• Korean Journal of Poultry Science
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• v.50 no.4
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• pp.193-202
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• 2023

Influenza IAVs are encapsulated negative-strand RNA viruses that infect many bird species' respiratory systems and can spread to other animals, including humans. This work reanalyzed previous microarray datasets to identify common and specific differentially expressed genes (DEGs) in chickens, as well as their biological activities. There were 760 and 405 DEGs detected in HPAIV and LPAIV-infected chicken cells, respectively. HPAIV and LPAIV have 670 and 315 DEGs, respectively, with both viruses sharing 90 DEGs. Because of HPAIV infection, numerous genes were implicated in a fundamental biological function of the cell cycle, according to the functional annotation of DEGs. Of the targeted genes, expressions of CDC Like Kinase 3 (CLK3), Nucleic Acid Binding Protein 1 (NABP1), Interferon-Inducible Protein 6 (IFI6), PIN2 (TERF1) Interacting Telomerase Inhibitor 1 (PINX1), and Cellular Communication Network Factor 4 (WISP1) were altered in DF-1 cells treated with polyinosinic:polycytidylic acid (PIC), a toll-like receptor 3 (TLR3) ligand, suggesting that transcription of these genes be controlled by TLR3 signaling. To gain a better understanding of the pathophysiology of AIVs in chickens, it is crucial to focus more research on unraveling the mechanisms through which AIV infections may manipulate host responses during the infection process. Insights into these mechanisms could facilitate the development of novel therapeutic strategies.

• The Journal of the Acoustical Society of Korea
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• v.43 no.1
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• pp.9-18
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• 2024

The importance of active sonar systems is emerging due to the quietness of underwater targets and the increase in ambient noise due to the increase in maritime traffic. However, the low signal-to-noise ratio of the echo signal due to multipath propagation of the signal, various clutter, ambient noise and reverberation makes it difficult to identify underwater targets using active sonar. Attempts have been made to apply data-based methods such as machine learning or deep learning to improve the performance of underwater target recognition systems, but it is difficult to collect enough data for training due to the nature of sonar datasets. Methods based on mathematical modeling have been mainly used to compensate for insufficient active sonar data. However, methodologies based on mathematical modeling have limitations in accurately simulating complex underwater phenomena. Therefore, in this paper, we propose a sonar signal synthesis method based on a deep neural network. In order to apply the neural network model to the field of sonar signal synthesis, the proposed method appropriately corrects the attention-based encoder and decoder to the sonar signal, which is the main module of the Tacotron model mainly used in the field of speech synthesis. It is possible to synthesize a signal more similar to the actual signal by training the proposed model using the dataset collected by arranging a simulated target in an actual marine environment. In order to verify the performance of the proposed method, Perceptual evaluation of audio quality test was conducted and within score difference -2.3 was shown compared to actual signal in a total of four different environments. These results prove that the active sonar signal generated by the proposed method approximates the actual signal.

• Korean Journal of Veterinary Pathology
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• v.6 no.2
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• pp.101-104
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• 2002

닭의 전신장기에 림프종 발생이 특정인 마렉병(Marek's disease; MD)은 림프구성 백혈병(Lymphoid leukosis; LL)과 병리학적 소견이 매우 유사하여 감별이 요구된다. 마렉병 바이러스(Marek's disease virus; MDV)는 질병초기에서 후기에 이르기까지 모낭상피세포에 세포용해성 감염을 지속적으로 일으킨다. 세포용해성 감염이 있는 모낭상피세포는 변성내지 괴사되어 있고 핵내봉입체가 관찰된다. 또한 세포용해성 감염이 있는 모낭상피세포 바로 밑의 진피와 깃털 수질(feather pulp)내의 혈관주위에 림프구 침윤이 관찰된다. 이러한 피부병변은 MD의 특징적인 병변들로서 LL과 감별할 수 있는 결정적인 단서이다. 본 고에서는 MD에 관한 전반적인 것과 특히 MD 진단을 위한 피부병변의 유용성에 대해서 자세히 논하고자 한다. 양계산업에 문제를 야기하고 있는 림프구 증식성 종양은 크게 마렉병(Marek’s disease; MD)과 백혈병(Lymphoid leukosis; LL)이 있다. 이들 질환의 원인체들이 분리되기 전까지는 이들 질병들은 발병부위에 따라 질병명을 붙였다. 즉, 내부장기냐 근육에 발생한 것은 visceral lymphomatosis, 피부에 발생한 것은 skin leukosis, 말초신경의 병변은 poly­n neuritis, neuritis, neurolymphomatosis gallinarum, range paralyis로 불리었다. 또한 눈에 발생한 것은 blindness, gray eye, iritis, uveitis, ocular lymphomatosis라고 불리었다. 1961년에 Biggs는 이러한 림프구 증식성 질병을 마렉병과 백혈병 으로 분류하자는 제안을 하였고, 드디어 1960년대 중반에 림프구 증식성 병변 중의 일부에서 herpesvirus가 분리되어서 Biggs가 제안한 병명인 마렉병을 본격적으로 사용하게 되었다. MD는 마렉병 바이러스(Marek’s disease virus; MDV)가 원 인제로서 닭에 전염성이 강한 염증성에서 종양성의 병변을 내부장기, 피부, 근육, 안구, 중추신경계, 말초신경계 등에 일 으킨다. MDV는 림프종을 유발하기 때문에 처음에는 사람에서 림프종을 유발하는 Epstein-Bar 바이러스와 관련이 있을 것으로 생각되어 gamma-herpesvirus로 분류되었지만, MDV의 게놈 구조와 세포배양에서 빠르게 성장한다는 점 때문에 지금은 alpha-herpesvirus로 재분류 되었다. MDV는 바이러스 중화시험과 한천 겔 침강법에 의해서 3개의 혈청형으로 분류 된다. 혈청형 1은 종양원성 바이러스와 종양원성 바이러스의 계대배양에 의한 약독주가 있다. 혈청형 2는 자연적으로 발 생하는 비종양원성 닭의 MDV이고, 혈정형 3은 바종양원성 칠면조 herpesvirus (HVT)이다. 림프종을 유발하는 MDV 감염은 4개의 과정, 즉 초기 세포용해성 감염, 잠복감염, 후기 세포용해성 감염, 마지막으로 종양화로 나눌 수 있다. 감염의 경로를 보면, 흡입된 MDV는 폐의 대식세포에 감염한 후 전선 장기로 MDV를 전파 시킨다. 특히, 흉선, F냥, 비장 등의 림프구에 초기 세포용해성 감염을 일으키는데, B 림프구가 주로 감염된다. 세포용해성 감염음 방어하기 위해 몰려든 T 림프구가 활성화가 되면, T 세포도 감염되게 된다. 잠복감염은 여러 가지 사이토카인 등 을 포함한 면역반응에 의해서 일어나며, 이 때 잠복감염된 세포는 특히 혈중의 T 세포라고 한다. 혈중 MDV 감염세포 는 피부 모낭상피세포, 선장 등 상피세포 유래의 조직에 MDV를 전파 시켜서 이들 조직에서 후기 세포용해성 감염이 일어나게 한다. 후기 세포용해성 감염을 유발하는 것은 이러한 MDV가 감염된 혈중 림프구라는 증거는 혈중의 세포 외에는 감염성 바이러스가 없기 때문이다. 후기 세포용해성 감염이 있는 후 육안적 혹은 현미경적으로 검출이 가능한 림프종이 여러 장기에서 관찰된다. MDV가 감염되면 병변 발생부위에 따라서 다양한 임상증상이 발생한다. 즉 내부장기에 병변이 있을 경우는 침울, 체중감소, 산란율 저하 등이 발생하며, 신경계는 발생부위별 신경증상이 일어난다. 이러한 장기나 조직에서는 육안적으로 백색에서 회백색의 종양성 병변이 관찰된다. 말초신경에 병변이 발생한 경우에는 특히 좌골신경 및 신경총에서 호발하는데, 이들 조직은 편측성 혹은 양측성으로 종창되어 있다. 안구는 간혹 육안적으로 식별이 가능한 홍채 퇴색 및 증식 병변이 관찰된다. 피부형 MD는 특히 육용계에서 문제가 되고 있으며, 산란계의 내장형 MD가 발생한 경우에도 피부를 자세히 설펴보면 피부형 MD를 간혹 관찰할 수 있다. 피부형 MD는 모낭주위에 원형의 결절형태로 발생하는데, 이들 병변이 커지면 바로 옆의 병변과 융합 되어 큰 결절을 형성하기도 한다. (중략)

• Journal of Intelligence and Information Systems
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• v.29 no.3
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• pp.57-78
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• 2023

COVID-19, which started in Wuhan, China in November 2019, spread beyond China in 2020 and spread worldwide in March 2020. It is important to prevent a highly contagious virus like COVID-19 in advance and to actively treat it when confirmed, but it is more important to identify the confirmed fact quickly and prevent its spread since it is a virus that spreads quickly. However, PCR test to check for infection is costly and time consuming, and self-kit test is also easy to access, but the cost of the kit is not easy to receive every time. Therefore, if it is possible to determine whether or not a person is positive for COVID-19 based on the sound of a cough so that anyone can use it easily, anyone can easily check whether or not they are confirmed at anytime, anywhere, and it can have great economic advantages. In this study, an experiment was conducted on a method to identify whether or not COVID-19 was confirmed based on a cough sound. Cough sound features were extracted through MFCC, Mel-Spectrogram, and spectral contrast. For the quality of cough sound, noisy data was deleted through SNR, and only the cough sound was extracted from the voice file through chunk. Since the objective is COVID-19 positive and negative classification, learning was performed through XGBoost, LightGBM, and FCNN algorithms, which are often used for classification, and the results were compared. Additionally, we conducted a comparative experiment on the performance of the model using multidimensional vectors obtained by converting cough sounds into both images and vectors. The experimental results showed that the LightGBM model utilizing features obtained by converting basic information about health status and cough sounds into multidimensional vectors through MFCC, Mel-Spectogram, Spectral contrast, and Spectrogram achieved the highest accuracy of 0.74.

• The Korean Journal of Ecology
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• v.22 no.3
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• pp.169-179
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• 1999

The present study was undertaken to classify and describe the spring naturalized plant communities in old-Andong city by the methodology of the ZM school of phytosociology. As a result, the vegetation was classified into the six communities and two subcommunities: A. Bromus tectorum community A-a. Bromus japonicus subcommunity, A-b. Melica onoei subcommunity; B. Poa pratensis community; C. Rumex crispus community; D. Oenothera lamarckiana community; E. Ambrosia artemisiifolia var. eiatior community; F. Rumex conglomeratus community. The total taxa of the naturalized plant communities consisted of 31 families, 86 genera, 114 species and 13 varieties. Of which the taxa of the naturalized plant species consisted of 8 families, 21 genera, 25 species and 1 variety. The result of Bray-Curtis ordination revealed that the plots suveyed were arranged according largely to the vegetation units of' the communities. Also the interspecific affinity was examined by an analysis of interspecific association and the main component species in the communities were divided into two groups. The naturalized rate was higher in the communitise affected by strong human impacts, while was lower in the communities affected relatively less by human impacts. On the other hand the seasonal changes of the communities and the naturalized rate between the spring and the autumn were investigated. Many naturalized communities present in Spring were replaced by the other native ruderal communitues in the Autumn. The naturalized rate based on the dominance was largely decreased over from the spring to the Autumn.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.13 no.2
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• pp.89-105
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• 2008

Sea level and atmospheric pressure data of 1999-2005 from four stations along the Korean east coast were analyzed to understand the sea level variability and its causal mechanism. The results of the wavelet and the auto-spectrum analyses indicate that the sea level fluctuations of 3-17 day period are statistically significant at the 95% confidence level, especially in spring to early summer. In this period, the coherency between the sea levels and the atmospheric pressures in a cross-spectrum is high, implying the importance of an inverted barometric effect in generation of the sea level fluctuations. To learn about the sea level variability, the cross-spectrum analyses were applied between the sea levels of the adjacent stations. The results show a case of southward phase propagations along the coast, as in 1999, 2003 and 2005, and an another case of no progressive phase lags between the stations, as in 2000-2002, and 2004. The phase speed in the former case is 12-15 m/s, which is a commonly observed phase speed of coastal Kelvin waves. Generation of such fluctuations seems to be related to low pressure cells developed in the Asian continent in spring and summer and moving eastward over the coastal region north of the stations. The latter case of no progressive phase lag, however, occurs when the low pressure cells developed in the continent move along the region south of the stations. In this case, the northeastward phase propagation with a speed of 5-8 m/s is observed along the southwestern coast of Japan.