• Radiation Oncology Journal
• /
• v.25 no.1
• /
• pp.7-15
• /
• 2007

[ $\underline{Purpose}$ ]: To determine the patterns of evaluation and treatment in patients with breast cancer after mastectomy and treated with radiotherapy. A nationwide study was performed with the goal of improving radiotherapy treatment. $\underline{Materials\;and\;Methods}$: A web- based database system for the Korean Patterns of Care Study (PCS) for 6 common cancers was developed. Randomly selected records of 286 eligible patients treated between 1998 and 1999 from 17 hospitals were reviewed. $\underline{Results}$: The ages of the study patients ranged from 20 to 80 years (median age 44 years). The pathologic T stage by the AJCC was T1 in 9.7% of the cases, T2 in 59.2% of the cases, T3 in 25.6% of the cases, and T4 in 5.3% of the cases. For analysis of nodal involvement, N0 was 7.3%, N1 was 14%, N2 was 38.8%, and N3 was 38.5% of the cases. The AJCC stage was stage I in 0.7% of the cases, stage IIa in 3.8% of the cases, stage IIb in 9.8% of the cases, stage IIIa in 43% of the cases, stage IIIb in 2.8% of the cases, and IIIc in 38.5% of the cases. There were various sequences of chemotherapy and radiotherapy after mastectomy. Mastectomy and chemotherapy followed by radiotherapy was the most commonly performed sequence in 47% of the cases. Mastectomy, chemotherapy, and radiotherapy followed by additional chemotherapy was performed in 35% of the cases, and neoadjuvant chemoradiotherapy was performed in 12.5% of the cases. The radiotherapy volume was chest wall only in 5.6% of the cases. The volume was chest wall and supraclavicular fossa (SCL) in 20.3% of the cases; chest wall, SCL and internal mammary lymph node (IMN) in 27.6% of the cases; chest wall, SCL and posterior axillary lymph node in 25.9% of the cases; chest wall, SCL, IMN, and posterior axillary lymph node in 19.9% of the cases. Two patients received IMN only. The method of chest wall irradiation was tangential field in 57.3% of the cases and electron beam in 42% of the cases. A bolus for the chest wall was used in 54.8% of the tangential field cases and 52.5% of the electron beam cases. The radiation dose to the chest wall was $45{\sim}59.4\;Gy$ (median 50.4 Gy), to the SCL was $45{\sim}59.4\;Gy$ (median 50.4 Gy), and to the PAB was $4.8{\sim}38.8\;Gy$, (median 9 Gy) $\underline{Conclusion}$: Different and various treatment methods were used for radiotherapy of the breast cancer patients after mastectomy in each hospital. Most of treatment methods varied in the irradiation of the chest wall. A separate analysis for the details of radiotherapy planning also needs to be followed and the outcome of treatment is needed in order to evaluate the different processes.

• Geophysics and Geophysical Exploration
• /
• v.2 no.1
• /
• pp.26-32
• /
• 1999

Among the various seismic data processing sequences, the velocity analysis is the most time consuming and man-hour intensive processing steps. For the production seismic data processing, a good velocity analysis tool as well as the high performance computer is required. The tool must give fast and accurate velocity analysis. There are two different approches in the velocity analysis, batch and interactive. In the batch processing, a velocity plot is made at every analysis point. Generally, the plot consisted of a semblance contour, super gather, and a stack pannel. The interpreter chooses the velocity function by analyzing the velocity plot. The technique is highly dependent on the interpreters skill and requires human efforts. As the high speed graphic workstations are becoming more popular, various interactive velocity analysis programs are developed. Although, the programs enabled faster picking of the velocity nodes using mouse, the main improvement of these programs is simply the replacement of the paper plot by the graphic screen. The velocity spectrum is highly sensitive to the presence of the noise, especially the coherent noise often found in the shallow region of the marine seismic data. For the accurate velocity analysis, these noise must be removed before the spectrum is computed. Also, the velocity analysis must be carried out by carefully choosing the location of the analysis point and accuarate computation of the spectrum. The analyzed velocity function must be verified by the mute and stack, and the sequence must be repeated most time. Therefore an iterative, interactive, and unified velocity analysis tool is highly required. An interactive velocity analysis program, xva(X-Window based Velocity Analysis) was invented. The program handles all processes required in the velocity analysis such as composing the super gather, computing the velocity spectrum, NMO correction, mute, and stack. Most of the parameter changes give the final stack via a few mouse clicks thereby enabling the iterative and interactive processing. A simple trace indexing scheme is introduced and a program to nike the index of the Geobit seismic disk file was invented. The index is used to reference the original input, i.e., CDP sort, directly A transformation techinique of the mute function between the T-X domain and NMOC domain is introduced and adopted to the program. The result of the transform is simliar to the remove-NMO technique in suppressing the shallow noise such as direct wave and refracted wave. However, it has two improvements, i.e., no interpolation error and very high speed computing time. By the introduction of the technique, the mute times can be easily designed from the NMOC domain and applied to the super gather in the T-X domain, thereby producing more accurate velocity spectrum interactively. The xva program consists of 28 files, 12,029 lines, 34,990 words and 304,073 characters. The program references Geobit utility libraries and can be installed under Geobit preinstalled environment. The program runs on X-Window/Motif environment. The program menu is designed according to the Motif style guide. A brief usage of the program has been discussed. The program allows fast and accurate seismic velocity analysis, which is necessary computing the AVO (Amplitude Versus Offset) based DHI (Direct Hydrocarn Indicator), and making the high quality seismic sections.

• Journal of Intelligence and Information Systems
• /
• v.24 no.2
• /
• pp.59-83
• /
• 2018

With the increasing importance of sentiment analysis to grasp the needs of customers and the public, various types of deep learning models have been actively applied to English texts. In the sentiment analysis of English texts by deep learning, natural language sentences included in training and test datasets are usually converted into sequences of word vectors before being entered into the deep learning models. In this case, word vectors generally refer to vector representations of words obtained through splitting a sentence by space characters. There are several ways to derive word vectors, one of which is Word2Vec used for producing the 300 dimensional Google word vectors from about 100 billion words of Google News data. They have been widely used in the studies of sentiment analysis of reviews from various fields such as restaurants, movies, laptops, cameras, etc. Unlike English, morpheme plays an essential role in sentiment analysis and sentence structure analysis in Korean, which is a typical agglutinative language with developed postpositions and endings. A morpheme can be defined as the smallest meaningful unit of a language, and a word consists of one or more morphemes. For example, for a word '예쁘고', the morphemes are '예쁘(= adjective)' and '고(=connective ending)'. Reflecting the significance of Korean morphemes, it seems reasonable to adopt the morphemes as a basic unit in Korean sentiment analysis. Therefore, in this study, we use 'morpheme vector' as an input to a deep learning model rather than 'word vector' which is mainly used in English text. The morpheme vector refers to a vector representation for the morpheme and can be derived by applying an existent word vector derivation mechanism to the sentences divided into constituent morphemes. By the way, here come some questions as follows. What is the desirable range of POS(Part-Of-Speech) tags when deriving morpheme vectors for improving the classification accuracy of a deep learning model? Is it proper to apply a typical word vector model which primarily relies on the form of words to Korean with a high homonym ratio? Will the text preprocessing such as correcting spelling or spacing errors affect the classification accuracy, especially when drawing morpheme vectors from Korean product reviews with a lot of grammatical mistakes and variations? We seek to find empirical answers to these fundamental issues, which may be encountered first when applying various deep learning models to Korean texts. As a starting point, we summarized these issues as three central research questions as follows. First, which is better effective, to use morpheme vectors from grammatically correct texts of other domain than the analysis target, or to use morpheme vectors from considerably ungrammatical texts of the same domain, as the initial input of a deep learning model? Second, what is an appropriate morpheme vector derivation method for Korean regarding the range of POS tags, homonym, text preprocessing, minimum frequency? Third, can we get a satisfactory level of classification accuracy when applying deep learning to Korean sentiment analysis? As an approach to these research questions, we generate various types of morpheme vectors reflecting the research questions and then compare the classification accuracy through a non-static CNN(Convolutional Neural Network) model taking in the morpheme vectors. As for training and test datasets, Naver Shopping's 17,260 cosmetics product reviews are used. To derive morpheme vectors, we use data from the same domain as the target one and data from other domain; Naver shopping's about 2 million cosmetics product reviews and 520,000 Naver News data arguably corresponding to Google's News data. The six primary sets of morpheme vectors constructed in this study differ in terms of the following three criteria. First, they come from two types of data source; Naver news of high grammatical correctness and Naver shopping's cosmetics product reviews of low grammatical correctness. Second, they are distinguished in the degree of data preprocessing, namely, only splitting sentences or up to additional spelling and spacing corrections after sentence separation. Third, they vary concerning the form of input fed into a word vector model; whether the morphemes themselves are entered into a word vector model or with their POS tags attached. The morpheme vectors further vary depending on the consideration range of POS tags, the minimum frequency of morphemes included, and the random initialization range. All morpheme vectors are derived through CBOW(Continuous Bag-Of-Words) model with the context window 5 and the vector dimension 300. It seems that utilizing the same domain text even with a lower degree of grammatical correctness, performing spelling and spacing corrections as well as sentence splitting, and incorporating morphemes of any POS tags including incomprehensible category lead to the better classification accuracy. The POS tag attachment, which is devised for the high proportion of homonyms in Korean, and the minimum frequency standard for the morpheme to be included seem not to have any definite influence on the classification accuracy.

• Journal of Animal Science and Technology
• /
• v.54 no.1
• /
• pp.1-8
• /
• 2012

This study aimed to investigate the single nucleotide polymorphisms (SNPs) of the porcine MC4R gene and validate the effect of the MC4R genotype for marker assisted selection (MAS). Six amplicons were produced to analyze the entire base sequences of the porcine MC4R gene and six SNPs were detected (c.-780C>G, c.-135C>T, c.175C>T-Leu59Leu, c.707A>G-Arg236His, c.892A>G-Asp298Asn, and c.*430A>T). Linkage disequilibrium (LD) of the six SNPs was analyzed by performing haploid analysis. There was a perfect linkage disequilibrium in c.-780C>G, c.-135C>T, c.175C>T-Leu59Leu, c.707A>G-Arg236His, and c.*430A>T. Only the c.892A>G (Asp298Asn) SNP showed a very low LD with an $r^2$ value of 0.028 and the D' value of 0.348. As a result, the two SNPs-c.707A>G (Arg236His) and c.892A>G (Asp298Asn)-were selected to extract the genotype frequencies from the 5 pig breeds by using the polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) genotype analysis method. The SNP frequency of c.707A>G (Arg236His) indicated the presence of the A (His) allele only in Yorkshire, while the G allele was fixed in the KNP, Landrace, Berkshire, and Duroc. Association analysis was carried out in 484 pigs with the c.707A>G (Arg236His) SNP and the meat quality traits of four different pig cross populations: a significant association was noted in crude fat, sirloin moisture, meat color, and the degree of red and yellow coloration. The frequency of the c.892A>G(Asp298Asn) SNP genotype varied among the breeds; while Duroc showed the highest frequency of the A (Asn) allele, KNP showed the highest frequency of the G (Asp) allele. Association analysis was carried out in 1126 pigs with the c.892A>G (Asp298Asn) SNP and the meat quality traits of four pig populations: a highly significant linkage was noted in the back-fat thickness (P<0.002). It was found that the back-fat thickness was higher in individuals with the AA genotype than in those with the AG or GG genotype. Thus, in this study, we verified that the c.892A>G (Asp298Asn) SNP in the pig MC4R gene has a sufficient effect as a gene marker for MAS in Korean pork industry.

• Economic and Environmental Geology
• /
• v.25 no.3
• /
• pp.337-349
• /
• 1992

The Tertiary basins in Korea have widely been studied by numerous researchers producing individual results in sedimentology, paleontology, stratigraphy, volcanic petrology and structural geology, but interdisciplinary studies, inter-basin analysis and basin-forming process have not been carried out yet. Major work of this study is to elucidate evidences obtained from different parts of a basin as well as different Tertiary basins (Pohang, Changgi, Eoil, Haseo and Ulsan basins) in order to build up the correlation between the basins, and an overall picture of the basin architecture and evolution in Korea. According to the paleontologic evidences the geologic age of the Pohang marine basin is dated to be late Lower Miocence to Middle Miocene, whereas other non-marine basins are older as being either Early Miocene or Oligocene(Lee, 1975, 1978: Bong, 1984: Chun, 1982: Choi et al., 1984: Yun et al., 1990: Yoon, 1982). However, detailed ages of the Tertiary sediments, and their correlations in a basin and between basins are still controversial, since the basins are separated from each other, sedimentary sequence is disturbed and intruded by voncanic rocks, and non-marine sediments are not fossiliferous to be correlated. Therefore, in this work radiometric, magnetostratigraphic, and biostratigraphic data was integrated for the refinement of chronostratigraphy and synopsis of stratigraphy of Tertiary basins of Korea. A total of 21 samples including 10 basaltic, 2 porphyritic, and 9 andesitic rocks from 4 basins were collected for the K-Ar dating of whole rock method. The obtained age can be grouped as follows: $14.8{\pm}0.4{\sim}15.2{\pm}0.4Ma$, $19.9{\pm}0.5{\sim}22.1{\pm}0.7Ma$, $18.0{\pm}1.1{\sim}20.4+0.5Ma$, and $14.6{\pm}0.7{\sim}21.1{\pm}0.5Ma$. Stratigraphically they mostly fall into the range of Lower Miocene to Mid Miocene. The oldest volcanic rock recorded is a basalt (911213-6) with the age of $22.05{\pm}0.67Ma$ near Sangjeong-ri in the Changgi (or Janggi) basin and presumed to be formed in the Early Miocene, when Changgi Conglomerate began to deposit. The youngest one (911214-9) is a basalt of $14.64{\pm}0.66Ma$ in the Haseo basin. This means the intrusive and extrusive rocks are not a product of sudden voncanic activity of short duration as previously accepted but of successive processes lasting relatively long period of 8 or 9 Ma. The radiometric age of the volcanic rocks is not randomly distributed but varies systematically with basins and localities. It becomes generlly younger to the south, namely from the Changgi basin to the Haseo basin. The rocks in the Changgi basin are dated to be from $19.92{\pm}0.47$ to $22.05{\pm}0.67Ma$. With exception of only one locality in the Geumgwangdong they all formed before 20 Ma B.P. The Eoil basalt by Tateiwa in the Eoil basin are dated to be from $20.44{\pm}0.47$ to $18.35{\pm}0.62Ma$ and they are younger than those in the Changgi basin by 2~4 Ma. Specifically, basaltic rocks in the sedimentary and voncanic sequences of the Eoil basin can be well compared to the sequence of associated sedimentary rocks. Generally they become younger to the stratigraphically upper part. Among the basin, the Haseo basin is characterized by the youngest volcanic rocks. The basalt (911214-7) which crops out in Jeongja-ri, Gangdong-myon, Ulsan-gun is $16.22{\pm}0.75Ma$ and the other one (911214-9) in coastal area, Jujon-dong, Ulsan is $14.64{\pm}0.66Ma$ old. The radiometric data are positively collaborated with the results of paleomagnetic study, pull-apart basin model and East Sea spreading theory. Especially, the successively changing age of Eoil basalts are in accordance with successively changing degree of rotation. In detail, following results are discussed. Firstly, the porphyritic rocks previously known as Cretaceous basement (911213-2, 911214-1) show the age of $43.73{\pm}1.05$ 및 $49.58{\pm}1.13Ma$(Eocene) confirms the results of Jin et al. (1988). This means sequential volcanic activity from Cretaceous up to Lower Tertiary. Secondly, intrusive andesitic rocks in the Pohang basin, which are dated to be $21.8{\pm}2.8Ma$ (Jin et al., 1988) are found out to be 15 Ma old in coincindence with the age of host strata of 16.5 Ma. Thirdly, The Quaternary basalt (911213-5 and 911213-6) of Tateiwa(1924) is not homogeneous regarding formation age and petrological characteristics. The basalt in the Changgi basin show the age of $19.92{\pm}0.47$ and $22.05{\pm}0.67$ (Miocene). The basalt (911213-8) in Sangjond-ri, which intruded Nultaeri Trachytic Tuff is dated to be $20.55{\pm}0.50Ma$, which means Changgi Group is older than this age. The Yeonil Basalt, which Tateiwa described as Quaternary one shows different age ranging from Lower Miocene to Upper Miocene(cf. Jin et al., 1988: sample no. 93-33: $10.20{\pm}0.30Ma$). Therefore, the Yeonil Quarterary basalt should be revised and divided into different geologic epochs. Fourthly, Yeonil basalt of Tateiwa (1926) in the Eoil basin is correlated to the Yeonil basalt in the Changgi basin. Yoon (1989) intergrated both basalts as Eoil basaltic andesitic volcanic rocks or Eoil basalt (Yoon et al., 1991), and placed uppermost unit of the Changgi Group. As mentioned above the so-called Quarternary basalt in the Eoil basin are not extruded or intruaed simultaneously, but differentiatedly (14 Ma~25 Ma) so that they can not be classified as one unit. Fifthly, the Yongdong-ri formation of the Pomgogri Group is intruded by the Eoil basalt (911214-3) of 18.35~0.62 Ma age. Therefore, the deposition of the Pomgogri Group is completed before this age. Referring petrological characteristics, occurences, paleomagnetic data, and relationship to other Eoil basalts, it is most provable that this basalt is younger than two others. That means the Pomgogri Group is underlain by the Changgi Group. Sixthly, mineral composition of the basalts and andesitic rocks from the 4 basins show different ground mass and phenocryst. In volcanic rocks in the Pohang basin, phenocrysts are pyroxene and a small amount of biotite. Those of the Changgi basin is predominant by Labradorite, in the Eoil by bytownite-anorthite and a small amount pyroxene.

• The Korean Journal of Nuclear Medicine
• /
• v.38 no.6
• /
• pp.486-491
• /
• 2004

Purpose: factor analysis and independent component analysis (ICA) has been used for handling dynamic image sequences. Theoretical advantages of a newly suggested ICA method, ensemble ICA, leaded us to consider applying this method to the analysis of dynamic myocardial $H_2^{15}O$ PET data. In this study, we quantified patients' blood flow using the ensemble ICA method. Materials and Methods: Twenty subjects underwent $H_2^{15}O$ PET scans using ECAT EXACT 47 scanner and myocardial perfusion SPECT using Vertex scanner. After transmission scanning, dynamic emission scans were initiated simultaneously with the injection of $555{\sim}740$ MBq $H_2^{15}O$. Hidden independent components can be extracted from the observed mixed data (PET image) by means of ICA algorithms. Ensemble learning is a variational Bayesian method that provides an analytical approximation to the parameter posterior using a tractable distribution. Variational approximation forms a lower bound on the ensemble likelihood and the maximization of the lower bound is achieved through minimizing the Kullback-Leibler divergence between the true posterior and the variational posterior. In this study, posterior pdf was approximated by a rectified Gaussian distribution to incorporate non-negativity constraint, which is suitable to dynamic images in nuclear medicine. Blood flow was measured in 9 regions - apex, four areas in mid wall, and four areas in base wall. Myocardial perfusion SPECT score and angiography results were compared with the regional blood flow. Results: Major cardiac components were separated successfully by the ensemble ICA method and blood flow could be estimated in 15 among 20 patients. Mean myocardial blood flow was $1.2{\pm}0.40$ ml/min/g in rest, $1.85{\pm}1.12$ ml/min/g in stress state. Blood flow values obtained by an operator in two different occasion were highly correlated (r=0.99). In myocardium component image, the image contrast between left ventricle and myocardium was 1:2.7 in average. Perfusion reserve was significantly different between the regions with and without stenosis detected by the coronary angiography (P<0.01). In 66 segment with stenosis confirmed by angiography, the segments with reversible perfusion decrease in perfusion SPECT showed lower perfusion reserve values in $H_2^{15}O$ PET. Conclusions: Myocardial blood flow could be estimated using an ICA method with ensemble learning. We suggest that the ensemble ICA incorporating non-negative constraint is a feasible method to handle dynamic image sequence obtained by the nuclear medicine techniques.

• Journal of Intelligence and Information Systems
• /
• v.25 no.1
• /
• pp.85-107
• /
• 2019

Online consumers browse products belonging to a particular product line or brand for purchase, or simply leave a wide range of navigation without making purchase. The research on the behavior and purchase of online consumers has been steadily progressed, and related services and applications based on behavior data of consumers have been developed in practice. In recent years, customization strategies and recommendation systems of consumers have been utilized due to the development of big data technology, and attempts are being made to optimize users' shopping experience. However, even in such an attempt, it is very unlikely that online consumers will actually be able to visit the website and switch to the purchase stage. This is because online consumers do not just visit the website to purchase products but use and browse the websites differently according to their shopping motives and purposes. Therefore, it is important to analyze various types of visits as well as visits to purchase, which is important for understanding the behaviors of online consumers. In this study, we explored the clustering analysis of session based on click stream data of e-commerce company in order to explain diversity and complexity of search behavior of online consumers and typified search behavior. For the analysis, we converted data points of more than 8 million pages units into visit units' sessions, resulting in a total of over 500,000 website visit sessions. For each visit session, 12 characteristics such as page view, duration, search diversity, and page type concentration were extracted for clustering analysis. Considering the size of the data set, we performed the analysis using the Mini-Batch K-means algorithm, which has advantages in terms of learning speed and efficiency while maintaining the clustering performance similar to that of the clustering algorithm K-means. The most optimized number of clusters was derived from four, and the differences in session unit characteristics and purchasing rates were identified for each cluster. The online consumer visits the website several times and learns about the product and decides the purchase. In order to analyze the purchasing process over several visits of the online consumer, we constructed the visiting sequence data of the consumer based on the navigation patterns in the web site derived clustering analysis. The visit sequence data includes a series of visiting sequences until one purchase is made, and the items constituting one sequence become cluster labels derived from the foregoing. We have separately established a sequence data for consumers who have made purchases and data on visits for consumers who have only explored products without making purchases during the same period of time. And then sequential pattern mining was applied to extract frequent patterns from each sequence data. The minimum support is set to 10%, and frequent patterns consist of a sequence of cluster labels. While there are common derived patterns in both sequence data, there are also frequent patterns derived only from one side of sequence data. We found that the consumers who made purchases through the comparative analysis of the extracted frequent patterns showed the visiting pattern to decide to purchase the product repeatedly while searching for the specific product. The implication of this study is that we analyze the search type of online consumers by using large - scale click stream data and analyze the patterns of them to explain the behavior of purchasing process with data-driven point. Most studies that typology of online consumers have focused on the characteristics of the type and what factors are key in distinguishing that type. In this study, we carried out an analysis to type the behavior of online consumers, and further analyzed what order the types could be organized into one another and become a series of search patterns. In addition, online retailers will be able to try to improve their purchasing conversion through marketing strategies and recommendations for various types of visit and will be able to evaluate the effect of the strategy through changes in consumers' visit patterns.

• Korean Journal of Soil Science and Fertilizer
• /
• v.25 no.3
• /
• pp.202-212
• /
• 1992

This study reports on the genesis and mineralogical characteristics of the clay minerals in the soils derived from the five major parent rocks of granite, granite-gneiss, limestone, shale, and basalt in Korea. The investigation on the mineralogical aspects of primary and secondary minerals of the rocks and coarse fractions in the soils have been already reported. In this report, the identification of clay minerals in the soil clay fractions was done through the analyses of chemical, X-ray diffraction, and thermal methods. The studies showed clearly that much of the clay minerals was evolved by the weathering of primary minerals and some were further developed by the transformation of secondary minerals. Cation exchange capacity(CEC) of the clay fractions increased with higher amotunts of vermiculite, chlorite, and illite, however, decreased with higher hydroxy octahedral sheet within the interlayer spaces of vermiculite even if dominant clay with vermiculite. Feldspars in the granite and granite-gneiss might be completely transformed to kaolin mineral, Illite, chlolrite, and vermiculite formed by the alteration of micas, amphibole, augite, and primary chlorile seem to be subsequently transformed to the mixed layer minerals such as illite/vermiculite, illite/chlorite, and chlorite/vermiculite. These weathering products may be ultimately transformed into kaolin minerals. The smectite minerals in the clay fractions of the soils developed on the limestone are considerably present and they seem to be formed directly by the precipitation from high Mg solution and/or by the transformation of vermiculite from micas and chlorite in the parent materials. Abundant presence of illite in the soil clays developed on the shale is considered to have inherited from the fine particles and more resistant hydrous muscovite. The weathering sequences of the hydrous muscovite were as follows according to the degree of soil development ; hydrous muscovite ${\rightarrow}$ illite/vermiculite mixed layer(Inceptisols, Daegu series) and hydrous muscovite ${\rightarrow}$ illite/vermiculite mixed layer ${\rightarrow}$ vermiculite ${\rightarrow}$ kaolin mineral(Alfisols, Buyeo series). The plagioclase in the basalt might be mostly weathered to kaolin minerais. The augite in the basalt is likely to be transformed through progressive stage of weathering, augite ${\rightarrow}$ chlorite ${\rightarrow}$ chlorote/vermiculite mixed layer ${\rightarrow}$ vermiculite ${\rightarrow}$ kaolin. Another weathering sequence of augite could be expected, augite ${\rightarrow}$ chlorite ${\rightarrow}$ illite by the presence of illite and illite/vermiculite mixed layer in the clay fractions. Vermiculite and gibbsite were quantified from thermogravimetry(TG) and kaolin minerals, from both TG and differerential thermal analysis (DTA). Vermiculite in Jangseong series from the limestone was the dominant clay mineral of 21.7 percent and had a range in the order of 9.2 percent in Buyeo series to 5.4 percent in Daegu series from the shale. The rest soils ranged from 8.8 to 28.3 percent. Kaolin minerals were the dominant clay mineral of 32.7 percent in Asan series from the granite-gneiss and Gueom series of 32.0 percent from the basalt. The soils from the limestone ranged from 9.4 to 14.9 percent. The rest soils ranged from 8.9 to 28.6 percent. Gibbsite were 3.9 and 2.3 percent for Weoljeong and Chahang series from the granite, respectively. In Asan and Cheongsan series from the giranite-gneiss were 1.4 and 4.5 percent, respectively, and 3.6 percent in Jangpa series from the basalt.

• Korean Journal of Environmental Biology
• /
• v.39 no.1
• /
• pp.119-135
• /
• 2021

Korea has stepped up efforts to investigate and catalog its flora and fauna to conserve the biodiversity of the Korean Peninsula and secure biological resources since the ratification of the Convention on Biological Diversity (CBD) in 1992 and the Nagoya Protocol on Access to Genetic Resources and the Fair and Equitable Sharing of Benefits (ABS) in 2010. Thus, after its establishment in 2007, the National Institute of Biological Resources (NIBR) of the Ministry of Environment of Korea initiated a project called the Korean Indigenous Species Investigation Project to investigate indigenous species on the Korean Peninsula. For 15 years since its beginning in 2006, this project has been carried out in five phases, Phase 1 from 2006-2008, Phase 2 from 2009-2011, Phase 3 from 2012-2014, Phase 4 from 2015-2017, and Phase 5 from 2018-2020. Before this project, in 2006, the number of indigenous species surveyed was 29,916. The figure was cumulatively aggregated at the end of each phase as 33,253 species for Phase 1 (2008), 38,011 species for Phase 2 (2011), 42,756 species for Phase 3 (2014), 49,027 species for Phase 4 (2017), and 54,428 species for Phase 5(2020). The number of indigenous species surveyed grew rapidly, showing an approximately 1.8-fold increase as the project progressed. These statistics showed an annual average of 2,320 newly recorded species during the project period. Among the recorded species, a total of 5,242 new species were reported in scientific publications, a great scientific achievement. During this project period, newly recorded species on the Korean Peninsula were identified using the recent taxonomic classifications as follows: 4,440 insect species (including 988 new species), 4,333 invertebrate species except for insects (including 1,492 new species), 98 vertebrate species (fish) (including nine new species), 309 plant species (including 176 vascular plant species, 133 bryophyte species, and 39 new species), 1,916 algae species (including 178 new species), 1,716 fungi and lichen species(including 309 new species), and 4,812 prokaryotic species (including 2,226 new species). The number of collected biological specimens in each phase was aggregated as follows: 247,226 for Phase 1 (2008), 207,827 for Phase 2 (2011), 287,133 for Phase 3 (2014), 244,920 for Phase 4(2017), and 144,333 for Phase 5(2020). A total of 1,131,439 specimens were obtained with an annual average of 75,429. More specifically, 281,054 insect specimens, 194,667 invertebrate specimens (except for insects), 40,100 fish specimens, 378,251 plant specimens, 140,490 algae specimens, 61,695 fungi specimens, and 35,182 prokaryotic specimens were collected. The cumulative number of researchers, which were nearly all professional taxonomists and graduate students majoring in taxonomy across the country, involved in this project was around 5,000, with an annual average of 395. The number of researchers/assistant researchers or mainly graduate students participating in Phase 1 was 597/268; 522/191 in Phase 2; 939/292 in Phase 3; 575/852 in Phase 4; and 601/1,097 in Phase 5. During this project period, 3,488 papers were published in major scientific journals. Of these, 2,320 papers were published in domestic journals and 1,168 papers were published in Science Citation Index(SCI) journals. During the project period, a total of 83.3 billion won (annual average of 5.5 billion won) or approximately US $75 million (annual average of US $5 million) was invested in investigating indigenous species and collecting specimens. This project was a large-scale research study led by the Korean government. It is considered to be a successful example of Korea's compressed development as it attracted almost all of the taxonomists in Korea and made remarkable achievements with a massive budget in a short time. The results from this project led to the National List of Species of Korea, where all species were organized by taxonomic classification. Information regarding the National List of Species of Korea is available to experts, students, and the general public (https://species.nibr.go.kr/index.do). The information, including descriptions, DNA sequences, habitats, distributions, ecological aspects, images, and multimedia, has been digitized, making contributions to scientific advancement in research fields such as phylogenetics and evolution. The species information also serves as a basis for projects aimed at species distribution and biological monitoring such as climate-sensitive biological indicator species. Moreover, the species information helps bio-industries search for useful biological resources. The most meaningful achievement of this project can be in providing support for nurturing young taxonomists like graduate students. This project has continued for the past 15 years and is still ongoing. Efforts to address issues, including species misidentification and invalid synonyms, still have to be made to enhance taxonomic research. Research needs to be conducted to investigate another 50,000 species out of the estimated 100,000 indigenous species on the Korean Peninsula.

• The Korean Journal of Pesticide Science
• /
• v.15 no.4
• /
• pp.545-572
• /
• 2011

The genetic diagnosis methods by RT-PCR and Virion capture (VC)/RT-PCR against Rice stripe virus (RSV) were developed. Three diagnosis methods of seedling test, ELISA and RT-PCR were compared in virus detection sensitivity (VDS) for RSV. The VDS of ELISA for RSV viruliferous small brown plant hopper (SBPH) was higher with 40.5% than that of seedling test. The VDS of RT-PCR was higher with 21% than that of ELISA. The VDS of ELISA and VC/RT-PCR was same with 9.2% in average on the SBPH collected from fields at the areas of Gimpo, Pyungtaeg and Sihueng, Gyeonggi province in 2009. The specific primers of RSV for SBPH and rice plant were developed for the diagnosis by Real time PCR. The RQ value of Real time PCR for the viruliferous and non viruliferous SBPH was 1 for 50 heads of non viruliferous SBPH, 96.5 for 50 heads of viruliferous SBPH, 23.1 for 10 heads of viruliferous SBPH + 40 heads of non viruliferous SBPH, and 75.6 for 30 heads of viruliferous SBPH + 20 heads of non viruliferous SBPH. The RQ value was increased positively by the ratio of viruliferous SBPH. Full sequences of 4 genomes of RSV RNA1, RNA2, RNA3 and RNA4 were analysed for the 13 RSV isolates from rice plants collected from different areas. Genetic relationships among the RSV isolates of Korea, Japan and China were classified as China + Korea, and China + Korea + Japan by phylogenetic analysis for RSV RNA1 and RNA2. In case of RNA3 involved in pathogenicity, genetic relationship of RSV among the three countries was grouped into 3 as China, China + Korea, and Korea + Japan. According to the genetic relationships in RSV RNA4, RSV isolates were grouped into 4 as China, Korea, China + Korea + Japan, and Korea + Japan. Viruliferous insect rate (VIR) of RSV in average increased in each year from 2008 to 2010, and the rates were 4.3%, 6.1%, and 7.2%, respectively, at the 28 major rice production areas in 7 provinces including Gyeonggido. The highest VIR in each year was 11.3% of Gyeonggido in 2008, 20.1% of Jellanamdo in 2009 and 14.2% of Chungcheongbukdo in 2010. The highest VIR depending upon the investigated areas was 22.1% at Buan of Jellabukdo in 2008, 36% at Wando and Jindo of Jellanamdo in 2009, and 30.0% at Boeun of Chungcheongbukdo in 2010. Average population density (APD) of overwintered SBPH was 13.1 heads in 2008, 13.9 heads in 2009 and 5.6 heads in 2010. The highest APD was 39.1 and 60.4 heads at Buan of Jellabukdo in 2008 and 2009, respectively, and 14.0 heads at Pyungtaeg of Gyeonggido. The acreage of RSV occurred fields was 869 ha in the western and southern parts, mainly at Jindo and Wando areas, of Jellanamdo in 2008. In 2009, RSV occurred in the acreage of 21,541 ha covered whole country, especially, partial and whole plant death were occurred with infection rate of 55.2% at 3,025 plots in 53 Li, 39 Eup/Myun, 19 Si/Gun of Gyeonggido, Incheonsi, Chungcheongnamdo, Jeollabukdo and Jeollanamdo. Seasonal development of overwintered SBPH was investigated at Buan, Jeollabukdo, and Jindo, Jeollanamdo for 3 years from 2008. Most SBPH developed to the 3rd and 4th instar on the periods of May 20 to June 10, and they developed to the adult stage for the 1st generation on Mid and Late June. In 2009, all SBPH trapped by sky net trap were adult on May 31 to June 1 at Mid-western aeas of Taean, Seosan and Buan, and South-western areas of Sinan and Jindo. The population density of adult SBPH was 963 heads at Taean, 919 at Seocheon and 819 at Sinan area. The origin of these higher population of adult SBPH were verified from the population of non-overwintered SBPH but immigrant SBPH. From Mid May to Mid June in 2010, adult SBPH could not be counted as immigrant insects by sky net trap. The variation of RSV VIR was high with 2.1% to 9.5% for immigrant adult SBPH trapped by sky net trap at Hongsung of Chungcheongbukdo, Buan of Jeollabukdo and so forth in 2009. The highest VIR for the immigrant adult SBPH was 9.5% at Boryung of Chungcheongnamdo, followed by 7.9% at Hongsung of Chungcheongnamdo, 6.5% at Younggwang of Jeollanamdo, and 6.4% at Taean of Cheongcheongnamdo. The infection rate of RSV on rice plants induced by the immigrant adult SBPH cultivated near sky net trap after about 10 days from immigration on June 12 in 2009 was 84.6% at Taean, 65.4% at Buan and 92.9% at Jindo, and 81% in average through genetic diagnosis of RT-PCR. Barley known as a overwintering host plant of RSV had very low infection rate of 0.2% from 530 specimens collected at 10 areas covering whole country including Pyungtaeg of Gyeonggido. Twenty nine plant species were newly recorded as natural hosts of RSV. In winter annual plant species, 11 plants including Vulpia myuros showed RSV infection rate of 24.9%. The plant species in summer annual ecotype were 13 including Digitaria ciliaris with 44.9%, Echinochloa crusgalli var. echinata with 95.2% and Setaria faberi with 65.5% in infection rate of RSV. Five perennial plants including Miscanths sacchariflorus with infection rate of 33.3% were recorded as hosts of RSV. Rice cultivars, 8 susceptible cultivars including Donggin1 and 17 resistant ones including Samgwang, were screened in field conditions at 3 different areas of Buan, Iksan and Ginje in 2009. All the susceptible cultivars were showed typical symptom of mosaic and wilt. In 17 genetic resistant cultivar, 12 cultivars were susceptible, however, 5 cultivars were field-resistant plus genetic resistant to RSV as non symptom expression. When RSV was artificially inoculated at seedling stage to 4 cultivars known as genetic resistant and 3 cultivars known as genetic susceptible, the symptom expression in resistant cultivars was lower as 19.3% in average than that of 53.3% in susceptible ones. In comparison of symptom expression rate and viral infection rate using resistant Nampyung and susceptible Heugnam cultivars by artificial inoculation of RSV at seedling stage, the symptom expression of Heugnam was higher as 28% than 12% of Nampyung. However, virion infection of resistant Nampyung cultivar was higher as 12% reversely than 85% of susceptible Heugnam. Yield loss of rice was investigated by the artificial inoculation of RSV at the seedling stage of resistant cultivars of Nampyung and Onnuri, and susceptible cultivars of Donggin1 and Ungwang for 3 years from 2008. The average yield per plant was 7.8 g, 8.5 g and 13.8 g on rice plants inoculated at seedling stage, tillering stage and maximum tillering stage, respectively. The yield loss rate was increased by earlier infection of RSV with 51% at seedling stage, 46% at tillering stage and 13% at maximum tillering stage. In resistant rice cultivars, there was no statistically significant relation between infection time and yield loss. In natural fields on susceptible rice cultivar of Ungwang at Taean and Jindo areas in 2009, the yield loss rate was increased with same tendency to the infection hill rate having the corelation coefficient of 0.94 when the viral infection was over 23.4%.