In this study, we investigated and analyzed the impact of changes in driving speed and inter-vehicle distance on users’ perceived tension during autonomous vehicle operation. To this end, a survey experiment was conducted for both urban roads and highways. The results show that the greatest changes in perceived tension occurred in the range of 50–70 Km/h and 50–70 m following distance on urban roads, and in the range of 80–100 Km/he and 60–80 m following distance on highways. Furthermore, modeling user behavioral responses to perceived tension based on changes in speed and following distance revealed that linear models best described the relationship for speed on both urban roads and highways. For the following distance, a quadratic model was the most suitable for urban roads, whereas a logarithmic model best fit the highway data. These findings are expected to contribute to practical operational guidelines for autonomous vehicles by alleviating users’ psychological discomfort and enhancing public acceptance. Future research will extend this study using a driving simulator to examine user responses in more realistic driving environments.

Smart factory technology, a core component of the Fourth Industrial Revolution, demonstrates significant disparities in technological development across countries. To quantitatively assess these international technology gaps, this study proposes an integrated analytical framework that combines text mining-based topic modeling and social network analysis (SNA), using global smart factory-related patent data from 2017 to 2023. Approximately 4,300 patent documents (titles and abstracts) were collected through the GPASS system and preprocessed. Through Latent Dirichlet Allocation (LDA) modeling with optimized hyperparameters, major technology topics were identified. Semantic interpretation using ChatGPT and expert review enabled the assignment of precise topic labels, which were further mapped to CPC (Cooperative Patent Classification) codes to construct a standardized technology taxonomy. Subsequently, the network structures of topic and classification nodes were analyzed by country (China, the United States, and South Korea), and the relative importance of key technology areas was evaluated using centrality metrics such as degree, closeness, betweenness, and eigenvector centrality. The analysis revealed that, globally, the most central technology areas include manufacturing process management and control, IoT and data-driven decision making, and facility-based process optimization. At the national level, China showed a strategic focus on technologies related to product quality improvement and cost reduction, South Korea emphasized IoT-enabled technologies and equipment-level optimization, while the United States prioritized control systems and data-driven project management. By utilizing patent-based textual data, this study offers a novel methodology for quantitatively diagnosing structural differences in national technological capabilities. The proposed framework provides valuable insights for country-specific R&D planning and strategic decision-making in the field of smart manufacturing.

온도와 곤충 발육과의 관계는 생물학에서 오래된 핵심 주제이며, 하한임계온도와 온량상수를 기반으로 한 선형 적산온도 모형은 해충 발생 예측에 널리 활용되어 왔다. 그러나 이러한 모형은 중위 온도범위에서만 유효하며, 저온과 고온의 극단 온도에서는 발육률을 과소 또는 과대평가하 는 한계를 가진다. 이를 보완하기 위해 사인곡선 기반 적산온도 계산법과 수평제거법이 제안되었지만, 일중 최고온도가 최적온도나 상한임계온도 를 초과할 경우 유효온도가 여전히 과대평가된다. 본 리뷰는 하한, 최적, 상한의 세 임계온도를 도입하고, 최적온도에서 수평제거, 상한임계온도에 서 수직제거를 동시에 적용한 새로운 방법인 3임계온도 기반 사인곡선 이중제거법(시간별온도 이중제거법)을 제안하였다. 시간별온도 이중제거법 은 사인함수를 이용한 시간별 온도 추정을 통해 보다 정확한 유효온도 계산이 가능하며, 특히 고온조건에서 과대평가를 효과적으로 줄일 수 있었다. 최적온도와 상한임계온도 사이에서는 일부 오차가 남을 수 있으나, 기존 방식에 비해 실질적인 개선 효과가 있었다. 또한, 상한임계온도의 정의에 대한 혼란을 정리하고, 향후에는 비선형 발육모형을 통한 정밀 예측의 필요성도 제기하였다.

Water resources are a core component of Earth Science Education, and scientific modeling can be used to enhance students’ understanding of water resources. With recent shifts internationally toward standards-based science teaching and learning, researchers have noted the need for a deeper understanding of how teachers use curricula. The purpose of this study is to examine how science teachers interact with the curriculum and help better determine the role teachers’ conceptions of the curriculum play in how they implement the curriculum in teaching water resources. The concept of ‘curriculum use’ relates to the ways in which a teacher interacts with and is influenced by material resources constructed to support instruction. Further, this study focused on teachers’ perceptions of their role within the teachercurriculum relationship, where these might range from that of an enactor of a planned curriculum to that of a collaborator with curriculum materials, to better understand how their notions influence their curriculum use. Three teachers were purposely selected for a post-curriculum implementation interview following a professional development workshop with 21 science teachers. The interviews were analyzed using thematic analysis. Finally, in the context of the implementation of the curriculum, a better understanding of teachers’ experiences and interactions with the curriculum emerged which highlighted how curriculum resource designs can be improved to take advantage of how teachers work with curriculum materials.

The purpose of this paper is to investigate the vibration phenomenon occurring in the structure such as a ship with the hemispherical substructure and operating at fixed frequency, and to suggest the active vibration control method using the Fx-LMS algorithm to reduce vibration amplification. In order to study the possibility of reducing vibration in the hemispherical structure, the active vibration control model was developed and a vibration control experimental device for the hemispherical structure was constructed. The narrowband Fx-LMS algorithm was developed to enable precise real-time control at a specific frequency, and the secondary path for dynamic control was modeled with two coefficients per frequency. The experimental device is equipped with three exciters, six 3-axis actuators, and six 3-axis error sensors, which can acquire 18 error sensor signals. Real-time secondary path tracking was possible with the secondary path consisting of two coefficients and the control algorithm, and effective vibration control performance was confirmed through this. And the experimental results of active vibration control of the exciter for three frequencies showed that the exciter vibration was reduced by a minimum of 63.7% and a maximum of 97.7%, which shows the possibility of reducing the vibration of the structure in real time using the proposed method.

This paper reviews ordinal decision tree algorithms for ordinal classification, exploring theoretical foundations, key algorithms (MDT, QMDT), specialized splitting criteria (Ordinal Gini, Weighted Information Gain), and ensemble methods. It discusses applications in healthcare and social sciences, highlighting interpretability and flexibility while acknowledging overfitting and instability. As implications for future research, this study points out advantages such as interpretability and flexibility, and limitations such as overfitting and instability.

Ainsliaea acerifolia, a perennial herbaceous plant endemic to forested regions of the Korean Peninsula, has drawn attention for its bioactive properties and potential as a functional food and medicinal resource. Despite its ecological and economic value, little is known about its spatial distribution or habitat preferences under changing climatic conditions. This study aims to quantify the current and future habitat suitability of A. acerifolia in southeastern Korea—including Gyeongsangnam-do, Busan, and Ulsan—using the MaxEnt (Maximum Entropy) species distribution model. A total of 217 presence records were compiled from both GBIF data and field surveys, and seven key environmental variables were selected through multicollinearity screening. Model performance was robust (mean AUC = 0.845), and key predictors included topographic roughness (TRI), precipitation of the driest month (Bio14), and mean diurnal range (Bio2). Under current climate conditions, 31.5% of the study area was identified as suitable habitat (≥0.222), with only 4.7% categorized as core habitat (≥0.6). Future projections under SSP1-2.6, SSP2-4.5, and SSP5-8.5 scenarios indicated substantial habitat contraction, particularly in coastal and lowland areas, with refugial zones likely to persist in mid-elevation inland mountains (500–900 m). These findings suggest that A. acerifolia is highly sensitive to climatic variability and emphasizes the urgent need for conservation strategies focused on climate-resilient refugia and ecological corridors. The study provides a spatial framework for species conservation planning under future climate uncertainty.

Efficient donor-acceptor (D-A) molecular scaffolds should be developed for the advancement of organic solar cells (OSCs). Density functional theory (DFT) and time-dependent density functional theory (TDDFT) studies provide an effective methodology to perform initial studies to design and investigate D-A molecular systems. Two fluorine-substituted bis-benzothiadiazoles (FBBTs) are designed and optimized using the DFT method. The results show better planarity for FBBT2, which is attributed to π-extension between the FBBT units. A series of D-A small molecules CB1-4 are designed utilizing FBBT2 to study the effect of systematically substituting carbazole donor and cyano-based acceptor groups on the optoelectronic properties of FBBT. DFT calculations are performed using the B3LYP functional. The designed D-A scaffolds exhibit systematic tuning of the highest occupied molecular orbital (HOMO) and the lowest unoccupied molecular orbital (LUMO), HOMO-LUMO gap (from 2.333 eV to 1.825 eV). The observed HOMO-LUMO gap follows the trend CB1 > CB2 > CB4 > CB3. The Voc (open-circuit voltage) and power conversion efficiency (PCE) for CB1-4 are presented with the PC71BM acceptor. The overall trend observed for the Voc follows the order CB1 < CB4 < CB2 < CB3. The PCE trend observed using the Scharber model follows the trend CB3 > CB4 > CB2 > CB1. The results show that end cap modeling of π-extended FBBT with cyano-based acceptor groups significantly improves the observed PCE and Voc.

Due to the limited experimental data on the seismic performance of concrete-encased steel columns, standardized guidelines for nonlinear modeling parameters and acceptance criteria have not yet been developed. This study utilized analytical and numerical methods to predict the nonlinear behavior of concrete-encased steel columns with H-shaped steel sections. The findings of this study have direct and practical implications for the design and evaluation of concrete-encased steel columns. For instance, for concrete-encased steel columns constructed with normal-strength concrete and subjected to low-to-moderate axial load ratios, the yield rotation angle can be determined through fiber-based section analysis and analytical equations, and the nonlinear modeling parameter can be evaluated based on section analysis and the proposed empirical equation. For concrete-encased steel columns with high-strength concrete or high axial load ratios, inconsistencies between section analyses and experimental results are observed. Accordingly, the nonlinear modeling parameter a can be evaluated using the proposed empirical equation. The empirical equation was conservatively developed based on the modeling parameter criteria for reinforced concrete columns in ASCE 41-13.

Fabry disease is an X-linked lysosomal storage disorder caused by GLA mutations, leading to a deficiency in α-Galactosidase A activity and subsequent accumulation of globotriaosylceramide (Gb3). This accumulation contributes to progressive multiorgan dysfunction, with cardiovascular complications, particularly endothelial dysfunction and left ventricular hypertrophy being major drivers of disease morbidity and mortality. Although enzyme replacement therapy is currently the standard treatment, its effectiveness is limited in addressing advanced cardiovascular pathology. To better understand Fabry-associated vascular and cardiac phenotypes, an isogenic human induced pluripotent stem cell (hiPSC) model in which GLA was knocked out was developed using CRISPR/ Cas9. GLA-knockout (GLA-KO) hiPSCs were differentiated into endothelial cells (ECs) and cardiomyocytes (CMs) to evaluate disease-relevant phenotypes in vitro . GLA-KO ECs exhibited normal morphology and differentiation capacity but showed markedly impaired tube formation, high expression of inflammatory genes ICAM1, VCAM1, and SELE, and increased mitochondrial and cytoplasmic reactive oxygen species levels. GLA-KO CMs demonstrated enlarged cell size and nuclear translocation of NFATC4, consistent with hypertrophic remodeling. Together, these findings recapitulate key features of Fabry vasculopathy and cardiomyopathy in a genetically defined, human-derived system. This platform enables direct investigation of Gb3-induced oxidative and inflammatory mechanisms and provides a valuable model for the preclinical evaluation of therapeutic strategies targeting the cardiovascular manifestations of Fabry disease.

This study proposes a real-time content design pipeline optimized for Unreal Engine, integrating generative AI-based image creation with AI-assisted 3D modeling tools. The pipeline aims to streamline the production of high-quality assets for real-time applications, including games and simulations. Two types of subjects were selected: a bust combining organic character features, and a stone slab characterized by planar and symmetrical structure. Multi-angle image data were first synthesized using advanced generative AI models to simulate diverse viewpoints. These were then processed using AI-enhanced photogrammetry and modeling tools to reconstruct detailed 3D meshes and extract base textures. Post-processing steps, including mesh decimation, UV unwrapping, and texture baking, were performed to ensure compatibility with Physically Based Rendering (PBR) workflows used in Unreal Engine. The final assets were successfully imported into Unreal Engine, demonstrating visual fidelity and performance suitability in a real-time environment. The study confirms the pipeline’s potential for accelerating asset development and suggests promising future directions in AI-driven digital content creation.

In this paper, poly(glycolic acid–co-DL–lactic acid) (PGDLLA)/poly(ɛ-caprolactone) (PCL) incompatible nanocomposites were combined with multiscale modeling (MSM) in a ratio of 80/20. Since the behavior and mechanical properties of blends depend significantly on the interphase region, the compatibilizer poly(l,l-lactic acid–co-ɛ-caprolactone) (P(lLA-co-ɛ-CL)) was used to improve compatibility and graphene oxide (GO) was used to increase the interphase strength of PGDLLA matrix/PCL. This work was done by mixing solvent to achieve the optimum disperse of GO in the matrix. The investigation of interfacial phenomenon by the theoretical interfacial models is important. Under the assumption of constant modulus and elastic deformation in the zero interface region, the predictions in this region are more unreliable when the calculations of experimental mechanical properties are analyzed in detail. In this study, PGDLLA/P(lLA-co-ɛ-CL)/PCL compounds were compared with the MSM approach to predict the plastic deformation in the stress–strain behavior. In contrast to the hypothesis that a simple look at the interphase area in nanocomposites, a finite element code is proposed to evaluate the efficiency of the interphase area. Both experimental results and FEM analysis showed that Young’s modulus increases by incorporating GO into GO/PGDLLA/P(lLA-co-ɛ-CL)/PCL nanocomposites; the amount of increase for incorporating 1 phr GO is about 61%.

This paper presents an 2 kW commercial Li-ion(lithium-ion) battery model using PSIM simulation. An in-house designed transformer was employed to measure the leakage and magnetic inductance and determine the resonant frequency. The LLC resonant converter’s transfer function was derived using the FHA method, and voltage gain characteristics were analyzed concerning frequency, Q factor, and inductance variations. The CC-CV charge mode was evaluated at different C-rates, targeting the charging voltage for e-bikes. The results demonstrated that battery voltage increased with SOC until reaching the final charging voltage.