This paper aims to investigate the dielectric properties, i.e., dielectric constant (ε'), dielectric loss factor (ε″), dielectric tangent loss (tan δ), electrical conductivity (σ), and penetration depth (Dp), of the porous nanohydroxyapatite/starch composites in the function of starch proportion, pore size, and porosity over a broad band frequency range of 5 MHz-12 GHz. The porous nanohydroxyapatite/starch composites were fabricated using different starch proportions ranging from 30 to 90 wt%. The results reveal that the dielectric properties and the microstructural features of the porous nanohydroxyapatite/starch composites can be enhanced by the increment in the starch proportion. Nevertheless, the composite with 80 wt% of starch proportion exhibit low dielectric properties (ε', ε″, tan δ, and σ) and a high penetration depth because of its highly interconnected porous microstructures. The dielectric properties of the porous nanohydroxyapatite/starch composites are highly dependent on starch proportion, average pore size, and porosity. The regression models are developed to express the dielectric properties of the porous nanohydroxyapatite/starch composites (R2 > 0.96) in the function of starch proportion, pore size, and porosity from 1 to 11 GHz. This dielectric study can facilitate the assessment of bone scaffold design in bone tissue engineering applications.
The investigation of sediment transport in tropical rivers is essential for planning effective integrated river basin management to predict the changes in rivers. The characteristics of rivers and sediment in the tropical region are different compared to those of the rivers in Europe and the USA, where the median sediment size tends to be much more refined. The origins of the rivers are mainly tropical forests. Due to the complexity of determining sediment transport, many sediment transport equations were recommended in the literature. However, the accuracy of the prediction results remains low, particularly for the tropical rivers. The majority of the existing equations were developed using multiple non-linear regression (MNLR). Machine learning has recently been the method of choice to increase model prediction accuracy in complex hydrological problems. Compared to the conventional MNLR method, machine learning algorithms have advanced and can produce a useful prediction model. In this research, three machine learning models, namely evolutionary polynomial regression (EPR), multi-gene genetic programming (MGGP) and M5 tree model (M5P), were implemented to model sediment transport for rivers in Malaysia. The formulated variables for the prediction model were originated from the revised equations reported in the relevant literature for Malaysian rivers. Among the three machine learning models, in terms of different statistical measurement criteria, EPR gives the best prediction model, followed by MGGP and M5P. Machine learning is excellent at improving the prediction distribution of high data values but lacks accuracy compared to observations of lower data values. These results indicate that further study needs to be done to improve the machine learning model's accuracy to predict sediment transport.
Air surface temperature (AST) is a crucial importance element for many applications such as hydrology, agriculture, and climate change studies. The aim of this study is to develop regression equation for calculating AST and to analyze and investigate the effects of atmospheric parameters (O3, CH4, CO, H2Ovapor, and outgoing longwave radiation (OLR)) on the AST value in Iraq. Dataset retrieved from the Atmospheric Infrared Sounder (AIRS) at EOS Aqua Satellite, spanning the years of 2003 to 2016, and multiple linear regression were used to achieve the objectives of the study. For the study period, the five atmospheric parameters were highly correlated (R, 0.855-0.958) with predicted AST. Statistical analyses in terms of β showed that OLR (0.310 to 1.053) contributes significantly in enhancing AST values. Comparisons among selected five stations (Mosul, Kanaqin, Rutba, Baghdad, and Basra) for the year 2010 showed a close agreement between the predicted and observed AST from AIRS, with values ranging from 0.9 to 1.5 K and for ground stations data, within 0.9 to 2.6 K. To make more complete analysis, also, comparison between predicted and observed AST from AIRS for four selected month in 2016 (January, April, July, and October) has been carried out. The result showed a high correlation coefficient (R, 0.87 and 0.95) with less variability (RMSE ≤ 1.9) for all months studied, indicating model's capability and accuracy. In general, the results indicate the advantage of using the AIRS data and the regression analysis to investigate the impact of the atmospheric parameters on AST over the study area.
This paper mainly forecasts the daily closing price of stock markets. We propose a two-stage technique that combines the empirical mode decomposition (EMD) with nonparametric methods of local linear quantile (LLQ). We use the proposed technique, EMD-LLQ, to forecast two stock index time series. Detailed experiments are implemented for the proposed method, in which EMD-LPQ, EMD, and Holt-Winter methods are compared. The proposed EMD-LPQ model is determined to be superior to the EMD and Holt-Winter methods in predicting the stock closing prices.
Pharmacokinetic-pharmacodynamic information regarding warfarin is used to produce a predictive model based on the idea that pharmacodynamic variability is more important than pharmacokinetic variability in the overall dose-response variability to warfarin. A modification of the maximum effect model is tested on a group of patients initiating oral anticoagulation with warfarin. Results indicate that the model can account for at least half of the total variation in maintenance doses observed (sample coefficient of determination, 0.53) and offer the physician a framework for dose requirements at the onset of therapy. The basic prediction equation is as follows: Maintenance dose = (11/international normalized ratio)-1, with a coefficient of correlation of 0.73 (95% confidence limits, 0.46-0.88). Application of this model may improve on the traditional empiric approach to warfarin dose adjustment.
Awareness of haze pollution and management increased in Southeast Asia since 1990. However, the
focus on environmental management is decreasing especially in Malaysia due to the abundant
resources and increased development pressure. The total health damage cost because of haze in the
country became significantly high due to the long duration of haze events year by year. This paper
discusses the health damage caused by bronchitis due to the haze events in Malaysia. The analysis
shows positive coefficient of independent variables which indicates the positive relationship between
dependent variable and independent variables. Multiple linear regression analysis shows that 45.3%
variation in damage cost of bronchitis could be explained by FAI, GDPPC, and CO2.
We evaluated the species richness and beta diversity of epiphyllous assemblages from three selected localities in Sabah, i.e. Mt. Silam in Sapagaya Forest Reserve, and Ulu Senagang and Mt. Alab in Crocker Range Park. A total of 98 species were found and a phytosociological survey was carried out based on the three study areas. A detailed statistical analysis including standard correlation and regression analyses, ordination of species and leaves using centered principal component analysis, and the SDR simplex method to evaluate the beta diversity, was conducted. Beta diversity is very high in the epiphyllous liverwort assemblages in Sabah, with species replacement as the major component of pattern formation and less pronounced richness difference. The community analysis of the epiphyllous communities in Sabah makes possible their detailed description and comparison with similar communities of other continents.
With the advancement of technology, analysis of large-scale data of gene expression is feasible and has become very popular in the era of machine learning. This paper develops an improved ridge approach for the genome regression modeling. When multicollinearity exists in the data set with outliers, we consider a robust ridge estimator, namely the rank ridge regression estimator, for parameter estimation and prediction. On the other hand, the efficiency of the rank ridge regression estimator is highly dependent on the ridge parameter. In general, it is difficult to provide a satisfactory answer about the selection for the ridge parameter. Because of the good properties of generalized cross validation (GCV) and its simplicity, we use it to choose the optimum value of the ridge parameter. The GCV function creates a balance between the precision of the estimators and the bias caused by the ridge estimation. It behaves like an improved estimator of risk and can be used when the number of explanatory variables is larger than the sample size in high-dimensional problems. Finally, some numerical illustrations are given to support our findings.
Responses were recorded from normal healthy subjects and age-related macular degeneration (AMD) patients and evaluated, using a new variant of mfVEP. Subjects information was recorded using 64 EEG channels with a computer-based acquisition system. The stimulus layout was a 84 region corticallyscaled dartboard comprising 12 sectors and seven concentric rings subtending a diameter of 23º, presented dichoptically at 60 Hz. Data from the control and AMD patients were statistically compared when fitted concurrently into the multiple regression analysis. The Pattern-pulse mfVEP technique could distinguish between normal eyes and those with a definite diagnosis of dry and wet AMD when responses from the macula were considered.
Rheology is the science of deformation and flow behavior of fluid. Knowledge of rheological properties of fluid foods and their variation with temperature and concentration have been globally important for industrialization of food technology for quality, understanding the texture, process engineering application, correlation with sensory evaluation, designing of transport system , equipment design (heat exchanger and evaporator ), deciding pump capacity and power requirement for mixing. The aim of this study was to determine the rheological behavior of pomelo juice at different concentrations (20-60.4%) and temperatures (23-60°C) by using a rotational rotational Haake Rheostress 600 rheometer. Pomelo juice was found to exhibit both Newtonian and Non-Newtonian behavior. For lower concentration the Newtonian behavior is observed while at higher concentration Non-Newtonian behavior was observed. Standard error (SE) method was selected on the basis to carry out the error analysis due to the best fit model. For the four models the values of SE show that the Herschel-Bulkley and Power Law models perform better than the Bingham and Casson models but Herschel-Bulkley model is true at higher concentration. The rheological model of pomelo juice, incorporating the effects of concentration and temperature was developed. The master-curve was investigated for comparing data from different products at a reference temperature of 40°C. Multiple regression analysis indicated Master-Curve presents good agreement for pomelo juice at all concentrations studied with R2>0.8.
This study involves the adoption of the Geographic Information System (GIS) modeling approach to determine the quickest routes for fresh vegetable delivery. During transport, fresh vegetables mainly deteriorate on account of temperature and delivery time. Nonetheless, little attention has been directed to transportation issues in most areas within Kuala Lumpur. In addition, perishable food normally has a short shelf life, thus timely delivery significantly affects delivery costs. Therefore, selecting efficient routes would consequently reduce the total transportation costs. The regression model is applied in this study to determine the parameters that affect route selection with respect to the fastest delivery of fresh vegetables. For the purpose of this research, ArcGIS software with network analyst extension is adopted to solve the problem of complex networks. The final output of this research is a map of quickest routes with the best delivery times based on all variables. The variables tested from regression analysis are the most effective parameters to make the flow of road networks slower. The objective is to improve the delivery services by achieving the least drive time. The main findings of this research are that Land use such as residential area and population as variables are the effective parameters on drive time.
BACKGROUND: Value added services (VAS) are an innovative dispensing system created to provide an alternative means of collecting partial drug supply from our hospital. This in turn was projected to reduce the necessity for patient to visit pharmacy counter and thus reduce the burden of prescription handling.
OBJECTIVE: To evaluate the impact of increased VAS uptake following promotional campaign towards patient waiting time and to explore factors that may affect patient waiting time at the Ambulatory Pharmacy, Queen Elizabeth Hospital.
METHODS: A quasi experimental study design was conducted from September 2014 till June 2015 at the Ambulatory Pharmacy. During pre-intervention phase, baseline parameters were collected retrospectively. Then, VAS promotional campaign was carried out for six months and whilst this was done, the primary outcome of patient waiting time was measured by percentage of prescription served less than 30 minutes. A linear regression analysis was used to determine the impact of increased VAS uptake towards patient waiting time.
RESULTS: An increased in percentage of VAS registration (20.9% vs 35.7%, p<0.001) was observed after the promotional campaign. The mean percentage of prescription served less than 30 minutes increased from 83.2% SD=15.9 to 90.3% SD=11.5, p=0.001. After controlling for covariates, it was found that patient waiting time was affected by number of pharmacy technicians (b=-0.0349, 95%CI-0.0548 : -0.0150, p=0.001), number of pharmacy counters (b=0.1125, 95%CI 0.0631 : 0.1620, p<0.001), number of prescriptions (b=0.0008, 95%CI 0.0004 : 0.0011, p<0.001), and number of refill prescriptions (b=0.0004, 95%CI 0.0002 : 0.0007, p<0.001). The increased in percentage of VAS registration was associated with reduction in number of refill prescription (b=-2.9838, 95%CI -4.2289 : -1.7388, p<0.001).
CONCLUSIONS: Patient waiting time at the Ambulatory Pharmacy improved with the increased in VAS registration. The impact of increased VAS uptake on patient waiting time resulted from reduction in refill prescriptions. Patient waiting time is influenced by number of pharmacy technicians, number of pharmacy counters, number of prescriptions and number of refill prescriptions.
The application of solar disinfection for treating stored rainwater was investigated by the authors using indicator organisms. The multiple tube fermentation technique and pour plate method were used for the detection of microbial quality indicators like total and fecal coliforms, E. coli and heterotrophic plate count. These techniques have disadvantages mainly that these are laborious and time consuming. The correlation of total coliform with that of exposure time is proposed under different factors of weather, pH and turbidity. Statistical tools like root mean square error and coefficient of determination were used to validate these proposed equations. The correlation equations of fecal coliform, E. coli and heterotrophic plate count with total coliform are suggested by using four regression analysis including Reciprocal Quadratic, Polynomial Regression (2 degree), Gaussian Model and Linear Regression in order to reduce the tedious experimental work in similar types of experiments and treatment systems.
The objective of this study was to identify the exogenous variables of risk and investment management efficiency by using a two-stage data envelopment analysis (DEA) method. The first stage involves obtaining the efficiency scores of risk and investment management via DEA that requires only the traditional inputs and outputs. In the second stage, the Tobit regression analysis is conducted in which the efficiency score obtained from the first stage is treated as a dependent variable, while the exogenous factors are considered to be independent variables. The exogenous factors consist of operating systems, organizational form, consumer preference and size. The results showed that the mutual company as well as the takaful system demonstrate better risk management performance than their stock and conventional system counterparts. In addition, size is also a significant indicator for risk management efficiency in which the larger insurer/takaful operator exhibits better risk management performance than the smaller one. However, consumer preference is found to be insignificantly correlated with the efficiency of risk management. In contrast, with risk management, organizational form, operating system and size are not indicators of the investment management efficiency, but consumer preference is significantly and positively associated with investment management efficiency.
Employee deviance has received increasing attention in the past decade. Past research have reported that work environment related factors such as organizational support, supervisory support, role conflict, and job demand were associated with deviant behavior The purpose of this paper is to examine the relationship between job demand (psychological job demand), and job resources (social support), and employee workplace deviant behavior. This study adopts a cross-sectional correlation study design. A total of 315 employees were selected using cluster sampling technique participated in this study. Data were collected using a self-administered questionnaire using the drop and collect method. Data were analyzed using descriptive analysis (mean, standard deviation, frequency distribution) to describe the demographic profile and study variables. Correlation and regression analysis was performed to test the relationship between psychological job demand, and social support, and employee workplace deviant behaviors. The result revealed that lack of social support has significant positive influence on employee workplace deviant behavior. The findings suggest that lack of job resources such as social support may drive employees to engage in deviant work behavior. However, high job demand experienced by employees does not drive them towards engaging in deviant work behavior.
In this paper we investigated the concentrations of Pb in seven different soft tissues (foot, cephalic tentacles, mantle muscle, gill, digestive caecum and remaining soft tissues) of 17 geographical populations of Telescopium telescopium collected from the intertidal area of Peninsular Malaysia. Two points can be presented based on the present study. First, as expected, different concentrations of Pb were found in the different soft tissues, indicating different mechanisms of bioaccumulation and regulations of Pb in these different tissues. By comparing the Pb concentrations in the similar tissues, spatial variation of Pb was found in the different sampling sites although there is no consistent pattern of Pb contamination in these sampling sites. Second, based on the correlation coefficients and multiple linear stepwise regression analysis between Pb concentrations in the different soft tissues and Pb concentrations in geochemical factions in the surface sediments, it is found that gill and digestive caecum can truly reflect Pb contamination and Pb bioavailabilities in the tropical intertidal mudflats. To our knowledge, this is the most comprehensive study on Pb in the different soft tissues of T. telescopium, in relation to the habitat sediments of the snails.
This study aimed to examine the influence of the traditional leadership qualities towards to develop community cohesion in the Iban community in Malaysia. A quantitative approach was used to conduct this study, where data were collected through a self-administered survey questionnaire from 210 chiefs in the Iban longhouse at the Pakan District in Sarawak, Malaysia. A pre-tested questionaire was administrered to the respondents using a simple random sampling in the District of Pakan, Sarawak. The leadership quality was measured based on the leadership traits, leadership style, leadership behaviour, situational leadership, and trsnformational leadership; while the community cohesion was measured by a sense of belonging, social alienation, social support, rootedness, social solidarity, and social ties. The results of the correlation and regression analysis showed that the traditional leadership qualities had a significant correlation with the development of social cohesion. The findings proved that the traditional leadership is essential to increase community cohesion in the Iban community. The findings would be important guideline to the development thinkers, practitioners, community leaders, and development institutions.
Linearity assessment as required in method validation has always been subject to different interpretations and definitions by various guidelines and protocols. However, there are very limited applicable implementation procedures that can be followed by a laboratory chemist in assessing linearity. Thus, this work proposes a simple method for linearity assessment in method validation by a regression analysis that covers experimental design, estimation of the parameters, outlier treatment, and evaluation of the assumptions according to the International Union of Pure and Applied Chemistry guidelines. The suitability of this procedure was demonstrated by its application to an in-house validation for the determination of plasticizers in plastic food packaging by GC.
This study is aimed to evaluate the accuracy of Demirjian method in estimating the chronological age of male and female Kelantanese Malay children between 6 and 16 years of age and to establish a new dental age (DA) curve if the Demirjian method was not found to be accurate. About 905 panoramic radiographs of healthy Malay children between 6 and 16 years of age were collected from the radiographic unit in the Hospital Universiti Sains Malaysia (HUSM) and the orthodontic clinic in Hospital Kota Bharu (HKB). Children who had any disease affecting the dental development, or have agenesis in the lower arch and poor quality radiographic images were excluded. The results showed that Demirjian method overestimated the chronological age (CA) by 1.23 years for boys and 1.20 years for girls and it was less accurate for the Kelantanese Malay children. Thus new standard curve were produced and tested on external samples. Results showed that the mean difference between the chronological age and DA is about 0.17 years for boys and 0.11 years for girls. DA was more advanced in the Kelantanese Malay boys and girls as compared to French-Canadian children in all age groups. It is concluded that the Demirjian method tends to be less accurate in estimating the chronological age in Malay children. The new curve that was produced is more applicable to the Kelantanese Malay children.
Oil palm fibre was used to prepare activated carbon using physiochemical activation method which consisted of potassium hydroxide (KOH) treatment and carbon dioxide (CO(2)) gasification. The effects of three preparation variables: the activation temperature, activation time and chemical impregnation (KOH:char) ratio on methylene blue (MB) uptake from aqueous solutions and activated carbon yield were investigated. Based on the central composite design (CCD), a quadratic model and a two factor interaction (2FI) model were respectively developed to correlate the preparation variables to the MB uptake and carbon yield. From the analysis of variance (ANOVA), the significant factors on each experimental design response were identified. The optimum activated carbon prepared from oil palm fibre was obtained by using activation temperature of 862 degrees C, activation time of 1h and chemical impregnation ratio of 3.1. The optimum activated carbon showed MB uptake of 203.83 mg/g and activated carbon yield of 16.50%. The equilibrium data for adsorption of MB on the optimum activated carbon were well represented by the Langmuir isotherm, giving maximum monolayer adsorption capacity as high as 400mg/g at 30 degrees C.