• Korean Journal of Environmental Biology
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• v.41 no.3
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• pp.325-334
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• 2023

The invasive red swamp crayfish, Procambarus clarkii, is native to south-central United States and northeastern Mexico. Recently, it has been being spreading in the wild in South Korea. However, its primary sources, introduction routes, establishment, and expansion in South Korea remain unclear. Here, we analyzed genetic diversity and population genetic structures of its domestic natural populations during early invasion, commercial stock from local aquaria (a suspected introduction source), and original United States population using mitochondrial COI gene sequences for 267 individuals and eight microsatellite markers for 158 individuals. Natural and commercial populations of P. clarkii showed reduced genetic diversity (e.g., haplotype diversity and allelic richness). The highest genetic diversity was observed in one original source population based on both genetic markers. Despite a large number of individuals in commercial aquaria, we detected remarkably low genetic diversity and only three haplotypes among 226 individuals, suggesting an inbred population likely originating from a small founder group. Additionally, the low genetic diversity in the natural population indicates a small effective population size during early establishment of P. clarkii in South Korea. Interestingly, genetic differentiation between natural populations and the United States population was lower than that between natural populations and aquarium populations. This suggests that various genetic types from the United States likely have entered different domestic aquariums, leading to distinct natural populations through separate pathways. Results of our study will provide an insight on the level of genetic divergence and population differentiation during the initial stage of invasion of non-indigenous species into new environments.

• Economic and Environmental Geology
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• v.45 no.3
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• pp.317-333
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• 2012

The Yeongweol Group is a Lower Paleozoic mixed carbonate-siliciclastic sequence in the Taebaeksan Basin of Korea, and consists of five lithologic formations: Sambangsan, Machari, Wagok, Mungok, and Yeongheung in ascending order. Sequence stratigraphic interpretation of the group indicates that initial flooding in the Yeongweol area of the Taebaeksan Basin resulted in basal siliciclastic-dominated sequences of the Sambangsan Formation during the Middle Cambrian. The accelerated sea-level rise in the late Middle to early Late Cambrian generated a mixed carbonate-siliciclastic slope or deep ramp sequence of shale, grainstone and breccia intercalations, representing the lower part of the Machari Formation. The continued rise of sea level in the Late Cambrian made substantial accommodation space and activated subtidal carbonate factory, forming carbonate-dominated subtidal platform sequence in the middle and upper parts of the Machari Formation. The overlying Wagok Formation might originally be a ramp carbonate sequence of subtidal ribbon carbonates and marls with conglomerates, deposited during the normal rise of relative sea level in the late Late Cambrian. The formation was affected by unstable dolomitization shortly after the deposition during the relative sea-level fall in the latest Cambrian or earliest Ordovician. Subsequently, it was extensively dolomitized under the deep burial diagenetic condition. During the Early Ordovician (Tremadocian), global transgression (viz. Sauk) was continued, and subtidal ramp deposition was sustained in the Yeongweol platform, forming the Mungok Formation. The formation is overlain by the peritidal carbonates of the Yeongheung Formation, and is stacked by cyclic sedimentation during the Early to Middle Ordovician (Arenigian to Caradocian). The lithologic change from subtidal ramp to peritidal facies is preserved at the uppermost part of the Mungok Formation. The transition between Sauk and Tippecanoe sequences is recognized within the middle part of the Yeongheung Formation as a minimum accommodation zone. The global eustatic fall in the earliest Middle Ordovician and the ensuing rise of relative sea level during the Darrwillian to Caradocian produced broadly-prograding peritidal carbonates of shallowing-upward cyclic successions within the Yeongheung Formation. The reconstructed relative sea-level curve of the Yeongweol platform is very similar to that of the Taebaek platform. This reveals that the Yeongweol platform experienced same tectonic movements with the Taebaek platform, and consequently that both platform sequences might be located in a body or somewhere separately in the margin of the North China platform. The significant differences in lithologic and stratigraphic successions imply that the Yeongweol platform was much far from the Taebaek platform and not associated with the Taebaek platform as a single depositional system. The Yeongweol platform was probably located in relatively open shallow marine environments, whereas the Taebaek platform was a part of the restricted embayments. During the late Paleozoic to early Mesozoic amalgamations of the Korean massifs, the Yeongweol platform was probably pushed against the Taebaek platform by the complex movement, forming fragmented platform sequences of the Taebaeksan Basin.

• Economic and Environmental Geology
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• v.35 no.3
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• pp.211-220
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• 2002

The Xiaoxinancha Cu-Au deposit in the Jilin province, located in NNE 800 km of Beijing, is hosted by diorite. The ore mineralization of Xiaoxinancha Cu-Au deposit show a stockwork occurrence that is concentrated on the potassic and phyllic alteration zones. The Xiaoxinancha Cu-Au deposit in the south is being mined with its reserves grading 0.8% Cu, 3.64 g/t Au and 16.8 g/t Ag and in the north, grading 0.63% Cu, 3.80 g/t Au and 6.8 glt Ag. The alteration assemblage occurs as a supergene blanket over deposit. Hydrothermal alteration at the Xiaoxinancha Cu-Au deposit is centered about the stock and was extensively related to the emplacement of the stock. Early hydrothermal alteration was dominantly potassic and followed by propylitic alteration. Chalcocite, often associated with hematite, account for the ore-grade copper, while chalcopyrite, bornite, quartz, epidote, chlorite and calcite constitute the typical gangue assemblage. Other minor opaque phases include pyrite, marcasite, native gold, electrum, hessite, hedleyite, volynskite, galenobismutite, covellite and goethite. Fluid inclusion data indicate that the formation of this porphyry copper deposit is thought to be a result of cooling followed by mixing with dilute and cooler meteoric water with time. In stage II vein, early boiling occurred at 497$^{\circ}$C was succeeded by the occurrence of halite-bearing type III fluid inclusion with homogenization temperature as much as 100$^{\circ}$C lower. The salinities of type 1II fluid inclusion in stage II vein are 54.3 to 66.9 wt.% NaCI + KCI equiv. at 383$^{\circ}$ to 495$^{\circ}$C, indicating the formation depth less than 1 km. Type I cupriferous fluids in stage III vein have the homogenization temperatures and salinity of 168$^{\circ}$ to 365$^{\circ}$C and 1.1 to 9.0 wt.% NaCI equiv. These fluid inclusions in stage III veins were trapped in quartz veins containing highly fractured breccia, indicating the predominance of boiling evidence. This corresponds to hydrostatic pressure of 50 to 80 bars. The $\delta$$^{34}S$ value of sulfide minerals increase slightly with paragenetic time and yield calculated $\delta$$^{34}S_{H2S}$ values of 0.8 to 3.7$\textperthousand$. There is no mineralogical evidence that fugacity of oxygen decreased, and it is thought that the oxygen fugacity of the mineralizing fluids have been buffered through reaction with magnetite. We interpreted the range of the calculated $\delta$$^{34}S_{H2S}$ values for sulfides to represent the incorporation of sulfur from two sources into the Xiaoxinancha Cu-Au hydrothermal fluids: (1) an isotopically light source with a $\delta$$^{34}S$ value of I to 2$\textperthousand$, probably a Mesozoic granitoid related to the ore mineralization. We can infer from the fact that diorite as the host rock in the Xiaoxinancha Cu-Au deposit area intruded plagiogranite; (2) an isotopically heavier source with a $\delta$$^{34}S$ value of > 4.0$\textperthousand$, probably the local porphyry.

• Korean Journal of Food Science and Technology
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• v.39 no.3
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• pp.348-352
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• 2007

Inflammation is a complex process resulting from a variety of mechanisms. Combined inhibition of the activities of enzymes involved in the process may therefore be considered more important in anti-inflammatory property of plant extracts than any single contribution. In this study, the inhibitory effects of the ethanol extracts of thirty plant foods on the activities of secretory phospholipase $A_{2}$ ($sPLA_{2}$), cyclooxygenase-1 (COX-1), cyclooxygenase-2 (COX-2), and 12-lipoxygenase (12-LOX) were examined. Several legumes, mungbean sprout and some leaf vegetables inhibited the activity of $sPLA_2$, upstream enzyme of inflammation pathway. Only soybean sprout and mungbean sprout significantly inhibited 12-LOX activity. Although most of extracts inhibited the activities of both COX-1 and COX-2, water dropwort and amaranth showed selectivity for the inhibition of COX-2 over COX-1. Especially, mungbean showed anti-inflammatory property at both upstream and downstream of inflammation pathway with relatively low $IC_{50}$ values for $sPLA_{2}$ and COX-2 enzymes. Mungbean sprout exhibited inhibitory effects on all enzymes related to early and late inflammation and soybean sprout suppressed 12-LOX and COX-2 simultaneously, although the activities of these plants were showed at relatively high concentration. Therefore, mungbean, mungbean sprout, and soybean sprout appear to exhibit anti-inflammatory effects by combined inhibition of inflammatory enzymes.

• Journal of The Korean Association For Science Education
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• v.42 no.1
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• pp.19-32
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• 2022

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.

• Journal of Intelligence and Information Systems
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• v.27 no.3
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• pp.57-73
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• 2021

Maintenance and prevention of failure through anomaly detection of ICT infrastructure is becoming important. System monitoring data is multidimensional time series data. When we deal with multidimensional time series data, we have difficulty in considering both characteristics of multidimensional data and characteristics of time series data. When dealing with multidimensional data, correlation between variables should be considered. Existing methods such as probability and linear base, distance base, etc. are degraded due to limitations called the curse of dimensions. In addition, time series data is preprocessed by applying sliding window technique and time series decomposition for self-correlation analysis. These techniques are the cause of increasing the dimension of data, so it is necessary to supplement them. The anomaly detection field is an old research field, and statistical methods and regression analysis were used in the early days. Currently, there are active studies to apply machine learning and artificial neural network technology to this field. Statistically based methods are difficult to apply when data is non-homogeneous, and do not detect local outliers well. The regression analysis method compares the predictive value and the actual value after learning the regression formula based on the parametric statistics and it detects abnormality. Anomaly detection using regression analysis has the disadvantage that the performance is lowered when the model is not solid and the noise or outliers of the data are included. There is a restriction that learning data with noise or outliers should be used. The autoencoder using artificial neural networks is learned to output as similar as possible to input data. It has many advantages compared to existing probability and linear model, cluster analysis, and map learning. It can be applied to data that does not satisfy probability distribution or linear assumption. In addition, it is possible to learn non-mapping without label data for teaching. However, there is a limitation of local outlier identification of multidimensional data in anomaly detection, and there is a problem that the dimension of data is greatly increased due to the characteristics of time series data. In this study, we propose a CMAE (Conditional Multimodal Autoencoder) that enhances the performance of anomaly detection by considering local outliers and time series characteristics. First, we applied Multimodal Autoencoder (MAE) to improve the limitations of local outlier identification of multidimensional data. Multimodals are commonly used to learn different types of inputs, such as voice and image. The different modal shares the bottleneck effect of Autoencoder and it learns correlation. In addition, CAE (Conditional Autoencoder) was used to learn the characteristics of time series data effectively without increasing the dimension of data. In general, conditional input mainly uses category variables, but in this study, time was used as a condition to learn periodicity. The CMAE model proposed in this paper was verified by comparing with the Unimodal Autoencoder (UAE) and Multi-modal Autoencoder (MAE). The restoration performance of Autoencoder for 41 variables was confirmed in the proposed model and the comparison model. The restoration performance is different by variables, and the restoration is normally well operated because the loss value is small for Memory, Disk, and Network modals in all three Autoencoder models. The process modal did not show a significant difference in all three models, and the CPU modal showed excellent performance in CMAE. ROC curve was prepared for the evaluation of anomaly detection performance in the proposed model and the comparison model, and AUC, accuracy, precision, recall, and F1-score were compared. In all indicators, the performance was shown in the order of CMAE, MAE, and AE. Especially, the reproduction rate was 0.9828 for CMAE, which can be confirmed to detect almost most of the abnormalities. The accuracy of the model was also improved and 87.12%, and the F1-score was 0.8883, which is considered to be suitable for anomaly detection. In practical aspect, the proposed model has an additional advantage in addition to performance improvement. The use of techniques such as time series decomposition and sliding windows has the disadvantage of managing unnecessary procedures; and their dimensional increase can cause a decrease in the computational speed in inference.The proposed model has characteristics that are easy to apply to practical tasks such as inference speed and model management.