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A Weibull statistics-based lignocellulose saccharification model and a built-in parameter accurately predict lignocellulose hydrolysis performance

Wang M, Han L, Liu S, Zhao X, Yang J, Loh SK, et al.

Biotechnol J, 2015 Sep;10(9):1424-33.
PMID: 26121186 DOI: 10.1002/biot.201400723

Renewable energy from lignocellulosic biomass has been deemed an alternative to depleting fossil fuels. In order to improve this technology, we aim to develop robust mathematical models for the enzymatic lignocellulose degradation process. By analyzing 96 groups of previously published and newly obtained lignocellulose saccharification results and fitting them to Weibull distribution, we discovered Weibull statistics can accurately predict lignocellulose saccharification data, regardless of the type of substrates, enzymes and saccharification conditions. A mathematical model for enzymatic lignocellulose degradation was subsequently constructed based on Weibull statistics. Further analysis of the mathematical structure of the model and experimental saccharification data showed the significance of the two parameters in this model. In particular, the λ value, defined the characteristic time, represents the overall performance of the saccharification system. This suggestion was further supported by statistical analysis of experimental saccharification data and analysis of the glucose production levels when λ and n values change. In conclusion, the constructed Weibull statistics-based model can accurately predict lignocellulose hydrolysis behavior and we can use the λ parameter to assess the overall performance of enzymatic lignocellulose degradation. Advantages and potential applications of the model and the λ value in saccharification performance assessment were discussed.

Matched MeSH terms: Models, Statistical*
Mechanical behaviour of in-situ chondrocytes subjected to different loading rates: a finite element study

Moo EK, Herzog W, Han SK, Abu Osman NA, Pingguan-Murphy B, Federico S

Biomech Model Mechanobiol, 2012 Sep;11(7):983-93.
PMID: 22234779 DOI: 10.1007/s10237-011-0367-2

Experimental findings indicate that in-situ chondrocytes die readily following impact loading, but remain essentially unaffected at low (non-impact) strain rates. This study was aimed at identifying possible causes for cell death in impact loading by quantifying chondrocyte mechanics when cartilage was subjected to a 5% nominal tissue strain at different strain rates. Multi-scale modelling techniques were used to simulate cartilage tissue and the corresponding chondrocytes residing in the tissue. Chondrocytes were modelled by accounting for the cell membrane, pericellular matrix and pericellular capsule. The results suggest that cell deformations, cell fluid pressures and fluid flow velocity through cells are highest at the highest (impact) strain rate, but they do not reach damaging levels. Tangential strain rates of the cell membrane were highest at the highest strain rate and were observed primarily in superficial tissue cells. Since cell death following impact loading occurs primarily in superficial zone cells, we speculate that cell death in impact loading is caused by the high tangential strain rates in the membrane of superficial zone cells causing membrane rupture and loss of cell content and integrity.

Matched MeSH terms: Models, Statistical
The relationship between dental anxiety and dental decay experience in antenatal mothers

Esa R, Savithri V, Humphris G, Freeman R

Eur J Oral Sci, 2010 Feb;118(1):59-65.
PMID: 20156266 DOI: 10.1111/j.1600-0722.2009.00701.x

The aim of this study was to investigate the relationship between dental anxiety and dental decay experience among antenatal mothers attending Maternal and Child Health clinics in Malaysia. A cross-sectional study was conducted on a consecutive sample of 407 antenatal mothers in Seremban, Malaysia. The questionnaire consisted of participants' demographic profile and the Dental Fear Survey. The D(3cv)MFS was employed as the outcome measure and was assessed by a single examiner (intraclass correlation = 0.98). A structural equation model was designed to inspect the relationship between dental anxiety and dental decay experience. The mean Dental Fear Survey score for all participants was 35.1 [95% confidence interval (34.0, 36.3)]. The mean D(3cv)MFS score was 10.8 [95% confidence interval (9.5, 12.1)]. Participants from low socio-economic status groups had significantly higher D(3cv)MFS counts than those from high socio-economic status groups. The path model with dental anxiety and socio-economic status as predictors of D(3cv)MFS showed satisfactory fit. The correlation between dental anxiety and dental decay experience was 0.30 (standardized estimate), indicating a positive association. Socio-economic status was also statistically significantly associated with the D(3cv)MFS count (beta = 0.19). This study presented robust evidence for the significant relationship between dental anxiety and dental decay experience in antenatal mothers.

Matched MeSH terms: Models, Statistical
Evaluation of traditional and consolidated rice farms in Guilan Province, Iran, using life cycle assessment and fuzzy modeling

Khoshnevisan B, Rajaeifar MA, Clark S, Shamahirband S, Anuar NB, Mohd Shuib NL, et al.

Sci Total Environ, 2014 May 15;481:242-51.
PMID: 24602908 DOI: 10.1016/j.scitotenv.2014.02.052

In this study the environmental impact of consolidated rice farms (CF) - farms which have been integrated to increase the mechanization index - and traditional farms (TF) - small farms with lower mechanization index - in Guilan Province, Iran, were evaluated and compared using Life cycle assessment (LCA) methodology and adaptive neuro-fuzzy inference system (ANFIS). Foreground data were collected from farmers using face-to-face questionnaires and background information about production process and inventory data was taken from the EcoInvent®2.0 database. The system boundary was confined to within the farm gate (cradle to farm gate) and two functional units (land and mass based) were chosen. The study also included a comparison of the input-output energy flows of the farms. The results revealed that the average amount of energy consumed by the CFs was 57 GJ compared to 74.2 GJ for the TFs. The energy ratios for CFs and TFs were 1.6 and 0.9, respectively. The LCA results indicated that CFs produced fewer environmental burdens per ton of produced rice. When compared according to the land-based FU the same results were obtained. This indicates that the differences between the two types of farms were not caused by a difference in their production level, but rather by improved management on the CFs. The analysis also showed that electricity accounted for the greatest share of the impact for both types of farms, followed by P-based and N-based chemical fertilizers. These findings suggest that the CFs had superior overall environmental performance compared to the TFs in the study area. The performance metrics of the model based on ANFIS show that it can be used to predict the environmental burdens of rice production with high accuracy and minimal error.

Matched MeSH terms: Models, Statistical*
A comparative study of count models: application to pedestrian-vehicle crashes along Malaysia federal roads

Hosseinpour M, Pour MH, Prasetijo J, Yahaya AS, Ghadiri SM

Traffic Inj Prev, 2013;14(6):630-8.
PMID: 23859313 DOI: 10.1080/15389588.2012.736649

The objective of this study was to examine the effects of various roadway characteristics on the incidence of pedestrian-vehicle crashes by developing a set of crash prediction models on 543 km of Malaysia federal roads over a 4-year time span between 2007 and 2010.

Matched MeSH terms: Models, Statistical*
Fulltext Investigation of micro- and nanosized particle erosion in a 90° pipe bend using a two-phase discrete phase model

Safaei MR, Mahian O, Garoosi F, Hooman K, Karimipour A, Kazi SN, et al.

ScientificWorldJournal, 2014;2014:740578.
PMID: 25379542 DOI: 10.1155/2014/740578

This paper addresses erosion prediction in 3-D, 90° elbow for two-phase (solid and liquid) turbulent flow with low volume fraction of copper. For a range of particle sizes from 10 nm to 100 microns and particle volume fractions from 0.00 to 0.04, the simulations were performed for the velocity range of 5-20 m/s. The 3-D governing differential equations were discretized using finite volume method. The influences of size and concentration of micro- and nanoparticles, shear forces, and turbulence on erosion behavior of fluid flow were studied. The model predictions are compared with the earlier studies and a good agreement is found. The results indicate that the erosion rate is directly dependent on particles' size and volume fraction as well as flow velocity. It has been observed that the maximum pressure has direct relationship with the particle volume fraction and velocity but has a reverse relationship with the particle diameter. It also has been noted that there is a threshold velocity as well as a threshold particle size, beyond which significant erosion effects kick in. The average friction factor is independent of the particle size and volume fraction at a given fluid velocity but increases with the increase of inlet velocities.

Matched MeSH terms: Models, Statistical*
Fulltext Forecasting COVID-19 Case Trends Using SARIMA Models during the Third Wave of COVID-19 in Malaysia

Tan CV, Singh S, Lai CH, Zamri ASSM, Dass SC, Aris TB, et al.

Int J Environ Res Public Health, 2022 Jan 28;19(3).
PMID: 35162523 DOI: 10.3390/ijerph19031504

With many countries experiencing a resurgence in COVID-19 cases, it is important to forecast disease trends to enable effective planning and implementation of control measures. This study aims to develop Seasonal Autoregressive Integrated Moving Average (SARIMA) models using 593 data points and smoothened case and covariate time-series data to generate a 28-day forecast of COVID-19 case trends during the third wave in Malaysia. SARIMA models were developed using COVID-19 case data sourced from the Ministry of Health Malaysia's official website. Model training and validation was conducted from 22 January 2020 to 5 September 2021 using daily COVID-19 case data. The SARIMA model with the lowest root mean square error (RMSE), mean absolute percentage error (MAE) and Bayesian information criterion (BIC) was selected to generate forecasts from 6 September to 3 October 2021. The best SARIMA model with a RMSE = 73.374, MAE = 39.716 and BIC = 8.656 showed a downward trend of COVID-19 cases during the forecast period, wherein the observed daily cases were within the forecast range. The majority (89%) of the difference between the forecasted and observed values was well within a deviation range of 25%. Based on this work, we conclude that SARIMA models developed in this paper using 593 data points and smoothened data and sensitive covariates can generate accurate forecast of COVID-19 case trends.

Matched MeSH terms: Models, Statistical
Fulltext Determine neighboring region spatial effect on dengue cases using ensemble ARIMA models

Thiruchelvam L, Dass SC, Asirvadam VS, Daud H, Gill BS

Sci Rep, 2021 Mar 12;11(1):5873.
PMID: 33712664 DOI: 10.1038/s41598-021-84176-y

The state of Selangor, in Malaysia consist of urban and peri-urban centres with good transportation system, and suitable temperature levels with high precipitations and humidity which make the state ideal for high number of dengue cases, annually. This study investigates if districts within the Selangor state do influence each other in determining pattern of dengue cases. Study compares two different models; the Autoregressive Integrated Moving Average (ARIMA) and Ensemble ARIMA models, using the Akaike Information Criterion (AIC) and Bayesian Information Criterion (BIC) measurement to gauge their performance tools. ARIMA model is developed using the epidemiological data of dengue cases, whereas ensemble ARIMA incorporates the neighbouring regions' dengue models as the exogenous variable (X), into traditional ARIMA model. Ensemble ARIMA models have better model fit compared to the basic ARIMA models by incorporating neighbuoring effects of seven districts which made of state of Selangor. The AIC and BIC values of ensemble ARIMA models to be smaller compared to traditional ARIMA counterpart models. Thus, study concludes that pattern of dengue cases for a district is subject to spatial effects of its neighbouring districts and number of dengue cases in the surrounding areas.

Matched MeSH terms: Models, Statistical*
Fulltext Existing and potential infection risk zones of yellow fever worldwide: a modelling analysis

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
Factor structure of parent and teacher ratings of the ODD symptoms for Malaysian primary school children

Gomez R

Asian J Psychiatr, 2017 Feb;25:22-26.
PMID: 28262156 DOI: 10.1016/j.ajp.2016.10.013

This present study used confirmatory factor analysis (CFA) to examine the applicability of one-, two- three- and second order Oppositional Defiant Disorder (ODD) factor models, proposed in previous studies, in a group of Malaysian primary school children. These models were primarily based on parent reports. In the current study, parent and teacher ratings of the ODD symptoms were obtained for 934 children. For both groups of respondents, the findings showing some support for all models examined, with most support for a second order model with Burke et al. (2010) three factors (oppositional, antagonistic, and negative affect) as the primary factors. The diagnostic implications of the findings are discussed.

Matched MeSH terms: Models, Statistical*
Hybrid Harmony Search-Artificial Intelligence Models in Credit Scoring

Goh RY, Lee LS, Seow HV, Gopal K

Entropy (Basel), 2020 Sep 04;22(9).
PMID: 33286758 DOI: 10.3390/e22090989

Credit scoring is an important tool used by financial institutions to correctly identify defaulters and non-defaulters. Support Vector Machines (SVM) and Random Forest (RF) are the Artificial Intelligence techniques that have been attracting interest due to their flexibility to account for various data patterns. Both are black-box models which are sensitive to hyperparameter settings. Feature selection can be performed on SVM to enable explanation with the reduced features, whereas feature importance computed by RF can be used for model explanation. The benefits of accuracy and interpretation allow for significant improvement in the area of credit risk and credit scoring. This paper proposes the use of Harmony Search (HS), to form a hybrid HS-SVM to perform feature selection and hyperparameter tuning simultaneously, and a hybrid HS-RF to tune the hyperparameters. A Modified HS (MHS) is also proposed with the main objective to achieve comparable results as the standard HS with a shorter computational time. MHS consists of four main modifications in the standard HS: (i) Elitism selection during memory consideration instead of random selection, (ii) dynamic exploration and exploitation operators in place of the original static operators, (iii) a self-adjusted bandwidth operator, and (iv) inclusion of additional termination criteria to reach faster convergence. Along with parallel computing, MHS effectively reduces the computational time of the proposed hybrid models. The proposed hybrid models are compared with standard statistical models across three different datasets commonly used in credit scoring studies. The computational results show that MHS-RF is most robust in terms of model performance, model explainability and computational time.

Matched MeSH terms: Models, Statistical
Computerized segmentation and measurement of chronic wound images

Ahmad Fauzi MF, Khansa I, Catignani K, Gordillo G, Sen CK, Gurcan MN

Comput Biol Med, 2015 May;60:74-85.
PMID: 25756704 DOI: 10.1016/j.compbiomed.2015.02.015

An estimated 6.5 million patients in the United States are affected by chronic wounds, with more than US$25 billion and countless hours spent annually for all aspects of chronic wound care. There is a need for an intelligent software tool to analyze wound images, characterize wound tissue composition, measure wound size, and monitor changes in wound in between visits. Performed manually, this process is very time-consuming and subject to intra- and inter-reader variability. In this work, our objective is to develop methods to segment, measure and characterize clinically presented chronic wounds from photographic images. The first step of our method is to generate a Red-Yellow-Black-White (RYKW) probability map, which then guides the segmentation process using either optimal thresholding or region growing. The red, yellow and black probability maps are designed to handle the granulation, slough and eschar tissues, respectively; while the white probability map is to detect the white label card for measurement calibration purposes. The innovative aspects of this work include defining a four-dimensional probability map specific to wound characteristics, a computationally efficient method to segment wound images utilizing the probability map, and auto-calibration of wound measurements using the content of the image. These methods were applied to 80 wound images, captured in a clinical setting at the Ohio State University Comprehensive Wound Center, with the ground truth independently generated by the consensus of at least two clinicians. While the mean inter-reader agreement between the readers varied between 67.4% and 84.3%, the computer achieved an average accuracy of 75.1%.

Matched MeSH terms: Models, Statistical
Fulltext Synthetic-type control charts for time-between-events monitoring

Yen FY, Chong KM, Ha LM

PLoS One, 2013;8(6):e65440.
PMID: 23755231 DOI: 10.1371/journal.pone.0065440

This paper proposes three synthetic-type control charts to monitor the mean time-between-events of a homogenous Poisson process. The first proposed chart combines an Erlang (cumulative time between events, Tr ) chart and a conforming run length (CRL) chart, denoted as Synth-Tr chart. The second proposed chart combines an exponential (or T) chart and a group conforming run length (GCRL) chart, denoted as GR-T chart. The third proposed chart combines an Erlang chart and a GCRL chart, denoted as GR-Tr chart. By using a Markov chain approach, the zero- and steady-state average number of observations to signal (ANOS) of the proposed charts are obtained, in order to evaluate the performance of the three charts. The optimal design of the proposed charts is shown in this paper. The proposed charts are superior to the existing T chart, Tr chart, and Synth-T chart. As compared to the EWMA-T chart, the GR-T chart performs better in detecting large shifts, in terms of the zero- and steady-state performances. The zero-state Synth-T4 and GR-Tr (r = 3 or 4) charts outperform the EWMA-T chart for all shifts, whereas the Synth-Tr (r = 2 or 3) and GR-T 2 charts perform better for moderate to large shifts. For the steady-state process, the Synth-Tr and GR-Tr charts are more efficient than the EWMA-T chart in detecting small to moderate shifts.

Matched MeSH terms: Models, Statistical*
Contraceptive method switching over women's reproductive careers: evidence from Malaysian life history data, 1940s-70s

DaVanzo J, Reboussin D, Starbird E, Tan BA, Hadi SA

J Biosoc Sci Suppl, 1989;11:95-116.
PMID: 2489987

Several new concepts are used to describe contraceptive use histories for nearly 1200 women in Peninsular Malaysia. These histories are summarized by 81 episode histories. Transition matrices provide useful summaries of the changes women make in their contraceptive practice from one pregnancy interval to the next. Data from the mid-1940s to mid-1970s, during which period there was a dramatic increase in contraceptive use, reveal considerable inertia in individual couples' contraceptive practice. Persistence with a method was greater the less effective the method: while 86% of couples using no method in one interval used no method in the next, only 56% of couples using the pill in one interval also used it in the next. Virtually all transitions are of three types: continuation with the same method, a change from no method to some method, or a change from some method to no method. For only 1% of all pregnancies did couples use one contraceptive method before a pregnancy and a different method after the pregnancy. Differences are examined by calendar year and education.

Matched MeSH terms: Models, Statistical
Fulltext The ability of analysts' recommendations to predict optimistic and pessimistic forecasts

Biglari V, Alfan EB, Ahmad RB, Hajian N

PLoS One, 2013;8(10):e73853.
PMID: 24146741 DOI: 10.1371/journal.pone.0073853

Previous researches show that buy (growth) companies conduct income increasing earnings management in order to meet forecasts and generate positive forecast Errors (FEs). This behavior however, is not inherent in sell (non-growth) companies. Using the aforementioned background, this research hypothesizes that since sell companies are pressured to avoid income increasing earnings management, they are capable, and in fact more inclined, to pursue income decreasing Forecast Management (FM) with the purpose of generating positive FEs. Using a sample of 6553 firm-years of companies that are listed in the NYSE between the years 2005-2010, the study determines that sell companies conduct income decreasing FM to generate positive FEs. However, the frequency of positive FEs of sell companies does not exceed that of buy companies. Using the efficiency perspective, the study suggests that even though buy and sell companies have immense motivation in avoiding negative FEs, they exploit different but efficient strategies, respectively, in order to meet forecasts. Furthermore, the findings illuminated the complexities behind informative and opportunistic forecasts that falls under the efficiency versus opportunistic theories in literature.

Matched MeSH terms: Models, Statistical*
Fulltext The influence of lightning induced voltage on the distribution power line polymer insulators

Izadi M, Abd Rahman MS, Ab-Kadir MZ, Gomes C, Jasni J, Hajikhani M

PLoS One, 2017;12(2):e0172118.
PMID: 28234930 DOI: 10.1371/journal.pone.0172118

Protection of medium voltage (MV) overhead lines against the indirect effects of lightning is an important issue in Malaysia and other tropical countries. Protection of these lines against the indirect effects of lightning is a major concern and can be improved by several ways. The choice of insulator to be used for instance, between the glass, ceramic or polymer, can help to improve the line performance from the perspective of increasing the breakdown strength. In this paper, the electrical performance of a 10 kV polymer insulator under different conditions for impulse, weather and insulator angle with respect to a cross-arm were studied (both experimental and modelling) and the results were discussed accordingly. Results show that the weather and insulator angle (with respect to the cross-arm) are surprisingly influenced the values of breakdown voltage and leakage current for both negative and positive impulses. Therefore, in order to select a proper protection system for MV lines against lightning induced voltage, consideration of the local information concerning the weather and also the insulator angles with respect to the cross-arm are very useful for line stability and performance.

Matched MeSH terms: Models, Statistical
Fulltext The Impact of Emotional Solidarity on Residents' Attitude and Tourism Development

Hasani A, Moghavvemi S, Hamzah A

PLoS One, 2016;11(6):e0157624.
PMID: 27341569 DOI: 10.1371/journal.pone.0157624

In many countries, especially one such as Malaysia, tourism has become a key factor in economic development, and the industry heavily relies on feedback from local residents. It is essential to observe and examine the perceptions of residents towards tourists and tourism development for better planning in realizing successful and sustainable tourism development. Therefore, this research measured the relationship between residents' welcoming nature, emotional closeness, and sympathetic understanding (emotional solidarity) towards tourists and their respective attitudes towards supporting tourism development. To test the proposed research model, we collected data using a questionnaire survey from 333 residents in rural areas in Malaysia. We used the structural equation modelling technique (Amos) to evaluate the research model, and the results revealed that the residents' willingness (welcoming nature) to accept tourists is the strongest factor that effects the residents' attitudes towards supporting tourism development. However, there was no significant relationship between residents' emotional closeness and their sympathetic understanding towards tourists with their attitude and support towards tourism development. Welcoming nature, emotional closeness, and sympathetic understanding are able to predict 48% of residents' attitudes towards tourism development and 62% of their support towards tourism development.

Matched MeSH terms: Models, Statistical
Fulltext An Efficient Framework Model for Optimizing Routing Performance in VANETs

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
Fulltext Scavenging of caffeine from aqueous medium through optimized H3PO4-activated Acacia mangium wood activated carbon: Statistical data of optimization

Danish M, Birnbach J, Mohamad Ibrahim MN, Hashim R

Data Brief, 2020 Feb;28:105045.
PMID: 31921950 DOI: 10.1016/j.dib.2019.105045

The optimization data presented here are part of the study planned to remove the caffeine from aqueous solution through the large surface area optimized H3PO4-activated Acacia mangium wood activated carbon (OAMW-AC). The maximum adsorption capacity of the OAMW-AC for caffeine adsorption was achieved (30.3 mg/g) through optimized independent variables such as, OAMW-AC dosage (3.0 g/L), initial caffeine concentration (100 mg/L), contact time (60 min), and solution pH (7.7). The adsorption capacity of OAMW-AC was optimized with the help of rotatable central composite design of response surface methodology. Under the stated optimized conditions for maximum adsorption capacity, the removal efficiency was calculated to be 93%. The statistical significance of the data set was tested through the analysis of variance (ANOVA) study. Data confirmed the statistical model for caffeine adsorption was significant. The regression coefficient (R2) of curve fitting through the quadratic model was found to be 0.9832, and the adjusted regression coefficient was observed to be 0.9675.

Matched MeSH terms: Models, Statistical
Response surface analysis and modeling of n-alkanes removal through bioremediation of weathered crude oil

Mohajeri L, Abdul Aziz H, Ali Zahed M, Mohajeri S, Mohamed Kutty SR, Hasnain Isa M

Water Sci Technol, 2011;63(4):618-26.
PMID: 21330705 DOI: 10.2166/wst.2011.211

Central composite design (CCD) and response surface methodology (RSM) were employed to optimize four important variables, i.e. amounts of oil, bacterial inoculum, nitrogen and phosphorus, for the removal of selected n-alkanes during bioremediation of weathered crude oil in coastal sediments using laboratory bioreactors over a 60 day experimentation period. The reactors contained 1 kg soil with different oil, microorganisms and nutrients concentrations. The F Value of 26.89 and the probability value (P < 0.0001) demonstrated significance of the regression model. For crude oil concentration of 2, 16 and 30 g per kg sediments and under optimized conditions, n-alkanes removal was 97.38, 93.14 and 90.21% respectively. Natural attenuation removed 30.07, 25.92 and 23.09% n-alkanes from 2, 16 and 30 g oil/kg sediments respectively. Excessive nutrients addition was found to inhibit bioremediation.

Matched MeSH terms: Models, Statistical*

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