Air quality monitoring in Vietnam has been limited by sparse ground-based observations, leaving long-term pollution dynamics poorly understood. This study provides the first 43-year (1980-2023) spatiotemporal assessment of major pollutants including carbon monoxide (CO), sulfur dioxide (SO2), black carbon (BC), and fine particulate matter (PM2.5), across Vietnam's two largest urban-industrial regions. In addition, we combined remote sensing data, ground-based PM2.5 data, statistical analyses, and source attribution modeling to disentangle local and transboundary influences on air quality in Vietnam. Overall, the concentrations of air pollutants were consistently 2-4 times higher in the North than in the South during the last five years (CO: 2.30; SO2: 4.43; BC: 3.40, PM25: 4.14 times). BC was strongly correlated to PM2.5 (rho up to 0.97, p < 0.01), demonstrating its central role in PM2.5 composition. The Modern-Era Retrospective Analysis for Research and Applications, Version 2 (MERRA-2) reproduced seasonal PM2.5 variability in Hanoi (rho = 0.64 divided by 0.82) but underestimated dry-wet contrasts in Ho Chi Minh City, emphasizing the need for enhanced ground-based monitoring. Results of potential source contribution function (PSCF) highlighted northern PM2.5 hotspots associated with transport from neighboring countries, while southern hotspots were more diffuse and strongly influenced by traffic, industrial, and shipping emissions. Moderate Resolution Imaging Spectroradiometer (MODIS) fire data confirmed biomass burning in the Mekong subregion during March-April as a significant episodic contributor to northern PM2.5. The findings of this study provide a robust baseline for emission trend evaluation, targeted mitigation, and cross-border pollution management, offering critical evidence to support Vietnam's net-zero emission strategies.
The rapid growth of the textile and garment industry generates large quantities of solid waste and heavy-metal-contaminated wastewater, creating coupled environmental challenges that require integrated solutions. In this study, post-industrial garment waste was valorized into a multifunctional carbon material via anaerobic pyrolysis and evaluated for dual applications as a solid fuel and as an adsorbent for simultaneous Pb(ii) and Cr(vi) removal from aqueous solutions. Carbonized garment waste biochars (CGW) were produced at 400-900 °C and characterized by SEM, EDX, XRD, FTIR and BET analyses. Carbonization temperature strongly influenced surface chemistry, pore structure, and functionality. CGW600 exhibited the highest surface area (56.85 m2 g-1) and pore volume (0.046 cm3 g-1), whereas CGW800-900 showed superior fuel properties with high carbon content (>76 wt%), low ash (<1.4 wt%), and high calorific values (6906-7069 kcal kg-1). CGW600 achieved maximum adsorption capacities of 23.18 mg g-1 for Pb(ii) and 19.68 mg g-1 for Cr(vi), with effective simultaneous removal at pH 7 (9.43 ± 0.26 and 8.78 ± 0.18 mg g-1, respectively). Spectroscopic evidence and modeling indicate adsorption dominated by surface complexation and ion exchange, with additional redox-assisted interactions for Cr(vi). Machine learning analysis (R 2 = 0.99 for Pb; 0.987 for Cr) identified pH, adsorbent dosage and initial concentration as key controlling factors. The present results outline a temperature-dependent methodology for upcycling textile waste into advanced carbon materials with dual applicability in energy generation and aqueous pollutant removal. Such an integrated framework advances sustainable material development and contributes to effective strategies for environmental cleanup and reduced waste burden.
Nitrous oxide (N₂O) is a potent greenhouse gas and a major ozone-depleting substance in the modern atmosphere, and the development of efficient low-temperature catalysts for its abatement is of significant industrial relevance. In this work, a ternary NiY co-modified cobalt spinel catalyst (NCY) was synthesized via a controlled co-precipitation route to tune the surface reactivity of Co₃O₄ toward N₂O decomposition. The NCY catalyst exhibits superior low-temperature performance, achieving over 90% N₂O conversion at 400 °C with a low apparent activation energy of 52.77 kJ mol-1, markedly outperforming the corresponding binary catalysts. Structural and surface analyses indicate that Ni incorporation modifies the redox-responsive surface environments of cobalt oxides, while Y3+ contributes to lattice stabilization and structural robustness under reaction conditions. In situ FTIR, mass spectrometry, and 18O isotope-tracing experiments reveal dynamic surface oxygen exchange during O₂ formation, consistent with a surface-mediated N₂O decomposition pathway dominated by adsorption, dissociation, and suprafacial oxygen recombination. The cooperative effect of Ni and Y therefore tunes surface oxygen behavior and enhances catalytic efficiency at low temperatures, providing a practical strategy for improving N₂O abatement over cobalt spinel catalysts.
It remains difficult to automate the creation and validation of Unified Modeling Language (UML) diagrams due to unstructured requirements, limited automated pipelines, and the lack of reliable evaluation methods. This study introduces a cohesive architecture that amalgamates requirement development, UML synthesis, and multimodal validation. First, LLaMA-3.2-1B-Instruct was utilized to generate user-focused requirements. Then, DeepSeek-R1-Distill-Qwen-32B applies its reasoning skills to transform these requirements into PlantUML code. Using this dual-LLM pipeline, we constructed a synthetic dataset of 11,997 UML diagrams spanning six major diagram families. Rendering analysis showed that 89.5% of the generated diagrams compile correctly, while invalid cases were detected automatically. To assess quality, we employed a multimodal scoring method that combines Qwen2.5-VL-3B, LLaMA-3.2-11B-Vision-Instruct and Aya-Vision-8B, with weights based on MMMU performance. A study with 94 experts revealed strong alignment between automatic and manual evaluations, yielding a Pearson correlation of r = 0.82 and a Fleiss' Kappa of 0.78. This indicates a high degree of concordance between automated metrics and human judgment. Overall, the results demonstrated that our scoring system is effective and that the proposed generation pipeline produces UML diagrams that are both syntactically correct and semantically coherent. More broadly, the system provides a scalable and reproducible foundation for future work in AI-driven software modeling and multimodal verification.
In this article, we investigate all almost maximum distance separable (briefly, AMDS) negacyclic codes of length 2ps over the finite field Fpm, where p is an odd prime. A necessary and sufficient condition for a code to be an AMDS and NMDS negacyclic code of length 2ps over Fpm is also provided. In addition, we construct quantum AMDS (qAMDS) codes using both the Calderbank-Shor-Steane (CSS) and Hermitian constructions. These newly constructed codes have different parameters compared to previous constructions. Moreover, our qAMDS codes are better than all known quantum error correction (QEC) codes.
