in tumor-tree survival and a highest number of survivors were observed after administration of CSLT $(300{\mu}g/kg)$, which was considered as an optimum dose for its antineoplastic action. The mean survival time (MST) for this dose was approximately $47.1{\pm}0.74d$, when compared with $19.0{\pm}0.36d$ of untreated control. Administration of $300{\mu}g/kg$ CSLT resulted in 130% long-term increased survival time. The measurement of body weight, tumor volume, packed cell volume, viable and non-viable count indicated the efficacy of CSLT in tumor-bearing mice, there was a significant recovery in hematological profiles, and there was depletion in lipid peroxidation levels, and the antioxidant enzyme activities such as GSH, SOD and CAT were restored to near the normal levels. The CSLT was found to be devoid of conspicuous short-term toxicity in the mice when animals were intraperitoneally injected with 250, 500, 750 and $1000{\mu}g/kg$ bodyweight. The treated mice showed conspicuous toxic symptoms only at a dose of $1500{\mu}g/kg$. Mortality of the animals was monitored up to 14 d post drug treatment, $1/7^{th}$ of the $LD_{50}$ dose has been considered for the optimal antineoplastic activity.

• The Korean Journal of Ecology
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• v.22 no.6
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• pp.355-361
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• 1999

Distribution of size class, population regeneration and changes in the population structure of Quercus mongolica were studied from 1994 to 1999 in Mt. Jumbong (128°27' E, 38° 04' N) of Mt. Sorak National Park and Biosphere Reserve in central Korea. Three 20m × 20m permanent quadrats were set up at the elevation of 900m. The vegetation of the study site was dominated by Quercus mongolica and Acer pseudosieboldianum, but little change was observed in the community structure from 1995 to 1999. Most mortality in the study site was observed in small trees of A. pseudosieboldianum and Tilia amurensis. Mean annual growth in dbh (diameter of breast height) of Q. mongolica for 4 years was only 0.09cm, and no ingrowth of saplings (dbh < 2.5cm) into tree class was observed during the study period. Among the 21 Q. mongolica trees studied in the permanent quadrats. all the smaller trees (dbh < 30cm) were established in 1920 ∼ 1950, while many bigger trees (with 40cm < dbh < 80cm) were established in 1750 ∼ 1800, indicating that its establishment was episodic. Distribution of dbh classes among Q. mongolica trees shows that smaller trees were poorly represented, and no saplings of Q. mongolica occurred in the permanent quadrats studied, indicating that currently Q. mongolica is not regenerating well in the study site. Total seed production of Q. mongolica in 1994 was estimated as 88 acorns per square meter in the study site. Rate of predation including caching of acorns was highest in 1994, then declined sharply thereafter. Most of the acorns which managed to survive in the first year were predated in the second year, and only 5% of the acorns produced in 1994 survived into the third year. No seeds produced in 1994 or seedlings germinated from them succeeded to survive to 5 years after seed production. However, seedling emergence rate and seedling survival were high in the early growing season in 1995. These results suggest that predation can be a significant factor in the regeneration of Q. mongolica. and that Q. mongolica is not regenerating well in Mt. Jumbong and needs large scale disturbances for its new recruitment.

• Journal of Veterinary Science
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• v.22 no.1
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• pp.1.1-1.12
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• 2021

Background: Goslings in several Taiwanese farms experienced gosling feather loss disease (GFL) at 21-35 days and goose broke feather disease (GBF) at 42-60 days. The prevalence ranges from a few birds to 500 cases per field. It is estimated that about 12,000 geese have been infected, the morbidity is 70-80% and the mortality is 20-30%. Objectives: This study aims to investigate the pathogens that cause GFL and GBF. Focus on the study of the correlation between goose circovirus (GoCV) and goose parvovirus (GPV) with the goose feather loss in southern Taiwan. Furthermore, a phylogenetic tree was established to align the differences between southern and northern Taiwan and compare with virus strains from China and Europe. Methods: Samples were collected from animal hospitals. Molecular and microscopy diagnostics were used to examine 92 geese. Specific quantitative polymerase chain reaction (Q-PCR) assays are performed to evaluate GPV and GoCV viral loads and simultaneously evaluated the feather loss conditions in geese with the scoring method. Results: High prevalence of GoCV and GPV infection in geese showing signs of GFL and GBF. Inclusion body was detected in the feather follicles and Lieberkuhn crypt epithelial cells. The Q-PCR showed the high correlation between feather loss and viruses during 3rd-5th week. However, the infection was not detected using the same test in 60 healthy geese. Conclusions: Thus, GFL and GBF appear to be significantly closely related to GoCV and GPV. The geese feathers showed increasing recovery after being quarantined and disinfected.

• Journal of Preventive Medicine and Public Health
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• v.55 no.5
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• pp.415-423
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• 2022

Economic evaluations in the healthcare are used to assess economic efficiency of pharmaceuticals and medical interventions such as diagnoses and medical procedures. This study introduces the main concepts of economic evaluation across its key steps: planning, outcome and cost calculation, modeling, cost-effectiveness results, uncertainty analysis, and decision-making. When planning an economic evaluation, we determine the study population, intervention, comparators, perspectives, time horizon, discount rates, and type of economic evaluation. In healthcare economic evaluations, outcomes include changes in mortality, the survival rate, life years, and quality-adjusted life years, while costs include medical, non-medical, and productivity costs. Model-based economic evaluations, including decision tree and Markov models, are mainly used to calculate the total costs and total effects. In cost-effectiveness or costutility analyses, cost-effectiveness is evaluated using the incremental cost-effectiveness ratio, which is the additional cost per one additional unit of effectiveness gained by an intervention compared with a comparator. All outcomes have uncertainties owing to limited evidence, diverse methodologies, and unexplained variation. Thus, researchers should review these uncertainties and confirm their robustness. We hope to contribute to the establishment and dissemination of economic evaluation methodologies that reflect Korean clinical and research environment and ultimately improve the rationality of healthcare policies.

• Journal of Korean Society for Quality Management
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• v.39 no.3
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• pp.391-399
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• 2011

Our study was carried out to analyze the variation factors of severity-adjusted length of stay(LOS) in coronary artery bypass graft(CABG). The subjects were 932 CABG inpatients of the Korean National Hospital Discharge In-depth Injury Survey from 2004 through 2008. The data were analyzed using $x^2$ test and the severity-adjusted model was developed using data mining technique. The results of the study were as follows: male(71.1%), older than 61 years of age(61.6%), more than 500 beds(92.8%) and admitting via ambulatory care(70.0%) appeared to have higher rate than otherwise. In-hospital mortality of CABG inpatients was 2.8%. In addition, 46.4% of the patients received their care in other residence. The angina pectoris(45.6%) was found to be the highest in principle diagnosis, followed by chronic ischemic heart disease(36.9%) and acute myocardial infarction(12.0%). We developed severity-adjusted LOS model using the variables such as gender, age and comorbidity. Comparison of adjusted values in predicted LOS revealed that there were significant variations in LOS by location of hospital, bed size, and whether patients received the care in their residences. The variations of LOS can be explained as the indirect indicator for quality variation of medical process. It is suggested that the severity-adjusted LOS model developed in this study should be utilized as a useful method for benchmarking in hospital and it is necessary that national standard clinical practice guideline should be developed.

• Korean Journal of Ecology and Environment
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• v.46 no.3
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• pp.319-331
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• 2013

Recent climate change, which is mostly ascribed to anthropogenic activities, is believed to be a major factor leading to biodiversity decreases and ecosystem service deteriorations. I have reviewed recent studies on climate change effects for many ecological processes involved with plants, in order to improve our understanding of the nature of ecological complexity. Plants in general have better growth and productivity under high levels of $CO_2$, although the long term effects of such $CO_2$ fertilizers are still controversial. Over the last 30 years, the Earth has been greening, particularly at higher latitudes of the Northern Hemisphere, perhaps due to a relaxation of climatic constraints. Human appropriation of net primary productivity (NPP), which corresponds up to 1/3 of global NPP, is ultimately responsible for climate change and biodiversity decreases. Climate change causes phenological variations in plants, especially in regards to spring flowering and fall leaf coloring. Many plants migrate polewards and towards higher altitudes to seek more appropriate climates. On the other hand, tree mortality and population declines have recently been reported in many continents. Landscape disturbance not only hinders the plant migration, but also makes it difficult to predict the plants' potential habitats. Plant and animal population declines, as well as local extinctions, are largely due to the disruption of species interactions through temporal mismatching. Temperature and $CO_2$ increase rates in Korea are higher than global means. The degree of landscape disturbances is also relatively high. Furthermore, long-term data on individual species responses and species interactions are lacking or quite limited in Korea. This review emphasizes the complex nature of species responses to climate change at both global and local scales. In order to keep pace with the direction and speed of climate change, it is urgently necessary to observe and analyze the patterns of phenology, migration, and trophic interactions of plants and animals in Korea's landscape.

• International Journal of Computer Science & Network Security
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• v.23 no.12
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• pp.101-106
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• 2023

Chronic illnesses are among the most common serious problems affecting human health. Early diagnosis of chronic diseases can assist to avoid or mitigate their consequences, potentially decreasing mortality rates. Using machine learning algorithms to identify risk factors is an exciting strategy. The issue with existing feature selection approaches is that each method provides a distinct set of properties that affect model correctness, and present methods cannot perform well on huge multidimensional datasets. We would like to introduce a novel model that contains a feature selection approach that selects optimal characteristics from big multidimensional data sets to provide reliable predictions of chronic illnesses without sacrificing data uniqueness.[1] To ensure the success of our proposed model, we employed balanced classes by employing hybrid balanced class sampling methods on the original dataset, as well as methods for data pre-processing and data transformation, to provide credible data for the training model. We ran and assessed our model on datasets with binary and multivalued classifications. We have used multiple datasets (Parkinson, arrythmia, breast cancer, kidney, diabetes). Suitable features are selected by using the Hybrid feature model consists of Lassocv, decision tree, random forest, gradient boosting,Adaboost, stochastic gradient descent and done voting of attributes which are common output from these methods.Accuracy of original dataset before applying framework is recorded and evaluated against reduced data set of attributes accuracy. The results are shown separately to provide comparisons. Based on the result analysis, we can conclude that our proposed model produced the highest accuracy on multi valued class datasets than on binary class attributes.[1]