6 papers indexed here
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Carbon quantum dots (CQDs) exhibit rich photophysical behaviors, including excitation-dependent emission, surface-state variability, and multimodal fluorescence pathways, which complicate accurate, signal interpretation in chemical sensing. Recent advances in machine learning (ML) offer powerful solutions for modeling these complexities and enhancing fluorescence-based detection performance. This review provides a comprehensive analysis of ML-driven methodologies for denoising, spectral decomposition, feature extraction, and high-accuracy classification in CQD fluorescence systems. Mathematical foundations of key ML paradigms are outlined to establish a rigorous framework for signal reconstruction and generalization. Evaluations of recent applications demonstrate how ML enables ultra-low-level analyte detection, interpretable photophysical modeling, and real-time intelligent sensing across chemical and biological environments. Emerging trends—including physics-informed learning, generative data augmentation, autonomous closed-loop sensing, and distributed multimodal architectures—are examined as frontiers poised to redefine CQD fluorescence analytics. Collectively, the integration of ML with CQD photophysics represents a transformative pathway toward robust, adaptive, and next-generation chemical sensing platforms.
This study presents a comprehensive deterministic compartmental model for malaria-dengue co-infection incorporating distinct vector populations (Anopheles for malaria and Aedes for dengue), disease-specific progression pathways, and co-infection compartments. The model is rigorously analyzed to establish positivity, boundedness, disease-free and endemic equilibria, and basic reproduction numbers. Optimal control theory is applied to evaluate six time-dependent intervention strategies: insecticide-treated bed nets (ITNs), indoor residual spraying (IRS), environmental management, personal protection measures, treatment compliance, and vaccination. Model parameters are estimated using Brazilian malaria and dengue case data (2011-2023). Sensitivity analysis identifies key parameters influencing disease transmission. Cost-effectiveness analysis using infection averted ratio (IAR), average cost-effectiveness ratio (ACER), and incremental cost-effectiveness ratio (ICER) reveals that the combined implementation of all six control measures (Strategy 9) is most cost-effective, averting 9,200 infections (35.38% reduction) at an ACER of 3,756.536. These findings provide crucial guidance for designing economically efficient intervention strategies in resource-constrained co-endemic settings.
This study presents a systematic investigation of the structural, thermal, and morphological characteristics of starch–PVA reinforced cactus bio-based composite films using FTIR, DSC, XRD, TGA, DMA, and SEM analyses. FTIR results suggested enhanced intermolecular hydrogen-bonding interactions among starch, PVA, and cactus-derived polysaccharides, with possible minor ester-link formation in the presence of citric acid. DSC analysis showed a glass transition temperature (Tg) in the range of 38–40 °C and a minor endothermic transition near 83 °C associated with bound moisture relaxation. The thermal transitions observed using the PerkinElmer DSC 9 were reproducible across replicate measurements, indicating good thermal consistency of the developed composite system. XRD analysis indicated a predominantly amorphous morphology with limited semi-crystalline domains and a crystallinity index of approximately 23.32%. TGA results suggested improved thermal stability relative to plasticized starch systems, while DMA results indicated moderate storage-modulus retention and viscoelastic stability over the investigated temperature range. SEM observations of tortuous crack propagation pathways and localized deformation mechanisms. The combined results indicate that the developed composite exhibits balanced thermal and structural performance and potential for sustainable flexible bio-based material applications. However, additional mechanical, durability, water-resistance, and comparative performance studies are necessary to evaluate its suitability as a leather substitute.