Chuncheon National University of Education

Microgravity profoundly influences cellular morphology and function, yet ground-based simulation requires systems capable of randomizing the gravity vector. A dual-axis rotating machine (RM), such as a clinostat and random positioning machine (RPM), achieves quasi-isotropic gravitational averaging, but its quantitative optimization remains unclear. Here, a computational-experimental framework was established to evaluate dynamic isotropy of a dual-axis RM. Gravity vector trajectories were simulated across rotation ratios, and five metrics-Spherical Coverage (C), Cumulative Bias (H), Normalized Shannon Entropy (H/Hₘₐₓ), Mean Resultant Length (R), and Degree of Gravity Dispersion (DGD)-were integrated into an isotropy index (Sₒₚₜ). The isotropy peaked within an asynchronous range (4.0:3.8, 4.0:3.6, and 4.0:3.4rpm), where gravity vectors exhibited uniform spherical coverage and minimal bias. To further assess the influence of rotational strength beyond the rotational ratio, an additional experiment was conducted using Huh7 hepatocellular carcinoma spheroids. Under high-speed random rotation (~ 4.0rpm), cells formed compact, circular spheroids, whereas low-speed (~ 1.0rpm) or static cultures produced irregular aggregates. These findings indicate that not only the ratio between dual-axis rotations but also the absolute rotational intensity critically affects isotropy and cellular morphogenesis under simulated microgravity. This integrative framework establishes a quantitative foundation for optimizing dual-axis rotating machines.

Recently, with the rapid growth of wearable healthcare devices, there has been an increasing demand for transparent and flexible electrode technologies that can adhere stably to curved and irregular surfaces while maintaining signal stability during long-term measurements. In this study, we propose a transparent and flexible CNT–PDMS based micro-column electrode that incorporates microscale protrusions to enable multi-point contact, thereby reducing contact impedance and enhancing signal stability. The proposed electrode features a continuous monolithic structure integrating an upper micro-column layer with a lower grid framework, which expands the effective contact area and uniformly distributes contact pressure on curved surfaces. CNT content optimization experiments (5–25 wt%) confirmed that a stable conductive pathway was established at 20 wt%, which was selected as the final composition. ECG signal quality was comparatively evaluated under identical conditions using commercial Ag/AgCl electrodes (gel removed), sheet-type electrodes, and micro-column electrodes with diameters of 480 μm, 690 μm, and 1,020 μm. The 690 μm micro-column electrode exhibited the best performance, with RMS 0.75% higher and SNR 4.7 dB greater than the commercial Ag/AgCl electrode. These results demonstrate that stable ECG signal acquisition can be achieved without conductive gel in both initial and long-term measurements, highlighting the electrode’s high applicability in curved-surface environments, wearable devices, and in-vehicle biosignal monitoring applications.

Abstract The rapid progression of science and technology has brought both remarkable conveniences and innovations and potential risks to us. To address these risks within science education, this study aims to identify the tendency of students’ risk perceptions across different technologies. For this purpose, we developed a survey addressing three key components of risk perception (i.e., risk recognition, risk assessment, and risk management) and the educational need for risk education. 311 responses were collected from elementary, middle, and high school students and statically analyzed. The results indicated that students showed various risk perception patterns depending on the technology. There were significant perception gaps between boys and girls regarding vaccines and antimicrobial technology. It was also found that high school students’ perceptions of the benefits of the technologies were higher than elementary and middle school students’ perceptions. Based on these findings, we discuss pedagogical implications for risk education in science classrooms.

Research on equity has received a great amount of attention in the field of mathematics education. Although various review studies have focused on race/ethnicity issues in mathematics education, they rarely examined how the studies on race/ethnicity issues in mathematics education have evolved over time. This study examined research topics and trends of race/ethnicity studies in mathematics education while drawing on a social-ecological model. We collected 920 articles in the field of mathematics education that are relevant to the issue of race/ethnicity during the last 2 decades and implemented a topic modelling method. Findings include 11 latent topics, which were classified into 4 levels of the social-ecological model: individual (Growth, Identity), interpersonal (Immigrants, English language learners), community (Kindergarten, Course taking and college, Culturally responsive teaching, Intervention, School programme and instructional practices), and societal (Stereotype threat, Segregation). Among the topics, Identity and Stereotype threat were getting more attention as hot topics, while Course taking and college and School programme and instructional practices are becoming gradually less popular. The implications were discussed related to equity issues in the field of mathematics education.

This paper presents a novel approach for finding the most semantically similar conversational sentences in Korean and English. Our method involves training separate embedding models for each language and using a hybrid algorithm that selects the appropriate model based on the language of the query. For the Korean model, we fine-tuned the KLUE-RoBERTa-small model using publicly available semantic textual similarity datasets and used Principal Component Analysis (PCA) to reduce the resulting embedding vectors. We also selected a highly-performing English embedding model from available SBERT models. We compared our approach to existing multilingual models using both human-generated and large language model-generated conversational datasets. Our experimental results demonstrate that our hybrid approach outperforms state-of-the-art multilingual models in terms of accuracy, elapsed time for sentence embedding, and elapsed time for finding the nearest neighbor, regardless of whether a GPU is used. These findings highlight the potential benefits of training separate embedding models for different languages, particularly for tasks involving finding the most semantically similar conversational sentences. We expect that our approach will be used for diverse natural language processing-related fields, including machine learning education.

Postulating that academic papers can positively impact the actual teaching practices of science teachers, this study analysed the process of understanding and utilising academic papers by science teachers to teach scientific creativity in their schools. The 45–hour graduate course of three science teachers was explored to identify the difficulties teachers encountered in trying to understand academic papers and to discover how to solve these difficulties. Second, which aspects should be considered when developing teaching materials for scientific creativity to be used in schools were analysed. A transformation model of an academic paper was proposed to understand this process, and the results were organised accordingly. According to this model, it was emphasized to translate academic papers from a general and abstract state to a local and concrete state. Therefore, the role of science educators as knowledge translators was discussed for more practical and effective use of academic papers in school. This study is expected to contribute to research-based teaching by linking academic research with teaching practice. Keywords: case study, research-based teaching, scientific creativity, teacher’s learning process, teaching plan

ABSTRACT Utilisation of instructional videos for science teaching has become more widespread due to the expansion of online teaching and learning environments and growing awareness of benefits of videos, such as enabling use of effective multiple representations. With this in mind, this study aimed to examine features of instructional videos for teaching scientific inquiry, a key element of science education, and learners’ engagement, a crucial issue in instruction in terms of representational strategies used. We analysed 16 instructional videos for science teaching generated by pre-service teachers. We found that the instructional videos tended to focus on posing a question related to a phenomenon and constructing its explanation conceptually rather than conducting investigations and interpreting the data. It was also found that there were alternations between providing relevant and conceptual resources and affording learners opportunities to answer questions verbally and visually to prompt their engagement. Various representational strategies, such as summarising, comparing, highlighting, sequencing, and presenting vivid phenomena, were also employed for better teaching scientific inquiry as a part of learners’ ongoing cognitive activities. Based on the findings, we argue that there is potential for using instructional videos for teaching science, considering representational strategies in terms of scientific inquiry and learners’ engagement.