Displaying publications 61 - 80 of 735 in total

Abstract:
Sort:
  1. Fulltext Investigation on the Curvature Correction Factor of Extension Spring
    Tan PS, Akhavan Farid A, Karimzadeh A, Rahimian Koloor SS, Petrů M
    Materials (Basel), 2020 Sep 21;13(18).
    PMID: 32967330 DOI: 10.3390/ma13184199
    The curvature correction factor is an important parameter in the stress calculation formulation of a helical extension spring, which describes the effect of spring wire curvature on the stress increase towards its inner radius. In this study, the parameters affecting the curvature correction factor were investigated through theoretical and numerical methods. Several finite element (FE) models of an extension spring were generated to obtain the distribution of the tensile stress in the spring. In this investigation, the hook orientation and the number of coils of the extension spring showed significant effects on the curvature correction factor. These parameters were not considered in the theoretical model for the calculation of the curvature correction factor, causing a deviation between the results of the FE model and the theoretical approach. A set of equations is proposed for the curvature correction factor, which relates both the spring index and the number of coils. These equations can be applied directly to the design of extension springs with a higher safety factor.
    Matched MeSH terms: Models, Theoretical
  2. Fulltext A novel design, analysis and 3D printing of Ti-6Al-4V alloy bio-inspired porous femoral stem
    Mehboob H, Tarlochan F, Mehboob A, Chang SH, Ramesh S, Harun WSW, et al.
    J Mater Sci Mater Med, 2020 Aug 20;31(9):78.
    PMID: 32816091 DOI: 10.1007/s10856-020-06420-7
    The current study is proposing a design envelope for porous Ti-6Al-4V alloy femoral stems to survive under fatigue loads. Numerical computational analysis of these stems with a body-centered-cube (BCC) structure is conducted in ABAQUS. Femoral stems without shell and with various outer dense shell thicknesses (0.5, 1.0, 1.5, and 2 mm) and inner cores (porosities of 90, 77, 63, 47, 30, and 18%) are analyzed. A design space (envelope) is derived by using stem stiffnesses close to that of the femur bone, maximum fatigue stresses of 0.3σys in the porous part, and endurance limits of the dense part of the stems. The Soderberg approach is successfully employed to compute the factor of safety Nf > 1.1. Fully porous stems without dense shells are concluded to fail under fatigue load. It is thus safe to use the porous stems with a shell thickness of 1.5 and 2 mm for all porosities (18-90%), 1 mm shell with 18 and 30% porosities, and 0.5 mm shell with 18% porosity. The reduction in stress shielding was achieved by 28%. Porous stems incorporated BCC structures with dense shells and beads were successfully printed.
    Matched MeSH terms: Models, Theoretical*
  3. Fulltext Pneumocephalus and air travel: an experimental investigation on the effects of aircraft cabin pressure on intracranial pressure
    Lim E, Lan BL, Ooi EH, Low HL
    Sci Rep, 2020 08 12;10(1):13626.
    PMID: 32788610 DOI: 10.1038/s41598-020-70614-w
    This study investigates the effects of aircraft cabin pressure on intracranial pressure (ICP) elevation of a pneumocephalus patient. We propose an experimental setup that simulates the intracranial hydrodynamics of a pneumocephalus patient during flight. It consists of an acrylic box (skull), air-filled balloon [intracranial air (ICA)], water-filled balloon (cerebrospinal fluid and blood) and agarose gel (brain). The cabin was replicated using a custom-made pressure chamber. The setup can measure the rise in ICP during depressurization to levels similar to that inside the cabin at cruising altitude. ΔICP, i.e. the difference between mean cruising ICP and initial ICP, was found to increase with ICA volume and ROC. However, ΔICP was independent of the initial ICP. The largest ΔICP was 5 mmHg; obtained when ICA volume and ROC were 20 ml and 1,600 ft/min, respectively. The postulated ICA expansion and the subsequent increase in ICP in pneumocephalus patients during flight were successfully quantified in a laboratory setting. Based on the quantitative and qualitative analyses of the results, an ICA volume of 20 ml and initial ICP of 15 mmHg were recommended as conservative thresholds that are required for safe air travel among pneumocephalus patients. This study provides laboratory data that may be used by doctors to advise post-neurosurgical patients if they can safely fly.
    Matched MeSH terms: Models, Theoretical*
  4. Fulltext Data of microwave assisted extraction and conventional hot water extraction of Dendrobium Sonia 'Earsakul' orchid flower
    Netramai S, Kijchavengkul T, Samsudin H, Lertsiri S
    Data Brief, 2020 Aug;31:105906.
    PMID: 32637506 DOI: 10.1016/j.dib.2020.105906
    Crude extracts of fresh Dendrobium Sonia 'Earsakul' orchid flowers (DSE) were prepared using microwave assisted extraction (MAE; using household microwave oven) and hot water extraction (HWE; at constant 80 °C). The obtained DSEs were measured their absorbance at λmax of 543 and 583 nm and determined their total monomeric anthocyanin contents (TAC). Mathematical models of MAE of Dendrobium Sonia 'Earsakul' orchid flower were constructed using response surface methodology - Box-Behnken design. Studied parameters included flower to water ratio, microwave power, and extraction time, with absorbance at λmax as response. The data generated were 1) visible spectrum (400-700 nm) of DSE; 2) absorbance values at λmax and 3) TAC of DSEs obtained from various extraction conditions of MAE and HWE; 4) linear equations describing correlations between TAC and absorbance at λmax of DSEs; and 5) mathematical models of MAE of Dendrobium Sonia 'Earsakul' orchid.
    Matched MeSH terms: Models, Theoretical
  5. Fulltext Modelling the Effectiveness of Epidemic Control Measures in Preventing the Transmission of COVID-19 in Malaysia
    Gill BS, Jayaraj VJ, Singh S, Mohd Ghazali S, Cheong YL, Md Iderus NH, et al.
    Int J Environ Res Public Health, 2020 Jul 30;17(15).
    PMID: 32751669 DOI: 10.3390/ijerph17155509
    Malaysia is currently facing an outbreak of COVID-19. We aim to present the first study in Malaysia to report the reproduction numbers and develop a mathematical model forecasting COVID-19 transmission by including isolation, quarantine, and movement control measures. We utilized a susceptible, exposed, infectious, and recovered (SEIR) model by incorporating isolation, quarantine, and movement control order (MCO) taken in Malaysia. The simulations were fitted into the Malaysian COVID-19 active case numbers, allowing approximation of parameters consisting of probability of transmission per contact (β), average number of contacts per day per case (ζ), and proportion of close-contact traced per day (q). The effective reproduction number (Rt) was also determined through this model. Our model calibration estimated that (β), (ζ), and (q) were 0.052, 25 persons, and 0.23, respectively. The (Rt) was estimated to be 1.68. MCO measures reduce the peak number of active COVID-19 cases by 99.1% and reduce (ζ) from 25 (pre-MCO) to 7 (during MCO). The flattening of the epidemic curve was also observed with the implementation of these control measures. We conclude that isolation, quarantine, and MCO measures are essential to break the transmission of COVID-19 in Malaysia.
    Matched MeSH terms: Models, Theoretical*
  6. Mathematical approaches in estimating aptamer-target binding affinity
    Thevendran R, Navien TN, Meng X, Wen K, Lin Q, Sarah S, et al.
    Anal Biochem, 2020 07 01;600:113742.
    PMID: 32315616 DOI: 10.1016/j.ab.2020.113742
    The performance of aptamers as versatile tools in numerous analytical applications is critically dependent on their high target binding specificity and selectivity. However, only the technical or methodological aspects of measuring aptamer-target binding affinities are focused, ignoring the equally important mathematical components that play pivotal roles in affinity measurements. In this study, we aim to provide a comprehensive review regarding the utilization of different mathematical models and equations, along with a detailed description of the computational steps involved in mathematically deriving the binding affinity of aptamers against their specific target molecules. Mathematical models ranging from one-site binding to multiple aptameric binding site-based models are explained in detail. Models applied in several different approaches of affinity measurements such as thermodynamics and kinetic analysis, including cooperativity and competitive-assay based mathematical models have been elaborately discussed. Mathematical models incorporating factors that could potentially affect affinity measurements are also further scrutinized.
    Matched MeSH terms: Models, Theoretical
  7. Optimized fuzzy inference system to enhance prediction accuracy for influent characteristics of a sewage treatment plant
    Ansari M, Othman F, El-Shafie A
    Sci Total Environ, 2020 Jun 20;722:137878.
    PMID: 32199382 DOI: 10.1016/j.scitotenv.2020.137878
    Sewage treatment plants (STPs) keep sewage contamination within safe levels and minimize the risk of environmental disasters. To achieve optimum operation of an STP, it is necessary for influent parameters to be measured or estimated precisely. In this research, six well-known influent chemical and biological characteristics, i.e., biochemical oxygen demand (BOD), chemical oxygen demand (COD), Ammoniacal Nitrogen (NH3-N), pH, oil and grease (OG) and suspended solids (SS), were modeled and predicted using the Sugeno fuzzy logic model. The membership function range of the fuzzy model was optimized by ANFIS, the integrated Genetic algorithms (GA), and the integrated particle swarm optimization (PSO) algorithms. The results were evaluated by different indices to find the accuracy of each algorithm. To ensure prediction accuracy, outliers in the predicted data were found and replaced with reasonable values. The results showed that both integrated GA-FIS and PSO-FIS algorithms performed at almost the same level and both had fewer errors than ANFIS. As the GA-FIS algorithm predicts BOD with fewer errors than PSO-FIS and the aim of this study is to provide an accurate prediction of missing data, GA-FIS was only used to predict the BOD parameter; the other parameters were predicted by PSO-FIS algorithm. As a result, the model successfully could provide outstanding performance for predicting the BOD, COD, NH3-N, OG, pH and SS with MAE equal to 3.79, 5.14, 0.4, 0.27, 0.02, and 3.16, respectively.
    Matched MeSH terms: Models, Theoretical
  8. Fulltext Modeling the Effect of Composition on Formation of Aerosolized Nanoemulsion System Encapsulating Docetaxel and Curcumin Using D-Optimal Mixture Experimental Design
    Asmawi AA, Salim N, Abdulmalek E, Abdul Rahman MB
    Int J Mol Sci, 2020 Jun 19;21(12).
    PMID: 32575390 DOI: 10.3390/ijms21124357
    The synergistic anticancer effect of docetaxel (DTX) and curcumin (CCM) has emerged as an attractive therapeutic candidate for lung cancer treatment. However, the lack of optimal bioavailability because of high toxicity, low stability, and poor solubility has limited their clinical success. Given this, an aerosolized nanoemulsion system for pulmonary delivery is recommended to mitigate these drawbacks. In this study, DTX- and CCM-loaded nanoemulsions were optimized using the D-optimal mixture experimental design (MED). The effect of nanoemulsion compositions towards two response variables, namely, particle size and aerosol size, was studied. The optimized formulations for both DTX- and CCM-loaded nanoemulsions were determined, and their physicochemical and aerodynamic properties were evaluated as well. The MED models achieved the optimum formulation for DTX- and CCM-loaded nanoemulsions containing a 6.0 wt% mixture of palm kernel oil ester (PKOE) and safflower seed oils (1:1), 2.5 wt% of lecithin, 2.0 wt% mixture of Tween 85 and Span 85 (9:1), and 2.5 wt% of glycerol in the aqueous phase. The actual values of the optimized formulations were in line with the predicted values obtained from the MED, and they exhibited desirable attributes of physicochemical and aerodynamic properties for inhalation therapy. Thus, the optimized formulations have potential use as a drug delivery system for a pulmonary application.
    Matched MeSH terms: Models, Theoretical
  9. Numerical simulation of normal and cancer cells' populations with fractional derivative under radiotherapy
    Farayola MF, Shafie S, Mohd Siam F, Khan I
    Comput Methods Programs Biomed, 2020 Apr;187:105202.
    PMID: 31835107 DOI: 10.1016/j.cmpb.2019.105202
    Background This paper presents a numerical simulation of normal and cancer cells' population dynamics during radiotherapy. The model used for the simulation was the improved cancer treatment model with radiotherapy. The model simulated the population changes during a fractionated cancer treatment process. The results gave the final populations of the cells, which provided the final volumes of the tumor and normal cells. Method The improved model was obtained by integrating the previous cancer treatment model with the Caputo fractional derivative. In addition, the cells' population decay due to radiation was accounted for by coupling the linear-quadratic model into the improved model. The simulation of the treatment process was done with numerical variables, numerical parameters, and radiation parameters. The numerical variables include the populations of the cells and the time of treatment. The numerical parameters were the model factors which included the proliferation rates of cells, competition coefficients of cells, and perturbation constant for normal cells. The radiation parameters were clinical data based on the treatment procedure. The numerical parameters were obtained from the previous literature while the numerical variables and radiation parameters, which were clinical data, were obtained from reported data of four cancer patients treated with radiotherapy. The four cancer patients had tumor volumes of 28.4 cm3, 18.8 cm3, 30.6 cm3, and 12.6 cm3 and were treated with different treatment plans and a fractionated dose of 1.8 Gy each. The initial populations of cells were obtained by using the tumor volumes. The computer simulations were done with MATLAB. Results The final volumes of the tumors, from the results of the simulations, were 5.67 cm3, 4.36 cm3, 5.74 cm3, and 6.15 cm3 while the normal cells' volumes were 28.17 cm3, 18.68 cm3, 30.34 cm3, and 12.54 cm3. The powers of the derivatives were 0.16774, 0.16557, 0.16835, and 0.16. A variance-based sensitivity analysis was done to corroborate the model with the clinical data. The result showed that the most sensitive factors were the power of the derivative and the cancer cells' proliferation rate. Conclusion The model provided information concerning the status of treatments and can also predict outcomes of other treatment plans.
    Matched MeSH terms: Models, Theoretical
  10. Fulltext Feedforward Artificial Neural Network-Based Model for Predicting the Removal of Phenolic Compounds from Water by Using Deep Eutectic Solvent-Functionalized CNTs
    Ibrahim RK, Fiyadh SS, AlSaadi MA, Hin LS, Mohd NS, Ibrahim S, et al.
    Molecules, 2020 Mar 26;25(7).
    PMID: 32225061 DOI: 10.3390/molecules25071511
    In the recent decade, deep eutectic solvents (DESs) have occupied a strategic place in green chemistry research. This paper discusses the application of DESs as functionalization agents for multi-walled carbon nanotubes (CNTs) to produce novel adsorbents for the removal of 2,4-dichlorophenol (2,4-DCP) from aqueous solution. Also, it focuses on the application of the feedforward backpropagation neural network (FBPNN) technique to predict the adsorption capacity of DES-functionalized CNTs. The optimum adsorption conditions that are required for the maximum removal of 2,4-DCP were determined by studying the impact of the operational parameters (i.e., the solution pH, adsorbent dosage, and contact time) on the adsorption capacity of the produced adsorbents. Two kinetic models were applied to describe the adsorption rate and mechanism. Based on the correlation coefficient (R2) value, the adsorption kinetic data were well defined by the pseudo second-order model. The precision and efficiency of the FBPNN model was approved by calculating four statistical indicators, with the smallest value of the mean square error being 5.01 × 10-5. Moreover, further accuracy checking was implemented through the sensitivity study of the experimental parameters. The competence of the model for prediction of 2,4-DCP removal was confirmed with an R2 of 0.99.
    Matched MeSH terms: Models, Theoretical
  11. Fulltext Microwave radiation-induced grafting of 2-methacryloyloxyethyl trimethyl ammonium chloride onto lentil extract (LE-g-DMC) as an emerging high-performance plant-based grafted coagulant
    Chua SC, Chong FK, Ul Mustafa MR, Mohamed Kutty SR, Sujarwo W, Abdul Malek M, et al.
    Sci Rep, 2020 03 03;10(1):3959.
    PMID: 32127558 DOI: 10.1038/s41598-020-60119-x
    The importance of graft copolymerization in the field of polymer science is analogous to the importance of alloying in the field of metals. This is attribute to the ability of the grafting method to regulate the properties of polymer 'tailor-made' according to specific needs. This paper described a novel plant-based coagulant, LE-g-DMC that synthesized through grafting of 2-methacryloyloxyethyl trimethyl ammonium chloride (DMC) onto the backbone of the lentil extract. The grafting process was optimized through the response surface methodology (RSM) using three-level Box-Behnken Design (BBD). Under optimum conditions, a promising grafting percentage of 120% was achieved. Besides, characterization study including SEM, zeta potential, TGA, FTIR and EDX were used to confirm the grafting of the DMC monomer chain onto the backbone of lentil extract. The grafted coagulant, LE-g-DMC outperformed lentil extract and alum in turbidity reduction and effective across a wide range of pH from pH 4 to pH 10. Besides, the use of LE-g-DMC as coagulant produced flocs with excellent settling ability (5.09 mL/g) and produced the least amount of sludge. Therefore, from an application and economic point of views, LE-g-DMC was superior to native lentil extract coagulant and commercial chemical coagulant, alum.
    Matched MeSH terms: Models, Theoretical
  12. Fulltext Cost-effectiveness of expanding the capacity of opioid agonist treatment in Ukraine: dynamic modeling analysis
    Morozova O, Crawford FW, Cohen T, Paltiel AD, Altice FL
    Addiction, 2020 Mar;115(3):437-450.
    PMID: 31478285 DOI: 10.1111/add.14797
    BACKGROUND AND AIMS: Although opioid agonist treatment (OAT) for opioid use disorder (OUD) is cost-effective in settings where the HIV epidemic is concentrated among people who inject drugs, OAT coverage in Ukraine remains far below internationally recommended targets. Scale-up is limited by both OAT availability and demand. This study aimed to evaluate the cost-effectiveness of a range of plausible OAT scale-up strategies in Ukraine incorporating the potential impact of treatment spillover and the real-world demand for addiction treatment.

    DESIGN, SETTING AND PARTICIPANTS: Ten-year horizon (2016-25) modeling study of opioid addiction epidemic and treatment that accommodated potential peer effects in opioid use initiation and supply-induced treatment demand in three Ukrainian cities: Kyiv, Mykolaiv and Lviv, comprising a simulated population of people at risk of and with OUD.

    MEASUREMENTS: Incremental cost per quality-adjusted life-year gained in the simulated population.

    FINDINGS: An estimated 12.2-, 2.4- and 13.4-fold OAT capacity increase over 2016 baseline capacity in Kyiv, Mykolaiv and Lviv, respectively, would be cost-effective at a willingness-to-pay of one per-capita gross domestic product (GDP) per quality-adjusted life-year gained. This result is robust to parametric and structural uncertainty. Even under the most ambitious capacity increase, OAT coverage (i.e. the proportion of people with OUD receiving OAT) over a 10-year modeling horizon would be 20, 11 and 17% in Kyiv, Mykolaiv and Lviv, respectively, owing to limited demand.

    CONCLUSIONS: It is estimated that a substantial increase in opioid agonist treatment (OAT) capacity in three Ukrainian cities would be cost-effective for a wide range of willingness-to-pay thresholds. Even a very ambitious capacity increase, however, is unlikely to reach internationally recommended coverage levels. Further increases in coverage may be limited by demand and would require addressing existing structural barriers to OAT access.

    Matched MeSH terms: Models, Theoretical
  13. Fulltext Effect of expanding opioid agonist therapies on the HIV epidemic and mortality in Ukraine: a modelling study
    Tan J, Altice FL, Madden LM, Zelenev A
    Lancet HIV, 2020 02;7(2):e121-e128.
    PMID: 31879250 DOI: 10.1016/S2352-3018(19)30373-X
    BACKGROUND: As HIV incidence and mortality continue to increase in eastern Europe and central Asia, particularly among people who inject drugs (PWID), it is crucial to effectively scale-up opioid agonist therapy (OAT), such as methadone or buprenorphine maintenance therapy, to optimise HIV outcomes. With low OAT coverage among PWID, we did an optimisation assessment using current OAT procurement and allocation, then modelled the effect of increased OAT scale-up on HIV incidence and mortality for 23 administrative regions of Ukraine.

    METHODS: We developed a linear optimisation model to estimate efficiency gains that could be achieved based on current procurement of OAT. We also developed a dynamic, compartmental population model of HIV transmission that included both injection and sexual risk to estimate the effect of OAT scale-up on HIV infections and mortality over a 10-year horizon. The compartmental population model was calibrated to HIV prevalence and incidence among PWID for 23 administrative regions of Ukraine. Sources for regional data included the SyrEx database, the Integrated Biological and Behavioral Survey, the Ukrainian Center for Socially Dangerous Disease Control of the Ministry of Health of Ukraine, the Public Health Center of the Ministry of Health of Ukraine, and the Ukrainian Census.

    FINDINGS: Under a status-quo scenario (OAT coverage of 2·7% among PWID), the number of new HIV infections among PWID in Ukraine over the next 10 years was projected to increase to 58 820 (95% CI 47 968-65 535), with striking regional differences. With optimum allocation of OAT without additional increases in procurement, OAT coverage could increase from 2·7% to 3·3% by increasing OAT doses to ensure higher retention levels. OAT scale-up to 10% and 20% over 10 years would, respectively, prevent 4368 (95% CI 3134-5243) and 10 864 (7787-13 038) new HIV infections and reduce deaths by 7096 (95% CI 5078-9160) and 17 863 (12 828-23 062), relative to the status quo. OAT expansion to 20% in five regions of Ukraine with the highest HIV burden would account for 56% of new HIV infections and 49% of deaths prevented over 10 years.

    INTERPRETATION: To optimise HIV prevention and treatment goals in Ukraine, OAT must be substantially scaled up in all regions. Increased medication procurement is needed, combined with optimisation of OAT dosing. Restricting OAT scale-up to some regions of Ukraine could benefit many PWID, but the regions most affected are not necessarily those with the highest HIV burden.

    FUNDING: National Institute on Drug Abuse.

    Matched MeSH terms: Models, Theoretical
  14. Fulltext Interventions to reduce HIV-related stigma in the healthcare settings: a scoping systematic review
    Natalia Che Ishak, Hayati Kadir Shahar, Rosliza Abdul Manaf
    Malaysian Journal of Medicine and Health Sciences, 2020;16(1):284-290.
    MyJurnal
    HIV-related stigma will discourage the efforts in preventing new infections and engaging people to receive treatment, care and support programmes. Identifying the valuable interventions programmes to reduce HIV-related stigma in a healthcare setting is vital in order to deliver the best health services. A scoping systematic review was conducted. Articles were searched based on Pubmed and ScienceDirect search engines. The key words used were HIV stigma, intervention and healthcare. Published English articles in the past ten years involving HIV stigma intervention studies, and studies that involved healthcare workers in a healthcare setting were included. Reviewed articles, systematic review and meta-analysis articles were excluded. Primary screening of titles and abstract of 85 articles were done. Secondary screening of 19 articles resulted in 8 articles, included in this manuscript. Most of the reviewed articles showed, application of the Integrated Theoretical Model in the intervention programme as a guide and utilising combined intervention components are effective tools in delivering the intervention programme. The stigma reduc- tion-intervention programme should focus on the intervention components as a whole including training of HCW, role plays, group discussions, games, sharing of information and contacts with PLHIV as well presentations and lec- tures. An integrative model of behavioural prophecy is perceived and it is particularly essential for interventions that focus on creating and fortifying the aim in conducting the chosen behaviour.
    Matched MeSH terms: Models, Theoretical
  15. Fulltext Photovoltaic modules evaluation and dry-season energy yield prediction model for NEM in Malaysia
    Islam SZ, Othman ML, Saufi M, Omar R, Toudeshki A, Islam SZ
    PLoS One, 2020;15(11):e0241927.
    PMID: 33180779 DOI: 10.1371/journal.pone.0241927
    This study analyzes the performance of two PV modules, amorphous silicon (a-Si) and crystalline silicon (c-Si) and predicts energy yield, which can be seen as facilitation to achieve the target of 35% reduction of greenhouse gases emission by 2030. Malaysia Energy Commission recommends crystalline PV modules for net energy metering (NEM), but the climate regime is a concern for output power and efficiency. Based on rainfall and irradiance data, this study aims to categorize the climate of peninsular Malaysia into rainy and dry seasons; and then the performance of the two modules are evaluated under the dry season. A new mathematical model is developed to predict energy yield and the results are validated through experimental and systematic error analysis. The parameters are collected using a self-developed ZigBeePRO-based wireless system with the rate of 3 samples/min over a period of five days. The results unveil that efficiency is inversely proportional to the irradiance due to negative temperature coefficient for crystalline modules. For this phenomenon, efficiency of c-Si (9.8%) is found always higher than a-Si (3.5%). However, a-Si shows better shadow tolerance compared to c-Si, observed from a lesser decrease rate in efficiency of the former with the increase in irradiance. Due to better spectrum response and temperature coefficient, a-Si shows greater performance on output power efficiency (OPE), performance ratio (PR), and yield factor. From the regression analysis, it is found that the coefficient of determination (R2) is between 0.7179 and 0.9611. The energy from the proposed model indicates that a-Si yields 15.07% higher kWh than c-Si when luminance for recorded days is 70% medium and 30% high. This study is important to determine the highest percentage of energy yield and to get faster NEM payback period, where as of now, there is no such model to indicate seasonal energy yield in Malaysia.
    Matched MeSH terms: Models, Theoretical
  16. Fulltext Evaluation and diagnosis of obstacles to land-based ecological security in resource-based cities: A case study of Xingtai city
    Zhu C, Li Y, Zhang L, Wang Y
    PLoS One, 2020;15(11):e0241618.
    PMID: 33156886 DOI: 10.1371/journal.pone.0241618
    To provide a theoretical basis for sustainable land resource utilization and a reference for areas with similar natural conditions, an evaluation index for land-based ecological security was constructed based on the Driving force-Pressure-State-Impact-Response (DPSIR) model and the improved analytic hierarchy process (IAHP) and entropy methods, and the land-based ecological security status of Xingtai city from 2006 to 2017 was evaluated. Then, the obstacles to land-based ecological security were diagnosed. The results show that the values of the comprehensive evaluation index of land-based ecological security were 0.28-0.66 in the period from 2006 to 2017. The value of the index of land-based ecological security was low in the first seven years and gradually improved in the last five years of the study period. However, the overall situation was grave, and the ecological security conditions were poor. The main obstacles to land-based ecological security were the usage of pesticides, investment in environmental pollution treatments, the degree of machine cultivation, the rate of cultivation and the usage of fertilizer in Xingtai city. Based on the results of the land-based ecological security evaluation and the main obstacles identified in Xingtai city, this paper proposes management strategies and suggestions for improving land-based ecological security in Xingtai city. The specific proposals are as follows: vigorously develop green agriculture, increase investment in environmental pollution control, increase input in science and technology, and strengthen supervision and management of land use.
    Matched MeSH terms: Models, Theoretical
  17. Fulltext Multi-stage feature selection (MSFS) algorithm for UWB-based early breast cancer size prediction
    Vijayasarveswari V, Andrew AM, Jusoh M, Sabapathy T, Raof RAA, Yasin MNM, et al.
    PLoS One, 2020;15(8):e0229367.
    PMID: 32790672 DOI: 10.1371/journal.pone.0229367
    Breast cancer is the most common cancer among women and it is one of the main causes of death for women worldwide. To attain an optimum medical treatment for breast cancer, an early breast cancer detection is crucial. This paper proposes a multi- stage feature selection method that extracts statistically significant features for breast cancer size detection using proposed data normalization techniques. Ultra-wideband (UWB) signals, controlled using microcontroller are transmitted via an antenna from one end of the breast phantom and are received on the other end. These ultra-wideband analogue signals are represented in both time and frequency domain. The preprocessed digital data is passed to the proposed multi- stage feature selection algorithm. This algorithm has four selection stages. It comprises of data normalization methods, feature extraction, data dimensional reduction and feature fusion. The output data is fused together to form the proposed datasets, namely, 8-HybridFeature, 9-HybridFeature and 10-HybridFeature datasets. The classification performance of these datasets is tested using the Support Vector Machine, Probabilistic Neural Network and Naïve Bayes classifiers for breast cancer size classification. The research findings indicate that the 8-HybridFeature dataset performs better in comparison to the other two datasets. For the 8-HybridFeature dataset, the Naïve Bayes classifier (91.98%) outperformed the Support Vector Machine (90.44%) and Probabilistic Neural Network (80.05%) classifiers in terms of classification accuracy. The finalized method is tested and visualized in the MATLAB based 2D and 3D environment.
    Matched MeSH terms: Models, Theoretical
  18. Fulltext Prediction of remaining useful life (RUL) of Komatsu excavator under reliability analysis in the Weibull-frailty model
    Ghomghaleh A, Khaloukakaie R, Ataei M, Barabadi A, Nouri Qarahasanlou A, Rahmani O, et al.
    PLoS One, 2020;15(7):e0236128.
    PMID: 32667940 DOI: 10.1371/journal.pone.0236128
    It is an essential task to estimate the remaining useful life (RUL) of machinery in the mining sector aimed at ensuring the production and the customer's satisfaction. In this study, a conceptual framework was used to determine the RUL under the reliability analysis in a frailty model. The proposed framework was implemented on a Komatsu PC-1250 excavator from the Sungun copper mine. Also, the Weibull-frailty model was selected to describe the failure behavior and compare it with the classical-exponential model. The frailty model was also used to evaluate the impact of unobserved environmental conditions on the RUL values. Both applied models were fitted to the obtained data from 80 operational hours of the Komatsu PC-1250 excavator. Plotting the results from the reliability analysis of two models demonstrated that the mine system with the frailty model performs better than the classical model before reaching the reliability of 80%. Besides, the frailty model shows a coherent with the operational time of the excavator, while the classical model demonstrates a sinusoid variation. The obtained results may be used for the development of maintenance, preventive repairs planning, and the spare parts replacement intervals.
    Matched MeSH terms: Models, Theoretical*
  19. Fulltext Risk Assessment of Fishing Trawl Activities to Subsea Pipelines of Sabah and Labuan Waters
    Ahmad Fuad AF, Said MH, Samo K, Rahman MAA, Mohd MH, Zainol I
    ScientificWorldJournal, 2020;2020:6957171.
    PMID: 33414690 DOI: 10.1155/2020/6957171
    Introduction. Trawling is a method of catching fish in a large volume where fish nets are pulled through water using one or two boats. Bottom trawling is where the nets are pulled over on the seabed. The gear of the bottom trawling would impact the exposed subsea pipeline, on the seabed. Subsea pipelines transport crude oil and gas from the offshore platform to shore facility. This study assesses the risk of fish trawling activities to the subsea pipelines at Sabah and Labuan offshore. The specification of trawl equipment used by local trawlers in Sabah was determined by the on-site survey. The frequency of a fish trawler crossing over the pipelines was calculated based interview on operation and site survey. The calculation of the pull-over load of the otter board was calculated using the DNVGL algorithm. The severity and frequency index of the risk matrix was developed based on literature review. Results showed that the pull-over load of the otter board would not damage the pipelines. The risk posed by the fish trawler activity to the pipelines is low and moderate.
    Matched MeSH terms: Models, Theoretical
  20. Scopolamine, a Toxin-Induced Experimental Model, Used for Research in Alzheimer's Disease
    Chen WN, Yeong KY
    CNS Neurol Disord Drug Targets, 2020;19(2):85-93.
    PMID: 32056532 DOI: 10.2174/1871527319666200214104331
    Scopolamine as a drug is often used to treat motion sickness. Derivatives of scopolamine have also found applications as antispasmodic drugs among others. In neuroscience-related research, it is often used to induce cognitive disorders in experimental models as it readily permeates the bloodbrain barrier. In the context of Alzheimer's disease, its effects include causing cholinergic dysfunction and increasing amyloid-β deposition, both of which are hallmarks of the disease. Hence, the application of scopolamine in Alzheimer's disease research is proven pivotal but seldom discussed. In this review, the relationship between scopolamine and Alzheimer's disease will be delineated through an overall effect of scopolamine administration and its specific mechanisms of action, discussing mainly its influences on cholinergic function and amyloid cascade. The validity of scopolamine as a model of cognitive impairment or neurotoxin model will also be discussed in terms of advantages and limitations with future insights.
    Matched MeSH terms: Models, Theoretical
Related Terms
Filters
Contact Us

Please provide feedback to Administrator (afdal@afpm.org.my)

External Links