복어는 동아시아 요리의 고급 원료로 상업적 가치가 높 은 수산자원이나, 야생 복어의 테트로도톡신은 치명적인 식중독 사건을 꾸준히 유발하고 있다. 자주복은 한국, 일 본, 중국에서 인기 있는 복어 종으로, 테트로도톡신이 없 는 복어 생산을 위해 양식되는 주된 어종이다. 따라서 양 식 자주복과 자연산 자주복의 구별은 식품 안전과 규제측면에서 매우 중요하다. 본 연구에서는 국내 온라인 및 오프라인 시장에서 판매되는 100개의 자주복 제품을 대상 으로 ‘양식 및 자연산’ 여부를 PCR 기반 방법을 이용하 여 확인하였으며, PCR 결과를 제품의 표시사항 정보와 비 교하였다. PCR 분석에는 자연산 자주복과 양식 자주복의 유전적 다양성 차이를 보이는 6개의 마커를 이용하였다. PCR 분석 결과 모든 양식 자주복 제품에서는 6개 마커에 서 모두 완전한 증폭 패턴을 보였으나, 자연산 자주복 제 품에서는 0 - 5개 마커에서 만 무작위 증폭 패턴을 나타냈 다. 따라서 6개 유전 마커의 증폭 패턴을 이용한 분석법 은 향후 자주복 제품의 허위표시 모니터링 및 테트로도톡 신 유무의 신속 검사에 널리 활용될 수 있을 것이다. 또 한 본 연구 결과는 현행 복어 종 판별을 보완할 수 있는 기초자료를 제공해 줄 수 있다.

As the demand for sustainable hydrogen (H₂) production grows, catalytic decomposition of methane (CDM) has emerged as a CO2- free pathway for H2 generation, producing valuable multi-walled carbon nanotubes (MWCNTs) as byproducts. This study examines the role of fuel type in shaping the properties and performance of NiOx/AlOx catalysts synthesized via solution combustion synthesis (SCS). Catalysts prepared with citric acid, urea, hexamethylenetetramine (HMTA), and glycine exhibited varying NiO nanoparticle (NP) sizes and dispersions. Among them, the HMTA catalyst achieved the highest Ni dispersion (~ 3.2%) and specific surface area (21.6 m2/ gcat), attributed to vigorous combustion facilitated by its high pH and amino-group-based fuel. Catalytic tests showed comparable activation energy (55.7–59.7 kJ/mol) across all catalysts, indicating similar active site formation mechanisms. However, the HMTA catalyst demonstrated superior CH4 conversion (~ 68%) and stability, maintaining performance for over 160 min under undiluted CH₄, while others deactivated rapidly. MWCNT characterization revealed consistent structural properties, such as graphitization degree and electrical conductivity, across all catalysts, emphasizing that fuel type influenced stability rather than MWCNT quality. H2 temperature-programmed reduction ( H2-TPR) analysis identified moderate metal-support interaction (MSI) in the HMTA catalyst as a key factor for optimizing stability and active site utilization. These findings underscore the importance of fuel selection in SCS to control MSIs and dispersion, offering a strategy to enhance catalytic performance in CDM and other thermocatalytic applications.

Si-based anodes are promising alternatives to graphite owing to their high capacities. However, their practical application is hindered by severe volume expansion during cycling. Herein, we propose employing a carbon support to address this challenge and utilize Si-based anode materials for lithium-ion batteries (LIBs). Specifically, carbon supports with various pore structures were prepared through KOH and NaOH activation of the pitch. In addition, Si was deposited into the carbon support pores via SiH4 chemical vapor deposition (CVD), and to enhance the conductivity and mechanical stability, a carbon coating was applied via CH4 CVD. The electrochemical performance of the C/Si/C composites was assessed, providing insights into their capacity retention rates, cycling stability, rate capability, and lithium-ion diffusion coefficients. Notably, the macrostructure of the carbon support differed significantly depending on the activation agent used. More importantly, the macrostructure of the carbon support significantly affected the Si deposition behavior and enhanced the stability by mitigating the volume expansion of the Si particles. This study elucidated the crucial role of the macrostructure of carbon supports in optimizing Si-based anode materials for LIBs, providing valuable guidance for the design and development of high-performance energy-storage systems.

Background: This study explores the potential of discarded male layer embryos as a sustainable and non-GMO cell source for cultivated chicken meat production. The research aims to identify efficient methods for isolating muscle progenitor cells (MPCs) with high proliferative potential by conducting transcriptome analysis on thigh muscle tissues from both male and female chick embryos. Methods: Transcriptome analysis was performed on the thigh muscle tissues of male and female chick embryos, aged 12-13 days, (n = 4 each), to investigate the gene expression profiles and identify strategies for efficiently isolating MPCs. This approach aims to pinpoint techniques that would allow for the selection of MPCs with optimal growth and proliferation capabilities. Results: Using heatmap, hierarchical clustering, and multidimensional scaling (MDS), we found no significant sex-based differences in gene expression, except for the overexpression of the female-specific gene LIPBLL. The expression of muscle stem cell factors, including PAX3, PAX7, and other myogenic regulatory genes, showed no significant variation. However, to recover MPC-rich cells isolated from male thigh muscle, we found that by the pre-plating 7 stage, myogenesis-related genes, MYHs and MUSTN1 were minimally expressed, while the cell cycle arrest gene CDKN1A sharply increased. Conclusions: Our findings suggest that simple cell isolation directly from tissue is a more scalable and efficient approach for cultivated meat production, compared to labor-intensive pre-plating methods, making it a viable solution for sustainable research and resource recycling.

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.

The clearwing moth, Synanthedon bicingulata (Staudinger, 1887), is a pest that infests various species of cherry trees. However, genetic information regarding the genus Synanthedon including S. bicingulata, is limited. In this study, we sequenced a complete mitochondrial genome (mitogenome) of the species. The 16,255 bp of S. bicingulata mitogenome differs from the typical gene arrangement formed in Lepidoptera: trnQ-trnS2-trnM-trnI arrangement between the A+T-rich region and the ND2 junction. Moreover, the genome has untranslated repetitive sequences in the intergenic space between lrRNA and trnV, as well as the CGA start codon in COI and the TTG start codon in ATP8. Similar observations are noted in species belonging to the tribe Synanthedonini within the genus Synanthedon.

The complexation of silicon with carbon materials is considered an effective method for using silicon as an anode material for lithium-ion batteries. In the present study, carbon frameworks with a 3D porous structure were fabricated using metal–organic frameworks (MOFs), which have been drawing significant attention as a promising material in a wide range of applications. Subsequently, the fabricated carbon frameworks were subjected to CVD to obtain silicon-carbon complexes. These siliconcarbon complexes with a 3D porous structure exhibited excellent rate capability because they provided sufficient paths for Li-ion diffusion while facilitating contact with the electrolyte. In addition, unoccupied space within the silicon complex, combined with the stable structure of the carbon framework, allowed the volume expansion of silicon and the resultant stress to be more effectively accommodated, thereby reducing electrode expansion. The major findings of the present study demonstrate the applicability of MOF-based carbon frameworks as a material for silicon complex anodes.

Truck no-show behavior has posed significant disruptions to the planning and execution of port operations. By delving into the key factors that contribute to truck appointment no-shows and proactively predicting such behavior, it becomes possible to make preemptive adjustments to port operation plans, thereby enhancing overall operational efficiency. Considering the data imbalance and the impact of accuracy for each decision tree on the performance of the random forest model, a model based on the Borderline Synthetic Minority Over-Sampling Technique and Weighted Random Forest (BSMOTE-WRF) is proposed to predict truck appointment no-shows and explore the relationship between truck appointment no-shows and factors such as weather conditions, appointment time slot, the number of truck appointments, and traffic conditions. In order to illustrate the effectiveness of the proposed model, the experiments were conducted with the available dataset from the Tianjin Port Second Container Terminal. It is demonstrated that the prediction accuracy of BSMOTE-WRF model is improved by 4%-5% compared with logistic regression, random forest, and support vector machines. Importance ranking of factors affecting truck no-show indicate that (1) The number of truck appointments during specific time slots have the highest impact on truck no-show behavior, and the congestion coefficient has the secondhighest impact on truck no-show behavior and its influence is also significant; (2) Compared to the number of truck appointments and congestion coefficient, the impact of severe weather on truck no-show behavior is relatively low, but it still has some influence; (3) Although the impact of appointment time slots is lower than other influencing factors, the influence of specific time slots on truck no-show behavior should not be overlooked. The BSMOTE-WRF model effectively analyzes the influencing factors and predicts truck no-show behavior in appointment-based systems.

The thermocatalytic decomposition of methane is a promising method for hydrogen production. To determine the cause of carbonaceous catalyst deactivation and to produce high-value carbon, methane decomposition behavior and deactivated catalysts were analyzed. The surface properties and crystallinity of a commercial activated carbon material, MSP20, used as a methane decomposition catalyst, varied with the reaction time at a reaction temperature of 900 °C. During the initial reaction, MSP20 provided a methane conversion of ≥ 50%; however, the catalyst exhibited rapid deactivation as crystalline carbon grew at surface defects; after 15 min of reaction, approximately 33% methane conversion was maintained. With increasing reaction time, the specific surface area of the catalyst decreased, whereas crystallinity increased. The R-square value of the conversion–crystallinity relationship was significantly higher than that of the conversion–specific surface area relationship; however, neither profile was linear. The activity of the activated carbon catalyst for methane decomposition is mainly determined by the complex actions of the specific surface area and defect sites. The activity was maintained after an initial sharp decline caused by the continuous growth of crystalline carbon product. This study presents the application of carbonaceous catalysts for the decomposition reaction of methane to form COx- free hydrogen, while simultaneously yielding porous carbon materials with an improved electrical conductivity.