Displaying publications 61 - 80 of 311 in total

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  1. Supramani S, Ahmad R, Ilham Z, Annuar MSM, Klaus A, Wan-Mohtar WAAQI
    AIMS Microbiol, 2019;5(1):19-38.
    PMID: 31384700 DOI: 10.3934/microbiol.2019.1.19
    Wild-cultivated medicinal mushroom Ganoderma lucidum was morphologically identified and sequenced using phylogenetic software. In submerged-liquid fermentation (SLF), biomass, exopolysaccharide (EPS) and intracellular polysaccharide (IPS) production of the identified G.lucidum was optimised based on initial pH, starting glucose concentration and agitation rate parameters using response surface methodology (RSM). Molecularly, the G. lucidum strain QRS 5120 generated 637 base pairs, which was commensurate with related Ganoderma species. In RSM, by applying central composite design (CCD), a polynomial model was fitted to the experimental data and was found to be significant in all parameters investigated. The strongest effect (p < 0.0001) was observed for initial pH for biomass, EPS and IPS production, while agitation showed a significant value (p < 0.005) for biomass. By applying the optimized conditions, the model was validated and generated 5.12 g/L of biomass (initial pH 4.01, 32.09 g/L of glucose and 102 rpm), 2.49 g/L EPS (initial pH 4, 24.25 g/L of glucose and 110 rpm) and 1.52 g/L of IPS (and initial pH 4, 40.43 g/L of glucose, 103 rpm) in 500 mL shake flask fermentation. The optimized parameters can be upscaled for efficient biomass, EPS and IPS production using G. lucidum.
    Matched MeSH terms: Models, Statistical
  2. Tuite AR, Watts AG, Khan K, Bogoch II
    Infect Dis Model, 2019;4:251-256.
    PMID: 31667444 DOI: 10.1016/j.idm.2019.09.001
    Southern Thailand has been experiencing a large chikungunya virus (CHIKV) outbreak since October 2018. Given the magnitude and duration of the outbreak and its location in a popular tourist destination, we sought to determine international case exportation risk and identify countries at greatest risk of receiving travel-associated imported CHIKV cases. We used a probabilistic model to estimate the expected number of exported cases from Southern Thailand between October 2018 and April 2019. The model incorporated data on CHIKV natural history, infection rates in Southern Thailand, average length of stay for tourists, and international outbound air passenger numbers from the outbreak area. For countries highly connected to Southern Thailand by air travel, we ran 1000 simulations to estimate the expected number of imported cases. We also identified destination countries with conditions suitable for autochthonous CHIKV transmission. Over the outbreak period, we estimated that an average of 125 (95% credible interval (CrI): 102-149) cases would be exported from Southern Thailand to international destinations via air travel. China was projected to receive the most cases (43, 95% CrI: 30-56), followed by Singapore (7, 95% CrI: 2-12) and Malaysia (5, 95% CrI: 1-10). Twenty-three countries were projected to receive at least one imported case, and 64% of these countries had one or more regions that could potentially support autochthonous CHIKV transmission. The overall risk of international exportation of CHIKV cases associated with the outbreak is Southern Thailand is high. Our model projections are consistent with recent reports of CHIKV in travelers returning from the region. Countries should be alert to the possibility of CHIKV infection in returning travelers, particularly in regions where autochthonous transmission is possible.
    Matched MeSH terms: Models, Statistical
  3. Muazu Musa R, P P Abdul Majeed A, Abdullah MR, Ab Nasir AF, Arif Hassan MH, Mohd Razman MA
    PLoS One, 2019;14(6):e0219138.
    PMID: 31247012 DOI: 10.1371/journal.pone.0219138
    The present study aims to identify the essential technical and tactical performance indicators that could differentiate winning and losing performance in the Asian elite beach soccer competition. A set of 20 technical and tactical performance indicators namely; shot back-third, shot mid-third, shot front-third, pass back-third, pass mid-third, pass front-third, shot in box, shot outbox, chances created, interception, turnover, goals scored 1st period, goals scored 2nd period, goals scored 3rd period, goals scored extra time, tackling, fouls committed, complete save, incomplete save and passing error were observed during the beach soccer Asian Football Confederation tournament 2017 held in Malaysia. A total of 23 matches from 12 teams were notated using StatWatch application in real-time. Discriminant analysis (DA) of standard, backward as well stepwise modes were used to develop a model for the winning (WT) and losing team (LT) whilst Mann-Whitney U test was utilized to ascertain the differences between the WT and LT with respect to the performance indicators evaluated. The standard backward, forward and stepwise discriminates the WT and the LT with an excellent accuracy of 95.65%, 91.30% and 89.13%, respectively. The standard DA model discriminated the teams from seven performance indicators whilst both the backward and forward stepwise identified two performance indicators. The Mann-Whitney U test analysis indicated that the WT is statistically significant from the LT based on the performance indicators determined from the standard mode model of the DA. It was demonstrated that seven performance indicators namely; shot front-third, pass front-third, chances created, goals scores at the 1st period, goals scored at the 2nd period, goals scored at 3rd period were directly linked to a successful performance whilst the incomplete save by the keeper attribute towards the poor performance of the team. The present finding could serve useful to the coaches as well as performance analysts as a measure of profiling successful performance and enables team improvement with respect to the associated performance indicators.
    Matched MeSH terms: Models, Statistical
  4. Nilashi M, Bin Ibrahim O, Mardani A, Ahani A, Jusoh A
    Health Informatics J, 2018 12;24(4):379-393.
    PMID: 30376769 DOI: 10.1177/1460458216675500
    As a chronic disease, diabetes mellitus has emerged as a worldwide epidemic. The aim of this study is to classify diabetes disease by developing an intelligence system using machine learning techniques. Our method is developed through clustering, noise removal and classification approaches. Accordingly, we use expectation maximization, principal component analysis and support vector machine for clustering, noise removal and classification tasks, respectively. We also develop the proposed method for incremental situation by applying the incremental principal component analysis and incremental support vector machine for incremental learning of data. Experimental results on Pima Indian Diabetes dataset show that proposed method remarkably improves the accuracy of prediction and reduces computation time in relation to the non-incremental approaches. The hybrid intelligent system can assist medical practitioners in the healthcare practice as a decision support system.
    Matched MeSH terms: Models, Statistical
  5. Rusli R, Haque MM, Afghari AP, King M
    Accid Anal Prev, 2018 Oct;119:80-90.
    PMID: 30007211 DOI: 10.1016/j.aap.2018.07.006
    Road safety in rural mountainous areas is a major concern as mountainous highways represent a complex road traffic environment due to complex topology and extreme weather conditions and are associated with more severe crashes compared to crashes along roads in flatter areas. The use of crash modelling to identify crash contributing factors along rural mountainous highways suffers from limitations in data availability, particularly in developing countries like Malaysia, and related challenges due to the presence of excess zero observations. To address these challenges, the objective of this study was to develop a safety performance function for multi-vehicle crashes along rural mountainous highways in Malaysia. To overcome the data limitations, an in-depth field survey, in addition to utilization of secondary data sources, was carried out to collect relevant information including roadway geometric factors, traffic characteristics, real-time weather conditions, cross-sectional elements, roadside features, and spatial characteristics. To address heterogeneity resulting from excess zeros, three specialized modelling techniques for excess zeros including Random Parameters Negative Binomial (RPNB), Random Parameters Negative Binomial - Lindley (RPNB-L) and Random Parameters Negative Binomial - Generalized Exponential (RPNB-GE) were employed. Results showed that the RPNB-L model outperformed the other two models in terms of prediction ability and model fit. It was found that heavy rainfall at the time of crash and the presence of minor junctions along mountainous highways increase the likelihood of multi-vehicle crashes, while the presence of horizontal curves along a steep gradient, the presence of a passing lane and presence of road delineation decrease the likelihood of multi-vehicle crashes. Findings of this study have significant implications for road safety along rural mountainous highways, particularly in the context of developing countries.
    Matched MeSH terms: Models, Statistical
  6. Hosseinpour M, Sahebi S, Zamzuri ZH, Yahaya AS, Ismail N
    Accid Anal Prev, 2018 Sep;118:277-288.
    PMID: 29861069 DOI: 10.1016/j.aap.2018.05.003
    According to crash configuration and pre-crash conditions, traffic crashes are classified into different collision types. Based on the literature, multi-vehicle crashes, such as head-on, rear-end, and angle crashes, are more frequent than single-vehicle crashes, and most often result in serious consequences. From a methodological point of view, the majority of prior studies focused on multivehicle collisions have employed univariate count models to estimate crash counts separately by collision type. However, univariate models fail to account for correlations which may exist between different collision types. Among others, multivariate Poisson lognormal (MVPLN) model with spatial correlation is a promising multivariate specification because it not only allows for unobserved heterogeneity (extra-Poisson variation) and dependencies between collision types, but also spatial correlation between adjacent sites. However, the MVPLN spatial model has rarely been applied in previous research for simultaneously modelling crash counts by collision type. Therefore, this study aims at utilizing a MVPLN spatial model to estimate crash counts for four different multi-vehicle collision types, including head-on, rear-end, angle, and sideswipe collisions. To investigate the performance of the MVPLN spatial model, a two-stage model and a univariate Poisson lognormal model (UNPLN) spatial model were also developed in this study. Detailed information on roadway characteristics, traffic volume, and crash history were collected on 407 homogeneous segments from Malaysian federal roads. The results indicate that the MVPLN spatial model outperforms the other comparing models in terms of goodness-of-fit measures. The results also show that the inclusion of spatial heterogeneity in the multivariate model significantly improves the model fit, as indicated by the Deviance Information Criterion (DIC). The correlation between crash types is high and positive, implying that the occurrence of a specific collision type is highly associated with the occurrence of other crash types on the same road segment. These results support the utilization of the MVPLN spatial model when predicting crash counts by collision manner. In terms of contributing factors, the results show that distinct crash types are attributed to different subsets of explanatory variables.
    Matched MeSH terms: Models, Statistical
  7. Alade IO, Bagudu A, Oyehan TA, Rahman MAA, Saleh TA, Olatunji SO
    Comput Methods Programs Biomed, 2018 Sep;163:135-142.
    PMID: 30119848 DOI: 10.1016/j.cmpb.2018.05.029
    BACKGROUND AND OBJECTIVES: The refractive index of hemoglobin plays important role in hematology due to its strong correlation with the pathophysiology of different diseases. Measurement of the real part of the refractive index remains a challenge due to strong absorption of the hemoglobin especially at relevant high physiological concentrations. So far, only a few studies on direct measurement of refractive index have been reported and there are no firm agreements on the reported values of refractive index of hemoglobin due to measurement artifacts. In addition, it is time consuming, laborious and expensive to perform several experiments to obtain the refractive index of hemoglobin. In this work, we proposed a very rapid and accurate computational intelligent approach using Genetic Algorithm/Support Vector Regression models to estimate the real part of the refractive index for oxygenated and deoxygenated hemoglobin samples.

    METHODS: These models utilized experimental data of wavelengths and hemoglobin concentrations in building highly accurate Genetic Algorithm/Support Vector Regression model (GA-SVR).

    RESULTS: The developed methodology showed high accuracy as indicated by the low root mean square error values of 4.65 × 10-4 and 4.62 × 10-4 for oxygenated and deoxygenated hemoglobin, respectively. In addition, the models exhibited 99.85 and 99.84% correlation coefficients (r) for the oxygenated and deoxygenated hemoglobin, thus, validating the strong agreement between the predicted and the experimental results CONCLUSIONS: Due to the accuracy and relative simplicity of the proposed models, we envisage that these models would serve as important references for future studies on optical properties of blood.

    Matched MeSH terms: Models, Statistical
  8. Ibrahim RW, Hasan AM, Jalab HA
    Comput Methods Programs Biomed, 2018 Sep;163:21-28.
    PMID: 30119853 DOI: 10.1016/j.cmpb.2018.05.031
    BACKGROUND AND OBJECTIVES: The MRI brain tumors segmentation is challenging due to variations in terms of size, shape, location and features' intensity of the tumor. Active contour has been applied in MRI scan image segmentation due to its ability to produce regions with boundaries. The main difficulty that encounters the active contour segmentation is the boundary tracking which is controlled by minimization of energy function for segmentation. Hence, this study proposes a novel fractional Wright function (FWF) as a minimization of energy technique to improve the performance of active contour without edge method.

    METHOD: In this study, we implement FWF as an energy minimization function to replace the standard gradient-descent method as minimization function in Chan-Vese segmentation technique. The proposed FWF is used to find the boundaries of an object by controlling the inside and outside values of the contour. In this study, the objective evaluation is used to distinguish the differences between the processed segmented images and ground truth using a set of statistical parameters; true positive, true negative, false positive, and false negative.

    RESULTS: The FWF as a minimization of energy was successfully implemented on BRATS 2013 image dataset. The achieved overall average sensitivity score of the brain tumors segmentation was 94.8 ± 4.7%.

    CONCLUSIONS: The results demonstrate that the proposed FWF method minimized the energy function more than the gradient-decent method that was used in the original three-dimensional active contour without edge (3DACWE) method.

    Matched MeSH terms: Models, Statistical
  9. Thiruchelvam L, Dass SC, Zaki R, Yahya A, Asirvadam VS
    Geospat Health, 2018 05 07;13(1):613.
    PMID: 29772882 DOI: 10.4081/gh.2018.613
    This study investigated the potential relationship between dengue cases and air quality - as measured by the Air Pollution Index (API) for five zones in the state of Selangor, Malaysia. Dengue case patterns can be learned using prediction models based on feedback (lagged terms). However, the question whether air quality affects dengue cases is still not thoroughly investigated based on such feedback models. This work developed dengue prediction models using the autoregressive integrated moving average (ARIMA) and ARIMA with an exogeneous variable (ARIMAX) time series methodologies with API as the exogeneous variable. The Box Jenkins approach based on maximum likelihood was used for analysis as it gives effective model estimates and prediction. Three stages of model comparison were carried out for each zone: first with ARIMA models without API, then ARIMAX models with API data from the API station for that zone and finally, ARIMAX models with API data from the zone and spatially neighbouring zones. Bayesian Information Criterion (BIC) gives goodness-of-fit versus parsimony comparisons between all elicited models. Our study found that ARIMA models, with the lowest BIC value, outperformed the rest in all five zones. The BIC values for the zone of Kuala Selangor were -800.66, -796.22, and -790.5229, respectively, for ARIMA only, ARIMAX with single API component and ARIMAX with API components from its zone and spatially neighbouring zones. Therefore, we concluded that API levels, either temporally for each zone or spatio- temporally based on neighbouring zones, do not have a significant effect on dengue cases.
    Matched MeSH terms: Models, Statistical
  10. Endarti D, Riewpaiboon A, Thavorncharoensap M, Praditsitthikorn N, Hutubessy R, Kristina SA
    Value Health Reg Issues, 2018 May;15:50-55.
    PMID: 29474178 DOI: 10.1016/j.vhri.2017.07.008
    OBJECTIVES: To gain insight into the most suitable foreign value set among Malaysian, Singaporean, Thai, and UK value sets for calculating the EuroQol five-dimensional questionnaire index score (utility) among patients with cervical cancer in Indonesia.

    METHODS: Data from 87 patients with cervical cancer recruited from a referral hospital in Yogyakarta province, Indonesia, from an earlier study of health-related quality of life were used in this study. The differences among the utility scores derived from the four value sets were determined using the Friedman test. Performance of the psychometric properties of the four value sets versus visual analogue scale (VAS) was assessed. Intraclass correlation coefficients and Bland-Altman plots were used to test the agreement among the utility scores. Spearman ρ correlation coefficients were used to assess convergent validity between utility scores and patients' sociodemographic and clinical characteristics. With respect to known-group validity, the Kruskal-Wallis test was used to examine the differences in utility according to the stages of cancer.

    RESULTS: There was significant difference among utility scores derived from the four value sets, among which the Malaysian value set yielded higher utility than the other three value sets. Utility obtained from the Malaysian value set had more agreements with VAS than the other value sets versus VAS (intraclass correlation coefficients and Bland-Altman plot tests results). As for the validity, the four value sets showed equivalent psychometric properties as those that resulted from convergent and known-group validity tests.

    CONCLUSIONS: In the absence of an Indonesian value set, the Malaysian value set was more preferable to be used compared with the other value sets. Further studies on the development of an Indonesian value set need to be conducted.

    Matched MeSH terms: Models, Statistical
  11. Thanimalai S, Shafie AA, Ahmad Hassali MA, Sinnadurai J
    Value Health Reg Issues, 2018 May;15:34-41.
    PMID: 29474176 DOI: 10.1016/j.vhri.2017.05.006
    BACKGROUND: Systematic anticoagulation management clinic is recommended to manage patients on chronic warfarin therapy. In Malaysia, the service was introduced as warfarin medication therapy adherence clinic (WMTAC), which is managed by pharmacists with a physician advisory.
    OBJECTIVES: To assess the cost-effectiveness of WMTAC in comparison with usual medical clinic (UMC), which is managed by medical officers in Kuala Lumpur Hospital, a tertiary referral hospital in Malaysia.
    METHODS: Data from a 6-month retrospective cohort study comparing the two clinics and the mean percentages of time in the therapeutic range for the patients were used to estimate the cost-effectiveness. The mean clinic costs were estimated using the time-motion study. A Markov model with a 6-monthly cycle was used to simulate lifetime cost-effectiveness from the perspective of the health care service provider. The base-case analysis assumed a cohort of patients with atrial fibrillation, 57 years of age with comorbid illnesses. The transition probabilities of these clinic outcomes were obtained from a literature search. Future costs and effectiveness were discounted by 3% to convert to present values. All costs were in Malaysian ringgit standardized for the year 2007.
    RESULTS: The mean 6-month treatment cost was lower for the WMTAC, which was significantly lower (P < 0.001). The UMC was found to be dominated by the WMTAC for both intermediate and lifetime analyses. The sensitivity analysis showed that clinic consultation costs had a major impact on the cost-effectiveness analysis.
    CONCLUSIONS: WMTAC is a more cost-effective option than UMC in Kuala Lumpur Hospital.
    Study site: Medical clinic, Hospital Kuala Lumpur, Malaysia
    Matched MeSH terms: Models, Statistical
  12. Shearer FM, Longbottom J, Browne AJ, Pigott DM, Brady OJ, Kraemer MUG, et al.
    Lancet Glob Health, 2018 03;6(3):e270-e278.
    PMID: 29398634 DOI: 10.1016/S2214-109X(18)30024-X
    BACKGROUND: Yellow fever cases are under-reported and the exact distribution of the disease is unknown. An effective vaccine is available but more information is needed about which populations within risk zones should be targeted to implement interventions. Substantial outbreaks of yellow fever in Angola, Democratic Republic of the Congo, and Brazil, coupled with the global expansion of the range of its main urban vector, Aedes aegypti, suggest that yellow fever has the propensity to spread further internationally. The aim of this study was to estimate the disease's contemporary distribution and potential for spread into new areas to help inform optimal control and prevention strategies.

    METHODS: We assembled 1155 geographical records of yellow fever virus infection in people from 1970 to 2016. We used a Poisson point process boosted regression tree model that explicitly incorporated environmental and biological explanatory covariates, vaccination coverage, and spatial variability in disease reporting rates to predict the relative risk of apparent yellow fever virus infection at a 5 × 5 km resolution across all risk zones (47 countries across the Americas and Africa). We also used the fitted model to predict the receptivity of areas outside at-risk zones to the introduction or reintroduction of yellow fever transmission. By use of previously published estimates of annual national case numbers, we used the model to map subnational variation in incidence of yellow fever across at-risk countries and to estimate the number of cases averted by vaccination worldwide.

    FINDINGS: Substantial international and subnational spatial variation exists in relative risk and incidence of yellow fever as well as varied success of vaccination in reducing incidence in several high-risk regions, including Brazil, Cameroon, and Togo. Areas with the highest predicted average annual case numbers include large parts of Nigeria, the Democratic Republic of the Congo, and South Sudan, where vaccination coverage in 2016 was estimated to be substantially less than the recommended threshold to prevent outbreaks. Overall, we estimated that vaccination coverage levels achieved by 2016 avert between 94 336 and 118 500 cases of yellow fever annually within risk zones, on the basis of conservative and optimistic vaccination scenarios. The areas outside at-risk regions with predicted high receptivity to yellow fever transmission (eg, parts of Malaysia, Indonesia, and Thailand) were less extensive than the distribution of the main urban vector, A aegypti, with low receptivity to yellow fever transmission in southern China, where A aegypti is known to occur.

    INTERPRETATION: Our results provide the evidence base for targeting vaccination campaigns within risk zones, as well as emphasising their high effectiveness. Our study highlights areas where public health authorities should be most vigilant for potential spread or importation events.

    FUNDING: Bill & Melinda Gates Foundation.

    Matched MeSH terms: Models, Statistical
  13. Loganathan T, Ng CW, Lee WS, Hutubessy RCW, Verguet S, Jit M
    Health Policy Plan, 2018 Mar 01;33(2):204-214.
    PMID: 29228339 DOI: 10.1093/heapol/czx166
    Cost-effectiveness thresholds (CETs) based on the Commission on Macroeconomics and Health (CMH) are extensively used in low- and middle-income countries (LMICs) lacking locally defined CETs. These thresholds were originally intended for global and regional prioritization, and do not reflect local context or affordability at the national level, so their value for informing resource allocation decisions has been questioned. Using these thresholds, rotavirus vaccines are widely regarded as cost-effective interventions in LMICs. However, high vaccine prices remain a barrier towards vaccine introduction. This study aims to evaluate the cost-effectiveness, affordability and threshold price of universal rotavirus vaccination at various CETs in Malaysia. Cost-effectiveness of Rotarix and RotaTeq were evaluated using a multi-cohort model. Pan American Health Organization Revolving Fund's vaccine prices were used as tender price, while the recommended retail price for Malaysia was used as market price. We estimate threshold prices defined as prices at which vaccination becomes cost-effective, at various CETs reflecting economic theories of human capital, societal willingness-to-pay and marginal productivity. A budget impact analysis compared programmatic costs with the healthcare budget. At tender prices, both vaccines were cost-saving. At market prices, cost-effectiveness differed with thresholds used. At market price, using 'CMH thresholds', Rotarix programmes were cost-effective and RotaTeq were not cost-effective from the healthcare provider's perspective, while both vaccines were cost-effective from the societal perspective. Using other CETs, both vaccines were not cost-effective at market price, from the healthcare provider's and societal perspectives. At tender and cost-effective prices, rotavirus vaccination cost ∼1 and 3% of the public health budget, respectively. Using locally defined thresholds, rotavirus vaccination is cost-effective at vaccine prices in line with international tenders, but not at market prices. Thresholds representing marginal productivity are likely to be lower than those reflecting human capital and individual preference measures, and may be useful in determining affordable vaccine prices.
    Matched MeSH terms: Models, Statistical
  14. Zabidin N, Mohamed AM, Zaharim A, Marizan Nor M, Rosli TI
    Int Orthod, 2018 03;16(1):133-143.
    PMID: 29478934 DOI: 10.1016/j.ortho.2018.01.009
    OBJECTIVES: To evaluate the relationship between human evaluation of the dental-arch form, to complete a mathematical analysis via two different methods in quantifying the arch form, and to establish agreement with the fourth-order polynomial equation.

    MATERIALS AND METHODS: This study included 64 sets of digitised maxilla and mandible dental casts obtained from a sample of dental arch with normal occlusion. For human evaluation, a convenient sample of orthodontic practitioners ranked the photo images of dental cast from the most tapered to the less tapered (square). In the mathematical analysis, dental arches were interpolated using the fourth-order polynomial equation with millimetric acetate paper and AutoCAD software. Finally, the relations between human evaluation and mathematical objective analyses were evaluated.

    RESULTS: Human evaluations were found to be generally in agreement, but only at the extremes of tapered and square arch forms; this indicated general human error and observer bias. The two methods used to plot the arch form were comparable.

    CONCLUSION: The use of fourth-order polynomial equation may be facilitative in obtaining a smooth curve, which can produce a template for individual arch that represents all potential tooth positions for the dental arch.

    Matched MeSH terms: Models, Statistical*
  15. Samsudin H, Auras R, Burgess G, Dolan K, Soto-Valdez H
    Food Res Int, 2018 03;105:920-929.
    PMID: 29433289 DOI: 10.1016/j.foodres.2017.11.065
    A two-step solution based on the boundary conditions of Crank's equations for mass transfer in a film was developed. Three driving factors, the diffusion (D), partition (Kp,f) and convective mass transfer coefficients (h), govern the sorption and/or desorption kinetics of migrants from polymer films. These three parameters were simultaneously estimated. They provide in-depth insight into the physics of a migration process. The first step was used to find the combination of D, Kp,f and h that minimized the sums of squared errors (SSE) between the predicted and actual results. In step 2, an ordinary least square (OLS) estimation was performed by using the proposed analytical solution containing D, Kp,f and h. Three selected migration studies of PLA/antioxidant-based films were used to demonstrate the use of this two-step solution. Additional parameter estimation approaches such as sequential and bootstrap were also performed to acquire a better knowledge about the kinetics of migration. The proposed model successfully provided the initial guesses for D, Kp,f and h. The h value was determined without performing a specific experiment for it. By determining h together with D, under or overestimation issues pertaining to a migration process can be avoided since these two parameters are correlated.
    Matched MeSH terms: Models, Statistical*
  16. Al-Kharasani NM, Zulkarnain ZA, Subramaniam S, Hanapi ZM
    Sensors (Basel), 2018 Feb 15;18(2).
    PMID: 29462884 DOI: 10.3390/s18020597
    Routing in Vehicular Ad hoc Networks (VANET) is a bit complicated because of the nature of the high dynamic mobility. The efficiency of routing protocol is influenced by a number of factors such as network density, bandwidth constraints, traffic load, and mobility patterns resulting in frequency changes in network topology. Therefore, Quality of Service (QoS) is strongly needed to enhance the capability of the routing protocol and improve the overall network performance. In this paper, we introduce a statistical framework model to address the problem of optimizing routing configuration parameters in Vehicle-to-Vehicle (V2V) communication. Our framework solution is based on the utilization of the network resources to further reflect the current state of the network and to balance the trade-off between frequent changes in network topology and the QoS requirements. It consists of three stages: simulation network stage used to execute different urban scenarios, the function stage used as a competitive approach to aggregate the weighted cost of the factors in a single value, and optimization stage used to evaluate the communication cost and to obtain the optimal configuration based on the competitive cost. The simulation results show significant performance improvement in terms of the Packet Delivery Ratio (PDR), Normalized Routing Load (NRL), Packet loss (PL), and End-to-End Delay (E2ED).
    Matched MeSH terms: Models, Statistical
  17. Khairudin N, Basri M, Fard Masoumi HR, Samson S, Ashari SE
    Molecules, 2018 Feb 13;23(2).
    PMID: 29438284 DOI: 10.3390/molecules23020397
    Azelaic acid (AzA) and its derivatives have been known to be effective in the treatment of acne and various cutaneous hyperpigmentary disorders. The esterification of azelaic acid with lauryl alcohol (LA) to produce dilaurylazelate using immobilized lipase B from Candida antarctica (Novozym 435) is reported. Response surface methodology was selected to optimize the reaction conditions. A well-fitting quadratic polynomial regression model for the acid conversion was established with regards to several parameters, including reaction time and temperature, enzyme amount, and substrate molar ratios. The regression equation obtained by the central composite design of RSM predicted that the optimal reaction conditions included a reaction time of 360 min, 0.14 g of enzyme, a reaction temperature of 46 °C, and a molar ratio of substrates of 1:4.1. The results from the model were in good agreement with the experimental data and were within the experimental range (R² of 0.9732).The inhibition zone can be seen at dilaurylazelate ester with diameter 9.0±0.1 mm activities against Staphylococcus epidermidis S273. The normal fibroblasts cell line (3T3) was used to assess the cytotoxicity activity of AzA and AzA derivative, which is dilaurylazelate ester. The comparison of the IC50 (50% inhibition of cell viability) value for AzA and AzA derivative was demonstrated. The IC50 value for AzA was 85.28 μg/mL, whereas the IC50 value for AzA derivative was more than 100 μg/mL. The 3T3 cell was still able to survive without any sign of toxicity from the AzA derivative; thus, it was proven to be non-toxic in this MTT assay when compared with AzA.
    Matched MeSH terms: Models, Statistical
  18. Zelenev A, Li J, Mazhnaya A, Basu S, Altice FL
    Lancet Infect Dis, 2018 02;18(2):215-224.
    PMID: 29153265 DOI: 10.1016/S1473-3099(17)30676-X
    BACKGROUND: Chronic infections with hepatitis C virus (HCV) and HIV are highly prevalent in the USA and concentrated in people who inject drugs. Treatment as prevention with highly effective new direct-acting antivirals is a prospective HCV elimination strategy. We used network-based modelling to analyse the effect of this strategy in HCV-infected people who inject drugs in a US city.

    METHODS: Five graph models were fit using data from 1574 people who inject drugs in Hartford, CT, USA. We used a degree-corrected stochastic block model, based on goodness-of-fit, to model networks of injection drug users. We simulated transmission of HCV and HIV through this network with varying levels of HCV treatment coverage (0%, 3%, 6%, 12%, or 24%) and varying baseline HCV prevalence in people who inject drugs (30%, 60%, 75%, or 85%). We compared the effectiveness of seven treatment-as-prevention strategies on reducing HCV prevalence over 10 years and 20 years versus no treatment. The strategies consisted of treatment assigned to either a randomly chosen individual who injects drugs or to an individual with the highest number of injection partners. Additional strategies explored the effects of treating either none, half, or all of the injection partners of the selected individual, as well as a strategy based on respondent-driven recruitment into treatment.

    FINDINGS: Our model estimates show that at the highest baseline HCV prevalence in people who inject drugs (85%), expansion of treatment coverage does not substantially reduce HCV prevalence for any treatment-as-prevention strategy. However, when baseline HCV prevalence is 60% or lower, treating more than 120 (12%) individuals per 1000 people who inject drugs per year would probably eliminate HCV within 10 years. On average, assigning treatment randomly to individuals who inject drugs is better than targeting individuals with the most injection partners. Treatment-as-prevention strategies that treat additional network members are among the best performing strategies and can enhance less effective strategies that target the degree (ie, the highest number of injection partners) within the network.

    INTERPRETATION: Successful HCV treatment as prevention should incorporate the baseline HCV prevalence and will achieve the greatest benefit when coverage is sufficiently expanded.

    FUNDING: National Institute on Drug Abuse.

    Matched MeSH terms: Models, Statistical
  19. Taha Z, Musa RM, P P Abdul Majeed A, Alim MM, Abdullah MR
    Hum Mov Sci, 2018 Feb;57:184-193.
    PMID: 29248809 DOI: 10.1016/j.humov.2017.12.008
    Support Vector Machine (SVM) has been shown to be an effective learning algorithm for classification and prediction. However, the application of SVM for prediction and classification in specific sport has rarely been used to quantify/discriminate low and high-performance athletes. The present study classified and predicted high and low-potential archers from a set of fitness and motor ability variables trained on different SVMs kernel algorithms. 50 youth archers with the mean age and standard deviation of 17.0 ± 0.6 years drawn from various archery programmes completed a six arrows shooting score test. Standard fitness and ability measurements namely hand grip, vertical jump, standing broad jump, static balance, upper muscle strength and the core muscle strength were also recorded. Hierarchical agglomerative cluster analysis (HACA) was used to cluster the archers based on the performance variables tested. SVM models with linear, quadratic, cubic, fine RBF, medium RBF, as well as the coarse RBF kernel functions, were trained based on the measured performance variables. The HACA clustered the archers into high-potential archers (HPA) and low-potential archers (LPA), respectively. The linear, quadratic, cubic, as well as the medium RBF kernel functions models, demonstrated reasonably excellent classification accuracy of 97.5% and 2.5% error rate for the prediction of the HPA and the LPA. The findings of this investigation can be valuable to coaches and sports managers to recognise high potential athletes from a combination of the selected few measured fitness and motor ability performance variables examined which would consequently save cost, time and effort during talent identification programme.
    Matched MeSH terms: Models, Statistical
  20. Sim SZ, Gupta RC, Ong SH
    Int J Biostat, 2018 Jan 09;14(1).
    PMID: 29306919 DOI: 10.1515/ijb-2016-0070
    In this paper, we study the zero-inflated Conway-Maxwell Poisson (ZICMP) distribution and develop a regression model. Score and likelihood ratio tests are also implemented for testing the inflation/deflation parameter. Simulation studies are carried out to examine the performance of these tests. A data example is presented to illustrate the concepts. In this example, the proposed model is compared to the well-known zero-inflated Poisson (ZIP) and the zero- inflated generalized Poisson (ZIGP) regression models. It is shown that the fit by ZICMP is comparable or better than these models.
    Matched MeSH terms: Models, Statistical*
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