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 paper presents the implementing multiple fan beam projection technique using optical fibre sensors for a tomography system. From the dynamic experiment of solid/gas flow using plastic beads in a gravity flow rig, the designed optical fibre sensors are reliable in measuring the mass flow rate below 40% of flow. Another important matter that has been discussed is the image processing rate or IPR. Generally, the applied image reconstruction algorithms, the construction of the sensor and also the designed software are considered to be reliable and suitable to perform real-time image reconstruction and mass flow rate measurements.
Vegetation fires have become an increasing problem in tropical environments as a consequence of socioeconomic pressures and subsequent land-use change. In response, fire management systems are being developed. This study set out to determine the relationships between two aspects of the fire problems in western Indonesia and Malaysia, and two components of the Canadian Forest Fire Weather Index System. The study resulted in a new method for calibrating components of fire danger rating systems based on satellite fire detection (hotspot) data. Once the climate was accounted for, a problematic number of fires were related to high levels of the Fine Fuel Moisture Code. The relationship between climate, Fine Fuel Moisture Code, and hotspot occurrence was used to calibrate Fire Occurrence Potential classes where low accounted for 3% of the fires from 1994 to 2000, moderate accounted for 25%, high 26%, and extreme 38%. Further problems arise when there are large clusters of fires burning that may consume valuable land or produce local smoke pollution. Once the climate was taken into account, the hotspot load (number and size of clusters of hotspots) was related to the Fire Weather Index. The relationship between climate, Fire Weather Index, and hotspot load was used to calibrate Fire Load Potential classes. Low Fire Load Potential conditions (75% of an average year) corresponded with 24% of the hotspot clusters, which had an average size of 30% of the largest cluster. In contrast, extreme Fire Load Potential conditions (1% of an average year) corresponded with 30% of the hotspot clusters, which had an average size of 58% of the maximum. Both Fire Occurrence Potential and Fire Load Potential calibrations were successfully validated with data from 2001. This study showed that when ground measurements are not available, fire statistics derived from satellite fire detection archives can be reliably used for calibration. More importantly, as a result of this work, Malaysia and Indonesia have two new sources of information to initiate fire prevention and suppression activities.
A study was carried out on the concentration of REEs (Dy, Sm, Eu,Yb, Lu, La and Ce) that are present in the core marine sediments of East Malaysia from three locations at South China Sea and one location each at Sulu Sea and Sulawesi Sea. The sediment samples were collected at a depth of between 49 and 109 m, dried, and crushed to powdery form. The entire core sediments prepared for Instrumental Neutron Activation Analysis (INAA) were weighted approximately 0.0500 g to 0.1000 g for short irradiation and 0.1500 g to 0.2000 g for long irradiation. The samples were irradiated with a thermal neutron flux of 4.0×10(12) cm(-2) s(-1) in a TRIGA Mark II research reactor operated at 750 kW. Blank samples and standard reference materials SL-1 were also irradiated for calibration and quality control purposes. It was found that the concentration of REEs varies in the range from 0.11 to 36.84 mg/kg. The chondrite-normalized REEs for different stations suggest that all the REEs are from similar origins. There was no significant REEs contamination as the enrichment factors normalized for Fe fall in the range of 0.42-2.82.
A simple and selective high-performance liquid chromatography (HPLC) method using ultraviolet detection was developed for simultaneous determination of fusidic acid and betamethasone dipropionate in a cream formulation. A Supelcosil LC18 column was used for chromatographic separation. The mobile phase consisted of acetonitrile and 0.01 M disodium hydrogen orthophosphate (70:30, % v/v) adjusted to pH 6 with glacial acetic acid. Analysis was run at a flow rate of 1.0 mL/minute with the detector operating at 235 nm. The standard calibration curve was linear over a concentration range of 0.3 to 1.2 mg/mL for fusidic acid and 9.6 to 38.4 micrograms/mL for betamethasone dipropionate. The average recovery values for fusidic acid and betamethasone dipropionate were almost 100%. The within-run and between-run coefficient of variation and percent error values for the two drugs were all less than 2% and +/- 3%, respectively.
The extraction of relevant wavelengths from a large dataset of Near Infrared Spectroscopy (NIRS) is a significant challenge in vibrational spectroscopy research. Nonetheless, this process allows the improvement in the chemical interpretability by emphasizing the chemical entities related to the chemical parameters of samples. With the complexity in the dataset, it may be possible that irrelevant wavelengths are still included in the multivariate calibration. This yields the computational process to become unnecessary complex and decreases the accuracy and robustness of the model. In multivariate analysis, Partial Least Square Regression (PLSR) is a method commonly used to build a predictive model from NIR spectral data. However, in the PLSR method and common commercial chemometrics software, there is no standard wavelength selection procedure applied to screen the irrelevant wavelengths. In this study, a new robust wavelength selection procedure called the modified VIP-MCUVE (mod-VIP-MCUVE) using Filter-Wrapper method and input scaling strategy is introduced. The proposed method combines the modified Variable Importance in Projection (VIP) and modified Monte Carlo Uninformative Variable Elimination (MCUVE) to calculate the scale matrix of the input variable. The modified VIP uses the orthogonal components of Partial Least Square (PLS) in investigating the informative variable in the model by applying the amount of variation both in X and y{SSX,SSY}, simultaneously. The modified MCUVE uses a robust reliability coefficient and a robust tolerance interval in the selection procedure. To evaluate the superiority of the proposed method, the classical VIP, MCUVE, and autoscaling procedure in classical PLSR were also included in the evaluation. Using artificial data with Monte Carlo simulation and NIR spectral data of oil palm (Elaeis guineensis Jacq.) fruit mesocarp, the study shows that the proposed method offers advantages to improve model interpretability, to be computationally extensive, and to produce better model accuracy.
Conventional air quality monitoring systems, such as gas analysers, are commonly used in many developed and developing countries to monitor air quality. However, these techniques have high costs associated with both installation and maintenance. One possible solution to complement these techniques is the application of low-cost air quality sensors (LAQSs), which have the potential to give higher spatial and temporal data of gas pollutants with high precision and accuracy. In this paper, we present DiracSense, a custom-made LAQS that monitors the gas pollutants ozone (O₃), nitrogen dioxide (NO₂), and carbon monoxide (CO). The aim of this study is to investigate its performance based on laboratory calibration and field experiments. Several model calibrations were developed to improve the accuracy and performance of the LAQS. Laboratory calibrations were carried out to determine the zero offset and sensitivities of each sensor. The results showed that the sensor performed with a highly linear correlation with the reference instrument with a response-time range from 0.5 to 1.7 min. The performance of several calibration models including a calibrated simple equation and supervised learning algorithms (adaptive neuro-fuzzy inference system or ANFIS and the multilayer feed-forward perceptron or MLP) were compared. The field calibration focused on O₃ measurements due to the lack of a reference instrument for CO and NO₂. Combinations of inputs were evaluated during the development of the supervised learning algorithm. The validation results demonstrated that the ANFIS model with four inputs (WE OX, AE OX, T, and NO₂) had the lowest error in terms of statistical performance and the highest correlation coefficients with respect to the reference instrument (0.8 < r < 0.95). These results suggest that the ANFIS model is promising as a calibration tool since it has the capability to improve the accuracy and performance of the low-cost electrochemical sensor.
In this work, voltammetric study based on cetyltrimethylammonium bromide (CTAB) as an ion-pairing agent for the determination of iodine level in iodized table salt has been explored. CTAB was used as an intermediate compound between iodide (I-) and the electrode due to its ability to dissociate to produce cetyltrimethylammonium ions ([CTA]+). The [CTA]+ with a long hydrophobic alkyl chain can be directly adsorbed onto the surface of the working electrode, and this in turns coated the electrode with cationic charge and enhance the electrode ability to bind to iodide (I-) and other molecular iodine ions. A mixture of iodide and CTAB ([CTA]+I-) was prepared and potential of 1.0 V for 60.0 s was applied to pre-concentrate the solution on the working electrode causing the [CTA]+I- to oxidize to iodine (I2). The produced I2 immediately react with chloride ion (Cl-) from the electrolyte of hydrochloric acid (HCl) to produce I2Cl- and form ion-pair with CTA+ as [CTA]+I2Cl-. The linear calibration curve of the developed method towards iodide was in the concentration range of 0.5-4.0 mg/L with sensitivity of - 1.383 µA mg/L-1 cm-2 (R2 = 0.9950), limit of detection (LOD) of 0.3 mg/L and limit of quantification (LOQ) of 1.0 mg/L, respectively. The proposed method indicates good agreement with the standard method for iodine determination with recovery range from 95.0 to 104.3%. The developed method provided potential application as a portable on-site iodine detector.
The data presented herein were collected from the Straits of Malacca, along the west coast of Peninsular Malaysia. A 3.9 m core sample was retrieved from the Straits of Malacca in 2001. This core was continuously sub-sampled at 5-cm intervals between selected core depths of 220 cm and 380 cm. The 32 sub-samples obtained were analysed to understand the species composition of benthic Foraminifera in them and the changes in lithology during the Holocene. The data available in this article include the raw counts of different species of Foraminifera and the weight percentages of sediment of different grain sizes and organic matter at different depth. In addition, the estimated ages of the sediment samples are also provided. The chronostratigraphic framework of the core was based on radiocarbon-14 Accelerator Mass Spectrometry (AMS) dates estimated from three selected sediment intervals. The results of carbon dating were calibrated to calendar years (cal BC/AD) and calibrated radiocarbon years (cal BP). Calibration was done using the INTCAL program with a Delta R value of -19 ± 70.
The analytical methods for the determination of the amine solvent properties do not provide input data for real-time process control and optimization and are labor-intensive, time-consuming, and impractical for studies of dynamic changes in a process. In this study, the potential of nondestructive determination of amine concentration, CO2 loading, and water content in CO2 absorption solvent in the gas processing unit was investigated through Fourier transform near-infrared (FT-NIR) spectroscopy that has the ability to readily carry out multicomponent analysis in association with multivariate analysis methods. The FT-NIR spectra for the solvent were captured and interpreted by using suitable spectra wavenumber regions through multivariate statistical techniques such as partial least square (PLS). The calibration model developed for amine determination had the highest coefficient of determination (R2) of 0.9955 and RMSECV of 0.75%. CO2 calibration model achieved R2 of 0.9902 with RMSECV of 0.25% whereas the water calibration model had R2 of 0.9915 with RMSECV of 1.02%. The statistical evaluation of the validation samples also confirmed that the difference between the actual value and the predicted value from the calibration model was not significantly different and acceptable. Therefore, the amine, CO2, and water models have given a satisfactory result for the concentration determination using the FT-NIR technique. The results of this study indicated that FT-NIR spectroscopy with chemometrics and multivariate technique can be used for the CO2 solvent monitoring to replace the time-consuming and labor-intensive conventional methods.
Objective: : The aim of this study was to evaluate the reliability of the pressure indicating film in measuring pressure exerted on it with and without Polyethylene (PE) sleeve as infection control purposes, and to analyze the pressure produced with its software for occlusal force study. Materials and Methods: The optimization of the pressure indicating film for occlusal force analysis commenced with the design and calibration of this sheet. The film was designed into horseshoe shape to suit the shape of maxillary and mandibular arches. The calibration was initiated with 5 different types of pressure which were 15 MPa, 25 MPa, 30 MPa, 35 MPa and 45 MPa exerted on two groups of the film: (i) with PE sleeve and (ii) without PE sleeve. Three readings were recorded for each group and mean value was documented. Then, the films were calibrated by its software for pressure analysis. Results: There was no significance difference found between the film with and without PE sleeve during the calibration stage (P>0.05). In all groups of pressure, there was no significant difference documented between pressure exerted and read out value. Conclusion: The results suggested that the film can be used for occlusal force analysis and improvement of the film with addition of PE sleeve for hygienic purpose is suitable to form the basis of clinical occlusal forces study.
FTIR spectroscopy in combination with multivariate calibrations, i.e. partial least square (PLS) and principle component regression (PCR) was developed for quantitative analysis of cod liver oil (CLO) in binary mixture with corn oil (CO). The spectra of CLO, CO and their blends with certain concentrations were scanned using horizontal attenuated total reflectance (HATR) accessory at mid infrared (MIR) region of 4,000 – 650 cm-1. The optimal spectral treatments selected for calibration models were based on its ability to provide the highest values of coefficient of determination (R2) and the lowest values of root mean error of calibration (RMSEC). PLS was slightly well suited for quantitative analysis of CLO compared to PCR. FTIR spectroscopy in combination with multivariate calibration offers rapid, no excessive chemical reagent, and easy in operational to be applied for determination of CLO in binary mixture with other oils.
Being an imperative material for man either used as building materials, pottery or as components in material industry and technology, knowledge of clays elemental contents is important. In the present study ten clay samples obtained from various locations in North-West Peninsular Malaysia were used. Majority of the clays were economically manufactured to be used as building materials or pottery. The objective of study was to determine the main elemental contents of the samples, and relate the results to the types of minerals, as well as to compare them with clays from other studies. In the study X-ray Fluorescence (XRF) coupled to samples dilution method and standard calibration samples was used. The elements detected in the study were Si, Al, Fe, Ti, K and Ca. Depending on locations, the percentage concentration ranged between 24.8 – 32.4 for Si, 10.8 – 19.0 for Al, 0.09 – 2.12 for Fe, 0.08 – 1.13 for Ti, 0.45 – 3.39 for K and trace amount of Ca and P. However, Mg that normally found in typical clay was not found in the studied samples. Comparing the oxide of the major elements with other studies, it was found that the clay samples contained mixtures of kaolinite (two-layered structure) and illite (three-layered structure).
Malaysia, Biosafety Bill 2006 was approved by Parliament in July 2007, and labeling legislation will be implemented soon. In this study, duplex polymerase chain reaction (PCR) was carried out to detect
endogenous soybean lectin gene and exogenous cp4-epsps (5’-enolpyruvylshikimate-3-phospate synthase) gene simultaneously. Additionally, real-time PCR utilizing SYBR Green fluorescence dye were established for the quantitative analysis of Roundup Ready soybean (RRS), which is based on the two established calibration curve from cloned fragment of cp4-epsps gene and lectin gene respectively. Approximately, 39.5% (45/114) of the samples examined in this study contain RRS, animal feeds (31), processed food (13) and raw soybean (1). Additionally, 75.6% (34/45) of the positive samples were found contained RRS above 0.9%. The sensitive GMO quantitative approach described in this study enable the analysis of various samples and this will facilitate the labeling process.
The use of Fourier transform infrared (FTIR) spectroscopy coupled with chemometric techniques to differentiate butter from beef fat (BF) was investigated. The spectral bands associated with butter, BF, and their mixtures were scanned, interpreted, and identified by relating them to those spectroscopically representative to pure butter and BF. For quantitative analysis, partial least square (PLS) regression was used to develop a calibration model at the selected fingerprint regions of 1500-1000 cm-1, with the values of coefficient of determination (R2) and root mean square error of calibration (RMSEC) are 0.999 and 0.89% (v/v), respectively. The PLS calibration model was subsequently used for the prediction of independent samples containing butter in the binary mixtures with BF. Using 6 principal components, root mean square error of prediction (RMSEP) is 2.42% (v/v). These results proved that FTIR spectroscopy in combination with multivariate calibration can be used for the detection and quantification of BF in butter formulation for authentication use.
The objective of this retrospective study was to investigate what percentage of the dental students in the University of Malaya has a tooth size discrepancy. The sample comprised 40 good quality pre-treatment study models with fully erupted and complete permanent dentitions from first molar to first molar, which were selected from the dental students of the University of Malaya. The mesiodistal diameter tooth sizes were randomly measured manually from first molar to first molar using digital calliper (Mitutoyu) accurate to 0.01 mm, and the Bolton analyses for anterior and overall ratios were calculated by scientific calculator. Reproducibility analysis for intra- and interexaminer calibrations was assessed by measuring 10 study models twice, a week apart. A paired sample t-test and the correlation coefficient were used to evaluate the systematic and random errors of the measurements using Statistical Package for Social Sciences (SPSS) version 12.0. The reproducibility of the intra and inter-examiners for the sum of upper and lower mesiodistal tooth size were high (average mean difference = 0.62, r = 0.82). This study found 47.5% of the samples had anterior, and about 10% had overall· tooth width ratios greater than 2 standard deviations from Bolton's mean. Large percentage of the dental students of the University of Malaya has tooth size discrepancies outside of Bolton 2 standard deviations. It would seem prudent to routinely perform the tooth size analysis and include the findings into orthodontic treatment planning.
Personal computer (PC) based user interface for equipment control and data acquisition from the nuclear counting system to count nuclear radiation energy from radioactive sources have been developed at Malaysian Nuclear Agency. Effort is made to ensure a good reliability of the system for nuclear counting, especially neutrons particles and gamma rays. It will be used in laboratory for testing and maintenance of nuclear spectrometry instruments. Personal computer is used to control the operation of equipment and data acquisition from counter/timer module. Control and data communication between PC and the Counter/ Timer is made through the USB' to RS 232 converter terminal. The program for this system was written using Labview 8.6 software on Windows XP environment. This system has been successfully tested using a pulse generator to simulate the detector signal for calibration and then followed by actual measurement using HE-3 detector.
An artificial neural network (ANN) was applied for the determination of V(V) based on immobilized fatty hydroxamic acid (FHA) in poly(methyl methacrylate) (PMMA). Spectra obtained from the V(V)-FHA complex at single wavelengths was used as the input data for the ANN. The V(V)-FHA complex shows a limited linear dynamic range of V(V) concentration of 10 - 100 mg/ L. After training with ANN, the linear dynamic range was extended with low calibration error. A three layer feed forward neural network using backpropagation (BP) algorithm was employed in this study. The input layer consisted of single neurons, 30 neurons in hidden a layer and one output neuron was found appropriate for the multivariate calibration used. The network were trained up to 10000 epochs with 0.003 % learning rate. This reagent also provided a good analytical pedormance with reproducibility characters of the method yielding relative standard deviation (RSD) of 9.29% and 7.09% for V(V) at concentrations of 50 mg/ L and 200 mg/ L, respectively. The limit of detection of the method was 8.4 mg/ L.
Two functional food oils, namely extra virgin olive oil (EVOO) and virgin coconut oil (VCO) have been analyzed simultaneously using Fourier transform infrared (FTIR) spectroscopy. The performance of multivariate calibration of principle component regression (PCR) and partial least square regression (PLSR) was evaluated in order to give the best prediction model for such determination. FTIR spectra were treated with several treatments including mean centering (MC), derivatization, and standard normal variate (SNV) at the combined frequency regions of 3050 – 3000, 1660 – 1650, and 1200 – 900 cm-1. Based on its capability to give the highest values of coefficient of correlation (R) for the relationship between actual value of EVOO/VCO and FTIR predicted value together with the lowest values of root mean square error of calibration (RMSEC), PLSR with mean centered-first derivative spectra was chosen for simultaneous determination of EVOO and VCO. It can be concluded that FTIR spectroscopy combined with multivariate calibration of PLSR was successfully applied to simultaneously quantify EVOO and VCO with acceptable parameters.
Introduction: Accurate yet inexpensive methods for measuring free-living energy expenditure (EE) are
much needed. The aim of this study was to determine the feasibility of heart-rate monitoring method
(HRM) in measuring EE as compared to the established activity diary (AD) method. Methodology:
Minute-by-minute HRM and an activity diary (AD) were used simultaneously in 34 young adults (18
females, 16 males; mean age 21.5 ± 1.5 years). Estimates of the EE from HRM were based on individual
calibration using the Flex-HR procedure while EE from AD were calculated using both individually
measured and published energy cost of various activities. Total daily energy expenditure (TDEE) and its
components (EE during sleep, during rest and during physical activity) were compared using Student
paired-t tests. Results: TDEE from HRM method averaged 8.17 ± 2.00 MJ/day compared to 8.50 ±
1.28 MJ/day from AD method. Although large intra-individual differences were found (ranging from
-36.9% to 47.4%), there was no significant difference between the two methods (mean difference -3.6 ± 19.4%). The limits of agreement (mean ± 2SD) were -3.77 and 3.11 MJ/day. There were no significant
differences for any of the TDEE components between the two methods, except for EE during sleep
(p