• Korean Journal of Mineralogy and Petrology
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• v.35 no.3
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• pp.367-376
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• 2022

This study is a preliminary step to understand the reaction between various liquids and zeolite in the subduction zone environment. Stilbite, NaCa₄(Al₉Si₂₇)O₇₂·28(H₂O), was selected and high pressure study was conducted on compressional behavior by the pressure-transmitting medium (PTM). Water and NaHCO₃ solution that can exist in the subduction zone was used as PTM, and samples were pressurized from ambient to a maximum of 2.5 GPa. Below 1.0 GPa, both experiments show a low linear compressibility in the range of 0.001 to 0.004 GPa^-1 and a high bulk modulus of 220(1) GPa. This is presumably because the structure of the stilbite becomes very dense due to insertion of water molecules or cations into the channel. On the other hand, at 1.0 GPa or higher, the trends of the two experiments are different. In the water run, the linear compressibility of the c-axis is increased to 0.006(1) GPa^-1. In the NaHCO₃ run, the linear compressibility of the b- and c-axis is increased to 0.006(1) GPa^-1. The bulk modulus after 1.0 GPa shows values of 40(1) and 52(7) GPa in water and NaHCO₃ run, respectively, confirming that stilbite becomes more compressible than that before 1.0 GPa. It is caused by the migration of cations and water molecules inside the channel, as the water molecules in the PTM start to freeze and stop to insert toward the channel at 1.0 GPa or more. In the NaHCO₃ run, it is assumed that the distribution of extra-framework species inside the structure is changed by substitution of the Na⁺ cation. It can be expected from tendency of the relative intensity ratio of the (001) and (020) peaks which show a different from that of the water run.

• Journal of Christian Education in Korea
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• v.69
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• pp.77-104
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• 2022

The purpose of this study was to investigate the research trend of forest play. The purpose of this study is to provide basic data for the vitalization of forest play research by analyzing the research period, research content, and research methods. For this study, 57 domestic master's and doctoral dissertations were extracted through the National Assembly Library and the Research Information Sharing Service(RISS) with the keywords of 'forest', 'play', and 'forest play'. The frequency and percentage were calculated by analyzing forest play research based on four criteria: research period, research content, research method, and research subject. As a result of the research, first, the trend of forest play research by period is from 2011 to 2021, with 49 articles (85.9%) for master's degrees and 8 articles (14.1%) for doctor's degrees. Second, the trend by research content was found to be 16 basic studies (28.1%) and 41 practical studies (71.9%). Forest play research is being actively conducted centered on practical research. Third, the trends by research method were in the order of 39 quantitative studies (68.4%), 17 qualitative studies (29.8%), and 1 literature study (1.8%). Forest play research is focused on quantitative research, and comparatively qualitative research and literature research account for a low proportion. Fourth, the trend by study subject was 56 single subject studies (98.2%). The single subjects were 52 children (91.2%), 3 teachers (5.2%), and 1 parent (1.8%). As for the mixed subjects, there is one study (1.8%) targeting children and parents, and it is necessary to conduct a study with mixed subjects. As for the study of material subjects, 42 articles (73.7%) in the natural environment, 13 articles (22.8%) in educational institutions, and 2 articles (3.5%) in the media were found in the order. Research on the home environment related to forest play is insufficient, so research on parents, children-parents, and home environment related to forest play should be conducted in the future.

• Journal of the Korean Society of Tobacco Science
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• v.24 no.1
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• pp.67-73
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• 2002

In light of addressing consumer health concern, coping with anti-tobacco movement, and promoting new product, tobacco industry is actively pursuing to make a new generation of cigarettes with low tar and nicotine deliveries, and less harmful substances. Low tar and low nicotine cigarettes increases their market shares dramatically world wide, especially in KT&G, multinational tobacco companies, EU countries, even in China regulated by CNTC to set up yearly target to lower tar and nicotine deliveries. On the other hand, to design a new cigarette with reduced harmful substances begins to gain speed. The "modified Hoffmann list" publishes thirty plus substances in tobacco leaf and main smoke stream, which is the prime suspect causing health problems. Various ways and means are developed to reduce such components including new tobacco breeds, new curing method, tobacco leaf treatment before processing, selected filtration system, innovated casing system to reduce free radicals, as well as some non conventional cigarette products. In TSRC held this year, the main topic is related to reduce tobacco specific nitrosamines in tobacco leaf. The new generation of cigarette is in the horizon. It still needs a lot help to produce commercial products with satisfied taste and aroma characters. The flavor industry is not regulated by many governments demanding which ingredients might or might not be for tobacco use. However, most of the cigarette companies self impose a list of ingredients to guide flavor suppliers to design flavors. Unfortunately, the number of ingredients in those lists is getting shorter every year. It is understandable that the health is not the only reason. Some cigarette companies are playing safe to protect the company from potential lawsuit, while others are just copying from their competitors. Moreover, it is obvious that it needs more assistance from casings and flavors to design new generation of cigarettes with missing certain flavor components in tobacco leaf and main smoke stream. These flavor components are either non-existed or at lower level at new form of cured tobacco leaf or filtered in the main smoke stream along with reduced harmful substances. The use of carbon filters and other selected filtration system poses another tough task for flavor system design. Specific flavor components are missing from the smoke analysis data, which brings a notion of "carbon taste" and "dryness" of mouth feel. It is ever more demanded by cigarette industry to flavor suppliers to produce flavors as body enhancer, tobacco notes, salivating agents, harshness reducer, and various of aromatic notes provided they are safe to use. Another trend is that water based flavor or flavor with reduced ethanol as solvent is gaining popularity. It is preferred by some cigarette companies that the flavor is compounded with all natural ingredients or all ingredients should he GMO free. The new generation of cigarettes demands many ways of new thinking process. It is also vital for tobacco industry. It reflects the real needs for the consumers that the cigarette product should be safe to use as well as bearing the taste and aroma characters smokers always enjoyed. An effective tobacco flavor system is definitely a part of the equation. The global trend of tobacco industry is like trends of any other industries lead by consumer needs, benefited with new technology availability, affected by the global economy, and subjected for various rules and regulations. Anti-tobacco organizations and media exceptionally scrutinize cigarette, as a legal commercial product. Cigarette is probably the most studied commercial product for its composition, structure, deliveries, effects, as well as its new developmental trend. Therefore, any new trend of cigarette development would be within these boundaries. This paper is trying to point out what it would be like for tobacco industry in the next few yews and what concerns the tobacco industry. It focuses mostly on the efforts to produce safer cigarettes. It is such a vital task for the tobacco industry and its affiliate industries such as cigarette papers, filters, flavors, and other materials. The facts and knowledge presented in this paper might be well known for the public. Some of the comments and predictions are very much personal opinion for a further discussion.

• Journal of Wetlands Research
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• v.25 no.2
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• pp.145-158
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• 2023

Constructed wetlands (CWs) are effective technologies for urban wastewater management, utilizing natural physico-chemical and biological processes to remove pollutants. This study employed a bibliometric analysis approach to investigate the progress and future research trends in the field of CWs. A comprehensive review of 100 most-recently published and open-access articles was performed to analyze the performance of CWs in treating wastewater. Spain, China, Italy, and the United States were among the most productive countries in terms of the number of published papers. The most frequently used keywords in publications include water quality (n=19), phytoremediation (n=13), stormwater (n=11), and phosphorus (n=11), suggesting that the efficiency of CWs in improving water quality and removal of nutrients were widely investigated. Among the different types of CWs reviewed, hybrid CWs exhibited the highest removal efficiencies for BOD (88.67%) and TSS (95.67%), whereas VSSF, and HSSF systems also showed high TSS removal efficiencies (83.25%, and 78.83% respectively). VSSF wetland displayed the highest COD removal efficiency (71.82%). Generally, physical processes (e.g., sedimentation, filtration, adsorption) and biological mechanisms (i.e., biodegradation) contributed to the high removal efficiency of TSS, BOD, and COD in CW systems. The hybrid CW system demonstrated highest TN removal efficiency (60.78%) by integrating multiple treatment processes, including aerobic and anaerobic conditions, various vegetation types, and different media configurations, which enhanced microbial activity and allowed for comprehensive nitrogen compound removal. The FWS system showed the highest TP removal efficiency (54.50%) due to combined process of settling sediment-bound phosphorus and plant uptake. Phragmites, Cyperus, Iris, and Typha were commonly used in CWs due to their superior phytoremediation capabilities. The study emphasized the potential of CWs as sustainable alternatives for wastewater management, particularly in urban areas.

• Knowledge Management Research
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• v.23 no.4
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• pp.315-338
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• 2022

In 1986, Korea established legal systems to support small and medium-sized start-ups, which becomes the main pillars of national development. The legal systems have stimulated start-up ecosystems to have more than 1 million new start-up companies founded every year during the past 30 years. To analyze the trend of Korea's start-up ecosystem, in this study, we collected 1.18 million news articles from 1991 to 2020. Then, we extracted news articles that have the keywords "start-up", "venture", and "start-up". We employed network analysis and topic modeling to analyze collected news articles. Our analysis can contribute to analyzing the government policy direction shown in the history of start-up support policy. Specifically, our analysis identifies the dynamic characteristics of government influenced by external environmental factors (e.g., society, economy, and culture). The results of our analysis suggest that the start-up ecosystems in Korea have changed and developed mainly by the government policies for corporation governance, industrial development planning, deregulation, and economic prosperity plan. Our frequency keyword analysis contributes to understanding entrepreneurial productivity attributed to activities among the networked components in industrial ecosystems. Our analyses and results provide practitioners and researchers with practical and academic implications that can help to establish dedicated support policies through forecast tasks of the economic environment surrounding the start-ups. Korean entrepreneurial productivity has been empowered by growing numbers of large companies in the mobile phone industry. The spectrum of large companies incorporates content startups, platform providers, online shopping malls, and youth-oriented start-ups. In addition, economic situational factors contribute to the growth of Korean entrepreneurial productivity the economic, which are related to the global expansions of the mobile industry, and government efforts to foster start-ups. Our research is methodologically implicative. We employ natural language processes for 30 years of media articles, which enables more rigorous analysis compared to the existing studies which only observe changes in government and policy based on a qualitative manner.

• Journal of Intelligence and Information Systems
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• v.24 no.1
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• pp.183-203
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• 2018

News articles are the most suitable medium for examining the events occurring at home and abroad. Especially, as the development of information and communication technology has brought various kinds of online news media, the news about the events occurring in society has increased greatly. So automatically summarizing key events from massive amounts of news data will help users to look at many of the events at a glance. In addition, if we build and provide an event network based on the relevance of events, it will be able to greatly help the reader in understanding the current events. In this study, we propose a method for extracting event networks from large news text data. To this end, we first collected Korean political and social articles from March 2016 to March 2017, and integrated the synonyms by leaving only meaningful words through preprocessing using NPMI and Word2Vec. Latent Dirichlet allocation (LDA) topic modeling was used to calculate the subject distribution by date and to find the peak of the subject distribution and to detect the event. A total of 32 topics were extracted from the topic modeling, and the point of occurrence of the event was deduced by looking at the point at which each subject distribution surged. As a result, a total of 85 events were detected, but the final 16 events were filtered and presented using the Gaussian smoothing technique. We also calculated the relevance score between events detected to construct the event network. Using the cosine coefficient between the co-occurred events, we calculated the relevance between the events and connected the events to construct the event network. Finally, we set up the event network by setting each event to each vertex and the relevance score between events to the vertices connecting the vertices. The event network constructed in our methods helped us to sort out major events in the political and social fields in Korea that occurred in the last one year in chronological order and at the same time identify which events are related to certain events. Our approach differs from existing event detection methods in that LDA topic modeling makes it possible to easily analyze large amounts of data and to identify the relevance of events that were difficult to detect in existing event detection. We applied various text mining techniques and Word2vec technique in the text preprocessing to improve the accuracy of the extraction of proper nouns and synthetic nouns, which have been difficult in analyzing existing Korean texts, can be found. In this study, the detection and network configuration techniques of the event have the following advantages in practical application. First, LDA topic modeling, which is unsupervised learning, can easily analyze subject and topic words and distribution from huge amount of data. Also, by using the date information of the collected news articles, it is possible to express the distribution by topic in a time series. Second, we can find out the connection of events in the form of present and summarized form by calculating relevance score and constructing event network by using simultaneous occurrence of topics that are difficult to grasp in existing event detection. It can be seen from the fact that the inter-event relevance-based event network proposed in this study was actually constructed in order of occurrence time. It is also possible to identify what happened as a starting point for a series of events through the event network. The limitation of this study is that the characteristics of LDA topic modeling have different results according to the initial parameters and the number of subjects, and the subject and event name of the analysis result should be given by the subjective judgment of the researcher. Also, since each topic is assumed to be exclusive and independent, it does not take into account the relevance between themes. Subsequent studies need to calculate the relevance between events that are not covered in this study or those that belong to the same subject.

• Journal of Intelligence and Information Systems
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• v.20 no.2
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• pp.109-122
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• 2014

People are nowadays creating a tremendous amount of data on Social Network Service (SNS). In particular, the incorporation of SNS into mobile devices has resulted in massive amounts of data generation, thereby greatly influencing society. This is an unmatched phenomenon in history, and now we live in the Age of Big Data. SNS Data is defined as a condition of Big Data where the amount of data (volume), data input and output speeds (velocity), and the variety of data types (variety) are satisfied. If someone intends to discover the trend of an issue in SNS Big Data, this information can be used as a new important source for the creation of new values because this information covers the whole of society. In this study, a Twitter Issue Tracking System (TITS) is designed and established to meet the needs of analyzing SNS Big Data. TITS extracts issues from Twitter texts and visualizes them on the web. The proposed system provides the following four functions: (1) Provide the topic keyword set that corresponds to daily ranking; (2) Visualize the daily time series graph of a topic for the duration of a month; (3) Provide the importance of a topic through a treemap based on the score system and frequency; (4) Visualize the daily time-series graph of keywords by searching the keyword; The present study analyzes the Big Data generated by SNS in real time. SNS Big Data analysis requires various natural language processing techniques, including the removal of stop words, and noun extraction for processing various unrefined forms of unstructured data. In addition, such analysis requires the latest big data technology to process rapidly a large amount of real-time data, such as the Hadoop distributed system or NoSQL, which is an alternative to relational database. We built TITS based on Hadoop to optimize the processing of big data because Hadoop is designed to scale up from single node computing to thousands of machines. Furthermore, we use MongoDB, which is classified as a NoSQL database. In addition, MongoDB is an open source platform, document-oriented database that provides high performance, high availability, and automatic scaling. Unlike existing relational database, there are no schema or tables with MongoDB, and its most important goal is that of data accessibility and data processing performance. In the Age of Big Data, the visualization of Big Data is more attractive to the Big Data community because it helps analysts to examine such data easily and clearly. Therefore, TITS uses the d3.js library as a visualization tool. This library is designed for the purpose of creating Data Driven Documents that bind document object model (DOM) and any data; the interaction between data is easy and useful for managing real-time data stream with smooth animation. In addition, TITS uses a bootstrap made of pre-configured plug-in style sheets and JavaScript libraries to build a web system. The TITS Graphical User Interface (GUI) is designed using these libraries, and it is capable of detecting issues on Twitter in an easy and intuitive manner. The proposed work demonstrates the superiority of our issue detection techniques by matching detected issues with corresponding online news articles. The contributions of the present study are threefold. First, we suggest an alternative approach to real-time big data analysis, which has become an extremely important issue. Second, we apply a topic modeling technique that is used in various research areas, including Library and Information Science (LIS). Based on this, we can confirm the utility of storytelling and time series analysis. Third, we develop a web-based system, and make the system available for the real-time discovery of topics. The present study conducted experiments with nearly 150 million tweets in Korea during March 2013.

• Journal of Intelligence and Information Systems
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• v.25 no.4
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• pp.141-154
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• 2019

Rapid growth of internet technology and social media is progressing. Data mining technology has evolved to enable unstructured document representations in a variety of applications. Sentiment analysis is an important technology that can distinguish poor or high-quality content through text data of products, and it has proliferated during text mining. Sentiment analysis mainly analyzes people's opinions in text data by assigning predefined data categories as positive and negative. This has been studied in various directions in terms of accuracy from simple rule-based to dictionary-based approaches using predefined labels. In fact, sentiment analysis is one of the most active researches in natural language processing and is widely studied in text mining. When real online reviews aren't available for others, it's not only easy to openly collect information, but it also affects your business. In marketing, real-world information from customers is gathered on websites, not surveys. Depending on whether the website's posts are positive or negative, the customer response is reflected in the sales and tries to identify the information. However, many reviews on a website are not always good, and difficult to identify. The earlier studies in this research area used the reviews data of the Amazon.com shopping mal, but the research data used in the recent studies uses the data for stock market trends, blogs, news articles, weather forecasts, IMDB, and facebook etc. However, the lack of accuracy is recognized because sentiment calculations are changed according to the subject, paragraph, sentiment lexicon direction, and sentence strength. This study aims to classify the polarity analysis of sentiment analysis into positive and negative categories and increase the prediction accuracy of the polarity analysis using the pretrained IMDB review data set. First, the text classification algorithm related to sentiment analysis adopts the popular machine learning algorithms such as NB (naive bayes), SVM (support vector machines), XGboost, RF (random forests), and Gradient Boost as comparative models. Second, deep learning has demonstrated discriminative features that can extract complex features of data. Representative algorithms are CNN (convolution neural networks), RNN (recurrent neural networks), LSTM (long-short term memory). CNN can be used similarly to BoW when processing a sentence in vector format, but does not consider sequential data attributes. RNN can handle well in order because it takes into account the time information of the data, but there is a long-term dependency on memory. To solve the problem of long-term dependence, LSTM is used. For the comparison, CNN and LSTM were chosen as simple deep learning models. In addition to classical machine learning algorithms, CNN, LSTM, and the integrated models were analyzed. Although there are many parameters for the algorithms, we examined the relationship between numerical value and precision to find the optimal combination. And, we tried to figure out how the models work well for sentiment analysis and how these models work. This study proposes integrated CNN and LSTM algorithms to extract the positive and negative features of text analysis. The reasons for mixing these two algorithms are as follows. CNN can extract features for the classification automatically by applying convolution layer and massively parallel processing. LSTM is not capable of highly parallel processing. Like faucets, the LSTM has input, output, and forget gates that can be moved and controlled at a desired time. These gates have the advantage of placing memory blocks on hidden nodes. The memory block of the LSTM may not store all the data, but it can solve the CNN's long-term dependency problem. Furthermore, when LSTM is used in CNN's pooling layer, it has an end-to-end structure, so that spatial and temporal features can be designed simultaneously. In combination with CNN-LSTM, 90.33% accuracy was measured. This is slower than CNN, but faster than LSTM. The presented model was more accurate than other models. In addition, each word embedding layer can be improved when training the kernel step by step. CNN-LSTM can improve the weakness of each model, and there is an advantage of improving the learning by layer using the end-to-end structure of LSTM. Based on these reasons, this study tries to enhance the classification accuracy of movie reviews using the integrated CNN-LSTM model.

• Korean journal of applied entomology
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• v.13 no.3 s.20
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• pp.105-133
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• 1974

The present study is an attempt to solve the basic problems involved in the control of the Sclerotium disease. The biologic stranis of Sclerotium rolfsii Sacc., pathogen of Sclerotium disease of Magnolia kobus, were differentiated, and the effects of vitamins, various nitrogen and carbon sources on its mycelial growth and sclerotial production have been investigated. In addition the relationship between the cultural filtrate of Penicillium sp. and the growth of Sclerotium rolfsii, the tolerance of its mycelia or sclerotia to moist heat or drought and to Benlate (methyl-(butylcarbamoy 1)-2-benzimidazole carbamate), Tachigaren (3-hydroxy-5-methylisoxazole) and other chemicals were also clarified. The results are summarizee as follows: 1. There were two biologic strains, Type-l and Type-2 among isolates. They differed from each other in the mode of growth and colonial appearance on the media, aversion phenomenon and in their pathogenicity. These two types had similar pathogenicity to the Magnolia kobus and Robinia pseudoacasia, but behaved somewhat differently to the soybaen and cucumber, the Type-l being more virulent. 2. Except potassium nitrite, sodium nitrite and glycine, all of the 12 nitrogen sources tested were utilized for the mycelial growth and sclerotial production of this fungus when 10r/l of thiamine hydrochloride was added in the culture solution. Considering the forms of nitrogen, ammonium nitrogen was more available than nitrate nitrogen for the growth of mycelia, but nitrate nitrogen was better for sclerotia formation. Organic nitrogen showed different availabilities according to compounds used. While nitrite nitrogen was unavailable for both mycelial growth and sclerotial formation whether thiamine hydrochlioride was added or not. 3. Seven kinds of carbon sources examined were not effective in general, as long as thiamine hydrochloride was not added. When thiamine hydrochloride was added, glucose and saccharose exhibited mycelial growth, while rnaltose and soluble starch gave lesser, and xylose, lactose, and glycine showed no effect at all,. In the sclerotial production, all the tested carbon sources, except lactose, were effective, and glucose, maltose, saccharose, and soluble starch gave better results. 4. At the same level of nitrogen, the amount of mycelial growth increased as more carbon Sources were applied but decreased with the increase of nitrogen above 0.5g/1. The amount of sclerotial production decreased wi th the increase of carbon sources. 5. Sclerotium rolfsii was thiamine-defficient and required thiamine 20r/l for maximun growth of mycelia. At a higher concentration of more than 20r/l, however, mycelial growth decreased as the concentration increased, and was inhibited at l50r/l to such a degree of thiamine-free. 6. The effect of the nitrogen sources on the mycelial growth under the presence of thiamine were recognized in the decreasing order of $NH_4NO_3,\;(NH_4)_2SO_4,\;asparagine,\;KNO_3$, and their effects on the sclerotial production in the order of $KNO_3,\;NH_4NO_3,\;asparagine,\;(NH_4)_2SO_4$. The optimum concentration of thiamine was about 12r/l in $KNO_3$ and about 16r/l in asparagine for the growth of mycelia; about 8r/l in $KNO_3$ and $NH_4NO_3$, and 16r/l in asparagine for the production of sclerotia. 7. After the fungus started to grow, the pH value of cultural filtrate rapidly dropped to about 3.5. Hereafter, its rate slowed down as the growth amount increased and did not depreciated below pH2.2. 8. The role of thiamine in the growth of the organism was vital. If thiamine was not added, the combination of biotin, pyridoxine, and inositol did not show any effects on the growth of the organism at all. Equivalent or better mycelial growth was recognized in the combination of thiamine+pyridoxine, thiamine+inositol, thiamine+biotin+pyridoxine, and thiamine+biotin+pyridoxine+inositol, as compared with thiamine alone. In the combinations of thiamine+biotin and thiamine+biotin+inositol, mycelial growth was inhibited. Sclerotial production in dry weight increased more in these combinations than in the medium of thiamine alone. 9. The stimulating effects of the Penicillium cultural filtrate on the mycelial growth was noticed. It increased linearly with the increase of filtrate concentration up to 6-15 ml/50ml basal medium solution. 10. $NH_4NO_3$. as a nitrogen source for mycelial growth was more effective than asparasine regardless of the concentration of cultural filtrate. 11. In the series of fractionations of the cultural filtrate, mycelial growth occured in unvolatile, ether insoluble cation-adsorbed or anion-unadsorbed substance fractions among the fractions of volatile, unvolatile acids, ether soluble organic acids, ether insoluble, cation-adsorbed, cation-unadsorbed, anion-adsorbed and anion-unadsorbed. and anion-un-adsorbed substance tested. Sclerotia were produced only in cation-adsorbed fraction. 12. According to the above results, it was assumed that substances for the mycelial growth and sclerotial formation and inhibitor of sclerotial formation were include::! in cultural filtrate and they were quite different from each other. I was further assumed that the former two substances are un volatile, ether insotuble, and adsorbed to cation-exchange resin, but not adsorbed to anion, whereas the latter is unvolatile, ether insoluble, and not adsorbed to cation or anion-exchange resin. 13. Seven amino acids-aspartic acid, cystine, glysine, histidine, Iycine, tyrosine and dinitroaniline-were detected in the fractions adsorbed to cation-exchange resin by applying the paper chromatography improved with DNP-amino acids. 14. Mycelial growth or sclerotial production was not stimulated significantly by separate or combined application of glutamic acid, aspartic acid, cystine, histidine, and glysine. Tyrosine gave the stimulating effect when applied .alone and when combined with other amino acids in some cases. 15. The tolerance of sclerotia to moist heat varied according to their water content, that was, the dried sclerotia are more tolerant than wet ones. The sclerotia harvested directly from the media, both Type-1 and Type-2, lost viability within 5 minutes at $52^{\circ}C$. Sclerotia dried for 155 days at$26^{\circ}C$ had more tolerance: sclerotia of Type-l were killed in 15 mins. at $52^{\circ}C$ and in 5 mins. at $57^{\circ}C$, and sclerotia of Type-2 were killed in 10 mins. both at $52^{\circ}C$ or $57^{\circ}C$. 16. Cultural sclerotia of both strains maintained good germinability for 132 days at$26^{\circ}C$. Natural sclerotia of them stored for 283 days under air dry condition still had good germinability, even for 443 days: type-l and type-2 maintained $20\%$ and $26.9\%$ germinability, respectively. 17. The tolerance to low temperature increased in the order of mycelia, felts and sclerotia. Mycelia completely lost the ability to grow within 1 week at $7-8^{\circ}C$> below zero, while mycelial felts still maintained the viability after .3 weeks at $7-20^{\circ}C$ below zero, and sclerotia were even more tolerant. 18. Sclerotia of type-l and type-2 were killed when dipped into the $0.05\%$ solution of mercury chloride for 180 mins. and 240 mins. respectively: and in the $0.1\%$ solution, Type-l for 60 mins. and Type-2 for 30 mins. In the $0.125\%$ uspulun solution, Type-l sclerotia were killed in 180 mins., and those of Type-2 were killed for 90 mins. in the$0.125\%$solution. Dipping into the $5\%$ copper sulphate solution or $0.2\%$ solution of Ceresan lime or Mercron for 240 mins. failed to kill sclerotia of either Type-l or Type-2. 19. Inhibitory effect on mycelial growth of Benlate or Tachi-garen in the liquid culture increased as the concentration increased. 6 days after application, obvious inhibitory effects were found in all treatments except Benlate 0.5ppm; but after 12 days, distingushed diflerences were shown among the different concentrations. As compared with the control, mycelial growth was inhibited by $66\%$ at 0.5ppm and by $92\%$ at 2.0ppm of Benlate, and by$54\%$ at 1ppm and about $77\%$ at 1.5ppm or 2.0ppm of Tachigaren. The mycelial growth was inhibited completely at 500ppm of both fungicides, and the formation of sclerotia was checked at 1,000ppm of Benlate ant at 500ppm or 1,000ppm of Tachigaren. 20. Consumptions of glucose or ammonium nitrogen in the culture solution usually increased with the increment of mycelial growth, but when Benlate or Tachigaren were applied, consumptions of glucose or ammonium nitrogen were inhibited with the increment of concentration of the fungicides. At the low concentrations of Benlate (0.5ppm or 1ppm), however, ammonium nitrogen consumption was higher than that of the ontrol. 21. The amount of mycelia produced by consuming 1mg of glucose or ammonium nitrogen in the culture solution was lowered markedly by Benlate or Tachigaren. Such effects were the severest on the third day after their treatment in all concentrations, and then gradually recovered with the progress of time. 22. In the sand culture, mycelial growth was not inhibited. It was indirectly estimated by the amount of $CO_2$ evolved at any concentrations, except in the Tachigaren 100mg/g sand in which mycelial growth was inhibited significantly. Sclerotial production was completely depressed in the 10mg/g sand of Benlate or Tachigaren. 23. There was no visible inhibitory effect on the germination of sclerotia when the sclerotia were dipped in the solution 0.1, 1.0, 100, 1.000ppm of Benlate or Tachigaren for 10 minutes or even 20 minutes.