Displaying publications 21 - 40 of 605 in total

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  1. Pervez MN, Yeo WS, Mishu MMR, Talukder ME, Roy H, Islam MS, et al.
    Sci Rep, 2023 Jun 15;13(1):9679.
    PMID: 37322139 DOI: 10.1038/s41598-023-36431-7
    Despite the widespread interest in electrospinning technology, very few simulation studies have been conducted. Thus, the current research produced a system for providing a sustainable and effective electrospinning process by combining the design of experiments with machine learning prediction models. Specifically, in order to estimate the diameter of the electrospun nanofiber membrane, we developed a locally weighted kernel partial least squares regression (LW-KPLSR) model based on a response surface methodology (RSM). The accuracy of the model's predictions was evaluated based on its root mean square error (RMSE), its mean absolute error (MAE), and its coefficient of determination (R2). In addition to principal component regression (PCR), locally weighted partial least squares regression (LW-PLSR), partial least square regression (PLSR), and least square support vector regression model (LSSVR), some of the other types of regression models used to verify and compare the results were fuzzy modelling and least square support vector regression model (LSSVR). According to the results of our research, the LW-KPLSR model performed far better than other competing models when attempting to forecast the membrane's diameter. This is made clear by the much lower RMSE and MAE values of the LW-KPLSR model. In addition, it offered the highest R2 values that could be achieved, reaching 0.9989.
    Matched MeSH terms: Computer Simulation
  2. Yahya MS, Soeung S, Singh NSS, Yunusa Z, Chinda FE, Rahim SKA, et al.
    Sensors (Basel), 2023 Jun 06;23(12).
    PMID: 37420526 DOI: 10.3390/s23125359
    In this study, a novel reconfigurable triple-band monopole antenna for LoRa IoT applications is fabricated on an FR-4 substrate. The proposed antenna is designed to function at three distinct LoRa frequency bands: 433 MHz, 868 MHz, and 915 MHz covering the LoRa bands in Europe, America, and Asia. The antenna is reconfigurable by using a PIN diode switching mechanism, which allows for the selection of the desired operating frequency band based on the state of the diodes. The antenna is designed using CST MWS® software 2019 and optimized for maximum gain, good radiation pattern and efficiency. The antenna with a total dimension of 80 mm × 50 mm × 0.6 mm (0.12λ0×0.07λ0 × 0.001λ0 at 433 MHz) has a gain of 2 dBi, 1.9 dBi, and 1.9 dBi at 433 MHz, 868 MHz, and 915 MHz, respectively, with an omnidirectional H-plane radiation pattern and a radiation efficiency above 90% across the three frequency bands. The fabrication and measurement of the antenna have been carried out, and the results of simulation and measurements are compared. The agreement among the simulation and measurement results confirms the design's accuracy and the antenna's suitability for LoRa IoT applications, particularly in providing a compact, flexible, and energy efficient communication solution for different LoRa frequency bands.
    Matched MeSH terms: Computer Simulation
  3. Naderipour A, Nowdeh SA, Babanezhad M, Najmi ES, Kamyab H, Abdul-Malek Z
    Environ Sci Pollut Res Int, 2023 Jun;30(28):71754-71765.
    PMID: 34499303 DOI: 10.1007/s11356-021-16342-8
    In this paper, the technical-economic framework for designing of water pumping system based on photovoltaic clean energy with water tank storage is presented to supply drinking water of customers for remote areas. The objective function is to minimize the net present cost (NPC) (as economic index) including initial investment costs, maintenance, and replacement costs, and reliability constraint is defined as customer's water not supplied probability (CWNSP) as technical index. A meta-heuristic intelligent water drops algorithm (IWDA) is proposed to optimize the solar water pumping system considering NPC and CWNSP with high accuracy and speed of optimization in achieving the global solution. The simulation results show that the proposed method is capable of responding to customer's water demand by optimally sizing components and water storage tank based on IWDA which is inspired based on flowing the water drops in rivers by achieving the lowest cost with optimal reliability. The NPC of the system with CWNSP equal to 3.17 % is obtained 0.24 M$ for 6-m-high water extraction. The results showed that with increasing the water extraction height, the NPC increased, and the reliability also weakened. Moreover, the superiority of the IWDA is confirmed compared with particle swarm optimization (PSO) in designing a water pumping system with the lowest NPC.
    Matched MeSH terms: Computer Simulation
  4. Naderipour A, Abdul-Malek Z, Davoodkhani IF, Kamyab H, Ali RR
    Environ Sci Pollut Res Int, 2023 Jun;30(28):71677-71688.
    PMID: 34241794 DOI: 10.1007/s11356-021-14799-1
    Due to the increased complexity and nonlinear nature of microgrid systems such as photovoltaic, wind-turbine fuel cell, and energy storage systems (PV/WT/FC/ESSs), load-frequency control has been a challenge. This paper employs a self-tuning controller based on the fuzzy logic to overcome parameter uncertainties of classic controllers, such as operation conditions, the change in the operating point of the microgrid, and the uncertainty of microgrid modeling. Furthermore, a combined fuzzy logic and fractional-order controller is used for load-frequency control of the off-grid microgrid with the influence of renewable resources because the latter controller benefits robust performance and enjoys a flexible structure. To reach a better operation for the proposed controller, a novel meta-heuristic whale algorithm has been used to optimally determine the input and output scale coefficients of the fuzzy controller and fractional orders of the fractional-order controller. The suggested approach is applied to a microgrid with a diesel generator, wind turbine, photovoltaic systems, and energy storage devices. The comparison made between the results of the proposed controller and those of the classic PID controller proves the superiority of the optimized fractional-order self-tuning fuzzy controller in terms of operation characteristics, response speed, and the reduction in frequency deviations against load variations.
    Matched MeSH terms: Computer Simulation
  5. Zulkifli MH, Abdullah ZL, Mohamed Yusof NIS, Mohd Fauzi F
    Curr Opin Struct Biol, 2023 Jun;80:102588.
    PMID: 37028096 DOI: 10.1016/j.sbi.2023.102588
    With the availability of public databases that store compound-target/compound-toxicity information, and Traditional Chinese medicine (TCM) databases, in silico approaches are used in toxicity studies of TCM herbal medicine. Here, three in silico approaches for toxicity studies were reviewed, which include machine learning, network toxicology and molecular docking. For each method, its application and implementation e.g., single classifier vs. multiple classifier, single compound vs. multiple compounds, validation vs. screening, were explored. While these methods provide data-driven toxicity prediction that is validated in vitro and/or in vivo, it is still limited to single compound analysis. In addition, these methods are limited to several types of toxicity, with hepatotoxicity being the most dominant. Future studies involving the testing of combination of compounds on the front end i.e., to generate data for in silico modeling, and back end i.e., validate findings from prediction models will advance the in silico toxicity modeling of TCM compounds.
    Matched MeSH terms: Computer Simulation
  6. Ismail AM, Remli MA, Choon YW, Nasarudin NA, Ismail NN, Ismail MA, et al.
    J Integr Bioinform, 2023 Jun 01;20(2).
    PMID: 37341516 DOI: 10.1515/jib-2022-0051
    Analyzing metabolic pathways in systems biology requires accurate kinetic parameters that represent the simulated in vivo processes. Simulation of the fermentation pathway in the Saccharomyces cerevisiae kinetic model help saves much time in the optimization process. Fitting the simulated model into the experimental data is categorized under the parameter estimation problem. Parameter estimation is conducted to obtain the optimal values for parameters related to the fermentation process. This step is essential because insufficient identification of model parameters can cause erroneous conclusions. The kinetic parameters cannot be measured directly. Therefore, they must be estimated from the experimental data either in vitro or in vivo. Parameter estimation is a challenging task in the biological process due to the complexity and nonlinearity of the model. Therefore, we propose the Artificial Bee Colony algorithm (ABC) to estimate the parameters in the fermentation pathway of S. cerevisiae to obtain more accurate values. A metabolite with a total of six parameters is involved in this article. The experimental results show that ABC outperforms other estimation algorithms and gives more accurate kinetic parameter values for the simulated model. Most of the estimated kinetic parameter values obtained from the proposed algorithm are the closest to the experimental data.
    Matched MeSH terms: Computer Simulation
  7. Thirugnanam S, Soong LW, Prabhu CM, Singh AK
    Sensors (Basel), 2023 May 26;23(11).
    PMID: 37299822 DOI: 10.3390/s23115095
    The need for power-efficient devices, such as smart sensor nodes, mobile devices, and portable digital gadgets, is markedly increasing and these devices are becoming commonly used in daily life. These devices continue to demand an energy-efficient cache memory designed on Static Random-Access Memory (SRAM) with enhanced speed, performance, and stability to perform on-chip data processing and faster computations. This paper presents an energy-efficient and variability-resilient 11T (E2VR11T) SRAM cell, which is designed with a novel Data-Aware Read-Write Assist (DARWA) technique. The E2VR11T cell comprises 11 transistors and operates with single-ended read and dynamic differential write circuits. The simulated results in a 45 nm CMOS technology exhibit 71.63% and 58.77% lower read energy than ST9T and LP10T and lower write energies of 28.25% and 51.79% against S8T and LP10T cells, respectively. The leakage power is reduced by 56.32% and 40.90% compared to ST9T and LP10T cells. The read static noise margin (RSNM) is improved by 1.94× and 0.18×, while the write noise margin (WNM) is improved by 19.57% and 8.70% against C6T and S8T cells. The variability investigation using the Monte Carlo simulation on 5000 samples highly validates the robustness and variability resilience of the proposed cell. The improved overall performance of the proposed E2VR11T cell makes it suitable for low-power applications.
    Matched MeSH terms: Computer Simulation
  8. Budati AK, Islam S, Hasan MK, Safie N, Bahar N, Ghazal TM
    Sensors (Basel), 2023 May 25;23(11).
    PMID: 37299798 DOI: 10.3390/s23115072
    The global expansion of the Visual Internet of Things (VIoT)'s deployment with multiple devices and sensor interconnections has been widespread. Frame collusion and buffering delays are the primary artifacts in the broad area of VIoT networking applications due to significant packet loss and network congestion. Numerous studies have been carried out on the impact of packet loss on Quality of Experience (QoE) for a wide range of applications. In this paper, a lossy video transmission framework for the VIoT considering the KNN classifier merged with the H.265 protocols. The performance of the proposed framework was assessed while considering the congestion of encrypted static images transmitted to the wireless sensor networks. The performance analysis of the proposed KNN-H.265 protocol is compared with the existing traditional H.265 and H.264 protocols. The analysis suggests that the traditional H.264 and H.265 protocols cause video conversation packet drops. The performance of the proposed protocol is estimated with the parameters of frame number, delay, throughput, packet loss ratio, and Peak Signal to Noise Ratio (PSNR) on MATLAB 2018a simulation software. The proposed model gives 4% and 6% better PSNR values than the existing two methods and better throughput.
    Matched MeSH terms: Computer Simulation
  9. Tan ZQ, Ooi EH, Chiew YS, Foo JJ, Ng EYK, Ooi ET
    Ultrasonics, 2023 May;131:106961.
    PMID: 36812819 DOI: 10.1016/j.ultras.2023.106961
    Sonothrombolysis is a technique that utilises ultrasound waves to excite microbubbles surrounding a clot. Clot lysis is achieved through mechanical damage induced by acoustic cavitation and through local clot displacement induced by acoustic radiation force (ARF). Despite the potential of microbubble-mediated sonothrombolysis, the selection of the optimal ultrasound and microbubble parameters remains a challenge. Existing experimental studies are not able to provide a complete picture of how ultrasound and microbubble characteristics influence the outcome of sonothrombolysis. Likewise, computational studies have not been applied in detail in the context of sonothrombolysis. Hence, the effect of interaction between the bubble dynamics and acoustic propagation on the acoustic streaming and clot deformation remains unclear. In the present study, we report for the first time the computational framework that couples the bubble dynamic phenomena with the acoustic propagation in a bubbly medium to simulate microbubble-mediated sonothrombolysis using a forward-viewing transducer. The computational framework was used to investigate the effects of ultrasound properties (pressure and frequency) and microbubble characteristics (radius and concentration) on the outcome of sonothrombolysis. Four major findings were obtained from the simulation results: (i) ultrasound pressure plays the most dominant role over all the other parameters in affecting the bubble dynamics, acoustic attenuation, ARF, acoustic streaming, and clot displacement, (ii) smaller microbubbles could contribute to a more violent oscillation and improve the ARF simultaneously when they are stimulated at higher ultrasound pressure, (iii) higher microbubbles concentration increases the ARF, and (iv) the effect of ultrasound frequency on acoustic attenuation is dependent on the ultrasound pressure. These results may provide fundamental insight that is crucial in bringing sonothrombolysis closer to clinical implementation.
    Matched MeSH terms: Computer Simulation*
  10. Walters K, Yaacob H
    Genet Epidemiol, 2023 Apr;47(3):249-260.
    PMID: 36739616 DOI: 10.1002/gepi.22517
    Currently, the only effect size prior that is routinely implemented in a Bayesian fine-mapping multi-single-nucleotide polymorphism (SNP) analysis is the Gaussian prior. Here, we show how the Laplace prior can be deployed in Bayesian multi-SNP fine mapping studies. We compare the ranking performance of the posterior inclusion probability (PIP) using a Laplace prior with the ranking performance of the corresponding Gaussian prior and FINEMAP. Our results indicate that, for the simulation scenarios we consider here, the Laplace prior can lead to higher PIPs than either the Gaussian prior or FINEMAP, particularly for moderately sized fine-mapping studies. The Laplace prior also appears to have better worst-case scenario properties. We reanalyse the iCOGS case-control data from the CASP8 region on Chromosome 2. Even though this study has a total sample size of nearly 90,000 individuals, there are still some differences in the top few ranked SNPs if the Laplace prior is used rather than the Gaussian prior. R code to implement the Laplace (and Gaussian) prior is available at https://github.com/Kevin-walters/lapmapr.
    Matched MeSH terms: Computer Simulation
  11. Dheyab MA, Aziz AA, Rahman AA, Ashour NI, Musa AS, Braim FS, et al.
    Biochim Biophys Acta Gen Subj, 2023 Apr;1867(4):130318.
    PMID: 36740000 DOI: 10.1016/j.bbagen.2023.130318
    BACKGROUND: Gold nanoparticles (Au NPs) are regarded as potential agents that enhance the radiosensitivity of tumor cells for theranostic applications. To elucidate the biological mechanisms of radiation dose enhancement effects of Au NPs as well as DNA damage attributable to the inclusion of Au NPs, Monte Carlo (MC) simulations have been deployed in a number of studies.

    SCOPE OF REVIEW: This review paper concisely collates and reviews the information reported in the simulation research in terms of MC simulation of radiosensitization and dose enhancement effects caused by the inclusion of Au NPs in tumor cells, simulation mechanisms, benefits and limitations.

    MAJOR CONCLUSIONS: In this review, we first explore the recent advances in MC simulation on Au NPs radiosensitization. The MC methods, physical dose enhancement and enhanced chemical and biological effects is discussed, followed by some results regarding the prediction of dose enhancement. We then review Multi-scale MC simulations of Au NP-induced DNA damages for X-ray irradiation. Moreover, we explain and look at Multi-scale MC simulations of Au NP-induced DNA damages for X-ray irradiation.

    GENERAL SIGNIFICANCE: Using advanced chemical module-implemented MC simulations, there is a need to assess the radiation-induced chemical radicals that contribute to the dose-enhancing and biological effects of multiple Au NPs.

    Matched MeSH terms: Computer Simulation
  12. Peter OJ, Panigoro HS, Abidemi A, Ojo MM, Oguntolu FA
    Acta Biotheor, 2023 Mar 06;71(2):9.
    PMID: 36877326 DOI: 10.1007/s10441-023-09460-y
    This paper is concerned with the formulation and analysis of an epidemic model of COVID-19 governed by an eight-dimensional system of ordinary differential equations, by taking into account the first dose and the second dose of vaccinated individuals in the population. The developed model is analyzed and the threshold quantity known as the control reproduction number [Formula: see text] is obtained. We investigate the equilibrium stability of the system, and the COVID-free equilibrium is said to be locally asymptotically stable when the control reproduction number is less than unity, and unstable otherwise. Using the least-squares method, the model is calibrated based on the cumulative number of COVID-19 reported cases and available information about the mass vaccine administration in Malaysia between the 24th of February 2021 and February 2022. Following the model fitting and estimation of the parameter values, a global sensitivity analysis was performed by using the Partial Rank Correlation Coefficient (PRCC) to determine the most influential parameters on the threshold quantities. The result shows that the effective transmission rate [Formula: see text], the rate of first vaccine dose [Formula: see text], the second dose vaccination rate [Formula: see text] and the recovery rate due to the second dose of vaccination [Formula: see text] are the most influential of all the model parameters. We further investigate the impact of these parameters by performing a numerical simulation on the developed COVID-19 model. The result of the study shows that adhering to the preventive measures has a huge impact on reducing the spread of the disease in the population. Particularly, an increase in both the first and second dose vaccination rates reduces the number of infected individuals, thus reducing the disease burden in the population.
    Matched MeSH terms: Computer Simulation
  13. Jain P, Chhabra H, Chauhan U, Prakash K, Gupta A, Soliman MS, et al.
    Sci Rep, 2023 Jan 31;13(1):1792.
    PMID: 36720922 DOI: 10.1038/s41598-023-29024-x
    A hepta-band terahertz metamaterial absorber (MMA) with modified dual T-shaped resonators deposited on polyimide is presented for sensing applications. The proposed polarization sensitive MMA is ultra-thin (0.061 λ) and compact (0.21 λ) at its lowest operational frequency, with multiple absorption peaks at 1.89, 4.15, 5.32, 5.84, 7.04, 8.02, and 8.13 THz. The impedance matching theory and electric field distribution are investigated to understand the physical mechanism of hepta-band absorption. The sensing functionality is evaluated using a surrounding medium with a refractive index between 1 and 1.1, resulting in good Quality factor (Q) value of 117. The proposed sensor has the highest sensitivity of 4.72 THz/RIU for glucose detection. Extreme randomized tree (ERT) model is utilized to predict absorptivities for intermediate frequencies with unit cell dimensions, substrate thickness, angle variation, and refractive index values to reduce simulation time. The effectiveness of the ERT model in predicting absorption values is evaluated using the Adjusted R2 score, which is close to 1.0 for nmin = 2, demonstrating the prediction efficiency in various test cases. The experimental results show that 60% of simulation time and resources can be saved by simulating absorber design using the ERT model. The proposed MMA sensor with an ERT model has potential applications in biomedical fields such as bacterial infections, malaria, and other diseases.
    Matched MeSH terms: Computer Simulation
  14. Paudel P, Park SE, Seong SH, Fauzi FM, Jung HA, Choi JS
    J Integr Neurosci, 2023 Jan 05;22(1):10.
    PMID: 36722239 DOI: 10.31083/j.jin2201010
    BACKGROUND: Cholecystokinin (CCK) is one of the most abundant peptides in the central nervous system and is believed to function as a neurotransmitter as well as a gut hormone with an inverse correlation of its level to anxiety and depression. Therefore, CCK receptors (CCKRs) could be a relevant target for novel antidepressant therapy.

    METHODS: In silico target prediction was first employed to predict the probability of the bromophenols interacting with key protein targets based on a model trained on known bioactivity data and chemical similarity considerations. Next, we tested the functional effect of natural bromophenols from Symphyocladia latiuscula on the CCK2 receptor followed by a molecular docking simulation to predict interactions between a compound and the binding site of the target protein.

    RESULTS: Results of cell-based functional G-protein coupled receptor (GPCR) assays demonstrate that bromophenols 2,3,6-tribromo-4,5-dihydroxybenzyl alcohol (1), 2,3,6-tribromo-4,5-dihydroxybenzyl methyl ether (2), and bis-(2,3,6-tribromo-4,5-dihydroxybenzyl) ether (3) are full CCK2 antagonists. Molecular docking simulation of 1‒3 with CCK2 demonstrated strong binding by means of interaction with prime interacting residues: Arg356, Asn353, Val349, His376, Phe227, and Pro210. Simulation results predicted good binding scores and interactions with prime residues, such as the reference antagonist YM022.

    CONCLUSIONS: The results of this study suggest bromophenols 1-3 are CCK2R antagonists that could be novel therapeutic agents for CCK2R-related diseases, especially anxiety and depression.

    Matched MeSH terms: Computer Simulation
  15. Baha Raja D, Abdul Taib NA, Teo AKJ, Jayaraj VJ, Ting CY
    Int Health, 2023 Jan 03;15(1):37-46.
    PMID: 35265998 DOI: 10.1093/inthealth/ihac005
    BACKGROUND: The computer simulation presented in this study aimed to investigate the effect of contact tracing on coronavirus disease 2019 (COVID-19) transmission and infection in the context of rising vaccination rates.

    METHODS: This study proposed a deterministic, compartmental model with contact tracing and vaccination components. We defined contact tracing effectiveness as the proportion of contacts of a positive case that was successfully traced and the vaccination rate as the proportion of daily doses administered per population in Malaysia. Sensitivity analyses on the untraced and infectious populations were conducted.

    RESULTS: At a vaccination rate of 1.4%, contact tracing with an effectiveness of 70% could delay the peak of untraced asymptomatic cases by 17 d and reduce it by 70% compared with 30% contact tracing effectiveness. A similar trend was observed for symptomatic cases when a similar experiment setting was used. We also performed sensitivity analyses by using different combinations of contact tracing effectiveness and vaccination rates. In all scenarios, the effect of contact tracing on COVID-19 incidence persisted for both asymptomatic and symptomatic cases.

    CONCLUSIONS: While vaccines are progressively rolled out, efficient contact tracing must be rapidly implemented concurrently to reach, find, test, isolate and support the affected populations to bring COVID-19 under control.

    Matched MeSH terms: Computer Simulation
  16. Mak WY, Ooi QX, Cruz CV, Looi I, Yuen KH, Standing JF
    Br J Clin Pharmacol, 2023 Jan;89(1):330-339.
    PMID: 35976674 DOI: 10.1111/bcp.15496
    AIM: nlmixr offers first-order conditional estimation (FOCE), FOCE with interaction (FOCEi) and stochastic approximation estimation-maximisation (SAEM) to fit nonlinear mixed-effect models (NLMEM). We modelled metformin's pharmacokinetic data using nlmixr and investigated SAEM and FOCEi's performance with respect to bias and precision of parameter estimates, and robustness to initial estimates.

    METHOD: Compartmental models were fitted. The final model was determined based on the objective function value and inspection of goodness-of-fit plots. The bias and precision of parameter estimates were compared between SAEM and FOCEi using stochastic simulations and estimations. For robustness, parameters were re-estimated as the initial estimates were perturbed 100 times and resultant changes evaluated.

    RESULTS: The absorption kinetics of metformin depend significantly on food status. Under the fasted state, the first-order absorption into the central compartment was preceded by zero-order infusion into the depot compartment, whereas for the fed state, the absorption into the depot was instantaneous followed by first-order absorption from depot into the central compartment. The means of relative mean estimation error (rMEE) ( ME E SAEM ME E FOCEi ) and rRMSE ( RMS E SAEM RMS E FOCEi ) were 0.48 and 0.35, respectively. All parameter estimates given by SAEM appeared to be narrowly distributed and were close to the true value used for simulation. In contrast, the distribution of estimates from FOCEi were skewed and more biased. When initial estimates were perturbed, FOCEi estimates were more biased and imprecise.

    DISCUSSION: nlmixr is reliable for NLMEM. SAEM was superior to FOCEi in terms of bias and precision, and more robust against initial estimate perturbations.

    Matched MeSH terms: Computer Simulation
  17. Athani A, Ghazali NNN, Anjum Badruddin I, Kamangar S, Salman Ahmed NJ, Honnutagi A
    Biomed Mater Eng, 2023;34(1):13-35.
    PMID: 36278331 DOI: 10.3233/BME-211333
    BACKGROUND: Coronary arteries disease has been reported as one of the principal roots of deaths worldwide.

    OBJECTIVE: The aim of this study is to analyze the multiphase pulsatile blood flow in the left coronary artery tree with stenosis.

    METHODS: The 3D left coronary artery model was reconstructed using 2D computerized tomography (CT) scan images. The Red Blood Cell (RBC) and varying hemodynamic parameters for single and multiphase blood flow conditions were analyzed.

    RESULTS: Results asserted that the multiphase blood flow modeling has a maximum velocity of 1.017 m/s and1.339 m/s at the stenosed region during the systolic and diastolic phases respectively. The increase in Wall Shear Stress (WSS) observed at the stenosed region during the diastole phase as compared during the systolic phase. It was also observed that the highest Oscillatory Shear Index (OSI) regions are found in the downstream area of stenosis and across the bifurcations. The increase in RBCs velocity from 0.45 m/s to 0.6 m/s across the stenosis was also noticed.

    CONCLUSION: The computational multiphase blood flow analysis improves the understanding and accuracy of the complex flow conditions of blood elements (RBC and Plasma) and provides the progression of the disease development in the coronary arteries. This study helps to enhance the diagnosis of the blocked (stenosed) arteries more precisely compared to the single-phase blood flow modeling.

    Matched MeSH terms: Computer Simulation
  18. Zain NM, Ismail Z
    PLoS One, 2023;18(2):e0276576.
    PMID: 36780455 DOI: 10.1371/journal.pone.0276576
    This paper presents a numerical analysis of blood flow in a diseased vessel within the presence of an external magnetic field. The blood flow was considered to be incompressible and fully developed, in that the non-Newtonian nature of the fluid was characterised as a generalised power law model for shear-thinning, Newtonian, and shear-thickening fluids. The impact of a transverse directed external magnetic field on blood flow through a stenosed bifurcated artery was investigated. The arterial geometry was considered as a bifurcated channel with overlapping shaped stenosis. The problem was treated mathematically using the Galerkin Least-Squares (GLS) method. The implementation of this numerical method managed to overcome the numerical instability faced by the classical Galerkin technique when adopted to a highly viscous flow. The benefit of GLS in circumventing the Ladyzhenskaya-Babuška-Brezzi (LBB) condition was utilized by evaluating both the velocity and pressure components at corner nodes of a unstructured triangular element. The non-linearity that emerged from the convective terms was then treated using the Newton-Raphson method, while the numerical integrals were computed using a Gaussian quadrature rule with six quadrature points. The findings obtained from this study were then compared with available results from the literature as well as Comsol multiphysics software to verify the accuracy and validity of the numerical algorithms. It was found that the application of magnetic field was able to overcome flow reversal by 39% for a shear-thinning fluid, 26% for a Newtonian fluid, and 27% for a shear-thickening fluid. The negative pressure and steep wall shear stress which occurs at the extremities of an overlapping stenosis throat were diminished by rise in magnetic intensity. This prevented thrombosis occurrence and produced a uniform calm flow.
    Matched MeSH terms: Computer Simulation
  19. Khalid H, Mekhilef S, Siddique MD, Wahyudie A, Ahmed M, Seyedmahmoudian M, et al.
    PLoS One, 2023;18(1):e0277331.
    PMID: 36638108 DOI: 10.1371/journal.pone.0277331
    Most silicon carbide (SiC) MOSFET models are application-specific. These are already defined by the manufacturers and their parameters are mostly partially accessible due to restrictions. The desired characteristic of any SiC model becomes highly important if an individual wants to visualize the impact of changing intrinsic parameters as well. Also, it requires a model prior knowledge to vary these parameters accordingly. This paper proposes the parameter extraction and its selection for Silicon Carbide (SiC) power N-MOSFET model in a unique way. The extracted parameters are verified through practical implementation with a small-scale high power DC-DC 5 to 2.5 output voltage buck converter using both hardware and software emphasis. The parameters extracted using the proposed method are also tested to verify the static and dynamic characteristics of SiC MOSFET. These parameters include intrinsic, junction and overlapping capacitance. The parameters thus extracted for the SiC MOSFET are analyzed by device performance. This includes input, output transfer characteristics and transient delays under different temperature conditions and loading capabilities. The simulation and experimental results show that the parameters are highly accurate. With its development, researchers will be able to simulate and test any change in intrinsic parameters along with circuit emphasis.
    Matched MeSH terms: Computer Simulation
  20. Butt AD, Khan J, Ahmad S, Ghaffar A, Abdullah Al-Gburi AJ, Hussein M
    PLoS One, 2023;18(4):e0280042.
    PMID: 37053176 DOI: 10.1371/journal.pone.0280042
    Biomedical telemetry relies heavily on implantable antennas. Due to this, we have designed and tested a compact, a circularly polarized, a low-profile biomedical implantable antenna that operate in the 2.45 GHz ISM band. In order to keep the antenna compact, modified co-planar waveguide (CPW) technology is used. Slotted rectangular patch with one 45-degree angle slot and truncated little patch on the left end of the ground plane generate a frequency-range antenna with circular polarization. Using a 0.25-millimeter-thick Roger Duroid-RT5880 substrate with a thickness of εr = 2.2, tanδ = 0.0009 provides flexibility. The volume of the antenna is 21 mm x 13.5 mm x 0.254 mm (0.25λg × 0.16λg × 0.003λg). The antenna covers 2.35-2.55 GHz (200 MHz) in free space and 1.63-1.17 GHz (1.17 GHz) in epidermal tissue. With skin tissue that has more bandwidth, the (x and y)-axis bends of the antenna are also simulated via the simulation. Bended antenna simulations and measurements show excellent agreement. At 2.45 GHz, the skin-like gel had -10dB impedance and 3dB axial ratio (AR) bandwidths of 47.7 and 53.8%, respectively. The ultimate result is that the SAR values are 0.78 W/kg in skin over 1 g of bulk tissue, as determined by simulations. The suggested SAR values are lower than the FCC's maximum allowable limit (FCC). This antenna is small enough to be implanted in the body, making it perfect for biomedical applications.
    Matched MeSH terms: Computer Simulation
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