• Journal of Life Science
• /
• v.26 no.9
• /
• pp.1007-1014
• /
• 2016

A highly efficient, rapid, and reliable multiplex polymerase chain reaction based method for distinguishing ten species of genus Cynoglossus (C. senegalensis, C. abbreviates, C. macrolepidotus, C. arel, C. semilaevis, C. interruptus, C. joyneri, C. lingua, C. robustus, and C. monodi) is described. The species-specific primer sets were designed base on the cytochrome oxidase subunit I gene (1,500 bp). The optimal PCR conditions and primers were selected for ten of Cynoglossus species to determine target base sequences using single PCR. Multiplex PCR using the ten pairs of primers either specifically amplified a DNA fragment of a unique size or failed, depending on each species DNA. The length of amplification fragment of 208 bp for C. senegalensis, 322 bp for C. abbreviates, 493 bp for C. macrolepidotus, 754 bp for C. arel, 874 bp for C. semilaevis, 952 bp for C. interruptus, 1,084 bp for C. joyneri, 1,198 bp for C. lingua, 1,307 bp for C. robustus, and 1,483 bp for C. monodi with the species-specific primers, visualized by agarose gel electrophoresis, allowed perfectly distinction of the Cynoglossus species. The multiplex PCR assay can be easily performed on multiple samples and attain final results in less than 6 hours. This technique should be a useful addition to the molecular typing tools for the tentative identification of Cynoglossus species.

• Journal of Life Science
• /
• v.15 no.4 s.71
• /
• pp.607-612
• /
• 2005

Heat shock protein 70 (HSP70) is a multigene family composed of constitutively expressed members(Hsc70) and stress-inducible members (Hsp70). In the mammalian nervous system, a considerable amount of HSPs is also synthesized under normal conditions suggesting that they play an important role in the metabolism of unstressed cells. In this study we examined the expression of Hsp70 in the synapses of rat cerebellar neurons. Immunohistochemistry using specific antibodies revealed that both Hsp70 and Hsc70 are expressed in the cerebellar tissue, with strongest expression in Purkinje cells followed by granule cells. Neurons in deep cerebellar nuclei were also intensely stained by Hsp70 antibody. Immunocytochemical stainings of cultured cerebellar cells showed that Hsp70 is expressed in both Purkinje and granule cells. The expression was punctate in the soma and along dendritic trees, and the punctae were colocalized with those of PSD95, a postsynaptic marker. Immunoblotting also indicates that Hsp70 is associated with the postsynaptic density fraction. Taken together, our results indicate that the Hsp70 is expressed in cerebellar neurons in normal conditions, and that some are localized in the synapses.

• Journal of Life Science
• /
• v.22 no.3
• /
• pp.324-331
• /
• 2012

Bacteriological examination of spring water in Jeju City was conducted. A total of 21 spring water samples were collected from January to April, 2010. During the study period, the range of temperature was 0.6 to $15.4^{\circ}C$, and the results of the analyses showed that hydrogen ion concentrations (pH) for spring water were 0.43 to 7.9. Salinity levels for the samples averaged from 3.0 to 1.64%, and levels of water-dissolved oxygen were 1.85 to 6.06 mg/l. The range of total coliforms in spring water samples at 21 stations located in the designated spring water were <1.8->1,600 MPN/100 ml. Furthermore, the range of geometric means of total coliforms was 9.9-151.6 MPN/100 ml, while the range of fecal coliforms in spring water samples at 21 stations located in the designated spring water area was <1.8->1,600 MPN/100 ml. Finally, the range of geometric mean of fecal coliforms was 3.1-151.6 MPN/100 ml. The level of microbial contamination was examined in 21 samples for indications of bacterial contamination such as heterotrophic bacteria, Escherichia coli O157:H7, Salmonella spp., Vibrio parahaemolyticus, Staphylococcus aureus, and Shigella spp. were frequently detected in the spring water. Salmonella spp., Shigella spp., Vibrio parahaemolyticus, and S. aureus were detected in the range of $0-0.5{\times}10^1$, $0-0.1{\times}10^1$, $0-0.1{\times}10^1$, and $0-0.3{\times}10^1$ CFU/ml, respectively, while E. coli O157:H7 was not detected in the examined spring water samples.

• Korean Journal of Heritage: History & Science
• /
• v.57 no.3
• /
• pp.56-67
• /
• 2024

This study aims to characterize the material of the finishing materials used in the No.1 stone chamber tomb of the Baekje-era tumuli in Songjeri, Naju with mineralogical, chemical, and physical analyses. The finishing material is a mixture of white lumps and fragments, presumed to be shells, that remain on the surface and between the gaps of the stone walls inside the tomb. The analysis results revealed that the main constituent mineral of the finishing material is calcite. Infrared spectroscopy showed peaks due to calcium carbonate, and thermal reaction decarbonation in the 700~800℃ range, high calcium content, and loss on ignition were confirmed. Therefore, the main material of the finishing materials was determined to be lime, and since no aggregates such as sand or gravel were found, it was identified as lime paste. The shell fragments mixed into the lime paste appear dark blue or grayish-white in color, with no original shape remaining. The surface has a layered structure, and microscopic observations revealed prismatic layers with a columnar structure and nacreous layers with a consistent orientation, suggesting that the shells are from bivalve mollusks. Additionally, X-ray imaging of the shell fragments showed holes and tunnels caused by boring marine organisms both on the surface and inside, and radiocarbon dating results confirmed that the dating of the shells was consistent with the construction period of the tomb. It is concluded that the finishing material used in Tomb No. 1 in Songje-ri, Naju, was lime paste mixed with shell fragments, and the lime was made using the shells of bivalve mollusks as the raw material.

• Journal of Intelligence and Information Systems
• /
• v.26 no.2
• /
• pp.1-25
• /
• 2020

In this paper, we suggest an application system architecture which provides accurate, fast and efficient automatic gasometer reading function. The system captures gasometer image using mobile device camera, transmits the image to a cloud server on top of private LTE network, and analyzes the image to extract character information of device ID and gas usage amount by selective optical character recognition based on deep learning technology. In general, there are many types of character in an image and optical character recognition technology extracts all character information in an image. But some applications need to ignore non-of-interest types of character and only have to focus on some specific types of characters. For an example of the application, automatic gasometer reading system only need to extract device ID and gas usage amount character information from gasometer images to send bill to users. Non-of-interest character strings, such as device type, manufacturer, manufacturing date, specification and etc., are not valuable information to the application. Thus, the application have to analyze point of interest region and specific types of characters to extract valuable information only. We adopted CNN (Convolutional Neural Network) based object detection and CRNN (Convolutional Recurrent Neural Network) technology for selective optical character recognition which only analyze point of interest region for selective character information extraction. We build up 3 neural networks for the application system. The first is a convolutional neural network which detects point of interest region of gas usage amount and device ID information character strings, the second is another convolutional neural network which transforms spatial information of point of interest region to spatial sequential feature vectors, and the third is bi-directional long short term memory network which converts spatial sequential information to character strings using time-series analysis mapping from feature vectors to character strings. In this research, point of interest character strings are device ID and gas usage amount. Device ID consists of 12 arabic character strings and gas usage amount consists of 4 ~ 5 arabic character strings. All system components are implemented in Amazon Web Service Cloud with Intel Zeon E5-2686 v4 CPU and NVidia TESLA V100 GPU. The system architecture adopts master-lave processing structure for efficient and fast parallel processing coping with about 700,000 requests per day. Mobile device captures gasometer image and transmits to master process in AWS cloud. Master process runs on Intel Zeon CPU and pushes reading request from mobile device to an input queue with FIFO (First In First Out) structure. Slave process consists of 3 types of deep neural networks which conduct character recognition process and runs on NVidia GPU module. Slave process is always polling the input queue to get recognition request. If there are some requests from master process in the input queue, slave process converts the image in the input queue to device ID character string, gas usage amount character string and position information of the strings, returns the information to output queue, and switch to idle mode to poll the input queue. Master process gets final information form the output queue and delivers the information to the mobile device. We used total 27,120 gasometer images for training, validation and testing of 3 types of deep neural network. 22,985 images were used for training and validation, 4,135 images were used for testing. We randomly splitted 22,985 images with 8:2 ratio for training and validation respectively for each training epoch. 4,135 test image were categorized into 5 types (Normal, noise, reflex, scale and slant). Normal data is clean image data, noise means image with noise signal, relfex means image with light reflection in gasometer region, scale means images with small object size due to long-distance capturing and slant means images which is not horizontally flat. Final character string recognition accuracies for device ID and gas usage amount of normal data are 0.960 and 0.864 respectively.

• Clean Technology
• /
• v.28 no.1
• /
• pp.46-53
• /
• 2022

The agglomeration characteristics of coal and silica sand were investigated under various conditions using mixed samples consisting of coal, silica sand, and potassium hydroxide, which is an agglomeration accelerator. The samples were prepared by either physically mixing or using aqueous solutions. The experiments using the physically mixed powder samples were performed with a two hour reaction time. The results showed that the number of aggregates generated increased as the reaction temperature and the total potassium content increased. The experiments using aqueous solutions were performed at 880 ℃, which is the operating temperature of a fluidized bed boiler, and at 980 ℃, which assumes a local hot spot. The amount of agglomeration generated as the reaction time increased and the total potassium content increased was identified. In the experiment performed at 880 ℃, the amount of aggregate generated clearly increased with the reaction time, and in the experiment performed at 980 ℃, assuming a local hot spot, a large amount of aggregate was generated in a relatively short time. The aggregates became harder as the potassium content increased. When the total potassium content was less than 1.37 wt.%, the aggregates were weak at both temperatures and collapsed even with a slight impact. Additionally, the surface characteristics of the silica sand and ash aggregates were observed by SEM-EDS analysis. The analysis revealed a large amount of potassium at the bonding sites. This result indicates that there is a high possibility of aggregation in the form of a eutectic compound when the alkali component is increased.

• The Journal of the Korea Contents Association
• /
• v.6 no.4
• /
• pp.146-157
• /
• 2006

Causal relationship means what relations the result occurred have with a fact as a reason. In general, a formular that no result exists without reasons is used for the method to confirm existence and inexistence of causal relationship. Problematic causal relationships in Private Law are reparations (Article No. 393 of Private Law) due to debt nonfulfillment and reparation due to tort (Application of Article No. 393 by Article No. 750, and No. 763 of Private Law). The purpose pursued by reparation system in private law is to promote equal burden of damages, and the range of reparation at this time is decided by the range of damage and the range of damage is decided by the principle of causal relationship. That the causal relationship theory fairly causes confusion by treating one problem and the other problem as the same thing, instead of dividing them according to the purpose of protection presented by the law is a reason of the criticism from different views.

• Progress in Medical Physics
• /
• v.19 no.2
• /
• pp.102-112
• /
• 2008

We developed a high-resolution micro-CT system based on rotational gantry and flat-panel detector for live mouse imaging. This system is composed primarily of an x-ray source with micro-focal spot size, a CMOS (complementary metal oxide semiconductor) flat panel detector coupled with Csl (TI) (thallium-doped cesium iodide) scintillator, a linearly moving couch, a rotational gantry coupled with positioning encoder, and a parallel processing system for image data. This system was designed to be of the gantry-rotation type which has several advantages in obtaining CT images of live mice, namely, the relative ease of minimizing the motion artifact of the mice and the capability of administering respiratory anesthesia during scanning. We evaluated the spatial resolution, image contrast, and uniformity of the CT system using CT phantoms. As the results, the spatial resolution of the system was approximately the 11.3 cycles/mm at 10% of the MTF curve, and the radiation dose to the mice was 81.5 mGy. The minimal resolving contrast was found to be less than 46 CT numbers on low-contrast phantom imaging test. We found that the image non-uniformity was approximately 70 CT numbers at a voxel size of ${\sim}55{\times}55{\times}X100\;{\mu}^3$. We present the image test results of the skull and lung, and body of the live mice.

• Economic and Environmental Geology
• /
• v.41 no.6
• /
• pp.645-655
• /
• 2008

The Cr(VI) concentrations at the shallow aquifer well (MPH-0-1) of the Moonpyung groundwater monitoring station were in the range of 0.5 to 3.1 mg/L exceeding 10 to 62 times the guideline for drinking-water quality, indicating continuous contamination. However, Cr was not detected at the deep bedrock well and the other subsidiary monitoring wells except for MPH-1 and 6. Cross-correlation analyses were conducted for rainfall and groundwater level time series, resulting in the mean time of recharge after precipitation events to be 5.6 days. For rainy season, the water level was raised and the Cr(VI) concentration was several times lower than that during dry season at well MPH-0-1 well. Correlation of the Cr(VI) concentration with the groundwater-level showed that the Cr(VI) reduction was closely related with the groundwater-level rise in the well. However, the groundwater level rise during high water season induced the lateral migration of the Cr(VI)-contaminated groundwater at well MPH-4. We enriched and isolated a chromium reducing bacteria, Enterobacter aerogenes, from the Cr(VI)-contaminated groundwater in the wells MPH-0-1 and MPH-1. The bacteria may play an important role for immobilizing Cr(VI) in the Cr(VI)-contaminated groundwater. Therefore, the migration of the contaminant (Cr(VI) must has been restricted because of the natural attenuation by microbial reduction of Cr(VI) in the groundwater. This research suggests that the bioremediation of the Cr(VI)-contaminated groundwater by the indigenous bacteria may be feasible in the Cr(VI) contaminated groundwater.

• Journal of radiological science and technology
• /
• v.29 no.1
• /
• pp.1-6
• /
• 2006

Purpose: Renal stones are common and typically arise within the collecting system. The renal sinus are contains the collection system, the renal vessels, lymphatcs, fat, and fibrous tissue. Because of the compression of all the large echoes in signal processing, the echo from the renal stone generally cannot be distinguished from large echoes emanating from normal structures of the renal sinus. Use of ultrasonography has been difficult for detecting small renal stone without posterior shadowing and chemical composition of stone. The aim of study was measuring for posterior acoustic shadowing to a stone for various scan parameter and it examines a help in renal stone diagnosis. Material & Methods: The stone was place on sponge examined in a water bath with a 3.5MHz or 7.5MHz transducer(LOGIQ 400, USA). First, tested a variety of gain. Second, tested a variety of dynamic range. Third, tested a variety of focal zone. Fourth, measuring of the echo level for low and high frequency for depth. Results: 1) Average echo level was 98 for low total gain(10 dB) and was 142 for high total gain(40 dB). Posterior acoustic shadowing of renal stone was clear for low gain. 2) Average echo level was 129 for low dynamic range(42 dB) and was 101 for high dynamic range(72 dB). Posterior acoustic shadowing of renal stone was clear for high dynamic range. 3) When stone is in focal zone of transducer, definite posterior acoustic shadow is identified. 4) Stone was clear appeared for high frequency(7.5 MHz) than low frequency(3.5 MHz) and it is not distorted. Conclusion: The demonstration of an posterior acoustic shadow of renal stone dependents on several technical factors such as gain, dynamic range, focus, and frequency. This various factors are a help in renal stone diagnosis.