Two tree frogs, Dryophytes suweonensis and Dryophytes japonicus, inhabiting Korea, are morphologically similar and share the same habitats. Therefore, they are identified mainly through their calls, especially for males. Dryophytes suweonensis is registered as an endangered (IUCN: EN grade) and protected species in South Korea. Thus, it is necessary to develop a method to rapidly identify and discriminate the two species and establish efficient protection and restoration plans. We identified significant genetic variation between them by sequencing a maternallyinherited mitochondrial 12S ribosomal DNA region. Based on the sequence data, we designed a pair of primers containing 7 bp differences for high resolution melting (HRM) analysis to rapidly and accurately characterize their genotypes. The HRM analysis using genomic DNA showed that the melting peak for D. suweonensis was 76.4±0.06°C, whereas that of D. japonicus was 75.0±0.05°C. The differential melt curve plot further showed a distinct difference between them. We also carried out a pilot test for the application of HRM analysis based on immersing D. suweonensis in distilled water for 30 min to generate artificial environmental DNA (eDNA). The results showed 1.10-1.31°C differences in the melting peaks between the two tree frog samples. Therefore, this HRM analysis is rapid and accurate in identifying two tree frogs not only using their genomic DNA but also using highly non-invasive eDNA.

We analyzed the hair microstructure of Korean small terrestrial mammals, such as Rodentia and Lagomorpha, to classify the characteristics of hair morphology. Micromys minutus showed a unicellular irregular type of medulla structures; on the other hand, the other mammals showed multicellular structures. Regarding the cuticular scale structures, the Rodentia species exhibited a narrow and broad diamond petal type, while the Lagomorpha species exhibited an elongated petal type. Interestingly, the hair cross-sections showed quite unique characteristics. We constructed hair identification keys to distinguish species with a single hair. The dichotomous key of Rodentia and Lagomorpha can be used for their behavioral ecology and dietary analysis of upper predators to serve as the basis for ecological research.

Human intestinal flora is very diverse; with lactic acid bacteria (LAB) existing as part of the most vital gut microbes that improve host health. The application of LAB as a whole organism or its metabolite in the case of probiotic and bacteriocin respectively is extensive. Thus, the need to always bio-prospect for newer strains of LAB is essential. This study focused on isolating LAB from kunun-zaki and kindirmo, a fermented non-alcoholic beverage of non-dairy and dairy sources respectively, explored their physiological and biochemical properties, antibiotics sensitivity pattern and identified based on their 16S rRNA sequencing. A total of eighty isolates were selected sixty-six from kunun-zaki and fourteen from kindirmo in which 93.7% were bacilli and 6.3% were spherical in shape having 68.75% and 30% homofermentative and heterofermentative pathway respectively. All isolates have the ability to utilize glucose to produce lactic acid while their tolerance to pH 3 and salt concentration at 2%, 4% and 6.5% varied widely. Thirty-four isolates based on their physiological and biochemical properties were selected for molecular identification to ascertain their genera and species. Limosilactobacillus fermentum (68%); Lactiplantibacillus plantarum (6%) and Weissella confusa (3%) were confirmed species isolated. Thus, it was concluded that traditional fermented foods such as kunun-zaki and kindirmo are a good source to bio-prospect for LAB for product development, starter culture and probiotic study.

Artificial intelligence is driving the Fourth Industrial Revolution and is in the spotlight as a general-purpose technology. As the data collection from the battlefield increases rapidly, the need to us artificial intelligence is increasing in the military, but it is still in its early stages. In order to identify maritime targets, Republic of Korea navy acquires images by ISAR(Inverse Synthetic Aperture Radar) of maritime patrol aircraft, and humans make out them. The radar image is displayed by synthesizing signals reflected from the target after radiating radar waves. In addition, day/night and all-weather observations are possible. In this study, an artificial intelligence is used to identify maritime targets based on radar images. Data of radar images of 24 maritime targets in Republic of Korea and North Korea acquired by ISAR were pre-processed, and an artificial intelligence algorithm( ResNet-50) was applied. The accuracy of maritime targets identification showed about 99%. Out of the 81 warship types, 75 types took less than 5 seconds, and 6 types took 15 to 163 seconds.

본 연구는 의료분야에서 정확한 환자 확인(patient identification)을 위한 의료생체인식기술(medical biometrics)을 소개하고 자 한다. 첫째, 생체인식기술(biometrics)에 대한 정의, 분류 및 종류와 같은 기본 정보다. 둘째, 생체신호 (biological signal)와 의료영상(medical imaging)을 활용한 의료생체인식기술의 종류와 최근 연구에 관한 정보를 기술했 다. 마지막으로 의료 환경에서 적용되는 생체인식기술의 종류와 사례와 함께 의료 환경의 현주소를 언급했다. 환자확인이 라는 궁극적인 목적을 가진 의료생체인식기술은 의료 현장에 점진적으로 도입되리라 생각한다. 본 연구는 본 연구가 정확 한 환자확인을 위한 의료생체인식기술을 이해하고 연구방향에 도움이 되는 기초 자료로 활용될 것으로 사료된다.

The rate of industrial accident reduction is slowing down as the attention of the Ministry of Employment and Labor and related agencies on risk assessment systems decreased. this paper focuses on weakness of legal system for the risk assessment in recent years. A survey was conducted to identify the status and condition of the risk assessment system applying on small and medium-sized manufacturing companies. A set of questionnaires is designed to reflect various perspectives of the companies regarding the problems and solutions of the system. The results refer that differentiated instructions and support systems in response to the actual conditions of the companies are mandatory to reinforce the efficiency of risk assessment system.

Various models have been proposed to describe the swelling behavior of buffer in high level waster repository. One of the most notable models, the Barcelona Basic Model (BBM), is a mechanical model that simulates the behavior of unsaturated ground and is widely applied to soils that undergo large expansion due to water. Among the BBM parameters of Kyeongju bentonite, which is found in Korea, there are no experimental data for parameters that describe the unsaturated state. Such hydromechanical properties should be characterized through experimental programs. However, such experiments are highly complicated and require long periods of time to produce an unsaturated state through different methods according to the suction range. Although there are several studies in which geotechnical parameters were obtained through a back analysis instead of direct experiments, few studies have employed machine learning methods for the identification of geotechnical parameters. In this study, instead of direct experiments, the results of a relatively simple swelling pressure experiment was compared to the numerical analysis results to propose a method of determining some of BBM parameters. Influential factors were identified by a sensitivity analysis and the values of the factors were estimated using an artificial neural network and optimization method. The obtained parameters were applied to the numerical model to estimate the swelling pressure growth, which was subsequently compared to the experimental value. As a result, it was found that there was no significant difference between the two swelling values.

The use of heat exchangers in various applications such as chemical, air conditioning systems, fuel processing, and power industries is increasing. In order to improve the performance of the heat exchanger, the problem of bonding quality of the copper tube, which is a major member, is emerging. However, since the copper tube is in the form of a pipe, it is difficult to identify internal defects with external factors. In this study, a thermal imaging camera was used to develop and verify an algorithm for detecting defects in the brazing part, and in the process, the brazing performance characteristics were analyzed according to the electrode position, and finally, a learning model was developed and performance evaluation was performed. It was confirmed that the method of supplying heat to the base material and melting the filler metal through the heat transfer effect is more effective than supplying heat input to the filler metal in the bonding process of copper tubes through high-frequency induction heating brazing. Thermal image data was used to develop a defect discrimination model, and 80% of training data and 20% of test data were selected, and a neural network-based single-layer copper tube brazing defect discrimination model was developed through k-Flod cross-validation., the prediction accuracy of 95.2% was confirmed as a result of the error matrix analysis.

Known for its effectiveness in weight loss and diabetes prevention, Gymnema sylvestre products can be found in the US, Japanese, and Indian markets. However, the recommended dosage or safety of these products has not yet been proven. Therefore, development of an analytical method for detecting the content of Gymnema sylvestre in food products is required. Accordingly, this study proposes an analysis method that can examine Gymnema sylvestre in food using LC-ESI-MS/MS and KASP (Kompetitive Allele-Specific PCR) markers. In LC-ESI-MS/MS, a simultaneous analysis method for gymnemic acid and deacylgymnemic acid was optimized using negative ionization mode, and its validation test was completed for solid and liquid samples. In addition, KASP markers were prepared by finding the specific SNP of G. sylvestre in ITS2 and matK through DNA barcodes. The two KASP markers returned positive FAM fluorescence result when combined with G. sylvestre, and this aspect was confirmed in raw G. sylvestre as well. The applicability of the method was tested on 21 different food and healthy functional products containing G. sylvestre purchased on the internet. As a result, although there was a difference in the ratios of gymnemic acid and deacylgymnemic acid in LC-ESI-MS/MS, the index component was detected in all 21 products samples. In the KASP analysis, 9 products returned positive FAM result, and the rest of the products were found to be containing G. sylvestre extract. This study is the first study to use the dual system of LC-ESI-MS/MS and KASP for the analysis of G. sylvestre. The study has confirmed that these two methods are applicable to the examine G. sylvestre content in food products.

To date, the development of anticancer drugs has been conducted using two-dimensional (2D) cell culture systems. However, since cancer cells in the body are generated and developed in three-dimensional (3D) microenvironments, the use of 2D anticancer drug screening can make it difficult to accurately evaluate the anticancer effects of drug candidates. Therefore, as a step towards developing a cancer cellfriendly 3D microenvironment based on a combination of vinylsulfone-functionalized polyethylene glycol (PEG-VS) with dicysteine-containing crosslinker peptides with an intervening matrix metalloproteinase (MMP)-specific cleavage site, the types of MMPs secreted from human hepatocarcinoma HepG2 cells, a representative cancer cell, were analyzed transcriptionally and translationally. MMP3 was confirmed to be the most highly expressed protease secreted by HepG2 cells. This knowledge will be important in the design of a crosslinker necessary for the construction of PEG-based hydrogels customized for the 3D culture of HepG2 cells.

The prevalence of cancer in companion dogs is growing nowadays with the increasing worldwide population of domestic dogs. Since there is a less established standard of care in veterinary medicine, investigational treatments, such as the development of biomarkers can be considered as a therapeutic intervention for early diagnosis. Despite the enormous efforts that have been invested in the search of biomarkers, still, there is a need for easy detection of significant biological markers for predicting canine cancers at an early stage. In this study, we have analyzed the expression pattern of previously reported 46 canine cancer-associated candidate genes in blood specimens using real-time qPCR. We hypothesized that analysis of gene expression in blood would provide preliminary evidence of local or systemic immunogenic response which further contribute to the easy and early diagnosis of canine cancer from blood specimen as an analytical tool. The datasets included a total of 22 blood samples collected from different breeds of dogs diagnosed with cancer and five from healthy normal dogs. RT-qPCR analysis was performed by employing the SYBR Green PCR mix to assess the expression of these 46 genes in a total of 27 samples. From our result, a total of nine genes (ROS1, C1QA, CD48, IL1b, TLR2, IL2R, CHI3L1, CTSS, and TLR7) were found to be significantly up-regulated (p < 0.05 and p < 0.01) in the cancer samples compared to non-cancer samples. The relative expression level of ROS1, C1QA, CD48, IL1b, TLR2, IL2R, CHI3L1, CTSS, and TLR7 genes was 5.74, 4.78, 3.94, 2.94, 2.57, 2.53, 2.50, 2.04, and 2.57, respectively, in cancer samples compared to non-cancer samples. Thus, our results reveal several highly expressed cancer genes that can be therapeutic target genes for further testing in canine cancers.

본 연구에서는 차량-교량 상호작용 시스템의 고유진동수 변화를 분석하였다. 차량이 주행하는 교량의 동특성은 차량의 질량 및 진 동을 무시하지 않는 경우 상호작용을 반영해야 하는데, 이때 시스템은 시간가변적이므로 고유진동수 또한 시간가변적인 특성을 보인 다. 따라서 본 연구에서는 차량과 교량을 각각 2자유도를 갖는 시스템으로 모델링하여 차량의 위치와 질량비 그리고 시스템 강성비에 따른 시간가변적 고유진동수를 산출하였다. 분석 결과 일반적으로 초기 고유진동수가 작은 시스템은 상호작용으로 인하여 증폭비가 낮아지는 추세를 보이나 상호작용이 발생할 경우 증폭비는 분기점을 보이며 비선형적 추세를 보이는것을 알 수 있다. 따라서 상호작 용이 발생하는 시스템차수에 대한 이해가 필요함을 알 수 있다.

본 연구에서는 가래떡에 오염된 곰팡이를 분리 동정한 후 곰팡이독소 생산 가능성을 조사하여 식품 이물 중 곰 팡이에 대한 위험성을 분석하였다. 실험에 사용된 가래떡 은 전라남도 소재 떡 제조업체에 곰팡이로 추정되는 이물 이 발견되어 반품된 제품을 사용하였다. 곰팡이 이물을 채 취한 후 Potato dextrose agar, Malt extract agar, Czapek yeast extract agar에 접종하고 25oC에서 7일간 배양하여 순수 분리 결과를 판단하였다. 순수 분리가 확인된 집락 에 대해 광학현미경으로 포자의 미세구조를 관찰하여 형 태학적으로 동정하였다. 유전학적 동정은 ITS primer를 이 용하여 증폭된 PCR 산물의 유전자 염기서열을 분석하였 다. Colony-1과 2는 각각 배지에서 동일한 성상을 나타내 어 순수분리 되었음을 확인하였다. Colony-1은 출아세포 가 관찰되어 효모로 판정하였다. Colony-2는 방추형의 분 생자가 관찰되어 Fusarium 속 곰팡이로 판정하였다. 유전 자 염기서열 분석 결과 Fusarium 속 곰팡이가 총 76건으 로 나타났으며, 그중 Fusarium solani가 53건으로 가장 높 게 나타났다. 형태학적 동정 결과와 유전학적 동정 결과 를 바탕으로 Colony-2는 Fusarium spp.로 동정되었고 그 중 Fusarium solani로 추정되었다. Fusarium 속 곰팡이는 Nivalenol, Zearalenone, Fumonisin 등의 곰팡이독소를 생 산하여 구토, 설사, 암 등을 유발한다. 이러한 결과를 종 합해 볼 때 가래떡에서 분리된 Fusarium 속 곰팡이에 의 한 곰팡이독소 생산 가능성은 상존하는 것으로 판단되었 다. 따라서 곰팡이 이물이 보고되면 곰팡이를 분리 동정 하여 곰팡이독소를 생산할 수 있는 균종인지 판단하고, 그 결과에 따라 행정조치를 강화하여야 할 것으로 판단된다.

Recently, the importance of preventive maintenance has been emerging since failures in a complex system are automatically detected due to the development of artificial intelligence techniques and sensor technology. Therefore, prognostic and health management (PHM) is being actively studied, and prediction of the remaining useful life (RUL) of the system is being one of the most important tasks. A lot of researches has been conducted to predict the RUL. Deep learning models have been developed to improve prediction performance, but studies on identifying the importance of features are not carried out. It is very meaningful to extract and interpret features that affect failures while improving the predictive accuracy of RUL is important. In this paper, a total of six popular deep learning models were employed to predict the RUL, and identified important variables for each model through SHAP (Shapley Additive explanations) that one of the explainable artificial intelligence (XAI). Moreover, the fluctuations and trends of prediction performance according to the number of variables were identified. This paper can suggest the possibility of explainability of various deep learning models, and the application of XAI can be demonstrated. Also, through this proposed method, it is expected that the possibility of utilizing SHAP as a feature selection method.