• Proceedings of the Korean Vacuum Society Conference
• /
• 2013.08a
• /
• pp.277.1-277.1
• /
• 2013

Molecular diagnostics consists of three processes, which are a sample pretreatment, a nucleic acid amplification, and an amplicon detection. Among three components, sample pretreatment is an important process in that it can increase the limit of detection by purifying nucleic acid in biological sample from contaminants that may interfere with the downstream genetic analysis such as nucleic acid amplification and detection. To achieve point-of-care virus detection system, the sample pretreatment process needs to be simple, rapid, and automatic. However, the commercial RNA extraction kits such as Rneasy (Qiagen) or MagnaPure (Roche) kit are highly labor-intensive and time-consuming due to numerous manual steps, and so it is not adequate for the on-site sample preparation. Herein, we have developed a rotary microfluidic system to extract and purify the RNA without necessity of external mechanical syringe pumps to allow flow control using microfluidic technology. We designed three reservoirs for sample, washing buffer, and elution buffer which were connected with different dimensional microfluidic channels. By controlling RPM, we could dispense a RNA sample solution, a washing buffer, and an elution buffer successively, so that the RNA was captured in the sol-gel solid phase, purified, and eluted in the downstream. Such a novel rotary sample preparation system eliminates some complicated hardwares and human intervention providing the opportunity to construct a fully integrated genetic analysis microsystem.

• Proceedings of the Korea Water Resources Association Conference
• /
• 2015.05a
• /
• pp.245-245
• /
• 2015

In the recent years, due to long-lasting heavy rainfall events, a large number of landslides have been observed in the mountainous area of the world. Such landslides can also form a dam as it blocks the course of a river, which may burst and cause a catastrophic flood. Numerical analysis of landslide dam formation is rarely available, while laboratory experimental studies often use assumed shape to analyze the landslide dam failure and flood hydraulics in downstream. In this study, both experimental and numerical studies have been carried out to investigate the formation of landslide dam. Two case laboratory experiments were conducted in two flumes simultaneously. The first flume (2.0 m 0.6 m 0.5 m) was set at $22^{\circ}$ and $27^{\circ}$ slope to generate the landslide using rainfall intensity of 70.0 mm/hr. On the other hand, the second flume (1.5 m 0.25 m 0.3 m) was set perpendicularly at the downstream end of the first flume to receive the landslide mass forming landslide dam. The formation of landslide dam was observed at $15^{\circ}$ slope of the second flume. The whole processes including the landslide initiation and movement of the landslide mass into the second channel was captured by three digital cameras. In numerical analysis, a two-dimensional (2D) seepage flow model, a 2D slope stability model (Spencer method) and a 2D landslide dam-geometry evaluation model were coupled as a single unit. This developed model can determine the landslide occurrence time, the failure mass and the geometry of landslide dam deposited in the second channel. The data obtained from numerical simulation results has good agreement with the experimental measurements.

• Journal of Korea Water Resources Association
• /
• v.57 no.3
• /
• pp.151-164
• /
• 2024

In water treatment plants supplying potable water, the management of chlorine concentration in water treatment processes involving pre-chlorination or intermediate chlorination requires process control. To address this, research has been conducted on water quality prediction techniques utilizing AI technology. This study developed an AI-based predictive model for automating the process control of chlorine disinfection, targeting the prediction of residual chlorine concentration downstream of sedimentation basins in water treatment processes. The AI-based model, which learns from past water quality observation data to predict future water quality, offers a simpler and more efficient approach compared to complex physicochemical and biological water quality models. The model was tested by predicting the residual chlorine concentration downstream of the sedimentation basins at Plant, using multiple regression models and AI-based models like Random Forest and LSTM, and the results were compared. For optimal prediction of residual chlorine concentration, the input-output structure of the AI model included the residual chlorine concentration upstream of the sedimentation basin, turbidity, pH, water temperature, electrical conductivity, inflow of raw water, alkalinity, NH₃, etc. as independent variables, and the desired residual chlorine concentration of the effluent from the sedimentation basin as the dependent variable. The independent variables were selected from observable data at the water treatment plant, which are influential on the residual chlorine concentration downstream of the sedimentation basin. The analysis showed that, for Plant, the model based on Random Forest had the lowest error compared to multiple regression models, neural network models, model trees, and other Random Forest models. The optimal predicted residual chlorine concentration downstream of the sedimentation basin presented in this study is expected to enable real-time control of chlorine dosing in previous treatment stages, thereby enhancing water treatment efficiency and reducing chemical costs.

• Journal of the Korean association of regional geographers
• /
• v.2 no.1
• /
• pp.39-49
• /
• 1996

There is a limestone basin surrounded by the mountains consisted of Paleozoic sedimentary and metamorphic rocks in the Masung, Munkyung city, Kyungsangpook do. The purpose of this paper is to elucidate the geomorphic processes of the gentle hillslopes in the marginal piedmont of Masung basin. To do so, I analyzed deposits over hillslopes and the relation ship between the distance from the divide and the height(above sea level) at the longitudinal profile of the hillslope, and considered interrelation between the distributions of the gentle hillslopes(less than 230m) and lithology. Geomorphic processes of Masung basin are as follow: (1) The depth of deposits over hillslope increases toward downstream of the hillslope. Most gravels within deposits, whose lithology is limestone, are those eroded at the boundary(overthrust fault zone) between the back-mountain and the hillslope. Deposits at the outward margin of hillslope is well sorted. and moderately imbricated. (2) Hillslope at the margin of the basin(160-230m asl) is formed by the action of 'the flow with channel'. At the boundary between the soft rock(limestone; basin floor) and hard rock(sedimentary and metamorphic rock; back-mountain), the relatively weak limestone is eroded to fresh bedrock by the subsequent action of the overland flow, and therefore discontinuity in slope appeared. (3) After hills lopes were formed, sediments(boulders and fine material) produced during dissection in back-mountain buried deposits over hillslope. In conclusion, geomorphic processes of Masung basin is 'differential erosion due to differentiation of lithological hardness' having suggested as geomorphic processes of granitic basin. However it is not 'removal of weathering material due to sheetflow' but 'erosion due to the overland flow with channel'.

• Journal of Life Science
• /
• v.22 no.10
• /
• pp.1359-1370
• /
• 2012

Arabidopsis AtERF71/HRE2, a transcription activator, is located in the nucleus and is involved in the signal transduction of low oxygen and osmotic stresses. In this study, microarray analysis using AtERF71/HRE2-overexpressing transgenic plants was performed to identify genes downstream of AtERF71/HRE2. A total of 161 different genes as well as AtERF71/HRE2 showed more than a twofold higher expression in AtERF71/HRE2-overexpressing transgenic plants compared with wild-type plants. Among the 161 genes, 24 genes were transcriptional regulators, such as transcription factors and DNA-binding proteins, based on gene ontology annotations, suggesting that AtERF71/HRE2 is an upstream transcription factor that regulates the activities of various downstream genes via these transcription regulators. RT-PCR analysis of 15 genes selected out of the 161 genes showed higher expression in AtERF71/HRE2-overexpressing transgenic plants, validating the microarray data. On the basis of Genevestigator database analysis, 51 genes among the 161 genes were highly expressed under low oxygen and/or osmotic stresses. RT-PCR analysis showed that the expression levels of three genes among the selected 15 genes increased under low oxygen stress and another three genes increased under high salt stress, suggesting that these genes might be downstream genes of AtERF71/HRE2 in low oxygen or high salt stress signal transduction. Microarray analysis results indicated that AtERF71/HRE2 might also be involved in the responses to other abiotic stresses and also in the regulation of plant developmental processes.

• Journal of Animal Reproduction and Biotechnology
• /
• v.34 no.2
• /
• pp.123-129
• /
• 2019

Many transcription factors are involved in directing the growth of porcine oocytes. The localization and expression level of a given transcription factor often differ at each stage of early embryonic growth, which spans from fertilization to the formation of the blastocyst. A hallmark of the blastocyst stage is the separation of the endodermal and mesodermal ectoderm. The embryo's medium and its effects are known to be crucial during early development compared to the other developmental stages, and thus require a lot of caution. Therefore, in many experiments, early development is divided into the quality of oocyte and cumulus cells and used in experiments. We thought that we were also heavily influenced by genetic reasons. Here, we examined the expression patterns of five key transcription factors (CDX2, OCT4, SOX2, NANOG, and E-CADHERIN) during porcine oocyte development whose expression patterns are controversial in the pig to the literature. Antibodies against these transcription factors were used to determine the expression and localization of them during the early development of pig embryos. These results indicate that the expressions of key transcription factors are generally similar in mouse and pig early developing embryos, but NANOG and SOX2 expression appears to show speciesspecific differences between pig and mouse developing embryos. This work helps us better understand how the expression patterns of transcription factors translate into developmental effects and processes, and how the expression and localization of different transcription factors can crucially impact oocyte growth and downstream developmental processes.

• Journal of the Korean association of regional geographers
• /
• v.15 no.2
• /
• pp.204-214
• /
• 2009

The purpose of this paper is to elucidate the formation processes of Hwaeumneup in Cheonseong Mountain which was designated as Wetland Conservation Area in 2002, and to offer data essential to sustainable management of wetland. According to wetland core samples and carbon dating of humus, grassland of Hwaeumneup Wetland Reservation resulted from slash-and-burn agriculture in no reference with climatic changes of last glacial period. And Hwaeumneup is a alpine wetland that is formed as rain water over Cheonseong Mountain crest area infiltrates into bedrock, springs out along joint line below main ridge, and dampens gentle grassland. It needs to support dense vegetation of southwestern ridge of Wetland Reservation in order to sustain water volumn of Hwaeumneup wetland, and to keep from breakdown of block dam at downstream fringe of wetland. And it needs to measure and analyse micro-topography and hydrology changes in Hwaeumneup Wetland Reservation through periodic monitoring.

• Corrosion Science and Technology
• /
• v.7 no.6
• /
• pp.350-361
• /
• 2008

Canada's oil sands contain one of the largest reserves of oil in the world. According to recent estimates, there are nearly 180 billion barrels of oil in the Canadian oil sands trapped in a complex mixture of sand, water and clay. More than 40 companies have been currently operating or developing oil sands facilities since the first production in 1967. The process of oil sands upgrading is similar with down stream refinery, but the corrosion environment in upgrading refinery is often more severe than in the refinery because of high chlorides, mineral contents, carbonic acid, heavy viscosity and fouling, higher naphthenic acid [$NA-R(CH_{2})nCOOH$], and greater sulfur contents. Naphthenic acid corrosion (NAC) which is one of the most critical corrosion issues in up & downstream refinery plants was observed for the first time in 1920's in refinery distillation processes of Rumania, Azerbaizan (Baku), Venezuela, and California. As a first API report, the 11th annual meeting stated sources and mechanism of NAC in early 1930's. API has been developing the risk base standards, such as API RP580, 571, and Publication 581 which are based on the worst NAC damage in the world since 2000. Nevertheless not only the NAC phenomena and control in Canadian sands oil process are not much widely known but also there are still no engineering guidances for the Canadian sands oil in API standards. This paper will give NAC phenomina and materials selection guidance against NA environment in Canadian oil sands upgrading processes.

• Journal of Life Science
• /
• v.22 no.9
• /
• pp.1237-1242
• /
• 2012

The use of biological-activated carbon (BAC) processes in water treatment involves biofiltration, which maximizes the bacteria's capabilities to remove organic matter. In this study, the distribution of the bacterial community was assessed in response to different types of BAC processes applied downstream in the Nakdong River. The bacterial biomass and activity were $1.20{\sim}34.0{\times}10^7$ CFU/g and 0.61~1.10 mg-C/$m^3{\cdot}hr$ in coal-based BAC, respectively. The attachment of the bacterial biomass and the removal efficiency of the organic carbon were greatest with the coal-based activated carbon. The bacteria attached to each activated carbon material were detected in the order of Pseudomonas genus, Chryseomonas genus, Flavobacterium genus, Alcaligenes genus, Acinetobacter genus, and Spingomona genus. Pseudomonas cepacia was the dominant species in the coal-based materials, and Chryseomonas luteola was the dominant species in the wood-based material.

• Proceedings of the Korea Water Resources Association Conference
• /
• 2023.05a
• /
• pp.246-246
• /
• 2023

Multi-purpose dams are operated accounting for both physical and socioeconomic factors. This study aims to evaluate the utility of a deep learning algorithm-based model for three multi-purpose dam operation (Seomjin River dam, Juam dam, and Juam Control dam) in Seomjin River. In this study, the Gated Recurrent Unit (GRU) algorithm is applied to predict hourly water level of the dam reservoirs over 2002-2021. The hyper-parameters are optimized by the Bayesian optimization algorithm to enhance the prediction skill of the GRU model. The GRU models are set by the following cases: single dam input - single dam output (S-S), multi-dam input - single dam output (M-S), and multi-dam input - multi-dam output (M-M). Results show that the S-S cases with the local dam information have the highest accuracy above 0.8 of NSE. Results from the M-S and M-M model cases confirm that upstream dam information can bring important information for downstream dam operation prediction. The S-S models are simulated with altered outflows (-40% to +40%) to generate the simulated water level of the dam reservoir as alternative dam operational scenarios. The alternative S-S model simulations show physically inconsistent results, indicating that our deep learning algorithm-based model is not explainable for multi-purpose dam operation patterns. To better understand this limitation, we further analyze the relationship between observed water level and outflow of each dam. Results show that complexity in outflow-water level relationship causes the limited predictability of the GRU algorithm-based model. This study highlights the importance of socioeconomic factors from hidden multi-purpose dam operation processes on not only physical processes-based modeling but also aritificial intelligence modeling.