Displaying publications 1 - 20 of 24 in total

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  1. Fulltext Synthesis of 1-(4-Bromobenzoyl)-1,3-dicyclohexylurea and Its Arylation via Readily Available Palladium Catalyst-Their Electronic, Spectroscopic, and Nonlinear Optical Studies via a Computational Approach
    Maqbool T, Younas H, Bilal M, Rasool N, Bajaber MA, Mubarik A, et al.
    ACS Omega, 2023 Aug 22;8(33):30306-30314.
    PMID: 37636953 DOI: 10.1021/acsomega.3c03183
    In this study, we reported the synthesis of 1-(4-bromobenzoyl)-1,3-dicyclohexylurea by the reaction of DCC (N,N'-dicyclohexylcarbodiimide) with 4-bromobenzoic acid. Subsequently, we further synthesized a new series of 1-(4-arylbenzoyl)-1,3-dicyclohexylurea (5a-g) derivatives using a Suzuki cross-coupling reaction between 1-(4-bromobenzoyl)-1,3-dicyclohexylurea (3) and various aryl/heteroaryl boronic acids (4). Thus, density functional theory (DFT) calculations have been performed to examine the electronic structure of the synthesized compounds (3, 5a-g) and to calculate their spectroscopic data. Moreover, optimized geometries and thermodynamic properties, such as frontier molecular orbitals (HOMO, LUMO), molecular electrostatic potential surfaces, and reactivity descriptors, were also calculated at the PBE0-D3BJ/def2-TZVP/SMD1,4-dioxane level of theory to validate the structures of the synthesized compounds.
  2. Roles of clock genes in the pathogenesis of Parkinson's disease
    Shkodina AD, Tan SC, Hasan MM, Abdelgawad M, Chopra H, Bilal M, et al.
    Ageing Res Rev, 2022 02;74:101554.
    PMID: 34973458 DOI: 10.1016/j.arr.2021.101554
    Parkinson's disease (PD) is a common motor disorder that has become increasingly prevalent in the ageing population. Recent works have suggested that circadian rhythms disruption is a common event in PD patients. Clock genes regulate the circadian rhythm of biological processes in eukaryotic organisms, but their roles in PD remain unclear. Despite this, several lines of evidence point to the possibility that clock genes may have a significant impact on the development and progression of the disease. This review aims to consolidate recent understanding of the roles of clock genes in PD. We first summarized the findings of clock gene expression and epigenetic analyses in PD patients and animal models. We also discussed the potential contributory role of clock gene variants in the development of PD and/or its symptoms. We further reviewed the mechanisms by which clock genes affect mitochondrial dynamics as well as the rhythmic synthesis and secretion of endocrine hormones, the impairment of which may contribute to the development of PD. Finally, we discussed the limitations of the currently available studies, and suggested future potential studies to deepen our understanding of the roles of clock genes in PD pathogenesis.
  3. Fulltext Reduction of Motion Artifacts in the Recovery of Undersampled DCE MR Images Using Data Binning and L+S Decomposition
    Bilal M, Anis H, Khan N, Qureshi I, Shah J, Kadir KA
    Biomed Res Int, 2019;2019:6139785.
    PMID: 31119178 DOI: 10.1155/2019/6139785
    Background: Motion is a major source of blurring and ghosting in recovered MR images. It is more challenging in Dynamic Contrast Enhancement (DCE) MRI because motion effects and rapid intensity changes in contrast agent are difficult to distinguish from each other.

    Material and Methods: In this study, we have introduced a new technique to reduce the motion artifacts, based on data binning and low rank plus sparse (L+S) reconstruction method for DCE MRI. For Data binning, radial k-space data is acquired continuously using the golden-angle radial sampling pattern and grouped into various motion states or bins. The respiratory signal for binning is extracted directly from radially acquired k-space data. A compressed sensing- (CS-) based L+S matrix decomposition model is then used to reconstruct motion sorted DCE MR images. Undersampled free breathing 3D liver and abdominal DCE MR data sets are used to validate the proposed technique.

    Results: The performance of the technique is compared with conventional L+S decomposition qualitatively along with the image sharpness and structural similarity index. Recovered images are visually sharper and have better similarity with reference images.

    Conclusion: L+S decomposition provides improved MR images with data binning as preprocessing step in free breathing scenario. Data binning resolves the respiratory motion by dividing different respiratory positions in multiple bins. It also differentiates the respiratory motion and contrast agent (CA) variations. MR images recovered for each bin are better as compared to the method without data binning.

  4. Innovations in the synthesis of graphene nanostructures for bio and gas sensors
    Ikram M, Bari MA, Bilal M, Jamal F, Nabgan W, Haider J, et al.
    Biomater Adv, 2023 Feb;145:213234.
    PMID: 36502548 DOI: 10.1016/j.bioadv.2022.213234
    Sensors play a significant role in modern technologies and devices used in industries, hospitals, healthcare, nanotechnology, astronomy, and meteorology. Sensors based upon nanostructured materials have gained special attention due to their high sensitivity, precision accuracy, and feasibility. This review discusses the fabrication of graphene-based biosensors and gas sensors, which have highly efficient performance. Significant developments in the synthesis routes to fabricate graphene-based materials with improved structural and surface properties have boosted their utilization in sensing applications. The higher surface area, better conductivity, tunable structure, and atom-thick morphology of these hybrid materials have made them highly desirable for the fabrication of flexible and stable sensors. Many publications have reported various modification approaches to improve the selectivity of these materials. In the current work, a compact and informative review focusing on the most recent developments in graphene-based biosensors and gas sensors has been designed and delivered. The research community has provided a complete critical analysis of the most robust case studies from the latest fabrication routes to the most complex challenges. Some significant ideas and solutions have been proposed to overcome the limitations regarding the field of biosensors and hazardous gas sensors.
  5. Biodegradation mechanism of chlorpyrifos by halophilic bacterium Hortaea sp. B15
    Hadibarata T, Kristanti RA, Bilal M, Yilmaz M, Sathishkumar P
    Chemosphere, 2023 Jan;312(Pt 1):137260.
    PMID: 36400190 DOI: 10.1016/j.chemosphere.2022.137260
    For decades, most of the developing nations have relied on chlorpyrifos for insecticidal activity in the agriculture sector. It is a common chlorinated organophosphorus pesticide that has been widely used to control insects to protect plants. This study aimed to investigate the effects of environmental characteristics such as salinity, pH, temperature, and surfactant on Hortaea sp. B15 mediated degradation of chlorpyrifos as well as enzyme activity and metabolic pathway. The highest bacterial growth (4.6 × 1016 CFU/mL) was achieved after 20 h of incubation in a 100 mg/L chlorpyrifos amended culture. The fit model and feasible way to express the chlorpyrifos biodegradation kinetics in normal condition and optimized was a first-order rate equation, with an R2 value of 0.95-0.98. The optimum pH for chlorpyrifos biodegradation was pH 9, which resulted in a high removal rate (91.1%) and a maximum total count of 3.8 × 1016 CFU/mL. Increasing the temperature over 40 °C may inhibit microbial development and biodegradation. There was no significant effect of culture salinity on degradation and bacterial growth. In the presence of non-ionic surfactant Tween 80, the maximum chlorpyrifos degradation (89.5%) and bacterial growth (3.8 × 1016 CFU/mL) was achieved. Metabolites such as 3,5,6-trichloropyridin-2-ol and 2-pyridinol were identified in the Hortaea sp. B15 mediated degradation of chlorpyrifos. According to the findings, Hortaea sp. B15 should be recommended for use in the investigation of in situ biodegradation of pesticides.
  6. Cytokine storm and neuropathological alterations in patients with neurological manifestations of COVID-19
    Tsagkaris C, Bilal M, Aktar I, Aboufandi Y, Tas A, Aborode AT, et al.
    Curr Alzheimer Res, 2022 Sep 08.
    PMID: 36089786 DOI: 10.2174/1567205019666220908084559
    The COVID-19 pandemic is caused by the severe acute respiratory syndrome coronavirus (SARS-CoV-2), a respiratory pathogen with neuroinvasive potential. Neurological COVID-19 manifestations include loss of smell and taste, headache, dizziness, stroke, and potentially fatal encephalitis. Several studies found elevated proinflammatory cytokines such as TNF-α, IFN-γ, IL-6 IL-8, IL-10 IL-16, IL-17A, and IL-18 in severely and critically ill COVID-19 patients, which may persist even after apparent recovery from infection. Biomarker studies on CSF and plasma and serum from COVID-19 patients have also shown a high level of IL-6, intrathecal IgG, neurofilament light chain (NFL), glial fibrillary acidic protein (GFAP), and tau protein. Emerging evidence on the matter has established the concept of COVID-19 associated neuroinflammation, in the context of COVID-19 associated cytokine storm. While the short-term implications of this condition are extensively documented, its long-term implications are yet to be understood. The association of the aforementioned cytokines with the pathogenesis of neurodegenerative diseases, including Alzheimer's disease, Parkinson's disease, Huntington disease, and amyotrophic lateral sclerosis, may increase COVID-19 patients' risk to develop neurodegenerative diseases. Analysis of proinflammatory cytokines and CSF biomarkers in patients with COVID-19 can contribute to the early detection of the disease's exacerbation, monitoring the neurological implications of the disease and devising risk scales, and identifying treatment targets.
  7. Social Profiling: A Review, Taxonomy, and Challenges
    Bilal M, Gani A, Lali MIU, Marjani M, Malik N
    Cyberpsychol Behav Soc Netw, 2019 Jul;22(7):433-450.
    PMID: 31074639 DOI: 10.1089/cyber.2018.0670
    Social media has taken an important place in the routine life of people. Every single second, users from all over the world are sharing interests, emotions, and other useful information that leads to the generation of huge volumes of user-generated data. Profiling users by extracting attribute information from social media data has been gaining importance with the increasing user-generated content over social media platforms. Meeting the user's satisfaction level for information collection is becoming more challenging and difficult. This is because of too much noise generated, which affects the process of information collection due to explosively increasing online data. Social profiling is an emerging approach to overcome the challenges faced in meeting user's demands by introducing the concept of personalized search while keeping in consideration user profiles generated using social network data. This study reviews and classifies research inferring users social profile attributes from social media data as individual and group profiling. The existing techniques along with utilized data sources, the limitations, and challenges are highlighted. The prominent approaches adopted include Machine Learning, Ontology, and Fuzzy logic. Social media data from Twitter and Facebook have been used by most of the studies to infer the social attributes of users. The studies show that user social attributes, including age, gender, home location, wellness, emotion, opinion, relation, influence, and so on, still need to be explored. This review gives researchers insights of the current state of literature and challenges for inferring user profile attributes using social media data.
  8. Fulltext An Automatic Premature Ventricular Contraction Recognition System Based on Imbalanced Dataset and Pre-Trained Residual Network Using Transfer Learning on ECG Signal
    Ullah H, Heyat MBB, Akhtar F, Muaad AY, Ukwuoma CC, Bilal M, et al.
    Diagnostics (Basel), 2022 Dec 28;13(1).
    PMID: 36611379 DOI: 10.3390/diagnostics13010087
    The development of automatic monitoring and diagnosis systems for cardiac patients over the internet has been facilitated by recent advancements in wearable sensor devices from electrocardiographs (ECGs), which need the use of patient-specific approaches. Premature ventricular contraction (PVC) is a common chronic cardiovascular disease that can cause conditions that are potentially fatal. Therefore, for the diagnosis of likely heart failure, precise PVC detection from ECGs is crucial. In the clinical settings, cardiologists typically employ long-term ECGs as a tool to identify PVCs, where a cardiologist must put in a lot of time and effort to appropriately assess the long-term ECGs which is time consuming and cumbersome. By addressing these issues, we have investigated a deep learning method with a pre-trained deep residual network, ResNet-18, to identify PVCs automatically using transfer learning mechanism. Herein, features are extracted by the inner layers of the network automatically compared to hand-crafted feature extraction methods. Transfer learning mechanism handles the difficulties of required large volume of training data for a deep model. The pre-trained model is evaluated on the Massachusetts Institute of Technology-Beth Israel Hospital (MIT-BIH) Arrhythmia and Institute of Cardiological Technics (INCART) datasets. First, we used the Pan-Tompkins algorithm to segment 44,103 normal and 6423 PVC beats, as well as 106,239 normal and 9987 PVC beats from the MIT-BIH Arrhythmia and IN-CART datasets, respectively. The pre-trained model employed the segmented beats as input after being converted into 2D (two-dimensional) images. The method is optimized with the using of weighted random samples, on-the-fly augmentation, Adam optimizer, and call back feature. The results from the proposed method demonstrate the satisfactory findings without the using of any complex pre-processing and feature extraction technique as well as design complexity of model. Using LOSOCV (leave one subject out cross-validation), the received accuracies on MIT-BIH and INCART are 99.93% and 99.77%, respectively, suppressing the state-of-the-art methods for PVC recognition on unseen data. This demonstrates the efficacy and generalizability of the proposed method on the imbalanced datasets. Due to the absence of device-specific (patient-specific) information at the evaluating stage on the target datasets in this study, the method might be used as a general approach to handle the situations in which ECG signals are obtained from different patients utilizing a variety of smart sensor devices.
  9. Biocatalytic remediation of pharmaceutically active micropollutants for environmental sustainability
    Bilal M, Lam SS, Iqbal HMN
    Environ Pollut, 2022 Jan 15;293:118582.
    PMID: 34856243 DOI: 10.1016/j.envpol.2021.118582
    The discharge of an alarming number of recalcitrant pollutants from various industrial activities presents a serious threat to environmental sustainability and ecological integrity. Bioremediation has gained immense interest around the world due to its environmentally friendly and cost-effective nature. In contrast to physical and chemical methods, the use of microbial enzymes, particularly immobilized biocatalysts, has been demonstrated as a versatile approach for the sustainable mitigation of environmental pollution. Considerable attention is now devoted to developing novel enzyme engineering approaches and state-of-the-art bioreactor design for ameliorating the overall bio-catalysis and biodegradation performance of enzymes. This review discusses the contemporary and state of the art technical and scientific progress regarding applying oxidoreductase enzyme-based biocatalytic systems to remediate a vast number of pharmaceutically active compounds from water and wastewater bodies. A comprehensive insight into enzyme immobilization, the role of mediators, bioreactors designing, and transformation products of pharmaceuticals and their associated toxicity is provided. Additional studies are necessary to elucidate enzymatic degradation mechanisms, monitor the toxicity levels of the resulting degraded metabolites and optimize the entire bio-treatment strategy for technical and economical affordability.
  10. Sustainable Hydrates for Enhanced Carbon Dioxide Capture from an Integrated Gasification Combined Cycle in a Fixed Bed Reactor
    Abu Hassan MH, Sher F, Fareed B, Ali U, Zafar A, Bilal M, et al.
    Ind Eng Chem Res, 2021 Aug 04;60(30):11346-11356.
    PMID: 34475634 DOI: 10.1021/acs.iecr.1c01174
    An increase in temperature of up to 2 °C occurs when the amount of CO2 reaches a range of 450 ppm. The permanent use of mineral oil is closely related to CO2 emissions. Maintaining the sustainability of fossil fuels and eliminating and reducing CO2 emissions is possible through carbon capture and storage (CCS) processes. One of the best ways to maintain CCS is hydrate-based gas separation. Selected type T1-5 (0.01 mol % sodium dodecyl sulphate (SDS) + 5.60 mol % tetrahydrofuran (THF), with the help of this silica gel promotion was strongly stimulated. A pressure of 36.5 bar of CO2 is needed in H2O to investigate the CO2 hydrate formation. Therefore, ethylene glycol monoethyl ether (EGME at 0.10 mol %) along with SDS (0.01 mol %) labeled as T1A-2 was used as an alternative to THF at the comparable working parameters in which CO2 uptake of 5.45 mmol of CO2/g of H2O was obtained. Additionally, it was found that with an increase in tetra-n-butyl ammonium bromide (TBAB) supplementation of CO2, the hydrate and operating capacity of the process increased. When the bed height was reduced from 3 cm to 2 cm with 0.1 mol % TBAB and 0.01% SDS (labelled as T3-2) in fixed bed reactor (FBR), the outcomes demonstrated a slight expansion in gas supply to 1.54 mmol of CO2/g of H2O at working states of 283 K and 70 bar. The gas selectivity experiment by using the high-pressure volume analysis through hydrate formation was performed in which the highest CO2 uptake for the employment of silica contacts with water in fuel gas mixture was observed in the non-IGCC conditions. Thus, two types of reactor configurations are being proposed for changing the process from batch to continuous with the employment of macroporous silica contacts with new consolidated promoters to improve the formation of CO2 hydrate in the IGCC conditions. Later, much work should be possible on this with an assortment of promoters and specific performance parameters. It was reported in previous work that the repeatability of equilibrium moisture content and gas uptake attained for the sample prepared by the highest rates of stirring was the greatest with the CIs of ±0.34 wt % and ±0.19 mmol of CO2/g of H2O respectively. This was due to the amount of water occluded inside silica gel pores was not an issue or in other words, vigorous stirring increased the spreadability. The variation of pore size to improve the process can be considered for future work.
  11. Fulltext Respiratory Motion Correction for Compressively Sampled Free Breathing Cardiac MRI Using Smoothl1-Norm Approximation
    Bilal M, Shah JA, Qureshi IM, Kadir K
    Int J Biomed Imaging, 2018;2018:7803067.
    PMID: 29610569 DOI: 10.1155/2018/7803067
    Transformed domain sparsity of Magnetic Resonance Imaging (MRI) has recently been used to reduce the acquisition time in conjunction with compressed sensing (CS) theory. Respiratory motion during MR scan results in strong blurring and ghosting artifacts in recovered MR images. To improve the quality of the recovered images, motion needs to be estimated and corrected. In this article, a two-step approach is proposed for the recovery of cardiac MR images in the presence of free breathing motion. In the first step, compressively sampled MR images are recovered by solving an optimization problem using gradient descent algorithm. TheL1-norm based regularizer, used in optimization problem, is approximated by a hyperbolic tangent function. In the second step, a block matching algorithm, known as Adaptive Rood Pattern Search (ARPS), is exploited to estimate and correct respiratory motion among the recovered images. The framework is tested for free breathing simulated andin vivo2D cardiac cine MRI data. Simulation results show improved structural similarity index (SSIM), peak signal-to-noise ratio (PSNR), and mean square error (MSE) with different acceleration factors for the proposed method. Experimental results also provide a comparison betweenk-tFOCUSS with MEMC and the proposed method.
  12. N-([1,1'-biaryl]-4-yl)-1-naphthamide-based scaffolds synthesis, their cheminformatics analyses, and screening as bacterial biofilm inhibitor
    Ejaz S, Zubair M, Rasool N, Ahmed F, Bilal M, Ahmad G, et al.
    J Basic Microbiol, 2021 Nov 01.
    PMID: 34724237 DOI: 10.1002/jobm.202100288
    Naphthamides have pharmacological potential as they express strong activities against microorganisms. The commercially available naphthoyl chloride and 4-bromoaniline were condensed in dry dichloromethane (DCM) in the presence of Et3 N to form N-(4-bromophenyl)-1-naphthamide (86%) (3). Using a Pd(0) catalyzed Suzuki-Miyaura Cross-Coupling reaction of (3) and various boronic acids, a series of N-([1,1'-biaryl]-4-yl)-1-naphthamide derivatives (4a-h) were synthesized in moderate to good yields. The synthesized derivatives were evaluated for cytotoxicity haemolytic assay and biofilm inhibition activity through in silico and in vitro studies. Molecular docking, ADME (absorption, distribution, metabolism, and excretion), toxicity risk, and other cheminformatics predict synthesized molecules as biologically active moieties, further validated through in vitro studies in which compounds (4c) and (4f) showed significant haemolytic activity whereas (4e) exhibited an efficient biofilm inhibition activity against Gram-negative bacteria Escherichia coli and Gram-positive bacteria Bacillus subtilis. When forming biofilms, bacteria become resistant to various antimicrobial treatments. Currently, research is focused on the development of agents that inhibit biofilm formation, thus the present work is valuable for preventing future drug resistance.
  13. Fulltext Total Synthesis of Terpenes and Their Biological Significance: A Critical Review
    Kanwal A, Bilal M, Rasool N, Zubair M, Shah SAA, Zakaria ZA
    Pharmaceuticals (Basel), 2022 Nov 11;15(11).
    PMID: 36422521 DOI: 10.3390/ph15111392
    Terpenes are a group of natural products made up of molecules with the formula (C5H8)n that are typically found in plants. They are widely employed in the medicinal, flavor, and fragrance industries. The total synthesis of terpenes as well as their origin and biological potential are discussed in this review.
  14. Fulltext The impact of PEG-induced drought stress on seed germination and seedling growth of different bread wheat (Triticum aestivum L.) genotypes
    Mahpara S, Zainab A, Ullah R, Kausar S, Bilal M, Latif MI, et al.
    PLoS One, 2022;17(2):e0262937.
    PMID: 35148345 DOI: 10.1371/journal.pone.0262937
    Wheat is an important crop, used as staple food in numerous countries around the world. However, wheat productivity is low in the developing world due to several biotic and abiotic stresses, particularly drought stress. Non-availability of drought-tolerant wheat genotypes at different growth stages is the major constraint in improving wheat productivity in the developing world. Therefore, screening/developing drought-tolerant genotypes at different growth stages could improve the productivity of wheat. This study assessed seed germination and seedling growth of eight wheat genotypes under polyethylene glycol (PEG)-induced stress. Two PEG-induced osmotic potentials (i.e., -0.6 and -1.2 MPa) were included in the study along with control (0 MPa). Wheat genotypes included in the study were 'KLR-16', 'B6', 'J10', '716', 'A12', 'Seher', 'KTDH-16', and 'J4'. Data relating to seed germination percentage, root and shoot length, fresh and dry weight of roots and shoot, root/shoot length ratio and chlorophyll content were recorded. The studied parameters were significantly altered by individual and interactive effects of genotypes and PEG-induced osmotic potentials. Seed germination and growth parameters were reduced by osmotic potentials; however, huge differences were noted among genotypes. A reduction of 32.83 to 53.50% was recorded in seed germination, 24.611 to 47.75% in root length, 37.83 to 53.72% in shoot length, and 53.35 to 65.16% in root fresh weight. The genotypes, 'J4', 'KLR-16' and 'KTDH-16', particularly 'J4' better tolerated increasing osmotic potentials compared to the rest of the genotypes included in the study. Principal component analysis segregated these genotypes from the rest of the genotypes included in the study indicated that these can be used in the future studies to improve the drought tolerance of wheat crop. The genotype 'J4' can be used as a breeding material to develop drought resistant wheat genotypes.
  15. Fulltext Green photosensitisers for the degradation of selected pesticides of high risk in most susceptible food: A safer approach
    Baig A, Zubair M, Sumrra SH, Rashid U, Zafar MN, Ahmad F, et al.
    PLoS One, 2021;16(10):e0258864.
    PMID: 34710164 DOI: 10.1371/journal.pone.0258864
    Pesticides are the leading defence against pests, but their unsafe use reciprocates the pesticide residues in highly susceptible food and is becoming a serious risk for human health. In this study, mint extract and riboflavin were tested as photosensitisers in combination with light irradiation of different frequencies, employed for various time intervals to improve the photo-degradation of deltamethrin (DM) and lambda cyhalothrin (λ-CHT) in cauliflower. Different source of light was studied, either in ultraviolet range (UV-C, 254 nm or UV-A, 320-380 nm) or sunlight simulator (> 380-800 nm). The degradation of the pesticides varied depending on the type of photosensitiser and light source. Photo-degradation of the DM and λ-CHT was enhanced by applying the mint extracts and riboflavin and a more significant degradation was achieved with UV-C than with either UV-A or sunlight, reaching a maximum decrement of the concentration by 67-76%. The light treatments did not significantly affect the in-vitro antioxidant activity of the natural antioxidants in cauliflower. A calculated dietary risk assessment revealed that obvious dietary health hazards of DM and λ-CHT pesticides when sprayed on cauliflower for pest control. The use of green chemical photosensitisers (mint extract and riboflavin) in combination with UV light irradiation represents a novel, sustainable, and safe approach to pesticide reduction in produce.
  16. Fulltext The non-Newtonian maxwell nanofluid flow between two parallel rotating disks under the effects of magnetic field
    Ahmadian A, Bilal M, Khan MA, Asjad MI
    Sci Rep, 2020 Oct 13;10(1):17088.
    PMID: 33051520 DOI: 10.1038/s41598-020-74096-8
    The main feature of the present numerical model is to explore the behavior of Maxwell nanoliquid moving within two horizontal rotating disks. The disks are stretchable and subjected to a magnetic field in axial direction. The time dependent characteristics of thermal conductivity have been considered to scrutinize the heat transfer phenomena. The thermophoresis and Brownian motion features of nanoliquid are studied with Buongiorno model. The lower and upper disk's rotation for both the cases, same direction as well as opposite direction of rotation is investigated. The subsequent arrangement of the three dimensional Navier Stoke's equations along with energy, mass and Maxwell equations are diminished to a dimensionless system of equations through the Von Karman's similarity framework. The comparative numerical arrangement of modeled equations is further set up by built-in numerical scheme "boundary value solver" (Bvp4c) and Runge Kutta fourth order method (RK4). The various physical constraints, such as Prandtl number, thermal conductivity, magnetic field, thermal radiation, time relaxation, Brownian motion and thermophoresis parameters and their impact are presented and discussed briefly for velocity, temperature, concentration and magnetic strength profiles. In the present analysis, some vital characteristics such as Nusselt and Sherwood numbers are considered for physical and numerical investigation. The outcomes concluded that the disk stretching action opposing the flow behavior. With the increases of magnetic field parameter [Formula: see text] the fluid velocity decreases, while improving its temperature. We show a good agreement of the present work by comparing with those published in literature.
  17. Fulltext Numerical analysis of thermal conductive hybrid nanofluid flow over the surface of a wavy spinning disk
    Ahmadian A, Bilal M, Khan MA, Asjad MI
    Sci Rep, 2020 Nov 02;10(1):18776.
    PMID: 33139760 DOI: 10.1038/s41598-020-75905-w
    A three dimensional (3D) numerical solution of unsteady, Ag-MgO hybrid nanoliquid flow with heat and mass transmission caused by upward/downward moving of wavy spinning disk has been scrutinized. The magnetic field has been also considered. The hybrid nanoliquid has been synthesized in the presence of Ag-MgO nanoparticles. The purpose of the study is to improve the rate of thermal energy transmission for several industrial purposes. The wavy rotating surface increases the heat transmission rate up to 15%, comparatively to the flat surface. The subsequent arrangement of modeled equations is diminished into dimensionless differential equation. The obtained system of equations is further analytically expounded via Homotopy analysis method HAM and the numerical Parametric continuation method (PCM) method has been used for the comparison of the outcomes. The results are graphically presented and discussed. It has been presumed that the geometry of spinning disk positively affects the velocity and thermal energy transmission. The addition of hybrid nanoparticles (silver and magnesium-oxide) significantly improved thermal property of carrier fluid. It uses is more efficacious to overcome low energy transmission. Such as, it provides improvement in thermal performance of carrier fluid, which play important role in power generation, hyperthermia, micro fabrication, air conditioning and metallurgical field.
  18. Fulltext Improved Reconstruction of MR Scanned Images by Using a Dictionary Learning Scheme
    Ikram S, Shah JA, Zubair S, Qureshi IM, Bilal M
    Sensors (Basel), 2019 Apr 23;19(8).
    PMID: 31018597 DOI: 10.3390/s19081918
    The application of compressed sensing (CS) to biomedical imaging is sensational since it permits a rationally accurate reconstruction of images by exploiting the image sparsity. The quality of CS reconstruction methods largely depends on the use of various sparsifying transforms, such as wavelets, curvelets or total variation (TV), to recover MR images. As per recently developed mathematical concepts of CS, the biomedical images with sparse representation can be recovered from randomly undersampled data, provided that an appropriate nonlinear recovery method is used. Due to high under-sampling, the reconstructed images have noise like artifacts because of aliasing. Reconstruction of images from CS involves two steps, one for dictionary learning and the other for sparse coding. In this novel framework, we choose Simultaneous code word optimization (SimCO) patch-based dictionary learning that updates the atoms simultaneously, whereas Focal underdetermined system solver (FOCUSS) is used for sparse representation because of a soft constraint on sparsity of an image. Combining SimCO and FOCUSS, we propose a new scheme called SiFo. Our proposed alternating reconstruction scheme learns the dictionary, uses it to eliminate aliasing and noise in one stage, and afterwards restores and fills in the k-space data in the second stage. Experiments were performed using different sampling schemes with noisy and noiseless cases of both phantom and real brain images. Based on various performance parameters, it has been shown that our designed technique outperforms the conventional techniques, like K-SVD with OMP, used in dictionary learning based MRI (DLMRI) reconstruction.
  19. Fulltext The Effect of 4-hydroxybenzaldehyde on the γ-aminobutyric Acid Type A Receptor
    Zhang J, Mohamad H, Wong JH, Bilal M, Ismail AHB, Lloyd AJ, et al.
    Malays J Med Sci, 2017 Mar;24(2):94-99.
    PMID: 28894409 DOI: 10.21315/mjms2017.24.2.12
    The α1β2γ2 subtype of GABAA receptors is the most commonly found GABAA receptor subtype in the mammalian cortex and hippocampus. It is expressed heterologously in the Xenopus laevis oocyte as a α1β2γ2S/L subtype for application as an in vitro model for the screening of compounds that modulate receptor activities. In fact, 4-hydroxybenzaldehyde (4-HB) has been identified as one of the major components in Dendrocalamus asper bamboo shoots in our previous study, and the current study showed that at 101.7 μM, 4-HB significantly reduced the GABA-induced chloride current of GABAA receptors expressed on Xenopus oocytes, indicating a possible GABAergic antagonistic effect at high concentrations.
  20. Time-domain reconstruction using sensitivity coefficients for limited view ultrawide band tomography
    Abdullah MZ, Yin W, Bilal M, Armitage DW, Mackin R, Peyton AJ
    Rev Sci Instrum, 2007 Aug;78(8):084703.
    PMID: 17764343
    This article addresses time-domain ultrawide band (UWB) electromagnetic tomography for reconstructing the unknown spatial characteristic of an object from observations of the arrivals of short electromagnetic (EM) pulses. Here, the determination of the first peak arrival of the EM traces constitutes the forward problem, and the inverse problem aims to reconstruct the EM property distribution of the media. In this article, the finite-difference time-domain method implementing a perfectly matched layer is used to solve the forward problem from which the system sensitivity maps are determined. Image reconstruction is based on the combination of a linearized update and regularized Landweber minimization algorithm. Experimental data from a laboratory UWB system using targets of different contrasts, sizes, and shapes in an aqueous media are presented. The results show that this technique can accurately detect and locate unknown targets in spite of the presence of significant levels of noise in the data.
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