Displaying publications 141 - 160 of 616 in total

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  1. Fulltext Correction of failure in linear antenna arrays with greedy sparseness constrained optimization technique
    Khan SU, Rahim MKA, Aminu-Baba M, Murad NA
    PLoS One, 2017;12(12):e0189240.
    PMID: 29253852 DOI: 10.1371/journal.pone.0189240
    This paper proposes the correction of faulty sensors using a synthesis of the greedy sparse constrained optimization GSCO) technique. The failure of sensors can damage the radiation power pattern in terms of sidelobes and nulls. The synthesis problem can recover the wanted power pattern with reduced number of sensors into the background of greedy algorithm and solved with orthogonal matching pursuit (OMP) technique. Numerical simulation examples of linear arrays are offered to demonstrate the effectiveness of getting the wanted power pattern with a reduced number of antenna sensors which is compared with the available techniques in terms of sidelobes level and number of nulls.
    Matched MeSH terms: Computer Simulation
  2. Fulltext Bromophenols from Symphyocladia latiuscula (Harvey) Yamada as Novel Cholecystokinin 2 Receptor Antagonists
    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
  3. Permeability studies of artificial and natural cancellous bone structures
    Syahrom A, Abdul Kadir MR, Abdullah J, Öchsner A
    Med Eng Phys, 2013 Jun;35(6):792-9.
    PMID: 22959618 DOI: 10.1016/j.medengphy.2012.08.011
    In the development of artificial cancellous bones, two major factors need to be considered: the integrity of the overall structure and its permeability. Whilst there have been many studies analysing the mechanical properties of artificial and natural cancellous bones, permeability studies, especially those using numerical simulation, are scarce. In this study, idealised cancellous bones were simulated from the morphological indices of natural cancellous bone. Three different orientations were also simulated to compare the anisotropic nature of the structure. Computational fluid dynamics methods were used to analyse fluid flow through the cancellous structures. A constant mass flow rate was used to determine the intrinsic permeability of the virtual specimens. The results showed similar permeability of the prismatic plate-and-rod model to the natural cancellous bone. The tetrakaidecahedral rod model had the highest permeability under simulated blood flow conditions, but the plate counterpart had the lowest. Analyses on the anisotropy of the virtual specimens showed the highest permeability for the horizontal orientation. Linear relationships were found between permeability and the two physical properties, porosity and bone surface area.
    Matched MeSH terms: Computer Simulation
  4. Fulltext Parameter extraction and selection for a scalable N-type SiC MOSFETs model and characteristic verification along with conventional dc-dc buck converter integration
    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
  5. Monte Carlo simulation of gold nanoparticles for X-ray enhancement application
    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
  6. Fulltext Machine learning assisted hepta band THz metamaterial absorber for biomedical applications
    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
  7. Technical-economic framework for designing of water pumping system based on photovoltaic clean energy with water storage for drinking application
    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
  8. Fulltext Single-fed broadband CPW-fed circularly polarized implantable antenna for sensing medical applications
    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
  9. In silico toxicity studies of traditional Chinese herbal medicine: A mini review
    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
  10. Mathematical Model of COVID-19 Pandemic with Double Dose Vaccination
    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
  11. Fulltext Artificial Bee Colony algorithm in estimating kinetic parameters for yeast fermentation pathway
    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
  12. Fulltext Classification-based deep neural network vs mixture density network models for insulin sensitivity prediction problem
    Benyó B, Paláncz B, Szlávecz Á, Szabó B, Kovács K, Chase JG
    Comput Methods Programs Biomed, 2023 Oct;240:107633.
    PMID: 37343375 DOI: 10.1016/j.cmpb.2023.107633
    Model-based glycemic control (GC) protocols are used to treat stress-induced hyperglycaemia in intensive care units (ICUs). The STAR (Stochastic-TARgeted) glycemic control protocol - used in clinical practice in several ICUs in New Zealand, Hungary, Belgium, and Malaysia - is a model-based GC protocol using a patient-specific, model-based insulin sensitivity to describe the patient's actual state. Two neural network based methods are defined in this study to predict the patient's insulin sensitivity parameter: a classification deep neural network and a Mixture Density Network based method. Treatment data from three different patient cohorts are used to train the network models. Accuracy of neural network predictions are compared with the current model- based predictions used to guide care. The prediction accuracy was found to be the same or better than the reference. The authors suggest that these methods may be a promising alternative in model-based clinical treatment for patient state prediction. Still, more research is needed to validate these findings, including in-silico simulations and clinical validation trials.
    Matched MeSH terms: Computer Simulation
  13. Fulltext Modeling discontinuous growth in reared Panulirus ornatus: A generalized additive model and Cox proportional hazard model approach
    Foo CH
    Math Biosci Eng, 2023 Jul 03;20(8):14487-14501.
    PMID: 37679145 DOI: 10.3934/mbe.2023648
    Crustaceans exhibit discontinuous growth as they shed hard shells periodically. Fundamentally, the growth of crustaceans is typically assessed through two key components, length increase after molting (LI) and time intervals between consecutive molts (TI). In this article, we propose a unified likelihood approach that combines a generalized additive model and a Cox proportional hazard model to estimate the parameters of LI and TI separately in crustaceans. This approach captures the observed discontinuity in individuals, providing a comprehensive understanding of crustacean growth patterns. Our study focuses on 75 ornate rock lobsters (Panulirus ornatus) off the Torres Strait in northeastern Australia. Through a simulation study, we demonstrate the effectiveness of the proposed models in characterizing the discontinuity with a continuous growth curve at the population level.
    Matched MeSH terms: Computer Simulation
  14. Fulltext ChatGPT's performance before and after teaching in mass casualty incident triage
    Gan RK, Uddin H, Gan AZ, Yew YY, González PA
    Sci Rep, 2023 Nov 21;13(1):20350.
    PMID: 37989755 DOI: 10.1038/s41598-023-46986-0
    Since its initial launching, ChatGPT has gained significant attention from the media, with many claiming that ChatGPT's arrival is a transformative milestone in the advancement of the AI revolution. Our aim was to assess the performance of ChatGPT before and after teaching the triage of mass casualty incidents by utilizing a validated questionnaire specifically designed for such scenarios. In addition, we compared the triage performance between ChatGPT and medical students. Our cross-sectional study employed a mixed-methods analysis to assess the performance of ChatGPT in mass casualty incident triage, pre- and post-teaching of Simple Triage And Rapid Treatment (START) triage. After teaching the START triage algorithm, ChatGPT scored an overall triage accuracy of 80%, with only 20% of cases being over-triaged. The mean accuracy of medical students on the same questionnaire yielded 64.3%. Qualitative analysis on pre-determined themes on 'walking-wounded', 'respiration', 'perfusion', and 'mental status' on ChatGPT showed similar performance in pre- and post-teaching of START triage. Additional themes on 'disclaimer', 'prediction', 'management plan', and 'assumption' were identified during the thematic analysis. ChatGPT exhibited promising results in effectively responding to mass casualty incident questionnaires. Nevertheless, additional research is necessary to ensure its safety and efficacy before clinical implementation.
    Matched MeSH terms: Computer Simulation
  15. Fulltext Performance of Google bard and ChatGPT in mass casualty incidents triage
    Gan RK, Ogbodo JC, Wee YZ, Gan AZ, González PA
    Am J Emerg Med, 2024 Jan;75:72-78.
    PMID: 37967485 DOI: 10.1016/j.ajem.2023.10.034
    AIM: The objective of our research is to evaluate and compare the performance of ChatGPT, Google Bard, and medical students in performing START triage during mass casualty situations.

    METHOD: We conducted a cross-sectional analysis to compare ChatGPT, Google Bard, and medical students in mass casualty incident (MCI) triage using the Simple Triage And Rapid Treatment (START) method. A validated questionnaire with 15 diverse MCI scenarios was used to assess triage accuracy and content analysis in four categories: "Walking wounded," "Respiration," "Perfusion," and "Mental Status." Statistical analysis compared the results.

    RESULT: Google Bard demonstrated a notably higher accuracy of 60%, while ChatGPT achieved an accuracy of 26.67% (p = 0.002). Comparatively, medical students performed at an accuracy rate of 64.3% in a previous study. However, there was no significant difference observed between Google Bard and medical students (p = 0.211). Qualitative content analysis of 'walking-wounded', 'respiration', 'perfusion', and 'mental status' indicated that Google Bard outperformed ChatGPT.

    CONCLUSION: Google Bard was found to be superior to ChatGPT in correctly performing mass casualty incident triage. Google Bard achieved an accuracy of 60%, while chatGPT only achieved an accuracy of 26.67%. This difference was statistically significant (p = 0.002).

    Matched MeSH terms: Computer Simulation
  16. Fulltext A new compact and low phase imbalance microstrip coupler for 5G wireless communication systems
    I Yahya S, Zubir F, Nouri L, Yusoff Z, Chaudhary MA, Assaad M, et al.
    PLoS One, 2023;18(12):e0296272.
    PMID: 38134045 DOI: 10.1371/journal.pone.0296272
    Microstrip couplers play a crucial role in signal processing and transmission in various applications, including RF and wireless communication, radar systems, and satellites. In this work, a novel microstrip 180° coupler is designed, fabricated and measured. The layout configuration of this coupler is completely new and different from the previously reported Rat-race, branch-line and directional couplers. To obtain the proposed coupler, the meandrous coupled lines are used and analyzed mathematically. To improve the performance of our coupler, an optimization method is used. The designed coupler is very compact with an overall size of 0.014λg2. The obtained values of S21 and S31 are -3.45 dB and -3.75 dB, respectively at the operating frequency, while the fractional bandwidth (FBW) is 56.2%. It operates at fo = 1.61 GHz (suitable for 5G applications) and can suppress harmonics up to 2.17fo. Another advantage of this coupler is its low phase imbalance, while the phase difference between S21 and S31 is 180°± 0.023°. Therefore, our device is a balanced coupler with ±0.3 dB magnitude unbalance at its operating frequency. It is important to note that it is very difficult to find a coupler that has all these advantages at the same time. The proposed 180° coupler is fabricated and measured. The comparison shows that the measurement and simulation results are in good agreement. Therefore, the proposed coupler can be easily used in designing high-performance 5G communication systems.
    Matched MeSH terms: Computer Simulation
  17. Fulltext A renewable approach to electric vehicle charging through solar energy storage
    Umair M, Hidayat NM, Sukri Ahmad A, Nik Ali NH, Mawardi MIM, Abdullah E
    PLoS One, 2024;19(2):e0297376.
    PMID: 38422065 DOI: 10.1371/journal.pone.0297376
    Developing novel EV chargers is crucial for accelerating Electric Vehicle (EV) adoption, mitigating range anxiety, and fostering technological advancements that enhance charging efficiency and grid integration. These advancements address current challenges and contribute to a more sustainable and convenient future of electric mobility. This paper explores the performance dynamics of a solar-integrated charging system. It outlines a simulation study on harnessing solar energy as the primary Direct Current (DC) EV charging source. The approach incorporates an Energy Storage System (ESS) to address solar intermittencies and mitigate photovoltaic (PV) mismatch losses. Executed through MATLAB, the system integrates key components, including solar PV panels, the ESS, a DC charger, and an EV battery. The study finds that a change in solar irradiance from 400 W/m2 to 1000 W/m2 resulted in a substantial 47% increase in the output power of the solar PV system. Simultaneously, the ESS shows a 38% boost in output power under similar conditions, with the assessments conducted at a room temperature of 25°C. The results emphasize that optimal solar panel placement with higher irradiance levels is essential to leverage integrated solar energy EV chargers. The research also illuminates the positive correlation between elevated irradiance levels and the EV battery's State of Charge (SOC). This correlation underscores the efficiency gains achievable through enhanced solar power absorption, facilitating more effective and expedited EV charging.
    Matched MeSH terms: Computer Simulation
  18. Fulltext Optimal power flow using hybrid firefly and particle swarm optimization algorithm
    Khan A, Hizam H, Bin Abdul Wahab NI, Lutfi Othman M
    PLoS One, 2020;15(8):e0235668.
    PMID: 32776932 DOI: 10.1371/journal.pone.0235668
    In this paper, a novel, effective meta-heuristic, population-based Hybrid Firefly Particle Swarm Optimization (HFPSO) algorithm is applied to solve different non-linear and convex optimal power flow (OPF) problems. The HFPSO algorithm is a hybridization of the Firefly Optimization (FFO) and the Particle Swarm Optimization (PSO) technique, to enhance the exploration, exploitation strategies, and to speed up the convergence rate. In this work, five objective functions of OPF problems are studied to prove the strength of the proposed method: total generation cost minimization, voltage profile improvement, voltage stability enhancement, the transmission lines active power loss reductions, and the transmission lines reactive power loss reductions. The particular fitness function is chosen as a single objective based on control parameters. The proposed HFPSO technique is coded using MATLAB software and its effectiveness is tested on the standard IEEE 30-bus test system. The obtained results of the proposed algorithm are compared to simulated results of the original Particle Swarm Optimization (PSO) method and the present state-of-the-art optimization techniques. The comparison of optimum solutions reveals that the recommended method can generate optimum, feasible, global solutions with fast convergence and can also deal with the challenges and complexities of various OPF problems.
    Matched MeSH terms: Computer Simulation
  19. Fulltext Guidelines for the use and interpretation of assays for monitoring autophagy (3rd edition)
    Klionsky DJ, Abdelmohsen K, Abe A, Abedin MJ, Abeliovich H, Acevedo Arozena A, et al.
    Autophagy, 2016;12(1):1-222.
    PMID: 26799652 DOI: 10.1080/15548627.2015.1100356
    Matched MeSH terms: Computer Simulation
  20. Synthesis, spectral characterisation, biocidal investigation, in-silico and molecular docking studies of 4-[(2-chloro-4-methylphenyl)carbamoyl]butanoic acid derived triorganotin(IV) compounds
    Hanifa B, Bibi N, Sirajuddin M, Tiekink ERT, Kubicki M, Khan I, et al.
    J Biomol Struct Dyn, 2024;42(4):1826-1845.
    PMID: 37114651 DOI: 10.1080/07391102.2023.2204160
    Three triorganotin(IV) compounds, R3Sn(L), with R = CH3 (1), n-C4H9 (2) and C6H5 (3), and LH = 4-[(2-chloro-4-methylphenyl)carbamoyl]butanoic acid, were prepared and confirmed by various techniques. A five-coordinate, distorted trigonal-bipyramidal geometry was elucidated for tin(IV) centres both in solution and solid states. An intercalation mode was confirmed for the compound SS-DNA interaction by UV-visible, viscometric techniques and molecular docking. MD simulation revealed stable binding of LH with SS-DNA. Anti-bacterial investigation revealed 2 to be generally the most potent, especially against Sa and Ab, i.e. having the lowest MIC values (≤0.25 μg/mL) compared to the standard anti-biotics vancomycin-HCl (MIC = 1 μg/mL) and colistin-sulphate (MIC = 0.25 μg/mL). Similarly, the anti-fungal profile shows 2 exhibits 100% inhibition against Ca and Cn fungal strains and has MIC values (≤0.25 μg/mL) comparatively lower than standard drug fluconazole (0.125 and 8 μg/mL for Ca and Cn, respectively). Compound 2 has the greatest activity with CC50 ≤ 25 μg/mL and HC50 > 32 μg/mL performed against HEC239 and RBC cell lines. The anti-cancer potential was assessed against the MG-U87 cell line, using cisplatin as the standard (133 µM), indicates 2 displays the greatest activity (IC50: 5.521 µM) at a 5 µM dose. The greatest anti-leishmanial potential was observed for 2 (87.75 at 1000 μg/mL) in comparison to amphotericin B (90.67). The biological assay correlates with the observed maximum of 89% scavenging activity exhibited by 2. The Swiss-ADME data publicised the screened compounds generally follow the rule of 5 of drug-likeness and have good bioavailability potential.
    Matched MeSH terms: Computer Simulation
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