Vertical takeoff and landing (VTOL) drones are increasingly recognized as an important solution for last-mile delivery in the food and beverage sector, owing to their rapid deployment capabilities and high operational flexibility. In particular, growing interest in drone delivery services has been observed among fast food and coffee franchises, where rapid delivery is essential due to the time-sensitive nature of food and beverage items intended for immediate consumption. Despite this trend, there remains a lack of research on the structural modeling of flight routes for VTOL drones operating under automatic flight conditions, and on the implementation of first-come-first-served (FCFS) delivery services utilizing predefined flight routes. Accordingly, this study comprehensively describes the operations for food and beverage delivery services using VTOL drones. In particular, it addressed the use of multiple drones to conduct FCFS-type multi-point delivery services along fixed routes suitable for automatic flight.

Anomaly detection technique for the Unmanned Aerial Vehicles (UAVs) is one of the important techniques for ensuring airframe stability. There have been many researches on anomaly detection techniques using deep learning. However, most of research on the anomaly detection techniques are not consider the limited computational processing power and available energy of UAVs. Deep learning model convert to the model compression has significant advantages in terms of computational and energy efficiency for machine learning and deep learning. Therefore, this paper suggests a real-time anomaly detection model for the UAVs, achieved through model compression. The suggested anomaly detection model has three main layers which are a convolutional neural network (CNN) layer, a long short-term memory model (LSTM) layer, and an autoencoder (AE) layer. The suggested anomaly detection model undergoes model compression to increase computational efficiency. The model compression has same level of accuracy to that of the original model while reducing computational processing time of the UAVs. The proposed model can increase the stability of UAVs from a software perspective and is expected to contribute to improving UAVs efficiency through increased available computational capacity from a hardware perspective.

더듬이긴노린재과의 미기록종인 Pachygrontha similis Uhler, 1896 (닮은더듬이긴노린재, 신칭)을 한국에서 처음으로 보고한다. 외부형질 과, 진단형질, 성충 표본과 생식기의 사진 그리고 한국산 더듬이긴노린재속의 분류 키를 제공한다.

Cucumber mosaic virus (CMV) poses a considerable threat to a diverse array of crops in global agriculture. CMV impacts commercially important cut lilies by diminishing both yield and flower quality. We used RNA sequencing (RNA-seq) to investigate the changes in gene expression in the leaves and bulbs of four distinct cultivars of cut lily, ‘Cancun,’ ‘Brunello,’ ‘Connecticut King,’ and ‘Casa Blanca’ following CMV infection. Notably, CMV affected photosynthetic processes by significantly downregulating genes associated with photosynthesis. In addition, CMV infection was detrimental to chloroplast function and energy production. We observed differential expression of genes associated with both dominant and recessive resistance pathways that are crucial for preventing virus entry, replication, and systemic spread within the plant. Based on functional annotation and differential gene expression analysis, we identified the regulatory genes involved in triggering immune responses, modulating signal transduction, and specific host factors during CMV infection. To validate the RNA-seq findings, we selected four genes involved in resistance, virus multiplication, and virus spread and analyzed them using real-time quantitative reverse transcription PCR (qRT-PCR) with specific primers. The qRT-PCR results aligned closely with those from RNA-seq, showing consistent fold-change responses for the genes that were differentially expressed, indicating that the RNA-seq results were reliable. These results deepen our understanding of the complex genetics behind plant-virus interactions while also providing information for breeding programs that aim to develop CMV-resistant lily cultivars.

This study aims to develop an AI-based analysis system that aligns with the international trend of AI legislation, including the EU's AI Act, while also addressing the analytical needs of the public sector. The focus is on providing timely and objective information to policymakers and specialized researchers by exploring advanced analytical methodologies. As the complexity and volume of data rapidly increase in the modern policy environment, these methods have become essential for governments to obtain the objective information needed for critical decision-making. To achieve this, the study integrates machine learning, natural language processing (NLP), and Large Language Models (LLM) to create a system capable of meeting the analytical demands of government entities. The target dataset consists of “quantum” field data collected from South Korea's National R&D Information System (NTIS). Machine learning was applied to this data to assess the validity of the analysis, while BERTopic, a natural language analysis package, was used for text analysis. With the introduction of LLMs, the extracted information from machine learning and natural language analysis was not merely listed but also connected in meaningful ways to provide policy insights. This approach enhanced the transparency and reliability of AI analysis, minimizing potential errors or distortions in the data analysis process. In conclusion, this study emphasizes the development of a system that enables rapid and accurate information provision while maintaining compatibility with international AI regulations such as the AI Act. The use of LLMs, in particular, contributed to enhancing the system’s capabilities for deeper and more multifaceted analysis.

Lumpy Skin Disease (LSD) and Foot-and-Mouth Disease (FMD) cause substantial economic losses on the livestock industry. Therefore, vaccinations have been implemented as the control strategy in endemic countries. However, the potential adverse effects of administering vaccines for both diseases simultaneously have not been thoroughly evaluated. The aim of this study was to assess the impact of vaccinating dairy cows with either or both LSD and FMD vaccines on milk production and physiological parameters such as milk temperature, rumination time and body weight. The experimental groups were divided into four according to the injection materials: 1) saline, 2) LSD vaccine, 3) FMD vaccine, and 4) both vaccines. The impact of vaccination on milk yield and physiological parameters was evaluated daily until 12 days post-vaccination, and milk components were analyzed twice, once per week. Among the experimental groups as well as each vaccine group, no statistically significant differences (p < 0.05) were observed at milk yield, milk components, or milk temperature. This suggests that simultaneous vaccination of LSD and FMD can be administered without adverse effects.

본 연구를 통해 미기록종 Homalotylus albifrons (Ishii, 1925) (벌목: 깡충좀벌과)를 한국에 최초로 보고한다. 이 종에 대한 진단과 사진과 한국 의 Homalotylus 속의 종 키를 수록한다.

본 연구는 한국 언론에서 앙골라와 모잠비크를 중심으로 하는 포르투 갈어권 아프리카 국가들의 보도 행태를 분석하여, 이들 국가가 주변화와 소외의 시각에서 어떻게 묘사되고 있는지 고찰하였다. 뉴스 기사에 대한 종합적인 분석을 통해 다음과 같은 연구 결과가 도출되었다. 이들 국가 는 주로 자원 채취나 투자 기회의 장으로 경제적 관점에서만 조명되고 있으며, 그들의 문화적, 역사적, 사회적 복합성은 대부분 간과되고 있음 을 확인할 수 있었다. 더 나아가 앙골라와 모잠비크는 세계적 지경학·지 정학적 역학에서 수동적인 주체로 묘사되어 주변부적 존재로서의 지위가 공고화되고 있다. 이러한 연구 결과는 한국 언론의 보다 균형 있고 심층 적인 보도 방식을 요구하며, 이들 국가의 주체성과 다양한 경험을 인정 하는 방향으로의 변화를 촉구한다. 본 연구는 한국 언론이 아프리카 국 가들을 어떻게 프레임화하는지에 대한 이해를 확장하며, 특정 국가 혹은 지역에 대한 보다 포괄적인 보도 방식으로의 전환을 제안한다.

A 17-year-old spayed female Shih Tzu dog, weighing 5.0 kg, presented with frequent coughing and respiratory distress. Blood tests revealed mild thrombocytosis, and thoracic ultrasonography and radiography confirmed a significant amount of pleural effusion. However, the thoracic radiographs showed no radiopaque nodules or interstitial patterns indicative of thoracic tumors. Thoracentesis was performed to relieve effusion-induced thoracic pressure, yielding a hemorrhagic serosanguinous pleural fluid. The cytological analysis of this fluid revealed mesothelial cells, supporting the clinical diagnosis of mesothelioma in situ. To address the patient’s clinical symptoms, an aggressive management approach was implemented with chest tube placement to address recurrent pleural effusion after initial thoracentesis. During treatment, the patient exhibited stable health and adapted well to daily life. To the best of our knowledge, this is the first reported case of mesothelioma in situ with hemorrhagic malignant pleural effusion in South Korea. Using a chest tube as an aggressive treatment successfully alleviated dyspnea symptoms and provided symptomatic relief in a patient with mesothelioma in situ.

Mesenchymal stem cells (MSCs) have emerged as a promising therapeutic resource for the peripheral nervous system (PNS) and central nervous system (CNS) that is attributable to their capacity for neuronal differentiation. Human dental pulp stem cells (hDPSCs), which exhibit MSC-like traits, can differentiate into neuron-like cells and secrete critical neurotrophic factors; however, their therapeutic potential in peripheral nerve injury remains unexplored. This study investigated the regenerative effects of hDPSC transplantation following sciatic nerve injury (SNI) in rats. Transplantation of hDPSCs, STRO-1+ hDPSCs, or CD146+ hDPSCs after sciatic nerve transection in rats upregulated the levels of β3 tubulin, a marker of immature newborn neurons. Furthermore, the levels of glial cellderived neurotrophic factor, insulin-like growth factor 2, and the neuroregenerative factor NeuroD1 were upregulated. Motor dysfunction in rats with SNI was restored, as demonstrated by significantly higher sciatic functional index scores compared with the sciatic nerve transection group without transplantation. Transplantation of hDPSCs into injured peripheral nerves results in the upregulation of neurotrophic factors, differentiation into immature neurons, and promotion of motor function recovery. This approach holds promise as a valuable therapeutic strategy for repairing injured peripheral sciatic nerves, potentially providing a solution for nerve damage in both the PNS and CNS.

국립원예특작과학원에서는 밝은 화색과 안정적인 화형의 생 육이 우수한 빨간색 스탠다드 장미 품종을 육성하기 위해 진한 적색 스탠다드 장미 품종 ‘엔드리스러브(Endless Love)’를 모 본으로, 꽃잎수가 많고 안정적으로 가시가 적은 밝은 노란색 ‘페니레인(Penny Lane)’ 품종을 부본으로 인공교배하였다. 37 개의 교배실생을 양성해 1, 2, 3차에 걸친 특성검정 및 현장실증 을 통해 꽃이 크고 화형이 안정적이며, 재배안정성 및 생산성, 절화특성이 우수한 ‘원교 D1-390’을 최종 선발하였다. 2023년 ‘루비레드(Ruby Red)’로 명명하여 국립종자원에 품종보호출원·등록되었다. ‘루비레드’ 품종은 밝은 적색(R53C)을 가졌으 며, 꽃잎수가 32.8매, 화폭과 화고는 각각 10.9, 5.9cm로 대조 품종보다 크다. 절화장은 평균 71.7cm, 절화수명은 약 16.7일, 수량은 연간 168대/m2로 대조품종인 ‘레드스퀘어(Red Square)’ 대비 절화장이 길고 절화수명도 2배 이상 길며, 수확량도 1.4배 우수하다. 2023년 국내 육성 장미 품종 서울식물원 관람객 대상 공동평가회에서 스탠다드 장미 중 우수한 평가를 받았으며, 현 장 실증 결과 농가별로 균일하고 우수한 수량과 절화품질을 보 였다. 절화용 장미 ‘루비레드’ 품종은 밝은 적색과 우수한 화형 을 가지는 품종으로 해외 대체 품종으로 국내에서 많이 재배될 것으로 기대된다.