The objective of the study was to determine whether discriminant analysis of characteristics of dyspepsia can differentiate peptic ulcer from non-ulcer dyspepsia in a Malaysian population. Two hundred and twenty six patients with dyspepsia were interviewed using a standard history questionnaire before undergoing upper gastrointestinal endoscopy. Forty seven patients had peptic ulcer while 149 others were classified as having non-ulcer dyspepsia. Stepwise logistic regression analysis was done on 25 variables. The study showed that only five of these variables could differentiate peptic ulcer from non-ulcer dyspepsia, namely, nocturnal pain, pain before meals or when hungry, absence of nausea, age and sex. A scoring system was devised based on these discriminant symptoms. At a sensitivity of 51%, the specificity for peptic ulcer was 83%, but only prospective studies will determine if this scoring system is of actual clinical value.
Discriminant analysis of six trace element concentrations measured by instrumental neutron activation analysis (INAA) in 26 paired-samples of malignant and histologically normal human breast tissues shows the technique to be a potentially valuable clinical tool for making malignant-normal classification. Nonparametric discriminant analysis is performed for the data obtained. Linear and quadratic discriminant analyses are also carried out for comparison. For this data set a formal analysis shows that the elements which may be useful in distinguishing between malignant and normal tissues are Ca, Rb and Br, providing correct classification for 24 out of 26 normal samples and 22 out of 26 malignant samples.
The pollinators of 29 ginger species representing 11 genera in relation to certain floral morphological characteristics in a mixed-dipterocarp forest in Borneo were investigated. Among the 29 species studied, eight were pollinated by spiderhunters (Nectariniidae), 11 by medium-sized Amegilla bees (Anthophoridae), and ten by small halictid bees. These pollination guilds found in gingers in Sarawak are comparable to the pollination guilds of neotropical Zingiberales, i.e., hummingbird-, and euglossine-bee-pollinated guilds. Canonical discriminant analysis revealed that there were significant correlations between floral morphology and pollination guilds and suggests the importance of plant-pollinator interactions in the evolution of floral morphology. Most species in the three guilds were separated on the plot by the first and second canonical variables. Spiderhunter-pollinated flowers had longer floral tubes, while Amegilla-pollinated flowers had wider lips than the others, which function as a platform for the pollinators. Pistils and stamens of halictid-pollinated flowers were smaller than the others. The fact that gingers with diverse morphologies in a forest with high species diversity were grouped into only three pollination guilds and that the pollinators themselves showed low species diversity suggests that many species of rare understory plants have evolved without segregating pollinators in each pollination guild.
Allele frequencies for the nine STRs genetic loci included in the AmpFlSTR Profiler kit were obtained from samples of unrelated individuals comprising 139-156 Malays, 149-153 Chinese and 132-135 Indians, residing in Malaysia.
To validate the English version of the Spielberger State-Trait Anxiety Inventory (STAI) in a sample of Malaysia patients with and without urinary symptoms. Validity and reliability were studied in patients with lower urinary tract symptoms (LUTS) and patients without LUTS. Reliability was evaluated using the test-retest method and internal consistency was assessed using Cronbach's alpha. Sensitivity to change was expressed as the effect size in the pre-intervention versus post-intervention score in additional patients with LUTS who underwent transurethral resection of the prostate (TURP). Internal consistency was excellent. A high degree of internal consistency was observed for each of the 40 items with Cronbach's alpha value = 0.38 to 0.89 while the Cronbach's alpha for the total scores was 0.86. Test-retest correlation coefficients for the 40 items score were highly significant. Intraclass correlation coefficient was high (ICC=0.39 to 0.89). A high degree of sensitivity and specificity to the effects of treatment was observed. A high degree of significant level between baseline and post-treatment scores was observed across nearly half of the items in surgical group but not in the non-LUTS group (control subjects). The STAI is reliable, valid and sensitive to clinical change in a sample of Malaysian patients with and without urinary symptoms.
We examined the geographical variation of the skull size and shape of the lesser mouse deer (Tragulus javanicus) from Laos, Thailand, Peninsular Malaysia, Sumatra, Java, Borneo, Langkawi and some Islands of Tenasserim in Myanmar. Although the influence of the climatic condition on skull size was not confirmed in the mainland populations, the skull became rostro-caudally longer in the populations of Tenasserim and Sumatra because of island isolation effect. The skull size was classified into the following three clusters of localities from the matrix of Q-mode correlation coefficients: 1) Langkawi and Tenasserim, 2) Laos and Thailand, 3) Sumatra and Borneo. The skulls in the population of Java belong to the cluster of Langkawi and Tenasserim in male, however were morphologically similar to those in the cluster of Borneo and Sumatra. The canonical discriminant analysis pointed out that the Laos and Tenasserim populations were separated from the other ones and that the populations of Sumatra, Java and Borneo were intermingled each other.
Cockles (Anadara granosa) sample obtained from two rivers in the Penang State of Malaysia were analyzed for the content of arsenic (As) and heavy metals (Cr, Cd, Zn, Cu, Pb, and Hg) using a graphite flame atomic absorption spectrometer (GF-AAS) for Cr, Cd, Zn, Cu, Pb, As and cold vapor atomic absorption spectrometer (CV-AAS) for Hg. The two locations of interest with 20 sampling points of each location were Kuala Juru (Juru River) and Bukit Tambun (Jejawi River). Multivariate statistical techniques such as multivariate analysis of variance (MANOVA) and discriminant analysis (DA) were applied for analyzing the data. MANOVA showed a strong significant difference between the two rivers in term of As and heavy metals contents in cockles. DA gave the best result to identify the relative contribution for all parameters in discriminating (distinguishing) the two rivers. It provided an important data reduction as it used only two parameters (Zn and Cd) affording more than 72% correct assignations. Results indicated that the two rivers were different in terms of As and heavy metal contents in cockle, and the major difference was due to the contribution of Zn and Cd. A positive correlation was found between discriminate functions (DF) and Zn, Cd and Cr, whereas negative correlation was exhibited with other heavy metals. Therefore, DA allowed a reduction in the dimensionality of the data set, delineating a few indicator parameters responsible for large variations in heavy metals and arsenic content. Taking into account of these results, it can be suggested that a continuous monitoring of As and heavy metals in cockles be performed in these two rivers.
Four types of soft dates (SD), three types of semi-dried dates (SDD) and one type of dried dates (DD) were used in this study. The antioxidant activities were assessed using TEAC method (ABTS assay) and the ferric reducing/antioxidant power method (FRAP assay), while total phenolic content (TPC) and total flavonoid content (TFC) were measured using Folin-Ciocalteau and aluminum chloride colorimetric methods. Multivariate analysis of variance (MANOVA), discriminant analysis (DA) and principal component analysis (PCA) were used to analyze the data. MANOVA showed a strong significant difference between the eight types of dates. DA identified the relative contribution of each parameter in distinguishing the dates. DA also identified two functions responsible for discriminating the dates and showed the difference between different types of dates. The first function distinguished DD from other types of dates, whilst the second function discriminated SD and SDD, affording 100% correct assignation. PCA identified only one component responsible for explaining 98.85% of the total variance in antioxidant data. It is suggested that the TEAC method and the quantitative determination of TPC and TFC was suitable for differentiation of dates and quality control.
Physical properties of ripe banana flour were studied in Cavendish and Dream banana, in order to distinguish the two varieties. Flour was analyzed for pH, total soluble solids (TSS), water holding capacity
(WHC) and oil holding capacity (OHC) at 40, 60 and 80 °C, color values L*, a* and b*, back extrusion force
and viscosity. Physical properties data were analyzed by cluster analysis (CA) and discriminant analysis (DA). CA showed that the two types of flour were different in terms of selected physical properties. DA indicated that WHC at 60 °C was the main contributor in discriminating the two types of flour.
The present study deals with the assessment of Langat River water quality with some chemometrics approaches such as cluster and discriminant analysis coupled with an artificial neural network (ANN). The data used in this study were collected from seven monitoring stations under the river water quality monitoring program by the Department of Environment (DOE) from 1995 to 2002. Twenty three physico-chemical parameters were involved in this analysis. Cluster analysis successfully clustered the Langat River into three major clusters, namely high, moderate and less pollution regions. Discriminant analysis identified seven of the most significant parameters which contribute to the high variation of Langat River water quality, namely dissolved oxygen, biological oxygen demand, pH, ammoniacal nitrogen, chlorine, E. coli, and coliform. Discriminant analysis also plays an important role as an input selection parameter for an ANN of spatial prediction (pollution regions). The ANN showed better prediction performance in discriminating the regional area with an excellent percentage of correct classification compared to discriminant analysis. Multivariate analysis, coupled with ANN, is proposed, which could help in decision making and problem solving in the local environment.
This paper presents a statistical method for the detection of lobar pneumonia when using digitized chest X-ray films. Each region of interest was represented by a vector of wavelet texture measures which is then multiplied by the orthogonal matrix Q(2). The first two elements of the transformed vectors were shown to have a bivariate normal distribution. Misclassification probabilities were estimated using probability ellipsoids and discriminant functions. The result of this study recommends the detection of pneumonia by constructing probability ellipsoids or discriminant function using maximum energy and maximum column sum energy texture measures where misclassification probabilities were less than 0.15.
The task of identifying firearms from forensic ballistics specimens is exacting in crime investigation since the last two decades. Every firearm, regardless of its size, make and model, has its own unique 'fingerprint'. These fingerprints transfer when a firearm is fired to the fired bullet and cartridge case. The components that are involved in producing these unique characteristics are the firing chamber, breech face, firing pin, ejector, extractor and the rifling of the barrel. These unique characteristics are the critical features in identifying firearms. It allows investigators to decide on which particular firearm that has fired the bullet. Traditionally the comparison of ballistic evidence has been a tedious and time-consuming process requiring highly skilled examiners. Therefore, the main objective of this study is the extraction and identification of suitable features from firing pin impression of cartridge case images for firearm recognition. Some previous studies have shown that firing pin impression of cartridge case is one of the most important characteristics used for identifying an individual firearm. In this study, data are gathered using 747 cartridge case images captured from five different pistols of type 9mm Parabellum Vektor SP1, made in South Africa. All the images of the cartridge cases are then segmented into three regions, forming three different set of images, i.e. firing pin impression image, centre of firing pin impression image and ring of firing pin impression image. Then geometric moments up to the sixth order were generated from each part of the images to form a set of numerical features. These 48 features were found to be significantly different using the MANOVA test. This high dimension of features is then reduced into only 11 significant features using correlation analysis. Classification results using cross-validation under discriminant analysis show that 96.7% of the images were classified correctly. These results demonstrate the value of geometric moments technique for producing a set of numerical features, based on which the identification of firearms are made.
An improved classification of Orthosiphon stamineus using a data fusion technique is presented. Five different commercial sources along with freshly prepared samples were discriminated using an electronic nose (e-nose) and an electronic tongue (e-tongue). Samples from the different commercial brands were evaluated by the e-tongue and then followed by the e-nose. Applying Principal Component Analysis (PCA) separately on the respective e-tongue and e-nose data, only five distinct groups were projected. However, by employing a low level data fusion technique, six distinct groupings were achieved. Hence, this technique can enhance the ability of PCA to analyze the complex samples of Orthosiphon stamineus. Linear Discriminant Analysis (LDA) was then used to further validate and classify the samples. It was found that the LDA performance was also improved when the responses from the e-nose and e-tongue were fused together.
This study investigates the spatial water quality pattern of seven stations located along the main Langat River. Environmetric methods, namely, the hierarchical agglomerative cluster analysis (HACA), the discriminant analysis (DA), the principal component analysis (PCA), and the factor analysis (FA), were used to study the spatial variations of the most significant water quality variables and to determine the origin of pollution sources. Twenty-three water quality parameters were initially selected and analyzed. Three spatial clusters were formed based on HACA. These clusters are designated as downstream of Langat river, middle stream of Langat river, and upstream of Langat River regions. Forward and backward stepwise DA managed to discriminate six and seven water quality variables, respectively, from the original 23 variables. PCA and FA (varimax functionality) were used to investigate the origin of each water quality variable due to land use activities based on the three clustered regions. Seven principal components (PCs) were obtained with 81% total variation for the high-pollution source (HPS) region, while six PCs with 71% and 79% total variances were obtained for the moderate-pollution source (MPS) and low-pollution source (LPS) regions, respectively. The pollution sources for the HPS and MPS are of anthropogenic sources (industrial, municipal waste, and agricultural runoff). For the LPS region, the domestic and agricultural runoffs are the main sources of pollution. From this study, we can conclude that the application of environmetric methods can reveal meaningful information on the spatial variability of a large and complex river water quality data.
To assess the cross-sectional construct validity of the Malay-translated and cross-culturally adapted FACT-H&N (v 4.0) for discriminative use in a sample of Malaysian oral cancer patients. A cross-sectional study of adults newly diagnosed with oral cancer. HRQOL data were collected using the FACT-H&N (v 4.0), a global question and a supplementary set of eight questions ('MAQ') obtained earlier in pilot work. Of the 76 participants (61.8% female; 23.7% younger than 50), most (96.1%) had oral squamous cell carcinoma; two-thirds were in Stages III or IV. At baseline, patients' mean FACT summary (FACT-G, FACT-H&N, FACT-H&N TOI, and FHNSI) and subscale (pwb, swb, ewb, fwb, and hnsc) scores were towards the higher end of the range. Equal proportions (36.8%) rated their overall HRQOL as 'good' or 'average'; fewer than one-quarter rated it as 'poor', and only two as 'very good'. All six FACT summary and most subscales had moderate-to-good internal consistency. For all summary scales, those with 'very poor/poor' self-rated HRQOL differed significantly from the 'good/very good' group. All FACT summary scales correlated strongly (r>0.75). Summary scales showed convergent validity (r>0.90) but little discriminant validity. The discriminant validity of the FHNSI improved with the addition of the MAQ. The FACT-H&N summary scales and most subscales demonstrated acceptable cross-sectional construct validity, reliability and discriminative ability, and thus appear appropriate for further use among Malaysian oral cancer patients.
Currently, the authentication of virgin coconut oil (VCO) has become very important due to the possible adulteration of VCO with cheaper plant oils such as corn (CO) and sunflower (SFO) oils. Methods involving Fourier transform mid infrared (FT-MIR) spectroscopy combined with chemometrics techniques (partial least square (PLS) and discriminant analysis (DA)) were developed for quantification and classification of CO and SFO in VCO. MIR spectra of oil samples were recorded at frequency regions of 4000-650cm-1 on horizontal attenuated total reflectance (HATR) attachment of FTIR. DA can successfully classify VCO and that adulterated with CO and SFO using 10 principal components. Furthermore, PLS model correlates the actual and FTIR estimated values of oil adulterants (CO and SFO) with coefficient of determination (R2) of 0.999.
Red fruit (Pandanus conoideus Lam) is endemic plant of Papua, Indonesia and Papua New Guinea. The price of its oil (red fruit oil, RFO) is 10-15 times higher than that of common vegetable oils; consequently, RFO is subjected to adulteration with lower price oils. Among common vegetable oils, canola oil (CaO) and rice bran oil (RBO) have similar fatty acid profiles to RFO as indicated by the score plot of principal component analysis; therefore, CaO and RBO are potential adulterants in RFO.
The larval parasitoid Verticia fasciventris Malloch (Diptera: Calliphoridae) develops in the head of soldiers of the fungus-growing termite Macrotermes carbonarius (Hagen) (Isoptera: Termitidae). Morphological and behavioral changes in the host were evaluated and the termite castes and stages that were parasitized were identified. The larval emergence process is also described and possible mechanisms for the parasitoid fly's entry into the host body are discussed based on qualitative observations. Only a single larva per host was found. The mature larva pupated outside the host's body by exiting between the abdominal cerci. Parasitized soldiers possess a short and square-shaped head capsule, a pair of notably short mandibles, and a pair of 18-segmented antennae. Although parasitized soldiers were statistically less aggressive than healthy soldiers (P < 0.05), they expressed varying levels of aggression. Both minor and major soldiers can be parasitized and based on evidence from presoldiers, parasitization may begin during the precursor stages of soldiers. However, the stage at which parasitism first occurs has not been determined.
Increasing urbanization and changes in land use in Langat river basin lead to adverse impacts on the environment compartment. One of the major challenges is in identifying sources of organic contaminants. This study presented the application of selected chemometric techniques: cluster analysis (CA), discriminant analysis (DA), and principal component analysis (PCA) to classify the pollution sources in Langat river basin based on the analysis of water and sediment samples collected from 24 stations, monitored for 14 organic contaminants from polycyclic aromatic hydrocarbons (PAHs), sterols, and pesticides groups. The CA and DA enabled to group 24 monitoring sites into three groups of pollution source (industry and urban socioeconomic, agricultural activity, and urban/domestic sewage) with five major discriminating variables: naphthalene, pyrene, benzo[a]pyrene, coprostanol, and cholesterol. PCA analysis, applied to water data sets, resulted in four latent factors explaining 79.0% of the total variance while sediment samples gave five latent factors with 77.6% explained variance. The varifactors (VFs) obtained from PCA indicated that sterols (coprostanol, cholesterol, stigmasterol, β-sitosterol, and stigmastanol) are strongly correlated to domestic and urban sewage, PAHs (naphthalene, acenaphthene, pyrene, benzo[a]anthracene, and benzo[a]pyrene) from industrial and urban activities and chlorpyrifos correlated to samples nearby agricultural sites. The results demonstrated that chemometric techniques can be used for rapid assessment of water and sediment contaminations.
Gas chromatography mass spectrometry (GC-MS) and headspace gas chromatography mass spectrometry (HS/GC-MS) were used to study metabolites produced by Lactococcus lactis subsp. cremoris MG1363 grown at a temperature of 30 °C with and without agitation at 150 rpm, and at 37 °C without agitation. It was observed that L. lactis produced more organic acids under agitation. Primary alcohols, aldehydes, ketones and polyols were identified as the corresponding trimethylsilyl (TMS) derivatives, whereas amino acids and organic acids, including fatty acids, were detected through methyl chloroformate derivatization. HS analysis indicated that branched-chain methyl aldehydes, including 2-methylbutanal, 3-methylbutanal, and 2-methylpropanal are degdradation products of isoleucine, leucine or valine. Multivariate analysis (MVA) using partial least squares discriminant analysis (PLS-DA) revealed the major differences between treatments were due to changes of amino acids and fermentation products.