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Linear Discriminant Analysis (linear + discriminant_analysis)
Selected AbstractsFeature Extraction for Traffic Incident Detection Using Wavelet Transform and Linear Discriminant AnalysisCOMPUTER-AIDED CIVIL AND INFRASTRUCTURE ENGINEERING, Issue 4 2000A. Samant To eliminate false alarms, an effective traffic incident detection algorithm must be able to extract incident-related features from the traffic patterns. A robust feature-extraction algorithm also helps reduce the dimension of the input space for a neural network model without any significant loss of related traffic information, resulting in a substantial reduction in the network size, the effect of random traffic fluctuations, the number of required training samples, and the computational resources required to train the neural network. This article presents an effective traffic feature-extraction model using discrete wavelet transform (DWT) and linear discriminant analysis (LDA). The DWT is first applied to raw traffic data, and the finest resolution coefficients representing the random fluctuations of traffic are discarded. Next, LDA is employed to the filtered signal for further feature extraction and reducing the dimensionality of the problem. The results of LDA are used as input to a neural network model for traffic incident detection. [source] Combined counseling and bupropion therapy for smoking cessation: identification of outcome predictorsDRUG DEVELOPMENT RESEARCH, Issue 3 2006Maria Caterina Grassi Abstract Because some smoking-induced pathologies improve upon discontinuation, strategies have been developed to help smokers quit. The aim of this study was to measure the rate of smokers still abstinent one year after one cycle of a six-week group counseling given alone or in combination with a seven-week period of daily administration of bupropion. We also evaluated the predictor validity of nicotine dependence intensity at enrollment, administering both the Fageström Tolerance Questionnaire (FTQ) and the Severity of Dependence Scale (SDS). Visual Analogue Scale (VAS), to measure the intensity of "smoke craving," was also administered. Two hundred twenty-nine subjects trying to quit smoking were enrolled. Bupropion therapy was accepted by 110 subjects, but only 50 completed the 7-week cycle of therapy. Abstinence rates at one year were 68.0 and 56.6%, respectively, in the group that used bupropion for the scheduled 7 weeks and in the group that discontinued bupropion, and 35.3% in the group with counseling therapy alone. SDS (but not FTQ) scores at enrollment, VAS values for craving at the end of the program, and bupropion therapy were the variables selected by Linear Discriminant Analysis to assign subjects to the Smoker or Non-smoker group, with a global correctness of 70.9%. In conclusion, the efficacy of bupropion largely depends upon its interaction with psychological factors, such as the level of nicotine dependence, craving for nicotine, and the subject's commitment to quit smoking. Drug Dev. Res. 67:271,279, 2006. © 2006 Wiley-Liss, Inc. [source] Impact of warming and timing of snow melt on soil microarthropod assemblages associated with Dryas- dominated plant communities on SvalbardECOGRAPHY, Issue 1 2006Rebecca Dollery Open Top Chambers (OTCs) were used to measure impacts of predicted global warming on the structure of the invertebrate community of a Dryas octopetala heath in West Spitsbergen. Results from the OTC experiment were compared with natural variation in invertebrate community structure along a snowmelt transect through similar vegetation up the adjacent hillside. Changes along this transect represent the natural response of the invertebrate community to progressively longer and potentially warmer and drier growing seasons. Using MANOVA, ANOVA, Linear Discriminant Analysis and ,2 tests, significant differences in community composition were found between OTCs and controls and among stations along the transect. Numbers of cryptostigmatic and predatory mites tended to be higher in the warmer OTC treatment but numbers of the aphid Acyrthosiphon svalbardicum, hymenopterous parasitoids, Symphyta larvae, and weevils were higher in control plots. Most Collembola, including Hypogastrura tullbergi, Lepidocyrtus lignorum and Isotoma anglicana, followed a similar trend to the aphid, but Folsomia bisetosa was more abundant in the OTC treatment. Trends along the transect showed clear parallels with the OTC experiment. However, mite species, particularly Diapterobates notatus, tended to increase in numbers under warming, with several species collectively increasing at the earlier exposed transect stations. Overall, the results suggest that the composition and structure of Arctic invertebrate communities associated with Dryas will change significantly under global warming. [source] Classification of GC-MS measurements of wines by combining data dimension reduction and variable selection techniquesJOURNAL OF CHEMOMETRICS, Issue 8 2008Davide Ballabio Abstract Different classification methods (Partial Least Squares Discriminant Analysis, Extended Canonical Variates Analysis and Linear Discriminant Analysis), in combination with variable selection approaches (Forward Selection and Genetic Algorithms), were compared, evaluating their capabilities in the geographical discrimination of wine samples. Sixty-two samples were analysed by means of dynamic headspace gas chromatography mass spectrometry (HS-GC-MS) and the entire chromatographic profile was considered to build the dataset. Since variable selection techniques pose a risk of overfitting when a large number of variables is used, a method for coupling data dimension reduction and variable selection was proposed. This approach compresses windows of the original data by retaining only significant components of local Principal Component Analysis models. The subsequent variable selection is then performed on these locally derived score variables. The results confirmed that the classification models achieved on the reduced data were better than those obtained on the entire chromatographic profile, with the exception of Extended Canonical Variates Analysis, which gave acceptable models in both cases. Copyright © 2008 John Wiley & Sons, Ltd. [source] Microanatomical diversity of the humerus and lifestyle in lissamphibiansACTA ZOOLOGICA, Issue 2 2009Aurore Canoville Abstract A study of body size and the compactness profile parameters of the humerus of 37 species of lissamphibians demonstrates a relationship between lifestyle (aquatic, amphibious or terrestrial) and bone microstructure. Multiple linear regressions and variance partitioning with Phylogenetic eigenVector Regressions reveal an ecological and a phylogenetic signal in some body size and compactness profile parameters. Linear discriminant analyses segregate the various lifestyles (aquatic vs. amphibious or terrestrial) with a success rate of up to 89.2%. The models built from data on the humerus discriminate aquatic taxa relatively well from the other taxa. However, like previous models built from data on the radius of amniotes or on the femur of lissamphibians, the new models do not discriminate amphibious taxa from terrestrial taxa on the basis of body size or compactness profile data. To make our inference method accessible, spreadsheets (see supplementary material on the website), which allow anyone to infer a lissamphibian lifestyle solely from body size and bone compactness parameters, were produced. No such easy implementation of habitat inference models is found in earlier papers on this topic. [source] Forecasting migration of cereal aphids (Hemiptera: Aphididae) in autumn and springJOURNAL OF APPLIED ENTOMOLOGY, Issue 5 2009A. M. Klueken Abstract The migration of cereal aphids and the time of their arrival on winter cereal crops in autumn and spring are of particular importance for plant disease (e.g. barley yellow dwarf virus infection) and related yield losses. In order to identify days with migration potentials in autumn and spring, suction trap data from 29 and 45 case studies (locations and years), respectively, were set-off against meteorological parameters, focusing on the early immigration periods in autumn (22 September to 1 November) and spring (1 May to 9 June). The number of cereal aphids caught in a suction trap increased with increasing temperature, global radiation and duration of sunshine and decreased with increasing precipitation, relative humidity and wind speed. According to linear regression analyses, the temperature, global radiation and wind speed were most frequently and significantly associated with migration, suggesting that they have a major impact on flight activity. For subsequent model development, suction trap catches from different case studies were pooled and binarily classified as days with or without migration as defined by a certain number of migrating cereal aphids. Linear discriminant analyses of several predictor variables (assessed during light hours of a given day) were then performed based on the binary response variables. Three models were used to predict days with suction trap catches ,1, ,4 or ,10 migrating cereal aphids in autumn. Due to the predominance of Rhopalosiphum padi individuals (99.3% of total cereal aphid catch), no distinction between species (R. padi and Sitobion avenae) was made in autumn. As the suction trap catches were lower and species dominance changed in spring, three further models were developed for analysis of all cereal aphid species, R. padi only, and Metopolophium dirhodum and S. avenae combined in spring. The empirical, cross-classification and receiver operating characteristic analyses performed for model validation showed different levels of prediction accuracy. Additional datasets selected at random before model construction and parameterization showed that predictions by the six migration models were 33,81% correct. The models are useful for determining when to start field evaluations. Furthermore, they provide information on the size of the migrating aphid population and, thus, on the importance of immigration for early aphid population development in cereal crops in a given season. [source] The Chorus Song of Cooperatively Breeding Laughing Kookaburras (Coraciiformes, Halcyonidae: Dacelo novaeguineae): Characterization and Comparison Among GroupsETHOLOGY, Issue 1 2004Myron C. Baker I studied vocalizations of laughing kookaburras in Western Australia by sampling the laugh-song choruses of eight different groups and the isolated vocalizations of four individuals of this cooperatively breeding species. These data provided a description of the acoustic structure of vocal elements of the laugh song and a between-group comparison of laugh choruses. I identified six different categories of syllables: some syllable types appear graded with modal forms predominating. Group choruses were produced by several birds vocalizing simultaneously, usually following initiation by a single bird producing one of two typical introductory sets of syllable repetitions. Statistical analyses of samples of mid-chorus vocalizations of kookaburra groups revealed that the samples from each of the eight groups clustered in principal coordinate space and the group clusters segregated from each other to a significant degree. Linear discriminant analysis assigned 24 of the 25 samples to their correct groups. These results suggest that there is group-specific vocal signature information in the laugh chorus. The within-group similarity and between-group differences may result from heritable variation or from imitation learning. Observations of the contexts of the laugh chorus vocalization supported the interpretations of others that the chorus song is involved in group advertisement of territory occupancy and in defense of the communal borders. [source] Linear discriminant analysis in network traffic modellingINTERNATIONAL JOURNAL OF COMMUNICATION SYSTEMS, Issue 1 2006Bing-Yi Zhang Abstract It is difficult to give an accurate judgement of whether the traffic model fit the actual traffic. The traditional method is to compare the Hurst parameter, data histogram and autocorrelation function. The method of comparing Hurst parameter cannot give exact results and judgement. The method of comparing data histogram and autocorrelation only gives a qualitative judgement. Based on linear discriminant analysis we proposed a novel arithmetic. Utilizing this arithmetic we analysed some sets of data with large and little differences. We also analysed some sets of data generated by network simulator. The analysis result is accurate. Comparing with traditional method, this arithmetic is useful and can conveniently give an accurate judgement for complex network traffic trace. Copyright © 2005 John Wiley & Sons, Ltd. [source] Gene diversity in a fragmented population of Briza media: grassland continuity in a landscape contextJOURNAL OF ECOLOGY, Issue 1 2006HONOR C. PRENTICE Summary 1We investigated patterns of allozyme variation in demes of the grass Briza media in semi-natural grassland fragments within a mosaic agricultural landscape on the Baltic island of Öland. In the study area, Briza is both a characteristic species of old pastures and an early colonizer of young grasslands developing on previously forested or arable sites. 2Generalized linear models revealed that descriptors of both present landscape structure and past grassland history are significant determinants of genetic variation in the Briza demes. Genetic structure and levels of within-deme diversity are influenced by the size of grassland fragments, the type of habitat surrounding the grasslands, the size/spatial extent of the demes, the geographic position of the demes and the historical continuity of the grassland fragments. 3Gene diversity (H) was higher in demes from grassland polygons with a high proportion of adjacent grassland, higher in the more extensive demes, and decreased northwards within the study area. 4The negative association between the inbreeding coefficient (FIS) and grassland continuity is interpreted in terms of a two-stage colonization process: recruitment into young grasslands leads initially to spatial patchiness, but subsequent selection in maturing pastures occurs within an increasingly uniform and dense sward. 5Despite a weak overall genetic structure (as indicated by Bayesian cluster analysis) the between-deme FST was significant. Linear discriminant analysis of within-deme allele frequencies grouped the demes according to the age and previous land-use history of their grassland polygons. The convergence of the allele frequency profiles in the younger grasslands towards those of the old grasslands is consistent with convergence of selective regimes as pastures mature towards an increasingly uniform, dense sward and characteristic species assemblage. 6The genetic composition of demes of a grassland species appears to be influenced by the process of plant community convergence during grassland development , complementing the recent finding that convergence of species composition in experimental assemblages of grassland plants is dependent on the genotypic composition of the component species. [source] Discrimination and classification of adulterants in maple syrup with the use of infrared spectroscopic techniquesJOURNAL OF THE SCIENCE OF FOOD AND AGRICULTURE, Issue 5 2002M Paradkar Abstract Food adulteration is a profit-making business for some unscrupulous manufacturers. Maple syrup is a soft target for adulterators owing to its simplicity of chemical composition. The use of infrared spectroscopic techniques such as Fourier transform infrared (FTIR) and near-infrared (NIR) as a tool to detect adulterants such as cane and beet invert syrups as well as cane and beet sugar solutions in maple syrup was investigated. The FTIR spectra of adulterated samples were characterised and the regions of 800,1200,cm,1 (carbohydrates) and 1200,1800 and 2800,3200,cm,1 (carbohydrates, carboxylic acids and amino acids) were used for detection. The NIR spectral region between 1100 and 1660,nm was used for analysis. Linear discriminant analysis (LDA) and canonical variate analysis (CVA) were used for discriminant analysis, while partial least squares (PLS) and principal component regression (PCR) were used for quantitative analysis. FTIR was more accurate in predicting adulteration using the two different regions (R2,>,0.93 and 0.98) compared with NIR (R2,>,0.93). Classification and quantification of adulterants in maple syrup show that both NIR and FTIR can be used for detecting adulterants such as pure beet and cane sugar solutions, but FTIR was superior to NIR in detecting invert syrups. © 2002 Society of Chemical Industry [source] Discriminant analysis of autofluorescence spectra for classification of oral lesions in vivoLASERS IN SURGERY AND MEDICINE, Issue 5 2009J.L. Jayanthi MSc, MPhil Abstract Background and Objectives Low survival rate of individuals with oral cancer emphasize the significance of early detection and treatment. Optical spectroscopic techniques are under various stages of development for diagnosis of epithelial neoplasm. This study evaluates the potential of a multivariate statistical algorithm to classify oral mucosa from autofluorescence spectral features recorded in vivo. Study Design/Methods Autofluorescence spectra were recorded in a clinical trial from 15 healthy volunteers and 34 patients with diode laser excitation (404,nm) and pre-processed by normalization, mean-scaling and its combination. Linear discriminant analysis (LDA) based on leave-one-out (LOO) method of cross validation was performed on spectral data for tissue characterization. The sensitivity and specificity were determined for different lesion pairs from the scatter plot of discriminant function scores. Results Autofluorescence spectra of healthy volunteers consists of a broad emission at 500,nm that is characteristic of endogenous fluorophores, whereas in malignant lesions three additional peaks are observed at 635, 685, and 705,nm due to the accumulation of porphyrins in oral lesions. It was observed that classification design based on discriminant function scores obtained by LDA-LOO method was able to differentiate pre-malignant dysplasia from squamous cell carcinoma (SCC), benign hyperplasia from dysplasia and hyperplasia from normal with overall sensitivities of 86%, 78%, and 92%, and specificities of 90%, 100%, and 100%, respectively. Conclusions The application of LDA-LOO method on the autofluorescence spectra recorded during a clinical trial in patients was found suitable to discriminate oral mucosal alterations during tissue transformation towards malignancy with improved diagnostic accuracies. Lasers Surg. Med. 41:345,352, 2009. © 2009 Wiley-Liss, Inc. [source] Feature Extraction for Traffic Incident Detection Using Wavelet Transform and Linear Discriminant AnalysisCOMPUTER-AIDED CIVIL AND INFRASTRUCTURE ENGINEERING, Issue 4 2000A. Samant To eliminate false alarms, an effective traffic incident detection algorithm must be able to extract incident-related features from the traffic patterns. A robust feature-extraction algorithm also helps reduce the dimension of the input space for a neural network model without any significant loss of related traffic information, resulting in a substantial reduction in the network size, the effect of random traffic fluctuations, the number of required training samples, and the computational resources required to train the neural network. This article presents an effective traffic feature-extraction model using discrete wavelet transform (DWT) and linear discriminant analysis (LDA). The DWT is first applied to raw traffic data, and the finest resolution coefficients representing the random fluctuations of traffic are discarded. Next, LDA is employed to the filtered signal for further feature extraction and reducing the dimensionality of the problem. The results of LDA are used as input to a neural network model for traffic incident detection. [source] An Adaptive Conjugate Gradient Neural Network,Wavelet Model for Traffic Incident DetectionCOMPUTER-AIDED CIVIL AND INFRASTRUCTURE ENGINEERING, Issue 4 2000H. Adeli Artificial neural networks are known to be effective in solving problems involving pattern recognition and classification. The traffic incident-detection problem can be viewed as recognizing incident patterns from incident-free patterns. A neural network classifier has to be trained first using incident and incident-free traffic data. The dimensionality of the training input data is high, and the embedded incident characteristics are not easily detectable. In this article we present a computational model for automatic traffic incident detection using discrete wavelet transform, linear discriminant analysis, and neural networks. Wavelet transform and linear discriminant analysis are used for feature extraction, denoising, and effective preprocessing of data before an adaptive neural network model is used to make the traffic incident detection. Simulated as well as actual traffic data are used to test the model. For incidents with a duration of more than 5 minutes, the incident-detection model yields a detection rate of nearly 100 percent and a false-alarm rate of about 1 percent for two- or three-lane freeways. [source] Inducing safer oblique trees without costsEXPERT SYSTEMS, Issue 4 2005Sunil Vadera Abstract: Decision tree induction has been widely studied and applied. In safety applications, such as determining whether a chemical process is safe or whether a person has a medical condition, the cost of misclassification in one of the classes is significantly higher than in the other class. Several authors have tackled this problem by developing cost-sensitive decision tree learning algorithms or have suggested ways of changing the distribution of training examples to bias the decision tree learning process so as to take account of costs. A prerequisite for applying such algorithms is the availability of costs of misclassification. Although this may be possible for some applications, obtaining reasonable estimates of costs of misclassification is not easy in the area of safety. This paper presents a new algorithm for applications where the cost of misclassifications cannot be quantified, although the cost of misclassification in one class is known to be significantly higher than in another class. The algorithm utilizes linear discriminant analysis to identify oblique relationships between continuous attributes and then carries out an appropriate modification to ensure that the resulting tree errs on the side of safety. The algorithm is evaluated with respect to one of the best known cost-sensitive algorithms (ICET), a well-known oblique decision tree algorithm (OC1) and an algorithm that utilizes robust linear programming. [source] Linear models for minimizing misclassification costs in bankruptcy predictionINTELLIGENT SYSTEMS IN ACCOUNTING, FINANCE & MANAGEMENT, Issue 3 2001Sudhir Nanda This paper illustrates how a misclassification cost matrix can be incorporated into an evolutionary classification system for bankruptcy prediction. Most classification systems for predicting bankruptcy have attempted to minimize misclassifications. The minimizing misclassification approach assumes that Type I and Type II error costs for misclassifications are equal. There is evidence that these costs are not equal and incorporating costs into the classification systems can lead to better and more desirable results. In this paper, we use the principles of evolution to develop and test a genetic algorithm (GA) based approach that incorporates the asymmetric Type I and Type II error costs. Using simulated and real-life bankruptcy data, we compare the results of our proposed approach with three linear approaches: statistical linear discriminant analysis (LDA), a goal programming approach, and a GA-based classification approach that does not incorporate the asymmetric misclassification costs. Our results indicate that the proposed approach, incorporating Type I and Type II error costs, results in lower misclassification costs when compared to LDA and GA approaches that do not incorporate misclassification costs. Copyright © 2001 John Wiley & Sons, Ltd. [source] Linear discriminant analysis in network traffic modellingINTERNATIONAL JOURNAL OF COMMUNICATION SYSTEMS, Issue 1 2006Bing-Yi Zhang Abstract It is difficult to give an accurate judgement of whether the traffic model fit the actual traffic. The traditional method is to compare the Hurst parameter, data histogram and autocorrelation function. The method of comparing Hurst parameter cannot give exact results and judgement. The method of comparing data histogram and autocorrelation only gives a qualitative judgement. Based on linear discriminant analysis we proposed a novel arithmetic. Utilizing this arithmetic we analysed some sets of data with large and little differences. We also analysed some sets of data generated by network simulator. The analysis result is accurate. Comparing with traditional method, this arithmetic is useful and can conveniently give an accurate judgement for complex network traffic trace. Copyright © 2005 John Wiley & Sons, Ltd. [source] A comparative study of the egg morphology in four species of Eubothrium (Cestoda: Pseudophyllidea) with comments on their early developmentINVERTEBRATE BIOLOGY, Issue 1 2006Roman Kuchta Abstract. Freshly released eggs from four species of the cestode Eubothrium (Eubothrium crassum, Eubothrium fragile, Eubothrium rugosum, and Eubothrium salvelini) were subjected to morphological and morphometric analysis. The eggs of the two freshwater species, E. rugosum and E. salvelini, were ovoid with a lobed embryophore whereas the eggs of the two marine species, E. crassum and E. fragile, were more circular with a smooth embryophore. However, the morphological differences between species were not readily evident to permit their clear distinction from one another. To discriminate species, a forward stepwise linear discriminant analysis, using six of the seven measured metric characters made on the eggs, was used, which gave 100% correct classification of two species, E. rugosum and E. salvelini, and a high proportion of correct classification for E. crassum (98%) and E. fragile (83%). Of the latter two species, one specimen of E. crassum and five specimens of E. fragile were misclassified between the respective groups. The principal characters used in the classification of the species were the width of the egg, the length of the mediolateral hooks, and the width of the oncosphere. To provide more information on the life cycle of each species, the eggs were used in a series of infection trials to identify appropriate intermediate hosts. Experimental infections with freshwater copepods were successful when exposed to the eggs of E. salvelini, partially successful when exposed to the eggs of marine E. crassum with 10% of the copepods becoming infected, but no infections were obtained when the eggs of E. fragile were used. [source] Burnout and physical and mental health among Swedish healthcare workersJOURNAL OF ADVANCED NURSING, Issue 1 2008Ulla Peterson Abstract Title.,Burnout and physical and mental health among Swedish healthcare workers Aim., This paper is a report of a study to investigate how burnout relates to self-reported physical and mental health, sleep disturbance, memory and lifestyle factors. Background., Previous research on the possible relationship between lifestyle factors and burnout has yielded somewhat inconsistent results. Most of the previous research on possible health implications of burnout has focused on its negative impact on mental health. Exhaustion appears to be the most obvious manifestation of burnout, which also correlates positively with workload and with other stress-related outcomes. Method., A cross-sectional study was conducted, using questionnaires sent to all employees in a Swedish County Council (N = 6118) in 2002. The overall response rate was 65% (n = 3719). A linear discriminant analysis was used to look for different patterns of health indicators and lifestyle factors in four burnout groups (non-burnout, disengaged, exhausted and burnout). Results., Self-reported depression, anxiety, sleep disturbance, memory impairment and neck- and back pain most clearly discriminated burnout and exhausted groups from disengaged and non-burnout groups. Self-reported physical exercise and alcohol consumption played a minor role in discriminating between burnout and non-burnout groups, while physical exercise discriminated the exhausted from the disengaged group. Conclusion., Employees with burnout had most symptoms, compared with those who experienced only exhaustion, disengagement from work or no burnout, and the result underlines the importance of actions taken to prevent and combat burnout. [source] Partial least squares for discriminationJOURNAL OF CHEMOMETRICS, Issue 3 2003Matthew Barker Abstract Partial least squares (PLS) was not originally designed as a tool for statistical discrimination. In spite of this, applied scientists routinely use PLS for classification and there is substantial empirical evidence to suggest that it performs well in that role. The interesting question is: why can a procedure that is principally designed for overdetermined regression problems locate and emphasize group structure? Using PLS in this manner has heurestic support owing to the relationship between PLS and canonical correlation analysis (CCA) and the relationship, in turn, between CCA and linear discriminant analysis (LDA). This paper replaces the heuristics with a formal statistical explanation. As a consequence, it will become clear that PLS is to be preferred over PCA when discrimination is the goal and dimension reduction is needed. Copyright © 2003 John Wiley & Sons, Ltd. [source] QSAR model for alignment-free prediction of human breast cancer biomarkers based on electrostatic potentials of protein pseudofolding HP-lattice networksJOURNAL OF COMPUTATIONAL CHEMISTRY, Issue 16 2008Santiago Vilar Abstract Network theory allows relationships to be established between numerical parameters that describe the molecular structure of genes and proteins and their biological properties. These models can be considered as quantitative structure,activity relationships (QSAR) for biopolymers. The work described here concerns the first QSAR model for 122 proteins that are associated with human breast cancer (HBC), as identified experimentally by Sjöblom et al. (Science 2006, 314, 268) from over 10,000 human proteins. In this study, the 122 proteins related to HBC (HBCp) and a control group of 200 proteins that are not related to HBC (non-HBCp) were forced to fold in an HP lattice network. From these networks a series of electrostatic potential parameters (,k) was calculated to describe each protein numerically. The use of ,k as an entry point to linear discriminant analysis led to a QSAR model to discriminate between HBCp and non-HBCp, and this model could help to predict the involvement of a certain gene and/or protein in HBC. In addition, validation procedures were carried out on the model and these included an external prediction series and evaluation of an additional series of 1000 non-HBCp. In all cases good levels of classification were obtained with values above 80%. This study represents the first example of a QSAR model for the computational chemistry inspired search of potential HBC protein biomarkers. © 2008 Wiley Periodicals, Inc. J Comput Chem 2008 [source] Applying pattern recognition methods plus quantum and physico-chemical molecular descriptors to analyze the anabolic activity of structurally diverse steroidsJOURNAL OF COMPUTATIONAL CHEMISTRY, Issue 3 2008Yoanna María Alvarez-Ginarte Abstract The great cost associated with the development of new anabolic,androgenic steroid (AASs) makes necessary the development of computational methods that shorten the drug discovery pipeline. Toward this end, quantum, and physicochemical molecular descriptors, plus linear discriminant analysis (LDA) were used to analyze the anabolic/androgenic activity of structurally diverse steroids and to discover novel AASs, as well as also to give a structural interpretation of their anabolic,androgenic ratio (AAR). The obtained models are able to correctly classify 91.67% (86.27%) of the AASs in the training (test) sets, respectively. The results of predictions on the 10% full-out cross-validation test also evidence the robustness of the obtained model. Moreover, these classification functions are applied to an "in house" library of chemicals, to find novel AASs. Two new AASs are synthesized and tested for in vivo activity. Although both AASs are less active than some commercially AASs, this result leaves a door open to a virtual variational study of the structure of the two compounds, to improve their biological activity. The LDA-assisted QSAR models presented here, could significantly reduce the number of synthesized and tested AASs, as well as could increase the chance of finding new chemical entities with higher AAR. © 2007 Wiley Periodicals, Inc. J Comput Chem, 2008 [source] Using interpubic distance for sexing manakins in the fieldJOURNAL OF FIELD ORNITHOLOGY, Issue 1 2010Chase D. Mendenhall ABSTRACT Field methods for determining the sex of birds are often limited due to morphometric overlap between sexes, intermediate plumages, seasonality, and reliance on subjective age classification. Interpubic distance, characterized in birds as the distance between the distal ends of the pubic bones, has not been formally tested as a method for determining the sex of birds, despite references among parrot breeders and the frequent use of analogous measurements in mammals. We developed a harmless and easily performed field method for measuring interpubic distance in studies involving bird capture, and compared the interpubic distances of known sex White-ruffed Manakins (Corapipo altera), Orange-collared Manakins (Manacus aurantiacus), and Blue-crowned Manakins (Lepidothrix coronata) to evaluate the possible use of this measurement to determine sex. Using interpubic distance ranges based on 85% confidence intervals where overlap existed between sexes, the sex of 92.8,100% of all manakins in our study was accurately determined with no misclassification. Interpubic distance performed better than plumage-based methods that sexed 74.0% of all individuals and misclassified 1.5%. Using linear discriminant analysis, we developed classification equations that allowed us to accurately determine the sex of all individuals with 100% accuracy using mass and interpubic distance. Additionally, we compared the interpubic distances of female White-ruffed Manakins to evaluate the potential to determine age and reproductive status. Despite an apparent relationship between interpubic distance, age and reproductive status, we concluded that interpubic distance has limited use for determining age and reproductive status due to extensive overlap (31.6,100%), but shows potential in other applications. Based on these results, we endorse the use of interpubic distance to determine the sex of manakins. We encourage further study to develop additional classification equations using different morphometric measurements and to test the efficacy of interpubic distance to determine sex in other bird species. RESUMEN Los métodos del campo para distinguir el sexo de aves son limitados a causa de traslapes de medidas mórfometricas extremas entre sexos, plumajes intermedios, diferencias temporales y/o dependencia en clasificación sujeto de la edad. Distancia interpúbica, caracterizada en aves como la distancia entre los puntos distales de los huesos púbicos, no ha sido formalmente probada como un método para distinguir el sexo de las aves, a pesar de referencias por criadores de loros y uso de métodos similares en mamíferos. Diseñamos un método del campo rápido y sencillo que no tiene riesgo del daño para sacar la distancia interpúbica en estudios que capturan aves. Comparamos la distancia interpúbica de individuos de sexo conocido de Corapipo altera, Manacus aurantiacus, y Lepidothrix coronata para probar el método. Clasificamos correctamente el sexo de 92.8,100% de todos los individuos en este estudio por rangos determinados a través de intérvalos de confianza de 85%. La distancia interpúbica funcionó mejor que un método basado en plumaje, el cual que distinguió el sexo correcto de 74.0% pero falló en clasificar el sexo de 1.5% de los individuos estudiados. Usamos el análisis de discriminación linear para determinar el poder predictivo de la distancia interpúbica, longitud del ala y masa e hicimos ecuaciones de clasificación que distinguieron sexo con un 100% de éxito usando solo masa y distancia interpúbica. Además, comparamos distancia interpúbica de las hembras de C. altera para evaluar el potencial de distinguir edad y estadio reproductivo. A pesar de existir una conexión entre distancia interpúbica, edad y estadio reproductivo, concluimos que la distancia interpúbica es limitada en el contexto de distinguir edad y estadio reproductivo por traslape extensivo (31.6,100%), pero muestra potencial en otras aplicaciones. Basados en estos resultados recomendamos el uso de distancia interpúbica como un método para distinguir sexo de pipridos. Recomendamos más investigación para crear otras ecuaciones de clasificación usando medidas mórfometricas diferentes y probar la eficacia de la distancia interpúbica para distinguir el sexo de otras especies de aves. [source] DIFFERENTIATION OF CURED COOKED HAMS BY PHYSICO-CHEMICAL PROPERTIES AND CHEMOMETRICSJOURNAL OF FOOD QUALITY, Issue 1 2009VITTORIO M. MORETTI ABSTRACT Comparison of physico-chemical and compositional traits was carried out on cooked hams. Deboned fresh pig thighs of three different origins were divided into three batches: 200 pig thighs from the Italian market, H1; 200 from The Netherlands, H2; and 200 from Denmark, H3. Boneless pig thighs were processed under commercial guidelines for production of cooked hams, using brine at 25% level of injection. After processing, 12 cooked hams from each batch were sampled randomly and analyzed for proximate and fatty acid composition. Color measurement was performed on the muscles: biceps femoris, semimembranosus, and semitendinosus. H1 hams showed a higher weight loss and a lower technological yield compared to H2 and H3 hams. Analysis of variance on compositional data showed that H1 hams had a lower moisture/protein ratio, a higher fat content, a lower percentage of, -linolenic, eicosapentaenoic and docosahexaenoic acid, and a higher percentage of myristic and palmitic acids when compared to H2 and H3 hams (P < 0.05). Analysis of color of the three muscles demonstrated that hams from the H1 group had the highest a* values. The application of linear discriminant analysis demonstrated that the use of only four variables allowed to correctly discriminate among groups of cooked hams. PRACTICAL APPLICATIONS The following are the practical applications of this research. The comparison of physico-chemical and compositional traits were carried out on cooked hams. Pig thighs of different origin were processed under commercial guidelines. The physicochemical parameters of cooked hams were defined and showed some differences characterizing the products. [source] Rapid Determination of Invert Cane Sugar Adulteration in Honey Using FTIR Spectroscopy and Multivariate AnalysisJOURNAL OF FOOD SCIENCE, Issue 6 2003J. Irudayaraj ABSTRACT: Fourier transform infrared spectroscopy with an attenuated total reflection sampling accessory was combined with multivariate analysis to determine the level (1% to 25%, wt/wt) of invert cane sugar adulteration in honey. On the basis of the spectral data compression by principal component analysis and partial least squares, linear discriminant analysis (LDA), and canonical variate analysis (CVA), models were developed and validated. Two types of artificial neural networks were applied: a quick back propagation network (BPN) and a radial basis function network (RBFN). The prediction success rates were better with LDA (93.75% for validation set) and BPN (93.75%) than with CVA (87.50%) and RBFN (81.25%). [source] Statistical Discrimination of Liquid Gasoline Samples from CaseworkJOURNAL OF FORENSIC SCIENCES, Issue 5 2008Nicholas D. K. Petraco Ph.D. Abstract:, The intention of this study was to differentiate liquid gasoline samples from casework by utilizing multivariate pattern recognition procedures on data from gas chromatography-mass spectrometry. A supervised learning approach was undertaken to achieve this goal employing the methods of principal component analysis (PCA), canonical variate analysis (CVA), orthogonal canonical variate analysis (OCVA), and linear discriminant analysis. The study revealed that the variability in the sample population was sufficient enough to distinguish all the samples from one another knowing their groups a priori. CVA was able to differentiate all samples in the population using only three dimensions, while OCVA required four dimensions. PCA required 10 dimensions of data in order to predict the correct groupings. These results were all cross-validated using the "jackknife" method to confirm the classification functions and compute estimates of error rates. The results of this initial study have helped to develop procedures for the application of multivariate analysis to fire debris casework. [source] Multivariate analysis approach to the plasma protein profile of patients with advanced colorectal cancer,JOURNAL OF MASS SPECTROMETRY (INCORP BIOLOGICAL MASS SPECTROMETRY), Issue 12 2006Eugenio Ragazzi Abstract The aim of the present study was to identify the pattern of plasma protein species of interest as markers of colorectal cancer (CRC). Using matrix-assisted laser desorption/ionization-mass spectrometry (MALDI-MS), the plasma protein profile was determined in nine stage IV CRC patients (study group) and nine clean-colon healthy subjects (control group). Multivariate analysis methods were employed to identify distinctive disease patterns at protein spectrum. In the study and control groups, cluster analysis (CA) on the complete MALDI-MS spectra plasma protein profile showed a distinction between CRC patients and healthy subjects, thus allowing the identification of the most discriminating ionic species. Principal component analysis (PCA) and linear discriminant analysis (LDA) yielded similar grouping results. LDA with leave-one-out cross validation achieved a correct classification rate of 89% in both the patients and the healthy subjects. Copyright © 2006 John Wiley & Sons, Ltd. [source] A new FT-IR method combined with multivariate analysis for the classification of vinegars from different raw materials and production processesJOURNAL OF THE SCIENCE OF FOOD AND AGRICULTURE, Issue 4 2010Enrique Durán Guerrero Abstract BACKGROUND: Due to the diversity of vinegars on the market and the increase in demand, it is considered necessary to investigate and establish criteria for classifying them in order to obtain more information concerning their real origin. New spectroscopic techniques such us mid-infrared spectroscopy with Fourier transform (FT-IR) are capable of providing information in relation to these aspects. FT-IR combined with multivariate analysis has been used to classify vinegars according to the raw materials and production processes (with or without ageing in wood). Principal component analysis (PCA), partial least-squares discriminant analysis regression (PLS-DA) and stepwise linear discriminant analysis (SLDA) were used. RESULTS: The results obtained have been compared to those achieved using different analytical parameters (polyphenolic content, organic acids and volatile compounds). SLDA and PLS-DA results show the ability of mid-FT-IR spectra to discriminate among vinegars from different raw materials and with or without ageing in wood, with correct classification percentages similar to those obtained using different analytical parameters. CONCLUSION: The discriminative ability combined with other advantages (e.g. rapid and non-destructive analysis, low cost) makes this new FT-IR method a promising tool for the classification and/or differentiation of vinegars. Copyright © 2010 Society of Chemical Industry [source] Differentiation of eight tea (Camellia sinensis) cultivars in China by elemental fingerprint of their leavesJOURNAL OF THE SCIENCE OF FOOD AND AGRICULTURE, Issue 14 2009Yingxu Chen Abstract BACKGROUND: Tea is an infusion made from dried leaves of tea (Camellia sinensis) and can be a good dietary source of essential trace metals for humans. Therefore, it is necessary to consider variations in element content of tea leaves among tea cultivars. Thus, elemental fingerprint techniques, based on elemental contents (Al, B, Ca, Cd, Co, Cr, Cu, Fe, K, Mg, Mn, Na, P, Pb, and Zn) determined by inductively coupled plasma atomic emission spectrometry (ICP-AES) and multivariate statistical analysis, have been used to differentiate eight tea cultivars. RESULTS: The ranges of element concentrations in leaves of the eight cultivars were in good agreement with those obtained in previous studies and the level of most elements in tea leaves was significantly different among cultivars. The classifications of eight tea cultivars were 100% accurate in total by principal component analysis (PCA), hierarchical cluster analysis (HCA), linear discriminant analysis (LDA), and back-propagation neural network (BPNN) analysis. CONCLUSION: Each cultivar presented a distinctive element fingerprint and the elements in tea leaves can be significant predictors in differentiating tea cultivars. Copyright © 2009 Society of Chemical Industry [source] Using hyperspectral satellite imagery for regional inventories: a test with tropical emergent trees in the Amazon BasinJOURNAL OF VEGETATION SCIENCE, Issue 2 2010M. Pape Abstract Questions: Understanding distributions of tree species at landscape scales in tropical forests is a difficult task that could benefit from the recent development of satellite imaging spectroscopy. We tested an application of the EO-1 Hyperion satellite sensor to spectrally detect the location of five important tree taxa in the lowland humid tropical forests of southeastern Peru. Location: Peru, Departamento de Madre de Díos. Methods: We used linear discriminant analysis with a stepwise selection procedure to analyze two Hyperion datasets (July and December 2006) to choose the most informative narrow bands for classifying trees. Results: Optimal channels selected were different between the two seasons. Classification was 100% successful for the five taxa when using 25 narrow bands and pixels that represented >40% of tree crowns. We applied the discriminant functions developed separately for the two seasons to the entire study area, and found significantly nonrandom overlap in the anticipated distributions of the five taxa between seasons. Conclusions: Despite known issues, such as signal-to-noise ratio and spatial resolution, Hyperion imaging spectroscopy has potential for developing regional mapping of large-crowned tropical trees. [source] Temporally and spectrally resolved fluorescence spectroscopy for the detection of high grade dysplasia in Barrett's esophagusLASERS IN SURGERY AND MEDICINE, Issue 1 2003T. Joshua Pfefer PhD Abstract Background and Objectives Temporal and spectral fluorescence spectroscopy can identify adenomatous colonic polyps accurately. In this study, these techniques were examined as a potential means of improving the surveillance of high grade dysplasia (HGD) in Barrett's esophagus (BE). Study Design/Materials and Methods Using excitation wavelengths of 337 and 400 nm, 148 fluorescence spectra, and 108 transient decay profiles (at 550,±,20 nm) were obtained endoscopically in 37 patients. Corresponding biopsies were collected and classified as carcinoma, HGD, or low risk tissue (LRT) [non-dysplastic BE, indefinite for dysplasia (IFD), and low grade dysplasia (LGD)]. Diagnostic algorithms were developed retrospectively using linear discriminant analysis (LDA) to separate LRT from HGD. Results LDA produced diagnostic algorithms based solely on spectral data. Moderate levels of sensitivity (Se) and specificity (Sp) were obtained for both 337 nm (Se,=,74%, Sp,=,67%) and 400 nm (Se,=,74%, Sp,=,85%) excitation. Conclusions In the diagnosis of HGD in BE, steady-state fluorescence was more effective than time-resolved data, and excitation at 400 nm excitation was more effective than 337 nm. While fluorescence-targeted biopsy is approaching clinical usefulness, increased sensitivity to dysplastic changes,possibly through modification of system parameters,is needed to improve accuracy levels. Lasers Surg. Med. 32:10,16,2003. © 2003 Wiley-Liss, Inc. [source] | ||||||||||||||||||||||||||||||||||