• Microbiology and Biotechnology Letters
• /
• v.50 no.4
• /
• pp.563-573
• /
• 2022

Xanthomonas arboricola pv. juglandis (Xaj) is a globally important bacterial pathogen of walnut trees that causes substantial economic losses in commercial walnut production. Although prophages are common in bacterial plant pathogens and play important roles in bacterial diversity and pathogenicity, there has been limited investigation into the distribution and function of prophages in Xaj. In this study, we identified and characterized 13 predicted prophages from the genomes of 12 Xaj isolates from around the globe. These prophages ranged in length from 11.8 kb to 51.9 kb, with between 11-75 genes and 57.82-64.15% GC content. The closest relatives of these prophages belong to the Myoviridae and Siphoviridae families of the Caudovirales order. The phylogenetic analysis allowed the classification of the prophages into five groups. The gene constitution of these predicted prophages was revealed via Roary analysis. Amongst 126 total protein groups, the most prevalent group was only present in nine prophages, and 22 protein groups were present in only one prophage (singletons). Also, bioinformatic analysis of the 13 identified prophages revealed the presence of 431 genes with an average length of 389.7 bp. Prokka annotation of these prophages identified 466 hypothetical proteins, 24 proteins with known function, and six tRNA genes. The proteins with known function mainly comprised prophage integrase IntA, replicative DNA helicase, tyrosine recombinase XerC, and IS3 family transposase. There was no detectable insertion site specificity for these prophages in the Xaj genomes. The identified Xaj prophage genes, particularly those of unknown function, merit future investigation.

• Journal of Ecology and Environment
• /
• v.47 no.3
• /
• pp.118-133
• /
• 2023

Background: Free-living amoebae (FLA) are widely distributed in freshwater, seawater, soil, and extreme environments, and play a critical role as feeders on diverse preys in the ecosystem. Also, some FLA can become opportunistic pathogens in animals including humans. The taxa Amoebozoa and Heterolobosea are important amoeboid groups associated with human pathogens. However, the identification and habitat of amoebae belonging to Amoebozoa and Heterolobosea remain poorly reported in the Republic of Korea. This study highlights the first record for identification and source of four amoebae including putative pathogens in the Republic of Korea. Results: In the present study, four previously reported FLA were isolated from freshwaters in Sangju Gonggeomji Reservoir (strain GO001), one of the largest reservoirs during the Joseon Dynasty period, and along the Nakdong River, the largest river in the Republic of Korea (strains NR5-2, NR12-1, and NR14-1) for the first time. Microscopic observations and 18S rDNA phylogenetic trees revealed the four isolated strains to be Acanthamoeba polyphaga (strains NR5-2 and NR12-1), Tetramitus waccamawensis (strain GO001), and Naegleria australiensis (strain NR14-1). Strains NR5-2 and NR12-1 might be the same species and belonged to the morphological Group 2 and the T4 genotype of Acanthamoeba. Strain GO001 formed a clade with T. waccamawensis in 18S rDNA phylogeny, and showed morphological characteristics similar to previously recorded strains, although the species' flagellate form was not observed. Strain NR14-1 had the typical morphology of Naegleria and formed a strongly supported clade with previously recorded strains of N. australiensis in phylogenetic analysis of 18S rDNA sequences. Conclusions: On the bases of morphological and molecular analyses, four strains of FLA were newly observed and classified in the Republic of Korea. Three strains belonging to the two species (A. polyphaga and N. australiensis) isolated from the Nakdong River have the potential to act as opportunistic pathogens that can cause fatal diseases (i.e. granulomatous amoebic encephalitis, Acanthamoeba Keratitis, and meningoencephalitis) in animals including humans. The Nakdong River in the Republic of Korea may provide a habitat for potentially pathogenic amoebae, but additional research is required to confirm the true pathogenicity of these FLA now known in the Republic of Korea.

• Journal of Korean Society of Forest Science
• /
• v.106 no.3
• /
• pp.310-319
• /
• 2017

This study categorized the damaged trees by Supervised Classification using time-series-aerial photographs of Bukhan, Cheonggae and Suri mountains because oak wilt disease seemed to be concentrated in the metropolitan regions. In order to analyze the spatial characteristics of the damaged areas, the geographical characteristics such as elevation and slope were statistically analyzed to confirm their strong correlation. Based on the results from the statistical analysis of Moran's I, we have retrieved the following: (i) the value of Moran's I in Bukhan mountain is estimated to be 0.25, 0.32, and 0.24 in 2009, 2010 and 2012, respectively. (ii) the value of Moran's I in Cheonggye mountain estimated to be 0.26, 0.32 and 0.22 in 2010, 2012 and 2014, respectively and (iii) the value of Moran's I in Suri mountain estimated to be 0.42 and 0.42 in 2012 and 2014. respectively. These numbers suggest that the damaged trees are distributed in clusters. In addition, we conducted hotspot analysis to identify how the damaged tree clusters shift over time and we were able to verify that hotspots move in time series. According to our research outcome from the analysis of the entire hotspot areas (z-score>1.65), there were 80 percent probability of oak wilt disease occurring in the broadleaf or mixed-stand forests with elevation of 200~400 m and slope of 20~40 degrees. This result indicates that oak wilt disease hotspots can occur or shift into areas with the above geographical features or forest conditions. Therefore, this research outcome can be used as a basic resource when predicting the oak wilt disease spread-patterns, and it can also prevent disease and insect pest related harms to assist the policy makers to better implement the necessary solutions.

• Korean Journal of Environment and Ecology
• /
• v.27 no.1
• /
• pp.99-112
• /
• 2013

This study aims to show the changes of characteristics of vegetation structure for 20 years(1991~2010) in Naejangsan National Park. As a result of analysis of actual vegetation, the mixed community of Quercus variabilis and Quercus serrata was distributed with 56.1%, and Q. variabilis community showed in southern steep slope with 17.6%. Pinus densiflora community(5.8%) was observed on the ridge and Carpinu tschonoskii community distributed in the slope of the valley with 6.6%. Zelkova serrata and Prunus sargentii community were distributed in valley. The classification by TWINSPAN, ordination by DCA considering importance percentage and property of vegetation class were divided into 4 communities, which are community I(P. densiflora-Q. variabilis community), community II(Q. variabilis community), community III(C. tschonoskii community) and community IV(Mixed deciduous broad-leaved trees community). The age of Pinus densiflora was 32years old and Q. serrata was 36 years old in the community I, that of Q. variabilis was 64 years old in the community II, Q. serrata was 46 years old and C. tschonoskii was 45 years old in the community III, and Acer palmatum was 54 years old and Cornus controversa was 47 years old in the community IV. As the result of Shannon's index of species diversity, the community Iwas ranged from 0.9751 to 1.4199, community II was ranged from 1.0765 to 1.3278, community III was ranged from 1.0353 to 1.2881, and community IV was ranged from 1.1412 to 1.3807. The change of vegetation structure analyzed through the comparison with results of studies carried out 20 years ago were natural selection of P. densiflora, expansion of Quercus spp. and increase of C. tschonoskii. Especially, A. palmatum is dominated by Q. variabilis in canopy layer like the result of study 20 years ago. A. palmatum was analysed by 14.6% in the canopy layer of only mixed deciduous broad-leaved trees community. As a result of analysis of habitat property of Q. variabilis and A. palmatum, Q. variabilis was distributed in dry area with the low value of pH, O.M., exchangeable cations and Avail. P, and A. palmatum was located in the wet valley with huge value of nourishment. The tendency of reduction of bio-diversity by Sasa borealis is same as previous study but, the distributed areas were reduced in Naejangsan area.

• Journal of Korean Society of Forest Science
• /
• v.104 no.4
• /
• pp.564-577
• /
• 2015

The objectives of this study were to investigate the possibility of establishing a tree nursery at Saemangeum reclaimed land and to classify landscape trees based on the salt tolerance. A tree nursery (2.0 ha) was made in Gunsan Okgu area in 2012 with underground drain lines on the reclaimed land established in 2010. Salt content of the nursery soil within the 60 cm depth in 2013 was 5.13 dS/m and 8.20 dS/m for the pre-desalinated and non-desalinated lands, respectively. Thirty-six woody plant species (22 tree species and 14 shrub species at ages of 1 to 4) with a total of 3,943 individuals were planted in early April, 2013 and their growth performance was monitored until September of the same year. The average survival rate of the transplanted plants was 71.4% in late September, suggesting the high possibility of establishing a tree nursery at the reclaimed land. Based on the survival rate and tree vigor (amount of healthy leaves and crown development), the following 17 species with some salt tolerance were classified into three groups: "salt tolerant group" (3 species, Tamarix chinensis, Cudrania tricuspidata, Ilex serrata), "recommended group" (5 species, Pinus thunbergii, Albizia julibrissin, Ligustrum obtusifolium, Rosa rugosa, Pleioblatus pygmaeus), "plantable group" (9 species, Zelkova serrata, Hibiscus syriacus, Elaeagnus umbellata, Sorbus alnifolia, Sophora japonica, Metasequoia glyptostroboides, Quercus acutissima, Ulmus parvifolia, Robinia pseudoacacia). Seven tree species that had been adapted to the reclaimed land for three to four years before being transplanted to new reclaimed land in Gunsan Okgu area showed average survival rate of 98%, suggesting that pre-conditioned trees would survive well in the reclaimed land.

• Ecology and Resilient Infrastructure
• /
• v.7 no.4
• /
• pp.227-237
• /
• 2020

Microclimatic data were measured, and the human thermal sensation was analyzed at 10 local climate zones based on the major land cover classification to investigate the thermal environment of urban areas during summer nighttime. From the results, the green infrastructure areas (GNIAs) showed an average air temperature of 1.6℃ and up to 2.4℃ lower air temperature than the gray infrastructure areas (GYIAs), and the GNIAs showed an average relative humidity of 9.0% and up to 15.0% higher relative humidity. The wind speed of the GNIAs and GYIAs had minimal difference and showed no significance at all locations, except for the forest location, which had the lowest wind speed owing to the influence of trees. The local winds and the surface roughness, which was determined based on the heights of buildings and trees, appeared to be the main factors that influenced wind speed. At the mean radiant temperature, the forest location showed the maximum value, owing to the influence of trees. Except at the forest location, the GNIAs showed an average decrease of 5.5℃ compared to GYIAs. The main factor that influenced the mean radiant temperature was the sky view factor. In the analysis of the human thermal sensation, the GNIAs showed a "neutral" thermal perception level that was neither hot nor cold, and the GYIAs showed a "slightly warm" level, which was a level higher than those of the GNIAs. The GNIAs showed a 3.2℃ decrease compared to the GYIAs, except at the highest forest location, which indicated a half-level improvement in the human thermal environment.

• Korean Journal of Environment and Ecology
• /
• v.29 no.6
• /
• pp.895-906
• /
• 2015

This study was carried out to the structure of plant community from Sinseongam to Jungdaesa in Odaesan National Park, furthermore, it seeks to curate the basic data for planning of the Abies holophylla's forest management in Odaesan National Park. In order to identify the current ecological environment, this study explored the actual vegetation as primary research and set to twenty plots(i.e. $400m^2$) for analysing detailed structure of plant communities. The research methodology was qualitative analysis, therefore it used TWINSPAN and DCA analysis tools. Especially, TWINSPAN performed well in several comparisons of classification techniques, DCA is one of the ordination technique showed that the plant communities. The plant community was analysed classification and ordination by TWINSPAN and DCA, moreover it was analysed the structure of plant community such as importance percentage of woody species, DBH class distribution, the index of diversity and rate of sample tree growth. The main vegetation was A. holophylla-Quercus mongolica forest and Deciduous broad-leaved forest in the communities where located in low altitude and valley, whereas main vegetation where located in high altitude and slope was Q. mongolica forest. The research site's plant communities were classified four groups. In all of communities, A. holophylla was dominant species in main canopy layer, furthermore, the three communities (community I, II, III) are growing up next generation of A. holophylla excluding community IV. The communities (community I, II, III) can be sustained current status which dominates the A. holophylla communities, simultaneously, there might be expanded the Deciduous broad-leaved communities by Carpinus cordata, Betula schmidtii and so on. While, it showed that the community IV tended to be weaken the forces of A. holophylla, therefore the community IV can be transferred to C. cordata-Deciduous broad-leaved communities in the future. The age of sample trees was 79~128(i.e. A. holophylla), 75~87(i.e. Pinus koraiensis) and 190 years(i.e. Ulmus davidiana var. japonica). The index of Shannon's Species diversity (H') were ranged from 0.3889 to 1.3332 in the communities.

• Nuclear Medicine and Molecular Imaging
• /
• v.41 no.4
• /
• pp.299-308
• /
• 2007

Purpose: The aim of this study was to develop a bioinformatics software and to test it in serum samples of papillary thyroid cancer using mass spectrometry (SELDI-TOF-MS). Materials and Methods: Development of 'Protein analysis' software performing decision tree analysis was done by customizing C4.5. Sixty-one serum samples from 27 papillary thyroid cancer, 17 autoimmune thyroiditis, 17 controls were applied to 2 types of protein chips, CM10 (weak cation exchange) and IMAC3 (metal binding - Cu). Mass spectrometry was performed to reveal the protein expression profiles. Decision trees were generated using 'Protein analysis' software, and automatically detected biomarker candidates. Validation analysis was performed for CM10 chip by random sampling. Results: Decision tree software, which can perform training and validation from profiling data, was developed. For CM10 and IMAC3 chips, 23 of 113 and 8 of 41 protein peaks were significantly different among 3 groups (p<0.05), respectively. Decision tree correctly classified 3 groups with an error rate of 3.3% for CM10 and 2.0% for IMAC3, and 4 and 7 biomarker candidates were detected respectively. In 2 group comparisons, all cancer samples were correctly discriminated from non-cancer samples (error rate = 0%) for CM10 by single node and for IMAC3 by multiple nodes. Validation results from 5 test sets revealed SELDI-TOF-MS and decision tree correctly differentiated cancers from non-cancers (54/55, 98%), while predictability was moderate in 3 group classification (36/55, 65%). Conclusion: Our in-house software was able to successfully build decision trees and detect biomarker candidates, therefore it could be useful for biomarker discovery and clinical follow up of papillary thyroid cancer.

• Journal of Intelligence and Information Systems
• /
• v.19 no.2
• /
• pp.39-54
• /
• 2013

Recent explosive increase of electronic commerce provides many advantageous purchase opportunities to customers. In this situation, customers who do not have enough knowledge about their purchases, may accept product recommendations. Product recommender systems automatically reflect user's preference and provide recommendation list to the users. Thus, product recommender system in online shopping store has been known as one of the most popular tools for one-to-one marketing. However, recommender systems which do not properly reflect user's preference cause user's disappointment and waste of time. In this study, we propose a novel recommender system which uses data mining and multi-model ensemble techniques to enhance the recommendation performance through reflecting the precise user's preference. The research data is collected from the real-world online shopping store, which deals products from famous art galleries and museums in Korea. The data initially contain 5759 transaction data, but finally remain 3167 transaction data after deletion of null data. In this study, we transform the categorical variables into dummy variables and exclude outlier data. The proposed model consists of two steps. The first step predicts customers who have high likelihood to purchase products in the online shopping store. In this step, we first use logistic regression, decision trees, and artificial neural networks to predict customers who have high likelihood to purchase products in each product group. We perform above data mining techniques using SAS E-Miner software. In this study, we partition datasets into two sets as modeling and validation sets for the logistic regression and decision trees. We also partition datasets into three sets as training, test, and validation sets for the artificial neural network model. The validation dataset is equal for the all experiments. Then we composite the results of each predictor using the multi-model ensemble techniques such as bagging and bumping. Bagging is the abbreviation of "Bootstrap Aggregation" and it composite outputs from several machine learning techniques for raising the performance and stability of prediction or classification. This technique is special form of the averaging method. Bumping is the abbreviation of "Bootstrap Umbrella of Model Parameter," and it only considers the model which has the lowest error value. The results show that bumping outperforms bagging and the other predictors except for "Poster" product group. For the "Poster" product group, artificial neural network model performs better than the other models. In the second step, we use the market basket analysis to extract association rules for co-purchased products. We can extract thirty one association rules according to values of Lift, Support, and Confidence measure. We set the minimum transaction frequency to support associations as 5%, maximum number of items in an association as 4, and minimum confidence for rule generation as 10%. This study also excludes the extracted association rules below 1 of lift value. We finally get fifteen association rules by excluding duplicate rules. Among the fifteen association rules, eleven rules contain association between products in "Office Supplies" product group, one rules include the association between "Office Supplies" and "Fashion" product groups, and other three rules contain association between "Office Supplies" and "Home Decoration" product groups. Finally, the proposed product recommender systems provides list of recommendations to the proper customers. We test the usability of the proposed system by using prototype and real-world transaction and profile data. For this end, we construct the prototype system by using the ASP, Java Script and Microsoft Access. In addition, we survey about user satisfaction for the recommended product list from the proposed system and the randomly selected product lists. The participants for the survey are 173 persons who use MSN Messenger, Daum Caf$\acute{e}$, and P2P services. We evaluate the user satisfaction using five-scale Likert measure. This study also performs "Paired Sample T-test" for the results of the survey. The results show that the proposed model outperforms the random selection model with 1% statistical significance level. It means that the users satisfied the recommended product list significantly. The results also show that the proposed system may be useful in real-world online shopping store.

• Korean Journal of Environment and Ecology
• /
• v.33 no.1
• /
• pp.75-85
• /
• 2019

The purpose of this study is to understand the vegetation characteristics of ridges (Gyeongsusan-Seonunsan-Gaeipalsan) in the Seonunsan Provincial Park and to establish reference information for the management of the park in the future. We designated 62 plots with the area of $100m^2$ were installed and analyzed them to investigate the vegetation characteristics. The results of community classification based on TWINSPAN showed seven categories of vegetation communities in the surveyed region: Quercus dentata-Deciduous broad-leaved Community, Quercus variabilis-Pinus thunbergii-Quercus serrata Community, Pinus densiflora Community, Deciduous broad-leaved Community-I, Carpinus tschonoskii-Castanea crenata-Quercus aliena Community, Deciduous broad-leaved Community-II, and Carpinus tschonoskii-Carpinus laxiflora Community. In the vegetation of Seonunsan Provincial Park, coniferous trees such as Pinus thunbergii and Pinus densiflora have been gradually losing their population as part of ecological succession to deciduous broad-leaved trees such as Quercus spp., Carpinus tschonoskii, and Carpinus laxiflora. Moreover, Carpinus turczaninowii, Mallotus japonicus, and others were identified as vegetation reflecting the geographical characteristics of the region neighboring the west coast. The estimated age is 30-60 years, and the oldest tree Pinus densiflora is 63-years old. The index of diversity ($100m^2$) was 0.7942 for Carpinus tschonoskii-Carpinus laxiflora Community, 0.8406 for Carpinus tschonoskii-Castanea crenata-Quercus aliena Community, 0.8543 for Quercus dentata-Deciduous broad-leaved Community, 0.9434 for Quercus variabilis-Pinus thunbergii-Quercus serrata Community, 0.9520 for Deciduous broad-leaved Community-I, 0.9633 for Pinus densiflora Community, and 1.0340 for Deciduous broad-leaved Community-II in the ascending order.