• Korean Journal of Agricultural Science
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• v.2 no.1
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• pp.199-231
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• 1975

It is well known fact that antibiotic residues in milk of cows create significant problem for the fermented dairy industry and public health because of inhibition of starter activity and of creation of allergic disease. It can be assumed that antibiotic residues in milk of other aniimals also can create some problems for their infants as in the case of humen. For the above mentioned reasons, present studies were undertaken to determine concentration and duration of antibiotic residues in milk of cows, goats and dogs following intramuscular or intravenous injection and intramammary infusion of penicillin, streptomycin and oxytetracycline at usual dosage. The cylinder-plate method was used for their assay. The results obtained were summerized as follows: 1) Following the intramuscular injection of penicillin, the antibiotic was detected in milk of cows up to 72 hours, in milk of goats 48 hours and in milk of dogs 60 hours of postinjection. The mean peak concentrations were recorded at 12 hours as 0.136 I.U./ml in cows. 6 hours as 0.773 I.U./ml in goats and 3 hours as 1.192 I.U./ml in dogs. 2) Following the intramuscular injection of streptomycin, the antibiotic was detected in milk of cows and goats up to 36 hours and in milk of dogs 24 hours of post-injection. The mean peak concentration were recorded at 6 hours as $0.26{\mu}g/ml$ in cows and at 3 hours in goats and dogs $0.45{\mu}g/ml$ and $0.36{\mu}g/ml$ respectively. 3) Following the intra venous injection of oxytetracycline, the antibiotic was detectable in milk of all the test animals up to 48 hours of postinjection. The mean peak concentrations were recorded at 6 hours as $3.5{\mu}g/ml$ in cows $2.4{\mu}g/ml$ in goats and $2.0{\mu}g/ml$ in dogs respectively. 4) Following intrarnammary infusion of penicillin in amounts of 100,000 I.U. for cows, 20.000 I.U. for goats and 10,000 I.U. for dogs, the penicillin residues in milk of the infused quarter perssisted to 72 hours in cows and 84 hours in goats and dogs. 5) Following intramammary infusion of streptomycin in amount of 500mg for cows, 100mg for goats and 25mg for dogs, the streptomycin residues in milk of the infused quarter persisted to 72 hours in cows and goats and 60 hours in dogs. 6) Following intramammary infusion of oxytetracycline in amount of 500mg for cows, 100mg for goats and 25mg for dogs, the oxytetracycline residues in milk of the infused quarter persisted to 72 hours in cows and 60 hours in goats and dogs. 7) A corelation between the residual antibiotic concentration and milk yield in cows and goats was observed; That is, the lower in the milk production showed a higher the concentration of an antibiotic residues and a longer the time in persistance. 8) Intramammary transfer of the antibiotic from an infused to non infused quarters, in dogs, was observed following the intramammary infusion of penicillin. streptomycin and oxytetracyclne in amounts of 10.000 I.U. 25mg and 25mg respectively. However, no transfer by 100.000 I.U. or 20.000 I.U. of penicillin. 500mg of streptomycin and 100mg of oxytetracyline was observed in cows and goats. 9) In dogs, minimum dosage of antibiotics for transfer fro in treated to untreated quarters following intramammary infusion were 2,500 I.U. of penicillin and 5mg each of streptomycin and oxytetracycline.

• Journal of Intelligence and Information Systems
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• v.27 no.2
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• pp.33-54
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• 2021

With the fourth industrial revolution and the arrival of the New Normal era due to Corona, the importance of Non-contact technologies such as artificial intelligence and big data research has been increasing. Convergent research is being conducted in earnest to keep up with these research trends, but not many studies have been conducted in the area of nuclear research using artificial intelligence and big data-related technologies such as natural language processing and text mining analysis. This study was conducted to confirm the applicability of data science analysis techniques to the field of nuclear research. Furthermore, the study of identifying trends in nuclear spent fuel recognition is critical in terms of being able to determine directions to nuclear industry policies and respond in advance to changes in industrial policies. For those reasons, this study conducted a media trend analysis of pyroprocessing, a spent nuclear fuel treatment technology. We objectively analyze changes in media perception of spent nuclear fuel dry treatment techniques by applying text mining analysis techniques. Text data specializing in Naver's web news articles, including the keywords "Pyroprocessing" and "Sodium Cooled Reactor," were collected through Python code to identify changes in perception over time. The analysis period was set from 2007 to 2020, when the first article was published, and detailed and multi-layered analysis of text data was carried out through analysis methods such as word cloud writing based on frequency analysis, TF-IDF and degree centrality calculation. Analysis of the frequency of the keyword showed that there was a change in media perception of spent nuclear fuel dry treatment technology in the mid-2010s, which was influenced by the Gyeongju earthquake in 2016 and the implementation of the new government's energy conversion policy in 2017. Therefore, trend analysis was conducted based on the corresponding time period, and word frequency analysis, TF-IDF, degree centrality values, and semantic network graphs were derived. Studies show that before the 2010s, media perception of spent nuclear fuel dry treatment technology was diplomatic and positive. However, over time, the frequency of keywords such as "safety", "reexamination", "disposal", and "disassembly" has increased, indicating that the sustainability of spent nuclear fuel dry treatment technology is being seriously considered. It was confirmed that social awareness also changed as spent nuclear fuel dry treatment technology, which was recognized as a political and diplomatic technology, became ambiguous due to changes in domestic policy. This means that domestic policy changes such as nuclear power policy have a greater impact on media perceptions than issues of "spent nuclear fuel processing technology" itself. This seems to be because nuclear policy is a socially more discussed and public-friendly topic than spent nuclear fuel. Therefore, in order to improve social awareness of spent nuclear fuel processing technology, it would be necessary to provide sufficient information about this, and linking it to nuclear policy issues would also be a good idea. In addition, the study highlighted the importance of social science research in nuclear power. It is necessary to apply the social sciences sector widely to the nuclear engineering sector, and considering national policy changes, we could confirm that the nuclear industry would be sustainable. However, this study has limitations that it has applied big data analysis methods only to detailed research areas such as "Pyroprocessing," a spent nuclear fuel dry processing technology. Furthermore, there was no clear basis for the cause of the change in social perception, and only news articles were analyzed to determine social perception. Considering future comments, it is expected that more reliable results will be produced and efficiently used in the field of nuclear policy research if a media trend analysis study on nuclear power is conducted. Recently, the development of uncontact-related technologies such as artificial intelligence and big data research is accelerating in the wake of the recent arrival of the New Normal era caused by corona. Convergence research is being conducted in earnest in various research fields to follow these research trends, but not many studies have been conducted in the nuclear field with artificial intelligence and big data-related technologies such as natural language processing and text mining analysis. The academic significance of this study is that it was possible to confirm the applicability of data science analysis technology in the field of nuclear research. Furthermore, due to the impact of current government energy policies such as nuclear power plant reductions, re-evaluation of spent fuel treatment technology research is undertaken, and key keyword analysis in the field can contribute to future research orientation. It is important to consider the views of others outside, not just the safety technology and engineering integrity of nuclear power, and further reconsider whether it is appropriate to discuss nuclear engineering technology internally. In addition, if multidisciplinary research on nuclear power is carried out, reasonable alternatives can be prepared to maintain the nuclear industry.