Publications by authors named "T Aparna"

The prevalence and death due to cancer have been rising over the past few decades, and eliminating tumour cells without sacrificing healthy cells remains a difficult task. Due to the low specificity and solubility of drug molecules, patients often require high dosages to achieve the desired therapeutic effects. Silica nanoparticles (SiNPs) can effectively deliver therapeutic agents to targeted sites in the body, addressing these challenges.

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The article discusses an improved memory-event-triggered strategy for H control class of fractional-order neural networks (FONNs) with uncertainties, which are vulnerable to deception attacks. The system under consideration is simultaneously influenced by external disturbances, network-induced time delays, uncertainties, and deception attacks. The suggested enhanced memory event-triggered framework enhances communications security measures and conserves network bandwidth compared to standard control strategies.

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Herein we report the simultaneous detection of dopamine (DA) and uric acid (UA) using polydopamine (PDA) functionalized FeTiO nanohexagons. The nanohexagons were hydrothermally synthesized and subsequently functionalized with PDA in a Tris-buffer solution. The PDA functionalized nanostructure was characterized using X-ray diffraction (XRD), scanning electron microscopy (SEM), transmission electron microscopy (TEM), X-ray photoelectron spectroscopy (XPS), and Fourier transform infrared (FTIR), respectively.

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Introduction: Rheumatoid arthritis (RA) is a chronic, autoimmune and inflammatory disease that mostly impacts the joints. Chronotherapeutics refers to a treatment method in which in-vivo drug availability is timed to match rhythms of disease in order to optimize therapeutic outcomes and minimize side effects. Flurbiprofen is a non-steroidal anti-inflammatory drug, indicated for the relief of inflammation.

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The numerous and varied forms of neurodegenerative illnesses provide a considerable challenge to contemporary healthcare. The emergence of artificial intelligence has fundamentally changed the diagnostic picture by providing effective and early means of identifying these crippling illnesses. As a subset of computational intelligence, machine-learning algorithms have become very effective tools for the analysis of large datasets that include genetic, imaging, and clinical data.

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