Micro/nanoscale fabricated devices have widely been used in modern technology and bioengineering as they offer excellent heat transfer. Removal of excess heat, coolant selection, rapid mixing, and handling proportion of colloidal metallic nanogranules in the base fluid are the main challenges in micro/nanofluidic systems. To address these problems, the primary motivation of the intended mathematical flow problem is to investigate the thermal and flow aspects of blood-based ternary nanofluid in the presence of inclined magnetic field and thermal radiations through a microfluidic pump with elastic walls. Further, the pump inner surface is smeared with fabricated cilia. The embedded cilia blow in coordination to start metachronal travelling waves along the pump wall that assist homogenous mixing and manipulation. The entire analysis is conducted in moving frame and simplified under lubrication and Rosseland approximations. Numerical solution of various flow and thermal entities are computed via the shooting method and plotted for different values of the parameters of interest. A comparative glimpse allows us to conclude that the trimetallic blood-based nanofluid exhibits elevated heat transfer rate by 12–18%, bi-metallic by about 11–12%, and mono nanofluid by about 6% compared to the conventional blood model. The study also determines that the prolonged cilia commence augmentation in flowrate and pressure-gradient around the pump deep portion. Furthermore, the radiated ternary liquid under fragile magnetic field effects may contribute to the cooling process by eliminating unnecessary heat from the system. It is also noticed that around the ciliated wall, the heat transfer irreversibility effects are appreciable over the fluid frictional irreversibility.
Lung disorders involve swelling, inflammation, and muscle tightening around the airways, with symptoms such as coughing, wheezing, shortness of breath, and abnormal fluid build-up. The global prevalence of these conditions is rising, highlighting the need for extensive research to alleviate their severity and symptoms. Due to the chronic nature and recurrence of these disorders, the human body often develops immunity and side effects to certain medications. Therefore, developing novel and appropriate drug combinations is crucial. This study analyzes a dataset of lung disorder drugs, characterized by various topological indices. The structures of 16 drugs used to treat lung disorders are correlated with their physical properties using degree-based graph invariants. When considering specific attributes, the VIKOR (VlseKriterijumska Optimizacija I Kompromisno Resenje) method provides an optimal ranking for each drug. The QSPR results highlight the effectiveness of this approach in drug prioritization, offering valuable insights for clinical decision-making and drug development. This methodology can enhance the strategic selection of treatments for lung disorders, leading to improved patient care and better resource allocation.
Alzheimer’s Disease(AD) is the most common type of dementia. It is a progressive disease beginning with mild memory loss and possibly leading to loss of the ability to carry on a conversation and respond to the environment. This study investigates the relationship between the chemical structure of potential AD drugs and their therapeutic efficacy using Multi-Criteria Decision-Making (MCDM) techniques including The approach for Order Preference by Similarity to Ideal Solution (TOPSIS) and Simple Additive Weighting (SAW) method. A comprehensive dataset comprising molecular descriptors and corresponding pharmacological properties, i.e., melting point, boiling point, molecular weight and density of AD drugs was compiled from diverse sources. Topological indices were calculated to capture the structural characteristics of these compounds. Application of TOPSIS and SAW through Entropy method helps obtain optimal drugs for curing AD. Quantitative Structure Property Relationships (QSPR) analysis has been done between properties and topological indices of AD’s drug structures. Results revealed significant relations between specific topological indices and drug efficacy, providing insights into the structural features crucial for AD treatment efficacy. This approach offers a promising avenue for rational drug design and optimization in the quest for novel AD therapeutics.
This reply presents a point-by-point response to the comments received from Pantokratoras in our previously published research article. The comments highlighted that the values of electrical conductivity assigned to alumina (Al2O3), silicon dioxide (SiO2), and titanium dioxide (TiO2) nanoparticles were not appropriate and the experimental value of the Prandtl number for blood should remain within the range of 29–32. In response the electrical conductivity values for each nanoparticle were corrected and revised the Prandtl number values accordingly. The recomputed findings revealed that only small changes appeared in quantitative results while the overall trends and insights remained same.