• Tuberculosis and Respiratory Diseases
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• v.52 no.1
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• pp.24-36
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• 2002

Background: Bronchial reactivity is known to be a component of airway hyperresponsiveness, a cardinal feature of asthma, with bronchial sensitivity, and is increments in response to induced doses of bronchoconstrictors as manifested by the steepest slope of the dose-response curve. However, there is some controversy regarding methods of measuring bronchial reactivity and clinical impact of such measurements. The purpose of this study was to evaluate the clinical significance and assess the clinical use by analyzing the relationship of the bronchial sensitivity, the clinical severity and the changes in pulmonary function with bronchial reactivity. Method: A total of 116 subjects underwent a methacholine bronchial provocation test. They were divided into 3 groups : mild intermittent, mild persistent, moderate and cough asthma. Severe patients were excluded. Methacholine PC20 was determined from the log dose-response curve and PC40 was determined by one more dose inhalation after PC20. The steepest slope of log dose-response curve, connecting PC20 with PC40, was used to calculate the bronchial reactivity. Body plethysmography and a single breath for the DLCO were done in 43 subjects before and after methacholine test. Results: The average bronchial reactivity was 38.0 in the mild intermittent group, 49.8 in the mild persistent group, 61.0 in the moderate group, and 41.1 in the cough asthma group. There was a weak negative correlation between PC20 and bronchial reactivity. A heightened bronchial reactivity tends to produce an increased clinical severity in patients with a similar bronchial sensitivity and basal spirometric pulmonary function. There were significant correlations between the bronchial reactivity and the initial pulmonary function before the methacholine test in the order of sGaw, Raw, $FEV_1$/FVC, MMFR. There were no correlations between the bronchial sensitivity and the % change in the pulmonary function parameters after the methacholine test. However, there were significant correlations between the bronchial reactivity and the PEF, $FEV_1$, DLCO. Conclusion: There was weak significant negative correlation between the bronchial reactivity and the bronchial sensitivity, and the bronchial reactivity closely reflected the severity of the asthma. Accordingly, measuring both the bronchial sensitivity and the bronchial reactivity can be of assistance in assessing of the ongoing disease severity and in monitoring the effect of therapy.

• Korean Journal of Poultry Science
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• v.7 no.2
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• pp.54-76
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• 1980

A survey was conducted to determine the status of health and productivity of poultry farms in Korea. Area included Was Kyunggido where exist nearly 50% of national poultry population. From this area, 41 layer and 34 broiler farms covering 21 Countries were selected randomly for the survey. When farms were divided in the operation size, 95.1% of layer and 82.3% of broiler farms were classified as business or industrial level while the rest were managed in a small scale as part time job. Generally layer farms had been established much earlier than broiler farms. Geographically 10.7% of layer farms were sited near the housing area such as field foreast and rice field. No farms were located near the seashore. The distance from one farm from the other was very close, being 80% of the farms within the distance of 1km and as many as 28% of the farms within loom. This concentrated poultry farming in a certain area created serious problems for the sanitation and preventive measures, especially in case of outbreak of infectious diseases. Average farm size was 5,016${\times}$3.3㎡ for layers and 1,037${\times}$3.3㎡ for broilers. 89.5% of layer ana 70.6% of broiler farms owned the land for farming while the rest were on lease. In 60% of layer farms welters were employed for farming while in the rest their own labour was used. Majority of farms were equipped poorly for taking necessary practice of hygiene and sanitation. The amount of disinfectant used by farms was considerably low. As many as 97.6% of lave. farms were practised with Newcastle(ND) and fowl pox(F$.$pox) vaccine, whereas only 43.6% and 5.1% of broiler farms were practised with ND and F$.$pox vaccine, respectively. In 17-32.7% of farms ND vaccine was used less than twice until 60 days of age and in only 14.6% of farms adult birds were vaccinated every 4months. Monthly expense for preventive measures was over 200,000W in 32% of farms. Only 4.9-2.7% of vaccine users were soaking advice from veterinarians before practising vaccination, 85% of the users trusted the efficacy of the vaccines. Selection of medicine was generally determined by the farm owner rather than by veterinarans on whom 33.3% of farms were dependant. When diseases outbroke, 49.3% of farms called for veterinary hospital and the rest were handled by their own veterinarians, salesmen or professionals. Approximately 70% of farms were satisfied with the diagnosis made by the veterinarians. Frequency of disease outbreaks varied according to the age and type of birds. The livabilities of layers during the period of brooding, rearing ana adultwere 90.5, 98.9 and 75.2%, respectively while the livalibility of broilers until marketing was 92.2%. In layers, average culling age, was 533.3 day and hen housed eggs were 232.7. Average feed conversion rates of layers and broilers were 3.30 and 2.48, respectively. Those figures were considerably higher than anticipated but still far lower than those in developed countries.

• Clinical and Experimental Reproductive Medicine
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• v.34 no.1
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• pp.41-48
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• 2007

Objective: To determine whether the presence of Y-chromosome microdeletion affects the outcome of in vitro fertilization (IVF) and intracytoplasmic sperm injection (ICSI) program. Methods: Fourteen couples with microdeletion in azoospermic factor (AZF)c region who attempted IVF/ICSI or cryopreserved and thawed embryo transfer cycles were enrolled. All of the men showed severe oligoasthenoteratoazoospermia (OATS) or azoospermia. As a control, 12 couples with OATS or azoospermia and having normal Y-chromosome were included. Both groups were divided into two subgroups by sperm source used in ICSI such as those who underwent testicular sperm extraction (TESE) and those used ejaculate sperm. We retrospectively analyzed our database in respect to the IVF outcomes. The outcome measures were mean number of good quality embryos, fertilization rates, implantation rates, $\beta$-hCG positive rates, early pregnancy loss and live birth rates. Results: Mean number of good quality embryos, implantation rates, $\beta$-hCG positive rates, early pregnancy loss rates and live birth rates were not significantly different between Y-chromosome microdeletion and control groups. But, fertilization rates in the Y-chromosome microdeletion group (61.1%) was significantly lower than that of control group (79.8%, p=0.003). Also, the subgroup underwent TESE and having AZFc microdeletion showed significantly lower fertilization rates (52.9%) than the subgroup underwent TESE and having normal Y-chromosome (79.5%, p=0.008). Otherwise, in the subgroups used ejaculate sperm, fertilization rates were showed tendency toward lower in couples having Y-chromosome microdeletion than couples with normal Y-chromosome. (65.5% versus 79.9%, p=0.082). But, there was no significance statistically. Conclusions: In IVF/ICSI cycles using TESE sperm, presence of V-chromosome microdeletion may adversely affect to fertilization ability of injected sperm. But, in cases of ejaculate sperm available for ICSI, IVF outcome was not affected by presence of Y-chromosome AZFc microdeletion. However, more larger scaled prospective study was needed to support our results.

• Journal of Intelligence and Information Systems
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• v.25 no.1
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• pp.63-83
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• 2019

Investors prefer to look for trading points based on the graph shown in the chart rather than complex analysis, such as corporate intrinsic value analysis and technical auxiliary index analysis. However, the pattern analysis technique is difficult and computerized less than the needs of users. In recent years, there have been many cases of studying stock price patterns using various machine learning techniques including neural networks in the field of artificial intelligence(AI). In particular, the development of IT technology has made it easier to analyze a huge number of chart data to find patterns that can predict stock prices. Although short-term forecasting power of prices has increased in terms of performance so far, long-term forecasting power is limited and is used in short-term trading rather than long-term investment. Other studies have focused on mechanically and accurately identifying patterns that were not recognized by past technology, but it can be vulnerable in practical areas because it is a separate matter whether the patterns found are suitable for trading. When they find a meaningful pattern, they find a point that matches the pattern. They then measure their performance after n days, assuming that they have bought at that point in time. Since this approach is to calculate virtual revenues, there can be many disparities with reality. The existing research method tries to find a pattern with stock price prediction power, but this study proposes to define the patterns first and to trade when the pattern with high success probability appears. The M & W wave pattern published by Merrill(1980) is simple because we can distinguish it by five turning points. Despite the report that some patterns have price predictability, there were no performance reports used in the actual market. The simplicity of a pattern consisting of five turning points has the advantage of reducing the cost of increasing pattern recognition accuracy. In this study, 16 patterns of up conversion and 16 patterns of down conversion are reclassified into ten groups so that they can be easily implemented by the system. Only one pattern with high success rate per group is selected for trading. Patterns that had a high probability of success in the past are likely to succeed in the future. So we trade when such a pattern occurs. It is a real situation because it is measured assuming that both the buy and sell have been executed. We tested three ways to calculate the turning point. The first method, the minimum change rate zig-zag method, removes price movements below a certain percentage and calculates the vertex. In the second method, high-low line zig-zag, the high price that meets the n-day high price line is calculated at the peak price, and the low price that meets the n-day low price line is calculated at the valley price. In the third method, the swing wave method, the high price in the center higher than n high prices on the left and right is calculated as the peak price. If the central low price is lower than the n low price on the left and right, it is calculated as valley price. The swing wave method was superior to the other methods in the test results. It is interpreted that the transaction after checking the completion of the pattern is more effective than the transaction in the unfinished state of the pattern. Genetic algorithms(GA) were the most suitable solution, although it was virtually impossible to find patterns with high success rates because the number of cases was too large in this simulation. We also performed the simulation using the Walk-forward Analysis(WFA) method, which tests the test section and the application section separately. So we were able to respond appropriately to market changes. In this study, we optimize the stock portfolio because there is a risk of over-optimized if we implement the variable optimality for each individual stock. Therefore, we selected the number of constituent stocks as 20 to increase the effect of diversified investment while avoiding optimization. We tested the KOSPI market by dividing it into six categories. In the results, the portfolio of small cap stock was the most successful and the high vol stock portfolio was the second best. This shows that patterns need to have some price volatility in order for patterns to be shaped, but volatility is not the best.

• Journal of Intelligence and Information Systems
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• v.26 no.4
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• pp.149-171
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• 2020

The period at university is to make decision about getting an actual job. As our society develops rapidly and highly, jobs are diversified, subdivided, and specialized, and students' job preparation period is also getting longer and longer. This study analyzed the log data of college students to see how the various activities that college students experience inside and outside of school might have influences on employment. For this experiment, students' various activities were systematically classified, recorded as an activity data and were divided into six core competencies (Job reinforcement competency, Leadership & teamwork competency, Globalization competency, Organizational commitment competency, Job exploration competency, and Autonomous implementation competency). The effect of the six competency levels on the employment status (employed group, unemployed group) was analyzed. As a result of the analysis, it was confirmed that the difference in level between the employed group and the unemployed group was significant for all of the six competencies, so it was possible to infer that the activities at the school are significant for employment. Next, in order to analyze the impact of the six competencies on the qualitative performance of employment, we had ANOVA analysis after dividing the each competency level into 2 groups (low and high group), and creating 6 groups by the range of first annual salary. Students with high levels of globalization capability, job search capability, and autonomous implementation capability were also found to belong to a higher annual salary group. The theoretical contributions of this study are as follows. First, it connects the competencies that can be extracted from the school experience with the competencies in the Human Resource Management field and adds job search competencies and autonomous implementation competencies which are required for university students to have their own successful career & life. Second, we have conducted this analysis with the competency data measured form actual activity and result data collected from the interview and research. Third, it analyzed not only quantitative performance (employment rate) but also qualitative performance (annual salary level). The practical use of this study is as follows. First, it can be a guide when establishing career development plans for college students. It is necessary to prepare for a job that can express one's strengths based on an analysis of the world of work and job, rather than having a no-strategy, unbalanced, or accumulating excessive specifications competition. Second, the person in charge of experience design for college students, at an organizations such as schools, businesses, local governments, and governments, can refer to the six competencies suggested in this study to for the user-useful experiences design that may motivate more participation. By doing so, one event may bring mutual benefits for both event designers and students. Third, in the era of digital transformation, the government's policy manager who envisions the balanced development of the country can make a policy in the direction of achieving the curiosity and energy of college students together with the balanced development of the country. A lot of manpower is required to start up novel platform services that have not existed before or to digitize existing analog products, services and corporate culture. The activities of current digital-generation-college-students are not only catalysts in all industries, but also for very benefit and necessary for college students by themselves for their own successful career development.

• Journal of Intelligence and Information Systems
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• v.26 no.4
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• pp.173-198
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• 2020

For a long time, many studies have been conducted on predicting the success of campaigns for customers in academia, and prediction models applying various techniques are still being studied. Recently, as campaign channels have been expanded in various ways due to the rapid revitalization of online, various types of campaigns are being carried out by companies at a level that cannot be compared to the past. However, customers tend to perceive it as spam as the fatigue of campaigns due to duplicate exposure increases. Also, from a corporate standpoint, there is a problem that the effectiveness of the campaign itself is decreasing, such as increasing the cost of investing in the campaign, which leads to the low actual campaign success rate. Accordingly, various studies are ongoing to improve the effectiveness of the campaign in practice. This campaign system has the ultimate purpose to increase the success rate of various campaigns by collecting and analyzing various data related to customers and using them for campaigns. In particular, recent attempts to make various predictions related to the response of campaigns using machine learning have been made. It is very important to select appropriate features due to the various features of campaign data. If all of the input data are used in the process of classifying a large amount of data, it takes a lot of learning time as the classification class expands, so the minimum input data set must be extracted and used from the entire data. In addition, when a trained model is generated by using too many features, prediction accuracy may be degraded due to overfitting or correlation between features. Therefore, in order to improve accuracy, a feature selection technique that removes features close to noise should be applied, and feature selection is a necessary process in order to analyze a high-dimensional data set. Among the greedy algorithms, SFS (Sequential Forward Selection), SBS (Sequential Backward Selection), SFFS (Sequential Floating Forward Selection), etc. are widely used as traditional feature selection techniques. It is also true that if there are many risks and many features, there is a limitation in that the performance for classification prediction is poor and it takes a lot of learning time. Therefore, in this study, we propose an improved feature selection algorithm to enhance the effectiveness of the existing campaign. The purpose of this study is to improve the existing SFFS sequential method in the process of searching for feature subsets that are the basis for improving machine learning model performance using statistical characteristics of the data to be processed in the campaign system. Through this, features that have a lot of influence on performance are first derived, features that have a negative effect are removed, and then the sequential method is applied to increase the efficiency for search performance and to apply an improved algorithm to enable generalized prediction. Through this, it was confirmed that the proposed model showed better search and prediction performance than the traditional greed algorithm. Compared with the original data set, greed algorithm, genetic algorithm (GA), and recursive feature elimination (RFE), the campaign success prediction was higher. In addition, when performing campaign success prediction, the improved feature selection algorithm was found to be helpful in analyzing and interpreting the prediction results by providing the importance of the derived features. This is important features such as age, customer rating, and sales, which were previously known statistically. Unlike the previous campaign planners, features such as the combined product name, average 3-month data consumption rate, and the last 3-month wireless data usage were unexpectedly selected as important features for the campaign response, which they rarely used to select campaign targets. It was confirmed that base attributes can also be very important features depending on the type of campaign. Through this, it is possible to analyze and understand the important characteristics of each campaign type.

• Journal of the Daesoon Academy of Sciences
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• v.36
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• pp.153-199
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• 2020

The teachings of Sangje teachings have been spread to humanity and were provided as basis for building the earthly paradise due to His having performed the Reordering Works of the Universe (Cheonjigongsa) for nine years. The work that remains will be completed year by year following the cosmic program that Sangje set for the universe. The chapters titled 'Gyoun (Progress of the Order)' in Jeon-gyeong (The Canonical Scripture) can be summarized into three parts: Viewing Gyoun, Spreading Gyoun, and Establishing the firm ground of Gyoun. Viewing Gyoun is seeing how the teachings would be transmitted from the beginning to end. The work of Gyoun was established by Sangje and promoted as the teachings of Sangje which will ultimately unfold into the realization of an earthly paradise. Spreading Gyoun is performed by disciples who received the teachings from Sangje and then the successor to whom Sangje transmitted the religious authority. Since chapter two of Gyoun is about the hagiography of Doju Jo Jeongsan, it is shown that Doju unfolded and developed Sangje's teachings. Establishing the firm ground of Gyoun is carried out to enable practitioners to understand that Dotong-gunja ('Dao-Empowered Sages,' Earthly Immortals) will be produced as a result of Sangje's Reordering Works of Heaven and Earth and that humans can perfect themselves through cultivating the Dao. In conclusion, Gyoun can be summarized as a process that started during Doju Jo Jeongsan's 50 years (1909~1958) of holy works and spreading of the teachings. Next, it was continued through the time of Dojeon who was bestowed with religious authority through Doju's last words. Dojeon, like Doju before him, spread the teachings. In later times, there will be Dotong-gunjas who transmit Sangje's teachings to the whole world. Although the above characterizations are accurate, I compared some verses from Chapter 1 of Progress of the Order (Gyoun) in The Canonical Scripture (Jeon-gyeong) of Daesoon Jinrihoe to the 6 th edition (1965) of Daesoon Jeongyeong, a key scripture from the earliest strata of Jeungsanist scriptures, and found that there were a few earlier variations of the same content. The use of words and sentences were different though in several of these verses. Also, some of the verses indicated alternative historical dates (years), and some of the verses from Chapter 1 of Progress of the Order from The Canonical Scripture do not appear anywhere in the 6^th edition of Daesoon Jeong-gyeong.

• Journal of Intelligence and Information Systems
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• v.27 no.4
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• pp.1-22
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• 2021

Aspect Based Sentiment Analysis (ABSA), which analyzes sentiment based on aspects that appear in the text, is drawing attention because it can be used in various business industries. ABSA is a study that analyzes sentiment by aspects for multiple aspects that a text has. It is being studied in various forms depending on the purpose, such as analyzing all targets or just aspects and sentiments. Here, the aspect refers to the property of a target, and the target refers to the text that causes the sentiment. For example, for restaurant reviews, you could set the aspect into food taste, food price, quality of service, mood of the restaurant, etc. Also, if there is a review that says, "The pasta was delicious, but the salad was not," the words "steak" and "salad," which are directly mentioned in the sentence, become the "target." So far, in ABSA, most studies have analyzed sentiment only based on aspects or targets. However, even with the same aspects or targets, sentiment analysis may be inaccurate. Instances would be when aspects or sentiment are divided or when sentiment exists without a target. For example, sentences like, "Pizza and the salad were good, but the steak was disappointing." Although the aspect of this sentence is limited to "food," conflicting sentiments coexist. In addition, in the case of sentences such as "Shrimp was delicious, but the price was extravagant," although the target here is "shrimp," there are opposite sentiments coexisting that are dependent on the aspect. Finally, in sentences like "The food arrived too late and is cold now." there is no target (NULL), but it transmits a negative sentiment toward the aspect "service." Like this, failure to consider both aspects and targets - when sentiment or aspect is divided or when sentiment exists without a target - creates a dual dependency problem. To address this problem, this research analyzes sentiment by considering both aspects and targets (Target-Aspect-Sentiment Detection, hereby TASD). This study detected the limitations of existing research in the field of TASD: local contexts are not fully captured, and the number of epochs and batch size dramatically lowers the F1-score. The current model excels in spotting overall context and relations between each word. However, it struggles with phrases in the local context and is relatively slow when learning. Therefore, this study tries to improve the model's performance. To achieve the objective of this research, we additionally used auxiliary loss in aspect-sentiment classification by constructing CNN(Convolutional Neural Network) layers parallel to existing models. If existing models have analyzed aspect-sentiment through BERT encoding, Pooler, and Linear layers, this research added CNN layer-adaptive average pooling to existing models, and learning was progressed by adding additional loss values for aspect-sentiment to existing loss. In other words, when learning, the auxiliary loss, computed through CNN layers, allowed the local context to be captured more fitted. After learning, the model is designed to do aspect-sentiment analysis through the existing method. To evaluate the performance of this model, two datasets, SemEval-2015 task 12 and SemEval-2016 task 5, were used and the f1-score increased compared to the existing models. When the batch was 8 and epoch was 5, the difference was largest between the F1-score of existing models and this study with 29 and 45, respectively. Even when batch and epoch were adjusted, the F1-scores were higher than the existing models. It can be said that even when the batch and epoch numbers were small, they can be learned effectively compared to the existing models. Therefore, it can be useful in situations where resources are limited. Through this study, aspect-based sentiments can be more accurately analyzed. Through various uses in business, such as development or establishing marketing strategies, both consumers and sellers will be able to make efficient decisions. In addition, it is believed that the model can be fully learned and utilized by small businesses, those that do not have much data, given that they use a pre-training model and recorded a relatively high F1-score even with limited resources.

• The Korean Society of Law and Medicine
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• v.23 no.4
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• pp.29-74
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• 2022

As social disasters occur under the Disaster Management Act, which can damage the people's "life, body, and property" due to the rapid spread and spread of unexpected COVID-19 infectious diseases in 2020, information collected through inspection and reporting of infectious disease pathogens (Article 11), epidemiological investigation (Article 18), epidemiological investigation for vaccination (Article 29), artificial technology, and prevention policy Decision), (3) It was used as an important basis for decision-making in the context of an infectious disease crisis, such as promoting vaccination and understanding the current status of damage. In addition, medical policy decisions using infectious disease data contribute to quarantine policy decisions, information provision, drug development, and research technology development, and interest in the legal scope and limitations of using infectious disease data has increased worldwide. The use of infectious disease data can be classified for the purpose of spreading and blocking infectious diseases, prevention, management, and treatment of infectious diseases, and the use of information will be more widely made in the context of an infectious disease crisis. In particular, as the serious stage of the Disaster Management Act continues, the processing of personal identification information and sensitive information becomes an important issue. Information on "medical records, vaccination drugs, vaccination, underlying diseases, health rankings, long-term care recognition grades, pregnancy, etc." needs to be interpreted. In the case of "prevention, management, and treatment of infectious diseases", it is difficult to clearly define the concept of medical practicesThe types of actions are judged based on "legislative purposes, academic principles, expertise, and social norms," but the balance of legal interests should be based on the need for data use in quarantine policies and urgent judgment in public health crises. Specifically, the speed and degree of transmission of infectious diseases in a crisis, whether the purpose can be achieved without processing sensitive information, whether it unfairly violates the interests of third parties or information subjects, and the effectiveness of introducing quarantine policies through processing sensitive information can be used as major evaluation factors. On the other hand, the collection, provision, and use of infectious disease data for research purposes will be used through pseudonym processing under the Personal Information Protection Act, consent under the Bioethics Act and deliberation by the Institutional Bioethics Committee, and data provision deliberation committee. Therefore, the use of research purposes is recognized as long as procedural validity is secured as it is reviewed by the pseudonym processing and data review committee, the consent of the information subject, and the institutional bioethics review committee. However, the burden on research managers should be reduced by clarifying the pseudonymization or anonymization procedures, the introduction or consent procedures of the comprehensive consent system and the opt-out system should be clearly prepared, and the procedure for re-identifying or securing security that may arise from technological development should be clearly defined.

• Korean Journal of Veterinary Research
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• v.9 no.1
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• pp.23-62
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• 1969

Throughout the studies the following experimental results were obtained and are summarized: 1. Multiplication of agents in primary cell cultures of both GF classical and CR-64 acute strain of Marek's disease infected chicken kidneys was accompanied by the formation of distinct transformed cell foci. This characteristic nature of cell transformation was passaged regularly by addition of dispersed cell from infected cultures to normal chicken kidney cell cultures, and also transferred was the nature of cell transformation to normal chick-embryo liver and neuroglial cell cultures. No cytopathic changes were noticed in inoculated chick-embryo fibroblast cultures. 2. The same cytopathic effects were noticed in normal kidney cell monolayers after the inoculation of whole blood and huffy coat cells derived from both forms of Marek's disease infected chickens. In these cases, however, the number of transformed cell foci appearing was far less than that of uninoculated monolayers prepared directly from the kidneys of Marek's disease infected chickens. 3. The change in cell culture IS regarded as a specific cell transformation focus induced by an oncogenic virus rather than it plaque in slowly progressing cytopathic effect by non-oncogenic viruses, and it is quite similar to RSV focus in chick-embryo fibroblasts in many respects. 4. The infective agent (cell transformable) were extremely cell-associated and could not be separated in an infective state from cells under the experimental conditions. 5. The focus assay of these agents was valid as shown by the high degree of linear correlation (r=0.97 and 0.99) between the relative infected cell concentration (in inoculum) and the transformed cell foci counted. 6. No differences were observed between the GF classical strain and the CR-64 acute strain of Marek's disease as far as cell culture behavior. 7. Characterization of the isolates by physical and chemical treatments, development of internuclear inclusions in Infected cells, and nucleic acid typing by differential stainings and cytochemical treatments indicated that the natures of these cell transformation agents closely resemble to those described fer the group B herpes viruses. 8. Susceptible chicks inoculated with infected kidney tissue culture cells developed specific lesions of Marek's disease, and in a case of prolonged observation after inoculation (5 weeks) the birds developed clinical symptoms and gross lesions of Marek's disease. Kidney cell cultures prepared from those inoculated birds and sacrificed showed a superior recovery of cell transformation property by formation of distinct foci. 9. Electron microscopic study of infected kidney culture cells (GF agent) by negative staining technique revealed virus particles furnishing the properties of herpes viruses. The particle was measured about $100m{\mu}$ and, so far, no herpes virus envelop has been seen from these preparations. 10. No relationship of both isolates to avian leukosis/sarcoma group viruses and PPLO was observed.