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  1. Uddin MJ, Khan WA, Amin NS
    PLoS One, 2014;9(6):e99384.
    PMID: 24927277 DOI: 10.1371/journal.pone.0099384
    The unsteady two-dimensional laminar g-Jitter mixed convective boundary layer flow of Cu-water and Al2O3-water nanofluids past a permeable stretching sheet in a Darcian porous is studied by using an implicit finite difference numerical method with quasi-linearization technique. It is assumed that the plate is subjected to velocity and thermal slip boundary conditions. We have considered temperature dependent viscosity. The governing boundary layer equations are converted into non-similar equations using suitable transformations, before being solved numerically. The transport equations have been shown to be controlled by a number of parameters including viscosity parameter, Darcy number, nanoparticle volume fraction, Prandtl number, velocity slip, thermal slip, suction/injection and mixed convection parameters. The dimensionless velocity and temperature profiles as well as friction factor and heat transfer rates are presented graphically and discussed. It is found that the velocity reduces with velocity slip parameter for both nanofluids for fluid with both constant and variable properties. It is further found that the skin friction decreases with both Darcy number and momentum slip parameter while it increases with viscosity variation parameter. The surface temperature increases as the dimensionless time increases for both nanofluids. Nusselt numbers increase with mixed convection parameter and Darcy numbers and decreases with the momentum slip. Excellent agreement is found between the numerical results of the present paper with published results.
  2. Uddin MJ, Khan WA, Ismail AI
    PLoS One, 2012;7(11):e49499.
    PMID: 23166688 DOI: 10.1371/journal.pone.0049499
    Steady two dimensional MHD laminar free convective boundary layer flows of an electrically conducting Newtonian nanofluid over a solid stationary vertical plate in a quiescent fluid taking into account the Newtonian heating boundary condition is investigated numerically. A magnetic field can be used to control the motion of an electrically conducting fluid in micro/nano scale systems used for transportation of fluid. The transport equations along with the boundary conditions are first converted into dimensionless form and then using linear group of transformations, the similarity governing equations are developed. The transformed equations are solved numerically using the Runge-Kutta-Fehlberg fourth-fifth order method with shooting technique. The effects of different controlling parameters, namely, Lewis number, Prandtl number, buoyancy ratio, thermophoresis, Brownian motion, magnetic field and Newtonian heating on the flow and heat transfer are investigated. The numerical results for the dimensionless axial velocity, temperature and nanoparticle volume fraction as well as the reduced Nusselt and Sherwood number have been presented graphically and discussed. It is found that the rate of heat and mass transfer increase as Newtonian heating parameter increases. The dimensionless velocity and temperature distributions increase with the increase of Newtonian heating parameter. The results of the reduced heat transfer rate is compared for convective heating boundary condition and found an excellent agreement.
  3. Uddin MJ, Khan WA, Ismail AI
    PLoS One, 2015;10(5):e0122663.
    PMID: 25933066 DOI: 10.1371/journal.pone.0122663
    Taking into account the effect of constant convective thermal and mass boundary conditions, we present numerical solution of the 2-D laminar g-jitter mixed convective boundary layer flow of water-based nanofluids. The governing transport equations are converted into non-similar equations using suitable transformations, before being solved numerically by an implicit finite difference method with quasi-linearization technique. The skin friction decreases with time, buoyancy ratio, and thermophoresis parameters while it increases with frequency, mixed convection and Brownian motion parameters. Heat transfer rate decreases with time, Brownian motion, thermophoresis and diffusion-convection parameters while it increases with the Reynolds number, frequency, mixed convection, buoyancy ratio and conduction-convection parameters. Mass transfer rate decreases with time, frequency, thermophoresis, conduction-convection parameters while it increases with mixed convection, buoyancy ratio, diffusion-convection and Brownian motion parameters. To the best of our knowledge, this is the first paper on this topic and hence the results are new. We believe that the results will be useful in designing and operating thermal fluids systems for space materials processing. Special cases of the results have been compared with published results and an excellent agreement is found.
  4. Gholap AD, Uddin MJ, Faiyazuddin M, Omri A, Gowri S, Khalid M
    Comput Biol Med, 2024 Aug;178:108702.
    PMID: 38878397 DOI: 10.1016/j.compbiomed.2024.108702
    Artificial intelligence (AI) has emerged as a powerful tool to revolutionize the healthcare sector, including drug delivery and development. This review explores the current and future applications of AI in the pharmaceutical industry, focusing on drug delivery and development. It covers various aspects such as smart drug delivery networks, sensors, drug repurposing, statistical modeling, and simulation of biotechnological and biological systems. The integration of AI with nanotechnologies and nanomedicines is also examined. AI offers significant advancements in drug discovery by efficiently identifying compounds, validating drug targets, streamlining drug structures, and prioritizing response templates. Techniques like data mining, multitask learning, and high-throughput screening contribute to better drug discovery and development innovations. The review discusses AI applications in drug formulation and delivery, clinical trials, drug safety, and pharmacovigilance. It addresses regulatory considerations and challenges associated with AI in pharmaceuticals, including privacy, data security, and interpretability of AI models. The review concludes with future perspectives, highlighting emerging trends, addressing limitations and biases in AI models, and emphasizing the importance of collaboration and knowledge sharing. It provides a comprehensive overview of AI's potential to transform the pharmaceutical industry and improve patient care while identifying further research and development areas.
  5. Uddin MJ, Economidou SN, Guiraud L, Kazi M, Alanazi FK, Douroumis D
    Mol Pharm, 2024 Sep 02;21(9):4465-4475.
    PMID: 39110837 DOI: 10.1021/acs.molpharmaceut.4c00379
    Transdermal microneedles have demonstrated promising potential as an alternative to typical drug administration routes for the treatment of various diseases. As microneedles offer lower administration burden with enhanced patient adherence and reduced ecological footprint, there is a need for further exploitation of microneedle devices. One of the main objectives of this work was to initially develop an innovative biobased photocurable resin with high biobased carbon content comprising isobornyl acrylate (IBA) and pentaerythritol tetraacrylate blends (50:50 wt/wt). The optimization of the printing and curing process resulted in μNe3dle arrays with durable mechanical properties and piercing capacity. Another objective of the work was to employ the 3D printed hollow μNe3dles for the treatment of osteoporosis in vivo. The 3D printed μNe3dle arrays were used to administer denosumab (Dmab), a monoclonal antibody, to osteoporotic mice, and the serum concentrations of critical bone minerals were monitored for six months to assess recovery. It was found that the Dmab administered by the 3D printed μNe3dles showed fast in vitro rates and induced an enhanced therapeutic effect in restoring bone-related minerals compared to subcutaneous injections. The findings of this study introduce a novel green approach with a low ecological footprint for 3D printing of biobased μNe3dles, which can be tailored to improve clinical outcomes and patient compliance for chronic diseases.
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