• Applied Biological Chemistry
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• v.11
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• pp.151-166
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• 1969

I. Fffects of nitrogen supplying level and culture condition on the top growth aod tubers formation of Ipomoea Batatas. 1) The low level nitrogen (A plot) 3 Milliequivalent per liter of nutrient solution stimulated tuber formation while the high level nitrogen ($B_1\;and\;B_2$ plot) of 10 milliequivalent per liter failed to form tuber though fibrous roots were seen much activated. The suppressive effect of nitrogen on tuber formation in presumed to result from the direct suppressive effect of nitrogen or a certain biocatalystic effect rather than from any indirect effect through the stimulation to growth of tops or the competition with carbohydrates. 2) The addition of milligram urea to nutrient solution stimulated the growth and increased fresh weight and dry weight of the aerial part while suppressed, a little, plant length. 3) The water culture method, which this experiment newly adopted, stimulated plant growth more than the gravel Culture method. And the treatment of low level nitrogen (A plot) in this water culture also saw a considerable degree of tuber formation, as in the case of gravel culture. 4) The foliar application of growth retardant B-nine suppressed the plant length only, with no other recognizable effect. II. Fffects of urea supplying level on the growth of IPOMOEA BATATAS. 1) The higher level of urea which was absorbed tby roots through nutrient solution suppressed top growth, such as plant length, number of leaves and fresh weight. And this can be attributed to the direct absorption of urea which was not ammonificated. 2) Although the higher level of nitrate nitrogen (B plot) made no tuber formation in previous experiment (Report-1), the higher level of urea nitrogen (A plot) made tuber formation possible in this experiment. The ratio of tuber to top was, however, less in higher level of urea than in lower level of urea, and the suppressing effect was larger on tuber than on top. 3) The foliar application of urea stimulated top growth while the higher level of urea absorbed by roots suppressed it, though the amounts of urea supplied in two experiments were same. Ratio of top to roots was larger in foliar application of urea (C plot) and less in root absorption of urea both of higher (B plot) and lower urea levels (A plot). III. Fffects of growth retardant etc. on the growth of IPOMOEA BATATAS in relation to urea application. 1) B-nine (N-dimethyl amino-succinamic acid) is recognized as a growth retardant, suppressed the plant length irrespective of urea levels. The treatment of gibberellin stimulated distinctly plant length, and the combined treatment of gibberellin and B-nine recovered completely the plant length which had been suppressed by B-nine. 2) B-nine increased fresh weight, especially, fresh weight of top both in lower and higher level of The degree of fresh weight increase varied according to concentrations of B-nine, of which the 0.15% of B-nine ($B_1$ plot) was the effective in higher level of urea. The effect of B-nine for increasing fresh weight was the largest in top next in tuber, and the least in fibrous roots. The ratio of fibrous roots to top was always decreased by B-nine application, which the ratio of tuber to top was contrary increased by B-nine in higher level of urea though decreased in lower level of urea. 3) Gibberellin treatment also increased fresh weight but the combined treatment ($B_3$+GA plot) of gibberellin and B-nine was even more effective than any of single treatments. Gibberellin and B-nine proved to be synergistic with fresh weight while reverse with plant length. 4) Considerable influences were abserved mainly in the length of plants and their fresh weight after B-nine treatment. So that B-nine may be reguraded as a metabolic controller rather than as an antimetabolite. 5) The surpressed growth of plants cause by higher level of urea was normalized by B-nine treatment. This fact suggested a further study on the applicability for practical use.

• Journal of Intelligence and Information Systems
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• v.19 no.3
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• pp.57-71
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• 2013

Over a billion people in the world generate new news minute by minute. People forecasts some news but most news are from unexpected events such as natural disasters, accidents, crimes. People spend much time to watch a huge amount of news delivered from many media because they want to understand what is happening now, to predict what might happen in the near future, and to share and discuss on the news. People make better daily decisions through watching and obtaining useful information from news they saw. However, it is difficult that people choose news suitable to them and obtain useful information from the news because there are so many news media such as portal sites, broadcasters, and most news articles consist of gossipy news and breaking news. User interest changes over time and many people have no interest in outdated news. From this fact, applying users' recent interest to personalized news service is also required in news service. It means that personalized news service should dynamically manage user profiles. In this paper, a content-based news recommendation system is proposed to provide the personalized news service. For a personalized service, user's personal information is requisitely required. Social network service is used to extract user information for personalization service. The proposed system constructs dynamic user profile based on recent user information of Facebook, which is one of social network services. User information contains personal information, recent articles, and Facebook Page information. Facebook Pages are used for businesses, organizations and brands to share their contents and connect with people. Facebook users can add Facebook Page to specify their interest in the Page. The proposed system uses this Page information to create user profile, and to match user preferences to news topics. However, some Pages are not directly matched to news topic because Page deals with individual objects and do not provide topic information suitable to news. Freebase, which is a large collaborative database of well-known people, places, things, is used to match Page to news topic by using hierarchy information of its objects. By using recent Page information and articles of Facebook users, the proposed systems can own dynamic user profile. The generated user profile is used to measure user preferences on news. To generate news profile, news category predefined by news media is used and keywords of news articles are extracted after analysis of news contents including title, category, and scripts. TF-IDF technique, which reflects how important a word is to a document in a corpus, is used to identify keywords of each news article. For user profile and news profile, same format is used to efficiently measure similarity between user preferences and news. The proposed system calculates all similarity values between user profiles and news profiles. Existing methods of similarity calculation in vector space model do not cover synonym, hypernym and hyponym because they only handle given words in vector space model. The proposed system applies WordNet to similarity calculation to overcome the limitation. Top-N news articles, which have high similarity value for a target user, are recommended to the user. To evaluate the proposed news recommendation system, user profiles are generated using Facebook account with participants consent, and we implement a Web crawler to extract news information from PBS, which is non-profit public broadcasting television network in the United States, and construct news profiles. We compare the performance of the proposed method with that of benchmark algorithms. One is a traditional method based on TF-IDF. Another is 6Sub-Vectors method that divides the points to get keywords into six parts. Experimental results demonstrate that the proposed system provide useful news to users by applying user's social network information and WordNet functions, in terms of prediction error of recommended news.