최근 ChatGPT로 대표되는 인공지능의 급격한 발전은 인공지능 에 대한 낙관과 비관이 엇갈리는 가운데 기독교 선교가 새롭고도 실제적 인 방향을 모색해야 할 필요성을 제기했다. 이를 위해 본 연구는 행위자 -네트워크 이론을 주요 이론적 틀로 활용하여 인공지능을 단순한 도구가 아닌 인간과 상호작용하는 행위자로 인식한다. 이러한 관점에서 현재 인공지능 기술의 최전선에 있는 거대 언어 모델의 기술적 특성과 작동원리를 상세히 분석하여 인공지능이 인간과 맺는 관계에 주목한다. 이러한 이해를 토대로 인공지능과의 선교적 접점을 모색하기 위한 방안은 첫째, 인공지능을 선교 현장으로 인식하는 것, 둘째, 인간에게만 주어진 선교적 삶을 사는 것. 셋째, 인공지능을 선교사역의 협력자로 받아들이는 것, 넷째, 오픈소스 거대 언어 모델을 활용한 선교적 목적의 인공지능을 개발하는 것이다. 본 연구는 인공지능 시대의 기독교 선교 가 단순히 인공지능을 도구로 활용하는 차원을 넘어, 인공지능과의 협력적 관계를 통해 새로운 선교의 지평을 열어가야 함을 제안한다. 이는 데이비드 보쉬가 주장한 것처럼, 선교는 각 시대의 변화에 따라 새로운 패러다임으로 변화되어야 한다는 관점에 기반한다.

Fishways, particularly installed at the estuary, have a purpose to encourage fluent migration for migratory fishes, as well as amphidromous and even freshwater species. Not choosing the laborious traditional method of using traps, we assessed the efficiency of the two fishways installed at the west and east barrage of the Nakdong River estuarine barrage respectively, by analyzing the videos recorded through automatic monitoring system. We randomly selected 30 videos monthly at each fishways and identified what kind of fishes were using the fishways and categorised their behaviour such as size, time and whether they passed the monitoring system or not. As a result, a total 8 families 14 species were recorded by monitoring system, with the most dominance of Erythroculter erythropterus (Relative Abundance: 59.5%), followed by Micropterus salmoides (R.A: 19.9%) and Mugil cephalus (R.A: 9.9%). The monitoring system can capture passing fishes during night but the number of appearances of fish species at each hour of a day indicated significant diurnal activities (p<0.05). When fishes pass the monitoring system, approximately 70% of them passed through the monitoring device, while 17% of them showed fallback movement. Our finding indicates that species-specific characteristics of each fish are well represented through video monitoring method. In order to maximise advantages of using video monitoring, it is necessary to consider the installation point properly so that the monitoring system does not interfere with the movement of fish. Also, the utilisation of AI technology in the future is also necessary.

The predator-prey interaction in freshwater ecosystems is a crucial area in the ecological study field and one of example to find such interaction is to investigate stomach contents. However, traditional method through visual inspection often induce misidentification, as it depends critically on intactness of physically visible data. In this study, we utilized Next-Generations Sequencing (NGS) technology to test the applicability stomach content analysis and overcome such limitation. NGS was applied to analyze the stomach contents of the Hemibarbus labeo, Tachysurus fulvidraco, and Plecoglossus altivelis collected in the lower part of Nakdong River. As a result, T. fulvidraco had a higher number of Animalia operational taxonomic units (OTUs) intake rate than H. labeo. At the same time, P. altivelis had higher number of Plantae OTUs intake rate than T. fulvidraco and higher Protozoa OTUs intake rate than H. labeo respectively. Therefore, NGS technology application enable to overcome traditional method’s limitation and discover hidden interspecific interaction which can further be used in appropriate habitat assessment.

E171, a mixture of titanium dioxide, has been widely used as a food additive due to its whitening effect and low toxicity. However, it has been proven that E171 is no longer safe for public health. So far, there are insufficient studies on the toxic effects of E171 on organisms especially using standardized test methods. In this study, toxicity assessments of E171 to two aquatic species, water flea (Daphnia magna) and zebrafish (Danio rerio), were performed using modified standardized test methods based on the physicochemical properties of E171. The hydrodynamic diameter, polydispersity index, and turbiscan stability index (TSI) were measured to ensure the dispersion stability of E171 in exposure media during the test period. The EC50 for immobilization of water flea was 141.7 mg L-1 while zebrafish was not affected until 100 mg L-1 of E171. Measurements of reactive oxygen species (ROS) and antioxidant enzyme activities confirmed that E171 induced oxidative stress, leading to the activation of superoxide dismutase and catalase in both water flea and zebrafish, although the expression of antioxidant enzyme genes differed between species. These results suggested the potential risk of E171 to aquatic organisms and provided toxicological insights into the impacts of E171 on the environment.