Browsing by Author "S, R."

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    Real-time Neonatal Monitoring Using a Hybrid Deep Learning Model
    (SAGE Publications Ltd, 2025) R, M.; Benz, P.J.; S, R.
    The neonatal intensive care unit (NICU) provides emergency medical care for preterm babies. In some of the existing NICUs, neonatal parameters are monitored and analyzed by healthcare professionals. This can lead to human errors and further delays during emergency cases. The emergence of Internet of Things (IoT) devices has improved real-time data collection in NICUs. IoT devices generate enormous data every second in the NICUs. Therefore, it is important to design an efficient artificial intelligence algorithm to analyze the data in the NICUs. Among artificial intelligence, deep learning model excels in identifying the features of data. A hybrid deep learning model integrates two or more distinct deep learning models to enhance the overall performance. This article introduces a hybrid deep learning model that integrates an attention mechanism, a long short-term memory (LSTM) network, and a one-dimensional convolutional neural network (1D-CNN) for classifying NICU data. A simulation of the proposed model has been conducted using Python. The proposed model obtained a validation accuracy of 97.44%, a validation loss of 0.0794, and an F1-score of 0.98. The simulation results demonstrate that the model efficiently classifies the NICU data. © 2025 National Neonatology Forum
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    Synthesis and characteristics of Fe/Ni/Cr oxide nanoparticles/PLA hybrid composite coatings on Mg–Zn–Ca alloy
    (Elsevier Editora Ltda, 2025) Kumar, P.; Kudva S, A.; T, A.; S, R.; Ramesh, M.R.; Prabhu, A.; Anne, G.
    Biodegradable materials research is dominated by magnesium and alloys thereof due to their excellent compatibility with biological barriers and biomechanical strength. Despite this, the rapid degradation of these materials in the physiological environment is the primary obstacle hindering their utilization in biomedical applications. This issue must be resolved before considering their use in clinical applications. To improve resistance towards corrosion and enhance biological efficacy and compatibility, the surfaces were coated with polylactic acid (PLA) using dip-coating. In this study, iron (Fe), nickel (Ni), and chromium (Cr) oxide nanoparticles from the Coleus amboinicus extract are synthesized and mixed with PLA to develop hybrid composite coatings, which are then applied onto the Mg–4Zn–1Ca alloy. Coleus amboinicus is known for its various medicinal properties, including immunoregulatory effects, antimicrobial activity, anti-inflammatory properties, and potential use in treating sepsis and other ailments. The extracted FeNiCr was used the develop composite coatings on Mg–4Zn–1Ca alloy. The coating improves biocompatibility, antibacterial properties, and overall performance of biomedical implants. These composite coatings were evaluated for their morphological and optical characteristics using a scanning electron microscope (SEM), 3-D non-contact profilometer, Fourier transform infrared spectroscopy (FTIR), and X-ray diffraction (XRD). The corrosion characteristics of developed samples were measured by electrochemical corrosion in standard simulation body fluid (SBF) at 37 °C. Furthermore, cytocompatibility of the PLA hybrid composites on osteoblast cells and apoptosis detection using acridine orange-ethidium bromide. Our developed coating showed ratings of 5B and 4B were obtained for FeNiCr/PLA NC- ball burnished (BB) Mg and FeNiCr/PLA nano composite (NC)–Mg samples, respectively, demonstrating the exceptional coating strength and the substrate. The corrosion rate of the FeNiCr/PLA NC-BB-Mg sample (0.02890 mm/y) is two-fold times increased against comparison with the H Mg sample (0.00012 mm/y). Cytocompatibility indicates their cytocompatibility for bone implant applications. © 2025 The Authors