• Development and Reproduction
• /
• v.23 no.1
• /
• pp.35-42
• /
• 2019

Fish shows great difference in growth rate between individuals during larval development and early growth. This difference seriously reduces the production efficiency in fish culture. Growth hormone (GH)/Insulin-like growth factor 1 (IGF1) system is said to play some pivotal roles in fish growth. In this study, we investigated differences of GH, IGF1 and GHR gene expressions in juvenile red spotted grouper (Epinephelus akaara) with different growth performance. Red spotted groupers were reared under the same environmental condition (water temperature $24{\pm}1^{\circ}C$, natural light) for 96 days after hatching. They were divided into 3 groups by size (fast growing, middle growing and slow growing groups: FGG, MGG, and SGG, respectively). RNA was extracted from the brain, liver and muscle tissues from each group, and target gene expression was examined by real-time PCR. In the brain with pituitary gland, expression of GH gene in FGG was significantly higher than the expression in SGG, but the expression of IGF1 and GHR genes in the muscle was highest in SGG. Difference of GHR and IGF1 mRNA in the liver between groups with different growth performance was less clear than that in other tissues, although level of IGF1 mRNA was higher in SGG than in MGG. These results suggest that hormonal governing of growth is not the same in fast growing and slow growing fish, and size grading could cause a shift of hormonal state and growth pattern in this species.

• Journal of Forest and Environmental Science
• /
• v.27 no.3
• /
• pp.135-141
• /
• 2011

The present study was carried out from September 2007 to February 2008 in Umfakarin natural forest reserve, South Kordofan, Sudan. The objective was to analyze the effect of different management strategies on yield of gum talha from Acacia seyal. A total of 493 single target trees were selected, based on their diameters, and assigned to tapping treatments in three different stand densities (making a total of nine treatments per stand density). The treatments are as follows: tapping date with three levels (first of October, 15 October and first of November) and two levels of local tapping tools (sonki, and makmak). Untapped trees were used as control. The first picking of gum was started fifteen days after tapping while the subsequent pickings were done in intervals of fifteen days. Yield per tree throughout the season was obtained by summing up the gum yield from all pickings. Yield throughout the season (from first to the last picking) were analyzed. General linear model (GLM) was used to test the effect of different tapping treatments on the yield of gum talha. Post hoc test after analysis of variance (ANOVA) based on Scheffe test was performed to examine the differences in gum yield as a result of different management strategies. The results showed that tapping has a significant influence on gum yield. Analysis of pick-to-pick yield indicated that only three treatments in dense stand density showed a decreasing pattern while the rest of treatments either have constant or unclear patterns. The results of the present study were based on a single season data and that may underscore the real effect of Acacia seyal stands' management strategies on gum talha yield. Conducting gum yield experiments in permanent trial plots are highly recommended in order to analyze gum yield of seasonal time series.

• BMB Reports
• /
• v.52 no.11
• /
• pp.665-670
• /
• 2019

Nucleotide-binding oligomerization domain protein 2 (NOD2), an intracellular pattern recognition receptor, plays important roles in inflammation and cell death. Previously, we have shown that NOD2 is expressed in vascular smooth muscle cells (VSMCs) and that NOD2 deficiency promotes VSMC proliferation, migration, and neointimal formation after vascular injury. However, its role in endoplasmic reticulum (ER) stress-induced cell death in VSMCs remains unclear. Thus, the objective of this study was to evaluate ER stress-induced viability of mouse primary VSMCs. NOD2 deficiency increased ER stress-induced cell death and expression levels of apoptosis mediators (cleaved caspase-3, Bax, and Bak) in VSMCs in the presence of tunicamycin (TM), an ER stress inducer. In contrast, ER stress-induced cell death and expression levels of apoptosis mediators (cleaved caspase-3, Bax, and Bak) were decreased in NOD2-overexpressed VSMCs. We found that the $IRE-1{\alpha}-XBP1$ pathway, one of unfolded protein response branches, was decreased in NOD2-deficient VSMCs and reversed in NOD2-overexpressed VSMCs in the presence of TM. Furthermore, NOD2 deficiency reduced the expression of XBP1 target genes such as GRP78, PDI-1, and Herpud1, thus improving cell survival. Taken together, these data suggest that the induction of ER stress through NOD2 expression can protect against TM-induced cell death in VSMCs. These results may contribute to a new paradigm in vascular homeostasis.

• Journal of Information Technology Services
• /
• v.18 no.2
• /
• pp.143-159
• /
• 2019

Machine learning (ML) is a method of fitting given data to a mathematical model to derive insights or to predict. In the age of big data, where the amount of available data increases exponentially due to the development of information technology and smart devices, ML shows high prediction performance due to pattern detection without bias. The feature engineering that generates the features that can explain the problem to be solved in the ML process has a great influence on the performance and its importance is continuously emphasized. Despite this importance, however, it is still considered a difficult task as it requires a thorough understanding of the domain characteristics as well as an understanding of source data and the iterative procedure. Therefore, we propose methods to apply deep learning for solving the complexity and difficulty of feature extraction and improving the performance of ML model. Unlike other techniques, the most common reason for the superior performance of deep learning techniques in complex unstructured data processing is that it is possible to extract features from the source data itself. In order to apply these advantages to the business problems, we propose deep learning based methods that can automatically extract features from transaction data or directly predict and classify target variables. In particular, we applied techniques that show high performance in existing text processing based on the structural similarity between transaction data and text data. And we also verified the suitability of each method according to the characteristics of transaction data. Through our study, it is possible not only to search for the possibility of automated feature extraction but also to obtain a benchmark model that shows a certain level of performance before performing the feature extraction task by a human. In addition, it is expected that it will be able to provide guidelines for choosing a suitable deep learning model based on the business problem and the data characteristics.

• The Journal of the Acoustical Society of Korea
• /
• v.38 no.2
• /
• pp.231-239
• /
• 2019

In sonar systems, the passive ranging of a target is an active research area. This paper analyzed the performance of passive ranging based on an array invariant method for different environmental and sonar parameters. The array invariant developed for source range estimation in shallow water. The advantages of this method are that detailed environmental information is not required, and the real-time ranging is possible since the computational burden is very small. Simulation was performed to verify the algorithm. And this method is applied to sea-going experimental data in 2013 near Jinhae port. This study shows the performance of ranging for source orientation, transmission signal length, and length of a receiver through numerical simulation experiments. Also, the results using nested array and uniform line arrays are compared.

• Atmosphere
• /
• v.29 no.1
• /
• pp.1-12
• /
• 2019

For the allergy patient who needs to know the situation about the extent of pollen risk, the National Institute of Meteorological Sciences developed a pollen forecasting system based on the Community Multiscale Air Quality Modeling (CMAQ). In the old system, pollen emission from the oak was estimated just based on the airborne concentration and meteorology factors, resulted in high uncertainty. For improving the quality of current pollen forecasting system, therefore the estimation of pollen emission is now corrected based on the observation of pollen emission at the oak forest to better reflect the real emission pattern. In this study, the performance of the previous (NIMS2014) and current (NIMS2016) model system was compared using observed oak pollen concentration. Daily pollen concentrations and emissions were simulated in pollen season 2016 and accuracy of onset and end of pollen season were evaluated. In the NIMS2014 model, pollen season was longer than actual pollen season; The simulated pollen season started 6 days earlier and finished 13.25 days later than the actual pollen season. The NIMS2016 model, however, the simulated pollen season started only 1.83 days later, and finished 0.25 days later than the actual pollen season, showing the improvement to predict the temporal range of pollen events. Also, the NIMS2016 model shows better performance for the prediction of pollen concentration, while there is a still large uncertainty to capture the maximum pollen concentration at the target site. Continuous efforts to correct these problems will be required in the future.

• BMB Reports
• /
• v.54 no.10
• /
• pp.497-504
• /
• 2021

EGR1 (early growth response 1) is dysregulated in many cancers and exhibits both tumor suppressor and promoter activities, making it an appealing target for cancer therapy. Here, we used a systematic multi-omics analysis to review the expression of EGR1 and its role in regulating clinical outcomes in breast cancer (BC). EGR1 expression, its promoter methylation, and protein expression pattern were assessed using various publicly available tools. COSMIC-based somatic mutations and cBioPortal-based copy number alterations were analyzed, and the prognostic roles of EGR1 in BC were determined using Prognoscan and Kaplan-Meier Plotter. We also used bc-GenEx-Miner to investigate the EGR1 co-expression profile. EGR1 was more often downregulated in BC tissues than in normal breast tissue, and its knockdown was positively correlated with poor survival. Low EGR1 expression levels were also associated with increased risk of ER+, PR+, and HER2- BCs. High positive correlations were observed among EGR1, DUSP1, FOS, FOSB, CYR61, and JUN mRNA expression in BC tissue. This systematic review suggested that EGR1 expression may serve as a prognostic marker for BC patients and that clinicopathological parameters influence its prognostic utility. In addition to EGR1, DUSP1, FOS, FOSB, CYR61, and JUN can jointly be considered prognostic indicators for BC.

• Korean Journal of Agricultural Science
• /
• v.48 no.3
• /
• pp.643-654
• /
• 2021

Phytophthora capsici is one of the most destructive hemibiotrophic pathogens; it can cause blight in chili peppers, and secrete various effector proteins to infect the plants. These effectors contain an N-terminal conserved RXLR motif. Here, we generated full-length RXLR effector coding genes using primer pairs, and cloned them into the pGR106 vector for in planta expression. Two of these genes, PcREK6 and PcREK41 (P. capsici RXLR effector from the Korea isolate), were further characterized. PcREK6 and PcREK41 genes showed that they encode effector proteins with a general modular structure, including the N-terminal conserved RXLR-DEER motif and signal peptide sequences. PcREK6 and PcREK41 expressions were strongly induced when the chili pepper plants (Capsicum annuum) were challenged with P. capsici. These results provide molecular evidence to elucidate the virulence or avirulence factors in chili pepper. Our results also showed that two effectors induce hypersensitive response (HR) cell death when expressed in chili leaves. Cell death suppression assays in Nicotiana benthamiana revealed that most effectors could not suppress programmed cell death (PCD) triggered by Bcl-associated X (BAX) or Phytophthora infestans elicitin (INF1). However, PcREK6 fully suppressed PCD triggered by BAX, while PcREK41 partially suppressed PCD triggered by INF1 elicitin. These results suggest that PcREK effectors from P. capsici interact with putative resistance (R) proteins in planta, and different effectors may target different pathways in a plant cell to suppress pattern-triggered immunity (PTI) or effector-triggered immunity (ETI).

• Structural Engineering and Mechanics
• /
• v.78 no.1
• /
• pp.53-66
• /
• 2021

The determination of the damage index to reveal the performance level of a structure can constitute the seismic risk generalization approach based on the parametric analysis. This study implemented this concept to one kind of civil engineering structure that is the concrete gravity dam. Different cases of the structure exhibit their individual responses, which constitute different considerations. Therefore, this approach allows the parametric study of concrete as well as soil for evaluating the seismic nature in the generalized case. To ensure that the target algorithm applicable to most of the concrete gravity dams, a very simple procedure has been considered. In order to develop a correlated algorithm (by response surface methodology; RSM) between the ground motion and the structural property, randomized sampling was adopted through a stochastic method called half-fractional central composite design. The responses in the case of fluid-foundation-dam interaction (FFDI) make it more reliable by introducing the foundation as being bounded by infinite elements. To evaluate the seismic generalization of FFDI models, incremental dynamic analysis (IDA) was carried out under the impacts of various earthquake records, which have been selected from the Pacific Earthquake Engineering Research Center data. Here, the displacement-based damage indexed fragility curves have been generated to show the variation in the seismic pattern of the dam. The responses to the sensitivity analysis of the various parameters presented here are the most effective controlling factors for the concrete gravity dam. Finally, to establish the accuracy of the proposed approach, reliable verification was adopted in this study.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.22 no.3
• /
• pp.770-776
• /
• 2021

Positioning systems have been actively researched and developed over the past few years and have been used in many applications. This paper presents a method to determine a location in a large space using a sensor system consisting of an accelerometer and a single-axis gyroscope. In particular, to consider usability, a sensor device was loosely worn on the waist so that the experimental data could be used in practical applications. Based on the experimental results of circular tracks with radiuses of 1m and 3m, in this paper, an algorithm using the threshold of rotation angle was proposed and applied to the experimental results. A tracking experiment was performed on the grid-pattern track model. For raw sensor data, the average deviation between the final tracking point and the target point was approximately 15.2 m, which could be reduced to approximately 4.0 m using an algorithm applying the rotation angle threshold.