Food webs have received global attention as next-generation biomonitoring tools; however, it remains challenging because revealing trophic links between species is costly and laborious. Although a link-extrapolation method utilizing published trophic link data can address this difficulty, it has limitations when applied to construct food webs in domestic streams due to the lack of information on endemic species in global literature. Therefore, this study aimed to develop a link extrapolation-based food web model adapted to Korean stream ecosystems. We considered taxonomic similarity of predation and dominance of generalists in aquatic ecosystems, designing taxonomically higher-level matching methods: family matching for all fish (Family), endemic fish (Family-E), endemic fish playing the role of consumers (Family-EC), and resources (Family-ER). By adding the commonly used genus matching method (Genus) to these four matching methods, a total of five matching methods were used to construct 103 domestic food webs. Predictive power of both individual links and food web indices were evaluated by comparing constructed food webs with corresponding empirical food webs. Results showed that, in both evaluations, proposed methods tended to perform better than Genus in a data-poor environment. In particular, Family-E and Family-EC were the most effective matching methods. Our model addressed domestic data scarcity problems when using a link-extrapolation method. It offers opportunities to understand stream ecosystem food webs and may provide novel insights into biomonitoring.

4차 산업혁명 시대에 건설산업은 전통적인 업무 방식에서 디지털 프로세스로 전환하고 있다. 특히, 건설산업의 특성으로 인해 업무 절차의 변경에는 어려움이 따르며, 점진적인 디지털 전환 및 시행착오가 발생하고 있다. 건설현장의 안전관리 분야도 역시 이 흐름을 따라 모든 데이터의 디지털화와 자동화를 목표로 연구 및 시도가 활발히 진행되고 있다. 그러나 최근의 통계에 따르면, 건설업 안전사 고는 계속해서 발생하고 있으며, 안전사고 사망자 수도 줄지 않고 있다. 본 연구는 이러한 문제를 해결하기 위해 건설공사 안전관리 종 합정보망의 빅데이터를 대규모 언어모델 인공지능을 통해 분석하였다. 분석된 결과는 실시간으로 업데이트가 가능한 상세설계모델 로부터 위치정보와 공간적 특성을 반영하여 안전관리가 필요한 현장모델링에 정보를 맵핑하였다. 해당 연구를 통해 건설현장 안전관 리 데이터의 디지털화를 통한 시설물 및 근로자의 안전을 강화하고, 건설사고 예방 및 효과적인 교육 지시를 위한 빅데이터 기반 안전 관리 플랫폼 개발을 목표로 한다.

Spider silk, which combines strength and lightness, emerges as an ideal candidate for non-woven fabric production. Unlike synthetic polymeric materials, silk are nontoxic and biocompatible and cause no allergic reaction. In particular, the dragline silk produced by the golden orb-web spider, Trichoephila clavata, is renowned for its superior strength and exceptional mechanical properties compared to other spider silks. Non-woven fabrics have found extensive applications in diverse industrial sectors, owing to their advantageous qualities such as breathability, durability, and lightweight characteristics. Natural dragline silk was extracted from the orb-weaving spider and subsequently randomly arranged. Compressing into a sheet-plane form, in addition to inducing the formation of water-resistant, stable β-sheet structures through ethanol vapor treatment or direct treatment, preserved the morphology of the silk fibers. The resulting non-woven sheets were analyzed with an field emission scanning electron microscope (FESEM) to observe their fine structures and mesh size were measured through image analysis.

Transmission electron microscopy was used to examine the microscopic structural features and myofibril organization of cardiac muscle cells in the orb-web spider T. clavata. There are many myofibrils, many mitochondria, a large sarcoplasmic reticulum, and transverse tubules (T-tubules) in the muscle fibers, even if the myofibril striations may not be as noticeable as in skeletal muscles. Because of their consistent striations, sarcomeres are characterized by Z-lines that are 2.0 μm on average in length and do not clearly distinguish between the A- and I-bands. A single T-tubule paired with a terminal cisterna of the sarcoplasmic reticulum constitutes a dyadic junction, which is primarily located at the A-I level of sarcomeres. Cells are joined by intercalated discs, which create several linkages via specialized junctions such as desmosomes, gap junctions, and fascia adherens—all of which are essential for heart function. Our results with transmission electron microscopy (TEM) clearly show that the contraction of the spider's heart muscle is neurogenically controlled, since each fiber is innervated by a motor neuron branch via neuromuscular junctions. These results highlight the neurogenic process controlling spiders' cardiac muscle contractions and advance our knowledge of the peculiar cardiac muscle structure of these animals.

이 글은 한국어 학습을 위한 웹 기반 한자 사전 모델을 제시하기 위한 것이다. 중국 문화권 학습자를 대상으로 한 이 연구에서는 웹 기반 한자 사전의 필요성을 확인하고 기존 사전의 한자 단어 학습의 문제점 을 분석하였다. 한자 단어 학습 시 한자 원어 형태소 인식이 중요하다고 보고 이를 반영한 별도의 팝오버 (popover) 창을 개발하였다. 한자 사전의 미시구조에는 항목, 단어 유형, 발음, 한-베트남어 단어(있는 경우), 한자의 어원, 한-베 소리(voice)가 포함되며, 이밖에 베트남어 어원에 대한 설명, 한자의 원래 형태소 와 관련된 한-베 단어, 번역, 설명, 예시 등이 포함되어야 함을 밝혔다. 그런 다음, 한자어 형태소와 한자- 베트남어의 발음을 포함하는 어원 틀, 베트남어 및 한자어의 한자 형태소 의미를 포함한 웹 사전을 구성하 고 그 활용 방안을 보여주었다. 본 연구는 한자어 형태소와 관련된 베트남 단어에 대한 정보를 추가하고, 프로그래밍 기술, 데이터베이스 업데이트 과정, 300개 규모의 한자 사전 모델을 제시한 기초연구로써 이후 한국어 학습자를 위한 웹 한자 사전 구축에 보탬이 되고자 한다.

이 글은 웹소설 <소녀, 홍길동>(2019)에 나타난 남장 서사를 중심으로 고전소설의 남장 서사 주체와 비교를 통해 우리 시대의 주체성에 대해 진단하는 것을 목적으로 한다. 지금까지 로맨스 웹소설 연구에서는 로맨 스 장르의 문제성이나 웹소설의 상업성과 통속성을 폭로하는 것이 대부분이었다. 이 글은 주체성의 측면에 서 바라보았을 때 시대정신과 관련해 변화된 부분이 더 중요하다고 생각했다. 그래서 작품 속 남장 서사를 고전소설의 것과 비교해본 결과, 남장이 로맨스를 조장하는 수단으로 활용되고 있으며 무엇보다 욕망을 은폐시킨 주체의 모습을 발견할 수 있었다. 이런 로맨스 웹소설의 낭만적 사랑은 기존 로맨스 소설의 문법을 일정 부분 따르면서도, 조금 다른 방식으로 로맨스를 형상화한 것이다. 기존 로맨스에서는 완벽한 ‘나’를 찾으려는 욕망이 내재해 있고, 이것은 진정성의 주체를 생산한다. 그러나 <소녀, 홍길동>에는 이러한 시도들이 부재하며, 오로지 상대방의 욕망 안으로 주인공의 욕망이 한정되기에 사랑‘만’을 읊조리는 유아 적이고 자폐적인 주체, 즉 ‘포스트-진정성’의 주체가 생산되었다. ‘포스트-진정성’의 주체는 환상성에 기대 고 있고, 이 환상은 생존을 중시하는 사회와 속물주의에 근원하고 있다. 이에 필자는 웹소설 장르가 환상성 이 아닌 상상력을 기반으로 한 새로운 주체 생산으로 가야할 것을 제안했다. 그것은 유목적 주체로, ‘타자 되기’를 통해 미래에 다가올 시대에 발맞춰 K-서사의 올바른 방향을 설정할 수 있으리라 본다.

This study aimed to explore nursing students' experience of learning cardiopulmonary resuscitation (CPR) in a web-based virtual simulation (vSim) through analysis of the reflection journals. Method: From June to July 2020, data were collected from 48 fourth-year nursing students who performed the simulation by reviewing prompt feedback on their CPR performance. The contents of the reflection journals were analyzed using NVivo qualitative data analysis software. Results: Nursing students experienced unfamiliarity with the English-based virtual environment as well as psychological pressure and anxiety about emergencies. Incorrect interventions were identified in the following order of frequency: violation of defibrillator guidelines, missing fundamental nursing care, error in applying an electrocardiogram monitor, inadequate initial response to cardiac arrest, insufficient chest compression, and inadequate ventilation. Lastly, the participants learned the importance of embodied knowledge, for knowing and acting accurately and reacting immediately, and their attitudes as nurses, such as responsibility, calmness, and attentiveness. Learning strategies included memory retention through repetition, real-time feedback analysis, pre-learning, and imagining action sequences in advance. The level of achievement, time required, CPR quality, and confidence improved with behavior-modification strategies developed through self-reflection. Conclusion: Educational interventions that are based on understanding accurate algorithms can strengthen selfawareness of mistakes to improve efficient imparting of CPR education.

The purpose of this study was to develop a nursing education program using Web-based simulation for the care of patients with intracranial pressure. An additional aim was to verify the effectiveness of nursing knowledge, problem-solving competency, a critical thinking disposition, and the expectation of learning transfer. Methods: This was an experimental study using repeated measures with a nonequivalent control group. The participants were senior nursing students, randomly assigned to experimental (n=30) and control (n=30) groups. The experimental group participated in a nursing education program that included Web-based lectures, pre-briefing, Web-based simulation, and debriefing, whereas the control group’s program included only Web-based lectures. Results: A significant difference was found between the experimental and control groups in problem-solving competency (F=5.84, p=.005), critical thinking disposition (F=4.25, p=.021), and the expectation of learning transfer (t=2.30, p<.025). Also, a significant interaction between time and group was found in problem-solving competency and critical thinking disposition. Conclusion: The results of this study showed that the education program using Web-based simulation positively affected nursing students’ problem-solving competency, critical thinking disposition, and the expectation of learning transfer. Therefore, this program can be considered a valuable aid in educating nursing students.

Land monitoring involves systematically understanding changes in land use, leveraging spatial information such as satellite imagery and aerial photographs. Recently, the integration of deep learning technologies, notably object detection and semantic segmentation, into land monitoring has spurred active research. This study developed a web service to facilitate such integrations, allowing users to analyze aerial and drone images using CNN models. The web service architecture comprises AI, WEB/WAS, and DB servers and employs three primary deep learning models: DeepLab V3, YOLO, and Rotated Mask R-CNN. Specifically, YOLO offers rapid detection capabilities, Rotated Mask R-CNN excels in detecting rotated objects, while DeepLab V3 provides pixel-wise image classification. The performance of these models fluctuates depending on the quantity and quality of the training data. Anticipated to be integrated into the LX Corporation's operational network and the Land-XI system, this service is expected to enhance the accuracy and efficiency of land monitoring.

The purpose of this study is to review the discourse on vaccination from a critical perspective by considering coronavirus disease 2019 (COVID-19) news on web portals to be practical arguments advocating for certain actions. For this purpose, this study analyzed the argument patterns of the discourse on vaccination with the keyword COVID-19 vaccine side effects and examined discourse characteristics highlighted by media reports to evaluate their meaning. Contrasting patterns were observed between pro- and anti-vaccine arguments, which consisted of the necessity of vaccination and medical evidence and which focused on personal choice and vaccine side effects, respectively. The characteristics of the political discourse were observed in the contest between these arguments. Rhetorical phrases, which are often used in the political discourse, represented the misleading arguments that lacked evidential accuracy and argumentative validity by maximizing fear, instead of alleviating fear about a health crisis with scientific information and discussion. As fake news trending on social media was introduced to online news portals, which are regarded as public discourse platforms, and undermined trust in the public discourse, it served as an opportunity to politicize the discourse on vaccination.

본 연구는 독립적인 정치 체제에 영향을 미치는 블록체인 기반 ‘탈중 앙화 자율 조직(decentralized autonomous organizations, 이하 DAO)’ 의 기술적 성격을 중심으로 정치철학 방향과 관련한 여러 가지 쟁점들을 밝히기 위한 것이다. 먼저, 정치적 DAO의 발전 방향을 파악하기 위해, 알고리즘과 분산원장기술(Distributed Ledger Technology, 이하 DLT) 의 특성과 사회적 이용에 대한 지금까지의 접근과 의견을 살펴본다. DAO는 다중 블록체인 기반의 사회 구조로, 스마트 계약으로 구성된 통 합 시스템을 통해 운영된다. 또한, 전체 조직을 자율적이고 완전하게 기 계화 및 자동화된 상태로 분할하여 결정이 이루어지는 정치적 성격을 갖 고 있다. 따라서, DAO는 데이터의 소유권 또는 운영과 관련한 투명성을 보장하는 장점을 갖는다. 또한, 투표자의 의사를 실행하는 자동화 메커니 즘, 예를 들어 위임과 같은 명령을 포함하여 대표 민주주의의 새로운 가 능성이 DAO에 있음을 밝히고자 한다. 이를 기반으로, 인공지능 기술을 비롯한 4차 산업혁명 시대에서 시민 참여의 합법성을 보장하는 방법에 대해 논의할 것이다. '알고리즘적 통치' 및 '자동화된 결정 과정'의 맥락 에서 기계 학습 알고리즘 및 방법의 증가는 이러한 기술적 진보의 윤리 적 합법성에 대한 문제를 제기한다.

We investigated the spatial distribution of heterotrophic bacteria associated with different water masses in the northern East China Sea (ECS) in summer. The surface water masses were divided into the Changjiang Diluted Water (CDW) and high salinity water (HSW). In the CDW region, the concentrations of dissolved inorganic nitrogen (DIN) and chlorophyll-a (Chl-a), and micro Chl-a contribution were high; and bacterial abundance (BA) and ciliate abundance (CA) were also high. In the HSW region with relatively low DIN concentrations, Chl-a concentration and micro Chl-a contribution were low, but pico Chl-a contribution was increased compared to those in the CDW region. BA did not show any significant difference from the CDW region, but CA was decreased. BA showed a positive correlation with Chl-a concentration in the CDW region; however, it did not show a significant correlation with Chl-a concentration in the HSW region. The ratio of bacterial carbon biomass/phytoplankton carbon biomass was exponentially increased with a decrease in the Chl-a concentration. Compared to the past (1990-2000s), the surface phosphate concentrations and the size of dominant phytoplankton have recently decreased in the ECS. Considering this trend of nutrient decrease and miniaturization of the phytoplankton, our results indicate that changes in the strength of the oligotrophic water mass could alter the function of the microbial food web.

Interactions between species in a community are very complex, and they are visualized and analyzed through a food web in simple way. Food web is a network of species connected by trophic links showing energy flow from prey to predator. Various models were developed to characterize the food web in ecosystems. In this study, we classified food web models to static models such as Ecopath and dynamic models such as AQUATOX. We presented characteristics of several different types of food web models in each category, and reviewed their applications used in aquatic ecosystems. Finally, we presented issues to be considered to develop food web models.