National Taiwan Normal University

The electrochemical reduction of CO 2 (eCO 2 RR) presents a promising strategy for mitigating carbon emissions while generating valuable fuels and chemicals. However, the limited chemical stability of metal–organic frameworks (MOFs) in electrochemical environments remains a significant challenge. This study explores the structural robustness and catalytic performance of MOF‐303 and Al‐TCPP frameworks, modified via Cu and Co metalation, for CO 2 reduction applications. A comprehensive investigation of their physicochemical properties, electrochemical stability across diverse electrolyte conditions, and catalytic efficiency was conducted. Structural integrity was analyzed using powder x‐ray diffraction, scanning electron microscopy, Brunauer–Emmett–Teller, x‐ray photoelectron spectroscopic, and x‐ray absorption spectroscopic techniques, revealing improved stability and electronic tuning upon metalation. Electrochemical studies demonstrated that Cu‐functionalized materials favored hydrocarbon production (CH 4 , C 2 H 4 ), whereas Co‐modified catalysts exhibited high selectivity toward CO formation with suppressed hydrogen evolution. Stability assessments across a broad pH range confirmed superior resilience of Cu‐modified MOFs, particularly in neutral and mild alkaline environments. The findings highlight the critical role of post‐synthetic metalation in enhancing MOF stability and catalytic selectivity, paving the way for scalable and durable MOF‐based eCO 2 RR technologies. This work provides valuable insights into rational MOF design strategies for efficient CO 2 electroreduction, contributing to sustainable carbon conversion pathways.

Wood superhydrophobicity is an advantageous characteristic for various industrial and mechanical applications. In this study, a superhydrophobic surface on veneer wood was achieved by grafting (1H,1H,2H,2H-perfluorodecyltriethoxysilane) fluorosilane molecules on its surface using a simple soaking technique at ambient conditions. The 24-h soaking time achieved the superhydrophobic surface with a contact angle > 150° when measured 1 week after soaking and was stable for up to 4 weeks. As weeks progressed, the 4-h and 8-h soaking showed improvement in water contact angle with the 8-h going as high as 166 ± 0.2°. The FTIR and Raman spectroscopy analyses on the veneer wood surface reveal the attachment of the OH bonds of the wood cellulose to the fluorosilane molecules. Secondary ion mass spectra (SIMS) show a uniformly distributed fluorine map confirming the formation of the low surface energy. The FTIR spectroscopy, Raman spectroscopy, and SIMS help elucidate the structure of the fluorosilane functionalization on veneer wood.

Diffraction calculations, which are fundamental in wave optics, can be significantly accelerated using Fourier transforms. However, they often suffer from ringing artifacts, also known as the Gibbs phenomenon, owing to the discontinuous borders of the calculation windows. Various techniques to suppress ringing artifacts have been proposed, but are typically time-consuming and require additional memory resources. This study proposes a fast method for reducing ringing artifacts using Fresnel integrals without necessitating additional memory. A comparison between the proposed and conventional techniques demonstrates that the proposed method achieves comparable image quality to conventional methods. Moreover, it offers the advantages of fast time and low memory usage. This paper demonstrates that the proposed method can be used to efficiently reduce ringing artifacts in reproduced images of two inline holograms optically acquired with laser and light-emitting diode sources.

Chiral halide perovskites have attracted considerable attention due to their intrinsic chirality‐induced circular dichroism (CD), circularly polarized luminescence (CPL), and spin selectivity. However, chiroptical activities of low‐dimensional lead‐free chiral halide perovskites are hardly observed, especially for those with white‐light emission. Herein, lead‐free halide perovskites with different ratios of 0D Cs3Cu2I5 and 1D CsCu2I3 are realized. Chiroptical activities are introduced into these films by post‐treatment with r‐/s‐methylbenzylammonium iodide to realize lead‐free chiral halide perovskites. The absorption, photoluminescence, photoluminescence excitation, CD, and CPL spectra of these films are investigated. The Commission Internationale de L’Eclairage chromaticity coordinates (0.33, 0.33) are obtained when the excitation wavelength is 300 nm. Large Stokes shifts and broadband emission are observed and attributed to the presence of self‐trapped excitons. At room temperature, intrinsic chirality‐induced CD signals are observed without the application of an external magnetic field, indicating the presence of chirality in the low‐dimensional lead‐free chiral halide perovskites. Room‐temperature CPL is also observed from the low‐dimensional lead‐free chiral halide perovskites, but only from the Cs3Cu2I5 component. This is attributed to the fact that CsCu2I3 does not produce CPL and spin‐polarized excitons do not transfer from Cs3Cu2I5 to CsCu2I3.

Diagnostic classification models (DCMs) constitute a subset of restricted latent class models in which latent classes are constrained by an expert-specified Q matrix reflecting students’ mastery of the psychological attributes associated with items. In instances where uncertainty exists in the attribute elements of items specified by the Q matrix, the accurate estimation of the Q matrix is imperative for ensuring accurate person and item estimates. This paper investigates the application of the open-source NIMBLE (Numerical Inference for Hierarchical Models Using Bayesian and Likelihood Estimation) package in R software to infer the Q matrix while incorporating model constraints. Snippets of NIMBLE code illustrate the Q matrix estimation in DCMs, followed by parameter-recovery simulation studies and empirical data analyses. The research findings show a high degree of parameter recovery in simulation studies and provide insightful analyses of empirical data. This paper demonstrates that researchers can now effectively engage with DCMs using NIMBLE, particularly in scenarios where the Q matrix is uncertain. This eliminates the need to laboriously develop and code intricate parameter estimation algorithms, thus enabling researchers to confidently prioritize model development and statistical analysis.

Background Due to the rapid development of artificial intelligence (AI) and the widespread adoption of online learning post‐COVID‐19, the metaverse has become an important strategy for innovative teaching. Objectives This study aimed to investigate the impact of the metaverse on learning engagement, learning emotions, and creative performance in AI applications by analysing academic emotions through facial expressions. Methods The study was conducted as a non‐equivalent group pretest–posttest quasi‐experimental construct involving 97 students from a public high school. The experimental teaching theme focused on AI image recognition and speech recognition, with the experimental group receiving online metaverse instruction and the control group receiving instruction through Google Meet. Results and Conclusion Key findings include the following: the metaverse significantly and positively influenced cognitive, emotional, and social dimensions of learning engagement, but no impact was observed on the behavioural dimension; the metaverse had a substantial impact on the creative performance of AI application design, particularly in the empathy, definition, ideation, and testing stages; and the metaverse significantly affected academic emotions, with increased expressions of anger and sadness observed, particularly during the empathy, definition, and ideation stages of design thinking. Thus, the results of this study provide a pedagogical foundation for the adoption of the metaverse and auxiliary tools in teaching.

In this paper, we propose a general method for designing Takagi–Sugeno (T-S) fuzzy model controllers, applicable to a general class of nonlinear systems represented in state-space form. The method is an automated controller design process that introduces the BLOCK concept. Through the automatic division of BLOCKs, the system is divided into more subsystems, and corresponding fuzzy rules and membership functions are automatically generated, significantly shortening the development time for systems with known system models. According to T-S fuzzy theory, nonlinear systems are decomposed into multiple linear subsystems governed by fuzzy rules. Unlike conventional methods that rely on linear matrix inequalities (LMI), which may suffer from infeasibility or excessively large controller gains and generally involve higher computational complexity, we integrate the linear quadratic regulator (LQR) approach to enhance stability and performance. The LQR method offers a more computationally efficient solution while still achieving effective control. The effectiveness of the proposed automated process is demonstrated through its application to a two-link robotic manipulator, showcasing its ability to improve tracking accuracy. Experimental results confirm that the proposed controller outperforms conventional PID control, achieving reduced tracking errors and demonstrating the practicality of the method for broader nonlinear control applications.

Background Probiotic Bacillus coagulans (BC) may have an impact on gastrointestinal protection. This study was designed to investigate the BC effects on Helicobacter pylori ( H. pylori ) induced gastric inflammation in mice and acid-induced lower esophageal sphincter (LES) dysfunction in rats. We determined the oxidative stress/apoptosis/autophagy signaling pathways in H. pylori -induced gastric inflammation and HCl-evoked LES inflammation. Methods H. pylori -induced gastric inflammation was used in 40 mice and HCl-evoked LES inflammation in 40 Wistar rats. Western blot, immunohistochemistry and cytokine array were used to determine the pathophysiologic mechanisms. Results H. pylori increased leukocyte infiltration mediated inflammation and the expression levels of gastric cytokines, 3NT/4HNE-mediated oxidative stress and Bax/Caspase 3-mediated apoptosis, but decreased Beclin-1/LC3-II-mediated autophagy in the mice gastric mucosa. BC treatment decreased inflammation, cytokines release, oxidative stress and apoptosis and reversed autophagy in H. pylori infected gastric mucosa. To replace the antibiotic therapy, BC TCI803 was selected to inhibit H. pylori infection for commercial interests. Saline esophageal infusion evoked an increase in LES pressure and efferent vagus nerve activity during the emptying phase. However, HCI dysregulated LES motility esophageal infusion by a decrease in threshold pressure, intercontraction interval and an increase in efferent vagus nerve activity. BC treatment significantly recovered the level of threshold pressure, intercontraction interval and depressed the enhanced efferent vagus nerve activity. In vitro LES wire myography data displayed that HCl treated LES significantly decreased the contractile response to acetylcholine. BC treatment significantly restored the contractile response to acetylcholine in LES wire myography. LES after HCl stimulation significantly increased leukocyte infiltration-mediated inflammation, whereas BC treatment effectively reduced the leukocyte infiltration-mediated inflammation in the HCl treated LES. Conclusion BC via anti-oxidation and anti-inflammation confers gastroesophageal protection against H. pylori involved oxidative stress/inflammation/apoptosis/autophagy signaling in mice with gastric inflammation and HCl induced LES dysregulation and inflammation.

Vehicular ad hoc network (VANET) has widely been considered as a promising wireless networking technology to provide a variety of services or applications for the development of intelligent transportation systems (ITS). Messages are delivered between vehicles in a VANET for exchanges or updates of information. However, a sparse VANET may frequently suffer from network disconnections. In this paper, the routing of downstream messages in network disconnections is discussed, and the distribution of the delay incurred during the restoration of a network disconnection is calculated, where the Laplace transform and the inverse Laplace transform are utilized to calculate the distribution of the sum of random variables. Numerical results show that our proposed analysis provides better accuracy in predicting the end-to-end delay of a connection that may contain more than one network disconnection.

The literature reveals a gap in the understanding of the impact of meaningful work (MW) and strength use (SU) on teachers’ job performance (JP), which has not been widely studied. Additionally, the roles of SU and work engagement (WE) as mediating variables affecting teachers’ perceptions of MW in JP are less explored. This study addresses these gaps by determining the effect of MW on teachers’ JP and the roles of WE and SU in mediating the effect of MW on JP, which is evident. A quantitative approach was employed using a cross-sectional study design, applying partial least squares structural equation modeling. Data were obtained through a survey of 392 private high school teachers in Jakarta, Indonesia, using a convenience sampling method. The key findings of this study indicate that while MW has the smallest direct effect on JP, it is the construct with the highest importance and performance. WE and SU successfully mediate the effect of MW on JP, significantly enhancing the influence of MW on JP. Consequently, school leaders are advised to enhance teachers’ WE and SU by adjusting teaching loads according to educational backgrounds, providing incentives for additional work, supporting competency improvement, and encouraging knowledge sharing among teachers.

Artificial intelligence (AI) in biomedicine has gained significant attention, and its fusion with biology offers exciting possibilities. Understanding students' perspectives on AI is crucial for developing appropriate lessons. This study surveyed biology undergraduates and postgraduates in Taiwan ( n = 71) and Germany ( n = 51) to explore their perspectives on AI in precision medicine and life sciences and its integration into their education. Exploratory Factor Analysis identified dimensions such as perception of benefits, risks, ethics, acceptance, and willingness to learn AI. The findings revealed that about 70% of students were aware of AI discussions in the field, but 35% admitted lacking basic knowledge of the technologies. Notably, there was a positive correlation between perceiving benefits and the willingness to learn AI in both countries. Interestingly, Taiwanese students expressed more concerns about AI risks than German students but showed greater acceptance and willingness to learn AI. Additionally, a negative correlation between risk perception and willingness to learn AI was found among German students but not among Taiwanese students. This difference may relate to variations in AI education between the countries. Given the high willingness to incorporate AI into biology curricula, the field of biology should lead in educating students about these technologies.

The process of error detection, explanation, and correction is essential in project making. Such structured error-based learning is thought to occur via active exploration of metacognitive processes. To understand how error-based learning can strengthen metacognitive performance, this study focused on hands-on project making in a STEAM contest. According to trait activation theory, participants practice metacognitive skills to continue improving their project functions, this study explored how participants’ motivation in a hands-on project affected the three types of metacognitive performance: monitoring of cognition, knowledge of cognition, and regulation of cognition. This study utilized purposive sampling and delivered a questionnaire to participants in a STEAM contest called PowerTech. Confirmatory factor analysis and structural equation modeling were performed to verify the research model. The results indicated that the intrinsic motivation to attend the contest was positively related to the three types of metacognitive performance, and negatively related to anxiety about losing the contest. The implication of this study is that when involved in a hands-on project, metacognitive ability can be enhanced through the practice of detection, explanation, and correction while working on a project.

Reading motivation significantly influences the academic success of American college students. Existing literature often treats American students as a homogeneous group and overlooks the impact of diverse ethnic backgrounds on reading motivation. To address this gap, the present study investigated the relationships among reading motivation, reading amount, and reading comprehension in a sample of 1360 American college students representing three ethnic groups: White American, African American, and Hispanic American. Additionally, we explored the role of reading amount as a mediator in the relationship between reading motivation and reading comprehension, and assessed the magnitude of these effects across the three ethnic groups. Path analysis for each ethnic group revealed a direct effect of expectancy on reading comprehension for all groups. Furthermore, indirect effects of value and cost on reading comprehension were observed among White American and Hispanic American college students, whereas African American college students exhibited a direct effect of cost on reading comprehension. Multigroup path analyses showed similar magnitudes of direct and indirect effects across the three ethnic groups. Our findings provide new evidence of both commonalities and differences in reading motivation among American college students from different ethnic backgrounds.

Background/Objectives: Dementia is a growing public health issue, especially in rapidly aging societies like Taiwan, where nearly 10% of adults over 65 show signs of cognitive decline. Given that mild cognitive impairment (MCI) serves as a critical stage for early intervention, this study examined the feasibility and preliminary effectiveness of a virtual reality (VR)-based dementia prevention program, specifically designed based on self-regulated learning (SRL) principles to enhance dementia knowledge, health literacy, and self-efficacy among older adults with MCI. Methods: A pilot randomized controlled trial (RCT) was conducted with 60 older adults aged 65 and above with MCI. Participants were randomly assigned to either an experimental group, which received a VR-based dementia prevention program, or a comparison group, which received routine paper-based educational materials. Results: The experimental group demonstrated significant improvements in overall dementia knowledge and all subdomains. Significant gains were also observed in critical health literacy and self-efficacy, though no significant changes were found in overall health literacy. Conclusions: The preliminary findings suggest that the SRL-informed VR program showed initial effectiveness in enhancing dementia knowledge, critical health literacy, and self-efficacy among older adults with MCI, highlighting its potential as an innovative approach to dementia prevention education.

This study examines how beat gestures and humming influence the pronunciation skills of Taiwanese students learning English. Ninety-three Mandarin-speaking participants were assigned to one of three groups: speech-only practice, practice with beat gestures, or practice with humming. The study was conducted over twelve days, consisting of a six-day pre-treatment phase followed by a six-day pronunciation training period, during which participants engaged in daily practice using TED Talk videos adapted to their assigned experimental condition. Pronunciation was assessed before and after training. The results showed that both beat gestures and humming led to significant pronunciation improvements compared to speech-only practice. While no statistically significant differences emerged between the two techniques, effect size comparisons suggest that beat gestures were particularly effective for intonation and rhythm, whereas humming showed a slight advantage in improving segmentals and stress patterns. Participant feedback indicated that beat gestures were more engaging and intuitive, whereas humming required more effort to master but was ultimately effective. This highlights a distinction between learner engagement and cognitive demands in pronunciation learning. These findings suggest that incorporating nonverbal elements, such as beat gestures and humming, into pronunciation instruction can enhance both phonological skills and learner motivation, depending on the instructional focus.

The geographic center of El Niño has shifted from the tropical eastern Pacific (EP) in the 20th century to the tropical central Pacific (CP) in the 21st century. Analyzing data spanning 1948–2018, this study uncovers notable alterations in the impact of the changing El Niño patterns on California market squid (Doryteuthis opalescens) landings. While the traditional EP El Niño in the 20th century significantly reduces squid landings, this impact diminishes with the ascent of the CP type of El Niño in the 21st century. Remarkably, the CP‐I type of El Niño, a specific variant where warming occurs predominantly in the central Pacific and is often less intense but more frequent than traditional El Niño events, can even amplify squid landings. These transformations stem from variations in sea surface temperature, trade winds, and Sverdrup transport associated with different El Niño types. These findings suggest that the fishery community should consider developing adaptive approaches to address the evolving impacts of El Niño.

Recent research has confirmed that growth mindsets (GMs) have a positive effect on reading performance and attitudes towards engagement. However, due to the scarce use of second language (L2) texts as reading materials, if mindsets are relevant to L2 reading processes remain unclear. This study used an eye tracker, questionnaires, and a reading comprehension test to explore the relationship between readers’ language mindsets and levels of concentration and willingness to read L2 academic texts, reading processes, and comprehension performance. Data were collected from 107 college students with English as a second language. Participants filled out the Language Mindsets Inventory, read an academic English text with their eye movements recorded, and completed comprehension post-tests. Pearson’s correlation analysis revealed that students who considered language intelligence malleable also thought their English learning ability was changeable, had higher levels of concentration and willingness to read academic articles, and had better general English reading ability than those whose language intelligence level was fixed. Moreover, multiple regression analysis revealed that students approaching the growth mindset end had a shorter single-mean fixation duration (i.e., faster decoding) when reading the academic text, and this eye-movement measure could further predict their academic English reading comprehension outcomes, with general English ability providing mediating effects. Overall, the findings suggest that students’ language mindsets are directly relevant to L2 academic text reading processes, concentration, and willingness levels and indirectly relevant to reading comprehension performance.

Real‐time analysis of the structural formation of 2D and 3D perovskites in solution is challenging due to the sensitivity of perovskite intermediates to environmental conditions and their rapid growth. Conventional techniques often require stringent sample preparation, limiting the ability to study dynamic behaviors in solution. In this study, small‐ and wide‐angle X‐ray scattering (SWAXS) is employed to analyze the morphology and dynamics of 2D and 3D perovskite nanostructures in their native colloidal state. Unlike previous studies that attribute CsPbI3 degradation to delta‐phase formation, SWAXS revealed preexisting 2D Cs7Pb6I19 nanosheets in pristine CsPbI3 colloidal solutions. In situ SWAXS tracked the dynamic transformation of these structures during recrystallization in diluted solutions. Adding bis(trimethylsilyl)sulfide (TMS) disassembled the 2D nanosheets, while subsequent recrystallization in a poor solvent formed highly crystalline Cs7Pb6I19 nanosheets. The recrystallization dynamics aligned with crystal growth theory, with TMS concentration playing a critical role. Higher TMS concentrations slowed recrystallization, promoting stable lattice formation and enhanced crystallinity, resulting in bright yellow emission. Conversely, lower concentrations accelerated recrystallization, causing structural damage and limiting high‐crystallinity growth. This study highlights the importance of controlling recrystallization rates through TMS concentration to optimize the crystallinity and optoelectronic properties of perovskites, offering insights into improving their performance.