National University

The demand for portable real-time monitoring technologies for air quality and hazardous gas detection has significantly increased due to the growing interest in healthy living. In particular, nitrogen dioxide (NO 2 ) is a major contributor to air pollution in urban areas, and its concentration can fluctuate rapidly in a short period of time due to traffic emissions and industrial activities. Therefore, it is necessary to develop an ultra-sensitive sensor with fast response and recovery at room temperature. In this study, we demonstrate an NO 2 gas sensor operated at room temperature using Ag-decorated Sr 2 Nb 3 O 10 (ASNO) nanosheets, fabricated through a simple solution-based exfoliation process. This sensor exhibits excellent structural stability and an enhanced response of 935 % to NO 2 gas due to catalytic effect of the Ag decorated surface. It demonstrates fast response and recovery characteristics, which makes it a good candidate for reliable real-time monitoring and repeated use. Room-temperature NO 2 sensing using Ag-decorated 2D nanosheets supports sensitive and selective urban air pollution monitoring.

Visual speech recognition systems encounter significant challenges in multilingual nations such as the Philippines, where numerous regional languages, including Cebuano and Ilocano, feature distinct phonetic-visual characteristics. Deep learning models such as the Lip Reading Network and the Lightweight Crowd Segmentation Network have demonstrated strong performance with 3D Convolutional Neural Networks (CNNs). However, their substantial computational requirements restrict deployment on portable edge devices. We introduce a more efficient alternative that integrates a 2D Residual Network 50 architecture with a Long Short-Term Memory network and Connectionist Temporal Classification for lip-reading classification of Philippine regional languages. The proposed model is deployed on the Jetson Orin Nano, a high-performance edge device optimized for real-time inference through Compute Unified Device Architecture acceleration. Using a dataset of 2000 annotated videos encompassing 10 lexicons each for Cebuano and Ilocano, the model’s effectiveness was evaluated. Results achieved a regional language classification accuracy of 90%, with lexicon-level accuracies of 74% for Cebuano and 66% for Ilocano. This work represents a step toward developing accessible and scalable communication aids for deaf communities in linguistically diverse environments, leveraging transfer learning on pretrained models.

As artificial intelligence continues to reshape how knowledge is created, accessed and applied, teaching and learning across the educational areas are undergoing profound transformation. Entering 2026, educators face an urgent need to rethink instructional models, learning objectives and assessment practices to better support learners in increasingly complex, technology-rich environments. In this context, innovation in teaching and learning is no longer optional; rather, it calls for thoughtful, evidence-based inquiry into pedagogical approaches that can produce meaningful and lasting impact.Against this backdrop, we are pleased to announce the publication of JRIT&L Volume 19, Issue 1. This issue addresses a range of timely topics, including the use of ChatGPT in the classroom, project-based 6E learning, teachers’ gameful practices, modernization of photogrammetry curricula, AI-influenced STEM education and teacher resilience in teacher education. Collectively, these studies reflect a broader shift toward competency-based, learner-centered education, an emerging trend that is reshaping teaching and learning across both K–12 and higher education. To help lead this transformation, we encourage contributors to provide convincing evidence demonstrating how instructional models can cultivate learner competencies and drive reform in innovative teaching and learning.First, innovative teaching and learning increasingly emphasize student-centered approaches and authentic application in both K–12 and higher education. Educators are moving away from passive, isolated, content-driven instruction toward learning experiences that actively engage students in inquiry and problem solving. Prominent approaches include project-based learning grounded in real-world contexts and focused on practical outcomes, as well as inquiry-based learning that promotes questioning, exploration and discovery. In parallel, competency-based personalized learning models are gaining prominence, shifting the focus from time-based instruction to the development and demonstration of essential skills.Second, interdisciplinary STEAM and STEM education is becoming increasingly important, while traditional single-subject instruction faces growing limitations. Much contemporary learning is rooted in real-world scenarios, community challenges and engineering design problems that demand integrated knowledge and skills. These contexts are closely aligned with students’ career pathways and provide powerful opportunities to foster engagement and motivation. For educators, the challenge lies in designing learning environments that encourage cross-disciplinary thinking and guide students to address complex, authentic problems.Third, technology-enhanced learning will continue to play a crucial supporting and instrumental role in innovative education. These technologies will be increasingly used for personalized learning and to leverage data to support student learning analytics, helping students succeed. Importantly, with the advancement of artificial intelligence, the focus has shifted from viewing technology as a novelty to seeing it as a tool to enhance learning.Fourth, assessment practices are undergoing meaningful change. Authentic, performance-based assessment and formative feedback are gradually replacing traditional summative and formative assessment. Digital portfolios, project artifacts and continuous feedback enable students to demonstrate learning through meaningful processes while providing educators with rich evidence to inform curriculum design and instructional decision-making.Finally, teacher development and instructional models continue to evolve in response to these changes. Flipped classrooms, blended and flexible learning models, micro-credentials and open educational resources (OER) remain central to ongoing reform. At the same time, Universal Design for Learning (UDL) and social-emotional learning frameworks are being more fully integrated into curriculum design. Ensuring equitable, learner-centered instruction, particularly for young learners and diverse student populations, remains a critical priority across educational systems.Overall, the most influential trends in innovative teaching and learning emphasize authenticity, coherence and purpose. They connect learning to real-world contexts, integrate multiple disciplines, value credible evidence of learning outcomes and place learners’ needs, experiences and aspirations at the center of educational design. As we look ahead to 2026 and beyond, we hope that JRIT&L will continue to serve as a platform for rigorous scholarship that informs and advances meaningful innovation in teaching and learning.

Corneal neovascularization is a sight-threatening condition for which current treatments such as anti-VEGF agents are limited by invasiveness and side effects. We present the first non-viral, CRISPR/Cas9-based gene therapy delivered via topical eye drops that penetrates the cornea and inhibits pathological neovascularization. Cas9 ribonucleoproteins (RNPs) targeting the Vegfa gene were complexed with a liposomal carrier (lipofectamine) and administered to mice after alkali burn injury to the cornea. This approach achieved approximately 2% gene editing at the Vegfa locus in vivo, which significantly reduced local VEGF-A expression. Consequently, treated corneas showed markedly decreased macrophage infiltration and robust suppression of both hemangiogenesis and lymphangiogenesis compared to untreated controls. These findings demonstrate that even modest in vivo gene editing can yield a strong therapeutic effect, highlighting a clinically relevant strategy for controlling corneal angiogenesis. Our study introduces a feasible and safe topical CRISPR therapy for corneal diseases, offering a potential alternative to invasive or virus-based gene delivery methods.

ABSTRACT Monolithic III–V multijunction photovoltaics are promising candidates for both space power systems and solar‐to‐chemical energy conversion, yet their deployment in flexible, chemically aggressive, and radiation‐rich environments requires simultaneous control of epitaxial quality, conformability, and barrier properties. Here, we present a flexible InGaP/GaAs/InGaAs triple‐junction platform that addresses these requirements within a single device architecture. The optimized epitaxial stack and its growth process enable almost fully relaxed subcells with low dislocation density, supporting power conversion efficiencies above 33% under AM1.5G and ∼31% under AM0, even after transferring the epitaxial stack to a thin plastic substrate to improve mechanical compliance. To ensure environmental robustness, the flexible triple‐junction cells are encapsulated with an ultrathin glass sheet that provides strong protection against aqueous and strongly alkaline conditions, as well as against high‐energy proton and electron irradiation. By exploiting the high output voltage and durability of this platform, bias‐free electrocatalysis with formate as the predominant product is demonstrated using a simple electrocatalyst configuration. These results establish a unified III–V multijunction photovoltaic architecture that couples space‐relevant efficiency, flexibility, and radiation hardness with chemical durability suitable for unassisted solar‐to‐chemical conversion, offering a versatile route toward next‐generation terrestrial and space energy systems.

The industrial application of traditional tertiary amine solutions for CO2 absorption is limited by their slow absorption rates. Therefore, this study aims to synthesize mesoporous MgO nanoparticles through a simple method and utilize them to catalytically speed up the absorption of CO2 in representative tertiary amine MDEA solutions. This study primarily employed five magnesium sources as precursors to produce MgO nanoparticles through calcination. Among these, the MgO derived from the Mg(OH)2 precursor exhibited the most effective catalytic performance for CO2 absorption in MDEA solutions. Compared to the noncatalytic test, MgO-MgH achieved a 302.2% increase in the CO2 absorption rate and an 82.6% increase in absorption capacity. The superior CO2 absorption efficiency of the MgO-MgH catalyst is mainly attributed to its abundant surface alkaline sites and oxygen vacancies. Online FT-IR characterization results evidenced the catalytic role of MgO-MgH in facilitating the CO2 absorption process. A possible catalytic absorption mechanism over MgO-MgH is proposed. Moreover, the MgO-MgH’s stability was confirmed through a ten-cycle CO2 absorption–desorption study. This study proposes a method to enhance CO2 absorption by incorporating an easily synthesized alkaline nanomaterial, MgO-MgH, effectively overcoming its drawback and advancing the practical application of tertiary amine absorbents for CO2 capture.

Continuous device scaling has driven the demand for nanoscale patterning, where area-selective atomic layer deposition (AS-ALD) offers a promising bottom-up alternative to conventional lithography. Here, we investigate small molecular inhibitors (SMIs), tri(dimethylamino)phenylsilane (TDMAPS) with an aminosilane headgroup and trimethoxyphenylsilane (TMPS) with a methoxysilane headgroup, for selective Ru ALD. Combined density functional theory simulations and experimental analysis reveal that the headgroup chemistry plays a pivotal role in determining inhibition performance. On SiO2, both SMIs react via condensation with surface –OH groups, but TDMAPS follows a kinetically favorable pathway with lower activation energies, enabling rapid and robust passivation. On Cu, the two SMIs follow distinct pathways that prevent stable passivation, enabling Ru thin film growth. TDMAPS tends to desorb due to its high kinetic barriers, while TMPS undergoes decomposition through an energetically accessible pathway. Consequently, TDMAPS sustained perfect selectivity (S = 1.00) up to 150 cycles on SiO2/Cu, whereas TMPS allowed gradual nucleation of Ru with S decreasing from 1.00 to 0.25. These findings demonstrate that aminosilane-based inhibitors are superior to methoxysilane analogues in both kinetics and durability, providing valuable design principles for inhibitor-assisted AS-ALD in nanoscale patterning applications.

Photodynamic Therapy This cover illustrates a lipid-hybridized nanoplatform (CSA-psICG/BdTT-BNBE) for cascade-activated photodynamic therapy. Guided by CSA–CD44 targeting, the system responds to dual-light irradiation (NIR and white light), triggering glutathione depletion and amplified ROS generation. This strategy enables spatiotemporally controlled activation and enhances therapeutic efficacy against tumors. More in the Research Article (e12546), Jeeyeon Lee, Jae-Young Lee, and co-workers.