최근 기후변화 등으로 인한 꿀벌의 폐사가 증가하고 있으나 관련 데이터가 부족하여 이에 대한 연구가 어려움 을 겪고 있어 학습용 인공지능 데이터를 구축하여 양봉 산업 발전에 기여하고자 한다. 학습용 데이터로 생애주기 별 5단계(알, 애벌레, 번데기, 숫벌, 여왕벌), 종봉별 4가지(이탈리안, 카니올란, 한봉, 호박벌), 발생질병 1종(백묵 병) 총 10가지 클래스를 데이터 수집장소 6곳(장성, 포천, 칠곡, 완주, 의령, 장흥)에서 학습용 데이터를 274,206장 구축하였다. 수집된 데이터는 원시데이터, 원천데이터 가공, 라벨링 데이터 결합, 가공데이터 검수 등을 통해 만들어졌으며 관측지에서 온습도, CO, CH4, NH3 등 환경데이터를 200,000건 확보하여 데이터 라벨링을 수행하 였다. 데이터는 AI Hub(www.aihub.or.kr)에서 다운받을 수 있다. 확보된 데이터는 꿀벌의 생애 단계별, 종별, 건강 상태별 이미지 데이터로 구성되어 있어 양봉 관리 자동화, 꿀벌 질병 예측, 양봉 기술 개발 및 연구 등 다양한 분야에 활용될 수 있을 것으로 예상된다.

식용곤충은 미래식량 자원으로써 우수한 가치를 지니고 있어 해외에서는 사육자동화, IoT 및 AI 기술적용, 수직재배시스템 구축 등 많은 연구가 진행되고 있지만 국내에서는 대규모 사육농가나 곤충스마트팜 기술개발 이 부족하여 이를 위한 AI/빅데이터 인프라 구축이 시급한 실정이다. 학습용 인공지능 데이터는 식용곤충으로 활용되고 있는 장수풍뎅이, 흰점박이꽃무지, 갈색거저리, 백강잠, 메뚜기, 풀무치의 생애 주기별 총 6종의 RGB 사진데이터와 분광이미지 데이터 408,000장을 구축하였으며 온도, 습도, CO,, 암모니아, 조도, 수분 등 환경 데이 터 200,000세트를 수집하였다. 수집된 데이터는 원시데이터 수집, 원천데이터 가공, 라벨링 데이터 결합, 가공데 이터 검수 등을 통해 만들어졌으며 관련 데이터는 AI Hub(www.aihub.or.kr)에서 다운받을 수 있다. 확보된 식용곤 충 6종의 데이터는 곤충 종별 성장단계, 환경 변수에 따른 최적의 사육환경 조성, 생산시기 예측, 스마트대량사육 시스템 개발, 제품 가공시 추적이력제 도입, 식용곤충 스마트팜 기술 개발 및 연구 등 다양한 분야에 활용될 수 있을 것으로 예상된다.

Bangladeshi medicinal plants (BMP) have a history of traditional use in treating chronic inflammatory diseases, but a BMP bark’s antioxidant and anti-inflammatory effects remain largely unexplored. This study assessed methanolic extracts’ antioxidant and anti-inflammatory properties from the bark of 15 medicinal plant species native to Bangladesh. The methanol extracts of BMP bark were evaluated for their total antioxidant activity and ability to counteract inflammation induced by lipopolysaccharide (LPS) in RAW 264.7 macrophages. Among the 15 bark extracts from BMP, Albizia odoratissima (A. odoratissima), Engelhardia spicata (E. spicata), and Shorea robusta (S. robusta) showed the highest total phenolic contents and total antioxidant capacity by effectively scavenging free radicals. In particular, these three bark extracts significantly reduced the mRNA expression of LPS-induced inflammatory cytokines and enzymes inducible by inflammation in macrophages. Also, the mRNA expression of NADPH oxidase 2 was significantly suppressed by the three bark extracts in LPS-induced RAW 264.7 macrophages. These results suggest that out of the 15 bark extracts obtained from medicinal plants in Bangladesh, the extracts from A. odoratissima, E. spicata, and S. robusta exhibit substantial total antioxidant capacity by efficiently scavenging free radicals and also inhibit LPS-induced inflammation in macrophages.

The morphological features of germling cells were examined to identify an unspecified resting cyst (described as Cochlodinium cf. polykrikoides-like resting cyst) in the Korean coastal area. LSU rRNA gene sequences were also obtained from a strain established from the germling cells. The resting cysts isolated from Korean coastal sediment were characterized as being brown in color, having a large dark-red body, and fibrous lobed ornaments. The germling cells were ellipsoidal with an irregular outline and had an open comma-shaped ASC (apical structure complex), a wide and deep cingulum, and a deep sulcus. These morphological features were consistent with those of previously described harmful dinoflagellate Pseudocochlodinium profundisulcus. The molecular phylogeny revealed that the germling cells and P. profundisulcus were conspecific. Based on these morphological and phylogenetic data, this study documents the occurrence of P. profundisulcus in a Korean coastal area for the first time.

It has been known that as oxide layer (ZrO2) forms on the nuclear fuel cladding during irradiation in nuclear power plants, the corrosion kinetics are influenced by various parameters such as chemical environments. One of those environments, crud deposition driven by coolant chemistry has an adverse effect on the formation of oxide (ZrO2) and leads to increase thickness of the layer. In this study, crud formation was performed through loop experiment equipment on the surface of intentionally-made oxide layer (ZrO2) on cladding tubes and then the composition and characteristics of cruds were examined for the investigation of nuclear power plant environment. As a result, various cruds in composition and microstructure were formed depending on the exquisite methods and conditions such as metal ion concentration.

This study evaluated a potential sterilization process that uses calcium hypochlorite (Ca(ClO)2) as a disinfectant and hydrogen peroxide (H2O2) as a neutralizing agent for monoculture processes of microalgae (Nannochloropsis oculata). The results showed that no contaminants (prokaryote) were present when the Ca(ClO)2 concentration was greater than 0.010%. The use of an equivalent amount of H2O2 completely neutralized Ca(ClO)2 and had an additional bactericidal effect because of the formation of singlet oxygen. No substantial difference was observed in the biomass accumulation and chlorophyll contents compared to those in cultures sterilized using conventional physical methods such as autoclaving. Therefore, chemical sterilization using Ca(ClO)2 and H2O2 has an excellent economic advantage, and we expect the proposed ecofriendly chemical sterilization method to become a critical culture technology for microalgae-related industrialization.

Background: A breast cancer is the second leading cause of cancer death in women worldwide and among different types of breast cancers, triple-negative breast cancer (TNBC) has a poor prognosis. Methods: We investigated the potential of ginsenoside compound K (CK), an active ingredient in the bio-transformed ginsenoside, to be used as a therapeutic ingredient by examining the effects of CK on cell proliferation, apoptosis, and cancer-related gene expressions in breast cancer cells. Results: From the results of treating MCF-7, an ER and PR-positive breast cancer cells, and MDA-MB-231 (TNBC) with CK at a concentration of 0-100 μM, the half maximal inhibitory concentration (IC50) values for each cell were 52.17 μM and 29.88 μM, respectively. And also, it was confirmed that cell migration was inhibited above the IC50 concentration. In addition, fluorescence analysis of Apoptosis/Necrosis showed that CK induced apoptosis rather than necrosis of breast cancer cells. Through qPCR, it was confirmed that the expression of genes related to apoptosis and cell cycle arrest was increased in CK-treated breast cancer cells, and it acted more effectively on TNBC. However, the expression of genes related to tumor invasion and metastasis is also increased, so it is necessary to consider the timing of application of CK as a potential therapeutic anticancer compound. Conclusions: CK showed a stronger inhibitory effect in TNBC with poor prognosis but considering the high tumor invasion and metastasis-related gene expression, the timing of application of CK should be considered.

Background: This study has mainly focused on finding pharmacological effects of ginsenosides that can reduce the unwanted side effects of the cytotoxic anticancer drugs and are highly effective on prostate cancer, colorectal cancer, liver cancer, hormone-dependent breast cancer, triple-negative breast cancer, and brain cancer (neuroblastoma). Methods: Minor and rare ginsenosides (GS) of Rh2 which have a high absorption ability and excellent pharmacological actions were treated with the 6 different types of cancer cell lines and their anticancer activities were investigated by analyzing gene expressions associated with various cancers through qPCR and other relevant methods. Results: In cancer cells exposed to Rh2, cell viability and cell migration were reduced, and apoptosis was induced. Each cancer cell was divided into three groups according to the cell proliferation response by Rh2; 1) A group in which the cell viability decreases inversely to an increase in Rh2 treatment concentration; 2) A group in which the cell viability rapidly decreases in Rh2 treatment above a certain level of concentration; 3) A group in which the cell viability was not suppressed below 20-30% even with 100 μL of Rh2, the highest concentration used in this study. Conclusions: It was shown that Rh2 has a significant effect on inhibiting the proliferation of prostate cancer cells and hormone-dependent breast cancer cells.

This study aimed to establish the optimal conditions for producing gluten-free noodles by varying the amount of pregelatinized rice flour added to the regular rice flour and investigating their quality characteristics. With an increase in the amount of added pregelatinized rice flour, the brightness of the noodles decreased, and the color became more yellow both before and after cooking. Adding pregelatinized rice flour to the noodles also increased hardness, elasticity, chewiness, stickiness, and adhesiveness. The textures of the two groups of samples (PR-10 and PR-15) were similar to that of the control, indicating comparable structural characteristics. Furthermore, the absence of gluten made it inherently challenging to form gluten-free noodles. Still, adding pregelatinized rice flour improved the processability of the dough, leading to better noodle formation. An optimal addition of 15% pregelatinized rice flour was deemed suitable for optimal noodle formation in gluten-free noodles. This study established blending conditions using pregelatinized rice flour to improve the poor processability of gluten-free noodles. The findings are expected to be valuable for the industry’s future development of gluten-free processed food.

The body of knowledge from psychology has been useful to marketing for understanding consumer minds and behaviors (Jia et al., 2018). Daily activities, such as movie watching, grocery shopping, online shopping, drinking coffee (with friends or alone), and making an in-app purchases on social media, all involve consumption which is affected by the perceptions, attitudes, and behaviors of the decision maker (i.e., consumers). But when the ways in which we sense and interact with the world change, how does it shift our ways of communicating with each other and the processes of forming perceptions, attitudes, and behaviors?

To make semiconductor chips, a number of complex semiconductor manufacturing processes are required. Semiconductor chips that have undergone complex processes are subjected to EDS(Electrical Die Sorting) tests to check product quality, and a wafer bin map reflecting the information about the normal and defective chips is created. Defective chips found in the wafer bin map form various patterns, which are called defective patterns, and the defective patterns are a very important clue in determining the cause of defects in the process and design of semiconductors. Therefore, it is desired to automatically and quickly detect defective patterns in the field, and various methods have been proposed to detect defective patterns. Existing methods have considered simple, complex, and new defect patterns, but they had the disadvantage of being unable to provide field engineers the evidence of classification results through deep learning. It is necessary to supplement this and provide detailed information on the size, location, and patterns of the defects. In this paper, we propose an anomaly detection framework that can be explained through FCDD(Fully Convolutional Data Description) trained only with normal data to provide field engineers with details such as detection results of abnormal defect patterns, defect size, and location of defect patterns on wafer bin map. The results are analyzed using open dataset, providing prominent results of the proposed anomaly detection framework.