Displaying publications 1 - 20 of 602 in total

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  1. Syahrom A, Abdul Kadir MR, Abdullah J, Öchsner A
    Med Biol Eng Comput, 2011 Dec;49(12):1393-403.
    PMID: 21947767 DOI: 10.1007/s11517-011-0833-0
    The relationship between microarchitecture to the failure mechanism and mechanical properties can be assessed through experimental and computational methods. In this study, both methods were utilised using bovine cadavers. Twenty four samples of cancellous bone were extracted from fresh bovine and the samples were cleaned from excessive marrow. Uniaxial compression testing was performed with displacement control. After mechanical testing, each specimen was ashed in a furnace. Four of the samples were exemplarily scanned using micro-computed tomography (μCT) and three dimensional models of the cancellous bones were reconstructed for finite element simulation. The mechanical properties and the failure modes obtained from numerical simulations were then compared to the experiments. Correlations between microarchitectural parameters to the mechanical properties and failure modes were then made. The Young's modulus correlates well with the bone volume fraction with R² = 0.615 and P value 0.013. Three different types of failure modes of cancellous bone were observed: oblique fracture (21.7%), perpendicular global fracture (47.8%), and scattered localised fracture (30.4%). However, no correlations were found between the failure modes to the morphological parameters. The percentage of error between computer predictions and the actual experimental test was from 6 to 12%. These mechanical properties and information on failure modes can be used for the development of synthetic cancellous bone.
    Matched MeSH terms: Computer Simulation
  2. 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
  3. Gavai AK, Supandi F, Hettling H, Murrell P, Leunissen JA, van Beek JH
    PLoS One, 2015;10(3):e0119016.
    PMID: 25806817 DOI: 10.1371/journal.pone.0119016
    Predicting the distribution of metabolic fluxes in biochemical networks is of major interest in systems biology. Several databases provide metabolic reconstructions for different organisms. Software to analyze flux distributions exists, among others for the proprietary MATLAB environment. Given the large user community for the R computing environment, a simple implementation of flux analysis in R appears desirable and will facilitate easy interaction with computational tools to handle gene expression data. We extended the R software package BiGGR, an implementation of metabolic flux analysis in R. BiGGR makes use of public metabolic reconstruction databases, and contains the BiGG database and the reconstruction of human metabolism Recon2 as Systems Biology Markup Language (SBML) objects. Models can be assembled by querying the databases for pathways, genes or reactions of interest. Fluxes can then be estimated by maximization or minimization of an objective function using linear inverse modeling algorithms. Furthermore, BiGGR provides functionality to quantify the uncertainty in flux estimates by sampling the constrained multidimensional flux space. As a result, ensembles of possible flux configurations are constructed that agree with measured data within precision limits. BiGGR also features automatic visualization of selected parts of metabolic networks using hypergraphs, with hyperedge widths proportional to estimated flux values. BiGGR supports import and export of models encoded in SBML and is therefore interoperable with different modeling and analysis tools. As an application example, we calculated the flux distribution in healthy human brain using a model of central carbon metabolism. We introduce a new algorithm termed Least-squares with equalities and inequalities Flux Balance Analysis (Lsei-FBA) to predict flux changes from gene expression changes, for instance during disease. Our estimates of brain metabolic flux pattern with Lsei-FBA for Alzheimer's disease agree with independent measurements of cerebral metabolism in patients. This second version of BiGGR is available from Bioconductor.
    Matched MeSH terms: Computer Simulation*
  4. Conroy-Beam D, Buss DM, Asao K, Sorokowska A, Sorokowski P, Aavik T, et al.
    Sci Rep, 2019 11 15;9(1):16885.
    PMID: 31729413 DOI: 10.1038/s41598-019-52748-8
    Humans express a wide array of ideal mate preferences. Around the world, people desire romantic partners who are intelligent, healthy, kind, physically attractive, wealthy, and more. In order for these ideal preferences to guide the choice of actual romantic partners, human mating psychology must possess a means to integrate information across these many preference dimensions into summaries of the overall mate value of their potential mates. Here we explore the computational design of this mate preference integration process using a large sample of n = 14,487 people from 45 countries around the world. We combine this large cross-cultural sample with agent-based models to compare eight hypothesized models of human mating markets. Across cultures, people higher in mate value appear to experience greater power of choice on the mating market in that they set higher ideal standards, better fulfill their preferences in choice, and pair with higher mate value partners. Furthermore, we find that this cross-culturally universal pattern of mate choice is most consistent with a Euclidean model of mate preference integration.
    Matched MeSH terms: Computer Simulation*
  5. Fazlena H, Kamaruddin AH, Zulkali MM
    Bioprocess Biosyst Eng, 2006 Mar;28(4):227-33.
    PMID: 16215728
    A lipase catalysed enantioselective hydrolysis process under in situ racemization of the remaining (R)-ibuprofen ester substrate with sodium hydroxide as the catalyst was developed for the production of S-ibuprofen from (R,S)-ibuprofen ester in isooctane. Detailed investigations on parameters study indicated that 0.5 M NaOH, addition of 20% (v/v) co-solvent (dimethyl sulphoxide), operating temperature of 45 degrees C, and 40 mmol/L substrate gave 86% conversion and 99.4% optical purity of S-ibuprofen in dynamic kinetic resolution. Meanwhile, in common enzymatic kinetic resolution process, only 42% conversion of the racemate and 93% enantiomeric excess of the product was obtained which are of lower values as compared to dynamic kinetic resolution. The S-ibuprofen produced during each process was evaluated and approximately 50% increment in concentration of S-acid product was produced when dynamic kinetic resolution was applied into the process.
    Matched MeSH terms: Computer Simulation
  6. Siti Hawa Binti Aziz, Zuliana Bt Abdul Mutalib
    MyJurnal
    The problem of constructing such a continuous function is called data fitting. Many times, data given only at discrete points. With interpolation, we seek a function that allows us to approximate f(x) such that functional values between the original data set values may be determined. The process of finding such a polynomial is called interpolation and one of the most important approaches used are Lagrange interpolating formula. In this study, researcher determining the polynomial interpolation by using Lagrange interpolating formula. Then, a mathematical modelling was built by using MATLAB programming to determine the polynomial interpolation for a given points using the Lagrange method. The result of the study showed that the manual calculating and the MATLAB mathematical modelling will give the same answer for evaluated x and graph.
    Matched MeSH terms: Computer Simulation
  7. Tou KAS, Rehman K, Ishak WMW, Zulfakar MH
    Drug Dev Ind Pharm, 2019 Sep;45(9):1451-1458.
    PMID: 31216907 DOI: 10.1080/03639045.2019.1628042
    Objective: The aim of this study was to develop a coenzyme Q10 nanoemulsion cream, characterize and to determine the influence of omega fatty acids on the delivery of coenzyme Q10 across model skin membrane via ex vivo and in silico techniques. Methods: Coenzyme Q10 nanoemulsion creams were prepared using natural edible oils such as linseed, evening primrose, and olive oil. Their mechanical features and ability to deliver CoQ10 across rat skin were characterized. Computational docking analysis was performed for in silico evaluation of CoQ10 and omega fatty acid interactions. Results: Linseed, evening primrose, and olive oils each produced nano-sized emulsion creams (343.93-409.86 nm) and exhibited excellent rheological features. The computerized docking studies showed favorable interactions between CoQ10 and omega fatty acids that could improve skin permeation. The three edible-oil nanoemulsion creams displayed higher ex vivo skin permeation and drug flux compared to the liquid-paraffin control cream. The linseed oil formulation displayed the highest skin permeation (3.97 ± 0.91 mg/cm2) and drug flux (0.19 ± 0.05 mg/cm2/h). Conclusion: CoQ10 loaded-linseed oil nanoemulsion cream displayed the highest skin permeation. The highest permeation showed by linseed oil nanoemulsion cream may be due to the presence of omega-3, -6, and -9 fatty acids which might serve as permeation enhancers. This indicated that the edible oil nanoemulsion creams have potential as drug vehicles that enhance CoQ10 delivery across skin.
    Matched MeSH terms: Computer Simulation
  8. Adnan AI, Hanapi ZM, Othman M, Zukarnain ZA
    PLoS One, 2017;12(1):e0170273.
    PMID: 28121992 DOI: 10.1371/journal.pone.0170273
    Due to the lack of dependency for routing initiation and an inadequate allocated sextant on responding messages, the secure geographic routing protocols for Wireless Sensor Networks (WSNs) have attracted considerable attention. However, the existing protocols are more likely to drop packets when legitimate nodes fail to respond to the routing initiation messages while attackers in the allocated sextant manage to respond. Furthermore, these protocols are designed with inefficient collection window and inadequate verification criteria which may lead to a high number of attacker selections. To prevent the failure to find an appropriate relay node and undesirable packet retransmission, this paper presents Secure Region-Based Geographic Routing Protocol (SRBGR) to increase the probability of selecting the appropriate relay node. By extending the allocated sextant and applying different message contention priorities more legitimate nodes can be admitted in the routing process. Moreover, the paper also proposed the bound collection window for a sufficient collection time and verification cost for both attacker identification and isolation. Extensive simulation experiments have been performed to evaluate the performance of the proposed protocol in comparison with other existing protocols. The results demonstrate that SRBGR increases network performance in terms of the packet delivery ratio and isolates attacks such as Sybil and Black hole.
    Matched MeSH terms: Computer Simulation
  9. 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
  10. Corda JV, Shenoy BS, Ahmad KA, Lewis L, K P, Khader SMA, et al.
    Comput Methods Programs Biomed, 2022 Feb;214:106538.
    PMID: 34848078 DOI: 10.1016/j.cmpb.2021.106538
    BACKGROUND AND OBJECTIVE: Neonates are preferential nasal breathers up to 3 months of age. The nasal anatomy in neonates and infants is at developing stages whereas the adult nasal cavities are fully grown which implies that the study of airflow dynamics in the neonates and infants are significant. In the present study, the nasal airways of the neonate, infant and adult are anatomically compared and their airflow patterns are investigated.

    METHODS: Computational Fluid Dynamics (CFD) approach is used to simulate the airflow in a neonate, an infant and an adult in sedentary breathing conditions. The healthy CT scans are segmented using MIMICS 21.0 (Materialise, Ann arbor, MI). The patient-specific 3D airway models are analyzed for low Reynolds number flow using ANSYS FLUENT 2020 R2. The applicability of the Grid Convergence Index (GCI) for polyhedral mesh adopted in this work is also verified.

    RESULTS: This study shows that the inferior meatus of neonates accounted for only 15% of the total airflow. This was in contrast to the infants and adults who experienced 49 and 31% of airflow at the inferior meatus region. Superior meatus experienced 25% of total flow which is more than normal for the neonate. The highest velocity of 1.8, 2.6 and 3.7 m/s was observed at the nasal valve region for neonates, infants and adults, respectively. The anterior portion of the nasal cavity experienced maximum wall shear stress with average values of 0.48, 0.25 and 0.58 Pa for the neonates, infants and adults.

    CONCLUSIONS: The neonates have an underdeveloped nasal cavity which significantly affects their airway distribution. The absence of inferior meatus in the neonates has limited the flow through the inferior regions and resulted in uneven flow distribution.

    Matched MeSH terms: Computer Simulation
  11. Muniyandi RC, Zin AM
    Pak J Biol Sci, 2011 Dec 15;14(24):1100-8.
    PMID: 22335049
    Ligand-Receptor Networks of TGF-beta plays essential role in transmitting a wide range of extracellular signals that affect many cellular processes such as cell growth. However, the modeling of these networks with conventional approach such as ordinary differential equations has not taken into account, the spatial structure and stochastic behavior of processes involve in these networks. Membrane computing as the alternatives approach provides spatial structure for molecular computation in which processes are evaluated in a non-deterministic and maximally parallel way. This study is carried out to evaluate the membrane computing model of Ligand-Receptor Networks of TGF-beta with model checking approach. The results show that membrane computing model has sustained the behaviors and properties of Ligand-Receptor Networks of TGF-beta. This reinforce that membrane computing is capable in analyzing processes and behaviors in hierarchical structure of cell such as Ligand-Receptor Networks of TGF-beta better than the deterministic approach of conventional mathematical models.
    Matched MeSH terms: Computer Simulation*
  12. Zanariah Abdul Majid, Nurul Asyikin Azmi, Mohamed Suleiman, Zarina Bibi Ibrahaim
    Sains Malaysiana, 2012;41:623-632.
    Two-point four step direct implicit block method is presented by applying the simple form of Adams- Moulton method for solving directly the general third order ordinary differential equations (ODEs) using variable step size. This method is implemented to get the solutions of initial value problems (IVPs) at two points simultaneously in a block using four backward steps. The numerical results showed that the performance of the developed method is better in terms of maximum error at all tested tolerances and lesser total number of steps as the tolerances getting smaller compared to the existence direct method.
    Matched MeSH terms: Computer Simulation
  13. Nazreen Waeleh, Zanariah Abdul Majid
    Sains Malaysiana, 2017;46:817-824.
    This paper outlines an alternative algorithm for solving general second order ordinary differential equations (ODEs). Normally, the numerical method was designed for solving higher order ODEs by converting it into an n-dimensional first order equations with implementation of constant step length. Nevertheless, this involved a lot of computational complexity which led to consumption a lot of time. Consequently, a direct block multistep method with utilization of variable step size strategy is proposed. This method was developed for computing the solution at four points simultaneously and the derivation based on numerical integration as well as using interpolation approach. The convergence of the proposed method is justified under suitable conditions of stability and consistency. Five numerical examples are considered and some comparisons are made with the existing methods for demonstrating the validity and reliability of the proposed algorithm.
    Matched MeSH terms: Computer Simulation
  14. Saddique FA, Aslam S, Ahmad M, Ashfaq UA, Muddassar M, Sultan S, et al.
    Molecules, 2021 May 20;26(10).
    PMID: 34065194 DOI: 10.3390/molecules26103043
    Diabetes mellitus (DM) is a chronic disorder and has affected a large number of people worldwide. Insufficient insulin production causes an increase in blood glucose level that results in DM. To lower the blood glucose level, various drugs are employed that block the activity of the α-glucosidase enzyme, which is considered responsible for the breakdown of polysaccharides into monosaccharides leading to an increase in the intestinal blood glucose level. We have synthesized novel 2-(3-(benzoyl/4-bromobenzoyl)-4-hydroxy-1,1-dioxido-2H-benzo[e][1,2]thiazin-2-yl)-N-arylacetamides and have screened them for their in silico and in vitro α-glucosidase inhibition activity. The derivatives 11c, 12a, 12d, 12e, and 12g emerged as potent inhibitors of the α-glucosidase enzyme. These compounds exhibited good docking scores and excellent binding interactions with the selected residues (Asp203, Asp542, Asp327, His600, Arg526) during in silico screening. Similarly, these compounds also showed good in vitro α-glucosidase inhibitions with IC50 values of 30.65, 18.25, 20.76, 35.14, and 24.24 μM, respectively, which were better than the standard drug, acarbose (IC50 = 58.8 μM). Furthermore, a good agreement was observed between in silico and in vitro modes of study.
    Matched MeSH terms: Computer Simulation
  15. Albahri AS, Hamid RA, Albahri OS, Zaidan AA
    Artif Intell Med, 2021 Jan;111:101983.
    PMID: 33461683 DOI: 10.1016/j.artmed.2020.101983
    CONTEXT AND BACKGROUND: Corona virus (COVID) has rapidly gained a foothold and caused a global pandemic. Particularists try their best to tackle this global crisis. New challenges outlined from various medical perspectives may require a novel design solution. Asymptomatic COVID-19 carriers show different health conditions and no symptoms; hence, a differentiation process is required to avert the risk of chronic virus carriers.

    OBJECTIVES: Laboratory criteria and patient dataset are compulsory in constructing a new framework. Prioritisation is a popular topic and a complex issue for patients with COVID-19, especially for asymptomatic carriers due to multi-laboratory criteria, criterion importance and trade-off amongst these criteria. This study presents new integrated decision-making framework that handles the prioritisation of patients with COVID-19 and can detect the health conditions of asymptomatic carriers.

    METHODS: The methodology includes four phases. Firstly, eight important laboratory criteria are chosen using two feature selection approaches. Real and simulation datasets from various medical perspectives are integrated to produce a new dataset involving 56 patients with different health conditions and can be used to check asymptomatic cases that can be detected within the prioritisation configuration. The first phase aims to develop a new decision matrix depending on the intersection between 'multi-laboratory criteria' and 'COVID-19 patient list'. In the second phase, entropy is utilised to set the objective weight, and TOPSIS is adapted to prioritise patients in the third phase. Finally, objective validation is performed.

    RESULTS: The patients are prioritised based on the selected criteria in descending order of health situation starting from the worst to the best. The proposed framework can discriminate among mild, serious and critical conditions and put patients in a queue while considering asymptomatic carriers. Validation findings revealed that the patients are classified into four equal groups and showed significant differences in their scores, indicating the validity of ranking.

    CONCLUSIONS: This study implies and discusses the numerous benefits of the suggested framework in detecting/recognising the health condition of patients prior to discharge, supporting the hospitalisation characteristics, managing patient care and optimising clinical prediction rule.

    Matched MeSH terms: Computer Simulation
  16. Kamil RN, Yusup S
    Bioresour Technol, 2010 Aug;101(15):5877-84.
    PMID: 20304636 DOI: 10.1016/j.biortech.2010.02.084
    A mathematical model describing chemical kinetics of transesterification of palm-based methyl esters with trimethylolpropane has been developed. The model was developed by utilizing nonlinear regression method, which is an efficient and powerful way to determine rate constants for both forward and reverse reactions. A comparison with previous study which excludes the reverse reactions was made. The model was based on the reverse mechanism of transesterification reactions and describes concentration changes of trimethylolpropane, monoesters and diesters production. The developed model was validated against data from the literature. The reaction rate constants were determined using MATLAB version 7.2 and the ratios of rate constants obtained were well in agreement with those reported in the literature. A good correlation between model simulations and experimental data was observed. It was proven that both methods were able to predict the rate constants with plausible accuracy.
    Matched MeSH terms: Computer Simulation
  17. Shahla S, Ngoh GC, Yusoff R
    Bioresour Technol, 2012 Jan;104:1-5.
    PMID: 22154586 DOI: 10.1016/j.biortech.2011.11.010
    In this paper, the kinetics of palm oil ethanolysis with various models have been investigated in a temperature range of 25-55 °C. The highest yield was achieved when the conversion to ethyl ester was 97.5±0.5% in the stated temperature range, using ethanol:oil molar ratio of 12:1, and 1.0 wt.% sodium ethoxide. The level of conformity of the reaction with reversible second order, irreversible second order and first order kinetic models were evaluated by means of the R(2) values of the linear curves. The ethanolysis showed the best conformity with irreversible second order kinetic model with 92-98% level of confidence. The reaction rate constants were within 0.018-0.088 dm(3)/mol min and the activation energy of the reaction was 42.36 kJ/mol.
    Matched MeSH terms: Computer Simulation
  18. Salehi Z, Yusoff AL
    Radiat Prot Dosimetry, 2013;154(3):396-9.
    PMID: 23012482 DOI: 10.1093/rpd/ncs239
    A femur phantom made of wax and a real human bone was used to study the dose during radiographical procedures. The depth dose inside the phantom was determined using DOSXYZnrc, a Monte Carlo simulation software. The results were verified with measurements using TLD-100H. It was found that for 2.5 mm aluminium filtered 84-kVp X-rays, the radiation dose in the bone reached 57 % higher than the surface dose, i.e. 3.23 mGy as opposed to 2.06 mGy at the surface. The use of real bone introduces variations in the bone density in the DOSXYZnrc model, resulting in a lower attenuation effect than expected from solid bone tissues.
    Matched MeSH terms: Computer Simulation
  19. Salehi Z, Ya Ali NK, Yusoff AL
    Appl Radiat Isot, 2012 Nov;70(11):2586-9.
    PMID: 22940409 DOI: 10.1016/j.apradiso.2011.12.007
    BEAMnrc was used to derive the X-ray spectra, from which HVL and homogeneity coefficient were determined, for different kVp and filtration settings. Except for the peak at 61 keV, the spectra are in good agreement with the IPEM report 78 data for the case of filtered beams, whereas the unfiltered beams exhibit softer spectra. Although the current attenuation data deviates from the IPEM 78 data by ~±0.5%, this has negligible effects on the calculated HVL values.
    Matched MeSH terms: Computer Simulation
  20. Shabanzadeh P, Yusof R
    Comput Math Methods Med, 2015;2015:802754.
    PMID: 26336509 DOI: 10.1155/2015/802754
    Unsupervised data classification (or clustering) analysis is one of the most useful tools and a descriptive task in data mining that seeks to classify homogeneous groups of objects based on similarity and is used in many medical disciplines and various applications. In general, there is no single algorithm that is suitable for all types of data, conditions, and applications. Each algorithm has its own advantages, limitations, and deficiencies. Hence, research for novel and effective approaches for unsupervised data classification is still active. In this paper a heuristic algorithm, Biogeography-Based Optimization (BBO) algorithm, was adapted for data clustering problems by modifying the main operators of BBO algorithm, which is inspired from the natural biogeography distribution of different species. Similar to other population-based algorithms, BBO algorithm starts with an initial population of candidate solutions to an optimization problem and an objective function that is calculated for them. To evaluate the performance of the proposed algorithm assessment was carried on six medical and real life datasets and was compared with eight well known and recent unsupervised data classification algorithms. Numerical results demonstrate that the proposed evolutionary optimization algorithm is efficient for unsupervised data classification.
    Matched MeSH terms: Computer Simulation
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