This study developed a QSAR regression model using the XGBoost machine learning algorithm to predict the acute aquatic toxicity of highly hazardous PCBs. EC50 values for Daphnia magna were obtained from QSAR Toolbox 4.7. Input features consisted of approximately 3,000 molecular descriptors and fingerprints generated from official structure data using RDKit and the Morgan algorithm, excluding mixtures. The dataset was split into training and test sets (7 : 3) based on 500,000 randomized seeds, and the most balanced combination was selected using Kolmogorov-Smirnov and Wilcoxon rank-sum tests. Z-score standardization was applied based on the training set, and the XGBoost model was trained using 5-fold cross-validation with grid search optimization. The final model showed excellent predictive performance (R2 =0.97, RMSE= 0.19). A simplified model using only the top 10 predictive molecular features retained approximately 95% of the original accuracy while improving interpretability and efficiency. The model was applied to 38 PCB compounds lacking EC50 values, and the predicted values showed a statistically similar distribution to the measured group, with only minor differences in a few structural fingerprints. These results demonstrate the applicability of XGBoost-based models for reliable toxicity prediction and offer a promising alternative approach for assessing the environmental risk of untested PCBs.

The flora of the vascular plants in Ungseokbong County Park, Sancheonggun, Gyeongsangnam-do, was surveyed 11 times from April 2023 to September 2024. The surveys revealed 461 taxa, comprising 101 families, 288 genera, 417 species, 11 subspecies, 30 varieties, and three forms. Of these, two taxa were designated as endangered species, six taxa as rare plants, and 19 taxa as Korean endemic plants. The study also documented a total of 69 taxa as floristic regional plants, specifically two taxa of grade V, five taxa of grade IV, 11 taxa of grade III, 18 taxa of grade II, and 33 taxa of grade I. Furthermore, six taxa were identified as plants adaptable to climate change, comprising two northern species and four southern species. Forty-four taxa of alien plants and four taxa of ecosystem-disturbing plants were also found in this area. This study, based on reference specimens, provides fundamental data on the distribution and status of plants in Ungseokbong County Park and is expected to serve as a resource for the conservation and management of plant resources.

This study developed an early warning model for Korea’s salmon import supply chain, which relies heavily on a single country. A supply chain crisis is defined as a significant change in the CIF import price beyond a stable range, with potential impacts on domestic prices. The crisis index, using January 2010 as the base point, combines the relative price level and its year-on-year growth rate. The threshold was set based on earlier agricultural early warning studies. Monthly and quarterly data were used to select explanatory variables including supply factors and demand or macroeconomic factors. Variables with high 3~5 month lagged correlations were chosen using a stepwise method. Ordinary Least Squares (OLS) regression and Probit models were applied for both all crises and continuous crises, and predictive accuracy was evaluated using MAE and RMSE. Results show that the Probit model with a five-month lag for continuous crises provided the highest accuracy.

This study was conducted to elucidate the effects of feeding betaine or monosodium glutamate on the growth and carcass performance of Hanwoo steers according to the fattening stage under high-temperature stress. Farms in an area where THI was 78 or higher for more than 100 days were selected, and 30 head in the early fattening stage (14-15 months of age), 30 head in the mid-fattening stage (16-18 months of age), and 30 head in the late fattening stage (24-25 months of age) were tested, and 10 head were assigned to each treatment group. The experimental group was divided into control, T1 with 96% of the amino acid compound additive and 4% betaine, and T2 with the amino acid complex additive and 4% monosodium glutamate. 50 g per head were fed every morning for a total of 5 months from May 1, 2022 to September 30. In this study, there was no effect of betaine and monosodium glutamate on the growth and rectal temperature of Hanwoo steers at each fattening stage, but monosodium glutamate had a positive effect on the increase in rib eye area and decrease in back fat thickness in steers in the late fattening stage (P<0.05). Therefore, the results of this study indicate that monosodium glutamate did not have a direct effect on the growth of fattening Hanwoo steers, but it is thought to have a positive effect on the rib eye area and back fat thickness through protein metabolism and muscle development.

This study aims to analyze the risk factors contributing to marine accidents involving Korean distant water fishing vessels using a Bayesian network approach. As marine accidents in this sector often result in severe casualties and significant economic losses, understanding their underlying causes is critical. Based on official investigation records from the Korea Maritime Safety Tribunal (2000-2023), a dataset of 46 accident cases involving longliners, trawlers, and other fishing vessels was constructed. The analysis categorized accidents by vessel types, gross tonnage, vessel age, location, operating status, and specific causes, including poor lookout and inadequate maintenance. Following the Formal Safety Assessment (FSA) framework recommended by the International Maritime Organization (IMO), the study applied Bayesian networks to quantify the probabilistic relationships among risk factors. The results revealed that the most hazardous conditions for different accident types included: vessels with 300-500 GT, aged 20-40 years, operating outside harbor limits during navigation or fishing. Specifically, collision and grounding incidents were primarily associated with poor lookout, while sinking and fire/explosion incidents were linked to inadequate maintenance. The findings underscore the necessity of tailored safety control measures for each accident type and vessel category. This research provides empirical evidence to support decision-making for improving safety policies under the Act on the Punishment of Serious Accidents and the Distant Water Fisheries Development Act.

This study investigates the effects of canopy fabric material and vent diameter on the deployment performance of sea anchors for fishing operations through field experiments. Three canopy configurations were tested: polyamide (PA), polyester (PES), and a PA – PES alternating combination. Vent diameters of 80 cm and 40 cm were applied to each fabric as controlled structural factors. Deployment performance was evaluated from entrance diameter computed using four evenly spaced water level loggers, and maximum towing tension was recorded with a load cell. Key findings were discovered as follows: PES and the PA – PES mix achieved deployment diameter/ratio and maximum tension comparable to the current PA standard, indicating practical substitutability. PES also exhibited superior stability, showing reduced variability even with the smaller vent (a change in standard deviation ΔSD-1.75 cm). The mixed canopy maintained performance similar to PA. As expected, vent diameter systematically affected geometry and load (80 cm: 187 – 198 kgf vs. 40 cm: 249 – 268 kgf), underscoring the need to pair material selection with appropriate vent sizing. In conclusion, PES and mixed fabrics are viable alternatives to PA, and co-optimization of fabric choice and vent diameter can enhance sea-anchor performance, durability, and operational reliability for fishing operations.

This study assessed the processing suitability and functional potential of sweet potato paste by comparing quality characteristics across different cultivars and heat treatment methods (steaming and baking). Generally, moisture content was higher after steaming, with the ‘Bodami’ and ‘Pungwonmi’ cultivars retaining more moisture, while ‘Jinyulmi’ and ‘Danjami’ had lower moisture levels. Purple-fleshed cultivars displayed negative a* and b* values, indicating bluish hues, whereas yellow-fleshed cultivars maintained stable b* values after heating. Both °Brix and free sugar levels increased after treatment, with baking significantly elevating maltose levels and enhancing sweetness. Apparent viscosity was higher in ‘Danjami’, ‘Jinyulmi’, and ‘Bodami’, while ‘Hogammi’, ‘Hopungmi’, and ‘Sodammi’ exhibited lower viscosity. Additionally, ‘Bodami’ and ‘Danjami’ demonstrated the highest levels of polyphenols, flavonoids, and antioxidant activities, confirming their potential as valuable functional ingredients. These findings underscore the importance of selecting appropriate cultivars and heat treatments to optimize the physicochemical and functional qualities of sweet potato paste.

The cosmetics industry expects low irritation and skin improvement effects by utilizing natural ingredients and botanical extracts. In particular, Poncirus trifoliata fruit extract is a traditionally recognized ingredient with proven pharmacological efficacy and contains various bioactive compounds. According to previous studies, Poncirus trifoliata fruit has been reported to possess antioxidant, whitening, and skin-improving effects. In this study, the antioxidant and whitening efficacy of Poncirus trifoliata fruit extract was evaluated according to different extraction solvents, and the formulation stability of a cleanser containing this extract was analyzed. The antioxidant activity of Poncirus trifoliata fruit extract was confirmed by measuring DPPH and ABTS⁺ radical scavenging activity, while its whitening efficacy was assessed through tyrosinase inhibition activity. Additionally, the total polyphenol and flavonoid content was measured, confirming its strong antioxidant effects. These findings suggest that Poncirus trifoliata fruit extract may contribute to anti-aging and skin-whitening effects. To evaluate the stability of a cleansing formulation containing Poncirus trifoliata fruit extract, pH and viscosity changes were measured over 28 days under temperature conditions of 5°C, 25°C, and 45°C. The results indicated a decline in stability over long-term storage. Therefore, further studies are required to optimize the extract concentration and improve the formulation for enhanced long-term stability. This study suggests that Poncirus trifoliata fruit extract has potential as a functional cosmetic ingredient for skin whitening and anti-aging and can serve as fundamental data for future research on stability enhancement.

병원성대장균은 설사 및 장염의 원인균 중 하나이며, 가 장 흔한 기회감염의 병원체로서 내성에 대한 지표로도 사 용되고 있는 병원체이다. 2022년부터 2024년까지 경상남 도 내 식중독 환자로부터 분리된 병원성대장균의 병원성 유형, 독성 유전자, 항생제 내성 및 내성 유전자 등 발생 경향과 분자유전학적 특성을 조사하였다. 병원성 대장균 은 월별로 6월부터 8월까지, 연령대별로 20-29세 환자에게서 가장 많이 분리된 것으로 나타났다. 분리된 총 283 건의 병원성대장균은 장병원성대장균(EPEC)(118건 [43.7%]), 장독소형대장균(ETEC)(80건 [28.3%]), 장출혈성대장균 (EAEC)(73건 [25.8%]), 장출혈성대장균(EHEC)(11건 [3.9%]) 으로 분류됐다. 암피실린(57.6%)과 세파졸린(39.3%)에 대 한 내성이 가장 높았으며, 내성균주의 다제내성률은 4제 항생제에 대한 내성균주(42.6%)가 가장 많은 것으로 확인 되었다. 내성 유전자의 분포는 blaCTX-M(48.9%), blaTEM (24.9%) 순으로 확인되었고, blaOXA는 검출되지 않았다. 이러한 연구 결과는 병원성 대장균으로 인한 식중독 발생 을 예측하고, 내성균 확산을 예방하기 위한 공중 보건 관 리의 기초자료로 활용될 수 있을 것으로 기대된다.

본 연구는 울산광역시 유통 과채류 가공식품의 잔류농 약 오염도를 모니터링하여 소비자의 안전성을 평가하기 위해 수행하였다. 울산광역시 소재 대형마트와 온라인 쇼 핑몰을 통해 유통되고 있는 과일 및 채소 가공식품 120건 (과일류 58건, 채소류 62건)에 대해 잔류농약(401종)을 분 석하였으며, 검출률은 32.5%(39건)이었고, 총 48종의 농약 검출을 확인하였다. 한편, 2022년부터 2024년까지 울산광역시 보건환경연구 원(농수산물검사소)에서 수행한 비가공 농산물의 잔류농약 검출률과 비교했을 때, 과일 및 채소 가공식품의 검출률 은 60-70% 수준이었다. 또한 검출된 농약의 검출량은 모 든 시료에서 원료 농산물에 대한 한국 기준의 20% 미만 수준이었고, 위해도(%ADI) 평가 결과 0.0003-0.7658%로 모두 안전한 수준인 것으로 확인되었다. 본 연구는 가공식품과 일반 유통 농산물의 잔류농약 검 출률 및 검출 수준을 비교함으로써, 가공식품에서도 잔류 농약 관리가 필요함을 실증적으로 제시하였다. 다만, 조사 한 가공식품 검체의 수량 및 종류가 제한적이고, 비가공 농산물에 대한 자료는 울산광역시에 유통되는 농산물에 국한된 자료라는 점에서 한계가 있다. 따라서, 향후 연구 에서는 가공식품 검체를 더 많이 확보하고, 비가공 농산 물에 대한 자료는 전국 수준에서 수집하여 보다 정밀한 모니터링이 이루어질 필요가 있다고 사료된다.

최근 한반도 주변 해역에서 해상사고로 인한 인명피해가 증가함에 따라 실종자 수색 및 구조 활동을 지원하기 위한 수중환경 정보 산출 기술 개발의 필요성이 대두되고 있다. 끊임없이 변화하는 해양환경 속에서 수중시야를 예측하는 것은 매우 중요한 과제이다. 본 연구에서는 인공위성 영상과 현장실험 자료를 활용하여 탁도와 수중시야 간의 상관 성을 분석하고, 한반도 서해 연안에 적합한 수중시야 산출 알고리즘을 제시하고자 한다. 이를 위해 대천항 인근 해역의 두 정점을 선정하여 탁도 센서와 세키디스크를 이용해 깊이에 따른 탁도 및 수중시야를 측정하였으며, 동시에 고해상도 인공위성 영상을 수집하여 표층 원격반사도 자료를 획득하였다. 또한 서해 연안에서의 탁도 변화에 따른 수중시야의 공 간 분포를 비교하기 위해 Sentinel-2 위성의 560 nm 반사도를 활용하여 연구 해역의 탁도를 산출하고, 실측 탁도와 수 중시야 간의 상관성을 분석하였다. 연구 결과, 서해 연안에서는 2 .0- 3.0NTU 범위의 탁도가 분포하였으며, 수중거리는 1.5-3.5 m 사이의 값을 나타냈다. 특히, 만 지형이나 섬 주변에서는 상대적으로 낮은 수중시야가 관측된 반면, 대천해수 욕장 해안선을 따라서는 약 3.0m 이상의 높은 수중시야를 보였다. 본 연구를 통해 실측 및 원격탐사 자료를 활용한 수중시야 산출 가능성을 확인하였으며, 위 결과는 향후 해상 실종자 수색 지원을 위한 기초 자료로 활용될 것으로 기 대된다.

본 연구는 한국 기상대 데이터를 활용하여 콘크리트 포장의 깊이별 온도를 예측하는 ANN(Artificial Neural Network) 모델을 개발하는 것을 목표로 한다. 기존의 열평형 방정식 기반 모델은 특정 지역의 기상 데이터를 필요로 하기 때문에 일반적인 적용이 어렵다는 한계를 가지고 있다. 이에 본 연구에서는 ANN을 활용하여 기상대 데이터를 기반으로 범용적 인 온도 예측 모델을 개발하고자 한다. 이를 통해 다양한 지역 및 환경 조건에서도 적용 가능한 모델을 구축하는 것이 목적이다. 본 연구에서는 2017년 1월 1일부터 2018년 12월 31일까지의 1시간 단위 기상 및 온도 데이터를 활용하며, 0.05m, 0.15m, 0.25m, 0.35m, 0.45m 깊이별 온도 데이터를 학습 데이터로 사용한다. 입력 변수로는 기온, 풍속, 강수량, 습도, 일 조량, 일사량, 적설량, 적운량, 지면온도를 포함한다. 이러한 다양한 기상 데이터를 활용하여 신경망 모델을 학습하고, 기 존 방식보다 높은 정확도를 확보하는 것이 연구의 핵심 목표이다. 기존 ANN 구조인 O = WI + B에서 확장된 O = W(I + (WI + B)) + B 형태의 비선형 구조를 적용하여 기존 모델이 가지는 비선형 관계 반영의 한계를 극복하고자 한다. 또한, 선형 다중 은닉층 모델과 비선형 다중 은닉층 모델을 각각 개발하여 성능을 비교하고, 비선형 모델의 필요성과 일반화 능력을 평가할 예정이다. 최종적으로 두 모델의 성능을 평균 제곱 오차 및 평균 절대 오차 등과 같은 평가 지표들을 이용하여 비교 분석하고, 가장 적합한 모델을 도출하고자 한다.

In this study, we aim to classify personal mobility (PM)-related traffic crash data into four categories: PM-to-vehicle, PM-to-pedestrian, PM-single, and vehicle-to-PM crashes, and analyze the factors influencing the severity of each crash type. To overcome the limitations of existing studies in explaining the impact of independent variables on ordinal dependent variables, a random forest model was combined with the Shapley additive explanation technique. This approach visualizes the influence of independent variables on a dependent variable, providing clearer insights and enhancing interpretability. The analysis of PM traffic accidents, categorized into at-fault, single-vehicle, and victim accidents, revealed distinct key factors for each type. The main contributors to the severity of crashes caused by PM are traffic violations by teenagers and collisions with elderly pedestrians. Single-vehicle accidents were predominantly caused by overturn incidents, with inadequate driving skills among PM users aged 40 years and older, and significantly increasing severity. Victim accidents primarily occur at intersections, where the behavior of the at-fault driver and age of the PM user are critical factors influencing the severity. We identified various factors influencing the severity of PM crashes by type, highlighting the need for tailored policy measures. Proposed policies include physically separating bicycle–pedestrian shared spaces and strictly regulating illegal PM sidewalk riding, introducing PM licenses for teenagers to ensure compliance with traffic rules, and implementing regular safety education programs for all age groups. Although this study applied a new analytical technique, it relied on limited crash data, thus limiting the results to estimates.

Component-specific information is crucial for identifying sources of PM2.5 in indoor environments. However, profiles of PM2.5 at various locations, including subway tunnels are limited. This study aimed to evaluate the relationships between PM2.5 and its component across tunnels, platforms, and outdoor environments at underground subway stations in Incheon. The study was conducted at six underground subway stations in Incheon. PM2.5 concentrations were measured twice at each station, simultaneously covering the tunnel, platform, and outdoor areas. Carbon (two types), ion (eight types), and metal components (20 types) were analyzed using each analytical instruments. The mean PM2.5 concentration in the tunnel was 33.0±15.7 μg/ m3, significantly higher than the concentrations observed on the platform (12.9±4.6 μg/m3) and outdoors (13.1±7.6 μg/m3). The proportion of total metal concentrations in PM2.5 was highest in the tunnel (57.8%), followed by the platform (22.2%) and outdoor areas (11.3%). Significant correlations between the platform and tunnel were observed for organic carbon, SO4 2–, NO3 –, NH4 +, Ba, Mn, Fe, and Se. Significant correlations between the platform and outdoor were observed for SO4 2–, NO3 –, NH4 +, and Ti, while the tunnel and outdoor showed correlations for SO4 2– and NH4 +. PM2.5 concentrations and total metal concentrations were highest in the tunnel. While PM2.5 concentrations on the platform and outdoors were similar, total metal concentrations were higher on the platform than outdoors. From the platform’s perspective, the concentrations of Ba, Mn, Fe, and Se were only associated with the tunnel, while SO4 2–, NO3 –, and NH4 + had tendency of correlations between both the tunnel and outdoors. The findings suggest that for platform PM2.5 concentrations, Ba, Mn, Fe, and Se may serve as indicators of tunnel-originating PM2.5, while SO4 2–, NO3 –, and NH4 + may serve as indicators for outdoor sources.