Displaying publications 1 - 20 of 104 in total

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  1. Radford CA, Ghazali SM, Montgomery JC, Jeffs AG
    PLoS One, 2016;11(2):e0149338.
    PMID: 26890124 DOI: 10.1371/journal.pone.0149338
    Fish vocalisation is often a major component of underwater soundscapes. Therefore, interpretation of these soundscapes requires an understanding of the vocalisation characteristics of common soniferous fish species. This study of captive female bluefin gurnard, Chelidonichthys kumu, aims to formally characterise their vocalisation sounds and daily pattern of sound production. Four types of sound were produced and characterised, twice as many as previously reported in this species. These sounds fit two aural categories; grunt and growl, the mean peak frequencies for which ranged between 129 to 215 Hz. This species vocalized throughout the 24 hour period at an average rate of (18.5 ± 2.0 sounds fish-1 h-1) with an increase in vocalization rate at dawn and dusk. Competitive feeding did not elevate vocalisation as has been found in other gurnard species. Bluefin gurnard are common in coastal waters of New Zealand, Australia and Japan and, given their vocalization rate, are likely to be significant contributors to ambient underwater soundscape in these areas.
    Matched MeSH terms: Discriminant Analysis
  2. Muhammad SA, Seow EK, Mohd Omar AK, Rodhi AM, Mat Hassan H, Lalung J, et al.
    Sci Justice, 2018 Jan;58(1):59-66.
    PMID: 29332695 DOI: 10.1016/j.scijus.2017.05.008
    A total of 33 crude palm oil samples were randomly collected from different regions in Malaysia. Stable carbon isotopic composition (δ13C) was determined using Flash 2000 elemental analyzer while hydrogen and oxygen isotopic compositions (δ2H and δ18O) were analyzed by Thermo Finnigan TC/EA, wherein both instruments were coupled to an isotope ratio mass spectrometer. The bulk δ2H, δ18O and δ13C of the samples were analyzed by Hierarchical Cluster Analysis (HCA), Principal Component Analysis (PCA) and Orthogonal Partial Least Square-Discriminant Analysis (OPLS-DA). Unsupervised HCA and PCA methods have demonstrated that crude palm oil samples were grouped into clusters according to respective state. A predictive model was constructed by supervised OPLS-DA with good predictive power of 52.60%. Robustness of the predictive model was validated with overall accuracy of 71.43%. Blind test samples were correctly assigned to their respective cluster except for samples from southern region. δ18O was proposed as the promising discriminatory marker for discerning crude palm oil samples obtained from different regions. Stable isotopes profile was proven to be useful for origin traceability of crude palm oil samples at a narrower geographical area, i.e. based on regions in Malaysia. Predictive power and accuracy of the predictive model was expected to improve with the increase in sample size. Conclusively, the results in this study has fulfilled the main objective of this work where the simple approach of combining stable isotope analysis with chemometrics can be used to discriminate crude palm oil samples obtained from different regions in Malaysia. Overall, this study shows the feasibility of this approach to be used as a traceability assessment of crude palm oils.
    Matched MeSH terms: Discriminant Analysis
  3. Doss JG, Thomson WM, Drummond BK, Raja Latifah RJ
    Oral Oncol, 2011 Jul;47(7):648-52.
    PMID: 21602094 DOI: 10.1016/j.oraloncology.2011.04.023
    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.
    Matched MeSH terms: Discriminant Analysis
  4. Nik Mohd Fakhruddin NNI, Shahar S, Ismail IS, Ahmad Azam A, Rajab NF
    Nutrients, 2020 Sep 23;12(10).
    PMID: 32977370 DOI: 10.3390/nu12102900
    Food intake biomarkers (FIBs) can reflect the intake of specific foods or dietary patterns (DP). DP for successful aging (SA) has been widely studied. However, the relationship between SA and DP characterized by FIBs still needs further exploration as the candidate markers are scarce. Thus, 1H-nuclear magnetic resonance (1H-NMR)-based urine metabolomics profiling was conducted to identify potential metabolites which can act as specific markers representing DP for SA. Urine sample of nine subjects from each three aging groups, SA, usual aging (UA), and mild cognitive impairment (MCI), were analyzed using the 1H-NMR metabolomic approach. Principal components analysis (PCA) and partial least-squares discriminant analysis (PLS-DA) were applied. The association between SA urinary metabolites and its DP was assessed using the Pearson's correlation analysis. The urine of SA subjects was characterized by the greater excretion of citrate, taurine, hypotaurine, serotonin, and melatonin as compared to UA and MCI. These urinary metabolites were associated with alteration in "taurine and hypotaurine metabolism" and "tryptophan metabolism" in SA elderly. Urinary serotonin (r = 0.48, p < 0.05) and melatonin (r = 0.47, p < 0.05) were associated with oat intake. These findings demonstrate that a metabolomic approach may be useful for correlating DP with SA urinary metabolites and for further understanding of SA development.
    Matched MeSH terms: Discriminant Analysis
  5. Mohebbi K, Ibrahim S, Zamani M, Khezrian M
    PLoS One, 2014;9(8):e104735.
    PMID: 25157872 DOI: 10.1371/journal.pone.0104735
    In this paper, a Semantic Web service matchmaker called UltiMatch-NL is presented. UltiMatch-NL applies two filters namely Signature-based and Description-based on different abstraction levels of a service profile to achieve more accurate results. More specifically, the proposed filters rely on semantic knowledge to extract the similarity between a given pair of service descriptions. Thus it is a further step towards fully automated Web service discovery via making this process more semantic-aware. In addition, a new technique is proposed to weight and combine the results of different filters of UltiMatch-NL, automatically. Moreover, an innovative approach is introduced to predict the relevance of requests and Web services and eliminate the need for setting a threshold value of similarity. In order to evaluate UltiMatch-NL, the repository of OWLS-TC is used. The performance evaluation based on standard measures from the information retrieval field shows that semantic matching of OWL-S services can be significantly improved by incorporating designed matching filters.
    Matched MeSH terms: Discriminant Analysis
  6. Muhammad Zul Fayyadh Azizo Rahman, Chong, Hui Wen, Lim, Vuanghao
    MyJurnal
    Adulterated premixed coffees have turned into an issue in Malaysia lately and have caught the eye of the authorities due to death reports linked to these products. The major cause of this issue is reported that these premixed coffees have passed food inspection test and eventually released to the market for public consumption. These coffees were claimed to be spiked with several sexual enhancers like sildenafil, tadalafil, and vardenafill, which are common drugs used to treat erectile dysfunction. Methods: Chemometrics approach using UV-Vis spectroscopy was developed to detect the selected sexual enhancer drugs found in commercial coffees by employing SIMCA-P software for the multivariate statistical analysis. Seven brands of coffee samples were purchased from local stores, and 30 sachets each were tested, hence totalling to 210 samples. Each sample was named H, J, G, W, N, T, and K, respectively. Results: Three multivariate models were generated, namely principal component analysis (PCA), orthogonal partial least squares discriminant analysis (OPLS-DA), and partial least squares discriminant analysis (PLS-DA). OPLS-DA was selected as the best model for the overall results as it displayed minimal discriminate. Sildenafil, tadalafil, and vardenafil were detected in sample H, while vardenafil in brand J, and none in samples G, W, N, T, and K. Conclusion: OPLS-DA analysis showed discrimination for the sexual enhancer drugs in two brands of premixed coffee. The UV-Vis spectroscopy-based chemometrics method proved to be reliable and efficient in determining the selected drugs, as well as in saving time and cost.
    Matched MeSH terms: Discriminant Analysis
  7. Wang J, Chen T, Zhang W, Zhao Y, Yang S, Chen A
    Food Chem, 2020 May 30;313:126093.
    PMID: 31927205 DOI: 10.1016/j.foodchem.2019.126093
    Multivariate stable isotope analysis combined with chemometrics was used to investigate and discriminate rice samples from six rice producing provinces in China (Heilongjiang, Jilin, Jiangsu, Zhejiang, Hunan and Guizhou) and four other Asian rice producing countries (Thailand, Malaysia, Philippines, and Pakistan). The stable isotope characteristics were analyzed for rice of different species cultivated with varied farming methods at different altitudes and latitudes/longitudes. The index groups of δ13C, δ15N, δ18O, 207/206Pb and 208/207Pb were screened and established for the selected samples with different geographical features by means of principal component analysis (PCA) and discriminant analysis (DA), which would provide a sound technical solution for rice traceability and serve as a template for further research on the traceability of other agricultural products, especially plant-derived products.
    Matched MeSH terms: Discriminant Analysis
  8. Sakai S, Kato M, Inoue T
    Am J Bot, 1999 May;86(5):646-58.
    PMID: 10330067
    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.
    Matched MeSH terms: Discriminant Analysis
  9. Bilal S, Doss JG, Rogers SN
    J Craniomaxillofac Surg, 2014 Dec;42(8):1590-7.
    PMID: 25224886 DOI: 10.1016/j.jcms.2014.04.015
    In the last decade there has been an increasing awareness about 'quality of life' (QOL) of cancer survivors in developing countries. The study aimed to cross-culturally adapt and validate the FACT-H&N (v4) in Urdu language for Pakistani head and neck cancer patients. In this study the 'same language adaptation method' was used. Cognitive debriefing through in-depth interviews of 25 patients to assess semantic, operational and conceptual equivalence was done. The validation phase included 50 patients to evaluate the psychometric properties. The translated FACT-H&N was easily comprehended (100%). Cronbach's alpha for FACT-G subscales ranged from 0.726 - 0.969. The head and neck subscale and Pakistani questions subscale showed low internal consistency (0.426 and 0.541 respectively). Instrument demonstrated known-group validity in differentiating patients of different clinical stages, treatment status and tumor sites (p < 0.05). Most FACT summary scales correlated strongly with each other (r > 0.75) and showed convergent validity (r > 0.90), with little discriminant validity. Factor analysis revealed 6 factors explaining 85.1% of the total variance with very good (>0.8) Kaiser-Meyer-Olkin and highly significant Bartlett's Test of Sphericity (p < 0.001). The cross-culturally adapted FACT-H&N into Urdu language showed adequate reliability and validity to be incorporated in Pakistani clinical settings for head and neck cancer patients.
    Matched MeSH terms: Discriminant Analysis
  10. Rohman A, Che Man YB
    Food Chem, 2011 Nov 15;129(2):583-588.
    PMID: 30634271 DOI: 10.1016/j.foodchem.2011.04.070
    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.
    Matched MeSH terms: Discriminant Analysis
  11. Rajamoorthy Y, Radam A, Taib NM, Rahim KA, Wagner AL, Mudatsir M, et al.
    PLoS One, 2018;13(12):e0208402.
    PMID: 30521602 DOI: 10.1371/journal.pone.0208402
    BACKGROUND: Malaysia has a comprehensive, publicly-funded immunization program for hepatitis B (HepB) among infants, but adults must pay for the vaccine. The number of HepB carriers among adults is expected to increase in the future; therefore, we examined the impact of five constructs (cues to action, perceived barriers, perceived benefit, perceived severity, and perceived susceptibility) on adults' willingness to pay (WTP) for HepB vaccine; secondarily, we examined the association between perceived barriers and perceived benefits.

    METHODS: Adults were selected through a stratified, two-stage cluster community sample in Selangor, Malaysia. The reliability, convergent validity, and discriminant validity of the measurement model were assessed before implementing a partial least squares structural equation model (PLS-SEM) to evaluate the significance of the structural paths.

    RESULTS: A total of 728 participants were enrolled. The five constructs all showed adequate internal reliability, convergent validity, and discriminant validity. There was a significant, positive relationship to WTP from constructs (perceived barriers [Path coefficient (β) = 0.082, P = 0.036], perceived susceptibility [β = 0.214, P<0.001], and cues to action [β = 0.166, P<0.001]), and the model all together accounted for 8.8% of the variation in WTP. There was a significant, negative relationship between perceived barriers and perceived benefit [β = -0.261, P<0.001], which accounted for 6.8% of variation in perceived benefit.

    CONCLUSIONS: Policy and programs should be targeted that can modify individuals' thoughts about disease risk, their obstacles in obtaining the preventive action, and their readiness to obtain a vaccine. Such programs include educational materials about disease risk and clinic visits that can pair HepB screening and vaccination.

    Matched MeSH terms: Discriminant Analysis
  12. Neoh KB, Lee CY
    J Insect Sci, 2011;11:47.
    PMID: 21861651 DOI: 10.1673/031.011.4701
    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.
    Matched MeSH terms: Discriminant Analysis
  13. Sarpeshkar V, Mann DL, Spratford W, Abernethy B
    Hum Mov Sci, 2017 Aug;54:82-100.
    PMID: 28410536 DOI: 10.1016/j.humov.2017.04.003
    Successful interception relies on the use of perceptual information to accurately guide an efficient movement strategy that allows performers to be placed at the right place at the right time. Although previous studies have highlighted the differences in the timing and coordination of movement that underpin interceptive expertise, very little is known about how these movement patterns are adapted when intercepting targets that follow a curvilinear flight-path. The aim of this study was to examine how curvilinear ball-trajectories influence movement patterns when intercepting a fast-moving target. Movement timing and coordination was examined when four groups of cricket batters, who differed in their skill level and/or age, hit targets that followed straight or curvilinear flight-paths. The results revealed that when compared to hitting straight trials, (i) mixing straight with curvilinear trials altered movement coordination and when the ball was hit, (ii) curvilinear trajectories reduced interceptive performance and significantly delayed the timing of all kinematic moments, but there were (iii) larger decrease in performance when the ball swung away from (rather than in towards) the performer. Movement coordination differed between skill but not age groups, suggesting that skill-appropriate movement patterns that are apparent in adults may have fully emerged by late adolescence.
    Matched MeSH terms: Discriminant Analysis
  14. Lee YF, Sim XY, Teh YH, Ismail MN, Greimel P, Murugaiyah V, et al.
    Biotechnol Appl Biochem, 2021 Oct;68(5):1014-1026.
    PMID: 32931602 DOI: 10.1002/bab.2021
    High-fat diet (HFD) interferes with the dietary plan of patients with type 2 diabetes mellitus (T2DM). However, many diabetes patients consume food with higher fat content for a better taste bud experience. In this study, we examined the effect of HFD on rats at the early onset of diabetes and prediabetes by supplementing their feed with palm olein oil to provide a fat content representing 39% of total calorie intake. Urinary profile generated from liquid chromatography-mass spectrometry analysis was used to construct the orthogonal partial least squares discriminant analysis (OPLS-DA) score plots. The data provide insights into the physiological state of an organism. Healthy rats fed with normal chow (NC) and HFD cannot be distinguished by their urinary metabolite profiles, whereas diabetic and prediabetic rats showed a clear separation in OPLS-DA profile between the two diets, indicating a change in their physiological state. Metformin treatment altered the metabolomics profiles of diabetic rats and lowered their blood sugar levels. For prediabetic rats, metformin treatment on both NC- and HFD-fed rats not only reduced their blood sugar levels to normal but also altered the urinary metabolite profile to be more like healthy rats. The use of metformin is therefore beneficial at the prediabetes stage.
    Matched MeSH terms: Discriminant Analysis
  15. Mohd Khairuddin I, Sidek SN, P P Abdul Majeed A, Mohd Razman MA, Ahmad Puzi A, Md Yusof H
    PeerJ Comput Sci, 2021;7:e379.
    PMID: 33817026 DOI: 10.7717/peerj-cs.379
    Electromyography (EMG) signal is one of the extensively utilised biological signals for predicting human motor intention, which is an essential element in human-robot collaboration platforms. Studies on motion intention prediction from EMG signals have often been concentrated on either classification and regression models of muscle activity. In this study, we leverage the information from the EMG signals, to detect the subject's intentions in generating motion commands for a robot-assisted upper limb rehabilitation platform. The EMG signals are recorded from ten healthy subjects' biceps muscle, and the movements of the upper limb evaluated are voluntary elbow flexion and extension along the sagittal plane. The signals are filtered through a fifth-order Butterworth filter. A number of features were extracted from the filtered signals namely waveform length (WL), mean absolute value (MAV), root mean square (RMS), standard deviation (SD), minimum (MIN) and maximum (MAX). Several different classifiers viz. Linear Discriminant Analysis (LDA), Logistic Regression (LR), Decision Tree (DT), Support Vector Machine (SVM) and k-Nearest Neighbour (k-NN) were investigated on its efficacy to accurately classify the pre-intention and intention classes based on the significant features identified (MIN and MAX) via Extremely Randomised Tree feature selection technique. It was observed from the present investigation that the DT classifier yielded an excellent classification with a classification accuracy of 100%, 99% and 99% on training, testing and validation dataset, respectively based on the identified features. The findings of the present investigation are non-trivial towards facilitating the rehabilitation phase of patients based on their actual capability and hence, would eventually yield a more active participation from them.
    Matched MeSH terms: Discriminant Analysis
  16. Rashid M, Bari BS, Hasan MJ, Razman MAM, Musa RM, Ab Nasir AF, et al.
    PeerJ Comput Sci, 2021;7:e374.
    PMID: 33817022 DOI: 10.7717/peerj-cs.374
    Brain-computer interface (BCI) is a viable alternative communication strategy for patients of neurological disorders as it facilitates the translation of human intent into device commands. The performance of BCIs primarily depends on the efficacy of the feature extraction and feature selection techniques, as well as the classification algorithms employed. More often than not, high dimensional feature set contains redundant features that may degrade a given classifier's performance. In the present investigation, an ensemble learning-based classification algorithm, namely random subspace k-nearest neighbour (k-NN) has been proposed to classify the motor imagery (MI) data. The common spatial pattern (CSP) has been applied to extract the features from the MI response, and the effectiveness of random forest (RF)-based feature selection algorithm has also been investigated. In order to evaluate the efficacy of the proposed method, an experimental study has been implemented using four publicly available MI dataset (BCI Competition III dataset 1 (data-1), dataset IIIA (data-2), dataset IVA (data-3) and BCI Competition IV dataset II (data-4)). It was shown that the ensemble-based random subspace k-NN approach achieved the superior classification accuracy (CA) of 99.21%, 93.19%, 93.57% and 90.32% for data-1, data-2, data-3 and data-4, respectively against other models evaluated, namely linear discriminant analysis, support vector machine, random forest, Naïve Bayes and the conventional k-NN. In comparison with other classification approaches reported in the recent studies, the proposed method enhanced the accuracy by 2.09% for data-1, 1.29% for data-2, 4.95% for data-3 and 5.71% for data-4, respectively. Moreover, it is worth highlighting that the RF feature selection technique employed in the present study was able to significantly reduce the feature dimension without compromising the overall CA. The outcome from the present study implies that the proposed method may significantly enhance the accuracy of MI data classification.
    Matched MeSH terms: Discriminant Analysis
  17. Chong JA, Syed Mohamed AMF, Marizan Nor M, Pau A
    J Forensic Sci, 2020 Nov;65(6):2000-2007.
    PMID: 32692413 DOI: 10.1111/1556-4029.14507
    Although there is clinical applicability of the palatal rugae as an identification tool in forensic odontology, controversy exists whether the palatal rugae patterns are stable or variable. The greater the genetic component, the higher the probability that palatal rugae patterns are stable. The aim of this study was to compare the palatal rugae morphology between full siblings and the proportion of variability due to genetic component. This cross-sectional study was conducted on digital models of 162 siblings aged 15-30 years old. The palatal rugae patterns were assessed with Thomas and Kotze (1983) classification using Geomagic Studio software (3D Systems, Rock Hill, SC). The palatal rugae morphology between siblings showed significantly similar characteristics for total number of left rugae (p = 0.001), left primary rugae (p = 0.017), secondary rugae for right (p = 0.024) and left sides (p = 0.001), right straight rugae (p = 0.010), and right convergent rugae (p = 0.005) accounting for at least 6.25%-12.8% of the variability due to heredity. Despite the similarities found, the palatal rugae patterns showed significant differences between siblings of at least 46.9% (p = 0.001). Zero heritability was found in 9 of the 14 rugae patterns. Meanwhile, total number of rugae, primary, backward, and convergent rugae showed moderate heritability (h2  > 0.3) and total number of secondary rugae showed high heritability (h2  > 0.6). In conclusion, despite the individuality characteristics, an appreciable hereditary component is observed with significant similarities found between sibling pairs and the palatal rugae patterns were both environmentally and genetically influenced.
    Matched MeSH terms: Discriminant Analysis
  18. Phatsara M, Das S, Laowatthanaphong S, Tuamsuk P, Mahakkanukrauh P
    Clin Ter, 2016 May-Jun;167(3):72-6.
    PMID: 27424506 DOI: 10.7417/CT.2016.1929
    BACKGROUND: This study was carried out to evaluate the accuracy of sex estimation by discriminant analysis and stepwise discriminant analysis equations generated from metatarsal bones in a Thai population.
    MATERIAL AND METHODS: The testing samples utilized in this study consisted of 50 skeletons (25 males and 25 females) obtained from the Khon Kaen University Skeletal Collection, Department of Anatomy, Faculty of Medicine, Khon Kaen University. Seven measurements of metatarsal bones were measured in centimeters, using either a mini-osteometric board (MOB) or a sliding caliper. The values measured from the Khon Kaen Skeletal Collection were used to determine the accuracy and applicability of sex determination, as predicted by Y1-Y6 equations which were generated from a Chiang Mai Skeletal Collection.
    RESULTS: The percentage of sex determination accuracies predicted from the Y1-Y6 equations demonstrated accuracy rates of 80-95.6.
    CONCLUSIONS: The Chiang Mai sex determination equations, generated from metatarsal bones by discriminant analysis (Y1-Y3) and stepwise discriminant analysis (Y4-Y6), demonstrated high accuracy rates of prediction, suggesting that these equations may be useful for sex determination within the Thai population.
    KEYWORDS: Foot; Metatarsal bones; Sex determination; Thailand
    Matched MeSH terms: Discriminant Analysis
  19. Hussain H, Yusoff MK, Ramli MF, Abd Latif P, Juahir H, Zawawi MA
    Pak J Biol Sci, 2013 Nov 15;16(22):1524-30.
    PMID: 24511695
    Nitrate-nitrogen leaching from agricultural areas is a major cause for groundwater pollution. Polluted groundwater with high levels of nitrate is hazardous and cause adverse health effects. Human consumption of water with elevated levels of NO3-N has been linked to the infant disorder methemoglobinemia and also to non-Hodgkin's disease lymphoma in adults. This research aims to study the temporal patterns and source apportionment of nitrate-nitrogen leaching in a paddy soil at Ladang Merdeka Ismail Mulong in Kelantan, Malaysia. The complex data matrix (128 x 16) of nitrate-nitrogen parameters was subjected to multivariate analysis mainly Principal Component Analysis (PCA) and Discriminant Analysis (DA). PCA extracted four principal components from this data set which explained 86.4% of the total variance. The most important contributors were soil physical properties confirmed using Alyuda Forecaster software (R2 = 0.98). Discriminant analysis was used to evaluate the temporal variation in soil nitrate-nitrogen on leaching process. Discriminant analysis gave four parameters (hydraulic head, evapotranspiration, rainfall and temperature) contributing more than 98% correct assignments in temporal analysis. DA allowed reduction in dimensionality of the large data set which defines the four operating parameters most efficient and economical to be monitored for temporal variations. This knowledge is important so as to protect the precious groundwater from contamination with nitrate.
    Matched MeSH terms: Discriminant Analysis
  20. Mustapha A, Aris AZ, Ramli MF, Juahir H
    ScientificWorldJournal, 2012;2012:294540.
    PMID: 22919302 DOI: 10.1100/2012/294540
    Robust statistical tools were applied on the water quality datasets with the aim of determining the most significance parameters and their contribution towards temporal water quality variation. Surface water samples were collected from four different sampling points during dry and wet seasons and analyzed for their physicochemical constituents. Discriminant analysis (DA) provided better results with great discriminatory ability by using five parameters with (P < 0.05) for dry season affording more than 96% correct assignation and used five and six parameters for forward and backward stepwise in wet season data with P-value (P < 0.05) affording 68.20% and 82%, respectively. Partial correlation results revealed that there are strong (r(p) = 0.829) and moderate (r(p) = 0.614) relationships between five-day biochemical oxygen demand (BOD(5)) and chemical oxygen demand (COD), total solids (TS) and dissolved solids (DS) controlling for the linear effect of nitrogen in the form of ammonia (NH(3)) and conductivity for dry and wet seasons, respectively. Multiple linear regression identified the contribution of each variable with significant values r = 0.988, R(2) = 0.976 and r = 0.970, R(2) = 0.942 (P < 0.05) for dry and wet seasons, respectively. Repeated measure t-test confirmed that the surface water quality varies significantly between the seasons with significant value P < 0.05.
    Matched MeSH terms: Discriminant Analysis
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