Displaying publications 81 - 100 of 311 in total

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  1. Fulltext Determination of Cutoff Values for the Screening of Osteosarcopenia in Obese Postmenopausal Women
    Abidin NZ, Mitra SR
    Curr Gerontol Geriatr Res, 2021;2021:6634474.
    PMID: 33790963 DOI: 10.1155/2021/6634474
    Osteosarcopenic obesity (OSO) describes the concurrent presence of obesity, low bone mass, and low muscle mass in an individual. Currently, no established criteria exist to diagnose OSO. We hypothesized that obese individuals require different cut-points from standard cut-points to define low bone mass and low muscle mass due to their higher weight load. In this study, we determined cutoff values for the screening of osteosarcopenia (OS) in obese postmenopausal Malaysian women based on the measurements of quantitative ultrasound (QUS), bioelectrical impedance analysis (BIA), and functional performance test. Then, we compared the cutoff values derived by 3 different statistical modeling methods, (1) receiver operating characteristic (ROC) curve, (2) lowest quintile of the study population, and (3) 2 standard deviations (SD) below the mean value of a young reference group, and discussed the most suitable method to screen for the presence of OS in obese population. One hundred and forty-one (n = 141) postmenopausal Malaysian women participated in the study. Bone density was assessed using calcaneal quantitative ultrasound. Body composition was assessed using bioelectrical impedance analyzer. Handgrip strength was assessed using a handgrip dynamometer, and physical performance was assessed using a modified Short Physical Performance Battery test. ROC curve was determined to be the most suitable statistical modeling method to derive the cutoffs for the presence of OS in obese population. From the ROC curve method, the final model to estimate the probability of OS in obese postmenopausal women is comprised of five variables: handgrip strength (HGS, with area under the curve (AUC) = 0.698 and threshold ≤ 16.5 kg), skeletal muscle mass index (SMMI, AUC = 0.966 and threshold ≤ 8.2 kg/m2), fat-free mass index (FFMI, AUC = 0.946 and threshold ≤ 15.2 kg/m2), broadband ultrasonic attenuation (BUA, AUC = 0.987 and threshold ≤ 52.85 dB/MHz), and speed of sound (SOS, AUC = 0.991 and threshold ≤ 1492.15 m/s). Portable equipment may be used to screen for OS in obese women. Early identification of OS can help lower the risk of advanced functional impairment that can lead to physical disability in obese postmenopausal women.
    Matched MeSH terms: Models, Statistical
  2. Determination of biochemical oxygen demand and dissolved oxygen for semi-arid river environment: application of soft computing models
    Tao H, Bobaker AM, Ramal MM, Yaseen ZM, Hossain MS, Shahid S
    Environ Sci Pollut Res Int, 2019 Jan;26(1):923-937.
    PMID: 30421367 DOI: 10.1007/s11356-018-3663-x
    Surface and ground water resources are highly sensitive aquatic systems to contaminants due to their accessibility to multiple-point and non-point sources of pollutions. Determination of water quality variables using mathematical models instead of laboratory experiments can have venerable significance in term of the environmental prospective. In this research, application of a new developed hybrid response surface method (HRSM) which is a modified model of the existing response surface model (RSM) is proposed for the first time to predict biochemical oxygen demand (BOD) and dissolved oxygen (DO) in Euphrates River, Iraq. The model was constructed using various physical and chemical variables including water temperature (T), turbidity, power of hydrogen (pH), electrical conductivity (EC), alkalinity, calcium (Ca), chemical oxygen demand (COD), sulfate (SO4), total dissolved solids (TDS), and total suspended solids (TSS) as input attributes. The monthly water quality sampling data for the period 2004-2013 was considered for structuring the input-output pattern required for the development of the models. An advance analysis was conducted to comprehend the correlation between the predictors and predictand. The prediction performances of HRSM were compared with that of support vector regression (SVR) model which is one of the most predominate applied machine learning approaches of the state-of-the-art for water quality prediction. The results indicated a very optimistic modeling accuracy of the proposed HRSM model to predict BOD and DO. Furthermore, the results showed a robust alternative mathematical model for determining water quality particularly in a data scarce region like Iraq.
    Matched MeSH terms: Models, Statistical*
  3. Determination of physical processes influencing Chl a distribution using remotely sensed images
    Mustapha AM, Lihan T, Saitoh S
    Pak J Biol Sci, 2011 Jan 15;14(2):82-90.
    PMID: 21916257
    In management of the Japanese scallop Mizuhopecten yessoensis culture, it is important to understand the phytoplankton bloom development in the coastal region of the Okhotsk Sea. Variations in food available to this benthic bivalve are a primary environmental factor affecting growth in nature. This paper determined the seasonal variability of Chlorophyll a (Chl a) at the scallop farming region in the Okhotsk Sea from 1998 to 2004 using satellite imageries. Satellite images were processed using default NASA coefficients and community-standard algorithms as implemented by Sea DAS. Spatial and temporal variation of Chl a was determined by EOF analysis. The Chl a concentration showed high seasonal and interannual variability. Peak of Chl a concentration occurred in spring followed by autumn and summer. This was evident in the Empirical Orthogonal Function (EOF) analysis. The spatial pattern of the first mode of EOF analysis of Chl a revealed intensified Chl a at the shelf and offshore areas in spring and autumn (51.8% of variance). The second mode explained 14.2% of the variance indicating enhancement of spring (April-May) Chl a pattern in the frontal area along the coast. Meanwhile, the third mode captured 9.0% of the variability demonstrating high Chl a extending seaward from the shelf area during late autumn. These seasonal variability of Chl a resulted from the variability in occurrences of physical processes associated with retreat of sea ice in spring, advection of Soya Warm Current in summer and intrusion of East Sakhalin Current in autumn.
    Matched MeSH terms: Models, Statistical
  4. 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*
  5. Fulltext Determining optimum conditions for lipase-catalyzed synthesis of triethanolamine (TEA)-based esterquat cationic surfactant by a Taguchi robust design method
    Masoumi HR, Kassim A, Basri M, Abdullah DK
    Molecules, 2011 Jun 03;16(6):4672-80.
    PMID: 21642941 DOI: 10.3390/molecules16064672
    A Taguchi robust design method with an L₉ orthogonal array was implemented to optimize experimental conditions for the biosynthesis of triethanolamine (TEA)-based esterquat cationic surfactants using an enzymatic reaction method. The esterification reaction conversion% was considered as the response. Enzyme amount, reaction time, reaction temperature and molar ratio of substrates, [oleic acid: triethanolamine (OA:TEA)] were chosen as main parameters. As a result of the Taguchi analysis in this study, the molar ratio of substrates was found to be the most influential parameter on the esterification reaction conversion%. The amount of enzyme in the reaction had also a significant effect on reaction conversion%.
    Matched MeSH terms: Models, Statistical
  6. Developing a dengue prediction model based on climate in Tawau, Malaysia
    Jayaraj VJ, Avoi R, Gopalakrishnan N, Raja DB, Umasa Y
    Acta Trop, 2019 Sep;197:105055.
    PMID: 31185224 DOI: 10.1016/j.actatropica.2019.105055
    Dengue is fast becoming the most urgent health issue in Malaysia, recording close to a 10-fold increase in cases over the last decade. With much uncertainty hovering over the recently introduced tetravalent vaccine and no effective antiviral drugs, vector control remains the most important strategy in combating dengue. This study analyses the relationship between weather predictors including its lagged terms, and dengue incidence in the District of Tawau over a period of 12 years, from 2006 to 2017. A forecasting model purposed to predict future outbreaks in Tawau was then developed using this data. Monthly dengue incidence data, mean temperature, maximum temperature, minimum temperature, mean relative humidity and mean rainfall over a period of 12 years from 2006 to 2017 in Tawau were retrieved from Tawau District Health Office and the Malaysian Meteorological Department. Cross-correlation analysis between weather predictors, lagged terms of weather predictors and dengue incidences established statistically significant cross-correlation between lagged periods of weather predictors-namely maximum temperature, mean relative humidity and mean rainfall with dengue incidence at time lags of 4-6 months. These variables were then employed into 3 different methods: a multivariate Poisson regression model, a Seasonal Autoregressive Integrated Moving Average (SARIMA) model and a SARIMA with external regressors for selection. Three models were selected but the SARIMA with external regressors model utilising maximum temperature at a lag of 6 months (p-value:0.001), minimum temperature at a lag of 4 months (p-value:0.01), mean relative humidity at a lag of 2 months (p-value:0.001), and mean rainfall at a lag of 6 months (p-value:0.001) produced an AIC of 841.94, and a log-likelihood score of -413.97 establishing it as the best fitting model of the methodologies utilised. In validating the models, they were utilised to develop forecasts with the model selected with the highest accuracy of predictions being the SARIMA model predicting 1 month in advance (MAE: 7.032, MSE: 83.977). This study establishes the effect of weather on the intensity and magnitude of dengue incidence as has been previously studied. A prediction model remains a novel method of evidence-based forecasting in Tawau, Sabah. The model developed in this study, demonstrated an ability to forecast potential dengue outbreaks 1 to 4 months in advance. These findings are not dissimilar to what has been previously studied in many different countries- with temperature and humidity consistently being established as powerful predictors of dengue incidence magnitude. When used in prognostication, it can enhance- decision making and allow judicious use of resources in public health setting. Nevertheless, the model remains a work in progress- requiring larger and more diverse data.
    Matched MeSH terms: Models, Statistical
  7. Fulltext Developing an index based on GIS and statistical analysis for family support of substance abuser in Terengganu
    Juahir, H., Fazillah, A., Kamarudin, M.K.A., Toriman, E., Mohamad, N., Fairuz, A., et al.
    Malaysian Journal of Applied Sciences, 2018;2(2):45-54.
    MyJurnal
    Family support has a strong impact on individuals and there is no exception in substance abuse
    recovery process. Family support manages to play a positive role in substance abuse problems. The
    present study deals with the developing model of family support substance abuser with the
    combination method of Geographic Information System (GIS) and statistical models. The data used
    for this study was collected from seven districts in Terengganu with a constant number of
    respondents. 35 respondents for each district were involved in this study. It was then processed using
    factor analysis (FA) to develop index of family support. By using the developed indices, GIS tool was
    used to plot the distribution map of family support indices according to each form of family support.
    The result indicated that the highest index for all form of family support abuser was located in Besut
    district. High level of family support is essential as an effort for rehabilitation process of substance
    abusers.
    Matched MeSH terms: Models, Statistical
  8. Fulltext Developing forecasting model for future pandemic applications based on COVID-19 data 2020-2022
    Wan Mohamad Nawi WIA, K Abdul Hamid AA, Lola MS, Zakaria S, Aruchunan E, Gobithaasan RU, et al.
    PLoS One, 2023;18(5):e0285407.
    PMID: 37172040 DOI: 10.1371/journal.pone.0285407
    Improving forecasting particularly time series forecasting accuracy, efficiency and precisely become crucial for the authorities to forecast, monitor, and prevent the COVID-19 cases so that its spread can be controlled more effectively. However, the results obtained from prediction models are inaccurate, imprecise as well as inefficient due to linear and non-linear patterns exist in the data set, respectively. Therefore, to produce more accurate and efficient COVID-19 prediction value that is closer to the true COVID-19 value, a hybrid approach has been implemented. Thus, aims of this study is (1) to propose a hybrid ARIMA-SVM model to produce better forecasting results. (2) to investigate in terms of the performance of the proposed models and percentage improvement against ARIMA and SVM models. statistical measurements such as MSE, RMSE, MAE, and MAPE then conducted to verify that the proposed models are better than ARIMA and SVM models. Empirical results with three real datasets of well-known cases of COVID-19 in Malaysia show that, compared to the ARIMA and SVM models, the proposed model generates the smallest MSE, RMSE, MAE and MAPE values for the training and testing datasets, means that the predicted value from the proposed model is closer to the actual value. These results prove that the proposed model can generate estimated values more accurately and efficiently. As compared to ARIMA and SVM, our proposed models perform much better in terms of error reduction percentages for all datasets. This is demonstrated by the maximum scores of 73.12%, 74.6%, 90.38%, and 68.99% in the MAE, MAPE, MSE, and RMSE, respectively. Therefore, the proposed model can be the best and effective way to improve prediction performance with a higher level of accuracy and efficiency in predicting cases of COVID-19.
    Matched MeSH terms: Models, Statistical
  9. Development of a risk score to stratify symptomatic adults referred for colonoscopy
    Law CW, Rampal S, Roslani AC, Mahadeva S
    J Gastroenterol Hepatol, 2014 Nov;29(11):1890-6.
    PMID: 24909623 DOI: 10.1111/jgh.12638
    With an increasing burden on overstretched colonoscopy services, a simple risk score for significant pathology in symptomatic patients may aid in the prioritization of patients.
    Matched MeSH terms: Models, Statistical
  10. Fulltext Development of an edible coating based on chitosan-glycerol to delay ‘Berangan’ banana (Musa sapientum cv. Berangan) ripening process
    Jafarizadeh Malmiri, H., Osman, A., Tan, C.P., Abdul Rahman, R.
    International Food Research Journal, 2011;18(3):-.
    MyJurnal
    Response surface methodology (RSM) was used to optimize the concentrations of chitosan and glycerol for coating Berangan banana (Musa sapientum cv. Berangan). The effects of main edible coating components, chitosan (0.5-2.5%, w/w) and glycerol (0-2%, w/w) on weight loss, firmness, total colour difference, total soluble solids content (TSS) and titratable acidity (TA) of coated banana were studied during 10 days of storage at 26±2°C and 40-50% relative humidity. Results showed that the experimental data could be adequately fitted into a second-order polynomial model with coefficient of determination (R 2 ) ranging from 0.745 to 0.930 for all the variables studied. In general, the chitosan concentration appeared to be the most significant (P< 0.1) factor influencing all variables except for TSS. The optimum concentration of chitosan and glycerol were predicted to be 2.02% and 0.18%, respectively. Statistical assessment showed insignificant difference between experimental and predicted values.
    Matched MeSH terms: Models, Statistical
  11. Development of statistical models for predicting muscle and mental activities during repetitive precision tasks
    Zadry HR, Dawal SZ, Taha Z
    Int J Occup Saf Ergon, 2016 Sep;22(3):374-83.
    PMID: 27053140 DOI: 10.1080/10803548.2016.1150094
    This study was conducted to develop muscle and mental activities on repetitive precision tasks. A laboratory experiment was used to address the objectives. Surface electromyography was used to measure muscle activities from eight upper limb muscles, while electroencephalography recorded mental activities from six channels. Fourteen university students participated in the study. The results show that muscle and mental activities increase for all tasks, indicating the occurrence of muscle and mental fatigue. A linear relationship between muscle activity, mental activity and time was found while subjects were performing the task. Thus, models were developed using those variables. The models were found valid after validation using other students' and workers' data. Findings from this study can contribute as a reference for future studies investigating muscle and mental activity and can be applied in industry as guidelines to manage muscle and mental fatigue, especially to manage job schedules and rotation.
    Matched MeSH terms: Models, Statistical*
  12. Fulltext Dimensional model for estimating factors influencing childhood obesity: path analysis based modeling
    Kheirollahpour M, Shohaimi S
    ScientificWorldJournal, 2014;2014:512148.
    PMID: 25097878 DOI: 10.1155/2014/512148
    The main objective of this study is to identify and develop a comprehensive model which estimates and evaluates the overall relations among the factors that lead to weight gain in children by using structural equation modeling. The proposed models in this study explore the connection among the socioeconomic status of the family, parental feeding practice, and physical activity. Six structural models were tested to identify the direct and indirect relationship between the socioeconomic status and parental feeding practice general level of physical activity, and weight status of children. Finally, a comprehensive model was devised to show how these factors relate to each other as well as to the body mass index (BMI) of the children simultaneously. Concerning the methodology of the current study, confirmatory factor analysis (CFA) was applied to reveal the hidden (secondary) effect of socioeconomic factors on feeding practice and ultimately on the weight status of the children and also to determine the degree of model fit. The comprehensive structural model tested in this study suggested that there are significant direct and indirect relationships among variables of interest. Moreover, the results suggest that parental feeding practice and physical activity are mediators in the structural model.
    Matched MeSH terms: Models, Statistical*
  13. Fulltext Directional slack-based measure for the inverse data envelopment analysis
    Mirsalehy A, Abu Bakar MR, Lee LS, Jaafar AB, Heydar M
    ScientificWorldJournal, 2014;2014:138923.
    PMID: 24883350 DOI: 10.1155/2014/138923
    A novel technique has been introduced in this research which lends its basis to the Directional Slack-Based Measure for the inverse Data Envelopment Analysis. In practice, the current research endeavors to elucidate the inverse directional slack-based measure model within a new production possibility set. On one occasion, there is a modification imposed on the output (input) quantities of an efficient decision making unit. In detail, the efficient decision making unit in this method was omitted from the present production possibility set but substituted by the considered efficient decision making unit while its input and output quantities were subsequently modified. The efficiency score of the entire DMUs will be retained in this approach. Also, there would be an improvement in the efficiency score. The proposed approach was investigated in this study with reference to a resource allocation problem. It is possible to simultaneously consider any upsurges (declines) of certain outputs associated with the efficient decision making unit. The significance of the represented model is accentuated by presenting numerical examples.
    Matched MeSH terms: Models, Statistical*
  14. Do the physical and environment PETTLEP elements predict sport imagery ability?
    Anuar N, Williams SE, Cumming J
    Eur J Sport Sci, 2017 Nov;17(10):1319-1327.
    PMID: 28950801 DOI: 10.1080/17461391.2017.1377290
    The present study aimed to examine whether physical and environment elements of PETTLEP imagery relate to the ability to image five types of sport imagery (i.e. skill, strategy, goal, affect and mastery). Two hundred and ninety participants (152 males, 148 females; Mage = 20.24 years, SD = 4.36) from various sports completed the Sport Imagery Ability Questionnaire (SIAQ), and a set of items designed specifically for the study to assess how frequently participants incorporate physical (e.g. 'I make small movements or gestures during the imagery') and environment (e.g. 'I image in the real training/competition environment') elements of PETTLEP imagery. Structural equation modelling tested a hypothesised model in which imagery priming (i.e. the best fitting physical and environment elements) significantly and positively predicted imagery ability of the different imagery types (skill, β = 0.38; strategy, β = 0.23; goal, β = 0.21; affect, β = 0.25; mastery, β = 0.22). The model was a good fit to the data: χ2(174) = 263.87, p 
    Matched MeSH terms: Models, Statistical
  15. Dual-response quadratic model for optimisation of electricity generation and chlorophenol degradation by electro-degradative Bacillus subtilis in microbial fuel cell system
    Hassan H, Jin B, Dai S
    Environ Technol, 2021 Apr 01.
    PMID: 33749543 DOI: 10.1080/09593330.2021.1907451
    The interactions within microbial, chemical and electronic elements in microbial fuel cell (MFC) system can be crucial for its bio-electrochemical activities and overall performance. Therefore, this study explored polynomial models by response surface methodology (RSM) to better understand interactions among anode pH, cathode pH and inoculum size for optimising MFC system for generation of electricity and degradation of 2,4-dichlorophenol. A statistical central composite design by RSM was used to develop the quadratic model designs. The optimised parameters were determined and evaluated by statistical results and the best MFC systematic outcomes in terms of current generation and chlorophenol degradation. Statistical results revealed that the optimum current density of 106 mA/m2 could be achieved at anode pH 7.5, cathode pH 6.3-6.6 and 21-28% for inoculum size. Anode-cathode pHs interaction was found to positively influence the current generation through extracellular electron transfer mechanism. The phenolic degradation was found to have lower response using these three parameter interactions. Only inoculum size-cathode pH interaction appeared to be significant where the optimum predicted phenolic degradation could be attained at pH 7.6 for cathode pH and 29.6% for inoculum size.
    Matched MeSH terms: Models, Statistical
  16. Fulltext Early warning and response system (EWARS) for dengue outbreaks: Recent advancements towards widespread applications in critical settings
    Hussain-Alkhateeb L, Kroeger A, Olliaro P, Rocklöv J, Sewe MO, Tejeda G, et al.
    PLoS One, 2018;13(5):e0196811.
    PMID: 29727447 DOI: 10.1371/journal.pone.0196811
    BACKGROUND: Dengue outbreaks are increasing in frequency over space and time, affecting people's health and burdening resource-constrained health systems. The ability to detect early emerging outbreaks is key to mounting an effective response. The early warning and response system (EWARS) is a toolkit that provides countries with early-warning systems for efficient and cost-effective local responses. EWARS uses outbreak and alarm indicators to derive prediction models that can be used prospectively to predict a forthcoming dengue outbreak at district level.

    METHODS: We report on the development of the EWARS tool, based on users' recommendations into a convenient, user-friendly and reliable software aided by a user's workbook and its field testing in 30 health districts in Brazil, Malaysia and Mexico.

    FINDINGS: 34 Health officers from the 30 study districts who had used the original EWARS for 7 to 10 months responded to a questionnaire with mainly open-ended questions. Qualitative content analysis showed that participants were generally satisfied with the tool but preferred open-access vs. commercial software. EWARS users also stated that the geographical unit should be the district, while access to meteorological information should be improved. These recommendations were incorporated into the second-generation EWARS-R, using the free R software, combined with recent surveillance data and resulted in higher sensitivities and positive predictive values of alarm signals compared to the first-generation EWARS. Currently the use of satellite data for meteorological information is being tested and a dashboard is being developed to increase user-friendliness of the tool. The inclusion of other Aedes borne viral diseases is under discussion.

    CONCLUSION: EWARS is a pragmatic and useful tool for detecting imminent dengue outbreaks to trigger early response activities.

    Matched MeSH terms: Models, Statistical
  17. Fulltext Economic-statistical design of synthetic np chart with estimated process parameter
    Lee MH, Khoo MBC, Chew X, Then PHH
    PLoS One, 2020;15(4):e0230994.
    PMID: 32267874 DOI: 10.1371/journal.pone.0230994
    The economic-statistical design of the synthetic np chart with estimated process parameter is presented in this study. The effect of process parameter estimation on the expected cost of the synthetic np chart is investigated with the imposed statistical constraints. The minimum number of preliminary subgroups is determined where an almost similar expected cost to the known process parameter case is desired for the given cost model parameters. However, the available number of preliminary subgroups in practice is usually limited, especially when the number of preliminary subgroups is large. Consequently, the optimal chart parameters of the synthetic np chart are computed by considering the practical number of preliminary subgroups in which the cost function is minimized. This leads to a lower expected cost compared to that of adopting the optimal chart parameter corresponding to the known process parameter case.
    Matched MeSH terms: Models, Statistical
  18. Effect of asymmetrical street aspect ratios on microclimates in hot, humid regions
    Qaid A, Ossen DR
    Int J Biometeorol, 2015 Jun;59(6):657-77.
    PMID: 25108376 DOI: 10.1007/s00484-014-0878-5
    Asymmetrical street aspect ratios, i.e. different height-to-width (H1/W-H2/W) ratios, have not received much attention in the study of urban climates. Putrajaya Boulevard (northeast to southwest orientation) in Malaysia was selected to study the influence of six asymmetrical aspect ratio scenarios on the street microclimate using the Envi-met three-dimensional microclimate model (V3.1 Beta). Putrajaya Boulevard suffers from high surface and air temperature during the day due to the orientation, the low aspect ratio and the wide sky view factor. These issues are a common dilemma in many boulevards. Further, low and high symmetrical streets are incompatible with tropical regions as they offer conflicting properties during the day and at night. These scenarios are examined, therefore, to find asymmetrical streets which are able to reduce the impact of the day microclimate on boulevards, and as an alternative strategy fulfilling tropical day and night climatic conditions. Asymmetrical streets are better than low symmetrical streets in enhancing wind flow and blocking solar radiation, when tall buildings confront winds direction or solar altitudes. Therefore, mitigating heat islands or improving microclimates in asymmetrical streets based on tall buildings position which captures wind or caste shades. In northeast to southwest direction, aspect ratios of 0.8-2 reduce the morning microclimate and night heat islands yet the negative effects during the day are greater than the positive effects in the night. An aspect ratio of 2-0.8 reduces the temperature of surfaces by 10 to 14 °C and the air by 4.7 °C, recommended for enhancing boulevard microclimates and mitigating tropical heat islands.
    Matched MeSH terms: Models, Statistical*
  19. Effect of malting conditions and quality characteristics of malt and roasted malt extract from 'acha' grains (Digitaria exilis Stapf)
    Lasekan O, Salva JT, Abbas K
    J Sci Food Agric, 2010 Apr 15;90(5):850-60.
    PMID: 20355122 DOI: 10.1002/jsfa.3895
    Considering the importance of malting and roasting on the quality of 'acha' beverages, a study was conducted to find optimum conditions for malting and the production of a high-quality roasted extract that could be used for an 'acha' beverage.
    Matched MeSH terms: Models, Statistical
  20. Effect of roasting conditions on the browning intensity and structural changes in jackfruit (Artocarpus hetrophyllus) seeds
    Azeez S, Lasekan O, Jinap S, Sulaiman R
    J Food Sci Technol, 2015 Dec;52(12):8050-8.
    PMID: 26604377 DOI: 10.1007/s13197-015-1900-6
    Central composite rotatable design (CCRD) was used to optimize the settings for the roasting conditions of jackfruit (Artocapus hetrophyllus) seed (JFS). The response variables studied were; color attributes L*, a*, and b*, browning intensity, and fracturability. The colors L*, a*, b* and browning intensity were well predicted by a second-order polynomial model. Fracturability was predicted by a first-order polynomial. The determination coefficients for colors L*, a*, b*, browning intensity, and fracturability were 0.81, 0.96, 0.93, 0.92, and 0.74 respectively. The fitted models were checked for adequacy using analysis of variance (ANOVA). The optimum roasting conditions were established at a temperature of 153.36 °C, 34.36 min, and pH of 6.34 with composite desirability value of 0.95. Micro-structural studies of both raw and roasted JFS at different roasting levels (i.e., low, medium, and high) were also investigated using scanning electron microscope (SEM). JFS starch granules fell in the B-type category with semi-oval to bell-shaped granules (5-9 μm in diameter). In addition, Fourier Transform Infrared analysis was carried out on both raw and roasted JFS. The IR spectra was in the 4000-1000 cm(-1) region which is described by five main modes; O-H, C-H, C = O, (C-H) CH3, and C-O.
    Matched MeSH terms: Models, Statistical
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