A STUDY ABOUT THE APOPTOSIS OF EPITHELIAL CELLS IN THE FUSING FETAL RAT PALATE (흰쥐 태아 구개융합부위 상피세포의 아포프토시스에 관한 연구)
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- The korean journal of orthodontics
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- v.31 no.1 s.84
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- pp.71-83
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- 2001
The purpose of this study was to Prove that the medial edge epithelial cells covering the secondary palatal shelves were removed by apoptosis during palatal fusion. 12 mature female rats (Suprague-Dawley) were mated overnight with male rats and sacrificed on days 15.0, 16.5, 16.75, 17.0 of pregnancy. The embryos were removed from the uterus and the heads were embedded in paraffin. The paraffin blocks were sectioned and the sections were undergone H-E staining for general histologic feature and TdT staining for detection of apoptotic cells. The obtained results were as follows. k. In the section of 16.0 and 16.5 day embryos, the palatal shelves were prior to contact and no apoptotic cells wereobserved in the medial edge epithelium. At the initial contact of Palatal shelves, there was a few apoptotic cells in the fusing epithelium. 2. In the 16.75 day embryos, the samples that epithelial seams did not lost there continuity, apoptotic cells were rarely seen at the midline epithelial seam. In contrast, a lot of apoptotic cells were observed at epithelial triangles and the junction between palatal shelves and nasal septum. 3. In the 16,75 day embryos, the samples that epithelial seams lost their continuity and disrupted to epithelial islands, large number, of apoptotic cells were observed at epithelial islands and epithelial triangles. Some apoptotic cells were also observed at the oral, nasal epithelium near the midline. 4. In the 17.0 day embryos, most of epithelial islands were disappeared and mesenchymal confluence was achieved. Apoptotic cells were rarely observed in the mesenchymal tissue which replaced epithelial islands, but there were some apoptotic cells at the epithelial triangles, oral and nasal epithelium. From the results of the study, it was revealed that medial edge epithelial cells of fusing palate were removed by apoptosis. Apoptotic cells were found mainly in the disappearing midline epithelial seam and the oral and nasal epithelial triangles at some late stages of palatal fusion.
The incorporation of RAPD markers into the previous classical and RFLP genetic linkage maps will facilitate the generation of a detailed genetic map by compensating for the lack of one type of marker in the region of interest. The objective of this paper was to present features we observed when we associated RAPD map from an intraspecific cross of a Glycine max
The need for polar education was further emphasized, depending on the importance of the pole, which is the best place for climate change detection and prediction, and treasure trove of future technology and resources. Therefore, this study analyzed the general cognitive and affective characteristics of elementary school students' polar literacy, and in addition, analyzed the cognitive and affective characteristics according to the level of diversity about polar experience. The items developed for the study were revised through a pilot survey of 43 fifth graders. They consisted of questions about gender, polar experience, scientific literacy, polar knowledge, polar literacy skills, polar literacy beliefs, and polar literacy attitudes. The types of questions used are selectable, reliable, and Likert (4 points), for a total of 66 questions. The students who participated in the study were 323 fifth grade elementary students. The study found that students were more interested in the dramatic consequences of polar changes than the scientific causes and processes associated with it. This is confirmed through the fact that they are more interested in and familiar with polar creatures suffering from polar changes than understanding ice, which is the main feature of and the central mechanism of polar changes. Students also recognized the issue of polar climate change as a global issue other than their own. They believe that what happens in the Arctic and Antarctica will affect the whole world, but not significantly to himself and his community. The level of knowledge about polar region and the ability to analyze and infer were not significantly related to each other, and students with a higher level of diversity of experience about polar region had a better understanding of polar science and technology. In this research, it is meaningful to check the characteristics related to the students' polar region and to use it as a basic data to show the direction in which polar literacy education should proceed in the future.
We for the first time made a successful longest continuous sectional observation in the East Sea by an underwater glider during 95 days from September 18 to December 21 2020 in the Korea along the 106 Line (129.1 °E ~ 131.5 °E at 37.9 °N) of the regular shipboard measurements by the National Institute of Fishery Science (NIFS) and obtained twelve hydrographic sections with high spatiotemporal resolution. The glider was deployed at 129.1 °E in September 18 and conducted 88-days flight from September 19 to December 15 2020, yielding twelve hydrographic sections, and then recovered at 129.2 °E in December 21 after the last 6 days virtual mooring operation. During the total traveled distance of 2550 km, the estimated deviation from the predetermined zonal path had an average RMS distance of 262 m. Based on these high-resolution long-term glider measurements, we conducted a comparative study with the bi-monthly NIFS measurements in terms of spatial and temporal resolutions, and found distinguished features. One is that spatial features of sub-mesoscale such as sub-mesoscale frontal structure and intensified thermocline were detected only in the glider measurements, mainly due to glider's high spatial resolution. The other is the detection of intramonthly variations from the weekly time series of temperature and salinity, which were extracted from glider's continuous sections. Lastly, there were deviations and bias in measurements from both platforms. We argued these deviations in terms of the time scale of variation, the spatial scale of fixed-point observation, and the calibration status of CTD devices of both platforms.
The wall shear stress in the vicinity of end-to end anastomoses under steady flow conditions was measured using a flush-mounted hot-film anemometer(FMHFA) probe. The experimental measurements were in good agreement with numerical results except in flow with low Reynolds numbers. The wall shear stress increased proximal to the anastomosis in flow from the Penrose tubing (simulating an artery) to the PTFE: graft. In flow from the PTFE graft to the Penrose tubing, low wall shear stress was observed distal to the anastomosis. Abnormal distributions of wall shear stress in the vicinity of the anastomosis, resulting from the compliance mismatch between the graft and the host artery, might be an important factor of ANFH formation and the graft failure. The present study suggests a correlation between regions of the low wall shear stress and the development of anastomotic neointimal fibrous hyperplasia(ANPH) in end-to-end anastomoses. 30523 T00401030523 ^x Air pressure decay(APD) rate and ultrafiltration rate(UFR) tests were performed on new and saline rinsed dialyzers as well as those roused in patients several times. C-DAK 4000 (Cordis Dow) and CF IS-11 (Baxter Travenol) reused dialyzers obtained from the dialysis clinic were used in the present study. The new dialyzers exhibited a relatively flat APD, whereas saline rinsed and reused dialyzers showed considerable amount of decay. C-DAH dialyzers had a larger APD(11.70
The wall shear stress in the vicinity of end-to end anastomoses under steady flow conditions was measured using a flush-mounted hot-film anemometer(FMHFA) probe. The experimental measurements were in good agreement with numerical results except in flow with low Reynolds numbers. The wall shear stress increased proximal to the anastomosis in flow from the Penrose tubing (simulating an artery) to the PTFE: graft. In flow from the PTFE graft to the Penrose tubing, low wall shear stress was observed distal to the anastomosis. Abnormal distributions of wall shear stress in the vicinity of the anastomosis, resulting from the compliance mismatch between the graft and the host artery, might be an important factor of ANFH formation and the graft failure. The present study suggests a correlation between regions of the low wall shear stress and the development of anastomotic neointimal fibrous hyperplasia(ANPH) in end-to-end anastomoses. 30523 T00401030523 ^x Air pressure decay(APD) rate and ultrafiltration rate(UFR) tests were performed on new and saline rinsed dialyzers as well as those roused in patients several times. C-DAK 4000 (Cordis Dow) and CF IS-11 (Baxter Travenol) reused dialyzers obtained from the dialysis clinic were used in the present study. The new dialyzers exhibited a relatively flat APD, whereas saline rinsed and reused dialyzers showed considerable amount of decay. C-DAH dialyzers had a larger APD(11.70
From the 21st century, various high-quality services have come up with the growth of the internet or 'Information and Communication Technologies'. Especially, the scale of E-commerce industry in which Amazon and E-bay are standing out is exploding in a large way. As E-commerce grows, Customers could get what they want to buy easily while comparing various products because more products have been registered at online shopping malls. However, a problem has arisen with the growth of E-commerce. As too many products have been registered, it has become difficult for customers to search what they really need in the flood of products. When customers search for desired products with a generalized keyword, too many products have come out as a result. On the contrary, few products have been searched if customers type in details of products because concrete product-attributes have been registered rarely. In this situation, recognizing texts in images automatically with a machine can be a solution. Because bulk of product details are written in catalogs as image format, most of product information are not searched with text inputs in the current text-based searching system. It means if information in images can be converted to text format, customers can search products with product-details, which make them shop more conveniently. There are various existing OCR(Optical Character Recognition) programs which can recognize texts in images. But existing OCR programs are hard to be applied to catalog because they have problems in recognizing texts in certain circumstances, like texts are not big enough or fonts are not consistent. Therefore, this research suggests the way to recognize keywords in catalog with the Deep Learning algorithm which is state of the art in image-recognition area from 2010s. Single Shot Multibox Detector(SSD), which is a credited model for object-detection performance, can be used with structures re-designed to take into account the difference of text from object. But there is an issue that SSD model needs a lot of labeled-train data to be trained, because of the characteristic of deep learning algorithms, that it should be trained by supervised-learning. To collect data, we can try labelling location and classification information to texts in catalog manually. But if data are collected manually, many problems would come up. Some keywords would be missed because human can make mistakes while labelling train data. And it becomes too time-consuming to collect train data considering the scale of data needed or costly if a lot of workers are hired to shorten the time. Furthermore, if some specific keywords are needed to be trained, searching images that have the words would be difficult, as well. To solve the data issue, this research developed a program which create train data automatically. This program can make images which have various keywords and pictures like catalog and save location-information of keywords at the same time. With this program, not only data can be collected efficiently, but also the performance of SSD model becomes better. The SSD model recorded 81.99% of recognition rate with 20,000 data created by the program. Moreover, this research had an efficiency test of SSD model according to data differences to analyze what feature of data exert influence upon the performance of recognizing texts in images. As a result, it is figured out that the number of labeled keywords, the addition of overlapped keyword label, the existence of keywords that is not labeled, the spaces among keywords and the differences of background images are related to the performance of SSD model. This test can lead performance improvement of SSD model or other text-recognizing machine based on deep learning algorithm with high-quality data. SSD model which is re-designed to recognize texts in images and the program developed for creating train data are expected to contribute to improvement of searching system in E-commerce. Suppliers can put less time to register keywords for products and customers can search products with product-details which is written on the catalog.
As the era of space technology utilization is approaching, the launch of CAS (Compact Advanced Satellite) 500-1/2 satellites is scheduled during 2021 for acquisition of high-resolution images. Accordingly, the increase of image usability and processing efficiency has been emphasized as key design concepts of the CAS 500-1/2 ground station. In this regard, "CAS 500-1/2 Image Acquisition and Utilization Technology Development" project has been carried out to develop core technologies and processing systems for CAS 500-1/2 data collecting, processing, managing and distributing. In this paper, we introduce the results of the above project. We developed an operation system to generate precision images automatically with GCP (Ground Control Point) chip DB (Database) and DEM (Digital Elevation Model) DB over the entire Korean peninsula. We also developed the system to produce ortho-rectified images indexed to 1:5,000 map grids, and hence set a foundation for ARD (Analysis Ready Data)system. In addition, we linked various application software to the operation system and systematically produce mosaic images, DSM (Digital Surface Model)/DTM (Digital Terrain Model), spatial feature thematic map, and change detection thematic map. The major contribution of the developed system and technologies includes that precision images are to be automatically generated using GCP chip DB for the first time in Korea and the various utilization product technologies incorporated into the operation system of a satellite ground station. The developed operation system has been installed on Korea Land Observation Satellite Information Center of the NGII (National Geographic Information Institute). We expect the system to contribute greatly to the center's work and provide a standard for future ground station systems of earth observation satellites.
Social media is a representative form of the Web 2.0 that shapes the change of a user's information behavior by allowing users to produce their own contents without any expert skills. In particular, as a new communication medium, it has a profound impact on the social change by enabling users to communicate with the masses and acquaintances their opinions and thoughts. Social media data plays a significant role in an emerging Big Data arena. A variety of research areas such as social network analysis, opinion mining, and so on, therefore, have paid attention to discover meaningful information from vast amounts of data buried in social media. Social media has recently become main foci to the field of Information Retrieval and Text Mining because not only it produces massive unstructured textual data in real-time but also it serves as an influential channel for opinion leading. But most of the previous studies have adopted broad-brush and limited approaches. These approaches have made it difficult to find and analyze new information. To overcome these limitations, we developed a real-time Twitter trend mining system to capture the trend in real-time processing big stream datasets of Twitter. The system offers the functions of term co-occurrence retrieval, visualization of Twitter users by query, similarity calculation between two users, topic modeling to keep track of changes of topical trend, and mention-based user network analysis. In addition, we conducted a case study on the 2012 Korean presidential election. We collected 1,737,969 tweets which contain candidates' name and election on Twitter in Korea (http://www.twitter.com/) for one month in 2012 (October 1 to October 31). The case study shows that the system provides useful information and detects the trend of society effectively. The system also retrieves the list of terms co-occurred by given query terms. We compare the results of term co-occurrence retrieval by giving influential candidates' name, 'Geun Hae Park', 'Jae In Moon', and 'Chul Su Ahn' as query terms. General terms which are related to presidential election such as 'Presidential Election', 'Proclamation in Support', Public opinion poll' appear frequently. Also the results show specific terms that differentiate each candidate's feature such as 'Park Jung Hee' and 'Yuk Young Su' from the query 'Guen Hae Park', 'a single candidacy agreement' and 'Time of voting extension' from the query 'Jae In Moon' and 'a single candidacy agreement' and 'down contract' from the query 'Chul Su Ahn'. Our system not only extracts 10 topics along with related terms but also shows topics' dynamic changes over time by employing the multinomial Latent Dirichlet Allocation technique. Each topic can show one of two types of patterns-Rising tendency and Falling tendencydepending on the change of the probability distribution. To determine the relationship between topic trends in Twitter and social issues in the real world, we compare topic trends with related news articles. We are able to identify that Twitter can track the issue faster than the other media, newspapers. The user network in Twitter is different from those of other social media because of distinctive characteristics of making relationships in Twitter. Twitter users can make their relationships by exchanging mentions. We visualize and analyze mention based networks of 136,754 users. We put three candidates' name as query terms-Geun Hae Park', 'Jae In Moon', and 'Chul Su Ahn'. The results show that Twitter users mention all candidates' name regardless of their political tendencies. This case study discloses that Twitter could be an effective tool to detect and predict dynamic changes of social issues, and mention-based user networks could show different aspects of user behavior as a unique network that is uniquely found in Twitter.